WorldWideScience

Sample records for spectral vegetation indices

  1. Comparison of inversion accuracy of soil copper content from vegetation indices under different spectral resolution

    Science.gov (United States)

    Sun, Zhongqing; Shang, Kun; Jia, Lingjun

    2018-03-01

    Remote sensing inversion of heavy metal in vegetation leaves is generally based on the physiological characteristics of vegetation spectrum under heavy metal stress, and empirical models with vegetation indices are established to inverse the heavy metal content of vegetation leaves. However, the research of inversion of heavy metal content in vegetation-covered soil is still rare. In this study, Pulang is chosen as study area. The regression model of a typical heavy metal element, copper (Cu), is established with vegetation indices. We mainly investigate the inversion accuracies of Cu element in vegetation-covered soil by different vegetation indices according to specific spectral resolutions of ASD (Analytical Spectral Device) and Hyperion data. The inversion results of soil copper content in the vegetation-covered area shows a good accuracy, and the vegetation indices under ASD spectral resolution correspond to better results.

  2. Evaluating the capabilities of vegetation spectral indices on chlorophyll content estimation at Sentinel-2 spectral resolutions

    Science.gov (United States)

    Sun, Qi; Jiao, Quanjun; Dai, Huayang

    2018-03-01

    Chlorophyll is an important pigment in green plants for photosynthesis and obtaining the energy for growth and development. The rapid, nondestructive and accurate estimation of chlorophyll content is significant for understanding the crops growth, monitoring the disease and insect, and assessing the yield of crops. Sentinel-2 equipped with the Multi-Spectral Instrument (MSI), which will provide images with high spatial, spectral and temporal resolution. It covers the VNIR/SWIR spectral region in 13 bands and incorporates two new spectral bands in the red-edge region and a spatial resolution of 20nm, which can be used to derive vegetation indices using red-edge bands. In this paper, we will focus on assessing the potential of vegetation spectral indices for retrieving chlorophyll content from Sentinel-2 at different angles. Subsequently, we used in-situ spectral data and Sentinel-2 data to test the relationship between VIs and chlorophyll content. The REP, MTCI, CIred-edge, CIgreen, Macc01, TCARI/OSAVI [705,750], NDRE1 and NDRE2 were calculated. NDRE2 index displays a strongly similar result for hyperspectral and simulated Sentinel-2 spectral bands (R2 =0.53, R2 =0.51, for hyperspectral and Sentinel-2, respectively). At different observation angles, NDRE2 has the smallest difference in performance (R2 = 0.51, R2 =0.64, at 0° and 15° , respectively).

  3. Mapping swamp timothy (Cripsis schenoides) seed productivity using spectral values and vegetation indices in managed wetlands

    Energy Technology Data Exchange (ETDEWEB)

    Rahilly, P.J.A.; Li, D.; Guo, Q.; Zhu, J.; Ortega, R.; Quinn, N.W.T.; Harmon, T.C.

    2010-01-15

    This work examines the potential to predict the seed productivity of a key wetland plant species using spectral reflectance values and spectral vegetation indices. Specifically, the seed productivity of swamp timothy (Cripsis schenoides) was investigated in two wetland ponds, managed for waterfowl habitat, in California's San Joaquin Valley. Spectral reflectance values were obtained and associated spectral vegetation indices (SVI) calculated from two sets of high resolution aerial images (May 11, 2006 and June 9, 2006) and were compared to the collected vegetation data. Vegetation data were collected and analyzed from 156 plots for total aboveground biomass, total aboveground swamp timothy biomass, and total swamp timothy seed biomass. The SVI investigated included the Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Global Environment Monitoring Index (GEMI). We evaluated the correlation of the various SVI with in situ vegetation measurements for linear, quadratic, exponential and power functions. In all cases, the June image provided better predictive capacity relative to May, a result that underscores the importance of timing imagery to coincide with more favorable vegetation maturity. The north pond with the June image using SR and the exponential function (R{sup 2}=0.603) proved to be the best predictor of swamp timothy seed productivity. The June image for the south pond was less predictive, with TSAVI and the exponential function providing the best correlation (R{sup 2}=0.448). This result was attributed to insufficient vegetal cover in the south pond (or a higher percentage of bare soil) due to poor drainage conditions which resulted in a delay in swamp timothy germination. The results of this work suggest that spectral reflectance can be used to estimate seed productivity in managed seasonal

  4. Spectral data based vegetation indices to characterise crop growth parameters and radiation interception in brassica

    International Nuclear Information System (INIS)

    Kar, G.; Chakravarty, N.V.K.

    2001-01-01

    Four spectral data based vegetation indices viz., infra-red/red (IR/R) ratio, normalized difference (N.D.), greenness index (GNI) and brightness index (BNI) were derived to characterise leaf area index, above ground biomass production and intercepted photosynthetically active radiation in Brassica oilseed crop. It was found from correlation study among different spectral indices, plant growth parameters and radiation interception that there was strong relationship between infrared/red and normalized difference with green area index for all the three Brassica cultivars whereas these spectral were not significantly correlated with above ground biomass. On the other hand, the brightness and greenness indices were closely correlated with above groundry biomass as compared to infrared/red ratio and normalized difference. All the four spectral indices were correlated with intercepted photosynthetically active radiation (IP AR). The best fit equations relating them were derived, which can be incorporated in the algorithms of crop growth simulation model to estimate plant growth parameters and radiation interception using spectral indices

  5. Mapping the recovery of the burnt vegetation by classifying pre- and post-fire spectral indices

    Directory of Open Access Journals (Sweden)

    M. A Peña

    2017-12-01

    Full Text Available This study analyzed the state of recovery of the burnt vegetation in the National Park of Torres del Paine between December, 2011 and March, 2012. The calculation and comparison of the NVDI (normalized difference vegetation index of the burnt area throughout a time series of 24 Landsat images acquired before, during and after the fire (2009- 2015, showed the temporal variation in the biomass levels of the burnt vegetation. The subsequent classification and comparison of the spectral indices: NDVI, NBR (normalized burnt ratio and NDWI (normalized difference water index on a full-data available and phenologically matched pre- and post-fire image pair (acquired in October 2009 and 2014, enabled to analyze and mapping the state of recovery of the burnt vegetation. The results show that the area of the lowest classes of all the spectral indices of the pre-fire date became the most dominant on the post-fire date. The pre- and post- fire NDVI class crossing by a confusion matrix showed that the highest and most prevailing pre-fire NDVI classes, mostly corresponding to hydromorphic forests and Andean scrubs, turned into the lowest class in 2014. The remaining area, comprising Patagonian steppe, reestablished its biomass levels in 2014, mostly exhibiting the same pre-fire NDVI classes. These results may provide guidelines to monitor and manage the regeneration of the vegetation impacted by this fire.

  6. Response of Spectral Reflectances and Vegetation Indices on Varying Juniper Cone Densities

    Directory of Open Access Journals (Sweden)

    Guillermo E. Ponce-Campos

    2013-10-01

    Full Text Available Juniper trees are widely distributed throughout the world and are common sources of allergies when microscopic pollen grains are transported by wind and inhaled. In this study, we investigated the spectral influences of pollen-discharging male juniper cones within a juniper canopy. This was done through a controlled outdoor experiment involving ASD FieldSpec Pro Spectroradiometer measurements over juniper canopies of varying cone densities. Broadband and narrowband spectral reflectance and vegetation index (VI patterns were evaluated as to their sensitivity and their ability to discriminate the presence of cones. The overall aim of this research was to assess remotely sensed phenological capabilities to detect pollen-bearing juniper trees for public health applications. A general decrease in reflectance values with increasing juniper cone density was found, particularly in the Green (545–565 nm and NIR (750–1,350 nm regions. In contrast, reflectances in the shortwave-infrared (SWIR, 2,000 nm to 2,350 nm region decreased from no cone presence to intermediate amounts (90 g/m2 and then increased from intermediate levels to the highest cone densities (200 g/m2. Reflectance patterns in the Red (620–700 nm were more complex due to shifting contrast patterns in absorptance between cones and juniper foliage, where juniper foliage is more absorbing than cones only within the intense narrowband region of maximum chlorophyll absorption near 680 nm. Overall, narrowband reflectances were more sensitive to cone density changes than the equivalent MODIS broadbands. In all VIs analyzed, there were significant relationships with cone density levels, particularly with the narrowband versions and the two-band vegetation index (TBVI based on Green and Red bands, a promising outcome for the use of phenocams in juniper phenology trait studies. These results indicate that spectral indices are sensitive to certain juniper phenologic traits that can potentially be

  7. Correlation analysis between forest carbon stock and spectral vegetation indices in Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam

    Science.gov (United States)

    Dung Nguyen, The; Kappas, Martin

    2017-04-01

    In the last several years, the interest in forest biomass and carbon stock estimation has increased due to its importance for forest management, modelling carbon cycle, and other ecosystem services. However, no estimates of biomass and carbon stocks of deferent forest cover types exist throughout in the Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam. This study investigates the relationship between above ground carbon stock and different vegetation indices and to identify the most likely vegetation index that best correlate with forest carbon stock. The terrestrial inventory data come from 380 sample plots that were randomly sampled. Individual tree parameters such as DBH and tree height were collected to calculate the above ground volume, biomass and carbon for different forest types. The SPOT6 2013 satellite data was used in the study to obtain five vegetation indices NDVI, RDVI, MSR, RVI, and EVI. The relationships between the forest carbon stock and vegetation indices were investigated using a multiple linear regression analysis. R-square, RMSE values and cross-validation were used to measure the strength and validate the performance of the models. The methodology presented here demonstrates the possibility of estimating forest volume, biomass and carbon stock. It can also be further improved by addressing more spectral bands data and/or elevation.

  8. [Cross comparison of ASTER and Landsat ETM+ multispectral measurements for NDVI and SAVI vegetation indices].

    Science.gov (United States)

    Xu, Han-qiu; Zhang, Tie-jun

    2011-07-01

    The present paper investigates the quantitative relationship between the NDVI and SAVI vegetation indices of Landsat and ASTER sensors based on three tandem image pairs. The study examines how well ASTER sensor vegetation observations replicate ETM+ vegetation observations, and more importantly, the difference in the vegetation observations between the two sensors. The DN values of the three image pairs were first converted to at-sensor reflectance to reduce radiometric differences between two sensors, images. The NDVI and SAVI vegetation indices of the two sensors were then calculated using the converted reflectance. The quantitative relationship was revealed through regression analysis on the scatter plots of the vegetation index values of the two sensors. The models for the conversion between the two sensors, vegetation indices were also obtained from the regression. The results show that the difference does exist between the two sensors, vegetation indices though they have a very strong positive linear relationship. The study found that the red and near infrared measurements differ between the two sensors, with ASTER generally producing higher reflectance in the red band and lower reflectance in the near infrared band than the ETM+ sensor. This results in the ASTER sensor producing lower spectral vegetation index measurements, for the same target, than ETM+. The relative spectral response function differences in the red and near infrared bands between the two sensors are believed to be the main factor contributing to their differences in vegetation index measurements, because the red and near infrared relative spectral response features of the ASTER sensor overlap the vegetation "red edge" spectral region. The obtained conversion models have high accuracy with a RMSE less than 0.04 for both sensors' inter-conversion between corresponding vegetation indices.

  9. [Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices.

    Science.gov (United States)

    Zuo, Lu; Wang, Huan Jiong; Liu, Rong Gao; Liu, Yang; Shang, Rong

    2018-02-01

    Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.

  10. Vulnerable land ecosystems classification using spatial context and spectral indices

    Science.gov (United States)

    Ibarrola-Ulzurrun, Edurne; Gonzalo-Martín, Consuelo; Marcello, Javier

    2017-10-01

    Natural habitats are exposed to growing pressure due to intensification of land use and tourism development. Thus, obtaining information on the vegetation is necessary for conservation and management projects. In this context, remote sensing is an important tool for monitoring and managing habitats, being classification a crucial stage. The majority of image classifications techniques are based upon the pixel-based approach. An alternative is the object-based (OBIA) approach, in which a previous segmentation step merges image pixels to create objects that are then classified. Besides, improved results may be gained by incorporating additional spatial information and specific spectral indices into the classification process. The main goal of this work was to implement and assess object-based classification techniques on very-high resolution imagery incorporating spectral indices and contextual spatial information in the classification models. The study area was Teide National Park in Canary Islands (Spain) using Worldview-2 orthoready imagery. In the classification model, two common indices were selected Normalized Difference Vegetation Index (NDVI) and Optimized Soil Adjusted Vegetation Index (OSAVI), as well as two specific Worldview-2 sensor indices, Worldview Vegetation Index and Worldview Soil Index. To include the contextual information, Grey Level Co-occurrence Matrices (GLCM) were used. The classification was performed training a Support Vector Machine with sufficient and representative number of vegetation samples (Spartocytisus supranubius, Pterocephalus lasiospermus, Descurainia bourgaeana and Pinus canariensis) as well as urban, road and bare soil classes. Confusion Matrices were computed to evaluate the results from each classification model obtaining the highest overall accuracy (90.07%) combining both Worldview indices with the GLCM-dissimilarity.

  11. Spectral Indices to Monitor Nitrogen-Driven Carbon Uptake in Field Corn

    Science.gov (United States)

    Corp, Lawrence A.; Middleton, Elizabeth M.; Campbell, Peya E.; Huemmrich, K. Fred; Daughtry, Craig S. T.; Russ, Andrew; Cheng, Yen-Ben

    2010-01-01

    Climate change is heavily impacted by changing vegetation cover and productivity with large scale monitoring of vegetation only possible with remote sensing techniques. The goal of this effort was to evaluate existing reflectance (R) spectroscopic methods for determining vegetation parameters related to photosynthetic function and carbon (C) dynamics in plants. Since nitrogen (N) is a key constituent of photosynthetic pigments and C fixing enzymes, biological C sequestration is regulated in part by N availability. Spectral R information was obtained from field corn grown at four N application rates (0, 70, 140, 280 kg N/ha). A hierarchy of spectral observations were obtained: leaf and canopy with a spectral radiometer; aircraft with the AISA sensor; and satellite with EO-1 Hyperion. A number of spectral R indices were calculated from these hyperspectral observations and compared to geo-located biophysical measures of plant growth and physiological condition. Top performing indices included the R derivative index D730/D705 and the normalized difference of R750 vs. R705 (ND705), both of which differentiated three of the four N fertilization rates at multiple observation levels and yielded high correlations to these carbon parameters: light use efficiency (LUE); C:N ratio; and crop grain yield. These results advocate the use of hyperspectral sensors for remotely monitoring carbon cycle dynamics in managed terrestrial ecosystems.

  12. Testing the Potential of Vegetation Indices for Land Use/cover Classification Using High Resolution Data

    Science.gov (United States)

    Karakacan Kuzucu, A.; Bektas Balcik, F.

    2017-11-01

    Accurate and reliable land use/land cover (LULC) information obtained by remote sensing technology is necessary in many applications such as environmental monitoring, agricultural management, urban planning, hydrological applications, soil management, vegetation condition study and suitability analysis. But this information still remains a challenge especially in heterogeneous landscapes covering urban and rural areas due to spectrally similar LULC features. In parallel with technological developments, supplementary data such as satellite-derived spectral indices have begun to be used as additional bands in classification to produce data with high accuracy. The aim of this research is to test the potential of spectral vegetation indices combination with supervised classification methods and to extract reliable LULC information from SPOT 7 multispectral imagery. The Normalized Difference Vegetation Index (NDVI), the Ratio Vegetation Index (RATIO), the Soil Adjusted Vegetation Index (SAVI) were the three vegetation indices used in this study. The classical maximum likelihood classifier (MLC) and support vector machine (SVM) algorithm were applied to classify SPOT 7 image. Catalca is selected region located in the north west of the Istanbul in Turkey, which has complex landscape covering artificial surface, forest and natural area, agricultural field, quarry/mining area, pasture/scrubland and water body. Accuracy assessment of all classified images was performed through overall accuracy and kappa coefficient. The results indicated that the incorporation of these three different vegetation indices decrease the classification accuracy for the MLC and SVM classification. In addition, the maximum likelihood classification slightly outperformed the support vector machine classification approach in both overall accuracy and kappa statistics.

  13. Detecting post-fire burn severity and vegetation recovery using multitemporal remote sensing spectral indices and field-collected composite burn index data in a ponderosa pine forest

    Science.gov (United States)

    Chen, Xuexia; Vogelmann, James E.; Rollins, Matt; Ohlen, Donald; Key, Carl H.; Yang, Limin; Huang, Chengquan; Shi, Hua

    2011-01-01

    It is challenging to detect burn severity and vegetation recovery because of the relatively long time period required to capture the ecosystem characteristics. Multitemporal remote sensing data can providemultitemporal observations before, during and after a wildfire, and can improve the change detection accuracy. The goal of this study is to examine the correlations between multitemporal spectral indices and field-observed burn severity, and to provide a practical method to estimate burn severity and vegetation recovery. The study site is the Jasper Fire area in the Black Hills National Forest, South Dakota, that burned during August and September 2000. Six multitemporal Landsat images acquired from 2000 (pre-fire), 2001 (post-fire), 2002, 2003, 2005 and 2007 were used to assess burn severity. The normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized burn ratio (NBR), integrated forest index (IFI) and the differences of these indices between the pre-fire and post-fire years were computed and analysed with 66 field-based composite burn index (CBI) plots collected in 2002. Results showed that differences of NDVI and differences of EVI between the pre-fire year and the first two years post-fire were highly correlated with the CBI scores. The correlations were low beyond the second year post-fire. Differences of NBR had good correlation with CBI scores in all study years. Differences of IFI had low correlation with CBI in the first year post-fire and had good correlation in later years. A CBI map of the burnt area was produced using regression tree models and the multitemporal images. The dynamics of four spectral indices from 2000 to 2007 indicated that both NBR and IFI are valuable for monitoring long-term vegetation recovery. The high burn severity areas had a much slower recovery than the moderate and low burn areas.

  14. Modified vegetation indices for Ganoderma disease detection in oil palm from field spectroradiometer data

    Science.gov (United States)

    Shafri, Helmi Z. M.; Anuar, M. Izzuddin; Saripan, M. Iqbal

    2009-10-01

    High resolution field spectroradiometers are important for spectral analysis and mobile inspection of vegetation disease. The biggest challenges in using this technology for automated vegetation disease detection are in spectral signatures pre-processing, band selection and generating reflectance indices to improve the ability of hyperspectral data for early detection of disease. In this paper, new indices for oil palm Ganoderma disease detection were generated using band ratio and different band combination techniques. Unsupervised clustering method was used to cluster the values of each class resultant from each index. The wellness of band combinations was assessed by using Optimum Index Factor (OIF) while cluster validation was executed using Average Silhouette Width (ASW). 11 modified reflectance indices were generated in this study and the indices were ranked according to the values of their ASW. These modified indices were also compared to several existing and new indices. The results showed that the combination of spectral values at 610.5nm and 738nm was the best for clustering the three classes of infection levels in the determination of the best spectral index for early detection of Ganoderma disease.

  15. Monitoring vegetation recovery in fire-affected areas using temporal profiles of spectral signal from time series MODIS and LANDSAT satellite images

    Science.gov (United States)

    Georgopoulou, Danai; Koutsias, Nikos

    2015-04-01

    Vegetation phenology is an important element of vegetation characteristics that can be useful in vegetation monitoring especially when satellite remote sensing observations are used. In that sense temporal profiles extracted from spectral signal of time series MODIS and LANDSAT satellite images can be used to characterize vegetation phenology and thus to be helpful for monitoring vegetation recovery in fire-affected areas. The aim of this study is to explore the vegetation recovery pattern of the catastrophic wildfires that occurred in Peloponnisos, southern Greece, in 2007. These fires caused the loss of 67 lives and were recognized as the most extreme natural disaster in the country's recent history. Satellite remote sensing data from MODIS and LANDSAT satellites in the period from 2000 to 2014 were acquired and processed to extract the temporal profiles of the spectral signal for selected areas within the fire-affected areas. This dataset and time period analyzed together with the time that these fires occurred gave the opportunity to create temporal profiles seven years before and seven years after the fire. The different scale of the data used gave us the chance to understand how vegetation phenology and therefore the recovery patterns are influenced by the spatial resolution of the satellite data used. Different metrics linked to key phenological events have been created and used to assess vegetation recovery in the fire-affected areas. Our analysis was focused in the main land cover types that were mostly affected by the 2007 wildland fires. Based on CORINE land-cover maps these were agricultural lands highly interspersed with large areas of natural vegetation followed by sclerophyllous vegetation, transitional woodland shrubs, complex cultivation patterns and olive groves. Apart of the use of the original spectral data we estimated and used vegetation indices commonly found in vegetation studies as well as in burned area mapping studies. In this study we

  16. Estimation of the soil heat flux/net radiation ratio based on spectral vegetation indexes in high-latitude Arctic areas

    International Nuclear Information System (INIS)

    Jacobsen, A.; Hansen, B.U.

    1999-01-01

    The vegetation communities in the Arctic environment are very sensitive to even minor climatic variations and therefore the estimation of surface energy fluxes from high-latitude vegetated areas is an important subject to be pursued. This study was carried out in July-August and used micro meteorological data, spectral reflectance signatures, and vegetation biomass to establish the relation between the soil heat flux/net radiation (G / Rn) ratio and spectral vegetation indices (SVIs). Continuous measurements of soil temperature and soil heat flux were used to calculate the surface ground heat flux by use of conventional methods, and the relation to surface temperature was investigated. Twenty-seven locations were established, and six samples per location, including the measurement of the surface temperature and net radiation to establish the G/Rn ratio and simultaneous spectral reflectance signatures and wet biomass estimates, were registered. To obtain regional reliability, the locations were chosen in order to represent the different Arctic vegetation communities in the study area; ranging from dry tundra vegetation communities (fell fields and dry dwarf scrubs) to moist/wet tundra vegetation communities (snowbeds, grasslands and fens). Spectral vegetation indices, including the simple ratio vegetation index (RVI) and the normalized difference vegetation index (NDVI), were calculated. A comparison of SVIs to biomass proved that RVI gave the best linear expression, and NDVI the best exponential expression. A comparison of SVIs and the surface energy flux ratio G / Rn proved that NDVI gave the best linear expression. SPOT HRV images from July 1989 and 1992 were used to map NDVI and G / Rn at a regional scale. (author)

  17. [Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

    Science.gov (United States)

    Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

    2012-12-01

    This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

  18. Assessing and monitoring of urban vegetation using multiple endmember spectral mixture analysis

    Science.gov (United States)

    Zoran, M. A.; Savastru, R. S.; Savastru, D. M.

    2013-08-01

    During last years urban vegetation with significant health, biological and economical values had experienced dramatic changes due to urbanization and human activities in the metropolitan area of Bucharest in Romania. We investigated the utility of remote sensing approaches of multiple endmember spectral mixture analysis (MESMA) applied to IKONOS and Landsat TM/ETM satellite data for estimating fractional cover of urban/periurban forest, parks, agricultural vegetation areas. Because of the spectral heterogeneity of same physical features of urban vegetation increases with the increase of image resolution, the traditional spectral information-based statistical method may not be useful to classify land cover dynamics from high resolution imageries like IKONOS. So we used hierarchy tree classification method in classification and MESMA for vegetation land cover dynamics assessment based on available IKONOS high-resolution imagery of Bucharest town. This study employs thirty two endmembers and six hundred and sixty spectral models to identify all Earth's features (vegetation, water, soil, impervious) and shade in the Bucharest area. The mean RMS error for the selected vegetation land cover classes range from 0.0027 to 0.018. The Pearson correlation between the fraction outputs from MESMA and reference data from all IKONOS images 1m panchromatic resolution data for urban/periurban vegetation were ranging in the domain 0.7048 - 0.8287. The framework in this study can be applied to other urban vegetation areas in Romania.

  19. Comparing Broad-Band and Red Edge-Based Spectral Vegetation Indices to Estimate Nitrogen Concentration of Crops Using Casi Data

    Science.gov (United States)

    Wang, Yanjie; Liao, Qinhong; Yang, Guijun; Feng, Haikuan; Yang, Xiaodong; Yue, Jibo

    2016-06-01

    In recent decades, many spectral vegetation indices (SVIs) have been proposed to estimate the leaf nitrogen concentration (LNC) of crops. However, most of these indices were based on the field hyperspectral reflectance. To test whether they can be used in aerial remote platform effectively, in this work a comparison of the sensitivity between several broad-band and red edge-based SVIs to LNC is investigated over different crop types. By using data from experimental LNC values over 4 different crop types and image data acquired using the Compact Airborne Spectrographic Imager (CASI) sensor, the extensive dataset allowed us to evaluate broad-band and red edge-based SVIs. The result indicated that NDVI performed the best among the selected SVIs while red edge-based SVIs didn't show the potential for estimating the LNC based on the CASI data due to the spectral resolution. In order to search for the optimal SVIs, the band combination algorithm has been used in this work. The best linear correlation against the experimental LNC dataset was obtained by combining the 626.20nm and 569.00nm wavebands. These wavelengths correspond to the maximal chlorophyll absorption and reflection position region, respectively, and are known to be sensitive to the physiological status of the plant. Then this linear relationship was applied to the CASI image for generating an LNC map, which can guide farmers in the accurate application of their N fertilization strategies.

  20. Improvement in remote sensing of low vegetation cover in arid regions by correcting vegetation indices for soil ''noise''

    International Nuclear Information System (INIS)

    Escadafal, R.; Huete, A.

    1991-01-01

    The variations of near-infrared red reflectance ratios of ten aridic soil samples were correlated with a ''redness index'' computed from red and green spectral bands. These variations have been shown to limit the performances of vegetation indices (NDVI and SAVI) in discriminating low vegetation covers. The redness index is used to adjust for this ''soil noise''. Dala simulated for vegetation densities of 5 to 15% cover showed that the sensitivity of the corrected vegetation indices was significantly improved. Specifically, the ''noise-corrected'' SAVI was able to assess vegetation amounts with an error four times smaller than the uncorrected NDVI. These promising results should lead to a significant improvement in assessing biomass in arid lands from remotely sensed data. (author) [fr

  1. Combining Spectral Data and a DSM from UAS-Images for Improved Classification of Non-Submerged Aquatic Vegetation

    Directory of Open Access Journals (Sweden)

    Eva Husson

    2017-03-01

    Full Text Available Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a Growth forms including the classes of water, nymphaeid, and helophyte; and (b dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%–21% for growth-forms and 3%–30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities

  2. Effect of spectrally varying albedo of vegetation surfaces on shortwave radiation fluxes and aerosol direct radiative forcing

    Directory of Open Access Journals (Sweden)

    L. Zhu

    2012-12-01

    Full Text Available This study develops an algorithm for representing detailed spectral features of vegetation albedo based on Moderate Resolution Imaging Spectrometer (MODIS observations at 7 discrete channels, referred to as the MODIS Enhanced Vegetation Albedo (MEVA algorithm. The MEVA algorithm empirically fills spectral gaps around the vegetation red edge near 0.7 μm and vegetation water absorption features at 1.48 and 1.92 μm which cannot be adequately captured by the MODIS 7 channels. We then assess the effects of applying MEVA in comparison to four other traditional approaches to calculate solar fluxes and aerosol direct radiative forcing (DRF at the top of atmosphere (TOA based on the MODIS discrete reflectance bands. By comparing the DRF results obtained through the MEVA method with the results obtained through the other four traditional approaches, we show that filling the spectral gap of the MODIS measurements around 0.7 μm based on the general spectral behavior of healthy green vegetation leads to significant improvement in the instantaneous aerosol DRF at TOA (up to 3.02 W m−2 difference or 48% fraction of the aerosol DRF, −6.28 W m−2, calculated for high spectral resolution surface reflectance from 0.3 to 2.5 μm for deciduous vegetation surface. The corrections of the spectral gaps in the vegetation spectrum in the near infrared, again missed by the MODIS reflectances, also contributes to improving TOA DRF calculations but to a much lower extent (less than 0.27 W m−2, or about 4% of the instantaneous DRF.

    Compared to traditional approaches, MEVA also improves the accuracy of the outgoing solar flux between 0.3 to 2.5 μm at TOA by over 60 W m−2 (for aspen 3 surface and aerosol DRF by over 10 W m−2 (for dry grass. Specifically, for Amazon vegetation types, MEVA can improve the accuracy of daily averaged aerosol radiative forcing in the spectral range of 0.3 to 2.5 μm at

  3. Satellite monitoring of different vegetation types by differential optical absorption spectroscopy (DOAS in the red spectral range

    Directory of Open Access Journals (Sweden)

    T. Wagner

    2007-01-01

    Full Text Available A new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms relying on the strong change of the reflectivity in the red and near infrared spectral region, our method analyses weak narrow-band (few nm reflectance structures (i.e. "fingerprint" structures of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS, which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric absorptions are automatically corrected (in contrast to other algorithms. The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the results illustrate the seasonal cycles of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future.

  4. Leaf area index retrieval using Hyperion EO-1 data-based vegetation indices in Himalayan forest system

    Science.gov (United States)

    Singh, Dharmendra; Singh, Sarnam

    2016-04-01

    Present Study is being taken to retrieve Leaf Area Indexn(LAI) in Himalayan forest system using vegetation indices developed from Hyperion EO-1 hyperspectral data. Hemispherical photograph were captured in the month of March and April, 2012 at 40 locations, covering moist tropical Sal forest, subtropical Bauhinia and pine forest and temperate Oak forest and analysed using an open source GLA software. LAI in the study region was ranging in between 0.076 m2/m2 to 6.00 m2/m2. These LAI values were used to develop spectral models with the FLAASH corrected Hyperion measurements.Normalized difference vegetation index (NDVI) was used taking spectral reflectance values of all the possible combinations of 170 atmospherically corrected channels. The R2 was ranging from lowest 0.0 to highest 0.837 for the band combinations of spectral region 640 nm and 670 nm. The spectral model obtained was, spectral reflectance (y) = 0.02x LAI(x) - 0.0407.

  5. Detection of crop water status in mature olive orchards using vegetation spectral measurements

    Science.gov (United States)

    Rallo, Giovanni; Ciraolo, Giuseppe; Farina, Giuseppe; Minacapilli, Mario; Provenzano, Giuseppe

    2013-04-01

    Leaf/stem water potentials are generally considered the most accurate indicators of crop water status (CWS) and they are quite often used for irrigation scheduling, even if costly and time-consuming. For this reason, in the last decade vegetation spectral measurements have been proposed, not only for environmental monitoring, but also in precision agriculture, to evaluate crop parameters and consequently for irrigation scheduling. Objective of the study was to assess the potential of hyperspectral reflectance (450-2400 nm) data to predict the crop water status (CWS) of a Mediterranean olive orchard. Different approaches were tested and particularly, (i) several standard broad- and narrow-band vegetation indices (VIs), (ii) specific VIs computed on the basis of some key wavelengths, predetermined by simple correlations and finally, (iii) using partial least squares (PLS) regression technique. To this aim, an intensive experimental campaign was carried out in 2010 and a total of 201 reflectance spectra, at leaf and canopy level, were collected with an ASD FieldSpec Pro (Analytical Spectral Devices, Inc.) handheld field spectroradiometer. CWS was contemporarily determined by measuring leaf and stem water potentials with the Scholander chamber. The results indicated that the considered standard vegetation indices were weakly correlated with CWS. On the other side, the prediction of CWS can be improved using VIs pointed to key-specific wavelengths, predetermined with a correlation analysis. The best prediction accuracy, however, can be achieved with models based on PLS regressions. The results confirmed the dependence of leaf/canopy optical features from CWS so that, for the examined crop, the proposed methodology can be considered a promising tool that could also be extended for operational applications using multispectral aerial sensors.

  6. Development of land degradation spectral indices in a semi-arid Mediterranean ecosystem

    Science.gov (United States)

    Chabrillat, Sabine; Kaufmann, Hermann J.; Palacios-Orueta, Alicia; Escribano, Paula; Mueller, Andreas

    2004-10-01

    The goal of this study is to develop remote sensing desertification indicators for drylands, in particular using the capabilities of imaging spectroscopy (hyperspectral imagery) to derive soil and vegetation specific properties linked to land degradation status. The Cabo de Gata-Nijar Natural Park in SE Spain presents a still-preserved semiarid Mediterranean ecosystem that has undergone several changes in landscape patterns and vegetation cover due to human activity. Previous studies have revealed that traditional land uses, particularly grazing, favoured in the Park the transition from tall arid brush to tall grass steppe. In the past ~40 years, tall grass steppes and arid garrigues increased while crop field decreased, and tall arid brushes decreased but then recovered after the area was declared a Natural Park in 1987. Presently, major risk is observed from a potential effect of exponential tourism and agricultural growth. A monitoring program has been recently established in the Park. Several land degradation parcels presenting variable levels of soil development and biological activity were defined in summer 2003 in agricultural lands, calcareous and volcanic areas, covering the park spatial dynamics. Intensive field spectral campaigns took place in Summer 2003 and May 2004 to monitor inter-annual changes, and assess the landscape spectral variability in spatial and temporal dimension, from the dry to the green season. Up to total 1200 field spectra were acquired over ~120 targets each year in the land degradation parcels. The targets were chosen to encompass the whole range of rocks, soils, lichens, and vegetation that can be observed in the park. Simultaneously, acquisition of hyperspectral images was performed with the HyMap sensor. This paper presents preliminary results from mainly the field spectral campaigns. Identifying sources of variability in the spectra, in relation with the ecosystem dynamics, will allow the definition of spectral indicators of

  7. Intercomparison of Remotely Sensed Vegetation Indices, Ground Spectroscopy, and Foliar Chemistry Data from NEON

    Science.gov (United States)

    Hulslander, D.; Warren, J. N.; Weintraub, S. R.

    2017-12-01

    Hyperspectral imaging systems can be used to produce spectral reflectance curves giving rich information about composition, relative abundances of materials, mixes and combinations. Indices based on just a few spectral bands have been used for over 40 years to study vegetation health, mineral abundance, and more. These indices are much simpler to visualize and use than a full hyperspectral data set which may contain over 400 bands. Yet historically, it has been difficult to directly relate remotely sensed spectral indices to quantitative biophysical properties significant to forest ecology such as canopy nitrogen, lignin, and chlorophyll. This linkage is a critical piece in enabling the detection of high value ecological information, usually only available from labor-intensive canopy foliar chemistry sampling, to the geographic and temporal coverage available via remote sensing. Previous studies have shown some promising results linking ground-based data and remotely sensed indices, but are consistently limited in time, geographic extent, and land cover type. Moreover, previous studies are often focused on tuning linkage algorithms for the purpose of achieving good results for only one study site or one type of vegetation, precluding development of more generalized algorithms. The National Ecological Observatory Network (NEON) is a unique system of 47 terrestrial sites covering all of the major eco-climatic domains of the US, including AK, HI, and Puerto Rico. These sites are regularly monitored and sampled using uniform instrumentation and protocols, including both foliar chemistry sampling and remote sensing flights for high resolution hyperspectral, LiDAR, and digital camera data acquisition. In this study we compare the results of foliar chemistry analysis to the remote sensing vegetation indices and investigate possible sources for variance and difference through the use of the larger hyperspectral dataset as well as ground based spectrometer measurements of

  8. Spectral Discrimination of Vegetation Classes in Ice-Free Areas of Antarctica

    Directory of Open Access Journals (Sweden)

    María Calviño-Cancela

    2016-10-01

    Full Text Available Detailed monitoring of vegetation changes in ice-free areas of Antarctica is crucial to determine the effects of climate warming and increasing human presence in this vulnerable ecosystem. Remote sensing techniques are especially suitable in this distant and rough environment, with high spectral and spatial resolutions needed owing to the patchiness and similarity between vegetation elements. We analyze the reflectance spectra of the most representative vegetation elements in ice-free areas of Antarctica to assess the potential for discrimination. This research is aimed as a basis for future aircraft/satellite research for long-term vegetation monitoring. The study was conducted in the Barton Peninsula, King George Island. The reflectance of ground patches of different types of vegetation or bare ground (c. 0.25 m 2 , n = 30 patches per class was recorded with a spectrophotometer measuring between 340 nm to 1025 nm at a resolution of 0.38 n m . We used Linear Discriminant Analysis (LDA to classify the cover classes according to reflectance spectra, after reduction of the number of bands using Principal Component Analysis (PCA. The first five principal components explained an accumulated 99.4% of the total variance and were added to the discriminant function. The LDA classification resulted in c. 92% of cases correctly classified (a hit ratio 11.9 times greater than chance. The most important region for discrimination was the visible and near ultraviolet (UV, with the relative importance of spectral bands steeply decreasing in the Near Infra-Red (NIR region. Our study shows the feasibility of discriminating among representative taxa of Antarctic vegetation using their spectral patterns in the near UV, visible and NIR. The results are encouraging for hyperspectral vegetation mapping in Antarctica, which could greatly facilitate monitoring vegetation changes in response to a changing environment, reducing the costs and environmental impacts of

  9. Land use change analysis using spectral similarity and vegetation indices and its effect on runoff and sediment yield in tropical environment

    Science.gov (United States)

    Christanto, N.; Sartohadi, J.; Setiawan, M. A.; Shrestha, D. B. P.; Jetten, V. G.

    2018-04-01

    Land use change influences the hydrological as well as landscape processes such as runoff and sediment yields. The main objectives of this study are to assess the land use change and its impact on the runoff and sediment yield of the upper Serayu Catchment. Land use changes of 1991 to 2014 have been analyzed. Spectral similarity and vegetation indices were used to classify the old image. Therefore, the present and the past images are comparable. The influence of the past and present land use on runoff and sediment yield has been compared with field measurement. The effect of land use changes shows the increased surface runoff which is the result of change in the curve number (CN) values. The study shows that it is possible to classify previously obtained image based on spectral characteristics and indices of major land cover types derived from recently obtained image. This avoids the necessity of having training samples which will be difficult to obtain. On the other hand, it also demonstrates that it is possible to link land cover changes with land degradation processes and finally to sedimentation in the reservoir. The only condition is the requirement for having the comparable dataset which should not be difficult to generate. Any variation inherent in the data which are other than surface reflectance has to be corrected.

  10. Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

    Science.gov (United States)

    Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

    2017-09-11

    Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

  11. Grassland canopy parameters and their relationships to remotely sensed vegetation indices in the Nebraska Sand Hills

    Science.gov (United States)

    Wylie, Bruce K.; DeJong, Donovan D.; Tieszen, Larry L.; Biondini, Mario E.

    1996-01-01

    Relationships among spectral vegetation indices and grassland biophysical parameters including the effects of varying levels of standing dead vegetation, range sites, and range plant communities were examined. Range plant communities consisting of northern mixed grass prairie and a smooth brome field as well as range sites and management in a Sand Hills bluestem prairie were sampled with a ground radiometer and for LAI, biomass, chlorophy

  12. Evaluation of a linear spectral mixture model and vegetation indices (NDVI and EVI) in a study of schistosomiasis mansoni and Biomphalaria glabrata distribution in the state of Minas Gerais, Brazil.

    Science.gov (United States)

    Guimarães, Ricardo J P S; Freitas, Corina C; Dutra, Luciano V; Scholte, Ronaldo G C; Amaral, Ronaldo S; Drummond, Sandra C; Shimabukuro, Yosio E; Oliveira, Guilherme C; Carvalho, Omar S

    2010-07-01

    This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

  13. Spectral Bio-indicator Simulations for Tracking Photosynthetic Activities in a Corn Field

    Science.gov (United States)

    Cheng, Yen-Ben; Middleton, Elizabeth M.; Huemmrich, K. Fred; Zhang, Qingyuan; Corp, Lawrence; Campbell, Petya; Kustas, William

    2011-01-01

    Accurate assessment of vegetation canopy optical properties plays a critical role in monitoring natural and managed ecosystems under environmental changes. In this context, radiative transfer (RT) models simulating vegetation canopy reflectance have been demonstrated to be a powerful tool for understanding and estimating spectral bio-indicators. In this study, two narrow band spectroradiometers were utilized to acquire observations over corn canopies for two summers. These in situ spectral data were then used to validate a two-layer Markov chain-based canopy reflectance model for simulating the Photochemical Reflectance Index (PRI), which has been widely used in recent vegetation photosynthetic light use efficiency (LUE) studies. The in situ PRI derived from narrow band hyperspectral reflectance exhibited clear responses to: 1) viewing geometry which affects the asset of light environment; and 2) seasonal variation corresponding to the growth stage. The RT model (ACRM) successfully simulated the responses to the variable viewing geometry. The best simulations were obtained when the model was set to run in the two layer mode using the sunlit leaves as the upper layer and shaded leaves as the lower layer. Simulated PRI values yielded much better correlations to in situ observations when the cornfield was dominated by green foliage during the early growth, vegetative and reproductive stages (r = 0.78 to 0.86) than in the later senescent stage (r = 0.65). Further sensitivity analyses were conducted to show the important influences of leaf area index (LAI) and the sunlit/shaded ratio on PRI observations.

  14. Spectral Reflectance and Vegetation Index Changes in Deciduous Forest Foliage Following Tree Removal: Potential for Deforestation Monitoring

    Science.gov (United States)

    Peng, D.; Hu, Y.; Li, Z.

    2016-05-01

    It is important to detect and quantify deforestation to guide strategic decisions regarding environment, socioeconomic development, and climate change. In the present study, we conducted a field experiment to examine spectral reflectance and vegetation index changes in poplar and locust tree foliage with different leaf area indices over the course of three sunny days, following tree removal from the canopy. The spectral reflectance of foliage from harvested trees was measured using an ASD FieldSpec Prospectroradiometer; synchronous meteorological data were also obtained. We found that reflectance in short-wave infrared and red-edge reflectance was more time sensitive after tree removal than reflectance in other spectral regions, and that the normalized difference water index (NDWI) and the red-edge chlorophyll index (CIRE) were the preferred indicators of these changes from several indices evaluated. Synthesized meteorological environments were found to influence water and chlorophyll contents after tree removal, and this subsequently changed the spectral canopy reflectance. Our results indicate the potential for such tree removal to be detected with NDWI or CIRE from the second day of a deforestation event.

  15. [Vegetation index estimation by chlorophyll content of grassland based on spectral analysis].

    Science.gov (United States)

    Xiao, Han; Chen, Xiu-Wan; Yang, Zhen-Yu; Li, Huai-Yu; Zhu, Han

    2014-11-01

    Comparing the methods of existing remote sensing research on the estimation of chlorophyll content, the present paper confirms that the vegetation index is one of the most practical and popular research methods. In recent years, the increasingly serious problem of grassland degradation. This paper, firstly, analyzes the measured reflectance spectral curve and its first derivative curve in the grasslands of Songpan, Sichuan and Gongger, Inner Mongolia, conducts correlation analysis between these two spectral curves and chlorophyll content, and finds out the regulation between REP (red edge position) and grassland chlorophyll content, that is, the higher the chlorophyll content is, the higher the REIP (red-edge inflection point) value would be. Then, this paper constructs GCI (grassland chlorophyll index) and selects the most suitable band for retrieval. Finally, this paper calculates the GCI by the use of satellite hyperspectral image, conducts the verification and accuracy analysis of the calculation results compared with chlorophyll content data collected from field of twice experiments. The result shows that for grassland chlorophyll content, GCI has stronger sensitivity than other indices of chlorophyll, and has higher estimation accuracy. GCI is the first proposed to estimate the grassland chlorophyll content, and has wide application potential for the remote sensing retrieval of grassland chlorophyll content. In addition, the grassland chlorophyll content estimation method based on remote sensing retrieval in this paper provides new research ideas for other vegetation biochemical parameters' estimation, vegetation growth status' evaluation and grassland ecological environment change's monitoring.

  16. Estimating salinity stress in sugarcane fields with spaceborne hyperspectral vegetation indices

    Science.gov (United States)

    Hamzeh, S.; Naseri, A. A.; AlaviPanah, S. K.; Mojaradi, B.; Bartholomeus, H. M.; Clevers, J. G. P. W.; Behzad, M.

    2013-04-01

    The presence of salt in the soil profile negatively affects the growth and development of vegetation. As a result, the spectral reflectance of vegetation canopies varies for different salinity levels. This research was conducted to (1) investigate the capability of satellite-based hyperspectral vegetation indices (VIs) for estimating soil salinity in agricultural fields, (2) evaluate the performance of 21 existing VIs and (3) develop new VIs based on a combination of wavelengths sensitive for multiple stresses and find the best one for estimating soil salinity. For this purpose a Hyperion image of September 2, 2010, and data on soil salinity at 108 locations in sugarcane (Saccharum officina L.) fields were used. Results show that soil salinity could well be estimated by some of these VIs. Indices related to chlorophyll absorption bands or based on a combination of chlorophyll and water absorption bands had the highest correlation with soil salinity. In contrast, indices that are only based on water absorption bands had low to medium correlations, while indices that use only visible bands did not perform well. From the investigated indices the optimized soil-adjusted vegetation index (OSAVI) had the strongest relationship (R2 = 0.69) with soil salinity for the training data, but it did not perform well in the validation phase. The validation procedure showed that the new salinity and water stress indices (SWSI) implemented in this study (SWSI-1, SWSI-2, SWSI-3) and the Vogelmann red edge index yielded the best results for estimating soil salinity for independent fields with root mean square errors of 1.14, 1.15, 1.17 and 1.15 dS/m, respectively. Our results show that soil salinity could be estimated by satellite-based hyperspectral VIs, but validation of obtained models for independent data is essential for selecting the best model.

  17. EPR and IR spectral investigations on some leafy vegetables of Indian origin

    Science.gov (United States)

    Prasuna, C. P. Lakshmi; Chakradhar, R. P. S.; Rao, J. L.; Gopal, N. O.

    2009-09-01

    EPR spectral investigations have been carried out on four edible leafy vegetables of India, which are used as dietary component in day to day life. In Rumex vesicarius leaf sample, EPR spectral investigations at different temperatures indicate the presence of anti-ferromagnetically coupled Mn(IV)-Mn(IV) complexes. EPR spectra of Trigonella foenum graecum show the presence of Mn ions in multivalent state and Fe 3+ ions in rhombic symmetry. EPR spectra of Basella rubra indicate the presence of Mn(IV)-O-Mn(IV) type complexes. The EPR spectra of Basella rubra have been studied at different temperatures. It is found that the spin population for the resonance signal at g = 2.06 obeys the Boltzmann distribution law. The EPR spectra of Moringa oliefera leaves show the presence of Mn 2+ ions. Radiation induced changes in free radical of this sample have also been studied. The FT-IR spectra of Basella rubra and Moringa oliefera leaves show the evidences for the protein matrix bands and those corresponding to carboxylic C dbnd O bonds.

  18. Prototype simulates remote sensing spectral measurements on fruits and vegetables

    Science.gov (United States)

    Hahn, Federico

    1998-09-01

    A prototype was designed to simulate spectral packinghouse measurements in order to simplify fruit and vegetable damage assessment. A computerized spectrometer is used together with lenses and an externally controlled illumination in order to have a remote sensing simulator. A laser is introduced between the spectrometer and the lenses in order to mark the zone where the measurement is being taken. This facilitates further correlation work and can assure that the physical and remote sensing measurements are taken in the same place. Tomato ripening and mango anthracnose spectral signatures are shown.

  19. Assessment of Landsat multispectral scanner spectral indexes for monitoring arid rangeland

    Science.gov (United States)

    Musick, H. B.

    1984-01-01

    Correlations between spectral indices and vegetation parameters in south-central New Mexico were used to determine the utility of Landsat Multispectral Scanner (MSS) spectral indices in arid rangeland monitoring. In addition, spectral index change for 1976-1980 was calculated from retrospective MSS data and compared with qualitative ground truth in order to evaluate vegetation change detection by means of spectral indices. Brightness index change consistently differentiated between cover increase and decrease, but index change appears to have been offset from true cover change; this may at least partly be attributed to the failure of the methods used to standardize MSS scenes for differences in sensor response. Green vegetation indices, by contrast to brightness indices, failed to consistently differentiate between cover increase and decrease.

  20. Derivation of the canopy conductance from surface temperature and spectral indices for estimating evapotranspiration in semiarid vegetation

    International Nuclear Information System (INIS)

    Morillas, L.; Garcia, M.; Zarco-Tejada, P.; Ladron de Guevara, M.; Villagarcia, L.; Were, A.; Domingo, F.

    2009-01-01

    This work evaluates the possibilities for estimating stomata conductance (C) and leaf transpiration (Trf) at the ecosystem scale from radiometric indices and surface temperature. The relationships found between indices and the transpiration component of the water balance in a semiarid tussock ecosystem in SE Spain are discussed. Field data were collected from spring 2008 until winter 2009 in order to observe the annual variability of the relationships and the behaviour of spectral indices and surface temperature. (Author) 11 refs.

  1. Integrating multiple vegetation indices via an artificial neural network model for estimating the leaf chlorophyll content of Spartina alterniflora under interspecies competition.

    Science.gov (United States)

    Liu, Pudong; Shi, Runhe; Zhang, Chao; Zeng, Yuyan; Wang, Jiapeng; Tao, Zhu; Gao, Wei

    2017-10-31

    The invasive species Spartina alterniflora and native species Phragmites australis display a significant co-occurrence zonation pattern and this co-exist region exerts most competitive situations between these two species, competing for the limited space, directly influencing the co-exist distribution in the future. However, these two species have different growth ratios in this area, which increase the difficulty to detect the distribution situation directly by remote sensing. As chlorophyll content is a key indicator of plant growth and physiological status, the objective of this study was to reduce the effect of interspecies competition when estimating Cab content; we evaluated 79 published representative indices to determine the optimal indices for estimating the chlorophyll a and b (Cab) content. After performing a sensitivity analysis for all 79 spectral indices, five spectral indices were selected and integrated using an artificial neural network (ANN) to estimate the Cab content of different competition ratios: the Gitelson ratio green index, the transformed chlorophyll absorption ratio index/optimized soil-adjusted vegetation index, the modified normalized difference vegetation index, the chlorophyll fluorescence index, and the Vogelmann chlorophyll index. The ANN method yielded better results (R 2  = 0.7110 and RMSE = 8.3829 μg cm -2 ) on average than the best single spectral index (R 2  = 0.6319 and RMSE = 9.3535 μg cm -2 ), representing an increase of 10.78% in R 2 and a decrease of 10.38% in RMSE. Our results indicated that integrating multiple vegetation indices with an ANN can alleviate the impact of interspecies competition and achieve higher estimation accuracy than the traditional approach using a single index.

  2. Mapping the Wetland Vegetation Communities of the Australian Great Artesian Basin Springs Using SAM, Mtmf and Spectrally Segmented PCA Hyperspectral Analyses

    Science.gov (United States)

    White, D. C.; Lewis, M. M.

    2012-07-01

    segmented for the VIS-NIR (450-1,350 nm), SWIR 1 (1,400-1,800 nm) and SWIR 2 (1,950-2,480 nm). The resulting pure endmember image pixels of the vegetation communities identified were used as target spectra for input into the SAM and MTMF algorithms. Spring wetland vegetation communities successfully discriminated include low lying reeds and sedges along spring tails (Baumea spp. and Cyperus spp.), dense homogenous stands of Phragmites australis reeds, and sporadic patches of salt couch grass (Sparabolus spp.). Our results indicate that a combination of hyperspectral remote sensing techniques which reduce superfluous wavebands providing a targeted spectral matching approach are capable of discriminating and mapping key vegetation communities of the GAB springs. This approach provides reliable baseline mapping of the GAB spring wetland vegetation communities, with repeatability over space and time. In addition it has the capability to determine the sensitivity of spring wetland vegetation extent, distribution and diversity, to associated changes in spring flow rates due to water extractions. This approach will ultimately inform water allocation plan management policies.

  3. Improvement in remote sensing of low vegetation cover in arid regions by correcting vegetation indices for soil ''noise''; Etude des propriétés spectrales des sols arides appliquée à l'amélioration des indices de végétation obtenus par télédétection

    Energy Technology Data Exchange (ETDEWEB)

    Escadafal, R. [Institut Francais de Recherche Scientifique pour le Developpement en Cooperation, Bondy (France); Huete, A.

    1991-05-23

    The variations of near-infrared red reflectance ratios of ten aridic soil samples were correlated with a ''redness index'' computed from red and green spectral bands. These variations have been shown to limit the performances of vegetation indices (NDVI and SAVI) in discriminating low vegetation covers. The redness index is used to adjust for this ''soil noise''. Dala simulated for vegetation densities of 5 to 15% cover showed that the sensitivity of the corrected vegetation indices was significantly improved. Specifically, the ''noise-corrected'' SAVI was able to assess vegetation amounts with an error four times smaller than the uncorrected NDVI. These promising results should lead to a significant improvement in assessing biomass in arid lands from remotely sensed data. (author) [French] Les variations du rapport de la réflectance dans les bandes rouge et infrarouge sont mises en relation avec un (( indice de coloration )) pouf une série de dix sols arides. Ces variations gZnent fortement la détection des faibles taux de couvert végétal avec les indices de végétation (NDVI et SAVI) calculés à partir de ces deux bandes. Il est proposé d’utiliser l’indice de coloration comme facteur de correction de ce (( bruit )) dû au sol. Une simulation de la reflectance des sols avec une couverture végétale variant de O à 15 % en évidence un doublement de la sensibilité des indices de végétation ainsi corrigés. En particulier, le SAVI corrigé permet d’estimer le taux de végétation avec une erreur quatre fois inférieure à celle du NDVI non corrigé. Ces premiers résultats devraient conduire à une amélioration sensible de la mesure de la biomasse végétale des régions arides par télédétection. (author)

  4. Estimating Leaf Area Index for an arid region using Spectral Data ...

    African Journals Online (AJOL)

    In this study, spectral reflectance of pearl millet was computed at various wavelengths and at different times during the cropping season, using a spectroradiometer. Three main indices (Normalised Difference Vegetation Index, Ratio Vegetation Index, and Perpendicular Vegetation Index)were derived from the spectral data.

  5. [Analysis of spectral features based on water content of desert vegetation].

    Science.gov (United States)

    Zhao, Zhao; Li, Xia; Yin, Ye-biao; Tang, Jin; Zhou, Sheng-bin

    2010-09-01

    By using HR-768 field-portable spectroradiometer made by the Spectra Vista Corporation (SVC) of America, the hyper-spectral data of nine types of desert plants were measured, and the water content of corresponding vegetation was determined by roasting in lab. The continuum of measured hyperspectral data was removed by using ENVI, and the relationship between the water content of vegetation and the reflectance spectrum was analyzed by using correlation coefficient method. The result shows that the correlation between the bands from 978 to 1030 nm and water content of vegetation is weak while it is better for the bands from 1133 to 1266 nm. The bands from 1374 to 1534 nm are the characteristic bands because of the correlation between them and water content is the best. By using cluster analysis and according to the water content, the vegetation could be marked off into three grades: high (>70%), medium (50%-70%) and low (<50%). The research reveals the relationship between water content of desert vegetation and hyperspectral data, and provides basis for the analysis of area in desert and the monitoring of desert vegetation by using remote sensing data.

  6. Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data

    Science.gov (United States)

    Lhermitte, S.; Tips, M.; Verbesselt, J.; Jonckheere, I.; Van Aardt, J.; Coppin, Pol

    2005-10-01

    Large-scale wild fires have direct impacts on natural ecosystems and play a major role in the vegetation ecology and carbon budget. Accurate methods for describing post-fire development of vegetation are therefore essential for the understanding and monitoring of terrestrial ecosystems. Time series analysis of satellite imagery offers the potential to quantify these parameters with spatial and temporal accuracy. Current research focuses on the potential of time series analysis of SPOT Vegetation S10 data (1999-2001) to quantify the vegetation recovery of large-scale burns detected in the framework of GBA2000. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of vegetation recovery based on remote sensing indicators. Southern Africa was used as a pilot study area, given the availability of ground and satellite data. An automated technique was developed to extract consistent indicators of vegetation recovery from the SPOT-VGT time series. Reference areas were used to quantify the vegetation regrowth by means of Regeneration Indices (RI). Two kinds of recovery indicators (time and value- based) were tested for RI's of NDVI, SR, SAVI, NDWI, and pure band information. The effects of vegetation structure and temporal fire regime features on the recovery indicators were subsequently analyzed. Statistical analyses were conducted to assess whether the recovery indicators were different for different vegetation types and dependent on timing of the burning season. Results highlighted the importance of appropriate reference areas and the importance of correct normalization of the SPOT-VGT data.

  7. Spectral entropy as a mean to quantify water stress history for natural vegetation and irrigated agriculture in a water-stressed tropical environment

    Science.gov (United States)

    Kim, Y.; Johnson, M. S.

    2017-12-01

    Spectral entropy (Hs) is an index which can be used to measure the structural complexity of time series data. When a time series is made up of one periodic function, the Hs value becomes smaller, while Hs becomes larger when a time series is composed of several periodic functions. We hypothesized that this characteristic of the Hs could be used to quantify the water stress history of vegetation. For the ideal condition for which sufficient water is supplied to an agricultural crop or natural vegetation, there should be a single distinct phenological cycle represented in a vegetation index time series (e.g., NDVI and EVI). However, time series data for a vegetation area that repeatedly experiences water stress may include several fluctuations that can be observed in addition to the predominant phenological cycle. This is because the process of experiencing water stress and recovering from it generates small fluctuations in phenological characteristics. Consequently, the value of Hs increases when vegetation experiences several water shortages. Therefore, the Hs could be used as an indicator for water stress history. To test this hypothesis, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data for a natural area in comparison to a nearby sugarcane area in seasonally-dry western Costa Rica. In this presentation we will illustrate the use of spectral entropy to evaluate the vegetative responses of natural vegetation (dry tropical forest) and sugarcane under three different irrigation techniques (center pivot irrigation, drip irrigation and flood irrigation). Through this comparative analysis, the utility of Hs as an indicator will be tested. Furthermore, crop response to the different irrigation methods will be discussed in terms of Hs, NDVI and yield.

  8. Assessing corn water stress using spectral reflectance

    Science.gov (United States)

    Mefford, Brenna S.

    Multiple remote sensing techniques have been developed to identify crop water stress, but some methods may be difficult for farmers to apply. Unlike most techniques, shortwave vegetation indices can be calculated using satellite, aerial, or ground imagery from the green (525-600 nm), red (625-700 nm), and near infrared (750-900 nm) spectral bands. If vegetation indices can be used to monitor crop water stress, growers could use this information as a quick low-cost guideline for irrigation management, thus helping save water by preventing over irrigating. This study occurred in the 2013 growing season near Greeley, CO, where pressurized drip irrigation was used to irrigate twelve corn ( Zea mays L.) treatments of varying water deficit. Multispectral data was collected and four different vegetation indices were evaluated: Normalized Difference Vegetation Index (NDVI), Optimized Soil-Adjusted Vegetation Index (OSAVI), Green Normalized Difference Vegetation Index (GNDVI), and the Wide Dynamic Range Vegetation Index (WDRVI). The four vegetation indices were compared to corn water stress as indicated by the stress coefficient (Ks) and water deficit in the root zone, calculated by using a water balance that monitors crop evapotranspiration (ET), irrigation events, precipitation events, and deep percolation. ET for the water balance was calculated using two different methods for comparison purposes: (1) calculation of the stress coefficient (Ks) using FAO-56 standard procedures; (2) use of canopy temperature ratio (Tc ratio) of a stressed crop to a non-stressed crop to calculate Ks. It was found that obtaining Ks from Tc ratio is a viable option, and requires less data to obtain than Ks from FAO-56. In order to compare the indices to Ks, vegetation ratios were developed in the process of normalization. Vegetation ratios are defined as the non-stressed vegetation index divided by the stressed vegetation index. Results showed that vegetation ratios were sensitive to water

  9. Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

    Energy Technology Data Exchange (ETDEWEB)

    Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.; Cook, David R.; Matamala, Roser; Fischer, Marc L.; Jin, Cui; Dong, Jinwei; Biradar, Chandrashekhar

    2014-09-01

    Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared with the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.

  10. Canopy Modeling of Aquatic Vegetation: Construction of Submerged Vegetation Index

    Science.gov (United States)

    Ma, Z.; Zhou, G.

    2018-04-01

    The unique spectral characteristics of submerged vegetation in wetlands determine that the conventional terrestrial vegetation index cannot be directly employed to species identification and parameter inversion of submerged vegetation. Based on the Aquatic Vegetation Radiative Transfer model (AVRT), this paper attempts to construct an index suitable for submerged vegetation, the model simulated data and a scene of Sentinel-2A image in Taihu Lake, China are utilized for assessing the performance of the newly constructed indices and the existent vegetation indices. The results show that the angle index composed by 525 nm, 555 nm and 670 nm can resist the effects of water columns and is more sensitive to vegetation parameters such as LAI. Furthermore, it makes a well discrimination between submerged vegetation and water bodies in the satellite data. We hope that the new index will provide a theoretical basis for future research.

  11. Soil TPH Concentration Estimation Using Vegetation Indices in an Oil Polluted Area of Eastern China

    Science.gov (United States)

    Zhu, Linhai; Zhao, Xuechun; Lai, Liming; Wang, Jianjian; Jiang, Lianhe; Ding, Jinzhi; Liu, Nanxi; Yu, Yunjiang; Li, Junsheng; Xiao, Nengwen; Zheng, Yuanrun; Rimmington, Glyn M.

    2013-01-01

    Assessing oil pollution using traditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provide an alternative for monitoring oil pollution by recording the spectral signals of plants growing in polluted soils. Total petroleum hydrocarbon concentrations of soils and the hyperspectral canopy reflectance were measured in wetlands dominated by reeds (Phragmites australis) around oil wells that have been producing oil for approximately 10 years in the Yellow River Delta, eastern China to evaluate the potential of vegetation indices and red edge parameters to estimate soil oil pollution. The detrimental effect of oil pollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m−2 to 5.3 g m−2 with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg−1 to 652 mg kg−1. The modified chlorophyll absorption ratio index (MCARI) best estimated soil TPH concentration among 20 vegetation indices. The linear model involving MCARI had the highest coefficient of determination (R 2 = 0.73) and accuracy of prediction (RMSE = 104.2 mg kg−1). For other vegetation indices and red edge parameters, the R2 and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg−1 to 106.8 mg kg−1 respectively. The traditional broadband normalized difference vegetation index (NDVI), one of the broadband multispectral vegetation indices (BMVIs), produced a prediction (R 2 = 0.70 and RMSE = 110.1 mg kg−1) similar to that of MCARI. These results corroborated the potential of remote sensing for assessing soil oil pollution in large areas. Traditional BMVIs are still of great value in monitoring soil oil pollution when hyperspectral data are unavailable. PMID:23342066

  12. Variations of reflectance and vegetation indices as a function of the topographic modeling parameter of the Parque Estadual do Turvo, Rio Grande do Sul, Brasil

    Directory of Open Access Journals (Sweden)

    William Gaida

    2016-11-01

    Full Text Available Remote sensing techniques have been widely used in forestry studies because they allow evaluation and monitoring of large areas. The Parque Estadual do Turvo (PET (17.491 ha is the largest fragment of preserved subtropical deciduous forest of South Brazil, representing an extension of the Misiones forest in Argentina (10.000 km². This area has great environmental importance and is adequate for performing remote sensing studies using high or even coarse-to-moderate spatial resolution data as well as related vegetation indices. Both, the reflectance and vegetation indices, are affected by external factors that change the spectral response of the surface components. Among the factors that can introduce errors in the interpretation of the images, topographic effects add spectral variability in satellite products. In addition, previous studies in subtropical forests showed that the geometry of data acquisition affects significantly the estimates of vegetation parameters derived from images acquired at off-nadir viewing or by large field-of-view (FOV sensors. This study aimed to evaluate the magnitude of the bidirectional reflectance variations and of the derived vegetation indices as a function of local topography using high spatial resolution data acquired by the RapidEye constellation of satellites.

  13. Crop Type Classification Using Vegetation Indices of RapidEye Imagery

    Science.gov (United States)

    Ustuner, M.; Sanli, F. B.; Abdikan, S.; Esetlili, M. T.; Kurucu, Y.

    2014-09-01

    Cutting-edge remote sensing technology has a significant role for managing the natural resources as well as the any other applications about the earth observation. Crop monitoring is the one of these applications since remote sensing provides us accurate, up-to-date and cost-effective information about the crop types at the different temporal and spatial resolution. In this study, the potential use of three different vegetation indices of RapidEye imagery on crop type classification as well as the effect of each indices on classification accuracy were investigated. The Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) are the three vegetation indices used in this study since all of these incorporated the near-infrared (NIR) band. RapidEye imagery is highly demanded and preferred for agricultural and forestry applications since it has red-edge and NIR bands. The study area is located in Aegean region of Turkey. Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Original bands of RapidEye imagery were excluded and classification was performed with only three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 87, 46 % was obtained using three vegetation indices. This obtained classification accuracy is higher than the classification accuracy of any dual-combination of these vegetation indices. Results demonstrate that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the RapidEye imagery can get satisfactory results of classification accuracy without original bands.

  14. Changes in vertical distribution of spectral reflectance within Spring barley canopy as an indicator of nitrogen nutrition, canopy structure and yield parametrs

    Czech Academy of Sciences Publication Activity Database

    Klem, Karel; Rajsnerová, Petra; Novotná, Kateřina; Míša, P.; Křen, J.

    2014-01-01

    Roč. 60, č. 2 (2014), s. 50-59 ISSN 0551-3677 R&D Projects: GA MZe QI111A133; GA TA ČR TA02010780 Institutional support: RVO:67179843 Keywords : Hordeum vulgare * spectral reflectance * vertical gradient * vegetation indices * nitrogen * grain yield * protein content Subject RIV: GC - Agronomy

  15. Using Landsat Spectral Indices in Time-Series to Assess Wildfire Disturbance and Recovery

    Directory of Open Access Journals (Sweden)

    Samuel Hislop

    2018-03-01

    Full Text Available Satellite earth observation is being increasingly used to monitor forests across the world. Freely available Landsat data stretching back four decades, coupled with advances in computer processing capabilities, has enabled new time-series techniques for analyzing forest change. Typically, these methods track individual pixel values over time, through the use of various spectral indices. This study examines the utility of eight spectral indices for characterizing fire disturbance and recovery in sclerophyll forests, in order to determine their relative merits in the context of Landsat time-series. Although existing research into Landsat indices is comprehensive, this study presents a new approach, by comparing the distributions of pre and post-fire pixels using Glass’s delta, for evaluating indices without the need of detailed field information. Our results show that in the sclerophyll forests of southeast Australia, common indices, such as the Normalized Difference Vegetation Index (NDVI and the Normalized Burn Ratio (NBR, both accurately capture wildfire disturbance in a pixel-based time-series approach, especially if images from soon after the disturbance are available. However, for tracking forest regrowth and recovery, indices, such as NDVI, which typically capture chlorophyll concentration or canopy ‘greenness’, are not as reliable, with values returning to pre-fire levels in 3–5 years. In comparison, indices that are more sensitive to forest moisture and structure, such as NBR, indicate much longer (8–10 years recovery timeframes. This finding is consistent with studies that were conducted in other forest types. We also demonstrate that additional information regarding forest condition, particularly in relation to recovery, can be extracted from less well known indices, such as NBR2, as well as textural indices incorporating spatial variance. With Landsat time-series gaining in popularity in recent years, it is critical to

  16. Applicability of spectral indices on thickness identification of oil slick

    Science.gov (United States)

    Niu, Yanfei; Shen, Yonglin; Chen, Qihao; Liu, Xiuguo

    2016-10-01

    Hyperspectral remote sensing technology has played a vital role in the identification and monitoring of oil spill events, and amount of spectral indices have been developed. In this paper, the applicability of six frequently-used indices is analyzed, and a combination of spectral indices in aids of support vector machine (SVM) algorithm is used to identify the oil slicks and corresponding thickness. The six spectral indices are spectral rotation (SR), spectral absorption depth (HI), band ratio of blue and green (BG), band ratio of BG and shortwave infrared index (BGN), 555nm and 645nm normalized by the blue band index (NB) and spectral slope (ND). The experimental study is conducted in the Gulf of Mexico oil spill zone, with Airborne Visible Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery captured in May 17, 2010. The results show that SR index is the best in all six indices, which can effectively distinguish the thickness of the oil slick and identify it from seawater; HI index and ND index can obviously distinguish oil slick thickness; BG, BGN and NB are more suitable to identify oil slick from seawater. With the comparison among different kernel functions of SVM, the classify accuracy show that the polynomial and RBF kernel functions have the best effect on the separation of oil slick thickness and the relatively pure seawater. The applicability of spectral indices of oil slick and the method of oil film thickness identification will in aids of oil/gas exploration and oil spill monitoring.

  17. An evaluation of hyperspectral vegetation indices for detecting soil salinity in sugarcane fields using EO-1 Hyperion Data

    Science.gov (United States)

    Hamzeh, S.; Naseri, A. A.; Alavi Panah, S. K.; Bartholomeus, H.; Mojaradi, B.; Clevers, J.; Behzad, M.

    2012-04-01

    Sugarcane is the major agricultural crops in the Khuzestan province, in the southwest of Iran. But soil salinity is a major problem affecting the sugarcane yield, and therefore, monitoring and assessment of soil salinity is necessary. This research was carried out to investigate the performance of several hyperspectral vegetation indices to assess salinity stress in sugarcane fields and to determine the suitable indicators and statistical models for detecting various soil salinity levels. For this purpose one Hyperion image was acquired on Sept 2, 2010 and soil salinity was measured in 108 points 5 to 15 days from this date. 60 Samples were used for modeling and 48 samples were used for validation. Values of the soil salinity were linked with the corresponding pixel at the satellite imagery and 16 (hyperspectral) spectral indices were calculated. Then, the potential of these indices for estimating the soil salinity were analyzed and results show that soil salinity can well be estimated by vegetation indices derived from Hyperion data. Indices that are based on the chlorophyll and water absorption bands have medium to high relationship with soil salinity, while indices that only use visible bands or combination of visible and NIR bands don't perform well. From the investigated indices the Optimized Soil-Adjusted Vegetation Index (OSAVI) has the strongest relationship (R2 = 0.69) with soil salinity, because this index minimizes the variations in reflectance characteristics of soil background.

  18. Temporal dynamics of spectral bioindicators evidence biological and ecological differences among functional types in a cork oak open woodland

    Science.gov (United States)

    Cerasoli, Sofia; Costa e Silva, Filipe; Silva, João M. N.

    2016-06-01

    The application of spectral vegetation indices for the purpose of vegetation monitoring and modeling increased largely in recent years. Nonetheless, the interpretation of biophysical properties of vegetation through their spectral signature is still a challenging task. This is particularly true in Mediterranean oak forest characterized by a high spatial and temporal heterogeneity. In this study, the temporal dynamics of vegetation indices expected to be related with green biomass and photosynthetic efficiency were compared for the canopy of trees, the herbaceous layer, and two shrub species: cistus ( Cistus salviifolius) and ulex ( Ulex airensis). coexisting in a cork oak woodland. All indices were calculated from in situ measurements with a FieldSpec3 spectroradiometer (ASD Inc., Boulder, USA). Large differences emerged in the temporal trends and in the correlation between climate and vegetation indices. The relationship between spectral indices and temperature, radiation, and vapor pressure deficit for cork oak was opposite to that observed for the herbaceous layer and cistus. No correlation was observed between rainfall and vegetation indices in cork oak and ulex, but in the herbaceous layer and in the cistus, significant correlations were found. The analysis of spectral vegetation indices with fraction of absorbed PAR (fPAR) and quantum yield of chlorophyll fluorescence ( ΔF/ Fm') evidenced strongest relationships with the indices Normalized Difference Water Index (NDWI) and Photochemical Reflectance Index (PRI)512, respectively. Our results, while confirms the ability of spectral vegetation indices to represent temporal dynamics of biophysical properties of vegetation, evidence the importance to consider ecosystem composition for a correct ecological interpretation of results when the spatial resolution of observations includes different plant functional types.

  19. Performance Evaluation of Spectral Clustering Algorithm using Various Clustering Validity Indices

    OpenAIRE

    M. T. Somashekara; D. Manjunatha

    2014-01-01

    In spite of the popularity of spectral clustering algorithm, the evaluation procedures are still in developmental stage. In this article, we have taken benchmarking IRIS dataset for performing comparative study of twelve indices for evaluating spectral clustering algorithm. The results of the spectral clustering technique were also compared with k-mean algorithm. The validity of the indices was also verified with accuracy and (Normalized Mutual Information) NMI score. Spectral clustering algo...

  20. Climatic Changes Effects On Spectral Vegetation Indices For Forested Areas Analysis From Satellite Data

    International Nuclear Information System (INIS)

    Zoran, M.; Stefan, S.

    2007-01-01

    Climate-induced changes at the land surface may in turn feed back on the climate itself through changes in soil moisture, vegetation, radiative characteristics, and surface-atmosphere exchanges of water vapor. Thresholding based on biophysical variables derived from time trajectories of satellite data is a new approach to classifying forest land cover via remote . sensing .The input data are composite values of the Normalized Difference Vegetation Index (NDVI). Classification accuracies are function of the class, comparison method and season of the year. The aim of the paper is forest biomass assessment and land-cover changes analysis due to climatic effects

  1. Sensitivity of spectral indices to CO2 fluxes for several plant communities in a Sphagnum-dominated peatland

    International Nuclear Information System (INIS)

    Letendre, J.; Poulin, M.; Rochefort, L.

    2008-01-01

    A study was conducted in which the relationship between spectral indices and carbon dioxide (CO 2 ) fluxes was tested for different communities in a Sphagnum-dominated peatland. This paper focused on the remote sensing approach that was used to directly link spectral indices to CO 2 fluxes to highlight the potential of remote sensing for mapping the spatial distribution of CO 2 fluxes. Carbon exchange in these ecosystems has become an environmental concern since peatlands play a key role in the global carbon cycle. A portable climate-controlled chamber was used to measure fluxes while simultaneously recording reflectance with a hand-held spectroradiometer. A laboratory experiment was also conducted to find a water-related index that most correlated with Sphagnum water content in order to regulate the normalized difference vegetation index (NDVI) values obtained in the field. The laboratory experiment showed a strong correlation between Sphagnum water content and all spectral indices, notably the water index (WI), normalized difference water index (NDWI), and relative depth index (RDI). The water index was chosen to regulate NDVI values. This paper described the indices that were tested in the field for CO 2 flux estimations. NDVI alone was found to be a poor predictor of net ecosystem exchange. The relationship between CO 2 fluxes and narrow band chlorophyll indices was reasonably well adjusted. It was concluded that the chlorophyll indices may be the most promising for mapping the spatial distribution of CO 2 fluxes in the future. 62 refs., 2 tabs., 4 figs

  2. Evaluation of land and vegetation degradation indicators in Kiang ...

    African Journals Online (AJOL)

    Evaluation of land and vegetation degradation indicators in Kiang'ombe ... land and vegetation degradation risk and analyzing the effectiveness of various ... The methods used included; Focus Group Discussions (FGD), key informant ...

  3. Spectral Slope as an Indicator of Pasture Quality

    Directory of Open Access Journals (Sweden)

    Rachel Lugassi

    2014-12-01

    Full Text Available In this study, we develop a spectral method for assessment of pasture quality based only on the spectral information obtained with a small number of wavelengths. First, differences in spectral behavior were identified across the near infrared–shortwave infrared spectral range that were indicative of changes in chemical properties. Then, slopes across different spectral ranges were calculated and correlated with the changes in crude protein (CP, neutral detergent fiber (NDF and metabolic energy concentration (MEC. Finally, partial least squares (PLS regression analysis was applied to identify the optimal spectral ranges for accurate assessment of CP, NDF and MEC. Six spectral domains and a set of slope criteria for real-time evaluation of pasture quality were suggested. The evaluation of three level categories (low, medium, high for these three parameters showed a success rate of: 73%–96% for CP, 72%–87% for NDF and 60%–85% for MEC. Moreover, only one spectral range, 1748–1764 nm, was needed to provide a good estimation of CP, NDF and MEC. Importantly, five of the six selected spectral regions were not affected by water absorbance. With some modifications, this rationale can be applied to further analyses of pasture quality from airborne sensors.

  4. Analysis of Post-Fire Vegetation Recovery in the Mediterranean Basin using MODIS Derived Vegetation Indices

    Science.gov (United States)

    Hawtree, Daniel; San Miguel, Jesus; Sedano, Fernando; Kempeneers, Pieter

    2010-05-01

    The Mediterranean basin region is highly susceptible to wildfire, with approximately 60,000 individual fires and half a million ha of natural vegetation burnt per year. Of particular concern in this region is the impact of repeated wildfires on the ability of natural lands to return to a pre-fire state, and of the possibility of desertification of semi-arid areas. Given these concerns, understanding the temporal patterns of vegetation recovery is important for the management of environmental resources in the region. A valuable tool for evaluating these recovery patterns are vegetation indices derived from remote sensing data. Previous research on post-fire vegetation recovery conducted in this region has found significant variability in recovery times across different study sites. It is unclear what the primary variables are affecting the differences in the rates of recovery, and if any geographic patterns of behavior exist across the Mediterranean basin. This research has primarily been conducted using indices derived from Landsat imagery. However, no extensive analysis of vegetation regeneration for large regions has been published, and assessment of vegetation recovery on the basis of medium-spatial resolution imagery such as that of MODIS has not yet been analyzed. This study examines the temporal pattern of vegetation recovery in a number of fire sites in the Mediterranean basin, using data derived from MODIS 16 -day composite vegetation indices. The intent is to develop a more complete picture of the temporal sequence of vegetation recovery, and to evaluate what additional factors impact variations in the recovery sequence. In addition, this study evaluates the utility of using MODIS derived vegetation indices for regeneration studies, and compares the findings to earlier studies which rely on Landsat data. Wildfires occurring between the years 2000 and 2004 were considered as potential study sites for this research. Using the EFFIS dataset, all wildfires

  5. Using hyper-spectral indices to detect soil phosphorus concentration for various land use patterns.

    Science.gov (United States)

    Lin, Chen; Ma, Ronghua; Zhu, Qing; Li, Jingtao

    2015-01-01

    The management of nonpoint source pollution requires accurate information regarding soil phosphorus concentrations for different land use patterns. The use of remotely sensed information provides an important opportunity for such studies, and the previous studies showed that soil phosphorus shows no clear spectral response feature, while the phosphorus concentrations can be indirectly detected from the normalised difference vegetation indices (NDVI). Therefore, this study uses an optimised index in the RED and near-infrared (NIR) wavelengths to estimate total phosphorus and Olsen-P concentrations. The prediction accuracy is not entirely satisfactory with respect to a mixed land use dataset in which the determination coefficient was maintained at approximately 0.6, with particularly poor performance obtained for forest land group. However, the prediction accuracy increases markedly with the separation of samples into broad land use categories, even the R(2) was exceeded 0.8 for tea plantation group. The soil phosphorus prediction effect showed obvious variance for different land use patterns, which was related to vegetation growth conditions and critical soil properties including soil organic matter and mechanical composition.

  6. A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

    Science.gov (United States)

    Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

    2013-02-01

    Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was

  7. Sensitivity of spectral indices to CO{sub 2} fluxes for several plant communities in a Sphagnum-dominated peatland

    Energy Technology Data Exchange (ETDEWEB)

    Letendre, J.; Poulin, M.; Rochefort, L. [Laval Univ., Quebec City, PQ (Canada). Dept. de Phytologie, Peatland Ecology and Research Group

    2008-07-01

    A study was conducted in which the relationship between spectral indices and carbon dioxide (CO{sub 2}) fluxes was tested for different communities in a Sphagnum-dominated peatland. This paper focused on the remote sensing approach that was used to directly link spectral indices to CO{sub 2} fluxes to highlight the potential of remote sensing for mapping the spatial distribution of CO{sub 2} fluxes. Carbon exchange in these ecosystems has become an environmental concern since peatlands play a key role in the global carbon cycle. A portable climate-controlled chamber was used to measure fluxes while simultaneously recording reflectance with a hand-held spectroradiometer. A laboratory experiment was also conducted to find a water-related index that most correlated with Sphagnum water content in order to regulate the normalized difference vegetation index (NDVI) values obtained in the field. The laboratory experiment showed a strong correlation between Sphagnum water content and all spectral indices, notably the water index (WI), normalized difference water index (NDWI), and relative depth index (RDI). The water index was chosen to regulate NDVI values. This paper described the indices that were tested in the field for CO{sub 2} flux estimations. NDVI alone was found to be a poor predictor of net ecosystem exchange. The relationship between CO{sub 2} fluxes and narrow band chlorophyll indices was reasonably well adjusted. It was concluded that the chlorophyll indices may be the most promising for mapping the spatial distribution of CO{sub 2} fluxes in the future. 62 refs., 2 tabs., 4 figs.

  8. Using RPAS Multi-Spectral Imagery to Characterise Vigour, Leaf Development, Yield Components and Berry Composition Variability within a Vineyard

    Directory of Open Access Journals (Sweden)

    Clara Rey-Caramés

    2015-10-01

    Full Text Available Implementation of precision viticulture techniques requires the use of emerging sensing technologies to assess the vineyard spatial variability. This work shows the capability of multispectral imagery acquired from a remotely piloted aerial system (RPAS, and the derived spectral indices to assess the vegetative, productive, and berry composition spatial variability within a vineyard (Vitis vinifera L.. Multi-spectral imagery of 17 cm spatial resolution was acquired using a RPAS. Classical vegetation spectral indices and two newly defined normalised indices, NVI1 = (R802 − R531/(R802 + R531 and NVI2 = (R802 − R570/(R802 + R570, were computed. Their spatial distribution and relationships with grapevine vegetative, yield, and berry composition parameters were studied. Most of the spectral indices and field data varied spatially within the vineyard, as showed through the variogram parameters. While the correlations were significant but moderate among the spectral indices and the field variables, the kappa index showed that the spatial pattern of the spectral indices agreed with that of the vegetative variables (0.38–0.70 and mean cluster weight (0.40. These results proved the utility of the multi-spectral imagery acquired from a RPAS to delineate homogeneous zones within the vineyard, allowing the grapegrower to carry out a specific management of each subarea.

  9. Using Landsat Vegetation Indices to Estimate Impervious Surface Fractions for European Cities

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Fensholt, Rasmus; Drews, Martin

    2015-01-01

    and applicability of vegetation indices (VI), from Landsat imagery, to estimate IS fractions for European cities. The accuracy of three different measures of vegetation cover is examined for eight urban areas at different locations in Europe. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted...... Vegetation Index (SAVI) are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR), and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs ≈ 10%, MBE’s

  10. Different techniques of multispectral data analysis for vegetation fraction retrieval

    Science.gov (United States)

    Kancheva, Rumiana; Georgiev, Georgi

    2012-07-01

    Vegetation monitoring is one of the most important applications of remote sensing technologies. In respect to farmlands, the assessment of crop condition constitutes the basis of growth, development, and yield processes monitoring. Plant condition is defined by a set of biometric variables, such as density, height, biomass amount, leaf area index, and etc. The canopy cover fraction is closely related to these variables, and is state-indicative of the growth process. At the same time it is a defining factor of the soil-vegetation system spectral signatures. That is why spectral mixtures decomposition is a primary objective in remotely sensed data processing and interpretation, specifically in agricultural applications. The actual usefulness of the applied methods depends on their prediction reliability. The goal of this paper is to present and compare different techniques for quantitative endmember extraction from soil-crop patterns reflectance. These techniques include: linear spectral unmixing, two-dimensional spectra analysis, spectral ratio analysis (vegetation indices), spectral derivative analysis (red edge position), colorimetric analysis (tristimulus values sum, chromaticity coordinates and dominant wavelength). The objective is to reveal their potential, accuracy and robustness for plant fraction estimation from multispectral data. Regression relationships have been established between crop canopy cover and various spectral estimators.

  11. The red edge in arid region vegetation: 340-1060 nm spectra

    Science.gov (United States)

    Ray, Terrill W.; Murray, Bruce C.; Chehbouni, A.; Njoku, Eni

    1993-01-01

    The remote sensing study of vegetated regions of the world has typically been focused on the use of broad-band vegetation indices such as NDVI. Various modifications of these indices have been developed in attempts to minimize the effect of soil background, e.g., SAVI, or to reduce the effect of the atmosphere, e.g., ARVI. Most of these indices depend on the so-called 'red edge,' the sharp transition between the strong absorption of chlorophyll pigment in visible wavelengths and the strong scattering in the near-infrared from the cellular structure of leaves. These broadband indices tend to become highly inaccurate as the green canopy cover becomes sparse. The advent of high spectral resolution remote sensing instrument such as the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) has allowed the detection of narrow spectral features in vegetation and there are reports of detection of the red edge even for pixels with very low levels of green vegetation cover by Vane et al. and Elvidge et al., and to characterize algal biomass in coastal areas. Spectral mixing approaches similar to those of Smith et al. can be extended into the high spectral resolution domain allowing for the analysis of more endmembers, and potentially, discrimination between material with narrow spectral differences. Vegetation in arid regions tends to be sparse, often with small leaves such as the creosote bush. Many types of arid region vegetation spend much of the year with their leaves in a senescent state, i.e., yellow, with lowered chlorophyll pigmentation. The sparseness of the leaves of many arid region plants has the dual effect of lowering the green leaf area which can be observed and of allowing more of the sub-shrub soil to be visible which further complicates the spectrum of a region covered with arid region vegetation. Elvidge examined the spectral characteristics of dry plant materials showing significant differences in the region of the red edge and the diagnostic ligno

  12. Remote sensing of species diversity using Landsat 8 spectral variables

    Science.gov (United States)

    Madonsela, Sabelo; Cho, Moses Azong; Ramoelo, Abel; Mutanga, Onisimo

    2017-11-01

    The application of remote sensing in biodiversity estimation has largely relied on the Normalized Difference Vegetation Index (NDVI). The NDVI exploits spectral information from red and near infrared bands of Landsat images and it does not consider canopy background conditions hence it is affected by soil brightness which lowers its sensitivity to vegetation. As such NDVI may be insufficient in explaining tree species diversity. Meanwhile, the Landsat program also collects essential spectral information in the shortwave infrared (SWIR) region which is related to plant properties. The study was intended to: (i) explore the utility of spectral information across Landsat-8 spectrum using the Principal Component Analysis (PCA) and estimate alpha diversity (α-diversity) in the savannah woodland in southern Africa, and (ii) define the species diversity index (Shannon (H‧), Simpson (D2) and species richness (S) - defined as number of species in a community) that best relates to spectral variability on the Landsat-8 Operational Land Imager dataset. We designed 90 m × 90 m field plots (n = 71) and identified all trees with a diameter at breast height (DbH) above 10 cm. H‧, D2 and S were used to quantify tree species diversity within each plot and the corresponding spectral information on all Landsat-8 bands were extracted from each field plot. A stepwise linear regression was applied to determine the relationship between species diversity indices (H‧, D2 and S) and Principal Components (PCs), vegetation indices and Gray Level Co-occurrence Matrix (GLCM) texture layers with calibration (n = 46) and test (n = 23) datasets. The results of regression analysis showed that the Simple Ratio Index derivative had a higher relationship with H‧, D2 and S (r2= 0.36; r2= 0.41; r2= 0.24 respectively) compared to NDVI, EVI, SAVI or their derivatives. Moreover the Landsat-8 derived PCs also had a higher relationship with H‧ and D2 (r2 of 0.36 and 0.35 respectively) than the

  13. Using Landsat Vegetation Indices to Estimate Impervious Surface Fractions for European Cities

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Fensholt, Rasmus; Drews, Martin

    2015-01-01

    and applicability of vegetation indices (VI), from Landsat imagery, to estimate IS fractions for European cities. The accuracy of three different measures of vegetation cover is examined for eight urban areas at different locations in Europe. The Normalized Difference Vegetation Index (NDVI) and Soil Adjusted...... Vegetation Index (SAVI) are converted to IS fractions using a regression modelling approach. Also, NDVI is used to estimate fractional vegetation cover (FR), and consequently IS fractions. All three indices provide fairly accurate estimates (MAEs ≈ 10%, MBE’s ... the potential for developing and applying a single regression model to estimate IS fractions for numerous urban areas without reducing the accuracy considerably. Our findings indicate that the models can be applied broadly for multiple urban areas, and that the accuracy is reduced only marginally by applying...

  14. AfSIS MODIS Collection: Vegetation Indices, April 2014

    Data.gov (United States)

    Center for International Earth Science Information Network, Columbia University — The Africa Soil Information Service (AfSIS) Moderate Resolution Imaging Spectroradiometer (MODIS) Collection's Vegetation Indices data set contains rasters with the...

  15. Close relationship between spectral vegetation indices and Vcmax in deciduous and mixed forests

    Directory of Open Access Journals (Sweden)

    Yanlian Zhou

    2014-04-01

    Full Text Available Seasonal variations of photosynthetic capacity parameters, notably the maximum carboxylation rate, Vcmax, play an important role in accurate estimation of CO2 assimilation in gas-exchange models. Satellite-derived normalised difference vegetation index (NDVI, enhanced vegetation index (EVI and model-data fusion can provide means to predict seasonal variation in Vcmax. In this study, Vcmax was obtained from a process-based model inversion, based on an ensemble Kalman filter (EnKF, and gross primary productivity, and sensible and latent heat fluxes measured using eddy covariance technique at two deciduous broadleaf forest sites and a mixed forest site. Optimised Vcmax showed considerable seasonal and inter-annual variations in both mixed and deciduous forest ecosystems. There was noticeable seasonal hysteresis in Vcmax in relation to EVI and NDVI from 8 d composites of satellite data during the growing period. When the growing period was phenologically divided into two phases (increasing VIs and decreasing VIs phases, significant seasonal correlations were found between Vcmax and VIs, mostly showing R2>0.95. Vcmax varied exponentially with increasing VIs during the first phase (increasing VIs, but second and third-order polynomials provided the best fits of Vcmax to VIs in the second phase (decreasing VIs. The relationships between NDVI and EVI with Vcmax were different. Further efforts are needed to investigate Vcmax–VIs relationships at more ecosystem sites to the use of satellite-based VIs for estimating Vcmax.

  16. Assessing the Ability of Vegetation Indices to Identify Shallow Subsurface Water Flow Pathways from Hyperspectral Imagery Using Machine Learning: Methodology

    Science.gov (United States)

    Byers, J. M.; Doctor, K.

    2017-12-01

    A common application of the satellite and airborne acquired hyperspectral imagery in the visible and NIR spectrum is the assessment of vegetation. Various absorption features of plants related to both water and chlorophyll content can be used to measure the vigor and access to underlying water sources of the vegetation. The typical strategy is to form hand-crafted features from the hyperspectral data cube by selecting two wavelengths to form difference or ratio images in the pixel space. The new image attempts to provide greater contrast for some feature of the vegetation. The Normalized Difference Vegetation Index (NDVI) is a widely used example formed from the ratio of differences and sums at two different wavelengths. There are dozens of these indices that are ostensibly formed using insights about the underlying physics of the spectral absorption with claims to efficacy in representing various properties of vegetation. In the language of machine learning these vegetation indices are features that can be used as a useful data representation within an algorithm. In this work we use a powerful approach from machine learning, probabilistic graphical models (PGM), to balance the competing needs of using existing hydrological classifications of terrain while finding statistically reliable features within hyperspectral data for identifying the generative process of the data. The algorithm in its simplest form is called a Naïve Bayes (NB) classifier and can be constructed in a data-driven estimation procedure of the conditional probability distributions that form the PGM. The Naïve Bayes model assumes that all vegetation indices (VI) are independent of one another given the hydrological class label. We seek to test its validity in a pilot study of detecting subsurface water flow pathways from VI. A more sophisticated PGM will also be explored called a tree-augmented NB that accounts for the probabilistic dependence between VI features. This methodology provides a

  17. Design and Development of a Spectral Library for Different Vegetation and Landcover Types for Arctic, Antarctic and Chihuahua Desert Ecosystem

    Science.gov (United States)

    Matharasi, K.; Goswami, S.; Gamon, J.; Vargas, S.; Marin, R.; Lin, D.; Tweedie, C. E.

    2008-12-01

    All objects on the Earth's surface absorb and reflect portions of the electromagnetic spectrum. Depending on the composition of the material, every material has its characteristic spectral profile. The characteristic spectral profile for vegetation is often used to study how vegetation patterns at large spatial scales affect ecosystem structure and function. Analysis of spectroscopic data from the laboratory, and from various other platforms like aircraft or spacecraft, requires a knowledge base that consists of different characteristic spectral profiles for known different materials. This study reports on establishment of an online and searchable spectral library for a range of plant species and landcover types in the Arctic, Anatarctic and Chihuahuan desert ecosystems. Field data were collected from Arctic Alaska, the Antarctic Peninsula and the Chihuahuan desert in the visible to near infrared (IR) range using a handheld portable spectrometer. The data have been archived in a database created using postgre sql with have been made publicly available on a plone web-interface. This poster describes the data collected in more detail and offers instruction to users who wish to make use of this free online resource.

  18. Distinguishing Intensity Levels of Grassland Fertilization Using Vegetation Indices

    Directory of Open Access Journals (Sweden)

    Jens L. Hollberg

    2017-01-01

    Full Text Available Monitoring the reaction of grassland canopies on fertilizer application is of major importance to enable a well-adjusted management supporting a sustainable production of the grass crop. Up to date, grassland managers estimate the nutrient status and growth dynamics of grasslands by costly and time-consuming field surveys, which only provide low temporal and spatial data density. Grassland mapping using remotely-sensed Vegetation Indices (VIs has the potential to contribute to solving these problems. In this study, we explored the potential of VIs for distinguishing five differently-fertilized grassland communities. Therefore, we collected spectral signatures of these communities in a long-term fertilization experiment (since 1941 in Germany throughout the growing seasons 2012–2014. Fifteen VIs were calculated and their seasonal developments investigated. Welch tests revealed that the accuracy of VIs for distinguishing these grassland communities varies throughout the growing season. Thus, the selection of the most promising single VI for grassland mapping was dependent on the date of the spectra acquisition. A random forests classification using all calculated VIs reduced variations in classification accuracy within the growing season and provided a higher overall precision of classification. Thus, we recommend a careful selection of VIs for grassland mapping or the utilization of temporally-stable methods, i.e., including a set of VIs in the random forests algorithm.

  19. Global sampling of the seasonal changes in vegetation biophysical properties and associated carbon flux dynamics: using the synergy of information captured by spectral time series

    Science.gov (United States)

    Campbell, P. K. E.; Huemmrich, K. F.; Middleton, E.; Voorhis, S.; Landis, D.

    2016-12-01

    Spatial heterogeneity and seasonal dynamics in vegetation function contribute significantly to the uncertainties in regional and global CO2 budgets. High spectral resolution imaging spectroscopy ( 10 nm, 400-2500 nm) provides an efficient tool for synoptic evaluation of the factors significantly affecting the ability of the vegetation to sequester carbon and to reflect radiation, due to changes in vegetation chemical and structural composition. EO-1 Hyperion has collected more than 15 years of repeated observations for vegetation studies, and currently Hyperion time series are available for study of vegetation carbon dynamics at a number of FLUX sites. This study presents results from the analysis of EO-1 Hyperion and FLUX seasonal composites for a range of ecosystems across the globe. Spectral differences and seasonal trends were evaluated for each vegetation type and specific phenology. Evaluating the relationships between CO2 flux parameters (e.g., Net ecosystem production - NEP; Gross Ecosystem Exchange - GEE, CO2 flux, μmol m-2 s-1) and spectral parameters for these very different ecosystems, high correlations were established to parameters associated with canopy water and chlorophyll content for deciduous, and photosynthetic function for conifers. Imaging spectrometry provided high spatial resolution maps of CO2 fluxes absorbed by vegetation, and was efficient in tracing seasonal flux dynamics. This study will present examples for key ecosystem tipes to demonstrate the ability of imaging spectrometry and EO-1 Hyperion to map and compare CO2 flux dynamics across the globe.

  20. The spectral invariant approximation within canopy radiative transfer to support the use of the EPIC/DSCOVR oxygen B-band for monitoring vegetation

    International Nuclear Information System (INIS)

    Marshak, Alexander; Knyazikhin, Yuri

    2017-01-01

    EPIC (Earth Polychromatic Imaging Camera) is a 10-channel spectroradiometer onboard DSCOVR (Deep Space Climate Observatory) spacecraft. In addition to the near-infrared (NIR, 780 nm) and the ‘red’ (680 nm) channels, EPIC also has the O2 A-band (764±0.2 nm) and B-band (687.75±0.2 nm). The EPIC Normalized Difference Vegetation Index (NDVI) is defined as the difference between NIR and ‘red’ channels normalized to their sum. However, the use of the O2 B-band instead of the ‘red’ channel mitigates the effect of atmosphere on remote sensing of surface reflectance because O2 reduces contribution from the radiation scattered by the atmosphere. Applying the radiative transfer theory and the spectral invariant approximation to EPIC observations, the paper provides supportive arguments for using the O2 band instead of the red channel for monitoring vegetation dynamics. Our results suggest that the use of the O2 B-band enhances the sensitivity of the top-of-atmosphere NDVI to the presence of vegetation. - Highlights: • The use of the O2 B-band channel (688 nm) instead of the red channel (680 nm) mitigates the effect of atmosphere on remote sensing of surface reflectance. • The spectral invariant approach confirms that the synergy of the green, O2 B-band and near IR channels mimics spectral properties of vegetation. • The structural parameter of vegetation retrieved remotely is weakly sensitive to the uncertainty in the atmospheric optical depth.

  1. Scaling of vegetation indices for environmental change studies

    International Nuclear Information System (INIS)

    Qi, J.; Huete, A.; Sorooshian, S.; Chehbouni, A.; Kerr, Y.

    1992-01-01

    The spatial integration of physical parameters in remote sensing studies is of critical concern when evaluating the global biophysical processes on the earth's surface. When high resolution physical parameters, such as vegetation indices, are degraded for integration into global scale studies, they differ from lower spatial resolution data due to spatial variability and the method by which these parameters are integrated. In this study, multi-spatial resolution data sets of SPOT and ground based data obtained at Walnut Gulch Experimental Watershed in southern Arizona, US during MONSOON '90 were used. These data sets were examined to study the variations of the vegetation index parameters when integrated into coarser resolutions. Different integration methods (conventional mean and Geostatistical mean) were used in simulations of high-to-low resolutions. The sensitivity of the integrated parameters were found to vary with both the spatial variability of the area and the integration methods. Modeled equations describing the scale-dependency of the vegetation index are suggested

  2. High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision and hobbyist unmanned aerial vehicles

    Science.gov (United States)

    Dandois, J. P.; Ellis, E. C.

    2013-12-01

    High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing system enabling routine and inexpensive aerial 3D measurements of canopy structure and spectral attributes, with properties similar to those of LIDAR, but with RGB (red-green-blue) spectral attributes for each point, enabling high frequency observations within a single growing season. This 'Ecosynth' methodology applies photogrammetric ''Structure from Motion'' computer vision algorithms to large sets of highly overlapping low altitude (USA. Ecosynth canopy height maps (CHMs) were strong predictors of field-measured tree heights (R2 0.63 to 0.84) and were highly correlated with a LIDAR CHM (R 0.87) acquired 4 days earlier, though Ecosynth-based estimates of aboveground biomass densities included significant errors (31 - 36% of field-based estimates). Repeated scanning of a 0.25 ha forested area at six different times across a 16 month period revealed ecologically significant dynamics in canopy color at different heights and a structural shift upward in canopy density, as demonstrated by changes in vertical height profiles of point density and relative RGB brightness. Changes in canopy relative greenness were highly correlated (R2 = 0.88) with MODIS NDVI time series for the same area and vertical differences in canopy color revealed the early green up of the dominant canopy species, Liriodendron tulipifera, strong evidence that Ecosynth time series measurements capture vegetation structural and spectral dynamics at the spatial scale of individual trees. Observing canopy phenology in 3D at high temporal resolutions represents a breakthrough in forest ecology. Inexpensive user-deployed technologies for

  3. Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

    Science.gov (United States)

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for

  4. Derivation of the canopy conductance from surface temperature and spectral indices for estimating evapotranspiration in semiarid vegetation; Monitorizacion de conductancia en vegetacion semiarida a partir de indices espectrales y temperatura de supeficie

    Energy Technology Data Exchange (ETDEWEB)

    Morillas, L.; Garcia, M.; Zarco-Tejada, P.; Ladron de Guevara, M.; Villagarcia, L.; Were, A.; Domingo, F.

    2009-07-01

    This work evaluates the possibilities for estimating stomata conductance (C) and leaf transpiration (Trf) at the ecosystem scale from radiometric indices and surface temperature. The relationships found between indices and the transpiration component of the water balance in a semiarid tussock ecosystem in SE Spain are discussed. Field data were collected from spring 2008 until winter 2009 in order to observe the annual variability of the relationships and the behaviour of spectral indices and surface temperature. (Author) 11 refs.

  5. Advances in estimation methods of vegetation water content based on optical remote sensing techniques

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

  6. Estimating Pasture Quality of Fresh Vegetation Based on Spectral Slope of Mixed Data of Dry and Fresh Vegetation—Method Development

    Directory of Open Access Journals (Sweden)

    Rachel Lugassi

    2015-06-01

    Full Text Available The main objective of the present study was to apply a slope-based spectral method to both dry and fresh pasture vegetation. Differences in eight spectral ranges were identified across the near infrared-shortwave infrared (NIR-SWIR that were indicative of changes in chemical properties. Slopes across these ranges were calculated and a partial least squares (PLS analytical model was constructed for the slopes vs. crude protein (CP and neutral detergent fiber (NDF contents. Different datasets with different numbers of fresh/dry samples were constructed to predict CP and NDF contents. When using a mixed-sample dataset with dry-to-fresh ratios of 85%:15% and 75%:25%, the correlations of CP (R2 = 0.95, in both and NDF (R2 = 0.84 and 0.82, respectively were almost as high as when using only dry samples (0.97 and 0.85, respectively. Furthermore, satisfactory correlations were obtained with a dry-to-fresh ratio of 50%:50% for CP (R2 = 0.92. The results of our study are especially encouraging because CP and NDF contents could be predicted even though some of the selected spectral regions were directly affected by atmospheric water vapor or water in the plants.

  7. Assessing the Ability of Vegetation Indices to Identify Shallow Subsurface Water Flow Pathways from Hyperspectral Imagery Using Machine Learning: Application

    Science.gov (United States)

    Doctor, K.; Byers, J. M.

    2017-12-01

    Shallow underground water flow pathways expressed as slight depressions are common in the land surface. Under conditions of saturated overland flow, such as during heavy rain or snow melt, these areas of preferential flow might appear on the surface as very shallow flowing streams. When there is no water flowing in these ephemeral channels it can be difficult to identify them. It is especially difficult to discern the slight depressions above the subsurface water flow pathways (SWFP) when the area is covered by vegetation. Since the soil moisture content in these SWFP is often greater than the surrounding area, the vegetation growing on top of these channels shows different vigor and moisture content than the vegetation growing above the non-SWFP area. Vegetation indices (VI) are used in visible and near infrared (VNIR) hyperspectral imagery to enhance biophysical properties of vegetation, and so the brightness values between vegetation atop SWFP and the surrounding vegetation were highlighted. We performed supervised machine learning using ground-truth class labels to determine the conditional probability of a SWFP at a given pixel given either the spectral distribution or VI at that pixel. The training data estimates the probability distributions to a determined finite sampling accuracy for a binary Naïve Bayes classifier between SWFP and non-SWFP. The ground-truth data provides a test bed for understanding the ability to build SWFP classifiers using hyperspectral imagery. SWFP were distinguishable in the imagery within corn and grass fields and in areas with low-lying vegetation. However, the training data is limited to particular types of terrain and vegetation cover in the Shenandoah Valley, Virginia and this would limit the resulting classifier. Further training data could extend its use to other environments.

  8. Spectral identification of plant communities for mapping of semi-natural grasslands

    DEFF Research Database (Denmark)

    Jacobsen, Anne; Nielsen, Allan Aasbjerg; Ejrnæs, Rasmus

    2000-01-01

    identification of plant communities was based on a hierarchical approach relating the test sites to i) management (Ma) and ii) flora (Fl) using spectral consistency and separability as the main criteria. Evaluation of spectral consistency was based on unsupervised clustering of test sites of Ma classes 1 to 7...... as a measure of plant community heterogeneity within management classes. The spectral analysis as well as the maximum likelihood classification indicated that the source of spectral variation within management classes might be related to vegetation composition....

  9. Studying Vegetation Salinity: From the Field View to a Satellite-Based Perspective

    Directory of Open Access Journals (Sweden)

    Rachel Lugassi

    2017-02-01

    Full Text Available Salinization of irrigated lands in the semi-arid Jezreel Valley, Northern Israel results in soil-structure deterioration and crop damage. We formulated a generic rule for estimating salinity of different vegetation types by studying the relationship between Cl/Na and different spectral slopes in the visible–near infrared–shortwave infrared (VIS–NIR–SWIR spectral range using both field measurements and satellite imagery (Sentinel-2. For the field study, the slope-based model was integrated with conventional partial least squares (PLS analyses. Differences in 14 spectral ranges, indicating changes in salinity levels, were identified across the VIS–NIR–SWIR region (350–2500 nm. Next, two different models were run using PLS regression: (i using spectral slope data across these ranges; and (ii using preprocessed spectral reflectance. The best model for predicting Cl content was based on continuum removal reflectance (R2 = 0.84. Satisfactory correlations were obtained using the slope-based PLS model (R2 = 0.77 for Cl and R2 = 0.63 for Na. Thus, salinity contents in fresh plants could be estimated, despite masking of some spectral regions by water absorbance. Finally, we estimated the most sensitive spectral channels for monitoring vegetation salinity from a satellite perspective. We evaluated the recently available Sentinel-2 imagery’s ability to distinguish variability in vegetation salinity levels. The best estimate of a Sentinel-2-based vegetation salinity index was generated based on a ratio between calculated slopes: the 490–665 nm and 705–1610 nm. This index was denoted as the Sentinel-2-based vegetation salinity index (SVSI (band 4 − band 2/(band 5 + band 11.

  10. Global patterns of NDVI-indicated vegetation extremes and their sensitivity to climate extremes

    International Nuclear Information System (INIS)

    Liu Guo; Liu Hongyan; Yin Yi

    2013-01-01

    Extremes in climate have significant impacts on ecosystems and are expected to increase under future climate change. Extremes in vegetation could capture such impacts and indicate the vulnerability of ecosystems, but currently have not received a global long-term assessment. In this study, a robust method has been developed to detect significant extremes (low values) in biweekly time series of global normalized difference vegetation index (NDVI) from 1982 to 2006 and thus to acquire a global pattern of vegetation extreme frequency. This pattern coincides with vegetation vulnerability patterns suggested by earlier studies using different methods over different time spans, indicating a consistent mechanism of regulation. Vegetation extremes were found to aggregate in Amazonia and in the semi-arid and semi-humid regions in low and middle latitudes, while they seldom occurred in high latitudes. Among the environmental variables studied, extreme low precipitation has the highest slope against extreme vegetation. For the eight biomes analyzed, these slopes are highest in temperate broadleaf forest and temperate grassland, suggesting a higher sensitivity in these environments. The results presented here contradict the hypothesis that vegetation in water-limited semi-arid and semi-humid regions might be adapted to drought and suggest that vegetation in these regions (especially temperate broadleaf forest and temperate grassland) is highly prone to vegetation extreme events under more severe precipitation extremes. It is also suggested here that more attention be paid to precipitation-induced vegetation changes than to temperature-induced events. (letter)

  11. Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development.

    Science.gov (United States)

    Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N

    2012-06-01

    Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

  12. A comparison of multi-resource remote sensing data for vegetation indices

    International Nuclear Information System (INIS)

    Cao, Liqin; Wei, Lifei; Liu, Tingting

    2014-01-01

    With the development of the satellite sensor, multi-resource observation systems have become widely used. However, there is a huge difference between quantitative remote sensing products because of the different sensing observations and the quantitative retrieval algorithms. In this paper, the quantitative relationships between the normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) and the vegetation index based on the universal pattern decomposition method (VIUPD) of Landsat ETM+ and ASTER sensors are investigated. The difference in observations was examined between the two sensors, based on a pair of images. The results showed that: 1) There was a strong correlation between the different vegetation indices for the same sensor, with the coefficient of determination being greater than 0.9. 2) Whether for ASTER or Landsat, the information of VIUPD was richer than that of NDVI and SAVI. Furthermore, in dense vegetation areas, the values of NDVI and SAVI could easily reach saturation. 3) The values of SAVI were higher than NDVI in the areas of water or bare soil, while this was the opposite in areas of lush vegetation

  13. Phenological characteristics of the main vegetation types on the Tibetan Plateau based on vegetation and water indices

    International Nuclear Information System (INIS)

    Peng, D L; Huang, W J; Zhou, B; Li, C J; Wu, Y P; Yang, X H

    2014-01-01

    Plant phenology is considered one of the most sensitive and easily observable natural indicators of climate change, though few studies have focused on the heterogeneities of phenology across the different vegetation types. In this study, we tried to find the phenological characteristics of the main vegetation types on the Tibetan Plateau. MCD12Q1 images over the Tibetan Plateau from 2001 to 2010 were used to extract the main vegetation types. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) were calculated using surface reflectance values from the blue, red, near-infrared, short-wave infrared (SWIR) 6 (for LSIW6), and SWIR7 (for LSIW7) bands derived from MOD09A1 and used to explore the phenological characteristics of the main vegetation types on the Tibetan Plateau. The results showed that there were eight constant vegetation types on the Tibetan Plateau from 2001 to 2010 demonstrating multiple phenological characteristics. Evergreen needleleaf forest, evergreen broadleaf forest, and permanent wetland had the minimum NDVI values during the summer season, while open shrubland and grassland had the maximum NDVI/EVI values during this period. NDVI and EVI of cropland/natural vegetation had two peaks for their seasonal variations. EVI showed a more significant correlation with LSWI6/LSWI7 than NDVI. Compared to LSWI7, larger EVI values occurred in evergreen needleleaf forest, evergreen broadleaf forest, mixed forest, and permanent wetland, while smaller values occurred in shrubland and barren or sparsely vegetated cover, and nearly equal values occurred in grassland and cropland

  14. Indicator microorganisms in fresh vegetables from “farm to fork” in Rwanda

    NARCIS (Netherlands)

    Ssemanda, James Noah; Reij, Martine; Muvunyi, Claude Mambo; Joosten, Han; Zwietering, Marcel H.

    2017-01-01

    Microbial safety of ready-to-eat vegetables is currently a global concern. We studied indicator microorganisms in fresh vegetables from “farm to fork” in Rwanda, to identify possible trends in microbial counts along the supply chain in a developing country. A total of 453 samples were taken across

  15. Effect of vegetation on rock and soil type discrimination

    Science.gov (United States)

    Siegal, B. S.; Goetz, A. F. H.

    1977-01-01

    The effect of naturally occurring vegetation on the spectral reflectance of earth materials in the wavelength region of 0.45 to 2.4 microns is determined by computer averaging of in situ acquired spectral data. The amount and type of vegetation and the spectral reflectance of the ground are considered. Low albedo materials may be altered beyond recognition with only ten per cent green vegetation cover. Dead or dry vegetation does not greatly alter the shape of the spectral reflectance curve and only changes the albedo with minimum wavelength dependency. With increasing amounts of vegetation the Landsat MSS band ratios 4/6, 4/7, 5/6, and 5/7 are significantly decreased whereas MSS ratios 4/5 and 6/7 remain entirely constant.

  16. Scaling dimensions in spectroscopy of soil and vegetation

    Science.gov (United States)

    Malenovský, Zbyněk; Bartholomeus, Harm M.; Acerbi-Junior, Fausto W.; Schopfer, Jürg T.; Painter, Thomas H.; Epema, Gerrit F.; Bregt, Arnold K.

    2007-05-01

    The paper revises and clarifies definitions of the term scale and scaling conversions for imaging spectroscopy of soil and vegetation. We demonstrate a new four-dimensional scale concept that includes not only spatial but also the spectral, directional and temporal components. Three scaling remote sensing techniques are reviewed: (1) radiative transfer, (2) spectral (un)mixing, and (3) data fusion. Relevant case studies are given in the context of their up- and/or down-scaling abilities over the soil/vegetation surfaces and a multi-source approach is proposed for their integration. Radiative transfer (RT) models are described to show their capacity for spatial, spectral up-scaling, and directional down-scaling within a heterogeneous environment. Spectral information and spectral derivatives, like vegetation indices (e.g. TCARI/OSAVI), can be scaled and even tested by their means. Radiative transfer of an experimental Norway spruce ( Picea abies (L.) Karst.) research plot in the Czech Republic was simulated by the Discrete Anisotropic Radiative Transfer (DART) model to prove relevance of the correct object optical properties scaled up to image data at two different spatial resolutions. Interconnection of the successive modelling levels in vegetation is shown. A future development in measurement and simulation of the leaf directional spectral properties is discussed. We describe linear and/or non-linear spectral mixing techniques and unmixing methods that demonstrate spatial down-scaling. Relevance of proper selection or acquisition of the spectral endmembers using spectral libraries, field measurements, and pure pixels of the hyperspectral image is highlighted. An extensive list of advanced unmixing techniques, a particular example of unmixing a reflective optics system imaging spectrometer (ROSIS) image from Spain, and examples of other mixture applications give insight into the present status of scaling capabilities. Simultaneous spatial and temporal down

  17. MODIS/Terra Vegetation Indices Monthly L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  18. MODIS/Terra Vegetation Indices Monthly L3 Global 0.05Deg CMG V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  19. MODIS/Aqua Vegetation Indices Monthly L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  20. Reflectance spectral analyses for the assessment of environmental pollution in the geothermal site of Mt. Amiata (Italy)

    Science.gov (United States)

    Manzo, Ciro; Salvini, Riccardo; Guastaldi, Enrico; Nicolardi, Valentina; Protano, Giuseppe

    2013-11-01

    We studied the environmental impact of geothermal activities in the Mt. Amiata area, using on-site spectral analyses of various ecological components. Analytical techniques were based on the study of the “red-edge”, which represents the spectral feature of the reflectance spectra defined between red and infrared wavelengths (λ) within the range 670-780 nm. Since in the study area the geothermal exploitation causes the drifting of contaminants such as Hg, Sb, S, B, As and H2S (hydrogen sulfide) from power plants, the spectral response of vegetation and lichens depends on their distance from the power stations, and also on the exposed surface, material type and other physical parameters. In the present research, the spectral radiance of targets was measured in the field using an Analytical Spectral Device (ASD) Field-Spec™FR portable radiometer. Spectral measurements were made on vegetation and lichen samples located near to and far from geothermal areas and potential pollution sources (e.g., power plants), with the aim of spatially defining their environmental impact. Observations for vegetation and lichens showed correlation with laboratory chemical analyses when these organisms were under stress conditions. The evaluation of relationships was carried out using several statistical approaches, which allowed to identify methods for identifying contamination indicators for plants and lichens in polluted areas. Results show that the adopted spectral indices are sensitive to environmental pollution and their responses spatialstatically correlated to chemical and ecophysiological analyses within a notable distance.

  1. ANALYSIS OF CAMOUFLAGE COVER SPECTRAL CHARACTERISTICS BY IMAGING SPECTROMETER

    Directory of Open Access Journals (Sweden)

    A. Y. Kouznetsov

    2016-03-01

    Full Text Available Subject of Research.The paper deals with the problems of detection and identification of objects in hyperspectral imagery. The possibility of object type determination by statistical methods is demonstrated. The possibility of spectral image application for its data type identification is considered. Method. Researching was done by means of videospectral equipment for objects detection at "Fregat" substrate. The postprocessing of hyperspectral information was done with the use of math model of pattern recognition system. The vegetation indexes TCHVI (Three-Channel Vegetation Index and NDVI (Normalized Difference Vegetation Index were applied for quality control of object recognition. Neumann-Pearson criterion was offered as a tool for determination of objects differences. Main Results. We have carried out analysis of the spectral characteristics of summer-typecamouflage cover (Germany. We have calculated the density distribution of vegetation indexes. We have obtained statistical characteristics needed for creation of mathematical model for pattern recognition system. We have shown the applicability of vegetation indices for detection of summer camouflage cover on averdure background. We have presented mathematical model of object recognition based on Neumann-Pearson criterion. Practical Relevance. The results may be useful for specialists in the field of hyperspectral data processing for surface state monitoring.

  2. Non-stationarities significantly distort short-term spectral, symbolic and entropy heart rate variability indices

    International Nuclear Information System (INIS)

    Magagnin, Valentina; Bassani, Tito; Bari, Vlasta; Turiel, Maurizio; Porta, Alberto; Maestri, Roberto; Pinna, Gian Domenico

    2011-01-01

    The autonomic regulation is non-invasively estimated from heart rate variability (HRV). Many methods utilized to assess autonomic regulation require stationarity of HRV recordings. However, non-stationarities are frequently present even during well-controlled experiments, thus potentially biasing HRV indices. The aim of our study is to quantify the potential bias of spectral, symbolic and entropy HRV indices due to non-stationarities. We analyzed HRV series recorded in healthy subjects during uncontrolled daily life activities typical of 24 h Holter recordings and during predetermined levels of robotic-assisted treadmill-based physical exercise. A stationarity test checking the stability of the mean and variance over short HRV series (about 300 cardiac beats) was utilized to distinguish stationary periods from non-stationary ones. Spectral, symbolic and entropy indices evaluated solely over stationary periods were contrasted with those derived from all the HRV segments. When indices were calculated solely over stationary series, we found that (i) during both uncontrolled daily life activities and controlled physical exercise, the entropy-based complexity indices were significantly larger; (ii) during uncontrolled daily life activities, the spectral and symbolic indices linked to sympathetic modulation were significantly smaller and those associated with vagal modulation were significantly larger; (iii) while during uncontrolled daily life activities, the variance of spectral, symbolic and entropy rate indices was significantly larger, during controlled physical exercise, it was smaller. The study suggests that non-stationarities increase the likelihood to overestimate the contribution of sympathetic control and affect the power of statistical tests utilized to discriminate conditions and/or groups

  3. The spectral changes of deforestation in the Brazilian tropical savanna.

    Science.gov (United States)

    Trancoso, Ralph; Sano, Edson E; Meneses, Paulo R

    2015-01-01

    The Cerrado is a biome in Brazil that is experiencing the most rapid loss in natural vegetation. The objective of this study was to analyze the changes in the spectral response in the red, near infrared (NIR), middle infrared (MIR), and normalized difference vegetation index (NDVI) when native vegetation in the Cerrado is deforested. The test sites were regions of the Cerrado located in the states of Bahia, Minas Gerais, and Mato Grosso. For each region, a pair of Landsat Thematic Mapper (TM) scenes from 2008 (before deforestation) and 2009 (after deforestation) was compared. A set of 1,380 samples of deforested polygons and an equal number of samples of native vegetation have their spectral properties statistically analyzed. The accuracy of deforestation detections was also evaluated using high spatial resolution imagery. Results showed that the spectral data of deforested areas and their corresponding native vegetation were statistically different. The red band showed the highest difference between the reflectance data from deforested areas and native vegetation, while the NIR band showed the lowest difference. A consistent pattern of spectral change when native vegetation in the Cerrado is deforested was identified regardless of the location in the biome. The overall accuracy of deforestation detections was 97.75%. Considering both the marked pattern of spectral changes and the high deforestation detection accuracy, this study suggests that deforestation in Cerrado can be accurately monitored, but a strong seasonal and spatial variability of spectral changes might be expected.

  4. Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest

    Directory of Open Access Journals (Sweden)

    Zhihui Wang

    2016-06-01

    Full Text Available Hyperspectral remote sensing serves as an effective tool for estimating foliar nitrogen using a variety of techniques. Vegetation indices (VIs are a simple means of retrieving foliar nitrogen. Despite their popularity, few studies have been conducted to examine the utility of VIs for mapping canopy foliar nitrogen in a mixed forest context. In this study, we assessed the performance of 32 vegetation indices derived from HySpex airborne hyperspectral images for estimating canopy mass-based foliar nitrogen concentration (%N in the Bavarian Forest National Park. The partial least squares regression (PLSR was performed for comparison. These vegetation indices were classified into three categories that are mostly correlated to nitrogen, chlorophyll, and structural properties such as leaf area index (LAI. %N was destructively measured in 26 broadleaf, needle leaf, and mixed stand plots to represent the different species and canopy structure. The canopy foliar %N is defined as the plot-level mean foliar %N of all species weighted by species canopy foliar mass fraction. Our results showed that the variance of canopy foliar %N is mainly explained by functional type and species composition. The normalized difference nitrogen index (NDNI produced the most accurate estimation of %N (R2CV = 0.79, RMSECV = 0.26. A comparable estimation of %N was obtained by the chlorophyll index Boochs2 (R2CV = 0.76, RMSECV = 0.27. In addition, the mean NIR reflectance (800–850 nm, representing canopy structural properties, also achieved a good accuracy in %N estimation (R2CV = 0.73, RMSECV = 0.30. The PLSR model provided a less accurate estimation of %N (R2CV = 0.69, RMSECV = 0.32. We argue that the good performance of all three categories of vegetation indices in %N estimation can be attributed to the synergy among plant traits (i.e., canopy structure, leaf chemical and optical properties while these traits may converge across plant species for evolutionary reasons. Our

  5. MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  6. MODIS/Aqua Vegetation Indices 16-Day L3 Global 1km SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  7. MODIS/Terra Vegetation Indices 16-Day L3 Global 500m SIN Grid V005

    Data.gov (United States)

    National Aeronautics and Space Administration — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  8. Pattern Decomposition Method and a New Vegetation Index for Hyper-Multispectral Satellite Data Analysis

    Science.gov (United States)

    Muramatsu, K.; Furumi, S.; Hayashi, A.; Shiono, Y.; Ono, A.; Fujiwara, N.; Daigo, M.; Ochiai, F.

    We have developed the ``pattern decomposition method'' based on linear spectral mixing of ground objects for n-dimensional satellite data. In this method, spectral response patterns for each pixel in an image are decomposed into three components using three standard spectral shape patterns determined from the image data. Applying this method to AMSS (Airborne Multi-Spectral Scanner) data, eighteen-dimensional data are successfully transformed into three-dimensional data. Using the three components, we have developed a new vegetation index in which all the multispectral data are reflected. We consider that the index should be linear to the amount of vegetation and vegetation vigor. To validate the index, its relations to vegetation types, vegetation cover ratio, and chlorophyll contents of a leaf were studied using spectral reflectance data measured in the field with a spectrometer. The index was sensitive to vegetation types and vegetation vigor. This method and index are very useful for assessment of vegetation vigor, classifying land cover types and monitoring vegetation changes

  9. Effective Spectral Indices of Core and Extended Emissions for Radio ...

    Indian Academy of Sciences (India)

    Effective Spectral Indices of Core and Extended Emissions for Radio Sources. R. S. Yang1,∗, J. H. Yang1,2 & J. J. Nie1. 1Department of Physics and Electronics Science, Hunan University of Arts and Science,. Changde 415000, China. 2Centre for Astrophysics, Guangzhou University, Guangzhou 510006, China. ∗ e-mail: ...

  10. [Progress in inversion of vegetation nitrogen concentration by hyperspectral remote sensing].

    Science.gov (United States)

    Wang, Li-Wen; Wei, Ya-Xing

    2013-10-01

    Nitrogen is the necessary element in life activity of vegetation, which takes important function in biosynthesis of protein, nucleic acid, chlorophyll, and enzyme etc, and plays a key role in vegetation photosynthesis. The technology about inversion of vegetation nitrogen concentration by hyperspectral remote sensing has been the research hotspot since the 70s of last century. With the development of hyperspectral remote sensing technology in recent years, the advantage of spectral bands subdivision in a certain spectral region provides the powerful technology measure for correlative spectral characteristic research on vegetation nitrogen. In the present paper, combined with the newest research production about monitoring vegetation nitrogen concentration by hyperspectral remote sensing published in main geography science literature in recent several years, the principle and correlated problem about monitoring vegetation nitrogen concentration by hyperspectral remote sensing were introduced. From four aspects including vegetation nitrogen spectral index, vegetation nitrogen content inversion based on chlorophyll index, regression model, and eliminating influence factors to inversion of vegetation nitrogen concentration, main technology methods about inversion of vegetation nitrogen concentration by hyperspectral remote sensing were detailedly introduced. Correlative research conclusions were summarized and analyzed, and research development trend was discussed.

  11. Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape

    Directory of Open Access Journals (Sweden)

    Stephen G. Nelson

    2008-03-01

    Full Text Available Vegetation indices (VIs are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT, Surface Energy Balance (SEB, and Global Climate Models (GCM. These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with "Big Leaf" SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes.

  12. Relationship Between Remotely-sensed Vegetation Indices, Canopy Attributes and Plant Physiological Processes: What Vegetation Indices Can and Cannot Tell Us About the Landscape

    Science.gov (United States)

    Glenn, Edward P.; Huete, Alfredo R.; Nagler, Pamela L.; Nelson, Stephen G.

    2008-01-01

    Vegetation indices (VIs) are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT), Surface Energy Balance (SEB), and Global Climate Models (GCM). These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with “Big Leaf” SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes. PMID:27879814

  13. Quantitative indicators of fruit and vegetable consumption

    Directory of Open Access Journals (Sweden)

    Dagmar Kozelová

    2015-12-01

    Full Text Available The quantitative research of the market is often based on surveys and questionnaires which are finding out the behavior of customers in observed areas. Before purchasing process consumers consider where they will buy fruit and vegetables, what kind to choose and in what quantity of goods. Consumers' behavior is affected by the factors as: regional gastronomic traditions, price, product appearance, aroma, place of buying, own experience and knowledge, taste preferences as well as specific health issues of consumers and others. The consumption of fruit and vegetables brings into the human body biological active substances that favorably affect the health of consumers. In the presented research study we were interested in differences of consumers' behavior in the consumption of fruit and vegetables according to the place of residence and gender. In the survey 200 respondents has participated; their place of residence was city or village. The existence of dependences and statistical significance were examined by selected statistical testing methods. Firstly we analyzed the responses via statistical F-test whether observed random samples have the same variance. Then we applied two-sample unpaired t-test with equal variance and χ2-test of statistical independence. The statistical significance was tested by corresponding p values. Correlations were proved by the Cramer's V coefficient. We found that place of residence has no impact on the respondents' consumption of fruit. The gender of respondents does not affect their consumption of fruit. Equally, the gender does not affect the respondents' consumption of vegetables. Only in one observed case the significant differences proved that the place of respondent residence has impact on the consumption of vegetables. Higher consumption of vegetables is due to the fact that the majority of citizens, who live in villages, have a possibility to grow their own vegetables and, thus, the demand for it in village

  14. Vegetation indicators of transformation in the urban forest ecosystems of "Kuzminki-Lyublino" Park

    Science.gov (United States)

    Buyvolova, Anna; Trifonova, Tatiana; Bykova, Elena

    2017-04-01

    Forest ecosystems in the city are at the same time a component of its natural environment and part of urban developmental planning. It imposes upon urban forests a large functional load, both environmental (formation of environment, air purification, noise pollution reducing, etc.) and social (recreational, educational) which defines the special attitude to their management and study. It is not a simple task to preserve maximum accessibility to the forest ecosystems of the large metropolises with a minimum of change. The urban forest vegetates in naturally formed soil, it has all the elements of a morphological structure (canopy layers), represented by natural species of the zonal vegetation. Sometimes it is impossible for a specialist to distinguish between an urban forest and a rural one. However, the urban forests are changing, being under the threat of various negative influences of the city, of which pollution is arguably the most significant. This article presents some indicators of structural changes to the plant communities, which is a response of forest ecosystems to an anthropogenic impact. It is shown that the indicators of the transformation of natural ecosystems in the city can be a reduction of the projective cover of moss layer, until its complete absence (in the pine forest), increasing the role of Acer negundo (adventive species) in the undergrowth, high variability of floristic indicators of the ground herbaceous vegetation, and a change in the spatial arrangement of adventive species. The assessment of the impact of the urban environment on the state of vegetation in the "Kuzminki-Lyublino" Natural-Historical Park was conducted in two key areas least affected by anthropogenic impacts under different plant communities represented by complex pine and birch forests and in similar forest types in the Prioksko-Terrasny Biosphere Reserve. The selection of pine forests as a model is due to the fact that, according to some scientists, pine (Pinus

  15. Distinguishing Intensity Levels of Grassland Fertilization Using Vegetation Indices

    OpenAIRE

    Jens L. Hollberg; Jürgen Schellberg

    2017-01-01

    Monitoring the reaction of grassland canopies on fertilizer application is of major importance to enable a well-adjusted management supporting a sustainable production of the grass crop. Up to date, grassland managers estimate the nutrient status and growth dynamics of grasslands by costly and time-consuming field surveys, which only provide low temporal and spatial data density. Grassland mapping using remotely-sensed Vegetation Indices (VIs) has the potential to contribute to solving these ...

  16. Spectral indices of cardiovascular adaptations to short-term simulated microgravity exposure

    Science.gov (United States)

    Patwardhan, A. R.; Evans, J. M.; Berk, M.; Grande, K. J.; Charles, J. B.; Knapp, C. F.

    1995-01-01

    We investigated the effects of exposure to microgravity on the baseline autonomic balance in cardiovascular regulation using spectral analysis of cardiovascular variables measured during supine rest. Heart rate, arterial pressure, radial flow, thoracic fluid impedance and central venous pressure were recorded from nine volunteers before and after simulated microgravity, produced by 20 hours of 6 degrees head down bedrest plus furosemide. Spectral powers increased after simulated microgravity in the low frequency region (centered at about 0.03 Hz) in arterial pressure, heart rate and radial flow, and decreased in the respiratory frequency region (centered at about 0.25 Hz) in heart rate. Reduced heart rate power in the respiratory frequency region indicates reduced parasympathetic influence on the heart. A concurrent increase in the low frequency power in arterial pressure, heart rate, and radial flow indicates increased sympathetic influence. These results suggest that the baseline autonomic balance in cardiovascular regulation is shifted towards increased sympathetic and decreased parasympathetic influence after exposure to short-term simulated microgravity.

  17. Vegetation species composition and canopy architecture information expressed in leaf water absorption measured in the 1000 nm and 2200 spectral region by an imaging spectrometer

    Science.gov (United States)

    Green, Robert O.; Roberts, Dar A.

    1995-01-01

    Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring, and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local to regional and even synoptic scales. Classical approaches rely on vegetation indices such as the normalized difference vegetation index (NDVI) to estimate biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine-scale information about specific sites to larger areas of similar composition. Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and that may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some of this capability has been demonstrated through improved discrimination of vegetation, estimates of canopy biochemistry, and liquid water estimates from vegetation. We investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from two spectral regions, the 1000-nm region and the 2200-nm region. The study was conducted in the vicinity of Jasper Ridge, California, which is located on the San Francisco peninsula to the west of the Stanford University campus. AVIRIS data were acquired over Jasper Ridge, CA, on June 2, 1992, at 19:31 UTC. Spectra from three sites in this image were analyzed. These data are from an area of healthy grass, oak woodland, and redwood forest, respectively. For these analyses, the AVIRIS-measured upwelling radiance spectra for the entire Jasper

  18. Predicting soil nitrogen content using narrow-band indices from ...

    African Journals Online (AJOL)

    Optimal fertiliser applications for sustainable forest stand productivity management, whilst protecting the environment, is vital. This study estimated soil nitrogen content using leaf-level narrow-band vegetation indices derived from a hand-held 350–2 500 nm spectroradiometer. Leaf-level spectral data were collected and ...

  19. Association of water spectral indices with plant and soil water relations in contrasting wheat genotypes.

    Science.gov (United States)

    Gutierrez, Mario; Reynolds, Matthew P; Klatt, Arthur R

    2010-07-01

    Spectral reflectance indices can be used to estimate the water status of plants in a rapid, non-destructive manner. Water spectral indices were measured on wheat under a range of water-deficit conditions in field-based yield trials to establish their relationship with water relations parameters as well as available volumetric soil water (AVSW) to indicate soil water extraction patterns. Three types of wheat germplasm were studied which showed a range of drought adaptation; near-isomorphic sister lines from an elite/elite cross, advanced breeding lines, and lines derived from interspecific hybridization with wild relatives (synthetic derivative lines). Five water spectral indices (one water index and four normalized water indices) based on near infrared wavelengths were determined under field conditions between the booting and grain-filling stages of crop development. Among all water spectral indices, one in particular, which was denominated as NWI-3, showed the most consistent associations with water relations parameters and demonstrated the strongest associations in all three germplasm sets. NWI-3 showed a strong linear relationship (r(2) >0.6-0.8) with leaf water potential (psi(leaf)) across a broad range of values (-2.0 to -4.0 MPa) that were determined by natural variation in the environment associated with intra- and inter-seasonal affects. Association observed between NWI-3 and canopy temperature (CT) was consistent with the idea that genotypes with a better hydration status have a larger water flux (increased stomatal conductance) during the day. NWI-3 was also related to soil water potential (psi(soil)) and AVSW, indicating that drought-adapted lines could extract more water from deeper soil profiles to maintain favourable water relations. NWI-3 was sufficiently sensitive to detect genotypic differences (indicated by phenotypic and genetic correlations) in water status at the canopy and soil levels indicating its potential application in precision

  20. Comparison of Reflectance Measurements Acquired with a Contact Probe and an Integration Sphere: Implications for the Spectral Properties of Vegetation at a Leaf Level

    Directory of Open Access Journals (Sweden)

    Markéta Potůčková

    2016-10-01

    Full Text Available Laboratory spectroscopy in visible and infrared regions is an important tool for studies dealing with plant ecophysiology and early recognition of plant stress due to changing environmental conditions. Leaf optical properties are typically acquired with a spectroradiometer coupled with an integration sphere (IS in a laboratory or with a contact probe (CP, which has the advantage of operating flexibility and the provision of repetitive in-situ reflectance measurements. Experiments comparing reflectance spectra measured with different devices and device settings are rarely reported in literature. Thus, in our study we focused on a comparison of spectra collected with two ISs on identical samples ranging from a Spectralon and coloured papers as reference standards to vegetation samples with broadleaved (Nicotiana Rustica L. and coniferous (Picea abies L. Karst. leaf types. First, statistical measures such as mean absolute difference, median of differences, standard deviation and paired-sample t-test were applied in order to evaluate differences between collected reflectance values. The possibility of linear transformation between spectra was also tested. Moreover, correlation between normalised differential indexes (NDI derived for each device and all combinations of wavelengths between 450 nm and 1800 nm were assessed. Finally, relationships between laboratory measured leaf compounds (total chlorophyll, carotenoids and water content, NDI and selected spectral indices often used in remote sensing were studied. The results showed differences between spectra acquired with different devices. While differences were negligible in the case of the Spectralon and they were possible to be modelled with a linear transformation in the case of coloured papers, the spectra collected with the CP and the ISs differed significantly in the case of vegetation samples. Regarding the spectral indices calculated from the reflectance data collected with the three

  1. Ground Field-Based Hyperspectral Imaging: A Preliminary Study to Assess the Potential of Established Vegetation Indices to Infer Variation in Water-Use Efficiency.

    Science.gov (United States)

    Pelech, E. A.; McGrath, J.; Pederson, T.; Bernacchi, C.

    2017-12-01

    Increases in the global average temperature will consequently induce a higher occurrence of severe environmental conditions such as drought on arable land. To mitigate these threats, crops for fuel and food must be bred for higher water-use efficiencies (WUE). Defining genomic variation through high-throughput phenotypic analysis in field conditions has the potential to relieve the major bottleneck in linking desirable genetic traits to the associated phenotypic response. This can subsequently enable breeders to create new agricultural germplasm that supports the need for higher water-use efficient crops. From satellites to field-based aerial and ground sensors, the reflectance properties of vegetation measured by hyperspectral imaging is becoming a rapid high-throughput phenotyping technique. A variety of physiological traits can be inferred by regression analysis with leaf reflectance which is controlled by the properties and abundance of water, carbon, nitrogen and pigments. Although, given that the current established vegetation indices are designed to accentuate these properties from spectral reflectance, it becomes a challenge to infer relative measurements of WUE at a crop canopy scale without ground-truth data collection. This study aims to correlate established biomass and canopy-water-content indices with ground-truth data. Five bioenergy sorghum genotypes (Sorghum bicolor L. Moench) that have differences in WUE and wild-type Tobacco (Nicotiana tabacum var. Samsun) under irrigated and rainfed field conditions were examined. A linear regression analysis was conducted to determine if variation in canopy water content and biomass, driven by natural genotypic and artificial treatment influences, can be inferred using established vegetation indices. The results from this study will elucidate the ability of ground field-based hyperspectral imaging to assess variation in water content, biomass and water-use efficiency. This can lead to improved opportunities to

  2. Spectrometric analyses in comparison to the physiological condition of heavy metal stressed floodplain vegetation in a standardised experiment

    Science.gov (United States)

    Götze, Christian; Jung, András; Merbach, Ines; Wennrich, Rainer; Gläßer, Cornelia

    2010-06-01

    Floodplain ecosystems are affected by flood dynamics, nutrient supply as well as anthropogenic activities. Heavy metal pollution poses a serious environmental challenge. Pollution transfer from the soil to vegetation is still present at the central location of Elbe River, Germany. The goal of this study was to assess and separate the current heavy metal contamination of the floodplain ecosystem, using spectrometric field and laboratory measurements. A standardized pot experiment with floodplain vegetation in differently contaminated soils provided the basis for the measurements. The dominant plant types of the floodplains are: Urtica dioica, Phalaris arundinacea and Alopecurus pratensis, these were also chemically analysed. Various vegetation indices and methods were used to estimate the red edge position, to normalise the spectral curve of the vegetation and to investigate the potential of different methods for separating plant stress in floodplain vegetation. The main task was to compare spectral bands during phenological phases to find a method to detect heavy metal stress in plants. A multi-level algorithm for the curve parameterisation was developed. Chemo-analytical and ecophysiological parameters of plants were considered in the results and correlated with spectral data. The results of this study show the influence of heavy metals on the spectral characteristics of the focal plants. The developed method (depth CR1730) showed significant relationship between the plants and the contamination.

  3. Vegetation index analysis of multi-source remote sensing data in coal mine wasteland

    Energy Technology Data Exchange (ETDEWEB)

    Han, Y.X.; Li, M.Z.; Li, D.L. [China Agricultural University, Beijing (China)

    2007-12-15

    Thirty-six soil samples were collected and their hyperspectral data used to calculate vegetation indices such as a normalised difference vegetation index (NDVI) and a difference vegetation index (DVI). These were evaluated for typical surface object features within the wastelands around Haizhou Opencast Coal Mine in Fuxin city. A principal component analysis to the hyperspectral data was performed, and the result showed that the first and the second principal components satisfactorily accounted for the multi-spectral image information. The panchromatic and multi-spectral images of SPOT5 were then merged. The panchromatic image replaced the first principal component to improve spatial resolution of the image. In addition, the multispectral images and the NDVI image were classified into six types using the unsupervised classification method. The linear quantitative models were built up and the highest correlation coefficients were obtained between the hyperspectral vegetation index and the vegetation index data from the SPOT5 image. The results show that the hyperspectral data and remote sensing images can be used for quantitative estimation of soil nutrients in coal mine wasteland. They can also provide large area surface information for fast and effective decision making regarding revegetation and the monitoring of dynamic change.

  4. The NASA earth resources spectral information system: A data compilation, second supplement

    Science.gov (United States)

    Vincent, R. K.

    1973-01-01

    The NASA Earth Resources Spectral Information System (ERSIS) and the information contained therein are described. It is intended for use as a second supplement to the NASA Earth Resources Spectral Information System: A Data Compilation, NASA CR-31650-24-T, May 1971. The current supplement includes approximately 100 rock and mineral, and 375 vegetation directional reflectance spectral curves in the optical region from 0.2 to 22.0 microns. The data were categorized by subject and each curve plotted on a single graph. Each graph is fully titled to indicate curve source and indexed by subject to facilitate user retrieval from ERSIS magnetic tape records.

  5. Development of a high spectral resolution surface albedo product for the ARM Southern Great Plains Central Facility

    Energy Technology Data Exchange (ETDEWEB)

    McFarlane, Sally A.; Gaustad, Krista L.; Mlawer, Eli J.; Long, Charles N.; Delamere, Jennifer

    2011-09-01

    We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

  6. Development of a high spectral resolution surface albedo product for the ARM Southern Great Plains central facility

    Science.gov (United States)

    McFarlane, S. A.; Gaustad, K. L.; Mlawer, E. J.; Long, C. N.; Delamere, J.

    2011-09-01

    We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM) facility at the Southern Great Plains (SGP) site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs), four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated) can be identified. A normalized difference vegetation index (NDVI) is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs) and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

  7. Development of a high spectral resolution surface albedo product for the ARM Southern Great Plains central facility

    Directory of Open Access Journals (Sweden)

    J. Delamere

    2011-09-01

    Full Text Available We present a method for identifying dominant surface type and estimating high spectral resolution surface albedo at the Atmospheric Radiation Measurement (ARM facility at the Southern Great Plains (SGP site in Oklahoma for use in radiative transfer calculations. Given a set of 6-channel narrowband visible and near-infrared irradiance measurements from upward and downward looking multi-filter radiometers (MFRs, four different surface types (snow-covered, green vegetation, partial vegetation, non-vegetated can be identified. A normalized difference vegetation index (NDVI is used to distinguish between vegetated and non-vegetated surfaces, and a scaled NDVI index is used to estimate the percentage of green vegetation in partially vegetated surfaces. Based on libraries of spectral albedo measurements, a piecewise continuous function is developed to estimate the high spectral resolution surface albedo for each surface type given the MFR albedo values as input. For partially vegetated surfaces, the albedo is estimated as a linear combination of the green vegetation and non-vegetated surface albedo values. The estimated albedo values are evaluated through comparison to high spectral resolution albedo measurements taken during several Intensive Observational Periods (IOPs and through comparison of the integrated spectral albedo values to observed broadband albedo measurements. The estimated spectral albedo values agree well with observations for the visible wavelengths constrained by the MFR measurements, but have larger biases and variability at longer wavelengths. Additional MFR channels at 1100 nm and/or 1600 nm would help constrain the high resolution spectral albedo in the near infrared region.

  8. Deforestation and benthic indicators: how much vegetation cover is needed to sustain healthy Andean streams?

    Science.gov (United States)

    Iñiguez-Armijos, Carlos; Leiva, Adrián; Frede, Hans-Georg; Hampel, Henrietta; Breuer, Lutz

    2014-01-01

    Deforestation in the tropical Andes is affecting ecological conditions of streams, and determination of how much forest should be retained is a pressing task for conservation, restoration and management strategies. We calculated and analyzed eight benthic metrics (structural, compositional and water quality indices) and a physical-chemical composite index with gradients of vegetation cover to assess the effects of deforestation on macroinvertebrate communities and water quality of 23 streams in southern Ecuadorian Andes. Using a geographical information system (GIS), we quantified vegetation cover at three spatial scales: the entire catchment, the riparian buffer of 30 m width extending the entire stream length, and the local scale defined for a stream reach of 100 m in length and similar buffer width. Macroinvertebrate and water quality metrics had the strongest relationships with vegetation cover at catchment and riparian scales, while vegetation cover did not show any association with the macroinvertebrate metrics at local scale. At catchment scale, the water quality metrics indicate that ecological condition of Andean streams is good when vegetation cover is over 70%. Further, macroinvertebrate community assemblages were more diverse and related in catchments largely covered by native vegetation (>70%). Our results suggest that retaining an important quantity of native vegetation cover within the catchments and a linkage between headwater and riparian forests help to maintain and improve stream biodiversity and water quality in Andean streams affected by deforestation. This research proposes that a strong regulation focused to the management of riparian buffers can be successful when decision making is addressed to conservation/restoration of Andean catchments.

  9. ARM Climate Research Facility Spectral Surface Albedo Value-Added Product (VAP) Report

    Energy Technology Data Exchange (ETDEWEB)

    McFarlane, S; Gaustad, K; Long, C; Mlawer, E

    2011-07-15

    This document describes the input requirements, output data products, and methodology for the Spectral Surface Albedo (SURFSPECALB) value-added product (VAP). The SURFSPECALB VAP produces a best-estimate near-continuous high spectral resolution albedo data product using measurements from multifilter radiometers (MFRs). The VAP first identifies best estimates for the MFR downwelling and upwelling shortwave irradiance values, and then calculates narrowband spectral albedo from these best-estimate irradiance values. The methodology for finding the best-estimate values is based on a simple process of screening suspect data and backfilling screened and missing data with estimated values when possible. The resulting best-estimate MFR narrowband spectral albedos are used to determine a daily surface type (snow, 100% vegetation, partial vegetation, or 0% vegetation). For non-snow surfaces, a piecewise continuous function is used to estimate a high spectral resolution albedo at 1 min temporal and 10 cm-1 spectral resolution.

  10. Distinguishing plant population and variety with UAV-derived vegetation indices

    Science.gov (United States)

    Oakes, Joseph; Balota, Maria

    2017-05-01

    Variety selection and seeding rate are two important choice that a peanut grower must make. High yielding varieties can increase profit with no additional input costs, while seeding rate often determines input cost a grower will incur from seed costs. The overall purpose of this study was to examine the effect that seeding rate has on different peanut varieties. With the advent of new UAV technology, we now have the possibility to use indices collected with the UAV to measure emergence, seeding rate, growth rate, and perhaps make yield predictions. This information could enable growers to make management decisions early in the season based on low plant populations due to poor emergence, and could be a useful tool for growers to use to estimate plant population and growth rate in order to help achieve desired crop stands. Red-Green-Blue (RGB) and near-infrared (NIR) images were collected from a UAV platform starting two weeks after planting and continued weekly for the next six weeks. Ground NDVI was also collected each time aerial images were collected. Vegetation indices were derived from both the RGB and NIR images. Greener area (GGA- the proportion of green pixels with a hue angle from 80° to 120°) and a* (the average red/green color of the image) were derived from the RGB images while Normalized Differential Vegetative Index (NDVI) was derived from NIR images. Aerial indices were successful in distinguishing seeding rates and determining emergence during the first few weeks after planting, but not later in the season. Meanwhile, these aerial indices are not an adequate predictor of yield in peanut at this point.

  11. Enabling Searches on Wavelengths in a Hyperspectral Indices Database

    Science.gov (United States)

    Piñuela, F.; Cerra, D.; Müller, R.

    2017-10-01

    Spectral indices derived from hyperspectral reflectance measurements are powerful tools to estimate physical parameters in a non-destructive and precise way for several fields of applications, among others vegetation health analysis, coastal and deep water constituents, geology, and atmosphere composition. In the last years, several micro-hyperspectral sensors have appeared, with both full-frame and push-broom acquisition technologies, while in the near future several hyperspectral spaceborne missions are planned to be launched. This is fostering the use of hyperspectral data in basic and applied research causing a large number of spectral indices to be defined and used in various applications. Ad hoc search engines are therefore needed to retrieve the most appropriate indices for a given application. In traditional systems, query input parameters are limited to alphanumeric strings, while characteristics such as spectral range/ bandwidth are not used in any existing search engine. Such information would be relevant, as it enables an inverse type of search: given the spectral capabilities of a given sensor or a specific spectral band, find all indices which can be derived from it. This paper describes a tool which enables a search as described above, by using the central wavelength or spectral range used by a given index as a search parameter. This offers the ability to manage numeric wavelength ranges in order to select indices which work at best in a given set of wavelengths or wavelength ranges.

  12. Examination of Spectral Transformations on Spectral Mixture Analysis

    Science.gov (United States)

    Deng, Y.; Wu, C.

    2018-04-01

    While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes' spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs' difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.

  13. Very High Spectral Resolution Imaging Spectroscopy: the Fluorescence Explorer (FLEX) Mission

    Science.gov (United States)

    Moreno, Jose F.; Goulas, Yves; Huth, Andreas; Middleton, Elizabeth; Miglietta, Franco; Mohammed, Gina; Nedbal, Ladislav; Rascher, Uwe; Verhoef, Wouter; Drusch, Matthias

    2016-01-01

    The Fluorescence Explorer (FLEX) mission has been recently selected as the 8th Earth Explorer by the European Space Agency (ESA). It will be the first mission specifically designed to measure from space vegetation fluorescence emission, by making use of very high spectral resolution imaging spectroscopy techniques. Vegetation fluorescence is the best proxy to actual vegetation photosynthesis which can be measurable from space, allowing an improved quantification of vegetation carbon assimilation and vegetation stress conditions, thus having key relevance for global mapping of ecosystems dynamics and aspects related with agricultural production and food security. The FLEX mission carries the FLORIS spectrometer, with a spectral resolution in the range of 0.3 nm, and is designed to fly in tandem with Copernicus Sentinel-3, in order to provide all the necessary spectral / angular information to disentangle emitted fluorescence from reflected radiance, and to allow proper interpretation of the observed fluorescence spatial and temporal dynamics.

  14. Using multi-spectral sensors for vegetation mapping

    CSIR Research Space (South Africa)

    Van Deventer, Heidi

    2016-07-01

    Full Text Available Wetland and estuarine vegetation is often difficult to detect and separate from adjacent land covers with multispectral sensors for a number of reasons. The spatial resolution of space-borne sensors is often insufficient for these features which...

  15. SPECTRAL COLOR INDICES BASED GEOSPATIAL MODELING OF SOIL ORGANIC MATTER IN CHITWAN DISTRICT, NEPAL

    Directory of Open Access Journals (Sweden)

    U. K. Mandal

    2016-06-01

    Full Text Available Space Technology provides a resourceful-cost effective means to assess soil nutrients essential for soil management plan. Soil organic matter (SOM is one of valuable controlling productivity of crops by providing nutrient in farming systems. Geospatial modeling of soil organic matter is essential if there is unavailability of soil test laboratories and its strong spatial correlation. In the present analysis, soil organic matter is modeled from satellite image derived spectral color indices. Brightness Index (BI, Coloration Index (CI, Hue Index (HI, Redness Index (RI and Saturation Index (SI were calculated by converting DN value to radiance and radiance to reflectance from Thematic Mapper image. Geospatial model was developed by regressing SOM with color indices and producing multiple regression model using stepwise regression technique. The multiple regression equation between SOM and spectral indices was significant with R = 0. 56 at 95% confidence level. The resulting MLR equation was then used for the spatial prediction for the entire study area. Redness Index was found higher significance in estimating the SOM. It was used to predict SOM as auxiliary variables using cokringing spatial interpolation technique. It was tested in seven VDCs of Chitwan district of Nepal using Thematic Mapper remotely sensed data. SOM was found to be measured ranging from 0.15% to 4.75 %, with a mean of 2.24 %. Remotely sensed data derived spectral color indices have the potential as useful auxiliary variables for estimating SOM content to generate soil fertility management plans.

  16. Selection of vegetation indices for mapping the sugarcane condition around the oil and gas field of North West Java Basin, Indonesia

    Science.gov (United States)

    Muji Susantoro, Tri; Wikantika, Ketut; Saepuloh, Asep; Handoyo Harsolumakso, Agus

    2018-05-01

    Selection of vegetation indices in plant mapping is needed to provide the best information of plant conditions. The methods used in this research are the standard deviation and the linear regression. This research tried to determine the vegetation indices used for mapping the sugarcane conditions around oil and gas fields. The data used in this study is Landsat 8 OLI/TIRS. The standard deviation analysis on the 23 vegetation indices with 27 samples has resulted in the six highest standard deviations of vegetation indices, termed as GRVI, SR, NLI, SIPI, GEMI and LAI. The standard deviation values are 0.47; 0.43; 0.30; 0.17; 0.16 and 0.13. Regression correlation analysis on the 23 vegetation indices with 280 samples has resulted in the six vegetation indices, termed as NDVI, ENDVI, GDVI, VARI, LAI and SIPI. This was performed based on regression correlation with the lowest value R2 than 0,8. The combined analysis of the standard deviation and the regression correlation has obtained the five vegetation indices, termed as NDVI, ENDVI, GDVI, LAI and SIPI. The results of the analysis of both methods show that a combination of two methods needs to be done to produce a good analysis of sugarcane conditions. It has been clarified through field surveys and showed good results for the prediction of microseepages.

  17. Temporal profiles of vegetation indices for characterizing grazing intensity on natural grasslands in Pampa biome

    Directory of Open Access Journals (Sweden)

    Amanda Heemann Junges

    2016-08-01

    Full Text Available ABSTRACT The Pampa biome is an important ecosystem in Brazil that is highly relevant to livestock production. The objective of this study was to analyze the potential use of vegetation indices to discriminate grazing intensities on natural grasslands in the Pampa biome. Moderate Resolution Imaging Spectroradiometer (MODIS Normalized Difference Vegetation Index (NDVI and Enhanced Vegetation Index (EVI images from Jan to Dec, 2000 to 2013 series, were analyzed for natural grassland experimental units managed under high (forage allowance of 5 ± 2 % live weight – LW, moderate (13 ± 5 % LW and low grazing intensity (19 ± 7 % LW. Regardless of intensity, the temporal profiles showed lower NDVI and EVI during winter, increased values in spring because of summer species regrowth, slightly decreased values in summer, especially in years when there is a water deficit, and increased values in the fall associated with the beginning of winter forage development. The average temporal profiles of moderate grazing intensity exhibited greater vegetation index values compared with low and high grazing intensities. The temporal profiles of less vegetation index were associated with lower green biomass accumulation caused by the negative impact of stocking rates on the leaf area index under high grazing intensity and a floristic composition with a predominance of tussocks under low grazing intensity. Vegetation indices can be used for distinguishing moderate grazing intensity from low and high intensities. The average EVI values can discriminate moderate grazing intensity during any season, and the NDVI values can discriminate moderate grazing intensity during spring and winter.

  18. The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass

    NARCIS (Netherlands)

    Basuki, T.M.; Skidmore, A.K.; Laake, van P.E.; Duren, van I.C.; Hussin, Y.A.

    2012-01-01

    A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models

  19. Hyper-spectral frequency selection for the classification of vegetation diseases

    OpenAIRE

    Dijkstra, Klaas; van de Loosdrecht, Jaap; Schomaker, Lambert; Wiering, Marco

    2017-01-01

    Reducing the use of pesticides by early visual detection of diseases in precision agriculture is important. Because of the color similarity between potato-plant diseases, narrow band hyper-spectral imaging is required. Payload constraints on unmanned aerial vehicles require reduc- tion of spectral bands. Therefore, we present a methodology for per-patch classification combined with hyper-spectral band selection. In controlled experiments performed on a set of individual leaves, we measure the...

  20. Spectral variables, growth analysis and yield of sugarcane; Variaveis espectrais e indicadores de desenvolvimento e produtividade da cana-de-acucar

    Energy Technology Data Exchange (ETDEWEB)

    Simoes, Mauricio dos Santos [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Agricola. Programa de Pos-graduacao em Engenharia Agricola; Rocha, Jansle Vieira [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Agricola. Dept. de Planejamento e Desenvolvimento Rural Sustentavel; Lamparelli, Rubens Augusto Camargo [Universidade Estadual de Campinas, SP (Brazil). Centro de Pesquisas Meteorologicas e Climaticas Aplicadas a Agricultura (CEPAGRI)]. E-mail: rubens@cpa.unicamp.br

    2005-06-01

    Spectral information is well related with agronomic variables and can be used in crop monitoring and yield forecasting. This paper describes a multi temporal research with the sugarcane variety SP 80-1842, studying its spectral behavior using field spectroscopy and its relationship with agronomic parameters such as leaf area index (LAI), number of stalks per meter (NPM), yield (TSS) and total biomass (BMT). A commercial sugarcane field in Araras/SP/Brazil was monitored for two seasons. Radiometric data and agronomic characterization were gathered in 9 field campaigns. Spectral vegetation indices had similar patterns in both seasons and adjusted to agronomic parameters. Band 4 (B4), Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), and Soil Adjusted Vegetation Index (SAVI) increased their values until the end of the vegetative stage, around 240 days after harvest (DAC). After that stage, B4 reflectance and NDVI values began to stabilize and decrease because the crop reached ripening and senescence stages. Band 3 (B3) and RVI presented decreased values since the beginning of the cycle, followed by a stabilization stage. Later these values had a slight increase caused by the lower amount of green vegetation. Spectral variables B3, RVI, NDVI, and SAVI were highly correlated (above 0.79) with LAI, TSS, and BMT, and about 0.50 with NPM. The best regression models were verified for RVI, LAI, and NPM, which explained 0.97 of TSS variation and 0.99 of BMT variation. (author)

  1. Hyperspectral image classifier based on beach spectral feature

    International Nuclear Information System (INIS)

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-01-01

    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

  2. Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 1; Theory

    Science.gov (United States)

    Ganguly, Sangram; Schull, Mitchell A.; Samanta, Arindam; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramakrishna R.; Knyazikhin, Yuri; Myneni, Ranga B.

    2008-01-01

    The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher

  3. New developments of a knowledge based system (VEG) for inferring vegetation characteristics

    Science.gov (United States)

    Kimes, D. S.; Harrison, P. A.; Harrison, P. R.

    1992-01-01

    An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

  4. Improved crop residue cover estimates by coupling spectral indices for residue and moisture

    Science.gov (United States)

    Remote sensing assessment of soil residue cover (fR) and tillage intensity will improve our predictions of the impact of agricultural practices and promote sustainable management. Spectral indices for estimating fR are sensitive to soil and residue water content, therefore, the uncertainty of estima...

  5. Network based early warning indicators of vegetation changes in a land–atmosphere model

    NARCIS (Netherlands)

    Yin, Z.; Dekker, S.C.; Rietkerk, M.; Hurk, B.J.J.M. van den; Dijkstra, H.A.

    2016-01-01

    Abstract Numerous model studies demonstrate that ecosystems might not shift smoothly with a gradual change in resource concentration. At specific points, vegetation can suddenly shift from one stable state to another. To predict such undesirable shifts, statistical indicators are proposed for early

  6. Nonlinear spectral mixing theory to model multispectral signatures

    Energy Technology Data Exchange (ETDEWEB)

    Borel, C.C. [Los Alamos National Lab., NM (United States). Astrophysics and Radiation Measurements Group

    1996-02-01

    Nonlinear spectral mixing occurs due to multiple reflections and transmissions between discrete surfaces, e.g. leaves or facets of a rough surface. The radiosity method is an energy conserving computational method used in thermal engineering and it models nonlinear spectral mixing realistically and accurately. In contrast to the radiative transfer method the radiosity method takes into account the discreteness of the scattering surfaces (e.g. exact location, orientation and shape) such as leaves and includes mutual shading between them. An analytic radiosity-based scattering model for vegetation was developed and used to compute vegetation indices for various configurations. The leaf reflectance and transmittance was modeled using the PROSPECT model for various amounts of water, chlorophyll and variable leaf structure. The soil background was modeled using SOILSPEC with a linear mixture of reflectances of sand, clay and peat. A neural network and a geometry based retrieval scheme were used to retrieve leaf area index and chlorophyll concentration for dense canopies. Only simulated canopy reflectances in the 6 visible through short wave IR Landsat TM channels were used. The authors used an empirical function to compute the signal-to-noise ratio of a retrieved quantity.

  7. Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

    Science.gov (United States)

    Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

    2018-06-01

    An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

  8. Red-Edge Spectral Reflectance as an Indicator of Surface Moisture Content in an Alaskan Peatland Ecosystem

    Science.gov (United States)

    McPartland, M.; Kane, E. S.; Turetsky, M. R.; Douglass, T.; Falkowski, M. J.; Montgomery, R.; Edwards, J.

    2015-12-01

    Arctic and boreal peatlands serve as major reservoirs of terrestrial organic carbon (C) because Net Primary Productivity (NPP) outstrips C loss from decomposition over long periods of time. Peatland productivity varies as a function of water table position and surface moisture content, making C storage in these systems particularly vulnerable to the climate warming and drying predicted for high latitudes. Detailed spatial knowledge of how aboveground vegetation communities respond to changes in hydrology would allow for ecosystem response to environmental change to be measured at the landscape scale. This study leverages remotely sensed data along with field measurements taken at the Alaska Peatland Experiment (APEX) at the Bonanza Creek Long Term Ecological Research site to examine relationships between plant solar reflectance and surface moisture. APEX is a decade-long experiment investigating the effects of hydrologic change on peatland ecosystems using water table manipulation treatments (raised, lowered, and control). Water table levels were manipulated throughout the 2015 growing season, resulting in a maximum separation of 35 cm between raised and lowered treatment plots. Water table position, soil moisture content, depth to seasonal ice, soil temperature, photosynthetically active radiation (PAR), CO2 and CH4 fluxes were measured as predictors of C loss through decomposition and NPP. Vegetation was surveyed for percent cover of plant functional types. Remote sensing data was collected during peak growing season, when the separation between treatment plots was at maximum difference. Imagery was acquired via a SenseFly eBee airborne platform equipped with a Canon S110 red-edge camera capable of detecting spectral reflectance from plant tissue at 715 nm band center to within centimeters of spatial resolution. Here, we investigate empirical relationships between spectral reflectance, water table position, and surface moisture in relation to peat carbon balance.

  9. Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development

    Directory of Open Access Journals (Sweden)

    Fábio M. Breunig

    2012-06-01

    Full Text Available Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS. In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI1640 and NDWI2120 with the soybean development in two growing seasons (2004-2005 and 2005-2006. To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.Efeitos direcionais introduzem variabilidade na reflectância e na determinação de índices de vegetação, especialmente quando sensores de amplo campo de visada são usados (p.ex., Moderate Resolution Imaging Spectroradiometer - MODIS. Neste estudo, nós avaliamos os efeitos direcionais sobre a reflectância e quatro índices de vegetação (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized

  10. Multiseasonal-multispectral remote sensing of phenological change for natural vegetation inventory. Ph.D. Thesis

    Science.gov (United States)

    Schrumpf, B. J. (Principal Investigator)

    1975-01-01

    The author has identified the following significant results. Variations in phenological development among plant species was noted, as well as the tendency for the seasonal appearance of some vegetation types to be dominated by the appearance of one or a few similarly developing species. Most of the common plants in the study area could be characterized by temporal aspects of their phenological development. There was a strong similarity among the spectral signatures of vegetation types in which the spectral return was dominated by green plant material. When the soil background dominated the spectral return from a vegetation stand, then the spectral radiance and the vegetation physiognomy were apparently related. When the deciduous shrubs lost their leaves, their spectral signature altered with a slight decrease of radiance in the visible wavelengths and a strong decrease in the near infrared. As the foliage of perennial grasses cured from August to November, its apparent green radiance remained unchanged, red radiance increased over 50 percent, and near infrared radiance decreased approximately 30 percent. A reflective mineral surface exhibited high radiance levels in all four bands, thus providing a marked contrast to the absorption characteristics of vegetation canopies.

  11. Applying aerial digital photography as a spectral remote sensing technique for macrophytic cover assessment in small rural streams

    Science.gov (United States)

    Anker, Y.; Hershkovitz, Y.; Gasith, A.; Ben-Dor, E.

    2011-12-01

    Although remote sensing of fluvial ecosystems is well developed, the tradeoff between spectral and spatial resolutions prevents its application in small streams (habitat scales classifications, acquisition of aerial digital RGB datasets. B. For section scale classification, hyperspectral (HSR) dataset acquisition. C. For calibration, HSR reflectance measurements of specific ground targets, in close proximity to each dataset acquisition swath. D. For habitat scale classification, manual, in-stream flora grid transects classification. The digital RGB datasets were converted to reflectance units by spectral calibration against colored reference plates. These red, green, blue, white, and black EVA foam reference plates were measured by an ASD field spectrometer and each was given a spectral value. Each spectral value was later applied to the spectral calibration and radiometric correction of spectral RGB (SRGB) cube. Spectral calibration of the HSR dataset was done using the empirical line method, based on reference values of progressive grey scale targets. Differentiation between the vegetation species was done by supervised classification both for the HSR and for the SRGB datasets. This procedure was done using the Spectral Angle Mapper function with the spectral pattern of each vegetation species as a spectral end member. Comparison between the two remote sensing techniques and between the SRGB classification and the in-situ transects indicates that: A. Stream vegetation classification resolution is about 4 cm by the SRGB method compared to about 1 m by HSR. Moreover, this resolution is also higher than of the manual grid transect classification. B. The SRGB method is by far the most cost-efficient. The combination of spectral information (rather than the cognitive color) and high spatial resolution of aerial photography provides noise filtration and better sub-water detection capabilities than the HSR technique. C. Only the SRGB method applies for habitat and

  12. Alpine plant distribution and thermic vegetation indicator on Gloria summits in the central Greater Caucasus

    International Nuclear Information System (INIS)

    Gigauri, K.; Abdaladze, O.; Nakhutsrishvili, G

    2016-01-01

    The distribution of plant species within alpine areas is often directly related to climate or climate-influenced ecological factors. Responding to observed changes in plant species, cover and composition on the GLORIA summits in the Central Caucasus, an extensive setup of 1m * 1m permanent plots was established at the treeline-alpine zones and nival ecotone (between 2240 and 3024 m a.s.l.) on the main watershed range of the Central Greater Caucasus nearby the Cross Pass, Kazbegi region, Georgia. Recording was repeated in a representative selection of 64 quadrates in 2008. The local climatic factors - average soil T degree C and growing degree days (GDD) did not show significant increasing trends. For detection of climate warming we used two indices: thermic vegetation indicator S and thermophilization indicator D. They were varying along altitudinal and exposition gradients. The thermic vegetation indicator decrease in all monitoring summits. The abundance rank of the dominant and endemic species did not change during monitoring period. (author)

  13. Evaluation and cross-comparison of vegetation indices for crop monitoring from sentinel-2 and worldview-2 images

    Science.gov (United States)

    Psomiadis, Emmanouil; Dercas, Nicholas; Dalezios, Nicolas R.; Spyropoulos, Nikolaos V.

    2017-10-01

    Farmers throughout the world are constantly searching for ways to maximize their returns. Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop vigor problems. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. However, due to the various sensor characteristics, there are differences among VIs derived from multiple sensors for the same target. Therefore, multi-sensor VI capability and effectiveness are critical but complicated issues in the application of multi-sensor vegetation observations. Various factors such as the atmospheric conditions during acquisition, sensor and geometric characteristics, such as viewing angle, field of view, and sun elevation influence direct comparability of vegetation indicators among different sensors. In the present study, two experimental areas were used which are located near the villages Nea Lefki and Melia of Larissa Prefecture in Thessaly Plain area, containing a wheat and a cotton crop, respectively. Two satellite systems with different spatial resolution, WorldView-2 (W2) and Sentinel-2 (S2) with 2 and 10 meters pixel size, were used. Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI) were calculated and a statistical comparison of the VIs was made to designate their correlation and dependency. Finally, several other innovative indices were calculated and compared to evaluate their effectiveness in the detection of problematic plant growth areas.

  14. Primary studies of trace quantities of green vegetation in Mono Lake area using 1990 AVIRIS data

    Science.gov (United States)

    Chen, Zhi-Kang; Elvidge, Chris D.; Groeneveld, David P.

    1992-01-01

    Our primary results in Jasper Ridge Biological Preserve indicate that high spectral resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data may provide a substantial advantage in vegetation, based on the chlorophyll red edge feature from 700-780 nm. The chlorophyll red edge was detected for green vegetation cover as low as 4.8 percent. The objective of our studies in Mono Lake area is to continue the experiments performed in Jasper Ridge and to examine the persistence of red edge feature of trace quantities of green vegetation for different plant communities with non-uniform soil backgrounds.

  15. A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon

    Science.gov (United States)

    Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio

    2009-01-01

    Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716

  16. A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon.

    Science.gov (United States)

    Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E; Moran, Emilio

    2008-01-01

    Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin.

  17. Classification and mapping of rangeland vegetation physiognomic ...

    African Journals Online (AJOL)

    Plot vegetation species growth form, cover and height data were collected from 450 sampling sites based on eight spectral strata generated using unsupervised image classification. Field data were grouped at four levels of seven, six, three and two vegetation physiognomic classes which were subjected to both ML and ...

  18. Spectral Textile Detection in the VNIR/SWIR Band

    Science.gov (United States)

    2015-03-01

    which have spectral similarities to background vegetation , are generally more difficult to detect than animal fibers such as wool and artificial fibers...effectiveness at long ranges, and spectral dismount detection currently relies on detecting skin pixels. In scenarios where skin is not exposed, spectral...training set. Classifiers with optimized parameters are used to classify contact data with artificially added noise and remotely-sensed hyperspectral data

  19. Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

    Science.gov (United States)

    AlShamsi, Meera R.

    2016-10-01

    Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

  20. Spectral types, color indices, and abundances for Cepheids in the Magellanic Clouds and the Galaxy

    International Nuclear Information System (INIS)

    Laney, C.D.

    1982-01-01

    Accurate MK spectral types have been obtained for 58 Cepheids in the Galaxy and the Magellanic Clouds form 121 spectrograms. Simultaneous uvbyβ photometry has been obtained with many of the spectrograms. The spectra of galactic and LMC Cepheids are found to be very similar, and Cepheids in both systems appear to obey the same (B-V) 0 vs. spectral type relation. The low E(B-V) values of Feltz and McNamara (1980) and certain other recent authors are confirmed. The spectra of SMC Cepheids show slightly weaker metal lines, and SMC Cepheids average about 1.3 subclasses earlier in spectral type than LMC and galactic Cepheids at the same value of (B-V) 0 . Spectral types of LMC and SMC Cepheids at minimum light are found to be later than those reported by Feast (1974) when luminosity effects are allowed for. Curves of growth have been constructed for 7 SMC Cepheids, 5 LMC Cepheids, and 13 Milky Way Cepheids and spectral standards. Comparison indicates that [Fe/H]/sub LMC/ = -0.06 +/- 0.10 and [Fe/H]/sub SMC/ = -0.50 +/- 0.08

  1. Lead on vegetation as indicator of air pollution due to automobile exhaust's gases

    Energy Technology Data Exchange (ETDEWEB)

    Impens, R; Deroanne-Bauvin, J; Tilman, J

    1974-01-01

    Lead is regarded as an undesirable air contaminant. It's effects on health are well documented. Lead levels in air are very high in cities. Analyses have been performed on soils and urban vegetation (trees, shrubs and plants growing in city parks or near urban highways) from fifteen sites in Brussels. The collections were made from 72 to actually, at each site. The sites gave a very wide range of traffic density. A very significant correlation of lead concentration with density and characteristics of urban traffic was found. A continuous survey of lead levels on vegetation is a good indicator of air pollution caused by automobile exhaust's gases in urban and suburban areas.

  2. Texture classification of vegetation cover in high altitude wetlands zone

    International Nuclear Information System (INIS)

    Wentao, Zou; Bingfang, Wu; Hongbo, Ju; Hua, Liu

    2014-01-01

    The aim of this study was to investigate the utility of datasets composed of texture measures and other features for the classification of vegetation cover, specifically wetlands. QUEST decision tree classifier was applied to a SPOT-5 image sub-scene covering the typical wetlands area in Three River Sources region in Qinghai province, China. The dataset used for the classification comprised of: (1) spectral data and the components of principal component analysis; (2) texture measures derived from pixel basis; (3) DEM and other ancillary data covering the research area. Image textures is an important characteristic of remote sensing images; it can represent spatial variations with spectral brightness in digital numbers. When the spectral information is not enough to separate the different land covers, the texture information can be used to increase the classification accuracy. The texture measures used in this study were calculated from GLCM (Gray level Co-occurrence Matrix); eight frequently used measures were chosen to conduct the classification procedure. The results showed that variance, mean and entropy calculated by GLCM with a 9*9 size window were effective in distinguishing different vegetation types in wetlands zone. The overall accuracy of this method was 84.19% and the Kappa coefficient was 0.8261. The result indicated that the introduction of texture measures can improve the overall accuracy by 12.05% and the overall kappa coefficient by 0.1407 compared with the result using spectral and ancillary data

  3. Vegetation, population and ecological track as sustainability indicators in Colombia

    International Nuclear Information System (INIS)

    Marquez Calle, German

    2000-01-01

    Biophysical sustainability, namely natural capabilities to sustain human development in Colombia, is explored through environmental indicators based on land cover and demographic variables. Remnant vegetation index (IVR in Spanish) uses cover as a measure of ecosystem functionality. Population pressure index (IPD) applies population density to environmental demand analysis. Footprint index (IHE) relates the inverse of density with sustainability. Environmental criticality index combines IVR and IPD to detect offer/demand unbalances. Results suggest Colombia is sustainable although many places in it could be in danger; this could be related with social and economical features of the country

  4. Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

    Science.gov (United States)

    Y Yang, M.; Wang, J.; Zhang, Q.

    2017-07-01

    Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

  5. Spectral discrimination of giant reed (Arundo donax L.): A seasonal study in riparian areas

    Science.gov (United States)

    Fernandes, Maria Rosário; Aguiar, Francisca C.; Silva, João M. N.; Ferreira, Maria Teresa; Pereira, José M. C.

    2013-06-01

    The giant reed (Arundo donax L.) is amongst the one hundred worst invasive alien species of the world, and it is responsible for biodiversity loss and failure of ecosystem functions in riparian habitats. In this work, field spectroradiometry was used to assess the spectral separability of the giant reed from the adjacent vegetation and from the common reed, a native similar species. The study was conducted at different phenological periods and also for the giant reed stands regenerated after mechanical cutting (giant reed_RAC). A hierarchical procedure using Kruskal-Wallis test followed by Classification and Regression Trees (CART) was used to select the minimum number of optimal bands that discriminate the giant reed from the adjacent vegetation. A new approach was used to identify sets of wavelengths - wavezones - that maximize the spectral separability beyond the minimum number of optimal bands. Jeffries Matusita and Bhattacharya distance were used to evaluate the spectral separability using the minimum optimal bands and in three simulated satellite images, namely Landsat, IKONOS and SPOT. Giant reed was spectrally separable from the adjacent vegetation, both at the vegetative and the senescent period, exception made to the common reed at the vegetative period. The red edge region was repeatedly selected, although the visible region was also important to separate the giant reed from the herbaceous vegetation and the mid infrared region to the discrimination from the woody vegetation. The highest separability was obtained for the giant reed_RAC stands, due to its highly homogeneous, dense and dark-green stands. Results are discussed by relating the phenological, morphological and structural features of the giant reed stands and the adjacent vegetation with their optical traits. Weaknesses and strengths of the giant reed spectral discrimination are highlighted and implications of imagery selection for mapping purposes are argued based on present results.

  6. Environment, vegetation and greenness (NDVI) along the North America and Eurasia Arctic transects

    International Nuclear Information System (INIS)

    Walker, D A; Raynolds, M K; Kuss, P; Kade, A N; Epstein, H E; Frost, G V; Kopecky, M A; Daniëls, F J A; Leibman, M O; Moskalenko, N G; Khomutov, A V; Matyshak, G V; Khitun, O V; Forbes, B C; Bhatt, U S; Vonlanthen, C M; Tichý, L

    2012-01-01

    Satellite-based measurements of the normalized difference vegetation index (NDVI; an index of vegetation greenness and photosynthetic capacity) indicate that tundra environments are generally greening and becoming more productive as climates warm in the Arctic. The greening, however, varies and is even negative in some parts of the Arctic. To help interpret the space-based observations, the International Polar Year (IPY) Greening of the Arctic project conducted ground-based surveys along two >1500 km transects that span all five Arctic bioclimate subzones. Here we summarize the climate, soil, vegetation, biomass, and spectral information collected from the North America Arctic transect (NAAT), which has a more continental climate, and the Eurasia Arctic transect (EAT), which has a more oceanic climate. The transects have broadly similar summer temperature regimes and overall vegetation physiognomy, but strong differences in precipitation, especially winter precipitation, soil texture and pH, disturbance regimes, and plant species composition and structure. The results indicate that summer warmth and NDVI increased more strongly along the more continental transect. (letter)

  7. Spectral of electrocardiographic RR intervals to indicate atrial fibrillation

    Science.gov (United States)

    Nuryani, Nuryani; Satrio Nugroho, Anto

    2017-11-01

    Atrial fibrillation is a serious heart diseases, which is associated on the risk of death, and thus an early detection of atrial fibrillation is necessary. We have investigated spectral pattern of electrocardiogram in relation to atrial fibrillation. The utilized feature of electrocardiogram is RR interval. RR interval is the time interval between a two-consecutive R peaks. A series of RR intervals in a time segment is converted to a signal with a frequency domain. The frequency components are investigated to find the components which significantly associate to atrial fibrillation. A segment is defined as atrial fibrillation or normal segments by considering a defined number of atrial fibrillation RR in the segment. Using clinical data of 23 patients with atrial fibrillation, we find that the frequency components could be used to indicate atrial fibrillation.

  8. Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale

    Directory of Open Access Journals (Sweden)

    Anne Clasen

    2015-11-01

    Full Text Available Forest biochemical and biophysical variables and their spatial and temporal distribution are essential inputs to process-orientated ecosystem models. To provide this information, imaging spectroscopy appears to be a promising tool. In this context, the present study investigates the potential of spectral unmixing to derive sub-pixel crown component fractions in a temperate deciduous forest ecosystem. However, the high proportion of foliage in this complex vegetation structure leads to the problem of saturation effects, when applying broadband vegetation indices. This study illustrates that multiple endmember spectral mixture analysis (MESMA can contribute to overcoming this challenge. Reference fractional abundances, as well as spectral measurements of the canopy components, could be precisely determined from a crane measurement platform situated in a deciduous forest in North-East Germany. In contrast to most other studies, which only use leaf and soil endmembers, this experimental setup allowed for the inclusion of a bark endmember for the unmixing of components within the canopy. This study demonstrates that the inclusion of additional endmembers markedly improves the accuracy. A mean absolute error of 7.9% could be achieved for the fractional occurrence of the leaf endmember and 5.9% for the bark endmember. In order to evaluate the results of this field-based study for airborne and satellite-based remote sensing applications, a transfer to Airborne Imaging Spectrometer for Applications (AISA and simulated Environmental Mapping and Analysis Program (EnMAP and Sentinel-2 imagery was carried out. All sensors were capable of unmixing crown components with a mean absolute error ranging between 3% and 21%.

  9. Response of vegetation indices to changes in three measures of leaf water stress

    Science.gov (United States)

    Cohen, Warren B.

    1991-01-01

    The responses of vegetation indices to changes in water stress were evaluated in two separate laboratory experiments. In one experiment the normalized difference vegetation index (NDVI), the near-IR to red ratio (near-IR/red), the Infrared Index (II), and the Moisture Stress Index (MSI) were more highly correlated to leaf water potential in lodgepole pine branches than were the Leaf Water Content Index (LWCI), the mid-IR ratio (Mid-IR), or any of the single Thematic Mapper (TM) bands. In the other experiment, these six indices and the TM Tasseled Cap brightness, greenness, and wetness indices responded to changes in leaf relative water content (RWC) differently than they responded to changes in leaf water content (WC) of three plant species, and the responses were dependent on how experimental replicates were pooled. With no pooling, the LWCI was the most highly correlated index to both RWC and WC among replications, followed by the II, MSI, and wetness. Only the LWCI was highly correlated to RWC and WC when replications were pooled within species. With among species pooling the LWCI was the only index highly correlated with RWC, while the II, MSI, Mid-IR, and wetness were most highly correlated with WC.

  10. Fusion of Plant Height and Vegetation Indices for the Estimation of Barley Biomass

    Directory of Open Access Journals (Sweden)

    Nora Tilly

    2015-09-01

    Full Text Available Plant biomass is an important parameter for crop management and yield estimation. However, since biomass cannot be determined non-destructively, other plant parameters are used for estimations. In this study, plant height and hyperspectral data were used for barley biomass estimations with bivariate and multivariate models. During three consecutive growing seasons a terrestrial laser scanner was used to establish crop surface models for a pixel-wise calculation of plant height and manual measurements of plant height confirmed the results (R2 up to 0.98. Hyperspectral reflectance measurements were conducted with a field spectrometer and used for calculating six vegetation indices (VIs, which have been found to be related to biomass and LAI: GnyLi, NDVI, NRI, RDVI, REIP, and RGBVI. Furthermore, biomass samples were destructively taken on almost the same dates. Linear and exponential biomass regression models (BRMs were established for evaluating plant height and VIs as estimators of fresh and dry biomass. Each BRM was established for the whole observed period and pre-anthesis, which is important for management decisions. Bivariate BRMs supported plant height as a strong estimator (R2 up to 0.85, whereas BRMs based on individual VIs showed varying performances (R2: 0.07–0.87. Fused approaches, where plant height and one VI were used for establishing multivariate BRMs, yielded improvements in some cases (R2 up to 0.89. Overall, this study reveals the potential of remotely-sensed plant parameters for estimations of barley biomass. Moreover, it is a first step towards the fusion of 3D spatial and spectral measurements for improving non-destructive biomass estimations.

  11. The spectral response of Buxus sempervirens to different types of environmental stress - A laboratory experiment

    Science.gov (United States)

    de Jong, Steven M.; Addink, Elisabeth A.; Hoogenboom, Priscilla; Nijland, Wiebe

    2012-11-01

    The European Mediterranean regions are expected to encounter drier summer conditions and warmer temperatures for the winter of +2 °C and of +5 °C for the summer in the next six decennia. As a result the natural vegetation will face harsher conditions due to lower water availability, longer summer droughts and higher temperatures resulting in plant stress conditions. To monitor vegetation conditions like stress and leaf area index dynamics in our study area in Mediterranean France we use earth observation techniques like imaging spectroscopy. To assist image analysis interpretation we carried out a laboratory experiment to investigate the spectral and visible response of Buxus sempervirens, a common Mediterranean species, to five different types of stress: drought, drought-and-heat, light deprivation, total saturation and chlorine poisoning. For 52 days plants were subjected to stress. We collected data on the visible and spectral signs, and calculated thirteen vegetation indices. The plant's response time to different stress types varied from 10 to 32 days. Spectroscopic techniques revealed plant stress up to 15 days earlier than visual inspection. Visible signs of stress of the plants included curling and shrinking of the leaves, de-colouring of the leaves, leaves becoming breakable, opening up of the plant's canopy and sagging of the branches. Spectral signs of stress occurred first in the water absorption bands at 1450 and 1940 nm, followed by reduced absorption in the visible wavelengths, and next by reduced reflectance in near infrared. Light deprivation did not result in any stress signs, while drought, drought and heat and chlorine poisoning resulted in significant stress. The spectral response did not show differences for different stress types. Analysis of the vegetation indices identified the Carter-2 (R695/R760), the Red-Green Index (R690/R550) and the Vogelman-2 (R734 - R747)/(R715 + R726) as the best performing ones to identify stress. The lab

  12. Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

    Science.gov (United States)

    Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

    2015-12-01

    Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

  13. Vegetation burn severity mapping using Landsat-8 and WorldView-2

    Science.gov (United States)

    Wu, Zhuoting; Middleton, Barry R.; Hetzler, Robert; Vogel, John M.; Dye, Dennis G.

    2015-01-01

    We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

  14. Mapping and characterizing the vegetation types of the Democratic Republic of Congo using SPOT VEGETATION time series

    Science.gov (United States)

    Vancutsem, C.; Pekel, J.-F.; Evrard, C.; Malaisse, F.; Defourny, P.

    2009-02-01

    The need for quantitative and accurate information to characterize the state and evolution of vegetation types at a national scale is widely recognized. This type of information is crucial for the Democratic Republic of Congo, which contains the majority of the tropical forest cover of Central Africa and a large diversity of habitats. In spite of recent progress in earth observation capabilities, vegetation mapping and seasonality analysis in equatorial areas still represent an outstanding challenge owing to high cloud coverage and the extent and limited accessibility of the territory. On one hand, the use of coarse-resolution optical data is constrained by performance in the presence of cloud screening and by noise arising from the compositing process, which limits the spatial consistency of the composite and the temporal resolution. On the other hand, the use of high-resolution data suffers from heterogeneity of acquisition dates, images and interpretation from one scene to another. The objective of the present study was to propose and demonstrate a semi-automatic processing method for vegetation mapping and seasonality characterization based on temporal and spectral information from SPOT VEGETATION time series. A land cover map with 18 vegetation classes was produced using the proposed method that was fed by ecological knowledge gathered from botanists and reference documents. The floristic composition and physiognomy of each vegetation type are described using the Land Cover Classification System developed by the FAO. Moreover, the seasonality of each class is characterized on a monthly basis and the variation in different vegetation indicators is discussed from a phenological point of view. This mapping exercise delivers the first area estimates of seven different forest types, five different savannas characterized by specific seasonality behavior and two aquatic vegetation types. Finally, the result is compared to two recent land cover maps derived from

  15. Changes in spectral signatures of red lettuce regards to Zinc uptake

    Science.gov (United States)

    Shin, J.; Yu, J.; Koh, S. M.; Park, G.; Kim, S.

    2017-12-01

    Heavy metal contaminations caused by human activities such as mining and industrial activities caused serious soil contamination. Soil contaminations causes secondary impact on vegetation by uptake processes. Intakes of vegetables harvested from heavy metal contaminated soil may cause serious health problems. It would be very effective if screening tool could be developed before the vegetables are distributed over the market. This study investigated spectral response of red lettuce regards to Zn uptake from the treated soil in a laboratory condition. Zn solutions at different levels of concentration are injected to potted lettuce. The chemical composition and spectral characteristics of the leaves are analyzed every 2 days and the correlation between the Zn concentration and spectral reflectance is investigated. The experiment reveals that Zn uptake of red lettuce is significantly higher for the leaves from treated pot compared to untreated pot showing highly contaminated concentrations beyond the standard Zn concentrations for food. The spectral response regards to Zn is manifested at certain level of concentration threshold. Below the threshold, reflectance at NIR regions increases regards to increase in Zn concentration. On the other hand, above the threshold, IR reflectance decreases and slope of NIR shoulder increases regards to higher Zn concentration. We think this result may contribute for development of screening tools for heavy metal contaminations in vegetables.

  16. Suppression of vegetation in LANDSAT ETM+ remote sensing images

    Science.gov (United States)

    Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael

    2010-05-01

    Vegetation cover is an impediment to the interpretation of multispectral remote sensing images for geological applications, especially in densely vegetated terrains. In order to enhance the underlying geological information in such terrains, it is desirable to suppress the reflectance component of vegetation. One form of spectral unmixing that has been successfully used for vegetation reflectance suppression in multispectral images is called "forced invariance". It is based on segregating components of the reflectance spectrum that are invariant with respect to a specific spectral index such as the NDVI. The forced invariance method uses algorithms such as software defoliation. However, the outputs of software defoliation are single channel data, which are not amenable to geological interpretations. Crippen and Blom (2001) proposed a new forced invariance algorithm that utilizes band statistics, rather than band ratios. The authors demonstrated the effectiveness of their algorithms on a LANDSAT TM scene from Nevada, USA, especially in open canopy areas in mixed and semi-arid terrains. In this presentation, we report the results of our experimentation with this algorithm on a densely to sparsely vegetated Landsat ETM+ scene. We selected a scene (Path 119, Row 39) acquired on 18th July, 2004. Two study areas located around the city of Hangzhou, eastern China were tested. One of them covers uninhabited hilly terrain characterized by low rugged topography, parts of the hills are densely vegetated; another one covers both inhabited urban areas and uninhabited hilly terrain, which is densely vegetated. Crippen and Blom's algorithm is implemented in the following sequential steps: (1) dark pixel correction; (2) vegetation index calculation; (3) estimation of statistical relationship between vegetation index and digital number (DN) values for each band; (4) calculation of a smooth best-fit curve for the above relationships; and finally, (5) selection of a target average DN

  17. Integrated Spectral Energy Distributions and Absorption Feature Indices of Single Stellar Populations

    OpenAIRE

    Zhang, Fenghui; Han, Zhanwen; Li, Lifang; Hurley, Jarrod R.

    2004-01-01

    Using evolutionary population synthesis, we present integrated spectral energy distributions and absorption-line indices defined by the Lick Observatory image dissector scanner (referred to as Lick/IDS) system, for an extensive set of instantaneous burst single stellar populations (SSPs). The ages of the SSPs are in the range 1-19 Gyr and the metallicities [Fe/H] are in the range -2.3 - 0.2. Our models use the rapid single stellar evolution algorithm of Hurley, Pols and Tout for the stellar e...

  18. Modeling Agricultural Crop Production in China using AVHRR-based Vegetation Health Indices

    Science.gov (United States)

    Yang, B.; Kogan, F.; Guo, W.; Zhiyuan, P.; Xianfeng, J.

    Weather related crop losses have always been a concern for farmers On a wider scale it has always influenced decision of Governments traders and other policy makers for the purpose of balanced food supplies trade and distribution of aid to the nations in need Therefore national policy and decision makers are giving increasing importance to early assessment of crop losses in response to weather fluctuations This presentation emphasizes utility of AVHRR-based Vegetation health index VHI for early warning of drought-related losses of agricultural production in China The VHI is a three-channel index characterizing greenness vigor and temperature of land surface which can be used as proxy for estimation of how healthy and potentially productive could be vegetation China is the largest in the world producer of grain including wheat and rice and cotton In the major agricultural areas China s crop production is very dependent on weather The VHI being a proxy indicator of weather impact on vegetation showed some correlation with productivity of agricultural crops during the critical period of their development The periods of the strongest correlation were investigated and used to build regression models where crop yield deviation from technological trend was accepted as a dependent and VHI as independent variables The models were developed for several major crops including wheat corn and soybeans

  19. Fetal functional brain age assessed from universal developmental indices obtained from neuro-vegetative activity patterns.

    Directory of Open Access Journals (Sweden)

    Dirk Hoyer

    Full Text Available Fetal brain development involves the development of the neuro-vegetative (autonomic control that is mediated by the autonomic nervous system (ANS. Disturbances of the fetal brain development have implications for diseases in later postnatal life. In that context, the fetal functional brain age can be altered. Universal principles of developmental biology applied to patterns of autonomic control may allow a functional age assessment. The work aims at the development of a fetal autonomic brain age score (fABAS based on heart rate patterns. We analysed n = 113 recordings in quiet sleep, n = 286 in active sleep, and n = 29 in active awakeness from normals. We estimated fABAS from magnetocardiographic recordings (21.4-40.3 weeks of gestation preclassified in quiet sleep (n = 113, 63 females and active sleep (n = 286, 145 females state by cross-validated multivariate linear regression models in a cross-sectional study. According to universal system developmental principles, we included indices that address increasing fluctuation range, increasing complexity, and pattern formation (skewness, power spectral ratio VLF/LF, pNN5. The resulting models constituted fABAS. fABAS explained 66/63% (coefficient of determination R(2 of training and validation set of the variance by age in quiet, while 51/50% in active sleep. By means of a logistic regression model using fluctuation range and fetal age, quiet and active sleep were automatically reclassified (94.3/93.1% correct classifications. We did not find relevant gender differences. We conclude that functional brain age can be assessed based on universal developmental indices obtained from autonomic control patterns. fABAS reflect normal complex functional brain maturation. The presented normative data are supplemented by an explorative study of 19 fetuses compromised by intrauterine growth restriction. We observed a shift in the state distribution towards active awakeness. The lower WGA

  20. Real-time detection of natural objects using AM-coded spectral matching imager

    Science.gov (United States)

    Kimachi, Akira

    2005-01-01

    This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

  1. HARD X-RAY AND MICROWAVE EMISSIONS FROM SOLAR FLARES WITH HARD SPECTRAL INDICES

    Energy Technology Data Exchange (ETDEWEB)

    Kawate, T. [Kwasan and Hida Observatory, Kitashirakawa-oiwakecho, Sakyo, Kyoto 606-8502 (Japan); Nishizuka, N. [Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 229-8510 (Japan); Oi, A. [College of Science, Ibaraki University, Mito, Ibaraki 310-8512 (Japan); Ohyama, M. [Faculty of Education, Shiga University, 2-5-1 Hiratsu, Otsu, Shiga 1-1, Baba Hikone city, Siga 522-8522 (Japan); Nakajima, H., E-mail: kawate@kusastro.kyoto-u.ac.jp [Nobeyama Solar Radio Observatory, NAOJ, Nobeyama, Minamisaku, Nagano 384-1305 (Japan)

    2012-03-10

    We analyze 10 flare events that radiate intense hard X-ray (HXR) emission with significant photons over 300 keV to verify that the electrons that have a common origin of acceleration mechanism and energy power-law distribution with solar flares emit HXRs and microwaves. Most of these events have the following characteristics. HXRs emanate from the footpoints of flare loops, while microwaves emanate from the tops of flare loops. The time profiles of the microwave emission show delays of peak with respect to those of the corresponding HXR emission. The spectral indices of microwave emissions show gradual hardening in all events, while the spectral indices of the corresponding HXR emissions are roughly constant in most of the events, though rather rapid hardening is simultaneously observed in some for both indices during the onset time and the peak time. These characteristics suggest that the microwave emission emanates from the trapped electrons. Then, taking into account the role of the trapping of electrons for the microwave emission, we compare the observed microwave spectra with the model spectra calculated by a gyrosynchrotron code. As a result, we successfully reproduce the eight microwave spectra. From this result, we conclude that the electrons that have a common acceleration and a common energy distribution with solar flares emit both HXR and microwave emissions in the eight events, though microwave emission is contributed to by electrons with much higher energy than HXR emission.

  2. Accurate atmospheric parameters at moderate resolution using spectral indices: Preliminary application to the marvels survey

    International Nuclear Information System (INIS)

    Ghezzi, Luan; Da Costa, Luiz N.; Maia, Marcio A. G.; Ogando, Ricardo L. C.; Dutra-Ferreira, Letícia; Lorenzo-Oliveira, Diego; Porto de Mello, Gustavo F.; Santiago, Basílio X.; De Lee, Nathan; Lee, Brian L.; Ge, Jian; Wisniewski, John P.; González Hernández, Jonay I.; Stassun, Keivan G.; Cargile, Phillip; Pepper, Joshua; Fleming, Scott W.; Schneider, Donald P.; Mahadevan, Suvrath; Wang, Ji

    2014-01-01

    Studies of Galactic chemical, and dynamical evolution in the solar neighborhood depend on the availability of precise atmospheric parameters (effective temperature T eff , metallicity [Fe/H], and surface gravity log g) for solar-type stars. Many large-scale spectroscopic surveys operate at low to moderate spectral resolution for efficiency in observing large samples, which makes the stellar characterization difficult due to the high degree of blending of spectral features. Therefore, most surveys employ spectral synthesis, which is a powerful technique, but relies heavily on the completeness and accuracy of atomic line databases and can yield possibly correlated atmospheric parameters. In this work, we use an alternative method based on spectral indices to determine the atmospheric parameters of a sample of nearby FGK dwarfs and subgiants observed by the MARVELS survey at moderate resolving power (R ∼ 12,000). To avoid a time-consuming manual analysis, we have developed three codes to automatically normalize the observed spectra, measure the equivalent widths of the indices, and, through a comparison of those with values calculated with predetermined calibrations, estimate the atmospheric parameters of the stars. The calibrations were derived using a sample of 309 stars with precise stellar parameters obtained from the analysis of high-resolution FEROS spectra, permitting the low-resolution equivalent widths to be directly related to the stellar parameters. A validation test of the method was conducted with a sample of 30 MARVELS targets that also have reliable atmospheric parameters derived from the high-resolution spectra and spectroscopic analysis based on the excitation and ionization equilibria method. Our approach was able to recover the parameters within 80 K for T eff , 0.05 dex for [Fe/H], and 0.15 dex for log g, values that are lower than or equal to the typical external uncertainties found between different high-resolution analyses. An additional test

  3. UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis

    Directory of Open Access Journals (Sweden)

    Quanlong Feng

    2015-01-01

    Full Text Available Unmanned aerial vehicle (UAV remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1 Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2 the inclusion of texture features improved classification accuracy significantly; (3 classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.

  4. Extraction of urban vegetation with Pleiades multiangular images

    Science.gov (United States)

    Lefebvre, Antoine; Nabucet, Jean; Corpetti, Thomas; Courty, Nicolas; Hubert-Moy, Laurence

    2016-10-01

    Vegetation is essential in urban environments since it provides significant services in terms of health, heat, property value, ecology ... As part of the European Union Biodiversity Strategy Plan for 2020, the protection and development of green-infrastructures is strengthened in urban areas. In order to evaluate and monitor the quality of the green infra-structures, this article investigates contributions of Pléiades multi-angular images to extract and characterize low and high urban vegetation. From such images one can extract both spectral and elevation information from optical images. Our method is composed of 3 main steps : (1) the computation of a normalized Digital Surface Model from the multi-angular images ; (2) Extraction of spectral and contextual features ; (3) a classification of vegetation classes (tree and grass) performed with a random forest classifier. Results performed in the city of Rennes in France show the ability of multi-angular images to extract DEM in urban area despite building height. It also highlights its importance and its complementarity with contextual information to extract urban vegetation.

  5. Evaluation of the data of vegetable covering using fraction images and multitemporal vegetation index, derived of orbital data of moderate resolution of the sensor MODIS

    International Nuclear Information System (INIS)

    Murillo Mejia, Mario Humberto

    2006-01-01

    The objective was to evaluate the data obtained by sensor MODIS onboard the EOS terra satellite land cover units. The study area is the republic of Colombia in South America. The methodology consisted of analyzing the multitemporal (vegetation, soil and shade-water) fraction images and vegetation indices (NDVI) apply the lineal spectral mixture model to products derived from derived images by sensor MODIS data obtained in years 2001 and 2003. The mosaics of the original and the transformed vegetation (soil and shade-water) bands were generated for the whole study area using SPRING 4. 0 software, developed by INPE then these mosaics were segmented, classified, mapped, and edited to obtain a moderate resolution land cover map. The results derived from MODIS analysis were compared with Landsat ETM+ data acquire for a single test site. The results of the project showed the usefulness of MODIS images for large-scale land cover mapping and monitoring studies

  6. Surface soil phytoliths as vegetation and altitude indicators: a study from the southern Himalaya.

    Science.gov (United States)

    An, Xiaohong; Lu, Houyuan; Chu, Guoqiang

    2015-10-26

    Phytoliths represent one of the few available altitudinal vegetation proxies for mountain ecosystems. This study analyzed 41 topsoil phytolith samples collected from five altitudinal zones in the southern Himalaya as far as, and beyond, the timberline, from tropical forest (up to 1,000 m a.s.l.) to subtropical forest (1,000-2,000 m a.s.l.), to temperate forest (2,000-3,000 m a.s.l.), to subalpine forest (3,000-4,100 m a.s.l.) and finally to alpine scrub (4,100-5,200 m a.s.l.). The statistical results show a good correlation between phytolith assemblages and these five altitudinal vegetation zones: the five phytolith assemblages identified effectively differentiated these five altitudinal vegetation zones. In particular, coniferous phytoliths accurately indicated the timberline. Additionally, we tested the phytolith index Ic (a proxy for estimating the percentage of Pooideae vis-à-vis the total grass content) as a quantifier of phytolith variety versus altitude. Ic increased along altitude, as expected. An investigation of phytoliths provided an initial basis for the analysis of the composition of gramineous vegetation. Furthermore, redundancy analysis and discriminant analysis also suggested a significant correlation between phytolith assemblages and altitude. Our research therefore provides an up-to-date analogue for the reconstruction of changes to palaeovegetation and palaeoaltitude in mountainous areas.

  7. Spatiotemporal Built-up Land Density Mapping Using Various Spectral Indices in Landsat-7 ETM+ and Landsat-8 OLI/TIRS (Case Study: Surakarta City)

    Science.gov (United States)

    Risky, Yanuar S.; Aulia, Yogi H.; Widayani, Prima

    2017-12-01

    Spectral indices variations support for rapid and accurate extracting information such as built-up density. However, the exact determination of spectral waves for built-up density extraction is lacking. This study explains and compares the capabilities of 5 variations of spectral indices in spatiotemporal built-up density mapping using Landsat-7 ETM+ and Landsat-8 OLI/TIRS in Surakarta City on 2002 and 2015. The spectral indices variations used are 3 mid-infrared (MIR) based indices such as the Normalized Difference Built-up Index (NDBI), Urban Index (UI) and Built-up and 2 visible based indices such as VrNIR-BI (visible red) and VgNIR-BI (visible green). Linear regression statistics between ground value samples from Google Earth image in 2002 and 2015 and spectral indices for determining built-up land density. Ground value used amounted to 27 samples for model and 7 samples for accuracy test. The classification of built-up density mapping is divided into 9 classes: unclassified, 0-12.5%, 12.5-25%, 25-37.5%, 37.5-50%, 50-62.5%, 62.5-75%, 75-87.5% and 87.5-100 %. Accuracy of built-up land density mapping in 2002 and 2015 using VrNIR-BI (81,823% and 73.235%), VgNIR-BI (78.934% and 69.028%), NDBI (34.870% and 74.365%), UI (43.273% and 64.398%) and Built-up (59.755% and 72.664%). Based all spectral indices, Surakarta City on 2000-2015 has increased of built-up land density. VgNIR-BI has better capabilities for built-up land density mapping on Landsat-7 ETM + and Landsat-8 OLI/TIRS.

  8. Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic

    Science.gov (United States)

    Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav

    2015-04-01

    Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in

  9. Vegetation Dynamics in the Upper Guinean Forest Region of West Africa from 2001 to 2015

    Directory of Open Access Journals (Sweden)

    Zhihua Liu

    2016-12-01

    Full Text Available The Upper Guinea Forest (UGF region of West Africa is one of the most climatically marginal and human-impacted tropical forest regions in the world. Research on the patterns and drivers of vegetation change is critical for developing strategies to sustain ecosystem services in the region and to understand how climate and land use change will affect other tropical forests around the globe. We compared six spectral indices calculated from the 2001–2015 MODIS optical-infrared reflectance data with manually-interpreted measurements of woody vegetation cover from high resolution imagery. The tasseled cap wetness (TCW index was found to have the strongest association with woody vegetation cover, whereas greenness indices, such as the enhanced vegetation index (EVI, had relatively weak associations with woody cover. Trends in woody vegetation cover measured with the TCW index were analyzed using Mann–Kendall statistics and were contrasted with trends in vegetation greenness measured with EVI. In the drier West Sudanian Savanna and Guinean Forest-Savanna Mosaic ecoregions, EVI trends were primarily positive, and TCW trends were primarily negative, suggesting that woody vegetation cover was decreasing, while herbaceous vegetation cover is increasing. In the wettest tropical forests in the Western Guinean Lowland Forest ecoregion, declining trends in both TCW and EVI were indicative of widespread forest degradation resulting from human activities. Across all ecoregions, declines in woody cover were less prevalent in protected areas where human activities were restricted. Multiple lines of evidence suggested that human land use and resource extraction, rather than climate trends or short-term climatic anomalies, were the predominant drivers of recent vegetation change in the UGF region of West Africa.

  10. Temporal variation (seasonal and interannual) of vegetation indices of maize and soybeans across multiple years in central Iowa

    Science.gov (United States)

    Prueger, J. H.; Hatfield, J. L.

    2015-09-01

    Remotely sensed reflectance parameters from corn and soybean surfaces can be correlated to crop production. Surface reflectance of a typical Upper Midwest corn /soybean region in central Iowa across multiple years reveal subtle dynamics in vegetative surface response to a continually varying climate. From 2006 through 2014 remotely sensed data have been acquired over production fields of corn and soybeans in central IA, U.S.A. with the fields alternating between corn and soybeans. The data have been acquired using ground-based radiometers with 16 wavebands covering the visible, near infrared, shortwave infrared wavebands and combined into a series of vegetative indices. These data were collected on clear days with the goal of collecting data at a minimum of once per week from prior to planting until after fall tillage operations. Within each field, five sites were established and sampled during the year to reduce spatial variation and allow for an assessment of changes in the vegetative indices throughout the growing season. Ancillary data collected for each crop included the phenological stage at each sampling date along with biomass sampled at the onset of the reproductive stage and at physiological maturity. Evaluation of the vegetative indices for the different years revealed that patterns were related to weather effects on corn and soybean growth. Remote sensing provides a method to evaluate changes within and among growing seasons to assess crop growth and development as affected by differences in weather variability.

  11. Performance of spectral fitting methods for vegetation fluorescence quantification

    NARCIS (Netherlands)

    Meroni, M.; Busetto, D.; Colombo, R.; Guanter, L.; Moreno, J.; Verhoef, W.

    2010-01-01

    The Fraunhofer Line Discriminator (FLD) principle has long been considered as the reference method to quantify solar-induced chlorophyll fluorescence (F) from passive remote sensing measurements. Recently, alternative retrieval algorithms based on the spectral fitting of hyperspectral radiance

  12. Random Forest Variable Importance Spectral Indices Scheme for Burnt Forest Recovery Monitoring—Multilevel RF-VIMP

    Directory of Open Access Journals (Sweden)

    Sornkitja Boonprong

    2018-05-01

    Full Text Available Burnt forest recovery is normally monitored with a time-series analysis of satellite data because of its proficiency for large observation areas. Traditional methods, such as linear correlation plotting, have been proven to be effective, as forest recovery naturally increases with time. However, these methods are complicated and time consuming when increasing the number of observed parameters. In this work, we present a random forest variable importance (RF-VIMP scheme called multilevel RF-VIMP to compare and assess the relationship between 36 spectral indices (parameters of burnt boreal forest recovery in the Great Xing’an Mountain, China. Six Landsat images were acquired in the same month 0, 1, 4, 14, 16, and 20 years after a fire, and 39,380 fixed-location samples were then extracted to calculate the effectiveness of the 36 parameters. Consequently, the proposed method was applied to find correlations between the forest recovery indices. The experiment showed that the proposed method is suitable for explaining the efficacy of those spectral indices in terms of discrimination and trend analysis, and for showing the satellite data and forest succession dynamics when applied in a time series. The results suggest that the tasseled cap transformation wetness, brightness, and the shortwave infrared bands (both 1 and 2 perform better than other indices for both classification and monitoring.

  13. USGS Digital Spectral Library splib06a

    Science.gov (United States)

    Clark, Roger N.; Swayze, Gregg A.; Wise, Richard A.; Livo, K. Eric; Hoefen, Todd M.; Kokaly, Raymond F.; Sutley, Stephen J.

    2007-01-01

    Introduction We have assembled a digital reflectance spectral library that covers the wavelength range from the ultraviolet to far infrared along with sample documentation. The library includes samples of minerals, rocks, soils, physically constructed as well as mathematically computed mixtures, plants, vegetation communities, microorganisms, and man-made materials. The samples and spectra collected were assembled for the purpose of using spectral features for the remote detection of these and similar materials. Analysis of spectroscopic data from laboratory, aircraft, and spacecraft instrumentation requires a knowledge base. The spectral library discussed here forms a knowledge base for the spectroscopy of minerals and related materials of importance to a variety of research programs being conducted at the U.S. Geological Survey. Much of this library grew out of the need for spectra to support imaging spectroscopy studies of the Earth and planets. Imaging spectrometers, such as the National Aeronautics and Space Administration (NASA) Airborne Visible/Infra Red Imaging Spectrometer (AVIRIS) or the NASA Cassini Visual and Infrared Mapping Spectrometer (VIMS) which is currently orbiting Saturn, have narrow bandwidths in many contiguous spectral channels that permit accurate definition of absorption features in spectra from a variety of materials. Identification of materials from such data requires a comprehensive spectral library of minerals, vegetation, man-made materials, and other subjects in the scene. Our research involves the use of the spectral library to identify the components in a spectrum of an unknown. Therefore, the quality of the library must be very good. However, the quality required in a spectral library to successfully perform an investigation depends on the scientific questions to be answered and the type of algorithms to be used. For example, to map a mineral using imaging spectroscopy and the mapping algorithm of Clark and others (1990a, 2003b

  14. Annual Gross Primary Production from Vegetation Indices: A Theoretically Sound Approach

    Directory of Open Access Journals (Sweden)

    María Amparo Gilabert

    2017-02-01

    Full Text Available A linear relationship between the annual gross primary production (GPP and a PAR-weighted vegetation index is theoretically derived from the Monteith equation. A semi-empirical model is then proposed to estimate the annual GPP from commonly available vegetation indices images and a representative PAR, which does not require actual meteorological data. A cross validation procedure is used to calibrate and validate the model predictions against reference data. As the calibration/validation process depends on the reference GPP product, the higher the quality of the reference GPP, the better the performance of the semi-empirical model. The annual GPP has been estimated at 1-km scale from MODIS NDVI and EVI images for eight years. Two reference data sets have been used: an optimized GPP product for the study area previously obtained and the MOD17A3 product. Different statistics show a good agreement between the estimates and the reference GPP data, with correlation coefficient around 0.9 and relative RMSE around 20%. The annual GPP is overestimated in semiarid areas and slightly underestimated in dense forest areas. With the above limitations, the model provides an excellent compromise between simplicity and accuracy for the calculation of long time series of annual GPP.

  15. Accurate Atmospheric Parameters at Moderate Resolution Using Spectral Indices: Preliminary Application to the MARVELS Survey

    Science.gov (United States)

    Ghezzi, Luan; Dutra-Ferreira, Letícia; Lorenzo-Oliveira, Diego; Porto de Mello, Gustavo F.; Santiago, Basílio X.; De Lee, Nathan; Lee, Brian L.; da Costa, Luiz N.; Maia, Marcio A. G.; Ogando, Ricardo L. C.; Wisniewski, John P.; González Hernández, Jonay I.; Stassun, Keivan G.; Fleming, Scott W.; Schneider, Donald P.; Mahadevan, Suvrath; Cargile, Phillip; Ge, Jian; Pepper, Joshua; Wang, Ji; Paegert, Martin

    2014-12-01

    Studies of Galactic chemical, and dynamical evolution in the solar neighborhood depend on the availability of precise atmospheric parameters (effective temperature T eff, metallicity [Fe/H], and surface gravity log g) for solar-type stars. Many large-scale spectroscopic surveys operate at low to moderate spectral resolution for efficiency in observing large samples, which makes the stellar characterization difficult due to the high degree of blending of spectral features. Therefore, most surveys employ spectral synthesis, which is a powerful technique, but relies heavily on the completeness and accuracy of atomic line databases and can yield possibly correlated atmospheric parameters. In this work, we use an alternative method based on spectral indices to determine the atmospheric parameters of a sample of nearby FGK dwarfs and subgiants observed by the MARVELS survey at moderate resolving power (R ~ 12,000). To avoid a time-consuming manual analysis, we have developed three codes to automatically normalize the observed spectra, measure the equivalent widths of the indices, and, through a comparison of those with values calculated with predetermined calibrations, estimate the atmospheric parameters of the stars. The calibrations were derived using a sample of 309 stars with precise stellar parameters obtained from the analysis of high-resolution FEROS spectra, permitting the low-resolution equivalent widths to be directly related to the stellar parameters. A validation test of the method was conducted with a sample of 30 MARVELS targets that also have reliable atmospheric parameters derived from the high-resolution spectra and spectroscopic analysis based on the excitation and ionization equilibria method. Our approach was able to recover the parameters within 80 K for T eff, 0.05 dex for [Fe/H], and 0.15 dex for log g, values that are lower than or equal to the typical external uncertainties found between different high-resolution analyses. An additional test was

  16. ANALYZING SPECTRAL CHARACTERISTICS OF SHADOW AREA FROM ADS-40 HIGH RADIOMETRIC RESOLUTION AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    Y.-T. Hsieh

    2016-06-01

    Full Text Available The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i The DN values in shadow area are much lower than in nonshadow area; (ii DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv The shadow area NIR of vegetation category also shows a strong reflection; (v Generally, vegetation indexes (NDVI still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40 is potential for the extract land cover information of shadow areas.

  17. Assessment of the TNT- and AMPA-Induced Changes in Vegetation Morphology and Bio-physical Properties

    Science.gov (United States)

    Campbell, P. K.; Middleton, E.; Corp, L.

    2009-12-01

    Currently, there is no satisfactory method for locating unexploded ordinance or to mitigate the environmental impacts of leaked TNT. Non-exploded TNT-containing land mines deployed during military training exercises eventually leak TNT into the soils, where it is partially degraded into nitrate and toluene, a carcinogen. Environmental stresses alter plant physiology, affecting photosynthesis as well as the production of protective chemicals such as phenolic compounds which fluoresce in the blue/green spectrum. Changes in the fluorescence and reflectance spectral signatures of vegetation occur concurrently with the changes in plant vigor and chemical constituents. Thus, monitoring of vegetation vigor based on fluorescence and reflectance measurements could provide the means for detecting contamination from trinitrotoluene (TNT), a common compound contained in land mines. The goal of this study was to evaluate the capability of fluorescence sensing systems to remotely detect the presence of TNT-related compounds sequestered in vegetation growing on TNT contaminated soils. Using instrumentation and methodologies that utilize reflectance and actively induced fluorescence associated with “stead-state” emissions, we conducted experiments on four experimental species - two of which have the C4 photosynthetic pathway and two of which have the more common C3 pathway. The experimental plants were grown outdoors in 2 gallon pots in a 75:25 mixture of white quartz sand and perlite, with planted pots placed in larger pots to retain water and TNT solution added. Plants were randomly assigned to treatments for twice weekly applications of 0, 10, and 20 μl/l TNT solutions [doses ~30 μl/l are toxic] and watered daily as necessary. Our findings, using ChlF spectra, indicate statistically significant differences between TNT treated and control samples in the blue and green regions. Maximum treatment separation was achieved using 280Ex and measuring emissions in the blue

  18. Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing.

    Science.gov (United States)

    Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

    2015-09-30

    UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R²-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R²-values up to 0.77) corresponded with the OBRA

  19. Effects of leaf age within growth stages of pepper and sorghum plants on leaf thickness, water, chlorophyll, and light reflectance. [in spectral vegetation discrimination

    Science.gov (United States)

    Gausman, H. W.; Cardenas, R.; Berumen, A.

    1974-01-01

    Pepper and sorghum plants (characterized by porous and compact leaf mesophylls, respectively) were used to study the influence of leaf age on light reflectance. Measurements were limited to the upper five nodal positions within each growth stage, since upper leaves make up most of the reflectance surfaces remotely sensed. The increase in leaf thickness and water content with increasing leaf age was taken into consideration, since each of these factors affects the reflectance as well as the selection of spectral wavelength intervals for optimum discrimination of vegetation.

  20. Upscaling from leaf to canopy chlorophyll/carotenoid pigment based vegetation indices reveal phenology of photosynthesis in temperate evergreen and deciduous trees

    Science.gov (United States)

    Wong, C. Y.; Bhathena, Y.; Arain, M. A.; Ensminger, I.

    2017-12-01

    Optically derived vegetation indices have been developed to provide information about plant status including photosynthetic activity. They reflect changes in leaf pigments, which vary seasonally in pigment composition, enabling them to be used as a proxy of photosynthetic phenology. Important pigments in photosynthetic activity are carotenoids and chlorophylls, which are associated with light harvesting and energy dissipation. In temperate forests, which consist of deciduous and evergreen trees, there are difficulties resolving evergreen phenology using the most widely used index, the normalized difference vegetation index (NDVI). NDVI works well in deciduous trees, which exhibit a "visible" phenological process of leaf growth in the spring, and leaf senescence and abscission in the autumn. Evergreen conifers stay green year-round and utilize "invisible" changes of overwintering pigment composition that NDVI cannot resolve, so carotenoid pigment sensitive vegetation indices have been suggested for evergreens. The aim of this study was to evaluate carotenoid based vegetation indices over the chlorophyll sensitive NDVI. For this purpose, we evaluated the greenness index, NDVI, and carotenoid pigment sensitive indices: photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI) in red maple, white oak and eastern white pine for two years. We also measured leaf gas exchange and pigment concentrations. We observed that NDVI correlated with photosynthetic activity in deciduous trees, whereas PRI and CCI correlated with photosynthesis across both evergreen and deciduous trees. This pattern was consistent, upscaling from leaf- to canopy-scales indicating that the mechanisms involved in winter acclimation can be resolved at larger spatial scales. PRI and CCI detected seasonal changes in carotenoids and chlorophylls linked to photoprotection and are suitable as a proxy of photosynthetic activity. These findings have implications to improve our use and

  1. Analysis of the state of vegetation in the municipality of Jagodina (Serbia through remote sensing and suggestions for protection

    Directory of Open Access Journals (Sweden)

    Milanović Miško M.

    2016-01-01

    Full Text Available Both environmental control and appropriate measurement results present basis for the quality protection of geospatial elements. Providing environmental monitoring activities and creating control network is the obligation of each state, whereas local communities provide observation and control of air quality, water quality, waste quality, soil quality, vegetation and land cover control, etc. This has been the reason for the analysis of vegetation of the municipality of Jagodina in Serbia. By processing satellite images, data on the sources of pollution and polluting materials of the vegetation have been discovered. These include spot (stationary, linear (mobile and stationary and surface (stationary and mobile sources. While processing satellite images by the Idrisi software, we have acquired results that indicate certain vegetation modifications (images obtained through infrared spectral imaging. Results obtained through remote sensing indicate the necessity to define adequate vegetation monitoring, to complete a register of pollutants, to set up information system and define ways of data presentation in order to manage a single, complete register of environmental pollutants in the municipality of Jagodina.

  2. Evaluating Spectral Indices for Winter Wheat Health Status ...

    African Journals Online (AJOL)

    Helen

    study explored the application of Land Surface Temperature (LST)-vegetation ... Classification methods and crop growth models are widely used for crop monitoring. ... The limitations of the study were that some of the Landsat 8 images were contaminated with cloud ..... These relationships arise due to the cooling effects.

  3. Monitoring urban greenness dynamics using multiple endmember spectral mixture analysis.

    Directory of Open Access Journals (Sweden)

    Muye Gan

    Full Text Available Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents' quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.

  4. Characterization and Spectral Monitoring of Coffee Lands in Brazil

    Science.gov (United States)

    Alves, H. M. R.; Volpato, M. M. L.; Vieira, T. G. C.; Maciel, D. A.; Gonçalves, T. G.; Dantas, M. F.

    2016-06-01

    In Brazil, coffee production has great economic and social importance. Despite this fact, there is still a shortage of information regarding its spatial distribution, crop management and environment. The aim of this study was to carry out spectral monitoring of coffee lands and to characterize their environments using geotechnologies. Coffee fields with contiguous areas over 0.01 km2 within a 488.5 km2 region in the south of Minas Gerais state were selected for the study. Spectral data from the sensors OLI/Landsat 8 and the Shuttle Radar Topography Mission from 2014 to 2015 were obtained, as well as information on production areas, surface temperature, vegetation indexes, altitude and slope, were gathered and analyzed. The results indicate that there is great variation in the NDVI and NDWI values, with means ranging from 0.21 to 0.91 (NDVI) and 0.108 to 0.543 (NDWI). The altitude ranged from 803 to 1150 m, and the surface temperature from 20.9°C to 27.6°C. The altitude and the surface temperature distribution patterns were correlated with the vegetation indexes. The slope classes were very homogeneous, predominantly with declivities between 8 to 20 %, characterized as wavy relief. This study made possible the characterization and monitoring of coffee lands and its results may be instrumental in decision-making processes related to coffee management.

  5. CHARACTERIZATION AND SPECTRAL MONITORING OF COFFEE LANDS IN BRAZIL

    Directory of Open Access Journals (Sweden)

    H. M. R. Alves

    2016-06-01

    Full Text Available In Brazil, coffee production has great economic and social importance. Despite this fact, there is still a shortage of information regarding its spatial distribution, crop management and environment. The aim of this study was to carry out spectral monitoring of coffee lands and to characterize their environments using geotechnologies. Coffee fields with contiguous areas over 0.01 km2 within a 488.5 km2 region in the south of Minas Gerais state were selected for the study. Spectral data from the sensors OLI/Landsat 8 and the Shuttle Radar Topography Mission from 2014 to 2015 were obtained, as well as information on production areas, surface temperature, vegetation indexes, altitude and slope, were gathered and analyzed. The results indicate that there is great variation in the NDVI and NDWI values, with means ranging from 0.21 to 0.91 (NDVI and 0.108 to 0.543 (NDWI. The altitude ranged from 803 to 1150 m, and the surface temperature from 20.9°C to 27.6°C. The altitude and the surface temperature distribution patterns were correlated with the vegetation indexes. The slope classes were very homogeneous, predominantly with declivities between 8 to 20 %, characterized as wavy relief. This study made possible the characterization and monitoring of coffee lands and its results may be instrumental in decision-making processes related to coffee management.

  6. Vegetation mapping of the Mond Protected Area of Bushehr Province (south-west Iran).

    Science.gov (United States)

    Mehrabian, Ahmadreza; Naqinezhad, Alireza; Mahiny, Abdolrassoul Salman; Mostafavi, Hossein; Liaghati, Homan; Kouchekzadeh, Mohsen

    2009-03-01

    Arid regions of the world occupy up to 35% of the earth's surface, the basis of various definitions of climatic conditions, vegetation types or potential for food production. Due to their high ecological value, monitoring of arid regions is necessary and modern vegetation studies can help in the conservation and management of these areas. The use of remote sensing for mapping of desert vegetation is difficult due to mixing of the spectral reflectance of bright desert soils with the weak spectral response of sparse vegetation. We studied the vegetation types in the semiarid to arid region of Mond Protected Area, south-west Iran, based on unsupervised classification of the Spot XS bands and then produced updated maps. Sixteen map units covering 12 vegetation types were recognized in the area based on both field works and satellite mapping. Halocnemum strobilaceum and Suaeda fruticosa vegetation types were the dominant types and Ephedra foliata, Salicornia europaea-Suaeda heterophylla vegetation types were the smallest. Vegetation coverage decreased sharply with the increase in salinity towards the coastal areas of the Persian Gulf. The highest vegetation coverage belonged to the riparian vegetation along the Mond River, which represents the northern boundary of the protected area. The location of vegetation types was studied on the separate soil and habitat diversity maps of the study area, which helped in final refinements of the vegetation map produced.

  7. Increasing the Accuracy of Mapping Urban Forest Carbon Density by Combining Spatial Modeling and Spectral Unmixing Analysis

    Directory of Open Access Journals (Sweden)

    Hua Sun

    2015-11-01

    Full Text Available Accurately mapping urban vegetation carbon density is challenging because of complex landscapes and mixed pixels. In this study, a novel methodology was proposed that combines a linear spectral unmixing analysis (LSUA with a linear stepwise regression (LSR, a logistic model-based stepwise regression (LMSR and k-Nearest Neighbors (kNN, to map the forest carbon density of Shenzhen City of China, using Landsat 8 imagery and sample plot data collected in 2014. The independent variables that contributed to statistically significantly improving the fit of a model to data and reducing the sum of squared errors were first selected from a total of 284 spectral variables derived from the image bands. The vegetation fraction from LSUA was then added as an independent variable. The results obtained using cross-validation showed that: (1 Compared to the methods without the vegetation information, adding the vegetation fraction increased the accuracy of mapping carbon density by 1%–9.3%; (2 As the observed values increased, the LSR and kNN residuals showed overestimates and underestimates for the smaller and larger observations, respectively, while LMSR improved the systematical over and underestimations; (3 LSR resulted in illogically negative and unreasonably large estimates, while KNN produced the greatest values of root mean square error (RMSE. The results indicate that combining the spatial modeling method LMSR and the spectral unmixing analysis LUSA, coupled with Landsat imagery, is most promising for increasing the accuracy of urban forest carbon density maps. In addition, this method has considerable potential for accurate, rapid and nondestructive prediction of urban and peri-urban forest carbon stocks with an acceptable level of error and low cost.

  8. Beyond leaf color: Comparing camera-based phenological metrics with leaf biochemical, biophysical, and spectral properties throughout the growing season of a temperate deciduous forest

    Science.gov (United States)

    Yang, Xi; Tang, Jianwu; Mustard, John F.

    2014-03-01

    Plant phenology, a sensitive indicator of climate change, influences vegetation-atmosphere interactions by changing the carbon and water cycles from local to global scales. Camera-based phenological observations of the color changes of the vegetation canopy throughout the growing season have become popular in recent years. However, the linkages between camera phenological metrics and leaf biochemical, biophysical, and spectral properties are elusive. We measured key leaf properties including chlorophyll concentration and leaf reflectance on a weekly basis from June to November 2011 in a white oak forest on the island of Martha's Vineyard, Massachusetts, USA. Concurrently, we used a digital camera to automatically acquire daily pictures of the tree canopies. We found that there was a mismatch between the camera-based phenological metric for the canopy greenness (green chromatic coordinate, gcc) and the total chlorophyll and carotenoids concentration and leaf mass per area during late spring/early summer. The seasonal peak of gcc is approximately 20 days earlier than the peak of the total chlorophyll concentration. During the fall, both canopy and leaf redness were significantly correlated with the vegetation index for anthocyanin concentration, opening a new window to quantify vegetation senescence remotely. Satellite- and camera-based vegetation indices agreed well, suggesting that camera-based observations can be used as the ground validation for satellites. Using the high-temporal resolution dataset of leaf biochemical, biophysical, and spectral properties, our results show the strengths and potential uncertainties to use canopy color as the proxy of ecosystem functioning.

  9. Detecting creeping thistle in sugar beet fields using vegetation indices

    DEFF Research Database (Denmark)

    Kazmi, Syed Wajahat Ali Shah; Garcia Ruiz, Francisco Jose; Nielsen, Jon

    2015-01-01

    In this article, we address the problem of thistle detection in sugar beet fields under natural, outdoor conditions. In our experiments, we used a commercial color camera and extracted vegetation indices from the images. A total of 474 field images of sugar beet and thistles were collected....... Stepwise linear regression selected nine out of 14 features and offered the highest accuracy of 97%. The results of LDA and MD were fairly close, making them both equally preferable. Finally, the results were validated by annotating images containing both sugar beet and thistles using the trained...... classifiers. The validation experiments showed that sunlight followed by the size of the plant, which is related to its growth stage, are the two most important factors affecting the classification. In this study, the best results were achieved for images of young sugar beet (in the seventh week) under...

  10. Tree species mapping in tropical forests using multi-temporal imaging spectroscopy: Wavelength adaptive spectral mixture analysis

    Science.gov (United States)

    Somers, B.; Asner, G. P.

    2014-09-01

    The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among co-existing species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection in Multiple Endmember Spectral Mixture Analysis (MESMA). The temporal analysis provided a way to incorporate species phenology while feature selection indicated the best phenological time and best spectral feature set to optimize the separability between tree species. Instead of using the same set of spectral bands throughout the image which is the standard approach in MESMA, our modified Wavelength Adaptive Spectral Mixture Analysis (WASMA) approach allowed the spectral subsets to vary on a per pixel basis. As such we were able to optimize the spectral separability between the tree species present in each pixel. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively assessed using both simulated and actual hyperspectral image time-series. With a Cohen's Kappa coefficient of 0.65, WASMA provided a more accurate tree species map compared to conventional MESMA (Kappa = 0.54; p-value < 0.05. The flexible or adaptive use of band sets in WASMA provides an interesting avenue to address spectral similarities in complex vegetation canopies.

  11. Quantitative indicators of fruit and vegetable consumption

    OpenAIRE

    Dagmar Kozelová; Dana Országhová; Milan Fiľa; Zuzana Čmiková

    2015-01-01

    The quantitative research of the market is often based on surveys and questionnaires which are finding out the behavior of customers in observed areas. Before purchasing process consumers consider where they will buy fruit and vegetables, what kind to choose and in what quantity of goods. Consumers' behavior is affected by the factors as: regional gastronomic traditions, price, product appearance, aroma, place of buying, own experience and knowledge, taste preferences as well as specific heal...

  12. Use of satellite imagery to identify vegetation cover changes following the Waldo Canyon Fire event, Colorado, 2012-2013

    Science.gov (United States)

    Cole, Christopher J.; Friesen, Beverly A.; Wilson, Earl M.

    2014-01-01

    The Waldo Canyon Fire of 2012 was one of the most destructive wildfire events in Colorado history. The fire burned a total of 18,247 acres, claimed 2 lives, and destroyed 347 homes. The Waldo Canyon Fire continues to pose challenges to nearby communities. In a preliminary emergency assessment conducted in 2012, the U.S. Geological Survey (USGS) concluded that drainage basins within and near the area affected by the Waldo Canyon Fire pose a risk for future debris flow events. Rainfall over burned, formerly vegetated surfaces resulted in multiple flood and debris flow events that affected the cities of Colorado Springs and Manitou Springs in 2013. One fatality resulted from a mudslide near Manitou Springs in August 2013. Federal, State, and local governments continue to monitor these hazards and other post-fire effects, along with the region’s ecological recovery. At the request of the Colorado Springs Office of Emergency Management, the USGS Special Applications Science Center developed a geospatial product to identify vegetation cover changes following the 2012 Waldo Canyon Fire event. Vegetation cover was derived from July 2012 WorldView-2 and September 2013 QuickBird multispectral imagery at a spatial resolution of two meters. The 2012 image was collected after the fire had reached its maximum extent. Per-pixel increases and decreases in vegetation cover were identified by measuring spectral changes that occurred between the 2012 and 2013 image dates. A Normalized Difference Vegetation Index (NDVI), and Green-Near Infrared Index (GRNIR) were computed from each image. These spectral indices are commonly used to characterize vegetation cover and health condition, due to their sensitivity to detect foliar chlorophyll content. Vector polygons identifying surface-cover feature boundaries were derived from the 2013 imagery using image segmentation software. This geographic software groups similar image pixels into vector objects based upon their spatial and spectral

  13. Optimization of contrast-enhanced spectral mammography depending on clinical indication.

    Science.gov (United States)

    Dromain, Clarisse; Canale, Sandra; Saab-Puong, Sylvie; Carton, Ann-Katherine; Muller, Serge; Fallenberg, Eva Maria

    2014-10-01

    The objective is to optimize low-energy (LE) and high-energy (HE) exposure parameters of contrast-enhanced spectral mammography (CESM) examinations in four different clinical applications for which different levels of average glandular dose (AGD) and ratios between LE and total doses are required. The optimization was performed on a Senographe DS with a SenoBright® upgrade. Simulations were performed to find the optima by maximizing the contrast-to-noise ratio (CNR) on the recombined CESM image using different targeted doses and LE image quality. The linearity between iodine concentration and CNR as well as the minimal detectable iodine concentration was assessed. The image quality of the LE image was assessed on the CDMAM contrast-detail phantom. Experiments confirmed the optima found on simulation. The CNR was higher for each clinical indication than for SenoBright®, including the screening indication for which the total AGD was 22% lower. Minimal iodine concentrations detectable in the case of a 3-mm-diameter round tumor were 12.5% lower than those obtained for the same dose in the clinical routine. LE image quality satisfied EUREF acceptable limits for threshold contrast. This newly optimized set of acquisition parameters allows increased contrast detectability compared to parameters currently used without a significant loss in LE image quality.

  14. Detection of plum pox virus infection in selection plum trees using spectral imaging

    Science.gov (United States)

    Angelova, Liliya; Stoev, Antoniy; Borisova, Ekaterina; Avramov, Latchezar

    2016-01-01

    Plum pox virus (PPV) is among the most studied viral diseases in the world in plants. It is considered to be one of the most devastating diseases of stone fruits in terms of agronomic impact and economic importance. Noninvasive, fast and reliable techniques are required for evaluation of the pathology in selection trees with economic impact. Such advanced tools for PPV detection could be optical techniques as light-induced fluorescence and diffuse reflectance spectroscopies. Specific regions in the electromagnetic spectra have been found to provide information about the physiological stress in plants, and consequently, diseased plants usually exhibit different spectral signature than non-stressed healthy plants in those specific ranges. In this study spectral reflectance and chlorophyll fluorescence were used for the identification of biotic stress caused by the pox virus on plum trees. The spectral responses of healthy and infected leaves from cultivars, which are widespread in Bulgaria were investigated. The two applied techniques revealed statistically significant differences between the spectral data of healthy plum leaves and those infected by PPV in the visible and near-infrared spectral ranges. Their application for biotic stress detection helps in monitoring diseases in plants using the different plant spectral properties in these spectral ranges. The strong relationship between the results indicates the applicability of diffuse reflectance and fluorescence techniques for conducting health condition assessments of vegetation and their importance for plant protection practices.

  15. Field-scale sensitivity of vegetation discrimination to hyperspectral reflectance and coupled statistics

    DEFF Research Database (Denmark)

    Manevski, Kiril; Jabloun, Mohamed; Gupta, Manika

    2016-01-01

    a more powerful input to a nonparametric analysis for discrimination at the field scale, when compared with unaltered reflectance and parametric analysis. However, the discrimination outputs interact and are very sensitive to the number of observations - an important implication for the design......Remote sensing of land covers utilizes an increasing number of methods for spectral reflectance processing and its accompanying statistics to discriminate between the covers’ spectral signatures at various scales. To this end, the present chapter deals with the field-scale sensitivity...... of the vegetation spectral discrimination to the most common types of reflectance (unaltered and continuum-removed) and statistical tests (parametric and nonparametric analysis of variance). It is divided into two distinct parts. The first part summarizes the current knowledge in relation to vegetation...

  16. Leaf Phenology of Amazonian Canopy Trees as Revealed by Spectral and Physiochemical Measurements

    Science.gov (United States)

    Chavana-Bryant, C.; Gerard, F. F.; Malhi, Y.; Enquist, B. J.; Asner, G. P.

    2013-12-01

    The phenological dynamics of terrestrial ecosystems reflect the response of the Earth's biosphere to inter- and intra-annual dynamics of climatic and hydrological regimes. Some Dynamic Global Vegetation Models (GDVMs) have predicted that by 2050 the Amazon rainforest will begin to dieback (Cox et al. 2000, Nature) or that the ecosystem will become unsustainable (Salazar et al. 2007, GRL). One major component in DGVMs is the simulation of vegetation phenology, however, modelers are challenged with the estimation of tropical phenology which is highly complex. Current modeled phenology is based on observations of temperate vegetation and accurate representation of tropical phenology is long overdue. Remote sensing (RS) data are a key tool in monitoring vegetation dynamics at regional and global scales. Of the many RS techniques available, time-series analysis of vegetation indices (VIs) has become the most common approach in monitoring vegetation phenology (Samanta et al. 2010, GRL; Bradley et al. 2011, GCB). Our research focuses on investigating the influence that age related variation in the spectral reflectance and physiochemical properties of leaves may have on VIs of tropical canopies. In order to do this, we collected a unique leaf and canopy phenological dataset at two different Amazonian sites: Inselberg, French Guyana (FG) and Tambopata, Peru (PE). Hyperspectral reflectance measurements were collected from 4,102 individual leaves sampled to represent different leaf ages and vertical canopy positions (top, mid and low canopy) from 20 different canopy tree species (8 in FG and 12 in PE). These leaf spectra were complemented with 1) leaf physical measurements: fresh and dry weight, area and thickness, LMA and LWC and 2) leaf chemical measurements: %N, %C, %P, C:N and d13C. Canopy level observations included top-of-canopy reflectance measurements obtained using a multispectral 16-band radiometer, leaf demography (tot. number and age distribution) and branch

  17. The Potential of Forest Biomass Inversion Based on Vegetation Indices Using Multi-Angle CHRIS/PROBA Data

    Directory of Open Access Journals (Sweden)

    Qiang Wang

    2016-10-01

    Full Text Available Multi-angle remote sensing can either be regarded as an added source of uncertainty for variable retrieval, or as a source of additional information, which enhances variable retrieval compared to traditional single-angle observation. However, the magnitude of these angular and band effects for forest structure parameters is difficult to quantify. We used the Discrete Anisotropic Radiative Transfer (DART model and the Zelig model to simulate the forest canopy Bidirectional Reflectance Distribution Factor (BRDF in order to build a look-up table, and eight vegetation indices were used to assess the relationship between BRDF and forest biomass in order to find the sensitive angles and bands. Further, the European Space Agency (ESA mission, Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy (CHRIS-PROBA and field sample measurements, were selected to test the angular and band effects on forest biomass retrieval. The results showed that the off-nadir vegetation indices could predict the forest biomass more accurately than the nadir. Additionally, we found that the viewing angle effect is more important, but the band effect could not be ignored, and the sensitive angles for extracting forest biomass are greater viewing angles, especially around the hot and dark spot directions. This work highlighted the combination of angles and bands, and found a new index based on the traditional vegetation index, Atmospherically Resistant Vegetation Index (ARVI, which is calculated by combining sensitive angles and sensitive bands, such as blue band 490 nm/−55°, green band 530 nm/55°, and the red band 697 nm/55°, and the new index was tested to improve the accuracy of forest biomass retrieval. This is a step forward in multi-angle remote sensing applications for mining the hidden relationship between BRDF and forest structure information, in order to increase the utilization efficiency of remote sensing data.

  18. Biodiversity Measurement Using Indices Based on Hyperspectral Reflectance on the Coast of Lagos

    Science.gov (United States)

    Omodanisi, E. O.; Salami, A. T.

    2013-12-01

    highest occurring frequency among the entire plots. Thus they were used to distinguish relatively healthy from relatively unhealthy vegetation and it was statistically higher at F-ratio 4.825 (p0.01, rho - correlation coefficient. (Source: Author: 2012) Field Spectral Indices Measurement The measurement above is the averaged value for the entire transect in each plot.(Source: Author, 2012)

  19. Vegetation Fraction Mapping with High Resolution Multispectral Data in the Texas High Plains

    Science.gov (United States)

    Oshaughnessy, S. A.; Gowda, P. H.; Basu, S.; Colaizzi, P. D.; Howell, T. A.; Schulthess, U.

    2010-12-01

    Land surface models use vegetation fraction to more accurately partition latent, sensible and soil heat fluxes from a partially vegetated surface as it affects energy and moisture exchanges between the earth’s surface and atmosphere. In recent years, there is interest to integrate vegetation fraction data into intelligent irrigation scheduling systems to avoid false positive signals to irrigate. Remote sensing can facilitate the collection of vegetation fraction information on individual fields over large areas in a timely and cost-effective manner. In this study, we developed and evaluated a set of vegetation fraction models using least square regression and artificial neural network (ANN) techniques using RapidEye satellite data (6.5 m spatial resolution and on-demand temporal resolution). Four images were acquired during the 2010 summer growing season, covering bare soil to full crop cover conditions, over the USDA-ARS-Conservation and Production Research Laboratory in Bushland, Texas [350 11' N, 1020 06' W; 1,170 m elevation MSL]. Spectral signatures were extracted from 25 ground truth locations with geographic coordinates. Vegetation fraction information was derived from digital photos taken at the time of image acquisition using a supervised classification technique. Comparison of performance statistics indicate that ANN performed slightly better than least square regression models.

  20. Ten Years of Post-Fire Vegetation Recovery following the 2007 Zaca Fire using Landsat Satellite Imagery

    Science.gov (United States)

    Hallett, J. K. E.; Miller, D.; Roberts, D. A.

    2017-12-01

    Forest fires play a key role in shaping eco-systems. The risk to vegetation depends on the fire regime, fuel conditions (age and amount), fire temperature, and physiological characteristics such as bark thickness and stem diameter. The 2007 Zaca Fire (24 kilometers NE of Buellton, Santa Barbara County, California) burned 826.4 km2 over the course of 2 months. In this study, we used a time series of Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager imagery, to evaluate plant burn severity and post fire recovery as defined into classes of above average recovery, normal recovery, and below average recovery. We spectrally unmixed the images into green vegetation (GV), non-photosynthetic vegetation (NPV), soil surface (SOIL), and ash with a spectral library developed using Constrained Reference Endmember Selection (CRES). We delineated the fire perimeter using the differenced Normalized Burn Ratio (dNBR) and evaluated changes in this index and the Normalized Difference Vegetation Index through time. The results showed an immediate decline in GV and NPV fractions, with a rise in soil and ash fractions directly following the fire, with a slow recovery in GV fraction and a loss of bare soil cover. The was a sharp increase in the ash fraction following the fire and gradual decrease in the year after. Most areas have recovered as of 2017, with prominent recovery in the center of the burn scar and reduced recovery in areas to the south. These results indicate how post-fire vegetation varies based on initial burn severity and pre-fire GV and NPV fractions.

  1. Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations

    Science.gov (United States)

    de Moura, Yhasmin Mendes; Galvão, Lênio Soares; Hilker, Thomas; Wu, Jin; Saleska, Scott; do Amaral, Cibele Hummel; Nelson, Bruce Walker; Lopes, Aline Pontes; Wiedeman, Kenia K.; Prohaska, Neill; de Oliveira, Raimundo Cosme; Machado, Carolyne Bueno; Aragão, Luiz E. O. C.

    2017-09-01

    The association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this study, we used a tower-mounted hyperspectral camera in an eastern Amazon forest to assess how canopy spectral signals of three species are linked with phenological processes in the 2012 dry season. We explored different approaches to disentangle the spectral components of canopy phenology processes and analyze their variations over time using 17 images acquired by the camera. The methods included linear spectral mixture analysis (SMA); principal component analysis (PCA); continuum removal (CR); and first-order derivative analysis. In addition, three vegetation indices potentially sensitive to leaf flushing, leaf loss and leaf area index (LAI) were calculated: the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and the entitled Green-Red Normalized Difference (GRND) index. We inspected also the consistency of the camera observations using Moderate Resolution Imaging Spectroradiometer (MODIS) and available phenological data on new leaf production and LAI of young, mature and old leaves simulated by a leaf demography-ontogeny model. The results showed a diversity of phenological responses during the 2012 dry season with related changes in canopy structure and greenness values. Because of the differences in timing and intensity of leaf flushing and leaf shedding, Erisma uncinatum, Manilkara huberi and Chamaecrista xinguensis presented different green vegetation (GV) and non-photosynthetic vegetation (NPV) SMA fractions; distinct PCA scores; changes in depth, width and area of the 681-nm chlorophyll absorption band; and variations over time in the EVI, GRND and NDVI. At the end of dry season, GV increased for Erisma uncinatum, while NPV increased for Chamaecrista xinguensis. For Manilkara huberi, the NPV first increased in the beginning of August and then decreased toward

  2. Hamiltonian indices and rational spectral densities

    Science.gov (United States)

    Byrnes, C. I.; Duncan, T. E.

    1980-01-01

    Several (global) topological properties of various spaces of linear systems, particularly symmetric, lossless, and Hamiltonian systems, and multivariable spectral densities of fixed McMillan degree are announced. The study is motivated by a result asserting that on a connected but not simply connected manifold, it is not possible to find a vector field having a sink as its only critical point. In the scalar case, this is illustrated by showing that only on the space of McMillan degree = /Cauchy index/ = n, scalar transfer functions can one define a globally convergent vector field. This result holds both in discrete-time and for the nonautonomous case. With these motivations in mind, theorems of Bochner and Fogarty are used in showing that spaces of transfer functions defined by symmetry conditions are, in fact, smooth algebraic manifolds.

  3. Exploring the Potential of WorldView-2 Red-Edge Band-Based Vegetation Indices for Estimation of Mangrove Leaf Area Index with Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Yuanhui Zhu

    2017-10-01

    Full Text Available To accurately estimate leaf area index (LAI in mangrove areas, the selection of appropriate models and predictor variables is critical. However, there is a major challenge in quantifying and mapping LAI using multi-spectral sensors due to the saturation effects of traditional vegetation indices (VIs for mangrove forests. WorldView-2 (WV2 imagery has proven to be effective to estimate LAI of grasslands and forests, but the sensitivity of its vegetation indices (VIs has been uncertain for mangrove forests. Furthermore, the single model may exhibit certain randomness and instability in model calibration and estimation accuracy. Therefore, this study aims to explore the sensitivity of WV2 VIs for estimating mangrove LAI by comparing artificial neural network regression (ANNR, support vector regression (SVR and random forest regression (RFR. The results suggest that the RFR algorithm yields the best results (RMSE = 0.45, 14.55% of the average LAI, followed by ANNR (RMSE = 0.49, 16.04% of the average LAI, and then SVR (RMSE = 0.51, 16.56% of the average LAI algorithms using 5-fold cross validation (CV using all VIs. Quantification of the variable importance shows that the VIs derived from the red-edge band consistently remain the most important contributor to LAI estimation. When the red-edge band-derived VIs are removed from the models, estimation accuracies measured in relative RMSE (RMSEr decrease by 3.79%, 2.70% and 4.47% for ANNR, SVR and RFR models respectively. VIs derived from red-edge band also yield better accuracy compared with other traditional bands of WV2, such as near-infrared-1 and near-infrared-2 band. Furthermore, the estimated LAI values vary significantly across different mangrove species. The study demonstrates the utility of VIs of WV2 imagery and the selected machine-learning algorithms in developing LAI models in mangrove forests. The results indicate that the red-edge band of WV2 imagery can help alleviate the saturation

  4. River floodplain vegetation classification using multi-temporal high-resolution colour infrared UAV imagery.

    NARCIS (Netherlands)

    van Iersel, W.K.; Straatsma, M.W.; Addink, E.A.; Middelkoop, H.

    2016-01-01

    To evaluate floodplain functioning, monitoring of its vegetation is essential. Although airborne imagery is widely applied for this purpose, classification accuracy (CA) remains low for grassland (< 88%) and herbaceous vegetation (<57%) due to the spectral and structural similarity of these

  5. [Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

    Science.gov (United States)

    Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

    2015-05-01

    Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

  6. Synergy between LIDAR and RADARSAT-2 images for the recognition of vegetation structures in the coastal wetlands of the Danube Delta

    Science.gov (United States)

    Niculescu, Simona; Lardeux, Cédric; Grigoras, Ion; Hanganu, Jenica; David, Laurence

    2014-05-01

    indices such as, for instance, the intensity of the four polarizations, the span and the polarimetric entropy. Entropy is very sensitive to vegetation density; the thicker the vegetation, the higher the entropy becomes. The approach allowed us to obtain valuable information regarding different types of exploitation of the reed (cut or burned reed). Moreover, the exploitation of the SPOT 5 spectral information was made possible due to the calibration carried out using spectrometers to perform spectral measurements in the areas previously identified on the images.

  7. Vegetation Index and Phenology (VIP) Vegetation Indices Monthly Global 0.05Deg CMG V004

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Vegetation Index and Phenology (VIP) global datasets were created using...

  8. Temporal reflectance changes in vegetables

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2009-01-01

    Quality control in the food industry is often performed by measuring various chemical compounds of the food involved. We propose an imaging concept for acquiring high quality multispectral images to evaluate changes of carrots and celeriac over a period of 14 days. Properties originating...... in the surface chemistry of vegetables may be captured in an integrating sphere illumination which enables the creation of detailed surface chemistry maps with a good combination of spectral and spatial resolutions. Prior to multispectral image recording, the vegetables were prefried and frozen at -30Â......°C for four months. During the 14 days of image recording, the vegetables were kept at +5°C in refrigeration. In this period, surface changes and thereby reflectance properties were very subtle. To describe this small variation we employed advanced statistical techniques to search a large featurespace...

  9. Vegetation Mapping of the Mond Protected Area of Bushehr Provice (SW Iran)

    OpenAIRE

    Mehrabian, Ahmadreza; Mahiny, Abdolrassoul Salman; Mostafavi, Hossein; Liaghati, Homan

    2010-01-01

    The current study is a new approach to vegetation mapping in Iran using remote sensing (RS) and the geographic information system (GIS). One of the most important problems in remote sensing of desert vegetation is that the reflectance from soil and rocks is often much greater than that of sparse vegetation and this makes it difficult to separate out the vegetation signal (Gates et al. 1965); and there is spectral variability within shrubs of the same species (Duncant et al., 1993). These prop...

  10. Analysis and Mapping of the Spectral Characteristics of Fractional Green Cover in Saline Wetlands (NE Spain Using Field and Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Manuela Domínguez-Beisiegel

    2016-07-01

    Full Text Available Inland saline wetlands are complex systems undergoing continuous changes in moisture and salinity and are especially vulnerable to human pressures. Remote sensing is helpful to identify vegetation change in semi-arid wetlands and to assess wetland degradation. Remote sensing-based monitoring requires identification of the spectral characteristics of soils and vegetation and their correspondence with the vegetation cover and soil conditions. We studied the spectral characteristics of soils and vegetation of saline wetlands in Monegros, NE Spain, through field and satellite images. Radiometric and complementary field measurements in two field surveys in 2007 and 2008 were collected in selected sites deemed as representative of different soil moisture, soil color, type of vegetation, and density. Despite the high local variability, we identified good relationships between field spectral data and Quickbird images. A methodology was established for mapping the fraction of vegetation cover in Monegros and other semi-arid areas. Estimating vegetation cover in arid wetlands is conditioned by the soil background and by the occurrence of dry and senescent vegetation accompanying the green component of perennial salt-tolerant plants. Normalized Difference Vegetation Index (NDVI was appropriate to map the distribution of the vegetation cover if the green and yellow-green parts of the plants are considered.

  11. Comparative study of thylakoid membranes in terminal heterocysts and vegetative cells from two cyanobacteria, Rivularia M-261 and Anabaena variabilis, by fluorescence and absorption spectral microscopy.

    Science.gov (United States)

    Nozue, Shuho; Katayama, Mitsunori; Terazima, Masahide; Kumazaki, Shigeichi

    2017-09-01

    Heterocyst is a nitrogen-fixing cell differentiated from a cell for oxygen-evolving photosynthesis (vegetative cell) in some filamentous cyanobacteria when fixed nitrogen (e.g., ammonia and nitrate) is limited. Heterocysts appear at multiple separated positions in a single filament with an interval of 10-20 cells in some genera (including Anabaena variabilis). In other genera, a single heterocyst appears only at the basal terminal in a filament (including Rivularia M-261). Such morphological diversity may necessitate different properties of heterocysts. However, possible differences in heterocysts have largely remained unexplored due to the minority of heterocysts among major vegetative cells. Here, we have applied spectroscopic microscopy to Rivularia and A. variabilis to analyze their thylakoid membranes in individual cells. Absorption and fluorescence spectral imaging enabled us to estimate concentrations and interconnections of key photosynthetic components like photosystem I (PSI), photosystem II (PSII) and subunits of light-harvesting phycobilisome including phycocyanin (PC). The concentration of PC in heterocysts of Rivularia is far higher than that of A. variabilis. Fluorescence quantum yield of PC in Rivularia heterocysts was found to be virtually the same as those in its vegetative cells, while fluorescence quantum yield of PC in A. variabilis heterocysts was enhanced in comparison with its vegetative cells. PSI concentration in the thylakoid membranes of heterocysts seems to remain nearly the same as those of the vegetative cells in both the species. The average stoichiometric ratio between PSI monomer and PC hexamer in Rivularia heterocysts is estimated to be about 1:1. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Automated vegetation classification using Thematic Mapper Simulation data

    Science.gov (United States)

    Nedelman, K. S.; Cate, R. B.; Bizzell, R. M.

    1983-01-01

    The present investigation is concerned with the results of a study of Thematic Mapper Simulation (TMS) data. One of the objectives of the study was related to an evaluation of the usefulness of the Thematic Mapper's (TM) improved spatial resolution and spectral coverage. The study was undertaken as part of a preparation for the efficient incorporation of Landsat 4 data into ongoing technology development in remote sensing. The study included an application of automated Landsat vegetation classification technology to TMS data. Results of comparing TMS data to Multispectral Scanner (MSS) data were found to indicate that all field definition, crop type discrimination, and subsequent proportion estimation may be greatly increased with the availability of TM data.

  13. Leds used as spectral selective light detectors in remote sensing techniques

    International Nuclear Information System (INIS)

    Weber, C; Tocho, J O; Rodriguez, E J; Acciaresi, H A

    2011-01-01

    Remote sensing has been commonly considered as an effective technique in developing precision agriculture tools. Ground based and satellite spectral sensors have wide uses to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies as well as vegetation ground cover. Usually in-field remote sensing technologies use either a combination of interferential filters and photodiodes or different compact spectrometers to separate the spectral regions of interest. In this paper we present a new development of a sensor with LEDs used as spectrally selective photodetectors. Its performance was compared with a photodiode-filter sensor used in agronomic applications. Subsequent measurements of weed cover degree were performed and compared with other methodologies. Results show that the new LEDs based sensor has similar features that conventional ones to determining the weed soil cover degree; while LEDs based sensor has comparative advantages related its very low manufacturing cost and its robustness compatible with agricultural field applications.

  14. Remote sensing applications for monitoring rangeland vegetation ...

    African Journals Online (AJOL)

    Remote sensing techniques hold considerable promise for the inventory and monitoring of natural resources on rangelands. A significant lack of information concerning basic spectral characteristics of range vegetation and soils has resulted in a lack of rangeland applications. The parameters of interest for range condition ...

  15. 3D documentation of outcrop by laser scanner – Filtration of vegetation

    Directory of Open Access Journals (Sweden)

    J. Kisztner

    2016-03-01

    Full Text Available This work deals with separation of vegetation from 3D data acquired by Terrestrial Laser Scanning for detecting more complex geological structures. Separation of vegetation is not an easy task. In many cases, the outcrop is not clear and the vegetation outgrows the outcrop. Therefore the separation of vegetation from 3D data is a task which requires adjustment of algorithms from image processing and remote sensing. By using cluster analysis and analysis of spectral behaviour we can detect vegetation from the rest of the scene and erase these points from the scene for detection of geological structures.

  16. Assessing Cd-induced stress from plant spectral response

    Science.gov (United States)

    Kancheva, Rumiana; Georgiev, Georgi

    2014-10-01

    Remote sensing plays a significant role in local, regional and global monitoring of land covers. Ecological concerns worldwide determine the importance of remote sensing applications for the assessment of soil conditions, vegetation health and identification of stress-induced changes. The extensive industrial growth and intensive agricultural land-use arise the serious ecological problem of environmental pollution associated with the increasing anthropogenic pressure on the environment. Soil contamination is a reason for degradation processes and temporary or permanent decrease of the productive capacity of land. Heavy metals are among the most dangerous pollutants because of their toxicity, persistent nature, easy up-take by plants and long biological half-life. This paper takes as its focus the study of crop species spectral response to Cd pollution. Ground-based experiments were performed, using alfalfa, spring barley and pea grown in Cd contaminated soils and in different hydroponic systems under varying concentrations of the heavy metal. Cd toxicity manifested itself by inhibition of plant growth and synthesis of photosynthetic pigments. Multispectral reflectance, absorbance and transmittance, as well as red and far red fluorescence were measured and examined for their suitability to detect differences in plant condition. Statistical analysis was performed and empirical relationships were established between Cd concentration, plant growth variables and spectral response Various spectral properties proved to be indicators of plant performance and quantitative estimators of the degree of the Cd-induced stress.

  17. UV-Vis-IR spectral complex refractive indices and optical properties of brown carbon aerosol from biomass burning

    Science.gov (United States)

    Sumlin, Benjamin J.; Heinson, Yuli W.; Shetty, Nishit; Pandey, Apoorva; Pattison, Robert S.; Baker, Stephen; Hao, Wei Min; Chakrabarty, Rajan K.

    2018-02-01

    Constraining the complex refractive indices, optical properties and size of brown carbon (BrC) aerosols is a vital endeavor for improving climate models and satellite retrieval algorithms. Smoldering wildfires are the largest source of primary BrC, and fuel parameters such as moisture content, source depth, geographic origin, and fuel packing density could influence the properties of the emitted aerosol. We measured in situ spectral (375-1047 nm) optical properties of BrC aerosols emitted from smoldering combustion of Boreal and Indonesian peatlands across a range of these fuel parameters. Inverse Lorenz-Mie algorithms used these optical measurements along with simultaneously measured particle size distributions to retrieve the aerosol complex refractive indices (m = n + iκ). Our results show that the real part n is constrained between 1.5 and 1.7 with no obvious functionality in wavelength (λ), moisture content, source depth, or geographic origin. With increasing λ from 375 to 532 nm, κ decreased from 0.014 to 0.003, with corresponding increase in single scattering albedo (SSA) from 0.93 to 0.99. The spectral variability of κ follows the Kramers-Kronig dispersion relation for a damped harmonic oscillator. For λ ≥ 532 nm, both κ and SSA showed no spectral dependency. We discuss differences between this study and previous work. The imaginary part κ was sensitive to changes in FPD, and we hypothesize mechanisms that might help explain this observation.

  18. Assessment of drought risk by using vegetation indices from remotely sensed data a perspective from hot and arid district of pakistan

    International Nuclear Information System (INIS)

    Tabassum, R.; Kahlid, A.

    2016-01-01

    The Shaheed Benazir Abad District is situated at the center of Sindh Province, which is one of the hottest and driest part of Pakistan. In the past few decades, the extreme and moderate droughts had been reported in the district with peak value -2.4 recorded using the Standardized Precipitation Index (SPI). In this study, satellite remote sensing and digital image processing techniques were used to monitor the drought conditions in the district. Multiple drought indices were calculated by using Thematic Mapper (TM) data of the Landsat satellite program, jointly managed by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), including Land Surface Temperature (LST), Normalized Vegetation Index (NDVI), Vegetation Condition Index (VCI) and Temperature Vegetation Index (TVX). These indices provided the agricultural drought conditions for the duration of 1992-2011. The VCI maps indicated the high drought conditions in the plain land, away from the built-up areas, while the proximity of the built-up land is under a moderate drought. However, in cultivated lands, the agriculture drought condition is not obvious due to canal irrigated cultivation. A drought in year 2011, was more severe than in the year 2000. It is an indication of climate change impacts in the region. (author)

  19. Optimization of lamp spectrum for vegetable growth

    Energy Technology Data Exchange (ETDEWEB)

    Prikupets, L.B.; Tikhomirov, A.A. [Institute of Biophysics, Krasnoyarsk (Russian Federation)

    1994-12-31

    Commmercial light sources were evaluated as to the optimum conditions for the production of tomatoes and cucumbers. Data is presented which corresponds to the maximum productivity and optimal spectral ratios. It is suggested that the commercial light sources evaluated were not efficient for the growing of the vegetables.

  20. Monitoring of vegetation dynamics and assessing vegetation response to drought in the Iberian Peninsula

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Haro, F. J.; Moreno, A.; Perez-Hoyos, A.; Gilabert, M. A.; Melia, J.; Belda, F.; Poquet, D.; Martinez, B.; Verger, A.

    2009-07-01

    Monitoring the vegetation activity over long time-scales is necessary to discern ecosystem response to climate variability. Spatial and temporally consistent estimates of the biophysical variables such as fractional vegetation cover (FVC) and leaf area index (LAI) have been obtained in the context of DULCINEA Project. We used long-term monthly climate statistics to build simple climatic indices (SPI, moisture index) at different time scales. From these indices, we estimated that the climatic disturbances affected both the growing season and the total amount of vegetation. This implies that the anomaly of vegetation cover is a good indicator of moisture condition and can be an important data source when used for detecting an monitoring drought in the Iberian Peninsula. The impact of climate variability on the vegetation dynamics has shown not to be the same for every region. We concluded that the relationships between vegetation anomaly and moisture availability are significant for the arid and semiarid areas. (Author) 6 refs.

  1. Monitoring of vegetation dynamics and assessing vegetation response to drought in the Iberian Peninsula

    International Nuclear Information System (INIS)

    Garcia-Haro, F. J.; Moreno, A.; Perez-Hoyos, A.; Gilabert, M. A.; Melia, J.; Belda, F.; Poquet, D.; Martinez, B.; Verger, A.

    2009-01-01

    Monitoring the vegetation activity over long time-scales is necessary to discern ecosystem response to climate variability. Spatial and temporally consistent estimates of the biophysical variables such as fractional vegetation cover (FVC) and leaf area index (LAI) have been obtained in the context of DULCINEA Project. We used long-term monthly climate statistics to build simple climatic indices (SPI, moisture index) at different time scales. From these indices, we estimated that the climatic disturbances affected both the growing season and the total amount of vegetation. This implies that the anomaly of vegetation cover is a good indicator of moisture condition and can be an important data source when used for detecting an monitoring drought in the Iberian Peninsula. The impact of climate variability on the vegetation dynamics has shown not to be the same for every region. We concluded that the relationships between vegetation anomaly and moisture availability are significant for the arid and semiarid areas. (Author) 6 refs.

  2. Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

    Directory of Open Access Journals (Sweden)

    Alfonso F. Torres-Rua

    2016-04-01

    Full Text Available Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains challenging due to coarse spatial and temporal resolution of existing remotely-sensed products. Furthermore, while preceding research on soil moisture using remote sensing (surface energy balance, weather parameters, and vegetation indices has demonstrated a relationship between these factors and soil moisture, practical continuous spatial quantification of the latter is still unavailable for use in water and agricultural management. In this study, a methodology is presented to estimate volumetric surface soil moisture by statistical selection from potential predictors that include vegetation indices and energy balance products derived from satellite (Landsat imagery and weather data as identified in scientific literature. This methodology employs a statistical learning machine called a Relevance Vector Machine (RVM to identify and relate the potential predictors to soil moisture by means of stratified cross-validation and forward variable selection. Surface soil moisture measurements from irrigated agricultural fields in Central Utah in the 2012 irrigation season were used, along with weather data, Landsat vegetation indices, and energy balance products. The methodology, data collection, processing, and estimation accuracy are presented and discussed.

  3. Quantifying seasonal dynamics of canopy structure and function using inexpensive narrowband spectral radiometers

    Science.gov (United States)

    Vierling, L. A.; Garrity, S. R.; Campbell, G.; Coops, N. C.; Eitel, J.; Gamon, J. A.; Hilker, T.; Krofcheck, D. J.; Litvak, M. E.; Naupari, J. A.; Richardson, A. D.; Sonnentag, O.; van Leeuwen, M.

    2011-12-01

    Increasing the spatial and temporal density of automated environmental sensing networks is necessary to quantify shifts in plant structure (e.g., leaf area index) and function (e.g., photosynthesis). Improving detection sensitivity can facilitate a mechanistic understanding by better linking plant processes to environmental change. Spectral radiometer measurements can be highly useful for tracking plant structure and function from diurnal to seasonal time scales and calibrating and validating satellite- and aircraft-based spectral measurements. However, dense ground networks of such instruments are challenging to establish due to the cost and complexity of automated instrument deployment. We therefore developed simple to operate, lightweight and inexpensive narrowband (~10nm bandwidth) spectral instruments capable of continuously measuring four to six discrete bands that have proven capacity to describe key physiological processes and structural features of plant canopies. These bands are centered at 530, 570, 675, 800, 880, and 970 nm to enable calculation of the physiological reflectance index (PRI), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and water band index (WBI) collected above and within vegetation canopies. To date, measurements have been collected above grassland, semi-arid shrub steppe, piñon-juniper woodland, dense conifer forest, mixed deciduous-conifer forest, and cropland canopies, with additional measurements collected along vertical transects through a temperate conifer rainforest. Findings from this work indicate not only that key shifts in plant phenology, physiology, and structure can be captured using such instruments, but that the temporally dense nature of the measurements can help to disentangle heretofore unreported complexities of simultaneous phenological and structural change on canopy reflectance.

  4. Combining vegetation index and model inversion methods for theextraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data

    DEFF Research Database (Denmark)

    Houborg, Rasmus Møller; Søgaard, Henrik; Bøgh, Eva

    2007-01-01

    for the inversion of a canopy reflectance model using Terra and Aqua MODIS multi-spectral, multi-temporal, and multi-angle reflectance observations to aid the determination of vegetation-specific physiological and structural canopy parameters. Land cover and site-specific inversion modeling was applied...

  5. A monitoring protocol for vegetation change on Irish peatland and heath

    Science.gov (United States)

    O'Connell, J.; Connolly, J.; Holden, N. M.

    2014-09-01

    Amendments to Articles 3.3 and 3.4 of the Kyoto Protocol have meant that detection of vegetation change may now form an interracial part of national soil carbon stocks. In this study multispectral multi-platform satellite data was processed to detect change to the surface vegetation of four peatland sites and one heath in Ireland. Spectral and spatial thresholds were used on difference images between master and slave data in the extraction of temporally invariant targets for multi-platform cross calibration. The Kolmogorov-Smirnov test was used to evaluate any difference in the cumulative probability distributions of the master, slave and calibrated slave data as expressed by the D statistic, with values reduced by an average of 89.7% due to the cross calibration procedure. A change detection model was created which incorporated a spatial threshold of 9 pixels and a standard deviation (SD) spectral threshold. Kappa accuracy values for the five sites ranged from 80 to 97%, showing that 1.5 SD was the optimum spectral threshold for detecting vegetation change. Change detection results showed mean percentage change ranging from 2.11 to 3.28% of total area and cumulative change over the observed time period of between 15.24 and 49.27% of total area.

  6. Spectral evolution of GRBs with negative spectral lag using Fermi GBM observations

    Science.gov (United States)

    Chakrabarti, Arundhati; Chaudhury, Kishor; Sarkar, Samir K.; Bhadra, Arunava

    2018-06-01

    The positive spectral lag of Gamma Ray Bursts (GRBs) is often explained in terms of hard-to-soft spectral evolution of GRB pulses. While positive lags of GRBs is very common, there are few GRB pulses that exhibits negative spectral lags. In the present work we examine whether negative lags of GRBs also can be interpreted in terms of spectral evolution of GRB pulses or not. Using Fermi-GBM data, we identify two GRBs, GRB 090426C and GRB 150213A, with clean pulses that exhibit negative spectral lag. An indication of soft to hard transition has been noticed for the negative spectral lag events from the spectral evolution study. The implication of the present findings on the models of GRB spectral lags are discussed.

  7. Using two classification schemes to develop vegetation indices of biological integrity for wetlands in West Virginia, USA.

    Science.gov (United States)

    Veselka, Walter; Rentch, James S; Grafton, William N; Kordek, Walter S; Anderson, James T

    2010-11-01

    Bioassessment methods for wetlands, and other bodies of water, have been developed worldwide to measure and quantify changes in "biological integrity." These assessments are based on a classification system, meant to ensure appropriate comparisons between wetland types. Using a local site-specific disturbance gradient, we built vegetation indices of biological integrity (Veg-IBIs) based on two commonly used wetland classification systems in the USA: One based on vegetative structure and the other based on a wetland's position in a landscape and sources of water. The resulting class-specific Veg-IBIs were comprised of 1-5 metrics that varied in their sensitivity to the disturbance gradient (R2=0.14-0.65). Moreover, the sensitivity to the disturbance gradient increased as metrics from each of the two classification schemes were combined (added). Using this information to monitor natural and created wetlands will help natural resource managers track changes in biological integrity of wetlands in response to anthropogenic disturbance and allows the use of vegetative communities to set ecological performance standards for mitigation banks.

  8. Vegetation Index and Phenology (VIP) Vegetation Indices 7Days Global 0.05Deg CMG V004

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Vegetation Index and Phenology (VIP) global datasets were created using...

  9. Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

    Science.gov (United States)

    Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

    2018-04-01

    Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

  10. Scaling dimensions in spectroscopy of soil and vegetation

    NARCIS (Netherlands)

    Malenovsky, Z.; Bartholomeus, H.; Weimar Acerbi, F.; Schopfer, J.T.; Painter, T.H.; Epema, G.F.; Bregt, A.K.

    2007-01-01

    The paper revises and clarifies definitions of the term scale and scaling conversions for imaging spectroscopy of soil and vegetation. We demonstrate a new four-dimensional scale concept that includes not only spatial but also the spectral, directional and temporal components. Three scaling remote

  11. MULTIMETRIC INDICES BASED ON VEGETATION DATA FOR ASSESSING ECOLOGICAL AND HYDROMORPHOLOGICAL QUALITY OF A MAN-REGULATED LAKE

    Directory of Open Access Journals (Sweden)

    R. Bolpagni

    2013-04-01

    Full Text Available A functional characterization of the littoral and shore vegetation was performed in the Lake Idro to assess its ecological quality and hydromorphological alteration. A detailed survey of hydro-hygrophilous vegetation was carried out in 2010-2012. Three multimetric indices were calculated: the MacroIMMI (the Italian macrophytic index for mid-size subalpine lakes with a maximum depth < 125 m, the SFI (Shorezone Functional Index, and the LHS (Lake Habitat Survey. The MacroIMMI (0.76 classified the lake in a good ecological status, although the dominant aquatic species were exotic (Elodea nuttallii and Lagarosiphon major. The SFI pointed out that the 50% of total shorelines displayed a very good or excellent conservation status; conversely, the LHS revealed high levels of morphological alteration coupled with rather good levels of habitat diversity, likely due to the high colonization rates of macrophytes along the lake shore. The lacustrine multimetric indices seem suitable for assessing the conservation status of mid-size lakes. However, for the present case-study, the metrics used require further implementation to suit the peculiarities of Italian subalpine lakes.

  12. Hydrological Controls on Floodplain Forest Phenology Assessed using Remotely Sensed Vegetation Indices

    Science.gov (United States)

    Lemon, M. G.; Keim, R.

    2017-12-01

    Although specific controls are not well understood, the phenology of temperate forests is generally thought to be controlled by photoperiod and temperature, although recent research suggests that soil moisture may also be important. The phenological controls of forested wetlands have not been thoroughly studied, and may be more controlled by site hydrology than other forests. For this study, remotely sensed vegetation indices were used to investigate hydrological controls on start-of-season timing, growing season length, and end-of-season timing at five floodplains in Louisiana, Arkansas, and Texas. A simple spring green-up model was used to determine the null spring start of season time for each site as a function of land surface temperature and photoperiod, or two remotely sensed indices: MODIS phenology data product and the MODIS Nadir Bidirectional Reflectance Distribution Function-Adjusted Reflectance (NBAR) product. Preliminary results indicate that topographically lower areas within the floodplain with higher flood frequency experience later start-of-season timing. In addition, start-of-season is delayed in wet years relative to predicted timing based solely on temperature and photoperiod. The consequences for these controls unclear, but results suggest hydrological controls on floodplain ecosystem structure and carbon budgets are likely at least partially expressed by variations in growing season length.

  13. Mapping invasive species and spectral mixture relationships with neotropical woody formations in southeastern Brazil

    Science.gov (United States)

    Amaral, Cibele H.; Roberts, Dar A.; Almeida, Teodoro I. R.; Souza Filho, Carlos R.

    2015-10-01

    Biological invasion substantially contributes to the increasing extinction rates of native vegetative species. The remote detection and mapping of invasive species is critical for environmental monitoring. This study aims to assess the performance of a Multiple Endmember Spectral Mixture Analysis (MESMA) applied to imaging spectroscopy data for mapping Dendrocalamus sp. (bamboo) and Pinus elliottii L. (slash pine), which are invasive plant species, in a Brazilian neotropical landscape within the tropical Brazilian savanna biome. The work also investigates the spectral mixture between these exotic species and the native woody formations, including woodland savanna, submontane and alluvial seasonal semideciduous forests (SSF). Visible to Shortwave Infrared (VSWIR) imaging spectroscopy data at one-meter spatial resolution were atmospherically corrected and subset into the different spectral ranges (VIS-NIR1: 530-919 nm; and NIR2-SWIR: 1141-2352 nm). The data were further normalized via continuum removal (CR). Multiple endmember selection methods, including Interactive Endmember Selection (IES), Endmember average root mean square error (EAR), Minimum average spectral angle (MASA) and Count-based (CoB) (collectively called EMC), were employed to create endmember libraries for the targeted vegetation classes. The performance of the MESMA was assessed at the pixel and crown scales. Statistically significant differences (α = 0.05) were observed between overall accuracies that were obtained at various spectral ranges. The infrared region (IR) was critical for detecting the vegetation classes using spectral data. The invasive species endmembers exhibited spectral patterns in the IR that were not observed in the native formations. Bamboo was characterized as having a high green vegetation (GV) fraction, lower non-photosynthetic vegetation (NPV) and a low shade fraction, while pine exhibited higher NPV and shade fractions. The invasive species showed a statistically

  14. Analytical treatment of the relationships between soil heat flux/net radiation ratio and vegetation indices

    International Nuclear Information System (INIS)

    Kustas, W.P.; Daughtry, C.S.T.; Oevelen, P.J. van

    1993-01-01

    Relationships between leaf area index (LAI) and midday soil heat flux/net radiation ratio (G/R n ) and two more commonly used vegetation indices (VIs) were used to analytically derive formulas describing the relationship between G/R n and VI. Use of VI for estimating G/R n may be useful in operational remote sensing models that evaluate the spatial variation in the surface energy balance over large areas. While previous experimental data have shown that linear equations can adequately describe the relationship between G/Rn and VI, this analytical treatment indicated that nonlinear relationships are more appropriate. Data over bare soil and soybeans under a range of canopy cover conditions from a humid climate and data collected over bare soil, alfalfa, and cotton fields in an arid climate were used to evaluate model formulations derived for LAI and G/R n , LAI and VI, and VI and G/R n . In general, equations describing LAI-G/R n and LAI-VI relationships agreed with the data and supported the analytical result of a nonlinear relationship between VI and G/R n . With the simple ratio (NIR/Red) as the VI, the nonlinear relationship with G/R n was confirmed qualitatively. But with the normalized difference vegetation index (NDVI), a nonlinear relationship did not appear to fit the data. (author)

  15. Classification of floodplain vegetation by data fusion of spectral (CASI) and LiDAR data

    NARCIS (Netherlands)

    Geerling, G.W.; Labrador-Garcia, M.; Clevers, J.G.P.W.; Ragas, A.M.J.; Smits, A.J.M.

    2007-01-01

    To safeguard the goals of flood protection and nature development, a river manager requires detailed and up-to-date information on vegetation structures in floodplains. In this study, remote-sensing data on the vegetation of a semi-natural floodplain along the river Waal in the Netherlands were

  16. Integrated High Resolution Monitoring of Mediterranean vegetation

    Science.gov (United States)

    Cesaraccio, Carla; Piga, Alessandra; Ventura, Andrea; Arca, Angelo; Duce, Pierpaolo; Mereu, Simone

    2017-04-01

    The study of the vegetation features in a complex and highly vulnerable ecosystems, such as Mediterranean maquis, leads to the need of using continuous monitoring systems at high spatial and temporal resolution, for a better interpretation of the mechanisms of phenological and eco-physiological processes. Near-surface remote sensing techniques are used to quantify, at high temporal resolution, and with a certain degree of spatial integration, the seasonal variations of the surface optical and radiometric properties. In recent decades, the design and implementation of global monitoring networks involved the use of non-destructive and/or cheaper approaches such as (i) continuous surface fluxes measurement stations, (ii) phenological observation networks, and (iii) measurement of temporal and spatial variations of the vegetation spectral properties. In this work preliminary results from the ECO-SCALE (Integrated High Resolution Monitoring of Mediterranean vegetation) project are reported. The project was manly aimed to develop an integrated system for environmental monitoring based on digital photography, hyperspectral radiometry , and micrometeorological techniques during three years of experimentation (2013-2016) in a Mediterranean site of Italy (Capo Caccia, Alghero). The main results concerned the analysis of chromatic coordinates indices from digital images, to characterized the phenological patterns for typical shrubland species, determining start and duration of the growing season, and the physiological status in relation to different environmental drought conditions; then the seasonal patterns of canopy phenology, was compared to NEE (Net Ecosystem Exchange) patterns, showing similarities. However, maximum values of NEE and ER (Ecosystem respiration), and short term variation, seemed mainly tuned by inter annual pattern of meteorological variables, in particular of temperature recorded in the months preceding the vegetation green-up. Finally, green signals

  17. Natural and artificial spectral edges in exoplanets

    Science.gov (United States)

    Lingam, Manasvi; Loeb, Abraham

    2017-09-01

    Technological civilizations may rely upon large-scale photovoltaic arrays to harness energy from their host star. Photovoltaic materials, such as silicon, possess distinctive spectral features, including an 'artificial edge' that is characteristically shifted in wavelength shortwards of the 'red edge' of vegetation. Future observations of reflected light from exoplanets would be able to detect both natural and artificial edges photometrically, if a significant fraction of the planet's surface is covered by vegetation or photovoltaic arrays, respectively. The stellar energy thus tapped can be utilized for terraforming activities by transferring heat and light from the day side to the night side on tidally locked exoplanets, thereby producing detectable artefacts.

  18. Responses of the reflectance indices PRI and NDVI to experimental warming and drought in European shrublands along a north–south climatic gradient

    DEFF Research Database (Denmark)

    Mänd, Pille; Hallik, Lea; Peñuelas, Josep

    2010-01-01

    NDVI680 [780 nm; 680 nm] using red spectral region, and NDVI570 [780 nm; 570 nm] using the same green spectral region as PRI. All three reflectance indices were significantly related to green LAIe and were able to detect changes in shrubland vegetation among treatments. In general warming treatment...... increased PRI and drought treatment reduced NDVI values. The significant treatment effect on photochemical efficiency of plants detected with PRI could not be detected by fluorescence measurements. However, we found canopy level measured PRI to be very sensitive to soil reflectance properties especially...

  19. Biological indication with the aid of submerged vegetation - potential and limits; Bioindikation mit Hilfe Hoeherer Wasserpflanzen - Moeglichkeiten und Grenzen

    Energy Technology Data Exchange (ETDEWEB)

    Schuetz, W.

    1991-12-31

    From 1986 to 1989 the submerged vegetation of the running waters of the `Schwaebische Alb` and `Oberschwaben` were investigated. The qualitative and quantitative distribution of macrophytes depends in the first place on the occurence of extreme discharges overlaying other factors influencing the distribution of macrophytes (trophical state). The effects of increasing eutrophication can be proved, too, by reconstructing the increase resp. decrease of suitable indicator-species [Groenlandia densa (L.) FOURR.] within a larger area. The effects of water-regulation measures with ensueing eutrophication can be demonstrated in the specific case of the submerged vegetation of the Danube river and the `suedbadische Oberrheinaue`. (orig.)

  20. Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

    Science.gov (United States)

    Huemmrich, Karl Fred; Gamon, John A.; Tweedie, Craig E.; Campbell, Petya K. Entcheva; Landis, David R.; Middleton, Elizabeth M.

    2013-01-01

    Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a

  1. Post-fire vegetation recovery in Portugal based on spot/vegetation data

    Science.gov (United States)

    Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

    2010-04-01

    A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

  2. Discrimination of growth and water stress in wheat by various vegetation indices through a clear a turbid atmosphere

    Science.gov (United States)

    Jackson, R. D.; Slater, P. M.; Pinter, P. J. (Principal Investigator)

    1982-01-01

    Reflectance data were obtained over a drought-stressed and a well-watered wheat plot with a hand-held radiometer having bands similar to the MSS bands of the LANDSAT satellites. Data for 48 clear days were interpolated to yield reflectance values for each day of the growing season, from planting until harvest. With an atmospheric path radiance model and LANDSAT-2 calibration data, the reflectance were used to simulate LANDSAT digital counts (not quantized) for the four LANDSAT bands for each day of the growing season, through a clear (approximately 100 km meteorological range) and a turbid (approximately 10 km meteorological range) atmosphere. Several ratios and linear combinations of bands were calculated using the simulated data, then assessed for their relative ability to discriminate vegetative growth and plant stress through the two atmospheres. The results show that water stress was not detected by any of the indices until after growth was retarded, and the sensitivity of the various indices to vegetation depended on plant growth stage and atmospheric path radiance.

  3. Broad-Band Spectral Indices Variability of BL Lacertae by Wavelet ...

    Indian Academy of Sciences (India)

    by Wavelet Method. Hao-Jing Zhang1,2,∗, Jing-Ming Bai1, Yu-Ying Bao3 & Xiong Zhang2. 1Yunnan Astronomical Observatory, National Astronomical Observatory, ... 3Department of Physics, Yuxi Teachers' College, Yuxi, Yunnan 653100, China. ∗ ... broad-band spectral indices—periodic variation—methods: numerical:.

  4. USGS Spectral Library Version 7

    Science.gov (United States)

    Kokaly, Raymond F.; Clark, Roger N.; Swayze, Gregg A.; Livo, K. Eric; Hoefen, Todd M.; Pearson, Neil C.; Wise, Richard A.; Benzel, William M.; Lowers, Heather A.; Driscoll, Rhonda L.; Klein, Anna J.

    2017-04-10

    We have assembled a library of spectra measured with laboratory, field, and airborne spectrometers. The instruments used cover wavelengths from the ultraviolet to the far infrared (0.2 to 200 microns [μm]). Laboratory samples of specific minerals, plants, chemical compounds, and manmade materials were measured. In many cases, samples were purified, so that unique spectral features of a material can be related to its chemical structure. These spectro-chemical links are important for interpreting remotely sensed data collected in the field or from an aircraft or spacecraft. This library also contains physically constructed as well as mathematically computed mixtures. Four different spectrometer types were used to measure spectra in the library: (1) Beckman™ 5270 covering the spectral range 0.2 to 3 µm, (2) standard, high resolution (hi-res), and high-resolution Next Generation (hi-resNG) models of Analytical Spectral Devices (ASD) field portable spectrometers covering the range from 0.35 to 2.5 µm, (3) Nicolet™ Fourier Transform Infra-Red (FTIR) interferometer spectrometers covering the range from about 1.12 to 216 µm, and (4) the NASA Airborne Visible/Infra-Red Imaging Spectrometer AVIRIS, covering the range 0.37 to 2.5 µm. Measurements of rocks, soils, and natural mixtures of minerals were made in laboratory and field settings. Spectra of plant components and vegetation plots, comprising many plant types and species with varying backgrounds, are also in this library. Measurements by airborne spectrometers are included for forested vegetation plots, in which the trees are too tall for measurement by a field spectrometer. This report describes the instruments used, the organization of materials into chapters, metadata descriptions of spectra and samples, and possible artifacts in the spectral measurements. To facilitate greater application of the spectra, the library has also been convolved to selected spectrometer and imaging spectrometers sampling and

  5. The effect of bi-directional reflectance distribution function on the estimation of vegetation indices and leaf area index (LAI): A case study of the vegetation in succession stages after forest fire in northwestern Canada

    International Nuclear Information System (INIS)

    Hasegawa, K.; Matsuyama, H.; Tsuzuki, H.; Sweda, T.

    2006-01-01

    The effect of the dependence of the satellite data on sun/sensor geometry must be considered in the case of monitoring vegetation from satellites. Vegetation structure causes uneven scattering of sunlight, which is expressed by bi-directional reflectance distribution function (BRDF). The purpose of this study is to estimate the effect of BRDF of monitoring vegetation using the reflectance of visible and near-infrared bands. We investigated the vegetation in succession stages after forest fire (main species: spruce) in the northwestern Canada. BRF (Bidirectional Reflectance Factor) was measured in the seven sites of some succession stages, along with the measurements of leaf area index (LAI) and biomass. The main results obtained in this study are summarized as follows. (1) In each site, the difference of Normalized Difference Vegetation Index (NDVI) value around 0.1-0.2 was caused by BRDF when the sensor angle was changed from -15deg to 15 deg, being equivalent to the standard image of IKONOS. Also, LAI estimated by NDVI varied from 22% to 65% of the average. (2) The robustness of other vegetation indices to BRDF was compared. The reflectance of the near-infrared band normalized by the sum of other bands (nNIR), and Global Environmental Monitoring Index (GEMI) were investigated along with NDVI. It is clarified that nNIR was most robust in the site where vegetation existed. GEMI was most robust in the sites of scarce vegetation, while NDVI was strongly affected by BRDF in such sites

  6. Using remotely sensed vegetation indices to model ecological pasture conditions in Kara-Unkur watershed, Kyrgyzstan

    Science.gov (United States)

    Masselink, Loes; Baartman, Jantiene; Verbesselt, Jan; Borchardt, Peter

    2017-04-01

    Kyrgyzstan has a long history of nomadic lifestyle in which pastures play an important role. However, currently the pastures are subject to severe grazing-induced degradation. Deteriorating levels of biomass, palatability and biodiversity reduce the pastures' productivity. To counter this and introduce sustainable pasture management, up-to-date information regarding the ecological conditions of the pastures is essential. This research aimed to investigate the potential of a remote sensing-based methodology to detect changing ecological pasture conditions in the Kara-Unkur watershed, Kyrgyzstan. The relations between Vegetation Indices (VIs) from Landsat ETM+ images and biomass, palatability and species richness field data were investigated. Both simple and multiple linear regression (MLR) analyses, including terrain attributes, were applied. Subsequently, trends of these three pasture conditions were mapped using time series analysis. The results show that biomass is most accurately estimated by a model including the Modified Soil Adjusted Vegetation Index (MSAVI) and a slope factor (R2 = 0.65, F = 0.0006). Regarding palatability, a model including the Enhanced Vegetation Index (EVI), Northness Index, Near Infrared (NIR) and Red band was most accurate (R2 = 0.61, F = 0.0160). Species richness was most accurately estimated by a model including Topographic Wetness Index (TWI), Eastness Index and estimated biomass (R2 = 0.81, F = 0.0028). Subsequent trend analyses of all three estimated ecological pasture conditions presented very similar trend patterns. Despite the need for a more robust validation, this study confirms the high potential of a remote sensing based methodology to detect changing ecological pasture conditions.

  7. Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

    Science.gov (United States)

    Nelson, P.; Paradis, D. P.

    2017-12-01

    The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined

  8. Characterizing CDOM Spectral Variability Across Diverse Regions and Spectral Ranges

    Science.gov (United States)

    Grunert, Brice K.; Mouw, Colleen B.; Ciochetto, Audrey B.

    2018-01-01

    Satellite remote sensing of colored dissolved organic matter (CDOM) has focused on CDOM absorption (aCDOM) at a reference wavelength, as its magnitude provides insight into the underwater light field and large-scale biogeochemical processes. CDOM spectral slope, SCDOM, has been treated as a constant or semiconstant parameter in satellite retrievals of aCDOM despite significant regional and temporal variabilities. SCDOM and other optical metrics provide insights into CDOM composition, processing, food web dynamics, and carbon cycling. To date, much of this work relies on fluorescence techniques or aCDOM in spectral ranges unavailable to current and planned satellite sensors (e.g., global variability in SCDOM and fit deviations in the aCDOM spectra using the recently proposed Gaussian decomposition method. From this, we investigate if global variability in retrieved SCDOM and Gaussian components is significant and regionally distinct. We iteratively decreased the spectral range considered and analyzed the number, location, and magnitude of fitted Gaussian components to understand if a reduced spectral range impacts information obtained within a common spectral window. We compared the fitted slope from the Gaussian decomposition method to absorption-based indices that indicate CDOM composition to determine the ability of satellite-derived slope to inform the analysis and modeling of large-scale biogeochemical processes. Finally, we present implications of the observed variability for remote sensing of CDOM characteristics via SCDOM.

  9. Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues.

    Science.gov (United States)

    Del Valle, José C; Gallardo-López, Antonio; Buide, Mª Luisa; Whittall, Justen B; Narbona, Eduardo

    2018-03-01

    Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer-level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content-chroma ratio, anthocyanin content-chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r 2 and normalized root-mean-square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the

  10. Phenological Indicators of Vegetation Recovery in Wetland Ecosystems

    Science.gov (United States)

    Taddeo, S.; Dronova, I.

    2017-12-01

    Landscape phenology is increasingly used to measure the impacts of climatic and environmental disturbances on plant communities. As plants show rapid phenological responses to environmental changes, variation in site phenology can help characterize vegetation recovery following restoration treatments and qualify their resistance to environmental fluctuations. By leveraging free remote sensing datasets, a phenology-based analysis of vegetation dynamics could offer a cost-effective assessment of restoration progress in wetland ecosystems. To fulfill this objective, we analyze 20 years of free remote sensing data from NASA's Landsat archive to offer a landscape-scale synthesis of wetland restoration efforts in the Sacramento-San Joaquin Delta of California, USA. Through an analysis of spatio-temporal changes in plant phenology and greenness, we assess how 25 restored wetlands across the Delta have responded to restoration treatments, time, and landscape context. We use a spline smoothing approach to generate both site-wide and pixel-specific phenological curves and identify key phenological events. Preliminary results reveal a greater variability in greenness and growing season length during the initial post-restoration years and a significant impact of landscape context in the time needed to reach phenological stability. Well-connected sites seem to benefit from an increased availability of propagules enabling them to reach peak greenness and maximum growing season length more rapidly. These results demonstrate the potential of phenological analyses to measure restoration progress and detect factors promoting wetland recovery. A thorough understanding of wetland phenology is key to the quantification of ecosystem processes including carbon sequestration and habitat provisioning.

  11. Investigation of Tree Spectral Reflectance Characteristics Using a Mobile Terrestrial Line Spectrometer and Laser Scanner

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    Eetu Puttonen

    2013-07-01

    Full Text Available In mobile terrestrial hyperspectral imaging, individual trees often present large variations in spectral reflectance that may impact the relevant applications, but the related studies have been seldom reported. To fill this gap, this study was dedicated to investigating the spectral reflectance characteristics of individual trees with a Sensei mobile mapping system, which comprises a Specim line spectrometer and an Ibeo Lux laser scanner. The addition of the latter unit facilitates recording the structural characteristics of the target trees synchronously, and this is beneficial for revealing the characteristics of the spatial distributions of tree spectral reflectance with variations at different levels. Then, the parts of trees with relatively low-level variations can be extracted. At the same time, since it is difficult to manipulate the whole spectrum, the traditional concept of vegetation indices (VI based on some particular spectral bands was taken into account here. Whether the assumed VIs capable of behaving consistently for the whole crown of each tree was also checked. The specific analyses were deployed based on four deciduous tree species and six kinds of VIs. The test showed that with the help of the laser scanner data, the parts of individual trees with relatively low-level variations can be located. Based on these parts, the relatively stable spectral reflectance characteristics for different tree species can be learnt.

  12. EVALUATION OF VEGETABLE EXTRACTS FROM THE SEMI-ARID AS NATURAL pH INDICATOR

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    Sebastiana Estefana Torres Brilhante

    2015-02-01

    Full Text Available Given the various difficulties to expose the contents of the subject of chemistry is a constant search for alternative materials to facilitate learning. This may partly be due to chemical science to be a significant practical character. However, due to professional educational institutions and material limitations ends up being passed on to the student of predominantly theoretical way, requiring a high degree of abstraction and consequently in their disinterest the same. In this context , we investigated the use of ethanol extracts of various plants, such as: Jitirana (Ipomoea glabra , Íxora (Ixora coccínea, Centro (Centrosema brasilianum and Candlebush (Senna alata flowers, Beet (Beta vulgaris L. fruit and Urucum (Bixa orellana seeds as an acids and bases natural indicator, from laboratory tests capable of identifying properties demonstrate the pH. Initially we evaluated the variation in the coloration of extracts using for this buffer solutions at pH 3, 7 and 12. Among the cited vegetable flowers Jitirana, ixora and Centro presented activities relevant indicator as staining variants between pH 2:13. The extracts of plants were further added in glass tubes containing buffer solutions with a pH ranging from 2 to 13. The change in color of the extracts showed good activity has the same pH indicator.

  13. Evaluation of different shadow detection and restoration methods and their impact on vegetation indices using UAV high-resolution imageries over vineyards

    Science.gov (United States)

    Aboutalebi, M.; Torres-Rua, A. F.; McKee, M.; Kustas, W. P.; Nieto, H.

    2017-12-01

    Shadows are an unavoidable component of high-resolution imagery. Although shadows can be a useful source of information about terrestrial features, they are a hindrance for image processing and lead to misclassification errors and increased uncertainty in defining surface reflectance properties. In precision agriculture activities, shadows may affect the performance of vegetation indices at pixel and plant scales. Thus, it becomes necessary to evaluate existing shadow detection and restoration methods, especially for applications that makes direct use of pixel information to estimate vegetation biomass, leaf area index (LAI), plant water use and stress, chlorophyll content, just to name a few. In this study, four high-resolution imageries captured by the Utah State University - AggieAir Unmanned Aerial Vehicle (UAV) system flown in 2014, 2015, and 2016 over a commercial vineyard located in the California for the USDA-Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program are used for shadow detection and restoration. Four different methods for shadow detection are compared: (1) unsupervised classification, (2) supervised classification, (3) index-based method, and (4) physically-based method. Also, two different shadow restoration methods are evaluated: (1) linear correlation correction, and (2) gamma correction. The models' performance is evaluated over two vegetation indices: normalized difference vegetation index (NDVI) and LAI for both sunlit and shadowed pixels. Histogram and analysis of variance (ANOVA) are used as performance indicators. Results indicated that the performance of the supervised classification and the index-based method are better than other methods. In addition, there is a statistical difference between the average of NDVI and LAI on the sunlit and shadowed pixels. Among the shadow restoration methods, gamma correction visually works better than the linear correlation

  14. Multiscale Trend Analysis for Pampa Grasslands Using Ground Data and Vegetation Sensor Imagery

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    Fernando C. Scottá

    2015-07-01

    Full Text Available This study aimed to evaluate changes in the aboveground net primary productivity (ANPP of grasslands in the Pampa biome by using experimental plots and changes in the spectral responses of similar vegetation communities obtained by remote sensing and to compare both datasets with meteorological variations to validate the transition scales of the datasets. Two different geographic scales were considered in this study. At the local scale, an analysis of the climate and its direct influences on grassland ANPP was performed using data from a long-term experiment. At the regional scale, the influences of climate on the grassland reflectance patterns were determined using vegetation sensor imagery data. Overall, the monthly variations of vegetation canopy growth analysed using environmental changes (air temperature, total rainfall and total evapotranspiration were similar. The results from the ANPP data and the NDVI data showed the that variations in grassland growth were similar and independent of the analysis scale, which indicated that local data and the relationships of local data with climate can be considered at the regional scale in the Pampa biome by using remote sensing.

  15. Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

    Science.gov (United States)

    Varlamova, Eugenia V.; Solovyev, Vladimir S.

    2017-11-01

    Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

  16. Hyperspectral remote sensing of vegetation

    Science.gov (United States)

    Thenkabail, Prasad S.; Lyon, John G.; Huete, Alfredo

    2011-01-01

    Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research.

  17. Assessing the Impact of Spectral Resolution on Classification of Lowland Native Grassland Communities Based on Field Spectroscopy in Tasmania, Australia

    Directory of Open Access Journals (Sweden)

    Bethany Melville

    2018-02-01

    Full Text Available This paper presents a case study for the analysis of endangered lowland native grassland communities in the Tasmanian Midlands region using field spectroscopy and spectral convolution techniques. The aim of the study was to determine whether there was significant improvement in classification accuracy for lowland native grasslands and other vegetation communities based on hyperspectral resolution datasets over multispectral equivalents. A spectral dataset was collected using an ASD Handheld-2 spectroradiometer at Tunbridge Township Lagoon. The study then employed a k-fold cross-validation approach for repeated classification of a full hyperspectral dataset, a reduced hyperspectral dataset, and two convoluted multispectral datasets. Classification was performed on each of the four datasets a total of 30 times, based on two different class configurations. The classes analysed were Themeda triandra grassland, Danthonia/Poa grassland, Wilsonia rotundifolia/Selliera radicans, saltpan, and a simplified C3 vegetation class. The results of the classifications were then tested for statistically significant differences using ANOVA and Tukey’s post-hoc comparisons. The results of the study indicated that hyperspectral resolution provides small but statistically significant increases in classification accuracy for Themeda and Danthonia grasslands. For other classes, differences in classification accuracy for all datasets were not statistically significant. The results obtained here indicate that there is some potential for enhanced detection of major lowland native grassland community types using hyperspectral resolution datasets, and that future analysis should prioritise good performance in these classes over others. This study presents a method for identification of optimal spectral resolution across multiple datasets, and constitutes an important case study for lowland native grassland mapping in Tasmania.

  18. Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

    Science.gov (United States)

    Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

    2016-01-01

    We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

  19. Spectral Classification of Similar Materials using the Tetracorder Algorithm: The Calcite-Epidote-Chlorite Problem

    Science.gov (United States)

    Dalton, J. Brad; Bove, Dana; Mladinich, Carol; Clark, Roger; Rockwell, Barnaby; Swayze, Gregg; King, Trude; Church, Stanley

    2001-01-01

    Recent work on automated spectral classification algorithms has sought to distinguish ever-more similar materials. From modest beginnings separating shade, soil, rock and vegetation to ambitious attempts to discriminate mineral types and specific plant species, the trend seems to be toward using increasingly subtle spectral differences to perform the classification. Rule-based expert systems exploiting the underlying physics of spectroscopy such as the US Geological Society Tetracorder system are now taking advantage of the high spectral resolution and dimensionality of current imaging spectrometer designs to discriminate spectrally similar materials. The current paper details recent efforts to discriminate three minerals having absorptions centered at the same wavelength, with encouraging results.

  20. Vegetation mapping from high-resolution satellite images in the heterogeneous arid environments of Socotra Island (Yemen)

    Science.gov (United States)

    Malatesta, Luca; Attorre, Fabio; Altobelli, Alfredo; Adeeb, Ahmed; De Sanctis, Michele; Taleb, Nadim M.; Scholte, Paul T.; Vitale, Marcello

    2013-01-01

    Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geomorphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum likelihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.

  1. Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

    Science.gov (United States)

    Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

    2015-01-01

    Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

  2. Post-fire vegetation recovery in Portugal based ewline on spot/vegetation data

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    C. Gouveia

    2010-04-01

    Full Text Available A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI, with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation

  3. A special vegetation index for the weed detection in sensor based precision agriculture.

    Science.gov (United States)

    Langner, Hans-R; Böttger, Hartmut; Schmidt, Helmut

    2006-06-01

    Many technologies in precision agriculture (PA) require image analysis and image- processing with weed and background differentiations. The detection of weeds on mulched cropland is one important image-processing task for sensor based precision herbicide applications. The article introduces a special vegetation index, the Difference Index with Red Threshold (DIRT), for the weed detection on mulched croplands. Experimental investigations in weed detection on mulched areas point out that the DIRT performs better than the Normalized Difference Vegetation Index (NDVI). The result of the evaluation with four different decision criteria indicate, that the new DIRT gives the highest reliability in weed/background differentiation on mulched areas. While using the same spectral bands (infrared and red) as the NDVI, the new DIRT is more suitable for weed detection than the other vegetation indices and requires only a small amount of additional calculation power. The new vegetation index DIRT was tested on mulched areas during automatic ratings with a special weed camera system. The test results compare the new DIRT and three other decision criteria: the difference between infrared and red intensity (Diff), the soil-adjusted quotient between infrared and red intensity (Quotient) and the NDVI. The decision criteria were compared with the definition of a worse case decision quality parameter Q, suitable for mulched croplands. Although this new index DIRT needs further testing, the index seems to be a good decision criterion for the weed detection on mulched areas and should also be useful for other image processing applications in precision agriculture. The weed detection hardware and the PC program for the weed image processing were developed with funds from the German Federal Ministry of Education and Research (BMBF).

  4. Model of Peatland Vegetation Species using HyMap Image and Machine Learning

    Science.gov (United States)

    Dayuf Jusuf, Muhammad; Danoedoro, Projo; Muljo Sukojo, Bangun; Hartono

    2017-12-01

    Species Tumih / Parepat (Combretocarpus-rotundatus Mig. Dancer) family Anisophylleaceae and Meranti (Shorea Belangerang, Shorea Teysmanniana Dyer ex Brandis) family Dipterocarpaceae is a group of vegetation species distribution model. Species pioneer is predicted as an indicator of the succession of ecosystem restoration of tropical peatland characteristics and extremely fragile (unique) in the endemic hot spot of Sundaland. Climate change projections and conservation planning are hot topics of current discussion, analysis of alternative approaches and the development of combinations of species projection modelling algorithms through geospatial information systems technology. Approach model to find out the research problem of vegetation level based on the machine learning hybrid method, wavelet and artificial neural networks. Field data are used as a reference collection of natural resource field sample objects and biodiversity assessment. The testing and training ANN data set iterations times 28, achieve a performance value of 0.0867 MSE value is smaller than the ANN training data, above 50%, and spectral accuracy 82.1 %. Identify the location of the sample point position of the Tumih / Parepat vegetation species using HyMap Image is good enough, at least the modelling, design of the species distribution can reach the target in this study. The computation validation rate above 90% proves the calculation can be considered.

  5. Contrast-enhanced Spectral Mammography: Technique, Indications, and Clinical Applications.

    Science.gov (United States)

    Bhimani, Chandni; Matta, Danielle; Roth, Robyn G; Liao, Lydia; Tinney, Elizabeth; Brill, Kristin; Germaine, Pauline

    2017-01-01

    Contrast-enhanced spectral mammography (CESM) combines the benefits of full field digital mammography with the concept of tumor angiogenesis. Technique and practical applications of CESM are discussed. An overview of the technique is followed by a demonstration of practical applications of CESM in our practice. We have successfully implemented CESM into our practice as a screening, diagnostic, staging, and treatment response tool. It is important to understand the technique of CESM and how to incorporate it into practice. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  6. Detecting land-cover change using mappable vegetation related indices: A case study from Sinharaja Man and the Biosphere Reserve

    Directory of Open Access Journals (Sweden)

    BD Madurapperuma

    2014-06-01

    Full Text Available This study evaluates multi-year changes of vegetation in the Sinharaja Man and the Biosphere (MAB reserve using mappable vegetation related indices viz., Normalized Difference Vegetation Index (NDVI and Burn Index (BI. Land-cover changes in the Sinharaja MAB reserve were detected using Landsat 7 ETM+ images for 1993, 2001, and 2005. Seven individual bands of each image were converted to new multiband files by layer stacking using ENVI® 4.5. Then the multiband files were re-projected to UTM Zone 44 North, WGS-84 Datum. Each data set was exported to ENVI® EX software package to detect the changes between time steps based on NDVI and BI using an image difference tool. Land-cover data, which were obtained from the DIVA GIS web portal, were compared with Landsat image data. Results of BI showed that the Sinharaja MAB reserve fringe was vulnerable to forest fire. For example, from 1993- 2001, 160 ha identified as burned area. In contrast, from 2001-2005, 79 ha burned, and for the entire period of 1993-2005, 10 ha burned. NDVI resulted in a 962 ha increase of vegetation prime at the western Sinharaja from 2001-2005. In addition, there was a 15 ha decrease in vegetation from 1993-2005. The results were visualized using an embedded 3D render window of Google Earth and 2D view of ArcGIS explorer online. In conclusion, in-situ ground truthing data is needed for the fire-influenced area for implementing sustainable forest resource management at the Sinharaja MAB reserve. Normal 0 false false false EN-GB X-NONE X-NONE

  7. Evaluation of Continuous VNIR-SWIR Spectra versus Narrowband Hyperspectral Indices to Discriminate the Invasive Acacia longifolia within a Mediterranean Dune Ecosystem

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    André Große-Stoltenberg

    2016-04-01

    Full Text Available Hyperspectral remote sensing is an effective tool to discriminate plant species, providing vast potential to trace plant invasions for ecological assessments. However, necessary baseline information for the use of remote sensing data is missing for many high-impact invaders. Furthermore, the identification of the suitable classification algorithms and spectral regions for successfully classifying species remains an open field of research. Here, we tested the separability of the invasive tree Acacia longifolia from adjacent exotic and native vegetation in a Natura 2000 protected Mediterranean dune ecosystem. We used continuous visible, near-infrared and short wave infrared (VNIR-SWIR data as well as vegetation indices at the leaf and canopy level for classification, comparing five different classification algorithms. We were able to successfully distinguish A. longifolia from surrounding vegetation based on vegetation indices. At the leaf level, radial-basis function kernel Support Vector Machine (SVM and Random Forest (RF achieved both a high Sensitivity (SVM: 0.83, RF: 0.78 and a high Positive Predicted Value (PPV (0.86, 0.83. At the canopy level, RF was the classifier with an optimal balance of Sensitivity (0.75 and PPV (0.75. The most relevant vegetation indices were linked to the biochemical parameters chlorophyll, water, nitrogen, and cellulose as well as vegetation cover, which is in line with biochemical and ecophysiological properties reported for A. longifolia. Our results highlight the potential to use remote sensing as a tool for an early detection of A. longifolia in Mediterranean coastal ecosystems.

  8. Evaluating potential spectral impacts of various artificial lights on melatonin suppression, photosynthesis, and star visibility.

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    Martin Aubé

    Full Text Available Artificial light at night can be harmful to the environment, and interferes with fauna and flora, star visibility, and human health. To estimate the relative impact of a lighting device, its radiant power, angular photometry and detailed spectral power distribution have to be considered. In this paper we focus on the spectral power distribution. While specific spectral characteristics can be considered harmful during the night, they can be considered advantageous during the day. As an example, while blue-rich Metal Halide lamps can be problematic for human health, star visibility and vegetation photosynthesis during the night, they can be highly appropriate during the day for plant growth and light therapy. In this paper we propose three new indices to characterize lamp spectra. These indices have been designed to allow a quick estimation of the potential impact of a lamp spectrum on melatonin suppression, photosynthesis, and star visibility. We used these new indices to compare various lighting technologies objectively. We also considered the transformation of such indices according to the propagation of light into the atmosphere as a function of distance to the observer. Among other results, we found that low pressure sodium, phosphor-converted amber light emitting diodes (LED and LED 2700 K lamps filtered with the new Ledtech's Equilib filter showed a lower or equivalent potential impact on melatonin suppression and star visibility in comparison to high pressure sodium lamps. Low pressure sodium, LED 5000 K-filtered and LED 2700 K-filtered lamps had a lower impact on photosynthesis than did high pressure sodium lamps. Finally, we propose these indices as new standards for the lighting industry to be used in characterizing their lighting technologies. We hope that their use will favor the design of new environmentally and health-friendly lighting technologies.

  9. Curvature Effect and the Spectral Softening Phenomenon Detected ...

    Indian Academy of Sciences (India)

    soft spectral evolution, indicating that this spectral softening is not a rare phenomenon .... of time, there exists a temporal steep decay phase accompanied by spectral softening. (d) In most cases, the temporal power law index α and the spectral.

  10. Assessing onset and length of greening period in six vegetation types in Oaxaca, Mexico, using NDVI-precipitation relationships.

    Science.gov (United States)

    Gómez-Mendoza, L; Galicia, L; Cuevas-Fernández, M L; Magaña, V; Gómez, G; Palacio-Prieto, J L

    2008-07-01

    Variations in the normalized vegetation index (NDVI) for the state of Oaxaca, in southern Mexico, were analyzed in terms of precipitation anomalies for the period 1997-2003. Using 10-day averages in NDVI data, obtained from AVHRR satellite information, the response of six types of vegetation to intra-annual and inter-annual fluctuations in precipitation were examined. The onset and temporal evolution of the greening period were studied in terms of precipitation variations through spectral analysis (coherence and phase). The results indicate that extremely dry periods, such as those observed in 1997 and 2001, resulted in low values of NDVI for much of Oaxaca, while good precipitation periods produced a rapid response (20-30 days of delay) from a stressed to a non-stressed condition in most vegetation types. One of these rapid changes occurred during the transition from dry to wet conditions during the summer of 1998. As in many parts of the tropics and subtropics, the NDVI reflects low frequency variations in precipitation on several spatial scales. Even after long dry periods (2001-2002), the various regional vegetation types are capable of recovering when a good rainy season takes place, indicating that vegetation types such as the evergreen forests in the high parts of Oaxaca respond better to rainfall characteristics (timing, amount) than to temperature changes, as is the case in most mid-latitudes. This finding may be relevant to prepare climate change scenarios for forests, where increases in surface temperature and precipitation anomalies are expected.

  11. Estimating water stressed dwarf green bean pigment concentration through hyperspectral indices

    International Nuclear Information System (INIS)

    Koksal, E.S.; Ustrun, H.; Ozcan, H.; Gunturk, A.

    2010-01-01

    In this study, the relationship between leaf pigment concentration (analyzed in the laboratory) and four spectral indexes (measured in the field) was investigated. For this purpose, field experiments consisting of six different irrigation treatments were conducted with dwarf green beans during 2005 growing season. Based on spectral data, spectral indexes were plotted against pigment concentration. Results showed that under water stress, the chlorophyll and carotene contents of green bean leaves rose. According to linear regression analysis between spectral indexes and pigment contents, the Normalized Difference Pigment Chlorophyll Index (NPCI) and Normalized Difference Vegetation Index (NDVI) had the highest correlations with the chlorophyll (a, b and total), and carotene content of leaves. (author)

  12. Millimetre spectral indices of transition disks and their relation to the cavity radius

    Science.gov (United States)

    Pinilla, P.; Benisty, M.; Birnstiel, T.; Ricci, L.; Isella, A.; Natta, A.; Dullemond, C. P.; Quiroga-Nuñez, L. H.; Henning, T.; Testi, L.

    2014-04-01

    Context. Transition disks are protoplanetary disks with inner depleted dust cavities that are excellent candidates for investigating the dust evolution when there is a pressure bump. A pressure bump at the outer edge of the cavity allows dust grains from the outer regions to stop their rapid inward migration towards the star and to efficiently grow to millimetre sizes. Dynamical interactions with planet(s) have been one of the most exciting theories to explain the clearing of the inner disk. Aims: We look for evidence of millimetre dust particles in transition disks by measuring their spectral index αmm with new and available photometric data. We investigate the influence of the size of the dust depleted cavity on the disk integrated millimetre spectral index. Methods: We present the 3-mm (100 GHz) photometric observations carried out with the Plateau de Bure Interferometer of four transition disks: LkHα 330, UX Tau A, LRLL 31, and LRLL 67. We used the available values of their fluxes at 345 GHz to calculate their spectral index, as well as the spectral index for a sample of twenty transition disks. We compared the observations with two kinds of models. In the first set of models, we considered coagulation and fragmentation of dust in a disk in which a cavity is formed by a massive planet located at different positions. The second set of models assumes disks with truncated inner parts at different radii and with power-law dust-size distributions, where the maximum size of grains is calculated considering turbulence as the source of destructive collisions. Results: We show that the integrated spectral index is higher for transition disks (TD) than for regular protoplanetary disks (PD) with mean values of bar{αmmTD} = 2.70 ± 0.13 and bar{αmmPD} = 2.20 ± 0.07 respectively. For transition disks, the probability that the measured spectral index is positively correlated with the cavity radius is 95%. High angular resolution imaging of transition disks is needed to

  13. Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges

    Science.gov (United States)

    Wang, Fenghe; Gao, Jay; Zha, Yong

    2018-02-01

    Remote sensing of heavy metal contamination of soils has been widely studied. These studies concentrate heavily on the hyperspectral reflectance of typical metals in soils and in plants measured either in situ or in the laboratory. The most used wavebands lie within the visible-near infrared portion of the spectrum, especially the red edge. In comparison, mid- and far-infrared wavelengths are used far less frequently. Hyperspectral data are optimized to suppress noises and enhance the signal of the targeted metals through spectral derivatives and vegetation indexing. It is found that only subtle disparity exists in spectral responses for some metals at a sufficiently high content level. Not all metals have their own unique spectral response. Their detection has to rely on their co-variation with the spectrally responsive metals or organic matter in the soils. The closeness of the correlation dictates the accuracy of prediction. Without any theoretical grounding, this correlation is site-specific. Various analytical methods, including stepwise multi-linear regression, partial least squares regression, and neural networks have been used to model metal content level from the identified spectrally sensitive bands and/or their transformed indices. Both the model and the explanatory variables vary with the metal under detection and the area from which in situ samples are collected. Despite the amply demonstrated feasibility of estimating several metals by a large number of authors, only a few have succeeded in mapping the spatial distribution of metals from HyMAP, HJ-1A and Hyperion images to a satisfactory accuracy using complex algorithms and after taking environmental variables into account. The large number of reported failures testifies the difficulty in the detection of heavy metals in soils and plants, especially when their concentration level is low. The reasons or factors responsible for the success or failure have not been systematically analyzed, including the

  14. Introduction to spectral theory

    CERN Document Server

    Levitan, B M

    1975-01-01

    This monograph is devoted to the spectral theory of the Sturm- Liouville operator and to the spectral theory of the Dirac system. In addition, some results are given for nth order ordinary differential operators. Those parts of this book which concern nth order operators can serve as simply an introduction to this domain, which at the present time has already had time to become very broad. For the convenience of the reader who is not familar with abstract spectral theory, the authors have inserted a chapter (Chapter 13) in which they discuss this theory, concisely and in the main without proofs, and indicate various connections with the spectral theory of differential operators.

  15. Using spectrotemporal indices to improve the fruit-tree crop classification accuracy

    Science.gov (United States)

    Peña, M. A.; Liao, R.; Brenning, A.

    2017-06-01

    This study assesses the potential of spectrotemporal indices derived from satellite image time series (SITS) to improve the classification accuracy of fruit-tree crops. Six major fruit-tree crop types in the Aconcagua Valley, Chile, were classified by applying various linear discriminant analysis (LDA) techniques on a Landsat-8 time series of nine images corresponding to the 2014-15 growing season. As features we not only used the complete spectral resolution of the SITS, but also all possible normalized difference indices (NDIs) that can be constructed from any two bands of the time series, a novel approach to derive features from SITS. Due to the high dimensionality of this "enhanced" feature set we used the lasso and ridge penalized variants of LDA (PLDA). Although classification accuracies yielded by the standard LDA applied on the full-band SITS were good (misclassification error rate, MER = 0.13), they were further improved by 23% (MER = 0.10) with ridge PLDA using the enhanced feature set. The most important bands to discriminate the crops of interest were mainly concentrated on the first two image dates of the time series, corresponding to the crops' greenup stage. Despite the high predictor weights provided by the red and near infrared bands, typically used to construct greenness spectral indices, other spectral regions were also found important for the discrimination, such as the shortwave infrared band at 2.11-2.19 μm, sensitive to foliar water changes. These findings support the usefulness of spectrotemporal indices in the context of SITS-based crop type classifications, which until now have been mainly constructed by the arithmetic combination of two bands of the same image date in order to derive greenness temporal profiles like those from the normalized difference vegetation index.

  16. DEEP WIDEBAND SINGLE POINTINGS AND MOSAICS IN RADIO INTERFEROMETRY: HOW ACCURATELY DO WE RECONSTRUCT INTENSITIES AND SPECTRAL INDICES OF FAINT SOURCES?

    Energy Technology Data Exchange (ETDEWEB)

    Rau, U.; Bhatnagar, S.; Owen, F. N., E-mail: rurvashi@nrao.edu [National Radio Astronomy Observatory, Socorro, NM-87801 (United States)

    2016-11-01

    Many deep wideband wide-field radio interferometric surveys are being designed to accurately measure intensities, spectral indices, and polarization properties of faint source populations. In this paper, we compare various wideband imaging methods to evaluate the accuracy to which intensities and spectral indices of sources close to the confusion limit can be reconstructed. We simulated a wideband single-pointing (C-array, L-Band (1–2 GHz)) and 46-pointing mosaic (D-array, C-Band (4–8 GHz)) JVLA observation using a realistic brightness distribution ranging from 1 μ Jy to 100 mJy and time-, frequency-, polarization-, and direction-dependent instrumental effects. The main results from these comparisons are (a) errors in the reconstructed intensities and spectral indices are larger for weaker sources even in the absence of simulated noise, (b) errors are systematically lower for joint reconstruction methods (such as Multi-Term Multi-Frequency-Synthesis (MT-MFS)) along with A-Projection for accurate primary beam correction, and (c) use of MT-MFS for image reconstruction eliminates Clean-bias (which is present otherwise). Auxiliary tests include solutions for deficiencies of data partitioning methods (e.g., the use of masks to remove clean bias and hybrid methods to remove sidelobes from sources left un-deconvolved), the effect of sources not at pixel centers, and the consequences of various other numerical approximations within software implementations. This paper also demonstrates the level of detail at which such simulations must be done in order to reflect reality, enable one to systematically identify specific reasons for every trend that is observed, and to estimate scientifically defensible imaging performance metrics and the associated computational complexity of the algorithms/analysis procedures.

  17. A Vegetation Database for the Colorado River Ecosystem from Glen Canyon Dam to the Western Boundary of Grand Canyon National Park, Arizona

    Science.gov (United States)

    Ralston, Barbara E.; Davis, Philip A.; Weber, Robert M.; Rundall, Jill M.

    2008-01-01

    A vegetation database of the riparian vegetation located within the Colorado River ecosystem (CRE), a subsection of the Colorado River between Glen Canyon Dam and the western boundary of Grand Canyon National Park, was constructed using four-band image mosaics acquired in May 2002. A digital line scanner was flown over the Colorado River corridor in Arizona by ISTAR Americas, using a Leica ADS-40 digital camera to acquire a digital surface model and four-band image mosaics (blue, green, red, and near-infrared) for vegetation mapping. The primary objective of this mapping project was to develop a digital inventory map of vegetation to enable patch- and landscape-scale change detection, and to establish randomized sampling points for ground surveys of terrestrial fauna (principally, but not exclusively, birds). The vegetation base map was constructed through a combination of ground surveys to identify vegetation classes, image processing, and automated supervised classification procedures. Analysis of the imagery and subsequent supervised classification involved multiple steps to evaluate band quality, band ratios, and vegetation texture and density. Identification of vegetation classes involved collection of cover data throughout the river corridor and subsequent analysis using two-way indicator species analysis (TWINSPAN). Vegetation was classified into six vegetation classes, following the National Vegetation Classification Standard, based on cover dominance. This analysis indicated that total area covered by all vegetation within the CRE was 3,346 ha. Considering the six vegetation classes, the sparse shrub (SS) class accounted for the greatest amount of vegetation (627 ha) followed by Pluchea (PLSE) and Tamarix (TARA) at 494 and 366 ha, respectively. The wetland (WTLD) and Prosopis-Acacia (PRGL) classes both had similar areal cover values (227 and 213 ha, respectively). Baccharis-Salix (BAXX) was the least represented at 94 ha. Accuracy assessment of the

  18. East African Cenozoic vegetation history.

    Science.gov (United States)

    Linder, Hans Peter

    2017-11-01

    The modern vegetation of East Africa is a complex mosaic of rainforest patches; small islands of tropic-alpine vegetation; extensive savannas, ranging from almost pure grassland to wooded savannas; thickets; and montane grassland and forest. Here I trace the evolution of these vegetation types through the Cenozoic. Paleogene East Africa was most likely geomorphologically subdued and, as the few Eocene fossil sites suggest, a woodland in a seasonal climate. Woodland rather than rainforest may well have been the regional vegetation. Mountain building started with the Oligocene trap lava flows in Ethiopia, on which rainforest developed, with little evidence of grass and none of montane forests. The uplift of the East African Plateau took place during the middle Miocene. Fossil sites indicate the presence of rainforest, montane forest and thicket, and wooded grassland, often in close juxtaposition, from 17 to 10 Ma. By 10 Ma, marine deposits indicate extensive grassland in the region and isotope analysis indicates that this was a C 3 grassland. In the later Miocene rifting, first of the western Albertine Rift and then of the eastern Gregory Rift, added to the complexity of the environment. The building of the high strato-volcanos during the later Mio-Pliocene added environments suitable for tropic-alpine vegetation. During this time, the C 3 grassland was replaced by C 4 savannas, although overall the extent of grassland was reduced from the mid-Miocene high to the current low level. Lake-level fluctuations during the Quaternary indicate substantial variation in rainfall, presumably as a result of movements in the intertropical convergence zone and the Congo air boundary, but the impact of these fluctuations on the vegetation is still speculative. I argue that, overall, there was an increase in the complexity of East African vegetation complexity during the Neogene, largely as a result of orogeny. The impact of Quaternary climatic fluctuation is still poorly understood

  19. Evaluating the Effects of Fire on Semi-Arid Savanna Ecosystem Productivity Using Integrated Spectral and Gas Exchange Measurements

    Science.gov (United States)

    Raub, H. D.; Jimenez, J. R.; Gallery, R. E.; Sutter, L., Jr.; Barron-Gafford, G.; Smith, W. K.

    2017-12-01

    Drylands account for 40% of the land surface and have been identified as increasingly important in driving interannual variability of the land carbon sink. Yet, understanding of dryland seasonal ecosystem productivity dynamics - termed Gross Primary Productivity (GPP) - is limited due to complex interactions between vegetation health, seasonal drought dynamics, a paucity of long-term measurements across these under-studied regions, and unanticipated disturbances from varying fire regimes. For instance, fire disturbance has been found to either greatly reduce post-fire GPP through vegetation mortality or enhance post-fire GPP though increased resource availability (e.g., water, light, nutrients, etc.). Here, we explore post-fire ecosystem recovery by evaluating seasonal GPP dynamics for two Ameriflux eddy covariance flux tower sites within the Santa Rita Experimental Range of southeastern Arizona: 1) the US-SRG savanna site dominated by a mix of grass and woody mesquite vegetation that was burned in May 2017, and 2) the US-SRM savanna site dominated by similar vegetation but unburned for the full measurement record. For each site, we collected leaf-level spectral and gas exchange measurements, as well as leaf-level chemistry and soil chemistry to characterize differences in nutrient availability and microbial activity throughout the 2017 growing season. From spectral data, we derived and evaluated multiple common vegetation metrics, including normalized difference vegetation index (NDVI), photochemical reflectivity index (PRI), near-infrared reflectance (NIRv), and MERIS terrestrial chlorophyll index (MTCI). Early results suggest rates of photosynthesis were enhanced at the burned site, with productivity increasing immediately following the onset of monsoonal precipitation; whereas initial photosynthesis at the unburned site remained relatively low following first monsoonal rains. MTCI values for burned vegetation appear to track higher levels of leaf-level nitrogen

  20. Remote sensing estimation of vegetation moisture for the prediction of fire hazard

    NARCIS (Netherlands)

    Maffei, C.; Menenti, M.

    2013-01-01

    Various factors contribute to forest fire hazard, and among them vegetation moisture is the one that dictates susceptibility to fire ignition and propagation. The scientific community has developed a number of spectral indexes based on remote sensing measurements in the optical domain for the

  1. Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

    Science.gov (United States)

    Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

    2018-04-01

    Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0

  2. Spectral response variation of a negative-electron-affinity photocathode in the preparation process

    International Nuclear Information System (INIS)

    Liu Lei; Du Yujie; Chang Benkang; Yunsheng Qian

    2006-01-01

    In order to research the spectral response variation of a negative electron affinity (NEA) photocathode in the preparation process, we have done two experiments on a transmission-type GaAs photocathode.First, an automatic spectral response recording system is described, which is used to take spectral response curves during the activation procedure of the photocathode. By this system, the spectral response curves of a GaAs:Cs-Ophotocathode measured in situ are presented. Then, after the cathode is sealed with a microchannel plate and a fluorescence screen into the image tube, we measure the spectral response of the tube by another measurement instrument. By way of comparing and analyzing these curves, we can find the typical variation in spectral-responses.The reasons for the variation are discussed. Based on these curves, spectral matching factors of a GaAs cathode for green vegetation and rough concrete are calculated. The visual ranges of night-vision goggles under specific circumstances are estimated. The results show that the spectral response of the NEA photocathode degraded in the sealing process, especially at long wavelengths. The variation has also influenced the whole performance of the intensifier tube

  3. Regional scale soil salinity assessment using remote sensing based environmental factors and vegetation indicators

    Science.gov (United States)

    Ma, Ligang; Ma, Fenglan; Li, Jiadan; Gu, Qing; Yang, Shengtian; Ding, Jianli

    2017-04-01

    Land degradation, specifically soil salinization has rendered large areas of China west sterile and unproductive while diminishing the productivity of adjacent lands and other areas where salting is less severe. Up to now despite decades of research in soil mapping, few accurate and up-to-date information on the spatial extent and variability of soil salinity are available for large geographic regions. This study explores the po-tentials of assessing soil salinity via linear and random forest modeling of remote sensing based environmental factors and indirect indicators. A case study is presented for the arid oases of Tarim and Junggar Basin, Xinjiang, China using time series land surface temperature (LST), evapotranspiration (ET), TRMM precipitation (TRM), DEM product and vegetation indexes as well as their second order products. In par-ticular, the location of the oasis, the best feature sets, different salinity degrees and modeling approaches were fully examined. All constructed models were evaluated for their fit to the whole data set and their performance in a leave-one-field-out spatial cross-validation. In addition, the Kruskal-Wallis rank test was adopted for the statis-tical comparison of different models. Overall, the random forest model outperformed the linear model for the two basins, all salinity degrees and datasets. As for feature set, LST and ET were consistently identified to be the most important factors for two ba-sins while the contribution of vegetation indexes vary with location. What's more, models performances are promising for the salinity ranges that are most relevant to agricultural productivity.

  4. Análise da dinâmica sazonal de fitofisionomias do bioma Mata Atlântica com base em índices de vegetação do sensor MODIS/TERRA / Analysis of the seasonal dynamics of some Atlantic Forest biome physiognomies with basis of vegetation indices derived from MOD

    Directory of Open Access Journals (Sweden)

    Elói Lennon Dalla Nora

    2010-08-01

    and with a climatic database (temperature and precipitation, for each physiognomy. The results showed that the fragments of seasonal deciduous forest and mixed rain forest present a common seasonal pattern, however, with variations of amplitude in relation to each index. The EVI was more sensible and hence, more efficient to annual variations of the vegetation compared to the NDVI. For both forest formations a positive correlation between profile EVI and NDVI with variations of temperature was established. The spectral/temporal dynamic showed a marked contrast under distinct seasonal conditions converging with the pattern presented for the vegetation indices. Data indicate potentialities of the use of MODIS sensor for the continuous monitoring of the south forest formations with moderate space resolution and high temporal resolution.

  5. Climatic drivers of vegetation based on wavelet analysis

    Science.gov (United States)

    Claessen, Jeroen; Martens, Brecht; Verhoest, Niko E. C.; Molini, Annalisa; Miralles, Diego

    2017-04-01

    Vegetation dynamics are driven by climate, and at the same time they play a key role in forcing the different bio-geochemical cycles. As climate change leads to an increase in frequency and intensity of hydro-meteorological extremes, vegetation is expected to respond to these changes, and subsequently feed back on their occurrence. This response can be analysed using time series of different vegetation diagnostics observed from space, in the optical (e.g. Normalised Difference Vegetation Index (NDVI), Solar Induced Fluorescence (SIF)) and microwave (Vegetation Optical Depth (VOD)) domains. In this contribution, we compare the climatic drivers of different vegetation diagnostics, based on a monthly global data-cube of 24 years at a 0.25° resolution. To do so, we calculate the wavelet coherence between each vegetation-related observation and observations of air temperature, precipitation and incoming radiation. The use of wavelet coherence allows unveiling the scale-by-scale response and sensitivity of the diverse vegetation indices to their climatic drivers. Our preliminary results show that the wavelet-based statistics prove to be a suitable tool for extracting information from different vegetation indices. Going beyond traditional methods based on linear correlations, the application of wavelet coherence provides information about: (a) the specific periods at which the correspondence between climate and vegetation dynamics is larger, (b) the frequencies at which this correspondence occurs (e.g. monthly or seasonal scales), and (c) the time lag in the response of vegetation to their climate drivers, and vice versa. As expected, areas of high rainfall volumes are characterised by a strong control of radiation and temperature over vegetation. Furthermore, precipitation is the most important driver of vegetation variability over short terms in most regions of the world - which can be explained by the rapid response of leaf development towards available water content

  6. Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion-EO-1 Data

    Science.gov (United States)

    Thenkabail, Prasad S.; Mariotto, Isabella; Gumma, Murali Krishna; Middleton, Elizabeth M.; Landis, David R.; Huemmrich, K. Fred

    2013-01-01

    The overarching goal of this study was to establish optimal hyperspectral vegetation indices (HVIs) and hyperspectral narrowbands (HNBs) that best characterize, classify, model, and map the world's main agricultural crops. The primary objectives were: (1) crop biophysical modeling through HNBs and HVIs, (2) accuracy assessment of crop type discrimination using Wilks' Lambda through a discriminant model, and (3) meta-analysis to select optimal HNBs and HVIs for applications related to agriculture. The study was conducted using two Earth Observing One (EO-1) Hyperion scenes and other surface hyperspectral data for the eight leading worldwide crops (wheat, corn, rice, barley, soybeans, pulses, cotton, and alfalfa) that occupy approx. 70% of all cropland areas globally. This study integrated data collected from multiple study areas in various agroecosystems of Africa, the Middle East, Central Asia, and India. Data were collected for the eight crop types in six distinct growth stages. These included (a) field spectroradiometer measurements (350-2500 nm) sampled at 1-nm discrete bandwidths, and (b) field biophysical variables (e.g., biomass, leaf area index) acquired to correspond with spectroradiometer measurements. The eight crops were described and classified using approx. 20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was approx. 25% better than the multi-spectral results possible from Landsat-7's Enhanced Thematic Mapper+ or EO-1's Advanced Land Imager. Further, based on this research and meta-analysis involving over 100 papers, the study established 33 optimal HNBs and an equal number of specific two-band normalized difference HVIs to best model and study specific biophysical and biochemical quantities of major agricultural crops of the world. Redundant bands identified in this study will help overcome the Hughes Phenomenon (or "the curse of high dimensionality") in hyperspectral data for a particular application (e

  7. Long-term decrease in satellite vegetation indices in response to environmental variables in an iconic desert riparian ecosystem: the Upper San Pedro, Arizona, United States

    Science.gov (United States)

    Nguyen, Uyen; Glenn, Edward P.; Nagler, Pamela L.; Scott, Russell L.

    2015-01-01

    The Upper San Pedro River is one of the few remaining undammed rivers that maintain a vibrant riparian ecosystem in the southwest United States. However, its riparian forest is threatened by diminishing groundwater and surface water inputs, due to either changes in watershed characteristics such as changes in riparian and upland vegetation, or human activities such as regional groundwater pumping. We used satellite vegetation indices to quantify the green leaf density of the groundwater-dependent riparian forest from 1984 to 2012. The river was divided into a southern, upstream (mainly perennial flow) reach and a northern, downstream (mainly intermittent and ephemeral flow) reach. Pre-monsoon (June) Landsat normalized difference vegetation index (NDVI) values showed a 20% drop for the northern reach (P  0·05). NDVI and enhanced vegetation index values were positively correlated (P deterioration of the riparian forest in the northern reach.

  8. [Hyperspectral remote sensing in monitoring the vegetation heavy metal pollution].

    Science.gov (United States)

    Li, Na; Lü, Jian-sheng; Altemann, W

    2010-09-01

    Mine exploitation aggravates the environment pollution. The large amount of heavy metal element in the drainage of slag from the mine pollutes the soil seriously, doing harm to the vegetation growing and human health. The investigation of mining environment pollution is urgent, in which remote sensing, as a new technique, helps a lot. In the present paper, copper mine in Dexing was selected as the study area and China sumac as the study plant. Samples and spectral data in field were gathered and analyzed in lab. The regression model from spectral characteristics for heavy metal content was built, and the feasibility of hyperspectral remote sensing in environment pollution monitoring was testified.

  9. Do invasive alien plants really threaten river bank vegetation? A case study based on plant communities typical for Chenopodium ficifolium—An indicator of large river valleys

    Science.gov (United States)

    Nowak, Arkadiusz; Rola, Kaja

    2018-01-01

    Riparian zones are very rich in species but subjected to strong anthropogenic changes and extremely prone to alien plant invasions, which are considered to be a serious threat to biodiversity. Our aim was to determine the spatial distribution of Chenopodium ficifolium, a species demonstrating strong confinement to large river valleys in Central Europe and an indicator of annual pioneer nitrophilous vegetation developing on river banks, which are considered to be of importance to the European Community. Additionally, the habitat preferences of the species were analysed. Differences in the richness and abundance of species diagnostic for riverside habitats, as well as the contribution of resident and invasive alien species in vegetation plots along three rivers differing in terms of size and anthropogenic impact were also examined. Finally, the effect of invaders on the phytocoenoses typical for C. ficifolium was assessed. The frequency of C. ficifolium clearly decreased with an increasing distance from the river. Among natural habitats, the species mostly preferred the banks of large rivers. The vegetation plots developing on the banks of the three studied rivers differed in total species richness, the number and cover of resident, diagnostic and invasive alien species, as well as in species composition. Our research indicates that abiotic and anthropogenic factors are the most significant drivers of species richness and plant cover of riverbank vegetation, and invasive alien plants affect this type of vegetation to a small extent. PMID:29543919

  10. Do invasive alien plants really threaten river bank vegetation? A case study based on plant communities typical for Chenopodium ficifolium-An indicator of large river valleys.

    Science.gov (United States)

    Nobis, Agnieszka; Nowak, Arkadiusz; Rola, Kaja

    2018-01-01

    Riparian zones are very rich in species but subjected to strong anthropogenic changes and extremely prone to alien plant invasions, which are considered to be a serious threat to biodiversity. Our aim was to determine the spatial distribution of Chenopodium ficifolium, a species demonstrating strong confinement to large river valleys in Central Europe and an indicator of annual pioneer nitrophilous vegetation developing on river banks, which are considered to be of importance to the European Community. Additionally, the habitat preferences of the species were analysed. Differences in the richness and abundance of species diagnostic for riverside habitats, as well as the contribution of resident and invasive alien species in vegetation plots along three rivers differing in terms of size and anthropogenic impact were also examined. Finally, the effect of invaders on the phytocoenoses typical for C. ficifolium was assessed. The frequency of C. ficifolium clearly decreased with an increasing distance from the river. Among natural habitats, the species mostly preferred the banks of large rivers. The vegetation plots developing on the banks of the three studied rivers differed in total species richness, the number and cover of resident, diagnostic and invasive alien species, as well as in species composition. Our research indicates that abiotic and anthropogenic factors are the most significant drivers of species richness and plant cover of riverbank vegetation, and invasive alien plants affect this type of vegetation to a small extent.

  11. [Research on the spectral feature and identification of the surface vegetation stressed by stored CO2 underground leakage].

    Science.gov (United States)

    Chen, Yun-Hao; Jiang, Jin-Bao; Steven, Michael D; Gong, A-Du; Li, Yi-Fan

    2012-07-01

    With the global climate warming, reducing greenhouse gas emissions becomes a focused problem for the world. The carbon capture and storage (CCS) techniques could mitigate CO2 into atmosphere, but there is a risk in case that the CO2 leaks from underground. The objective of this paper is to study the chlorophyll contents (SPAD value), relative water contents (RWC) and leaf spectra changing features of beetroot under CO2 leakage stress through field experiment. The result shows that the chlorophyll contents and RWC of beetroot under CO2 leakage stress become lower than the control beetroot', and the leaf reflectance increases in the 550 nm region and decreases in the 680nm region. A new vegetation index (R550/R680) was designed for identifying beetroot under CO2 leakage stress, and the result indicates that the vegetation index R550/R680 could identify the beetroots after CO2 leakage for 7 days. The index has strong sensitivity, stability and identification for monitoring the beetroots under CO2 stress. The result of this paper has very important meaning and application values for selecting spots of CCS project, monitoring and evaluating land-surface ecology under CO2 stress and monitoring the leakage spots by using remote sensing.

  12. componente vegetal

    Directory of Open Access Journals (Sweden)

    Fabio Moscovich

    2005-01-01

    Full Text Available In order to determine environmental impact, indicators based on vegetation characteristics that would generate the forestry monoculture with the adjacent native forest, 32 sample unit were installed in an area of LIPSIA private enterprise, Esperanza Department, Misiones with those characteristics. The plots of 100 m2 were distributed systematically every 25 meters. The vegetation was divided in stratum: superior (DBH ≥ 10 cm, middle (1,6 cm ≤ DBH > 10 cm and inferior (DBH< cm. There were installed 10 plots in a logged native forest, 10 plots in a 18 years old Pinus elliottii Engelm. with approximately 400 trees/ha., 6 plots in a 10 – 25 years old Araucaria angustifolia (Bertd. Kuntze limiting area with approximately 900 trees/ha., and 6 plots located in this plantation. In the studied area were identified 150 vegetation species. In the inferior stratum there were found differences as function of various floristic diversity indexes. In all the cases the native forest showed larger diversity than plantations, followed by Pinus elliottii, Araucaria plantation and Araucaria limiting area. All the studied forest fitted to a logarithmical series of species distributions, that would indicate the incidence of a environmental factor in this distribution.

  13. Mapping vegetation communities using statistical data fusion in the Ozark National Scenic Riverways, Missouri, USA

    Science.gov (United States)

    Chastain, R.A.; Struckhoff, M.A.; He, H.S.; Larsen, D.R.

    2008-01-01

    A vegetation community map was produced for the Ozark National Scenic Riverways consistent with the association level of the National Vegetation Classification System. Vegetation communities were differentiated using a large array of variables derived from remote sensing and topographic data, which were fused into independent mathematical functions using a discriminant analysis classification approach. Remote sensing data provided variables that discriminated vegetation communities based on differences in color, spectral reflectance, greenness, brightness, and texture. Topographic data facilitated differentiation of vegetation communities based on indirect gradients (e.g., landform position, slope, aspect), which relate to variations in resource and disturbance gradients. Variables derived from these data sources represent both actual and potential vegetation community patterns on the landscape. A hybrid combination of statistical and photointerpretation methods was used to obtain an overall accuracy of 63 percent for a map with 49 vegetation community and land-cover classes, and 78 percent for a 33-class map of the study area. ?? 2008 American Society for Photogrammetry and Remote Sensing.

  14. WILDFIRE INDUCED DEGRADATION OF WOODY VEGETATION IN DRY ZONE OF KAZAKHSTAN

    Directory of Open Access Journals (Sweden)

    A. Terekhov

    2012-08-01

    Full Text Available Small bushy tree species dominate the semi-arid areas of Kazakhstan. In the course of their life cycle, they form a layer of litter that is resistant to wind transport. This small shrub species with its own litter play a significant role in the spectral characteristics of the Earth surface. Changes in the density of shrub canopy forms or replacing them with herbaceous species is accompanied by significant changes in the spectral characteristics in the visible and near infrared spectral bands in the autumn. These changes can be recorded from satellite data. LANDSAT-TM images during 1985–2007 years and MODIS data (USGS: MOD09Q1, 2000–2010 used to diagnose changes in relation between woody\\herbaceous vegetation species in the dry zone of Kazakhstan. It was found that over the past 10 years, spreading small shrub forms of semi-arid vegetation significantly decreased. There is a persistent expansion of herbal forms, leading to the semi-steppe formation areas. The mechanism of repression of wood forms constructed through the accumulation of dry plant mass during wet years, with its subsequent burnout during wildfires. In the case of a strong fire, a complete destruction of species is observed. The restoration of small shrub cover demands more than 20 years. Comparative analysis of LANDSAT-TM images showed a 10 times increasing of the fire scar areas in the test area in the central part of Kazakhstan between 1985 and 2007. According MOD09Q1 was conducted mapping small shrub forms of degradation in Kazakhstan. Reducing the area occupied by woody vegetation, semi-desert was about 30 million hectares or over 30% of their total range in Kazakhstan.

  15. Remote sensing of potential and actual daily transpiration of plant canopies based on spectral reflectance and infrared thermal measurements: Concept with preliminary test

    International Nuclear Information System (INIS)

    Inoue, Y.; Moran, M.S.; Pinter, P.J.Jr.

    1994-01-01

    A new concept for estimating potential and actual values of daily transpiration rate of vegetation canopies is presented along with results of an initial test. The method is based on a physical foundation of spectral radiation balance for a vegetation canopy, the key inputs to the model being the remotely sensed spectral reflectance and the surface temperature of the plant canopy. The radiation interception or absorptance is estimated more directly from remotely sensed spectral data than it is from the leaf area index. The potential daily transpiration is defined as a linear function of the absorbed solar radiation, which can be estimated using a linear relationship between the fraction absorptance of solar radiation and the remotely sensed Soil Adjusted Vegetation Index for the canopy. The actual daily transpiration rate is estimated by combining this concept with the Jackson-Idso Crop Water Stress Index, which also can be calculated from remotely sensed plant leaf temperatures measured by infrared thermometry. An initial demonstration with data sets from an alfalfa crop and a rangeland suggests that the method may give reasonable estimates of potential and actual values of daily transpiration rate over diverse vegetation area based on simple remote sensing measurements and basic meteorological parameters

  16. Basic Functional Analysis Puzzles of Spectral Flow

    DEFF Research Database (Denmark)

    Booss-Bavnbek, Bernhelm

    2011-01-01

    We explain an array of basic functional analysis puzzles on the way to general spectral flow formulae and indicate a direction of future topological research for dealing with these puzzles.......We explain an array of basic functional analysis puzzles on the way to general spectral flow formulae and indicate a direction of future topological research for dealing with these puzzles....

  17. The experimental determination and evaluation of the spectral indices of the IPEN/MB-01 reactor for the IRPhE project

    International Nuclear Information System (INIS)

    Santos, Adimir dos; Fanaro, Leda C.C.B.; Jerez, Rogério

    2013-01-01

    Highlights: • A new experimental method for the spectral index measurements was developed. • The method eliminates the need of calculated correction factors for the case of 28 ρ. • The experimental results were approved for inclusion in the IRPhE handbook. • MCNP5 with ENDF/B-VII.0 described well the experimental data. - Abstract: New experimental results for the spectral indices of the IPEN/MB-01 reactor are presented in this work. The experimental approach considers a new technique for the 28 ρ case which does not require any sort of calculated correction factors. This aspect gave to the IPEN/MB-01 experiment an excellent quality and free of possible bias due to these calculated correction factors. The uncertainty analysis show, even considering the uncertainties of the geometric and material data of the facility, that the final uncertainties are small enough and well understood for a benchmark problem. The experiment was evaluated and included in the IRPhE handbook. The theory/experiment comparison reveals that there is considerable progress in the 238 U nuclear data for application in thermal reactors. The theory/experiment comparison employs the nuclear data libraries ENDF/B-VII.0, ENDF/B-VI.8, JEF3.1, and JENDL3.3 and reveals an excellent agreement for the spectral index 28 ρ * independently of the nuclear data library considered; aspect never found before in several other comparisons. The long term overprediction of the 238 U neutron epithermal capture appears to be eliminated with the improvements in the recent nuclear data libraries. The experimental performed at the IPEN/MB-01 reactor supports the changes in the 238 U nuclear data incorporated in ENDF/B-VII.0 as well as in the other libraries studied in this work. The theory/experiment comparison of 25 δ * and (C8/F) ept show that these spectral indices are in general slightly overpredicted, thus suggesting that the thermal fission cross section of 235 U might be a little bit underestimated

  18. Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey

    Directory of Open Access Journals (Sweden)

    Osman Orhan

    2014-01-01

    Full Text Available The main purpose of this paper is to investigate multitemporal land surface temperature (LST changes by using satellite remote sensing data. The study included a real-time field work performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake, Turkey. Normalized vegetation index (NDVI, vegetation condition index (VCI, and temperature vegetation index (TVX were used for evaluating drought impact over the region between 1984 and 2011. In the image processing step, geometric and radiometric correction procedures were conducted to make satellite remote sensing data comparable with in situ measurements carried out using thermal infrared thermometer supported by hand-held GPS. The results showed that real-time ground and satellite remote sensing data were in good agreement with correlation coefficient (R2 values of 0.90. The remotely sensed and treated satellite images and resulting thematic indices maps showed that dramatic land surface temperature changes occurred (about 2∘C in the Salt Lake Basin area during the 28-year period (1984–2011. Analysis of air temperature data also showed increases at a rate of 1.5–2∘C during the same period. Intensification of irrigated agriculture particularly in the southern basin was also detected. The use of water supplies, especially groundwater, should be controlled considering particularly summer drought impacts on the basin.

  19. CHANGE DETECTION OF CROPPING PATTERN IN PADDY FIELD USING MULTI SPECTRAL SATELLITE DATA FOR ESTIMATING IRRIGATION WATER NEEDS

    Directory of Open Access Journals (Sweden)

    Rizatus Shofiyati1

    2012-10-01

    Full Text Available This paper investigates the use of multi spectral satellite data for cropping pattern monitoring in paddy field. The southern coastal of Citarum watershed, West Java Province was selected as study sites. The analysis used in this study is identifying crop pattern based on growth stages of wetland paddy and other crops by investi-gating the characteristic of Normalized Differen-ce Vegetation Indices (NDVI and Wetness of Tasseled Cap Transformation (TCT derived from 14 scenes of Landsat TM date 1988 to 2001. In general, the phenological of growth stages of wetland paddy can be used to distinguish with other seasonal crops. The research results indicate that multi spectral satellite data has a great potential for identi-fication and monitoring cropping pattern in paddy field. Specific character of NDVI and Wetness can also produce a map of cropping pattern in paddy field that is useful to monitor agricultural land condition. The cropping pattern can also be used to estimate irrigation water needed of paddy field in the area. Expected implication of the information obtained from this analysis is useful for guiding more appropriate planning and better agricultural management.

  20. Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

    Science.gov (United States)

    Chiang, Y.; Chen, K.

    2013-12-01

    This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

  1. ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

  2. Automatic summary generating technology of vegetable traceability for information sharing

    Science.gov (United States)

    Zhenxuan, Zhang; Minjing, Peng

    2017-06-01

    In order to solve problems of excessive data entries and consequent high costs for data collection in vegetable traceablility for farmers in traceability applications, the automatic summary generating technology of vegetable traceability for information sharing was proposed. The proposed technology is an effective way for farmers to share real-time vegetable planting information in social networking platforms to enhance their brands and obtain more customers. In this research, the influencing factors in the vegetable traceablility for customers were analyzed to establish the sub-indicators and target indicators and propose a computing model based on the collected parameter values of the planted vegetables and standard legal systems on food safety. The proposed standard parameter model involves five steps: accessing database, establishing target indicators, establishing sub-indicators, establishing standard reference model and computing scores of indicators. On the basis of establishing and optimizing the standards of food safety and traceability system, this proposed technology could be accepted by more and more farmers and customers.

  3. Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)

    Science.gov (United States)

    Wilson, Natalie R.; Norman, Laura

    2018-01-01

    Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann– Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.

  4. Spectral features based tea garden extraction from digital orthophoto maps

    Science.gov (United States)

    Jamil, Akhtar; Bayram, Bulent; Kucuk, Turgay; Zafer Seker, Dursun

    2018-05-01

    The advancements in the photogrammetry and remote sensing technologies has made it possible to extract useful tangible information from data which plays a pivotal role in various application such as management and monitoring of forests and agricultural lands etc. This study aimed to evaluate the effectiveness of spectral signatures for extraction of tea gardens from 1 : 5000 scaled digital orthophoto maps obtained from Rize city in Turkey. First, the normalized difference vegetation index (NDVI) was derived from the input images to suppress the non-vegetation areas. NDVI values less than zero were discarded and the output images was normalized in the range 0-255. Individual pixels were then mapped into meaningful objects using global region growing technique. The resulting image was filtered and smoothed to reduce the impact of noise. Furthermore, geometrical constraints were applied to remove small objects (less than 500 pixels) followed by morphological opening operator to enhance the results. These objects served as building blocks for further image analysis. Finally, for the classification stage, a range of spectral values were empirically calculated for each band and applied on candidate objects to extract tea gardens. For accuracy assessment, we employed an area based similarity metric by overlapping obtained tea garden boundaries with the manually digitized tea garden boundaries created by experts of photogrammetry. The overall accuracy of the proposed method scored 89 % for tea gardens from 10 sample orthophoto maps. We concluded that exploiting the spectral signatures using object based analysis is an effective technique for extraction of dominant tree species from digital orthophoto maps.

  5. Advances in remote sensing of vegetation function and traits

    KAUST Repository

    Houborg, Rasmus

    2015-07-09

    Remote sensing of vegetation function and traits has advanced significantly over the past half-century in the capacity to retrieve useful plant biochemical, physiological and structural quantities across a range of spatial and temporal scales. However, the translation of remote sensing signals into meaningful descriptors of vegetation function and traits is still associated with large uncertainties due to complex interactions between leaf, canopy, and atmospheric mediums, and significant challenges in the treatment of confounding factors in spectrum-trait relations. This editorial provides (1) a background on major advances in the remote sensing of vegetation, (2) a detailed timeline and description of relevant historical and planned satellite missions, and (3) an outline of remaining challenges, upcoming opportunities and key research objectives to be tackled. The introduction sets the stage for thirteen Special Issue papers here that focus on novel approaches for exploiting current and future advancements in remote sensor technologies. The described enhancements in spectral, spatial and temporal resolution and radiometric performance provide exciting opportunities to significantly advance the ability to accurately monitor and model the state and function of vegetation canopies at multiple scales on a timely basis.

  6. Benchmarking LSM root-zone soil mositure predictions using satellite-based vegetation indices

    Science.gov (United States)

    The application of modern land surface models (LSMs) to agricultural drought monitoring is based on the premise that anomalies in LSM root-zone soil moisture estimates can accurately anticipate the subsequent impact of drought on vegetation productivity and health. In addition, the water and energy ...

  7. Night sleep in patients with vegetative state.

    Science.gov (United States)

    Pavlov, Yuri G; Gais, Steffen; Müller, Friedemann; Schönauer, Monika; Schäpers, Barbara; Born, Jan; Kotchoubey, Boris

    2017-10-01

    Polysomnographic recording of night sleep was carried out in 15 patients with the diagnosis vegetative state (syn. unresponsive wakefulness syndrome). Sleep scoring was performed by three raters, and confirmed by means of a spectral power analysis of the electroencephalogram, electrooculogram and electromyogram. All patients but one exhibited at least some signs of sleep. In particular, sleep stage N1 was found in 13 patients, N2 in 14 patients, N3 in nine patients, and rapid eye movement sleep in 10 patients. Three patients exhibited all phenomena characteristic for normal sleep, including spindles and rapid eye movements. However, in all but one patient, sleep patterns were severely disturbed as compared with normative data. All patients had frequent and long periods of wakefulness during the night. In some apparent rapid eye movement sleep episodes, no eye movements were recorded. Sleep spindles were detected in five patients only, and their density was very low. We conclude that the majority of vegetative state patients retain some important circadian changes. Further studies are necessary to disentangle multiple factors potentially affecting sleep pattern of vegetative state patients. © 2017 European Sleep Research Society.

  8. From the Icy Satellites to Small Moons and Rings: Spectral Indicators by Cassini-VIMS Unveil Compositional Trends in the Saturnian System

    Science.gov (United States)

    Filacchione, G.; Capaccioni, F.; Ciarniello, M.; Nicholson, P. D.; Clark, R. N.; Cuzzi, J. N.; Buratti, B. B.; Cruikshank, D. P.; Brown, R. H.

    2017-01-01

    Despite water ice being the most abundant species on Saturn satellites' surfaces and ring particles, remarkable spectral differences in the 0.35-5.0 μm range are observed among these objects. Here we report about the results of a comprehensive analysis of more than 3000 disk-integrated observations of regular satellites and small moons acquired by VIMS aboard Cassini mission between 2004 and 2016. These observations, taken from very different illumination and viewing geometries, allow us to classify satellites' and rings' compositions by means of spectral indicators, e.g. 350-550 nm - 550-950 nm spectral slopes and water ice band parameters [1,2,3]. Spectral classification is further supported by indirect retrieval of temperature by means of the 3.6 μm I/F peak wavelength [4,5]. The comparison with syntethic spectra modeled by means of Hapke's theory point to different compositional classes where water ice, amorphous carbon, tholins and CO2 ice in different quantities and mixing modalities are the principal endmembers [3, 6]. When compared to satellites, rings appear much more red at visible wavelengths and show more intense 1.5-2.0 μm band depths [7]. Our analysis shows that spectral classes are detected among the principal satellites with Enceladus and Tethys the ones with stronger water ice band depths and more neutral spectral slopes while Rhea evidences less intense band depths and more red visible spectra. Even more intense reddening in the 0.55-0.95 μm range is observed on Iapetus leading hemisphere [8] and on Hyperion [9]. With an intermediate reddening, the minor moons seems to be the spectral link between the principal satellites and main rings [10]: Prometheus and Pandora appear similar to Cassini Division ring particles. Epimetheus shows more intense water ice bands than Janus. Epimetheus' visible colors are similar to water ice rich moons while Janus is more similar to C ring particles. Finally, Dione and Tethys lagrangian satellites show a very

  9. Impact of soil moisture and winter wheat height from the Loess Plateau in Northwest China on surface spectral albedo

    Science.gov (United States)

    Li, Zhenchao; Yang, Jiaxi; Gao, Xiaoqing; Zheng, Zhiyuan; Yu, Ye; Hou, Xuhong; Wei, Zhigang

    2018-02-01

    The understanding of surface spectral radiation and reflected radiation characteristics of different surfaces in different climate zones aids in the interpretation of regional surface energy transfers and the development of land surface models. This study analysed surface spectral radiation variations and corresponding surface albedo characteristics at different wavelengths as well as the relationship between 5-cm soil moisture and surface albedo on typical sunny days during the winter wheat growth period. The analysis was conducted using observational Loess Plateau winter wheat data from 2015. The results show that the ratio of atmospheric downward radiation to global radiation on typical sunny days is highest for near-infrared wavelengths, followed by visible wavelengths and ultraviolet wavelengths, with values of 57.3, 38.7 and 4.0%, respectively. The ratio of reflected spectral radiation to global radiation varies based on land surface type. The visible radiation reflected by vegetated surfaces is far less than that reflected by bare ground, with surface albedos of 0.045 and 0.27, respectively. Thus, vegetated surfaces absorb more visible radiation than bare ground. The atmospheric downward spectral radiation to global radiation diurnal variation ratios vary for near-infrared wavelengths versus visible and ultraviolet wavelengths on typical sunny days. The near-infrared wavelengths ratio is higher in the morning and evening and lower at noon. The visible and ultraviolet wavelengths ratios are lower in the morning and evening and higher at noon. Visible and ultraviolet wavelength surface albedo is affected by 5-cm soil moisture, demonstrating a significant negative correlation. Excluding near-infrared wavelengths, correlations between surface albedo and 5-cm soil moisture pass the 99% confidence test at each wavelength. The correlation with 5-cm soil moisture is more significant at shorter wavelengths. However, this study obtained surface spectral radiation

  10. Trends in global vegetation activity and climatic drivers indicate a decoupled response to climate change

    DEFF Research Database (Denmark)

    Schut, Antonius G T; Ivits, Eva; Conijn, Jacob G.

    2015-01-01

    Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty...... in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS......-NPP) and TBWper biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land...

  11. Identification of acetates in elasmopalpulus lignosellus pheromone glands using a newly created mass spectral database and kóvats retention indices

    OpenAIRE

    Jham, Gulab N.; Silva, Alexsandro A. da; Lima, Eraldo R.; Viana, Paulo A.

    2007-01-01

    Based on a specially created mass spectral database utilizing 23 tetradecenyl and 22 hexadecenyl acetate standards along with Kóvats retention indices obtained on a very polar stationary phase [poly (biscyanopropyl siloxane)] (SP 2340), (Z)-9-hexadecenyl acetate, (Z)-11-hexadecenyl acetate and (E)-8-hexadecenyl acetate were identified in active pheromone extracts of Elasmopalpus lignosellus. This identification was more efficient than our previous study using gas chromatography/mass spectrome...

  12. Pollen and phytoliths from fired ancient potsherds as potential indicators for deciphering past vegetation and climate in Turpan, Xinjiang, NW China.

    Science.gov (United States)

    Yao, Yi-Feng; Li, Xiao; Jiang, Hong-En; Ferguson, David K; Hueber, Francis; Ghosh, Ruby; Bera, Subir; Li, Cheng-Sen

    2012-01-01

    It is demonstrated that palynomorphs can occur in fired ancient potsherds when the firing temperature was under 350°C. Pollen and phytoliths recovered from incompletely fired and fully fired potsherds (ca. 2700 yrs BP) from the Yanghai Tombs, Turpan, Xinjiang, NW China can be used as potential indicators for reconstructing past vegetation and corresponding climate in the area. The results show a higher rate of recovery of pollen and phytoliths from incompletely fired potsherds than from fully fired ones. Charred phytoliths recovered from both fully fired and incompletely fired potsherds prove that degree and condition of firing result in a permanent change in phytolith color. The palynological data, together with previous data of macrobotanical remains from the Yanghai Tombs, suggest that temperate vegetation and arid climatic conditions dominated in the area ca. 2700 yrs BP.

  13. Results and interpretation of spectral indices measurements made with AQUILON; Resultats et interpretation de mesures d'indices de spectre dans aquilon

    Energy Technology Data Exchange (ETDEWEB)

    Frichet, J P; Mougey, J N; Naudet, R; Taste, J [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1965-07-01

    This report deals with a set of spectral indices measurements made in the heavy water reactor Aquilon on lattices constituted by massive fuel elements of dia. 29,2 mm. The fuel elements were made either of natural uranium or of slightly depleted or slightly enriched uranium, or of an uranium-plutonium alloy. The measurements were carried out for various lattice pitches (square pitch from 110 to 210 mm) and in certain cases for various temperatures (from 20 to 80 deg. C). The results are compared to calculated values obtained by using the latest advances of the thermalization theory developed at Saclay applied to the moderation by heavy water. (authors) [French] Ce rapport est consacre a un ensemble de mesures d'indices de spectre realisees dans la pile a eau lourde Aquilon sur des reseaux d'elements combustibles pleins, de 29,2 mm de diametre. Ces combustibles se composaient ou bien d'uranium naturel, ou bien d'uranium tres legerement appauvri ou enrichi, ou bien d'un alliage uranium plutonium. Les mesures ont ete effectuees pour toute une serie de pas de reseaux (pas carre 110 a 210 mm), certaines d'entre elles a plusieurs temperatures (20 a 80 deg. C). Les resultats des mesures sont compares a des valeurs calculees obtenues en utilisant les plus recents developpements de la theorie de la thermalisation mise au point a Saclay, appliques au cas de la moderation par l'eau lourde. (auteurs)

  14. Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm

    Science.gov (United States)

    Kokaly, Raymond F.; Skidmore, Andrew K

    2015-01-01

    Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic C-H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf (r2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf (r2 = 0.79, RMSE = 2.1%, n = 56), and canopy (r2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the

  15. Response of vegetable organisms to quasi-monochromatic light of different duration, intensity and wavelength

    Energy Technology Data Exchange (ETDEWEB)

    Budagovsky, A V; Solovykh, N V [I.V.Michurin All-Russian Recearch Institute of Fruit Crops Genetics and Breeding (Russian Federation); Budagovskaya, O N [I.V.Michurin All-Russia Research and Development Institute of Gardening, Michurinsk, Tambov region (Russian Federation); Budagovsky, I A [P N Lebedev Physics Institute, Russian Academy of Sciences, Moscow (Russian Federation)

    2015-04-30

    By the example of vegetable organisms differing in structure and functional properties it is shown that their response to the action of quasi-monochromatic light from laser sources does not obey the Bunsen – Roscoe dose law. The dependence of biological effect on the irradiation time has the multimodal (multiextremal) form with alternating maxima and minima of the stimulating effect. Such a property manifests itself in the spectral ranges, corresponding to photoinduced conversion of chromoproteins of photocontrol systems and is probably related to the cyclic variations of metabolic activity in vegetable cells. (biophotonics)

  16. Structural Changes of Desertified and Managed Shrubland Landscapes in Response to Drought: Spectral, Spatial and Temporal Analyses

    Directory of Open Access Journals (Sweden)

    Tarin Paz-Kagan

    2014-08-01

    Full Text Available Drought events cause changes in ecosystem function and structure by reducing the shrub abundance and expanding the biological soil crusts (biocrusts. This change increases the leakage of nutrient resources and water into the river streams in semi-arid areas. A common management solution for decreasing this loss of resources is to create a runoff-harvesting system (RHS. The objective of the current research is to apply geo-information techniques, including remote sensing and geographic information systems (GIS, on the watershed scale, to monitor and analyze the spatial and temporal changes in response to drought of two source-sink systems, the natural shrubland and the human-made RHSs in the semi-arid area of the northern Negev Desert, Israel. This was done by evaluating the changes in soil, vegetation and landscape cover. The spatial changes were evaluated by three spectral indices: Normalized Difference Vegetation Index (NDVI, Crust Index (CI and landscape classification change between 2003 and 2010. In addition, we examined the effects of environmental factors on NDVI, CI and their clustering after successive drought years. The results show that vegetation cover indicates a negative ∆NDVI change due to a reduction in the abundance of woody vegetation. On the other hand, the soil cover change data indicate a positive ∆CI change due to the expansion of the biocrusts. These two trends are evidence for degradation processes in terms of resource conservation and bio-production. A considerable part of the changed area (39% represents transitions between redistribution processes of resources, such as water, sediments, nutrients and seeds, on the watershed scale. In the pre-drought period, resource redistribution mainly occurred on the slope scale, while in the post-drought period, resource redistribution occurred on the whole watershed scale. However, the RHS management is effective in reducing leakage, since these systems are located on the

  17. Innovative Hyperspectral Imaging-Based Techniques for Quality Evaluation of Fruits and Vegetables: A Review

    Directory of Open Access Journals (Sweden)

    Yuzhen Lu

    2017-02-01

    Full Text Available New, non-destructive sensing techniques for fast and more effective quality assessment of fruits and vegetables are needed to meet the ever-increasing consumer demand for better, more consistent and safer food products. Over the past 15 years, hyperspectral imaging has emerged as a new generation of sensing technology for non-destructive food quality and safety evaluation, because it integrates the major features of imaging and spectroscopy, thus enabling the acquisition of both spectral and spatial information from an object simultaneously. This paper first provides a brief overview of hyperspectral imaging configurations and common sensing modes used for food quality and safety evaluation. The paper is, however, focused on the three innovative hyperspectral imaging-based techniques or sensing platforms, i.e., spectral scattering, integrated reflectance and transmittance, and spatially-resolved spectroscopy, which have been developed in our laboratory for property and quality evaluation of fruits, vegetables and other food products. The basic principle and instrumentation of each technique are described, followed by the mathematical methods for processing and extracting critical information from the acquired data. Applications of these techniques for property and quality evaluation of fruits and vegetables are then presented. Finally, concluding remarks are given on future research needs to move forward these hyperspectral imaging techniques.

  18. [Research on identification of species of fruit trees by spectral analysis].

    Science.gov (United States)

    Xing, Dong-Xing; Chang, Qing-Rui

    2009-07-01

    Using the spectral reflectance data (R2) of canopies, the present paper identifies seven species of fruit trees bearing fruit in the fruit mature period. Firstly, it compares the fruit tree species identification capability of six kinds of satellite sensors and four kinds of vegetation index through re-sampling the spectral data with six kinds of pre-defined filter function and the related data processing of calculating vegetation indexes. Then, it structures a BP neural network model for identifying seven species of fruit trees on the basis of choosing the best transformation of R(lambda) and optimizing the model parameters. The main conclusions are: (1) the order of the identification capability of the six kinds of satellite sensors from strong to weak is: MODIS, ASTER, ETM+, HRG, QUICKBIRD and IKONOS; (2) among the four kinds of vegetation indexes, the identification capability of RVI is the most powerful, the next is NDVI, while the identification capability of SAVI or DVI is relatively weak; (3) The identification capability of RVI and NDVI calculated with the reflectance of near-infrared and red channels of ETM+ or MODIS sensor is relatively powerful; (4) Among R(lambda) and its 22 kinds of transformation data, d1 [log(1/R(lambda))](derivative gap is set 9 nm) is the best transformation for structuring BP neural network model; (5) The paper structures a 3-layer BP neural network model for identifying seven species of fruit trees using the best transformation of R(lambda) which is d1 [log(1/R(lambda))](derivative gap is set 9 nm).

  19. Measurements of spectral indices in homogeneous multiplying media; Mesures d'indices de spectre dans les milieux multiplicateurs homogenes

    Energy Technology Data Exchange (ETDEWEB)

    Bruna, J G; Brunet, J P; Clouet D' Orval, Ch; Verriere, Ph; Kremser, J; Moret-Bailly, J; Tellier, H [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1964-07-01

    Methods for computation of spectra in light water are developed at Saclay and it is interesting to carry out at the same time experimental studies of simple media such as solutions of fissionable salts which allow quite direct comparisons with computed values. The spectral indices measurements were made with two small fission chambers, one containing deposited plutonium, the other deposited uranium 235. Their response, when neutron spectrum is modified, allows to study the epithermal part of the flux. The media studied with these chambers are fissionable solutions (of plutonium or 90 per cent enriched uranium) which were made critical in bare cylindrical geometry in the Alecto reactor. If the ratio of the chambers is normalized to unity in a Maxwell spectrum, then the noted variation of the ratio of the counts Pu chamber/ U{sup 235} chamber reaches 1,4 in the range of the studied concentrations. (authors) [French] Des calculs de spectres dans l'eau legere sont mis au point a Saclay et il est interessant de mener parallelement des etudes experimentale sur des milieux simples tels que des solutions de sels fissiles, qui permettent des comparaisons tres directes avec les valeurs calculees. On a choisi d'effectuer des mesures d' 'indices de spectres' a l'aide de de deux petites chambres a fission contenant des depots, l'une de plutonium, l'autre d'uranium 235. Leur reponse lorsque le spectre des neutrons est modifie permet d'etudier la partie epithermique du flux. Les milieux etudies a l'aide de ces chambres sont des solutions fissiles (plutonium ou uranium enrichi a 90 pour cent) rendus critiques, en geometrie cylindrique nue, dans le reacteur Alecto. Si le rapport des chambres est normalise a un dans un spectre de Maxwell, la variation constatee du rapport des comptages chambre Pu/ chambre U{sup 235} atteint, dans les gammes de concentrations etudiees, 1,4. (auteurs)

  20. Airborne spectral measurements of surface anisotropy during SCAR-B

    Science.gov (United States)

    Tsay, Si-Chee; King, Michael D.; Arnold, G. Thomas; Li, Jason Y.

    1998-12-01

    During the Smoke, Clouds, and Radiation-Brazil (SCAR-B) deployment, angular distributions of spectral reflectance for vegetated surfaces and smoke layers were measured using the scanning cloud absorption radiometer (CAR) mounted on the University of Washington C-131A research aircraft. The CAR contains 13 narrowband spectral channels between 0.3 and 2.3 μm with a 190° scan aperture (5° before zenith to 5° past nadir) and 1° instantaneous field of view. The bidirectional reflectance is obtained by flying a clockwise circular orbit above the surface, resulting in a ground track ˜3 km in diameter within about 2 min. Although the CAR measurements are contaminated by minor atmospheric effects, results show distinct spectral characteristics for various types of surfaces. Spectral bidirectional reflectances of three simple and well-defined surfaces are presented: cerrado (August 18, 1995) and dense forest (August 25, 1995), both measured in Brazil under nearly clear-sky conditions, and thick smoke layers over dense forest (September 6 and 11, 1995). The bidirectional reflectances of cerrado and dense forest revealed fairly symmetric patterns along the principal plane, with varying maximal strengths and widths spectrally in the backscattering direction. In the shortwave-infrared region the aerosol effect is very small due to low spectral optical depth. Also, these backscattering maxima can be seen on the bidirectional reflectance of smoke layer over dense forest. These detailed measurements of the angular distribution of spectral reflectance can be parameterized by a few independent variables and utilized to retrieve either surface characteristics or aerosol microphysical and optical properties (e.g., size distribution and single-scattering parameters), if proper physical and radiation models are used. The spectral-hemispherical albedo of these surfaces is obtained directly by integrating all angular measurements and is compared with the measured nadir reflectance

  1. Coupling Analysis of Heat Island Effects, Vegetation Coverage and Urban Flood in Wuhan

    Science.gov (United States)

    Liu, Y.; Liu, Q.; Fan, W.; Wang, G.

    2018-04-01

    In this paper, satellite image, remote sensing technique and geographic information system technique are main technical bases. Spectral and other factors comprehensive analysis and visual interpretation are main methods. We use GF-1 and Landsat8 remote sensing satellite image of Wuhan as data source, and from which we extract vegetation distribution, urban heat island relative intensity distribution map and urban flood submergence range. Based on the extracted information, through spatial analysis and regression analysis, we find correlations among heat island effect, vegetation coverage and urban flood. The results show that there is a high degree of overlap between of urban heat island and urban flood. The area of urban heat island has buildings with little vegetation cover, which may be one of the reasons for the local heavy rainstorms. Furthermore, the urban heat island has a negative correlation with vegetation coverage, and the heat island effect can be alleviated by the vegetation to a certain extent. So it is easy to understand that the new industrial zones and commercial areas which under constructions distribute in the city, these land surfaces becoming bare or have low vegetation coverage, can form new heat islands easily.

  2. Comparison of Landsat 8 OLI and Landsat 7 ETM+ for estimating grassland LAI using model inversion and spectral indices: case study of Mpumalanga, South Africa

    CSIR Research Space (South Africa)

    Masemola, Cecilia

    2016-06-01

    Full Text Available the radiative transfer model (RTM) and spectral indices approaches for estimating LAI on rangeland systems in South Africa. The RTM was inverted using artificial neural network (ANN) and lookup table (LUT) algorithms. The accuracy of the models was higher...

  3. Multi‐angular observations of vegetation indices from UAV cameras

    DEFF Research Database (Denmark)

    Sobejano-Paz, Veronica; Wang, Sheng; Jakobsen, Jakob

    Unmanned aerial vehicles (UAVs) are found as an alternative to the classical manned aerial photogrammetry, which can be used to obtain environmental data or as a complementary solution to other methods (Nex and Remondino, 2014). Although UAVs have coverage limitations, they have better resolution...... (Berni et al., 2009), hyper spectral camera (Burkart et al., 2015) and photometric elevation mapping sensor (Shahbazi et al., 2015) among others. Therefore, UAVs can be used in many fields such as agriculture, forestry, archeology, architecture, environment and traffic monitoring (Nex and Remondino, 2014......). In this study, the UAV used is a hexacopter s900 equipped with a Global Positioning System (GPS) and two cameras; a digital RGB photo camera and a multispectral camera (MCA), with a resolution of 5472 x 3648 pixels and 1280 x 1024 pixels, respectively. In terms of applications, traditional methods using...

  4. Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation)

    Science.gov (United States)

    Marshall, Michael T.; Thenkabail, Prasad S.; Biggs, Trent; Post, Kirk

    2016-01-01

    Evapotranspiration (ET) is an important component of micro- and macro-scale climatic processes. In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295 nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10 nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (ΔR2 = 0.12), transpiration (ΔR2 = 0.17), and soil evaporation (ΔR2 = 0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong (R2 = 0.51), but the hyperspectral equivalent was superior (R2 = 0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R2 = 0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953 nm (R2 = 0.72) or 428 and 1518 nm (R2 = 0.69).

  5. Dynamics of climatic characteristics influencing vegetation in Siberia

    International Nuclear Information System (INIS)

    Shulgina, Tamara M; Genina, Elena Yu; Gordov, Evgeny P

    2011-01-01

    The spatiotemporal pattern of the dynamics of surface air temperature and precipitation and those bioclimatic indices that are based upon factors which control vegetation cover are investigated. Surface air temperature and precipitation data are retrieved from the ECMWF ERA Interim reanalysis and APHRODITE JMA datasets, respectively, which were found to be the closest to the observational data. We created an archive of bioclimatic indices for further detailed studies of interrelations between local climate and vegetation cover changes, which include carbon uptake changes related to changes of vegetation types and amount, as well as with spatial shifts of vegetation zones. Meanwhile, analysis reveals significant positive trends of the growing season length accompanied by a statistically significant increase of the sums of the growing degree days and precipitation over the south of West Siberia. The trends hint at a tendency for an increase of vegetation ecosystems' productivity across the south of West Siberia (55°–60°N, 59°–84°E) in the past several decades and (if sustained) may lead to a future increase of vegetation productivity in this region.

  6. THEORETICAL MODELLING STUDY ON THE RELATIONSHIP BETWEEN MULTI-FREQUENCY MICROWAVE VEGETATION INDEX AND VEGETATION PROPERTIES (OPTICAL DEPTH AND SINGLE SCATTERING ALBEDO

    Directory of Open Access Journals (Sweden)

    S. Talebi

    2018-04-01

    Full Text Available This paper presents a theoretical study of derivation Microwave Vegetation Indices (MVIs in different pairs of frequencies using two methods. In the first method calculating MVI in different frequencies based on Matrix Doubling Model (to take in to account multi scattering effects has been done and analyzed in various soil properties. The second method was based on MVI theoretical basis and its independency to underlying soil surface signals. Comparing the results from two methods with vegetation properties (single scattering albedo and optical depth indicated partial correlation between MVI from first method and optical depth, and full correlation between MVI from second method and vegetation properties. The second method to derive MVI can be used widely in global microwave vegetation monitoring.

  7. Investigation on the Patterns of Global Vegetation Change Using a Satellite-Sensed Vegetation Index

    Directory of Open Access Journals (Sweden)

    Ainong Li

    2010-06-01

    Full Text Available The pattern of vegetation change in response to global change still remains a controversial issue. A Normalized Difference Vegetation Index (NDVI dataset compiled by the Global Inventory Modeling and Mapping Studies (GIMMS was used for analysis. For the period 1982–2006, GIMMS-NDVI analysis indicated that monthly NDVI changes show homogenous trends in middle and high latitude areas in the northern hemisphere and within, or near, the Tropic of Cancer and Capricorn; with obvious spatio-temporal heterogeneity on a global scale over the past two decades. The former areas featured increasing vegetation activity during growth seasons, and the latter areas experienced an even greater amplitude in places where precipitation is adequate. The discussion suggests that one should be cautious of using the NDVI time-series to analyze local vegetation dynamics because of its coarse resolution and uncertainties.

  8. Algorithm for retrieving vegetative canopy and leaf parameters from multi- and hyperspectral imagery

    Science.gov (United States)

    Borel, Christoph

    2009-05-01

    In recent years hyper-spectral data has been used to retrieve information about vegetative canopies such as leaf area index and canopy water content. For the environmental scientist these two parameters are valuable, but there is potentially more information to be gained as high spatial resolution data becomes available. We developed an Amoeba (Nelder-Mead or Simplex) based program to invert a vegetative canopy radiosity model coupled with a leaf (PROSPECT5) reflectance model and modeled for the background reflectance (e.g. soil, water, leaf litter) to a measured reflectance spectrum. The PROSPECT5 leaf model has five parameters: leaf structure parameter Nstru, chlorophyll a+b concentration Cab, carotenoids content Car, equivalent water thickness Cw and dry matter content Cm. The canopy model has two parameters: total leaf area index (LAI) and number of layers. The background reflectance model is either a single reflectance spectrum from a spectral library() derived from a bare area pixel on an image or a linear mixture of soil spectra. We summarize the radiosity model of a layered canopy and give references to the leaf/needle models. The method is then tested on simulated and measured data. We investigate the uniqueness, limitations and accuracy of the retrieved parameters on canopy parameters (low, medium and high leaf area index) spectral resolution (32 to 211 band hyperspectral), sensor noise and initial conditions.

  9. Space-resolved analysis of trace elements in fresh vegetables using ultraviolet nanosecond laser-induced breakdown spectroscopy

    International Nuclear Information System (INIS)

    Juve, Vincent; Portelli, Richard; Boueri, Myriam; Baudelet, Matthieu; Yu Jin

    2008-01-01

    Laser-induced breakdown spectroscopy (LIBS) has been applied to analyze trace elements contained in fresh vegetables. A quadrupled Nd:YAG laser is used in the experiments for ablation. Analyzed samples come from local markets and represent frequently consumed vegetables. For a typical root vegetable, such as potato, spectral analysis of the plasma emission reveals more than 400 lines emitted by 27 elements and 2 molecules, C 2 and CN. Among these species, one can find trace as well as ultra-trace elements. A space-resolved analysis of several trace elements with strong emissions is then applied to typical root, stem and fruit vegetables. The results from this study demonstrate the potential of an interesting tool for botanical and agricultural studies as well for food quality/safety and environment pollution assessment and control

  10. Spectral gamuts and spectral gamut mapping

    Science.gov (United States)

    Rosen, Mitchell R.; Derhak, Maxim W.

    2006-01-01

    All imaging devices have two gamuts: the stimulus gamut and the response gamut. The response gamut of a print engine is typically described in CIE colorimetry units, a system derived to quantify human color response. More fundamental than colorimetric gamuts are spectral gamuts, based on radiance, reflectance or transmittance units. Spectral gamuts depend on the physics of light or on how materials interact with light and do not involve the human's photoreceptor integration or brain processing. Methods for visualizing a spectral gamut raise challenges as do considerations of how to utilize such a data-set for producing superior color reproductions. Recent work has described a transformation of spectra reduced to 6-dimensions called LabPQR. LabPQR was designed as a hybrid space with three explicit colorimetric axes and three additional spectral reconstruction axes. In this paper spectral gamuts are discussed making use of LabPQR. Also, spectral gamut mapping is considered in light of the colorimetric-spectral duality of the LabPQR space.

  11. Intensity of competition in the market of greenhouse vegetables

    Directory of Open Access Journals (Sweden)

    Oleg Ivanovich Botkin

    2012-03-01

    Full Text Available This paper reviews the competitive environment of the market greenhouse vegetables. Revealed specific features of the industry, determining the level of intensity of competition in the market greenhouse vegetables. Classified factors internal and external environment, identify indicators that affect the state of the market. The factors that determine the intensity of competition in the market greenhouse vegetables.The main competitors on the Russian market of greenhouse production.Identified indicators of the intensity level of competition, in particular: the level of monopolization of the market greenhouse vegetables, the level of concentration of production in the industry, the generalized index of the intensity of the competitive environment.Shows a comparative analysis of competitors’ market greenhouse vegetables in Udmurtia.Revealed competitive advantages which can help local producers to reduce the pressure of competition and intra-industry to occupy a leading position in the Russian market of greenhouse vegetable production.The dynamics of economic performance of Russian producers. Ways of improving the competitiveness of enterprises for the production of greenhouse vegetables

  12. Simple luminosity normalization of greenness, yellowness and redness/greenness for comparison of leaf spectral profiles in multi-temporally acquired remote sensing images.

    Science.gov (United States)

    Doi, Ryoichi

    2012-09-01

    Observation of leaf colour (spectral profiles) through remote sensing is an effective method of identifying the spatial distribution patterns of abnormalities in leaf colour, which enables appropriate plant management measures to be taken. However, because the brightness of remote sensing images varies with acquisition time, in the observation of leaf spectral profiles in multi-temporally acquired remote sensing images, changes in brightness must be taken into account. This study identified a simple luminosity normalization technique that enables leaf colours to be compared in remote sensing images over time. The intensity values of green and yellow (green+red) exhibited strong linear relationships with luminosity (R2 greater than 0.926) when various invariant rooftops in Bangkok or Tokyo were spectralprofiled using remote sensing images acquired at different time points. The values of the coefficient and constant or the coefficient of the formulae describing the intensity of green or yellow were comparable among the single Bangkok site and the two Tokyo sites, indicating the technique's general applicability. For single rooftops, the values of the coefficient of variation for green, yellow, and red/green were 16% or less (n=6-11), indicating an accuracy not less than those of well-established remote sensing measures such as the normalized difference vegetation index. After obtaining the above linear relationships, raw intensity values were normalized and a temporal comparison of the spectral profiles of the canopies of evergreen and deciduous tree species in Tokyo was made to highlight the changes in the canopies' spectral profiles. Future aspects of this technique are discussed herein.

  13. Burned Area Detection and Burn Severity Assessment of a Heathland Fire in Belgium Using Airborne Imaging Spectroscopy (APEX

    Directory of Open Access Journals (Sweden)

    Lennert Schepers

    2014-02-01

    Full Text Available Uncontrolled, large fires are a major threat to the biodiversity of protected heath landscapes. The severity of the fire is an important factor influencing vegetation recovery. We used airborne imaging spectroscopy data from the Airborne Prism Experiment (APEX sensor to: (1 investigate which spectral regions and spectral indices perform best in discriminating burned from unburned areas; and (2 assess the burn severity of a recent fire in the Kalmthoutse Heide, a heathland area in Belgium. A separability index was used to estimate the effectiveness of individual bands and spectral indices to discriminate between burned and unburned land. For the burn severity analysis, a modified version of the Geometrically structured Composite Burn Index (GeoCBI was developed for the field data collection. The field data were collected in four different vegetation types: Calluna vulgaris-dominated heath (dry heath, Erica tetralix-dominated heath (wet heath, Molinia caerulea (grass-encroached heath, and coniferous woodland. Discrimination between burned and unburned areas differed among vegetation types. For the pooled dataset, bands in the near infrared (NIR spectral region demonstrated the highest discriminatory power, followed by short wave infrared (SWIR bands. Visible wavelengths performed considerably poorer. The Normalized Burn Ratio (NBR outperformed the other spectral indices and the individual spectral bands in discriminating between burned and unburned areas. For the burn severity assessment, all spectral bands and indices showed low correlations with the field data GeoCBI, when data of all pre-fire vegetation types were pooled (R2 maximum 0.41. Analysis per vegetation type, however, revealed considerably higher correlations (R2 up to 0.78. The Mid Infrared Burn Index (MIRBI had the highest correlations for Molinia and Erica (R2 = 0.78 and 0.42, respectively. In Calluna stands, the Char Soil Index (CSI achieved the highest correlations, with R2 = 0

  14. Assessment of plant species diversity based on hyperspectral indices at a fine scale.

    Science.gov (United States)

    Peng, Yu; Fan, Min; Song, Jingyi; Cui, Tiantian; Li, Rui

    2018-03-19

    Fast and nondestructive approaches of measuring plant species diversity have been a subject of excessive scientific curiosity and disquiet to environmentalists and field ecologists worldwide. In this study, we measured the hyperspectral reflectances and plant species diversity indices at a fine scale (0.8 meter) in central Hunshandak Sandland of Inner Mongolia, China. The first-order derivative value (FD) at each waveband and 37 hyperspectral indices were used to assess plant species diversity. Results demonstrated that the stepwise linear regression of FD can accurately estimate the Simpson (R 2  = 0.83), Pielou (R 2  = 0.87) and Shannon-Wiener index (R 2  = 0.88). Stepwise linear regression of FD (R 2  = 0.81, R 2  = 0.82) and spectral vegetation indices (R 2  = 0.51, R 2  = 0.58) significantly predicted the Margalef and Gleason index. It was proposed that the Simpson, Pielou and Shannon-Wiener indices, which are widely used as plant species diversity indicators, can be precisely estimated through hyperspectral indices at a fine scale. This research promotes the development of methods for assessment of plant diversity using hyperspectral data.

  15. Application of a regularized model inversion system (REGFLEC) to multi-temporal RapidEye imagery for retrieving vegetation characteristics

    KAUST Repository

    Houborg, Rasmus

    2015-10-14

    Accurate retrieval of canopy biophysical and leaf biochemical constituents from space observations is critical to diagnosing the functioning and condition of vegetation canopies across spatio-temporal scales. Retrieved vegetation characteristics may serve as important inputs to precision farming applications and as constraints in spatially and temporally distributed model simulations of water and carbon exchange processes. However significant challenges remain in the translation of composite remote sensing signals into useful biochemical, physiological or structural quantities and treatment of confounding factors in spectrum-trait relations. Bands in the red-edge spectrum have particular potential for improving the robustness of retrieved vegetation properties. The development of observationally based vegetation retrieval capacities, effectively constrained by the enhanced information content afforded by bands in the red-edge, is a needed investment towards optimizing the benefit of current and future satellite sensor systems. In this study, a REGularized canopy reFLECtance model (REGFLEC) for joint leaf chlorophyll (Chll) and leaf area index (LAI) retrieval is extended to sensor systems with a band in the red-edge region for the first time. Application to time-series of 5 m resolution multi-spectral RapidEye data is demonstrated over an irrigated agricultural region in central Saudi Arabia, showcasing the value of satellite-derived crop information at this fine scale for precision management. Validation against in-situ measurements in fields of alfalfa, Rhodes grass, carrot and maize indicate improved accuracy of retrieved vegetation properties when exploiting red-edge information in the model inversion process. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  16. NDVI indicated characteristics of vegetation cover change in China's metropolises over the last three decades.

    Science.gov (United States)

    Sun, Jinyu; Wang, Xuhui; Chen, Anping; Ma, Yuecun; Cui, Mengdi; Piao, Shilong

    2011-08-01

    How urban vegetation was influenced by three decades of intensive urbanization in China is of great interest but rarely studied. In this paper, we used satellite derived Normalized Difference Vegetation Index (NDVI) and socioeconomic data to evaluate effects of urbanization on vegetation cover in China's 117 metropolises over the last three decades. Our results suggest that current urbanization has caused deterioration of urban vegetation across most cities in China, particularly in East China. At the national scale, average urban area NDVI (NDVI(u)) significantly decreased during the last three decades (P NDVI(u) did not show statistically significant trend before 1990 but decrease remarkably after 1990 (P NDVI(u) turning point. The year when NDVI(u) started to decline significantly for Central China and East China was 1987 and 1990, respectively, while NDVI(u) in West China remained relatively constant until 1998. NDVI(u) changes in the Yangtze River Delta and the Pearl River Delta, two regions which has been undergoing the most rapid urbanization in China, also show different characteristics. The Pearl River Delta experienced a rapid decline in NDVI(u) from the early 1980s to the mid-1990s; while in the Yangtze River Delta, NDVI(u) did not decline significantly until the early 1990s. Such different patterns of NDVI(u) changes are closely linked with policy-oriented difference in urbanization dynamics of these regions, which highlights the importance of implementing a sustainable urban development policy.

  17. Extraction and prediction of indices for monsoon intraseasonal oscillations: an approach based on nonlinear Laplacian spectral analysis

    Science.gov (United States)

    Sabeerali, C. T.; Ajayamohan, R. S.; Giannakis, Dimitrios; Majda, Andrew J.

    2017-11-01

    An improved index for real-time monitoring and forecast verification of monsoon intraseasonal oscillations (MISOs) is introduced using the recently developed nonlinear Laplacian spectral analysis (NLSA) technique. Using NLSA, a hierarchy of Laplace-Beltrami (LB) eigenfunctions are extracted from unfiltered daily rainfall data from the Global Precipitation Climatology Project over the south Asian monsoon region. Two modes representing the full life cycle of the northeastward-propagating boreal summer MISO are identified from the hierarchy of LB eigenfunctions. These modes have a number of advantages over MISO modes extracted via extended empirical orthogonal function analysis including higher memory and predictability, stronger amplitude and higher fractional explained variance over the western Pacific, Western Ghats, and adjoining Arabian Sea regions, and more realistic representation of the regional heat sources over the Indian and Pacific Oceans. Real-time prediction of NLSA-derived MISO indices is demonstrated via extended-range hindcasts based on NCEP Coupled Forecast System version 2 operational output. It is shown that in these hindcasts the NLSA MISO indices remain predictable out to ˜3 weeks.

  18. Vegetation indices as indicators of damage by the sunn pest ...

    African Journals Online (AJOL)

    SERVER

    2008-01-18

    Jan 18, 2008 ... nylon cloth cage experiments were conducted to determine the feasibility of using remote sensing techniques to ... conventionally used method for the sunn pest manage- ... Study area and sunn pest experiment design ... graphy is nearly flat. .... for determination of indices showed an increasing pattern.

  19. Vegetation responses to sagebrush-reduction treatments measured by satellites

    Science.gov (United States)

    Johnston, Aaron; Beever, Erik; Merkle, Jerod A.; Chong, Geneva W.

    2018-01-01

    Time series of vegetative indices derived from satellite imagery constitute tools to measure ecological effects of natural and management-induced disturbances to ecosystems. Over the past century, sagebrush-reduction treatments have been applied widely throughout western North America to increase herbaceous vegetation for livestock and wildlife. We used indices from satellite imagery to 1) quantify effects of prescribed-fire, herbicide, and mechanical treatments on vegetative cover, productivity, and phenology, and 2) describe how vegetation changed over time following these treatments. We hypothesized that treatments would increase herbaceous cover and accordingly shift phenologies towards those typical of grass-dominated systems. We expected prescribed burns would lead to the greatest and most-prolonged effects on vegetative cover and phenology, followed by herbicide and mechanical treatments. Treatments appeared to increase herbaceous cover and productivity, which coincided with signs of earlier senescence − signals expected of grass-dominated systems, relative to sagebrush-dominated systems. Spatial heterogeneity for most phenometrics was lower in treated areas relative to controls, which suggested treatment-induced homogenization of vegetative communities. Phenometrics that explain spring migrations of ungulates mostly were unaffected by sagebrush treatments. Fire had the strongest effect on vegetative cover, and yielded the least evidence for sagebrush recovery. Overall, treatment effects were small relative to those reported from field-based studies for reasons most likely related to sagebrush recovery, treatment specification, and untreated patches within mosaicked treatment applications. Treatment effects were also small relative to inter-annual variation in phenology and productivity that was explained by temperature, snowpack, and growing-season precipitation. Our results indicated that cumulative NDVI, late-season phenometrics, and spatial

  20. SPOT-Based Sub-Field Level Monitoring of Vegetation Cover Dynamics: A Case of Irrigated Croplands

    Directory of Open Access Journals (Sweden)

    Olena Dubovyk

    2015-05-01

    Full Text Available Acquiring multi-temporal spatial information on vegetation condition at scales appropriate for site-specific agricultural management is often complicated by the need for meticulous field measurements. Understanding spatial/temporal crop cover heterogeneity within irrigated croplands may support sustainable land use, specifically in areas affected by land degradation due to secondary soil salinization. This study demonstrates the use of multi-temporal, high spatial resolution (10 m SPOT-4/5 image data in an integrated change vector analysis and spectral mixture analysis (CVA-SMA procedure. This procedure was implemented with the principal objective of mapping sub-field vegetation cover dynamics in irrigated lowland areas within the lowerlands of the Amu Darya River. CVA intensity and direction were calculated separately for the periods of 1998–2006 and 2006–2010. Cumulative change intensity and the overall directional trend were also derived for the entire observation period of 1998–2010. Results show that most of the vector changes were observed between 1998 and 2006; persistent conditions were seen within the study region during the 2006–2010 period. A decreasing vegetation cover trend was identified within 38% of arable land. Areas of decreasing vegetation cover were located principally in the irrigation system periphery where deficient water supply and low soil quality lead to substandard crop development. During the 2006–2010 timeframe, degraded crop cover conditions persisted in 37% of arable land. Vegetation cover increased in 25% of the arable land where irrigation water supply was adequate. This high sub-field crop performance spatial heterogeneity clearly indicates that current land management practices are inefficient. Such information can provide the basis for implementing and adapting irrigation applications and salt leaching techniques to site-specific conditions and thereby make a significant contribution to sustainable

  1. Water and vegetation indices by using MODIS products for eucalyptus, pasture, and natural ecosystems in the eastern São Paulo state, Southeast Brazil

    Science.gov (United States)

    de C. Teixeira, Antônio H.; Leivas, Janice F.; Ronquim, Carlos C.; Garçon, Edlene A. M.; Bayma-Silva, Gustavo

    2017-10-01

    Eucalyptus (Ec) and pasture (Pt) are expanding while natural vegetation (Nv) are losing space in the Paraíba Valley, eastern side of the São Paulo state, Southeast Brazil. For quantification of water and vegetation conditions, the MODIS product MOD13Q1 was used together with a net of weather stations and vegetation land masks during the year 2015. The SAFER algorithm was applied to retrieve the actual evapotranspiration (ET), which was combined with the Monteith's radiation use efficiency (RUE) model to estimate the biomass production (BIO). Three moisture indices were applied, the climatic water balance ratio (WBr), the ratio of precipitation (P) to ET, the water balance deficit (WBd), the difference between P and ET, and the evapotranspiration ratio (ETr), the ratio of ET to the reference evapotranspiration (ET0). On the one hand, the highest ET rates for the Ec ecosystem should be a negative aspect under water scarcity conditions; however, it presented the best water productivity. Although the Ec ecosystem presenting the lowest WBr and WBd values, it had the highest ETr, averaging 0.92, when comparing to those for Nv (0.88) and Pt (0.79). These results indicated that eucalyptus plants have greater ability of conserving soil moisture in their root zones, increasing WP, when comparing with Pt and Nv ecosystems. These water relationships are relevant issues under the land-use change conditions in the Paraiba Valley, confirming the suitability of using the MODIS products together with weather stations to study the ecosystem dynamics.

  2. Implications of vegetation hydraulic capacitance as an indicator of water stress and drought recovery

    Science.gov (United States)

    Matheny, A. M.; Bohrer, G.

    2017-12-01

    Above-ground water storage in vegetation plays an integral role in the avoidance of hydraulic impairment to transpiration. New high temporal resolution measurements of dynamic changes in tree hydraulic capacitance are facilitating insights into vegetation water use strategies. Diurnal withdrawal from water storage in leaves, branches, stems, and roots significantly impacts sap flow, stomatal conductance, and transpiration. The ability to store and use water varies based on soil- and root-water availability, tree size, wood vessel anatomy and density, and stomatal response strategy (i.e. isohydricity). We present results from a three-year long study of stem capacitance dynamics in five species in a mixed deciduous forest in Michigan. The site receives 800mm of rainfall annually, but water potential in the well-drained sandy soil nears the permanent wilting point several times annually. We demonstrate radical differences in stored water use between drought tolerant and intolerant species. Red maple, a drought intolerant, isohydric species, showed a strong dependence on stem capacitance for transpiration during both wet and dry periods. Red oak, a more drought hearty, deep rooted, anisohydric species, was much less reliant on withdrawal from water storage during all conditions. During well-watered conditions, withdrawal from storage by red maple was 10 kg day-1, yet storage withdrawal from similarly sized red oaks was 1 kg day-1. Red oaks only drew strongly upon stored water during the driest extremes. Metrics of hydration status derived from capacitance provide a means to explore drought response and recovery. Declines in consecutive days' maximum capacitance indicate an inability to restore lost water and can be used to mark the onset of water stress. Drought recovery can be quantified as the time required for stem water content to return to pre-drought volumes. Capacitance withdrawal and depletion exhibit a clear threshold response to declining soil water

  3. Estimation of spectral kurtosis

    Science.gov (United States)

    Sutawanir

    2017-03-01

    Rolling bearings are the most important elements in rotating machinery. Bearing frequently fall out of service for various reasons: heavy loads, unsuitable lubrications, ineffective sealing. Bearing faults may cause a decrease in performance. Analysis of bearing vibration signals has attracted attention in the field of monitoring and fault diagnosis. Bearing vibration signals give rich information for early detection of bearing failures. Spectral kurtosis, SK, is a parameter in frequency domain indicating how the impulsiveness of a signal varies with frequency. Faults in rolling bearings give rise to a series of short impulse responses as the rolling elements strike faults, SK potentially useful for determining frequency bands dominated by bearing fault signals. SK can provide a measure of the distance of the analyzed bearings from a healthy one. SK provides additional information given by the power spectral density (psd). This paper aims to explore the estimation of spectral kurtosis using short time Fourier transform known as spectrogram. The estimation of SK is similar to the estimation of psd. The estimation falls in model-free estimation and plug-in estimator. Some numerical studies using simulations are discussed to support the methodology. Spectral kurtosis of some stationary signals are analytically obtained and used in simulation study. Kurtosis of time domain has been a popular tool for detecting non-normality. Spectral kurtosis is an extension of kurtosis in frequency domain. The relationship between time domain and frequency domain analysis is establish through power spectrum-autocovariance Fourier transform. Fourier transform is the main tool for estimation in frequency domain. The power spectral density is estimated through periodogram. In this paper, the short time Fourier transform of the spectral kurtosis is reviewed, a bearing fault (inner ring and outer ring) is simulated. The bearing response, power spectrum, and spectral kurtosis are plotted to

  4. Drought impacts on vegetation dynamics in the Mediterranean based on remote sensing and multi-scale drought indices

    Science.gov (United States)

    Trigo, Ricardo; Gouveia, Celia M.; Beguería, Santiago; Vicente-Serrano, Sergio

    2015-04-01

    A number of recent studies have identified a significant increase in the frequency of drought events in the Mediterranean basin (e.g. Trigo et al., 2013, Vicente-Serrano et al., 2014). In the Mediterranean region, large drought episodes are responsible for the most negative impacts on the vegetation including significant losses of crop yield, increasing risk of forest fires (e.g. Gouveia et al., 2012) and even forest decline. The aim of the present work is to analyze in detail the impacts of drought episodes on vegetation in the Mediterranean basin behavior using NDVI data from (from GIMMS) for entire Mediterranean basin (1982-2006) and the multi-scale drought index (the Standardised Precipitation-Evapotranspiration Index (SPEI). Correlation maps between fields of monthly NDVI and SPEI for at different time scales (1-24 months) were computed in order to identify the regions and seasons most affected by droughts. Affected vegetation presents high spatial and seasonal variability, with a maximum in summer and a minimum in winter. During February 50% of the affected pixels corresponded to a time scale of 6 months, while in November the most frequent time scale corresponded to 3 months, representing more than 40% of the affected region. Around 20% of grid points corresponded to the longer time scales (18 and 24 months), persisting fairly constant along the year. In all seasons the wetter clusters present higher NDVI values which indicates that aridity holds a key role to explain the spatial differences in the NDVI values along the year. Despite the localization of these clusters in areas with higher values of monthly water balance, the strongest control of drought on vegetation activity are observed for the drier classes located over regions with smaller absolute values of water balance. Gouveia C.M., Bastos A., Trigo R.M., DaCamara C.C. (2012) "Drought impacts on vegetation in the pre and post-fire events over Iberian Peninsula". Natural Hazards and Earth System

  5. Contribution of chlorophyll fluorescence to the apparent vegetation reflectance

    International Nuclear Information System (INIS)

    Campbell, P.K. Entcheva; Middleton, E.M.; Corp, L.A.; Kim, M.S.

    2008-01-01

    Current strategies for monitoring the physiologic status of terrestrial vegetation rely on remote sensing reflectance data, which provide estimates of vigor based primarily on chlorophyll content. Chlorophyll fluorescence (ChlF) measurements offer a non-destructive alternative and a more direct approach for diagnosis of vegetation stress before a significant reduction in chlorophyll content has occurred. Thus, technology based on ChlF may allow more accurate carbon sequestration estimates and earlier stress detection than is possible when using reflectance data alone. However, the observed apparent vegetation reflectance (Ra) in reality includes contributions from both the reflected and fluoresced radiation. The aim of this study is to determine the relative contributions of reflectance and ChlF fractions to Ra in the red to near-infrared region (650-800 nm) of the spectrum. The practical objectives of the study are to: 1) evaluate the relationship between ChlF and reflectance at the foliar level for corn, soybean and maple; and 2) for corn, determine if the relationship established for healthy vegetation changes under nitrogen (N) deficiency. To obtain generally applicable results, experimental measurements were conducted on unrelated crop and tree species (corn, soybean and maple) under controlled conditions and a gradient of inorganic N fertilization levels. Optical reflectance spectra and actively induced ChlF emissions were collected on the same foliar samples, in conjunction with measurements of photosynthetic function, pigment levels, and carbon (C) and N content. The spectral trends were examined for similarities. On average, 10-20% of Ra at 685 nm was actually due to ChlF. The spectral trends in steady state and maximum fluorescence varied significantly, with steady state fluorescence (especially red, 685 nm) showing higher ability for species and treatment separation. The relative contribution of ChlF to Ra varied significantly among species, with maple

  6. VEGETATIVE SUPPORT OF CARDIAC ACTIVITY IN ATHLETES WITH DIFFERENT ANTHROPOMETRIC PROFILE

    Directory of Open Access Journals (Sweden)

    O. N. Kudrya

    2016-01-01

    Full Text Available The purpose of research – to study the features of the functioning of the cardiovascular system and regulatory mechanisms of the young athletes of different heights.Materials and methods. The study included athletes aged 15-16 (32 girls and 36 boys engaged in competitive sports. To study the autonomic regulation of the cardiovascular system using mathematical methods and spectral analysis of heart rate variability. To characterize the vegetative support the circulatory apparatus, all subjects performed an active orthostatic test.Results. The features of vegetative maintenance of heart activity in tall athletes: stress regulatory mechanisms observed resting in tall men and decrease the functionality of the sympathetic division of the autonomic nervous system during active orthostatic test in athletes of different sex. Athletes tall urgent adaptation of the cardiovascular system to changing external conditions associated with activation of suprasegmental divisions of the autonomic nervous system and the excessive activation of the sympathetic division, which is an inefficient way of adaptation.Conclusion. Thus, high growth is evident not only in the increase of total size of the body of athletes, but also in the peculiarities of morphofunctional state involved, indicating the need of individual rationing of loads for tall players. The revealed morphofunctional characteristics of the organism tall athletes allow us to recommend an increase in the proportion of aerobic exercise to enhance the adaptive capacities of the organism. 

  7. Integrating UAV and orbital remote sensing for spatiotemporal assessment of coastal vegetation health following hurricane events

    Science.gov (United States)

    Bernardes, S.; Madden, M.; Jordan, T.; Knight, A.; Aragon, A.

    2017-12-01

    Hurricane impacts often include the total or partial removal of vegetation due to strong winds (e.g., uprooted trees and broken trunks and limbs). Those impacts can usually be quickly assessed following hurricanes, by using established field and remote sensing methods. Conversely, impacts on vegetation health may present challenges for identification and assessment, as they are disconnected in time from the hurricane event and may be less evident. For instance, hurricanes may promote drastic increases in salinity of water available to roots and may increase exposure of aerial parts to salt spray. Derived stress conditions can negatively impact biological processes and may lead to plant decline and death. Large areas along the coast of the United States have been affected by hurricanes and show such damage (vegetation browning). Those areas may continue to be impacted, as climate projections indicate that hurricanes may become more frequent and intense, resulting from the warming of ocean waters. This work uses remote sensing tools and techniques to record and assess impacts resulting from recent hurricanes at Sapelo Island, a barrier island off the coast of the State of Georgia, United States. Analyses included change detection at the island using time series of co-registered Sentinel 2 and Landsat images. A field campaign was conducted in September 2017, which included flying three UAVs over the island and collecting high-overlap 20-megapixel RGB images at two spatial resolutions (1 and 2 inches/pixel). A five-band MicaSense RedEdge camera, a downwelling radiation sensor and calibration panel were used to collect calibrated multispectral images of multiple vegetation types, including healthy vegetation and vegetation affected by browning. Drone images covering over 600 acres were then analyzed for vegetation status and damage, with emphasis to vegetation removal and browning resulting from salinity alterations and salt spray. Results from images acquired by drones

  8. The assessment of anthropogenic impact on the environment in East Fennoscandia based on the Normalized Difference Vegetation Index data

    Science.gov (United States)

    Miulgauzen, Daria; Pankratova, Lubov

    2017-04-01

    Being a part of Eurasian "cold sector", ecosystems of East Fennoscandia may fit in the category of the most vulnerable to any external impact, including anthropogenic one. The productivity of plant communities can serve as an indicator representing the state of ecosystems, especially in disturbed areas. The present research is aimed at the environmental impact assessment caused by the Pechenganikel Mining and Metallurgical Plant based on the plant communities' productivity data on the example of ecosystems of East Fennoscandia. Vegetation productivity was assessed on the basis of the Normalized Difference Vegetation Index (NDVI) which is often used for screenings to quantify plant canopy. The essence of the method is that of the difference between the spectral reflectance of vegetation in red and near-infrared regions. The index was calculated on the satellite images of Landsat 8 in IDRISI Kilimanjaro (Clark Labs) according to the equation: N DV I = N-IR- RED-; N IR +RED NIR - spectral reflectance measurements in near-infrared region, RED - spectral reflectance measurements in red region. To compare the index calculations with the information on the state of plant communities, the field studies were carried out in the area of 380 km2 in the vicinity of the Pechenganikel Mining and Metallurgical Plant (Kola Peninsula, Nikel urban-type settlement). As a result, there was created a map in MapInfo Professional 12.5 (Pitney Bowes Software) that represents the vegetation damage at a scale of 1:100,000. The field research has revealed the morphogenetic discrepancy between the soil-plant cover of the area in question and the one of "zonal" ecosystems. Plant communities have been widely modified or destroyed because of air pollution and there are numerous disturbances in the soil profile structure. In terms of vegetation productivity, the analysis of the NDVI figures has shown that the closer the pollution source (Pechenganikel Plant) is, the more significant the

  9. Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

    International Nuclear Information System (INIS)

    Hashim, M; Pour, A B; Onn, C H

    2014-01-01

    Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate

  10. Report of second LASFLEUR field campaign for remote sensing of vegetation health: ENEA contribution

    Energy Technology Data Exchange (ETDEWEB)

    Barbini, R; Colao, F; Fantoni, R; Palucci, A; Ribezzo, S [ENEA, Frascati (Italy). Dipt. Sviluppo Tecnologie di Punta

    1993-09-15

    The second European joint field campaign for the remote sensing of vegetation health was held in Oberpfaffenhofen (D) (30 Jun-9 Jul 1992) within the framework of the EUREKA/LASFLEUR Project. Italian groups, from ENEA (Italian Agency for Energy, New Technologies and the Environment), CNR (Italian National Research Council) and Viterbo University participated in this campaign together with German, French and Swedish groups from different institutes. On the occasion of this campaign, the lidar (light detection and ranging) fluorosensor system built at ENEA Frascati for the remote sensing of water and territory was improved, on the basis of the former field experience on plant fluorescence remote detection gained during the first LASFLEUR campaign held in Viterbo, and carried out on-site by means of a movable container. The new version of the set-up is presented here, together with the measurements performed on the available targets (spruce, maple, elm and cornel trees, and mais plants). Data analysis is discussed in detail, attempting to correlate the present spectral domain measurements with the plant photosynthetic activity under different weather and (nutrition or water) stress conditions. Several correlations were found between different pigment concentrations in various vegetables and spectrally resolved remote sensed data on the same species. It was demonstrated that the measurements, when performed from an airborne platform, would allow for a remote vegetation recognition across large areas (monitoring cultivations or forests). Part of the campaign was dedicated to the inter-calibration of different lidar systems operating in the spectrally resolved mode: this point is discussed here as well. Some conclusions drawn at the end of the LASFLEUR project Phase 1 are presented at the end of this report, as discussed during the last Project Workshop held in Florence from October 22nd to 26th, 1992.

  11. Vegetation cover analysis using a low budget hyperspectral proximal sensing system

    Directory of Open Access Journals (Sweden)

    C. Daquino

    2006-06-01

    Full Text Available This report describes the implementation of a hyperspectral proximal sensing low-budget acquisition system and its application to the detection of terrestrian vegetation cover anomalies in sites of high environmental quality. Anomalies can be due to stress for lack of water and/or pollution phenomena and weed presence in agricultural fields. The hyperspectral cube (90-bands ranging from 450 to 900 nm was acquired from the hill near Segni (RM, approximately 500 m far from the target, by means of electronically tunable filters and 8 bit CCD cameras. Spectral libraries were built using both endmember identification method and extraction of centroids of the clusters obtained from a k-means analysis of the image itself. Two classification methods were applied on the hyperspectral cube: Spectral Angle Mapper (hard and Mixed Tuned Matching Filters (MTMF. Results show the good capability of the system in detecting areas with an arboreal, shrub or leafage cover, distinguishing between zones with different spectral response. Better results were obtained using spectral library originated by the k-means method. The detected anomalies not correlated to seasonal phenomena suggest a ground true analysis to identify their origin.

  12. Using endmembers in AVIRIS images to estimate changes in vegetative biomass

    Science.gov (United States)

    Smith, Milton O.; Adams, John B.; Ustin, Susan L.; Roberts, Dar A.

    1992-01-01

    Field techniques for estimating vegetative biomass are labor intensive, and rarely are used to monitor changes in biomass over time. Remote-sensing offers an attractive alternative to field measurements; however, because there is no simple correspondence between encoded radiance in multispectral images and biomass, it is not possible to measure vegetative biomass directly from AVIRIS images. Ways to estimate vegetative biomass by identifying community types and then applying biomass scalars derived from field measurements are investigated. Field measurements of community-scale vegetative biomass can be made, at least for local areas, but it is not always possible to identify vegetation communities unambiguously using remote measurements and conventional image-processing techniques. Furthermore, even when communities are well characterized in a single image, it typically is difficult to assess the extent and nature of changes in a time series of images, owing to uncertainties introduced by variations in illumination geometry, atmospheric attenuation, and instrumental responses. Our objective is to develop an improved method based on spectral mixture analysis to characterize and identify vegetative communities, that can be applied to multi-temporal AVIRIS and other types of images. In previous studies, multi-temporal data sets (AVIRIS and TM) of Owens Valley, CA were analyzed and vegetation communities were defined in terms of fractions of reference (laboratory and field) endmember spectra. An advantage of converting an image to fractions of reference endmembers is that, although fractions in a given pixel may vary from image to image in a time series, the endmembers themselves typically are constant, thus providing a consistent frame of reference.

  13. [Estimation and Visualization of Nitrogen Content in Citrus Canopy Based on Two Band Vegetation Index (TBVI)].

    Science.gov (United States)

    Wang, Qiao-nan; Ye, Xu-jun; Li, Jin-meng; Xiao, Yu-zhao; He, Yong

    2015-03-01

    Nitrogen is a necessary and important element for the growth and development of fruit orchards. Timely, accurate and nondestructive monitoring of nitrogen status in fruit orchards would help maintain the fruit quality and efficient production of the orchard, and mitigate the pollution of water resources caused by excessive nitrogen fertilization. This study investigated the capability of hyperspectral imagery for estimating and visualizing the nitrogen content in citrus canopy. Hyperspectral images were obtained for leaf samples in laboratory as well as for the whole canopy in the field with ImSpector V10E (Spectral Imaging Ltd., Oulu, Finland). The spectral datas for each leaf sample were represented by the average spectral data extracted from the selected region of interest (ROI) in the hyperspectral images with the aid of ENVI software. The nitrogen content in each leaf sample was measured by the Dumas combustion method with the rapid N cube (Elementar Analytical, Germany). Simple correlation analysis and the two band vegetation index (TBVI) were then used to develop the spectra data-based nitrogen content prediction models. Results obtained through the formula calculation indicated that the model with the two band vegetation index (TBVI) based on the wavelengths 811 and 856 nm achieved the optimal estimation of nitrogen content in citrus leaves (R2 = 0.607 1). Furthermore, the canopy image for the identified TBVI was calculated, and the nitrogen content of the canopy was visualized by incorporating the model into the TBVI image. The tender leaves, middle-aged leaves and elder leaves showed distinct nitrogen status from highto low-levels in the canopy image. The results suggested the potential of hyperspectral imagery for the nondestructive detection and diagnosis of nitrogen status in citrus canopy in real time. Different from previous studies focused on nitrogen content prediction at leaf level, this study succeeded in predicting and visualizing the nutrient

  14. Carbonaceous aerosol particles from common vegetation in the Grand Canyon

    International Nuclear Information System (INIS)

    Hallock, K.A.; Mazurek, M.A.; Cass, G.R.

    1992-05-01

    The problem of visibility reduction in the Grand Canyon due to fine organic aerosol particles in the atmosphere has become an area of increased environmental concern. Aerosol particles can be derived from many emission sources. In this report, we focus on identifying organic aerosols derived from common vegetation in the Grand Canyon. These aerosols are expected to be significant contributors to the total atmospheric organic aerosol content. Aerosol samples from living vegetation were collected by resuspension of surface wax and resin components liberated from the leaves of vegetation common to areas of the Grand Canyon. The samples were analyzed using high-resolution gas chromatography/mass spectrometry (GC/MS). Probable identification of compounds was made by comparison of sample spectra with National Institute of Standards and Technology (NIST) mass spectral references and positive identification of compounds was made when possible by comparison with authentic standards as well as NIST references. Using these references, we have been able to positively identify the presence of n-alkane and n-alkanoic acid homolog series in the surface waxes of the vegetation sampled. Several monoterpenes, sesquiterpenes, and diterpenes were identified also as possible biogenic aerosols which may contribute to the total organic aerosol abundance leading to visibility reduction in the Grand Canyon

  15. Spatial relationship between climatologies and changes in global vegetation activity

    NARCIS (Netherlands)

    Jong, de R.; Schaepman, M.E.; Furrer, R.; Bruin, de S.; Verburg, P.H.

    2013-01-01

    Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time

  16. Study of a Vegetation Index Based on HJ CCD Data's top-of-atmosphere reflectance and FPAR Inversion

    International Nuclear Information System (INIS)

    Dong, Taifeng; Wu, Bingfang; Meng, Jihua

    2014-01-01

    The Fraction of Photosynthetically Active Radiation (FPAR)absorbed by plant canopies is a key parameter for monitoring crop condition and estimating crop yield. In general, it is necessary to obtain Top of Canopy (TOC) reflectance from optical remote sensing data in digital number through atmospheric correction procedures before retrieving FPAR. However, there are a few of uncertainties that existe in the process of atmosphere correction and reduced the quality of TOC. This paper presents a vegetation index based on Top-of-Atmosphere (TOA) reflectance derived from HJ-1 CCD satellite for estimating direct crop FPAR. The vegetation index (HJVI) was designed based on the simulated results of a canopy-atmosphere radiative transfer model, including TOA reflectance and corresponded FPAR. The HJVI had taken the advantages of information in the green, the red and the near-infrared spectral domainswith with a aim of reducing the atmospheric effect and enhancing the sensitive to green vegetation. The HJVI was used to estimate soybean FPAR directly and validated using field measurements. The result indicated that the inversion algorithm produced a good relationship between the prediction and measurement (R 2 = 0.546, RMSE = 0.083) and the HJVI showed high potential for estimating FPAR based on the HJ-1 TOA reflectance directly

  17. Can tissue element concentration patterns at the individual-species level indicate the factors underlying vegetation gradients in wetlands?

    Czech Academy of Sciences Publication Activity Database

    Rozbrojová, Zuzana; Hájek, M.

    2010-01-01

    Roč. 21, č. 2 (2010), s. 355-363 ISSN 1100-9233 Institutional research plan: CEZ:AV0Z60050516 Keywords : plant nutrient concentration * vegetation gradient * wetland vegetation Subject RIV: EF - Botanics Impact factor: 2.457, year: 2010

  18. Machine Vision-Based Measurement Systems for Fruit and Vegetable Quality Control in Postharvest.

    Science.gov (United States)

    Blasco, José; Munera, Sandra; Aleixos, Nuria; Cubero, Sergio; Molto, Enrique

    Individual items of any agricultural commodity are different from each other in terms of colour, shape or size. Furthermore, as they are living thing, they change their quality attributes over time, thereby making the development of accurate automatic inspection machines a challenging task. Machine vision-based systems and new optical technologies make it feasible to create non-destructive control and monitoring tools for quality assessment to ensure adequate accomplishment of food standards. Such systems are much faster than any manual non-destructive examination of fruit and vegetable quality, thus allowing the whole production to be inspected with objective and repeatable criteria. Moreover, current technology makes it possible to inspect the fruit in spectral ranges beyond the sensibility of the human eye, for instance in the ultraviolet and near-infrared regions. Machine vision-based applications require the use of multiple technologies and knowledge, ranging from those related to image acquisition (illumination, cameras, etc.) to the development of algorithms for spectral image analysis. Machine vision-based systems for inspecting fruit and vegetables are targeted towards different purposes, from in-line sorting into commercial categories to the detection of contaminants or the distribution of specific chemical compounds on the product's surface. This chapter summarises the current state of the art in these techniques, starting with systems based on colour images for the inspection of conventional colour, shape or external defects and then goes on to consider recent developments in spectral image analysis for internal quality assessment or contaminant detection.

  19. Spectral L2/L1 norm: A new perspective for spectral kurtosis for characterizing non-stationary signals

    Science.gov (United States)

    Wang, Dong

    2018-05-01

    Thanks to the great efforts made by Antoni (2006), spectral kurtosis has been recognized as a milestone for characterizing non-stationary signals, especially bearing fault signals. The main idea of spectral kurtosis is to use the fourth standardized moment, namely kurtosis, as a function of spectral frequency so as to indicate how repetitive transients caused by a bearing defect vary with frequency. Moreover, spectral kurtosis is defined based on an analytic bearing fault signal constructed from either a complex filter or Hilbert transform. On the other hand, another attractive work was reported by Borghesani et al. (2014) to mathematically reveal the relationship between the kurtosis of an analytical bearing fault signal and the square of the squared envelope spectrum of the analytical bearing fault signal for explaining spectral correlation for quantification of bearing fault signals. More interestingly, it was discovered that the sum of peaks at cyclic frequencies in the square of the squared envelope spectrum corresponds to the raw 4th order moment. Inspired by the aforementioned works, in this paper, we mathematically show that: (1) spectral kurtosis can be decomposed into squared envelope and squared L2/L1 norm so that spectral kurtosis can be explained as spectral squared L2/L1 norm; (2) spectral L2/L1 norm is formally defined for characterizing bearing fault signals and its two geometrical explanations are made; (3) spectral L2/L1 norm is proportional to the square root of the sum of peaks at cyclic frequencies in the square of the squared envelope spectrum; (4) some extensions of spectral L2/L1 norm for characterizing bearing fault signals are pointed out.

  20. Vegetation index anomaly response to varying lengths of drought across vegetation and climatic gradients in Hawaii

    Science.gov (United States)

    Lucas, M.; Miura, T.; Trauernicht, C.; Frazier, A. G.

    2017-12-01

    A drought which results in prolonged and extended deficit in naturally available water supply and creates multiple stresses across ecosystems is classified as an ecological drought. Detecting and understanding the dynamics and response of such droughts in tropical systems, specifically across various vegetation and climatic gradients is fairly undetermined, yet increasingly important for better understandings of the ecological effects of drought. To understanding the link between what lengths and intensities of known meteorological drought triggers detectable ecological vegetation responses, a landscape scale regression analysis evaluating the response (slope) and relationship strength (R-squared) of several cumulative SPI (standard precipitation index) lengths(1, 3, 6, 12, 18, 24, 36, 48, and 60 month), to various satellite derived monthly vegetation indices anomalies (NDVI, EVI, EVI2, and LSWI) was performed across a matrix of dominant vegetation covers (grassland, shrubland, and forest) and climatic moisture zones (arid, dry, mesic, and wet). The nine different SPI lags across these climactic and vegetation gradients was suggest that stronger relationships and steeper slopes were found in dryer climates (across all vegetation covers) and finer vegetation types (across all moisture zones). Overall NDVI, EVI and EVI2 showed the best utility in these dryer climatic zones across all vegetation types. Within arid and dry areas "best" fits showed increasing lengths of cumulative SPI were with increasing vegetation coarseness respectively. Overall these findings suggest that rainfall driven drought may have a stronger impact on the ecological condition of vegetation in water limited systems with finer vegetation types ecologically responding more rapidly to meteorological drought events than coarser woody vegetation systems. These results suggest that previously and newly documented trends of decreasing rainfall and increasing drought in Hawaiian drylands may have

  1. Comparison between sensors with different spectral resolutions, relative to the sumbandila satellite, for assessing site quality differences, in eucalyptus grandis plantations

    CSIR Research Space (South Africa)

    Main, R

    2008-10-01

    Full Text Available detailed spectral information. Narrowband sensors, with their many contiguous bands, have proved useful in discriminating between vegetation states, e.g. water stress and nutrient deficiencies. However, hyperspectral remote sensing has a number...

  2. Combining Estimation of Green Vegetation Fraction in an Arid Region from Landsat 7 ETM+ Data

    Directory of Open Access Journals (Sweden)

    Kun Jia

    2017-11-01

    Full Text Available Fractional vegetation cover (FVC, or green vegetation fraction, is an important parameter for characterizing conditions of the land surface vegetation, and also a key variable of models for simulating cycles of water, carbon and energy on the land surface. There are several types of FVC estimation models using remote sensing data, and evaluating their performance over a specific region is of great significance. Therefore, this study firstly evaluated three types of FVC estimation models using Landsat 7 ETM+ data in an agriculture region of Heihe River Basin, China, and then proposed a combination strategy from different individual models to improve the FVC estimation accuracy, which employed the multiple linear regression (MLR and Bayesian model average (BMA methods. The validation results indicated that the spectral mixture analysis model with three endmembers (SMA3 achieved the best FVC estimation accuracy (determination coefficient (R2 = 0.902, root mean square error (RMSE = 0.076 among the seven individual models using Landsat 7 ETM+ data. In addition, the MLR and BMA combination methods could both improve FVC estimation accuracy (R2 = 0.913, RMSE = 0.063 and R2 = 0.904, RMSE = 0.069 for MLR and BMA, respectively. Therefore, it could be concluded that both MLR and BMA combination methods integrating FVC estimates from different models using Landsat 7 ETM+ data could effectively weaken the estimation errors of individual models and improve the final FVC estimation accuracy.

  3. Comparison of Vegetation Indices from Rpas and SENTINEL-2 Imagery for Detecting Permanent Pastures

    Science.gov (United States)

    Piragnolo, M.; Lusiani, G.; Pirotti, F.

    2018-04-01

    Permanent pastures (PP) are defined as grasslands, which are not subjected to any tillage, but only to natural growth. They are important for local economies in the production of fodder and pastures (Ali et al. 2016). Under these definitions, a pasture is permanent when it is not under any crop-rotation, and its production is related to only irrigation, fertilization and mowing. Subsidy payments to landowners require monitoring activities to determine which sites can be considered PP. These activities are mainly done with visual field surveys by experienced personnel or lately also using remote sensing techniques. The regional agency for SPS subsidies, the Agenzia Veneta per i Pagamenti in Agricoltura (AVEPA) takes care of monitoring and control on behalf of the Veneto Region using remote sensing techniques. The investigation integrate temporal series of Sentinel-2 imagery with RPAS. Indeed, the testing area is specific region were the agricultural land is intensively cultivated for production of hay harvesting four times every year between May and October. The study goal of this study is to monitor vegetation presence and amount using the Normalized Difference Vegetation Index (NDVI), the Soil-adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Built Index (NDBI). The overall objective is to define for each index a set of thresholds to define if a pasture can be classified as PP or not and recognize the mowing.

  4. COMPARISON OF VEGETATION INDICES FROM RPAS AND SENTINEL-2 IMAGERY FOR DETECTING PERMANENT PASTURES

    Directory of Open Access Journals (Sweden)

    M. Piragnolo

    2018-04-01

    Full Text Available Permanent pastures (PP are defined as grasslands, which are not subjected to any tillage, but only to natural growth. They are important for local economies in the production of fodder and pastures (Ali et al. 2016. Under these definitions, a pasture is permanent when it is not under any crop-rotation, and its production is related to only irrigation, fertilization and mowing. Subsidy payments to landowners require monitoring activities to determine which sites can be considered PP. These activities are mainly done with visual field surveys by experienced personnel or lately also using remote sensing techniques. The regional agency for SPS subsidies, the Agenzia Veneta per i Pagamenti in Agricoltura (AVEPA takes care of monitoring and control on behalf of the Veneto Region using remote sensing techniques. The investigation integrate temporal series of Sentinel-2 imagery with RPAS. Indeed, the testing area is specific region were the agricultural land is intensively cultivated for production of hay harvesting four times every year between May and October. The study goal of this study is to monitor vegetation presence and amount using the Normalized Difference Vegetation Index (NDVI, the Soil-adjusted Vegetation Index (SAVI, the Normalized Difference Water Index (NDWI, and the Normalized Difference Built Index (NDBI. The overall objective is to define for each index a set of thresholds to define if a pasture can be classified as PP or not and recognize the mowing.

  5. Radiative modeling and characterization of aerosol plumes hyper-spectral imagery

    International Nuclear Information System (INIS)

    Alakian, A.

    2008-03-01

    This thesis aims at characterizing aerosols from plumes (biomass burning, industrial discharges, etc.) with hyper-spectral imagery. We want to estimate the optical properties of emitted particles and also their micro-physical properties such as number, size distribution and composition. To reach our goal, we have built a forward semi-analytical model, named APOM (Aerosol Plume Optical Model), which allows to simulate the radiative effects of aerosol plumes in the spectral range [0,4-2,5 μm] for nadir viewing sensors. Mathematical formulation and model coefficients are obtained from simulations performed with the radiative transfer code COMANCHE. APOM is assessed on simulated data and proves to be accurate with modeling errors between 1% and 3%. Three retrieval methods using APOM have been developed: L-APOM, M-APOM and A-APOM. These methods take advantage of spectral and spatial dimensions in hyper-spectral images. L-APOM and M-APOM assume a priori knowledge on particles but can estimate their optical and micro-physical properties. Their performances on simulated data are quite promising. A-APOM method does not require any a priori knowledge on particles but only estimates their optical properties. However, it still needs improvements before being usable. On real images, inversion provides satisfactory results for plumes above water but meets some difficulties for plumes above vegetation, which underlines some possibilities of improvement for the retrieval algorithm. (author)

  6. Exploring vegetation in the fourth dimension.

    Science.gov (United States)

    Mitchell, Fraser J G

    2011-01-01

    Much ecological research focuses on changes in vegetation on spatial scales from stands to landscapes; however, capturing data on vegetation change over relevant timescales remains a challenge. Pollen analysis offers unrivalled access to data with global coverage over long timescales. Robust techniques have now been developed that enable pollen data to be converted into vegetation data in terms of individual taxa, plant communities or biomes, with the possibility of deriving from those data a range of plant attributes and ecological indicators. In this review, I discuss how coupling pollen with macrofossil, charcoal and genetic data opens up the extensive pollen databases to investigation of the drivers of vegetation change over time and also provides extensive data sets for testing hypotheses with wide ecological relevance. © 2010 Elsevier Ltd. All rights reserved.

  7. The technology of fish-vegetable feed production

    Directory of Open Access Journals (Sweden)

    Mukatova M. D.

    2016-09-01

    Full Text Available Perspective direction of the Volga-Caspian basin fisheries is increasing the productivity of aquaculture production which requires the availability of sufficient quantities of feed. The cutting waste of carp and crucian carp, crayfish processing (cephalothorax, wheat bran, soy isolate, freshwater plants – pondweed perfoliate, fish-vegetable ration, produced feeding staffs have been investigated. In researching samples of manufactured pelleted feeds the standard methods adopted in the animal feed industry have been used. The number of nitrogen-free extractives and energy value has been determined by calculation. The composition of fish-vegetable ration has been worked out. Some manufacturing inspection of fish-vegetable feed technology using proofing process has been carried out. The possibility of manufacturing on the basis of crushed fish waste of the company LLC "VES" and dry ingredients of fish-vegetable feed has been determined; the output of feed at water content of not more than 10 % is 43 % of feed mix based on the mass of directed waste equal to 84 %. The pilot batch of dry fish-vegetable feed has been investigated to establish quality indicators. It has been determined that fish-vegetable feed meets the requirements of GOST 10385–2014 "Combined feeding staffs for fishes. General specifications" as for main quality indicators and refers to economic grower for catfish and carp fish weighing more than 50 g. This reveals good palatability of the experimental batch of floating feed by carp fish species and African catfish. Thus, fish-vegetable feed manufacturing technology can be implemented in the production for processing secondary raw materials: waste from butchering fish by grinding, cooking, mixing with selected vegetable fillings which is waste of flour or grain processing industries and freshwater plants mowed annually during the reclamation works on the Volga delta.

  8. Hyperspectral Monitoring of Green Roof Vegetation Health State in Sub-Mediterranean Climate: Preliminary Results.

    Science.gov (United States)

    Piro, Patrizia; Porti, Michele; Veltri, Simone; Lupo, Emanuela; Moroni, Monica

    2017-03-23

    In urban and industrial environments, the constant increase of impermeable surfaces has produced drastic changes in the natural hydrological cycle. Decreasing green areas not only produce negative effects from a hydrological-hydraulic perspective, but also from an energy point of view, modifying the urban microclimate and generating, as shown in the literature, heat islands in our cities. In this context, green infrastructures may represent an environmental compensation action that can be used to re-equilibrate the hydrological and energy balance and reduce the impact of pollutant load on receiving water bodies. To ensure that a green infrastructure will work properly, vegetated areas have to be continuously monitored to verify their health state. This paper presents a ground spectroscopy monitoring survey of a green roof installed at the University of Calabria fulfilled via the acquisition and analysis of hyperspectral data. This study is part of a larger research project financed by European Structural funds aimed at understanding the influence of green roofs on rainwater management and energy consumption for air conditioning in the Mediterranean area. Reflectance values were acquired with a field-portable spectroradiometer that operates in the range of wavelengths 350-2500 nm. The survey was carried out during the time period November 2014-June 2015 and data were acquired weekly. Climatic, thermo-physical, hydrological and hydraulic quantities were acquired as well and related to spectral data. Broadband and narrowband spectral indices, related to chlorophyll content and to chlorophyll-carotenoid ratio, were computed. The two narrowband indices NDVI 705 and SIPI turned out to be the most representative indices to detect the plant health status.

  9. A linear model to predict with a multi-spectral radiometer the amount of nitrogen in winter wheat

    NARCIS (Netherlands)

    Reyniers, M.; Walvoort, D.J.J.; Baardemaaker, De J.

    2006-01-01

    The objective was to develop an optimal vegetation index (VIopt) to predict with a multi-spectral radiometer nitrogen in wheat crop (kg[N] ha-1). Optimality means that nitrogen in the crop can be measured accurately in the field during the growing season. It also means that the measurements are

  10. UNMANNED AERIAL VEHICLE (UAV) HYPERSPECTRAL REMOTE SENSING FOR DRYLAND VEGETATION MONITORING

    Energy Technology Data Exchange (ETDEWEB)

    Nancy F. Glenn; Jessica J. Mitchell; Matthew O. Anderson; Ryan C. Hruska

    2012-06-01

    UAV-based hyperspectral remote sensing capabilities developed by the Idaho National Lab and Idaho State University, Boise Center Aerospace Lab, were recently tested via demonstration flights that explored the influence of altitude on geometric error, image mosaicking, and dryland vegetation classification. The test flights successfully acquired usable flightline data capable of supporting classifiable composite images. Unsupervised classification results support vegetation management objectives that rely on mapping shrub cover and distribution patterns. Overall, supervised classifications performed poorly despite spectral separability in the image-derived endmember pixels. Future mapping efforts that leverage ground reference data, ultra-high spatial resolution photos and time series analysis should be able to effectively distinguish native grasses such as Sandberg bluegrass (Poa secunda), from invasives such as burr buttercup (Ranunculus testiculatus) and cheatgrass (Bromus tectorum).

  11. Evaluating water controls on vegetation growth in the semi-arid sahel using field and earth observation data

    DEFF Research Database (Denmark)

    Abdi, Abdulhakim M.; Boke-Olen, Niklas; Tenenbaum, David E.

    2017-01-01

    Water loss is a crucial factor for vegetation in the semi-arid Sahel region of Africa. Global satellite-driven estimates of plant CO2 uptake (gross primary productivity, GPP) have been found to not accurately account for Sahelian conditions, particularly the impact of canopy water stress. Here, we...... identify the main biophysical limitations that induce canopy water stress in Sahelian vegetation and evaluate the relationships between field data and Earth observation-derived spectral products for up-scaling GPP. We find that plant-available water and vapor pressure deficit together control the GPP...

  12. High Spatial Resolution Visual Band Imagery Outperforms Medium Resolution Spectral Imagery for Ecosystem Assessment in the Semi-Arid Brazilian Sertão

    Directory of Open Access Journals (Sweden)

    Ran Goldblatt

    2017-12-01

    Full Text Available Semi-arid ecosystems play a key role in global agricultural production, seasonal carbon cycle dynamics, and longer-run climate change. Because semi-arid landscapes are heterogeneous and often sparsely vegetated, repeated and large-scale ecosystem assessments of these regions have to date been impossible. Here, we assess the potential of high-spatial resolution visible band imagery for semi-arid ecosystem mapping. We use WorldView satellite imagery at 0.3–0.5 m resolution to develop a reference data set of nearly 10,000 labeled examples of three classes—trees, shrubs/grasses, and bare land—across 1000 km 2 of the semi-arid Sertão region of northeast Brazil. Using Google Earth Engine, we show that classification with low-spectral but high-spatial resolution input (WorldView outperforms classification with the full spectral information available from Landsat 30 m resolution imagery as input. Classification with high spatial resolution input improves detection of sparse vegetation and distinction between trees and seasonal shrubs and grasses, two features which are lost at coarser spatial (but higher spectral resolution input. Our total tree cover estimates for the study area disagree with recent estimates using other methods that may underestimate treecover because they confuse trees with seasonal vegetation (shrubs and grasses. This distinction is important for monitoring seasonal and long-run carbon cycle and ecosystem health. Our results suggest that newer remote sensing products that promise high frequency global coverage at high spatial but lower spectral resolution may offer new possibilities for direct monitoring of the world’s semi-arid ecosystems, and we provide methods that could be scaled to do so.

  13. Spatiotemporal monitoring of soil salinization in irrigated Tadla Plain (Morocco) using satellite spectral indices

    Science.gov (United States)

    El Harti, Abderrazak; Lhissou, Rachid; Chokmani, Karem; Ouzemou, Jamal-eddine; Hassouna, Mohamed; Bachaoui, El Mostafa; El Ghmari, Abderrahmene

    2016-08-01

    Soil salinization is major environmental issue in irrigated agricultural production. Conventional methods for salinization monitoring are time and money consuming and limited by the high spatiotemporal variability of this phenomenon. This work aims to propose a spatiotemporal monitoring method of soil salinization in the Tadla plain in central Morocco using spectral indices derived from Thematic Mapper (TM) and Operational Land Imager (OLI) data. Six Landsat TM/OLI satellite images acquired during 13 years period (2000-2013) coupled with in-situ electrical conductivity (EC) measurements were used to develop the proposed method. After radiometric and atmospheric correction of TM/OLI images, a new soil salinity index (OLI-SI) is proposed for soil EC estimation. Validation shows that this index allowed a satisfactory EC estimation in the Tadla irrigated perimeter with coefficient of determination R2 varying from 0.55 to 0.77 and a Root Mean Square Error (RMSE) ranging between 1.02 dS/m and 2.35 dS/m. The times-series of salinity maps produced over the Tadla plain using the proposed method show that salinity is decreasing in intensity and progressively increasing in spatial extent, over the 2000-2013 period. This trend resulted in a decrease in agricultural activities in the southwestern part of the perimeter, located in the hydraulic downstream.

  14. Information-efficient spectral imaging sensor

    Science.gov (United States)

    Sweatt, William C.; Gentry, Stephen M.; Boye, Clinton A.; Grotbeck, Carter L.; Stallard, Brian R.; Descour, Michael R.

    2003-01-01

    A programmable optical filter for use in multispectral and hyperspectral imaging. The filter splits the light collected by an optical telescope into two channels for each of the pixels in a row in a scanned image, one channel to handle the positive elements of a spectral basis filter and one for the negative elements of the spectral basis filter. Each channel for each pixel disperses its light into n spectral bins, with the light in each bin being attenuated in accordance with the value of the associated positive or negative element of the spectral basis vector. The spectral basis vector is constructed so that its positive elements emphasize the presence of a target and its negative elements emphasize the presence of the constituents of the background of the imaged scene. The attenuated light in the channels is re-imaged onto separate detectors for each pixel and then the signals from the detectors are combined to give an indication of the presence or not of the target in each pixel of the scanned scene. This system provides for a very efficient optical determination of the presence of the target, as opposed to the very data intensive data manipulations that are required in conventional hyperspectral imaging systems.

  15. Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

    Directory of Open Access Journals (Sweden)

    Frank Canters

    2008-06-01

    Full Text Available Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city’s inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing.

  16. Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

    Science.gov (United States)

    Barrett, K.; Kasischke, E. S.; McGuire, A. D.; Turetsky, M. R.; Kane, E. S.

    2010-01-01

    Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface

  17. DETERMINING SPECTRAL REFLECTANCE COEFFICIENTS FROM HYPERSPECTRAL IMAGES OBTAINED FROM LOW ALTITUDES

    Directory of Open Access Journals (Sweden)

    P. Walczykowski

    2016-06-01

    Full Text Available Remote Sensing plays very important role in many different study fields, like hydrology, crop management, environmental and ecosystem studies. For all mentioned areas of interest different remote sensing and image processing techniques, such as: image classification (object and pixel- based, object identification, change detection, etc. can be applied. Most of this techniques use spectral reflectance coefficients as the basis for the identification and distinction of different objects and materials, e.g. monitoring of vegetation stress, identification of water pollutants, yield identification, etc. Spectral characteristics are usually acquired using discrete methods such as spectrometric measurements in both laboratory and field conditions. Such measurements however can be very time consuming, which has led many international researchers to investigate the reliability and accuracy of using image-based methods. According to published and ongoing studies, in order to acquire these spectral characteristics from images, it is necessary to have hyperspectral data. The presented article describes a series of experiments conducted using the push-broom Headwall MicroHyperspec A-series VNIR. This hyperspectral scanner allows for registration of images with more than 300 spectral channels with a 1.9 nm spectral bandwidth in the 380- 1000 nm range. The aim of these experiments was to establish a methodology for acquiring spectral reflectance characteristics of different forms of land cover using such sensor. All research work was conducted in controlled conditions from low altitudes. Hyperspectral images obtained with this specific type of sensor requires a unique approach in terms of post-processing, especially radiometric correction. Large amounts of acquired imagery data allowed the authors to establish a new post- processing approach. The developed methodology allowed the authors to obtain spectral reflectance coefficients from a hyperspectral sensor

  18. Determining Spectral Reflectance Coefficients from Hyperspectral Images Obtained from Low Altitudes

    Science.gov (United States)

    Walczykowski, P.; Jenerowicz, A.; Orych, A.; Siok, K.

    2016-06-01

    Remote Sensing plays very important role in many different study fields, like hydrology, crop management, environmental and ecosystem studies. For all mentioned areas of interest different remote sensing and image processing techniques, such as: image classification (object and pixel- based), object identification, change detection, etc. can be applied. Most of this techniques use spectral reflectance coefficients as the basis for the identification and distinction of different objects and materials, e.g. monitoring of vegetation stress, identification of water pollutants, yield identification, etc. Spectral characteristics are usually acquired using discrete methods such as spectrometric measurements in both laboratory and field conditions. Such measurements however can be very time consuming, which has led many international researchers to investigate the reliability and accuracy of using image-based methods. According to published and ongoing studies, in order to acquire these spectral characteristics from images, it is necessary to have hyperspectral data. The presented article describes a series of experiments conducted using the push-broom Headwall MicroHyperspec A-series VNIR. This hyperspectral scanner allows for registration of images with more than 300 spectral channels with a 1.9 nm spectral bandwidth in the 380- 1000 nm range. The aim of these experiments was to establish a methodology for acquiring spectral reflectance characteristics of different forms of land cover using such sensor. All research work was conducted in controlled conditions from low altitudes. Hyperspectral images obtained with this specific type of sensor requires a unique approach in terms of post-processing, especially radiometric correction. Large amounts of acquired imagery data allowed the authors to establish a new post- processing approach. The developed methodology allowed the authors to obtain spectral reflectance coefficients from a hyperspectral sensor mounted on an

  19. Comparative Analysis of Red-Edge Hyperspectral Indices

    Science.gov (United States)

    Gupta, R.; Vijayan, D.; Prasad, T.

    The spectrally continuous observations of 3 nm bandwidth in 680 to 800 nm range over the growth cycle of wheat were subjected to first order differentiation to identify the point of inflection in red to near-IR transition zone. During 40 to 84 days after sowing (DAS), the point of inflection was observed in 723 to 735 nm region with peak response at 729 nm for 64 DAS . For differentiated curve pertaining to 25 DAS (initial vegetative) and 90 DAS (initial senescence) phenological stages, the point of inflection was in 690-693 and 744-747 nm spectral region, respectively. The ratios corresponding to 1dB (RI1dB = R 735 /R720), 2dB (RI 2dB = R738/R 720), 3dB (RI3dB = R741 /R 717) down signal levels and half signal level (RIhalf = R747/R 708 ) were computed. For nomenclature point of view, R41 refers to reflectance for 3 nm7 bandwidth centered at 741 nm. Correlations for these developed RIs were studied with reference to indices given by Vogelmann i.e., VOG a = R 740 /R720 , VOG b = [(R 734-R747)/(R715+R720)] and red edge spectral parameter (RESP) = R750 /R 710. VOG a and RESP conceptually resemble with developed RI 2dB and RIhalf , respectively. All RIs were found correlated with VOGa , VOG b and RESP with r2 in the range of 0.96 to 0.99; r2 was 0.998 for RI2dB and VOG a pair and 0.996 for RI half and RESP pair; the slope factor of regression relationship improved by about 50% from RI dB to2 RI3dB and by about 125% from RI3dB to RIhalf with r2 in 0.97-0.99 range. Thus, theoretical basis for VOG a and RESP in terms of dB based indices has been provided. The wavelengths used in VOGb are noticed in dB based indices ; to provide stability to small magnitude R720, the sum of R720 and R715 has been used in VOGb. Based on regression analysis of these indices with LAI in its growth and decline phases separately, the slope value for VOG b, RI 2dB, VOG a, RIhalf, RESP and area under 680 to 760 nm for first order derivative curve (area) were in 0.08-0.11, 0.24 - 0.34, 0

  20. Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

    Science.gov (United States)

    Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

    2014-03-01

    In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

  1. Comparison Between Spectral, Spatial and Polarimetric Classification of Urban and Periurban Landcover Using Temporal Sentinel - 1 Images

    Science.gov (United States)

    Roychowdhury, K.

    2016-06-01

    Landcover is the easiest detectable indicator of human interventions on land. Urban and peri-urban areas present a complex combination of landcover, which makes classification challenging. This paper assesses the different methods of classifying landcover using dual polarimetric Sentinel-1 data collected during monsoon (July) and winter (December) months of 2015. Four broad landcover classes such as built up areas, water bodies and wetlands, vegetation and open spaces of Kolkata and its surrounding regions were identified. Polarimetric analyses were conducted on Single Look Complex (SLC) data of the region while ground range detected (GRD) data were used for spectral and spatial classification. Unsupervised classification by means of K-Means clustering used backscatter values and was able to identify homogenous landcovers over the study area. The results produced an overall accuracy of less than 50% for both the seasons. Higher classification accuracy (around 70%) was achieved by adding texture variables as inputs along with the backscatter values. However, the accuracy of classification increased significantly with polarimetric analyses. The overall accuracy was around 80% in Wishart H-A-Alpha unsupervised classification. The method was useful in identifying urban areas due to their double-bounce scattering and vegetated areas, which have more random scattering. Normalized Difference Built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) obtained from Landsat 8 data over the study area were used to verify vegetation and urban classes. The study compares the accuracies of different methods of classifying landcover using medium resolution SAR data in a complex urban area and suggests that polarimetric analyses present the most accurate results for urban and suburban areas.

  2. Colours of fruit and vegetables and 10-year incidence of CHD

    NARCIS (Netherlands)

    Oude Griep, L.M.; Verschuren, W.M.M.; Kromhout, D.; Ocke, M.C.; Geleijnse, J.M.

    2011-01-01

    The colours of the edible part of fruit and vegetables indicate the presence of specific micronutrients and phytochemicals. The extent to which fruit and vegetable colour groups contribute to CHD protection is unknown. We therefore examined the associations between fruit and vegetables of different

  3. The Need Of A Phenological Spectral Library Of Submersed Macrophytes For Lake Monitoring

    Science.gov (United States)

    Wolf, Patrick; Robler, Sebastian; Schneider, Thomas; Melzer, Arnulf

    2013-12-01

    Submersed macrophytes are bio-indicators for water quality. For plant monitoring by remote sensing, in-situ reflectance measurements are necessary. Hence, systematic measurements were carried out at Lake Starnberg and Lake Tegernsee (Germany) in the year 2011. Besides two wide-spread species (Chara spp. and Potamogeton perfoliatus), the invasive species Elodea nuttallii and Najas marina were investigated. Remote sensing reflectances were calculated from downwelling irradiance and upwelling radiance. Those were collected with RAMSES spectroradiometers (320nm-950nm, 3.3nm step). As data collection took place several times, changes in the spectral responses within the growing season were detected and could be linked to population density, growing height, biomass and pigmentation. Additionally, a stable sampling method and a processing chain for the in-situ reflectance measurements were developed. Part of the processing was a water column correction, including WASI (water colour simulator). Principal component analysis showed separability of sediment from vegetation and species differentiation.

  4. A New Measurement of the Spectral Lag of Gamma-Ray Bursts and its Implications for Spectral Evolution Behaviors

    Energy Technology Data Exchange (ETDEWEB)

    Shao, Lang; Wang, Fu-Ri; Cheng, Ye-Hao; Zhang, Xi; Yu, Bang-Yao; Xi, Bao-Jia; Wang, Xue; Feng, Huan-Xue; Zhang, Meng, E-mail: lshao@hebtu.edu.cn [Department of Space Sciences and Astronomy, Hebei Normal University, Shijiazhuang 050024 (China); Zhang, Bin-Bin [Instituto de Astrofísica de Andalucá (IAA-CSIC), P.O. Box 03004, E-18080 Granada (Spain); Wu, Xue-Feng [Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210008 (China); Xu, Dong [Key Laboratory of Space Astronomy and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China)

    2017-08-01

    We carry out a systematical study of the spectral lag properties of 50 single-pulsed gamma-ray bursts (GRBs) detected by the Fermi Gamma-Ray Burst Monitor. By dividing the light curves into multiple consecutive energy channels, we provide a new measurement of the spectral lag that is independent of energy channel selections. We perform a detailed statistical study of our new measurements. We find two similar power-law energy dependencies of both the pulse arrival time and pulse width. Our new results on the power-law indices would favor the relativistic geometric effects for the origin of spectral lag. However, a complete theoretical framework that can fully account for the diverse energy dependencies of both arrival time and pulse width revealed in this work is still lacking. We also study the spectral evolution behaviors of the GRB pulses. We find that a GRB pulse with negligible spectral lag would usually have a shorter pulse duration and would appear to have a “hardness-intensity tracking” behavior, and a GRB pulse with a significant spectral lag would usually have a longer pulse duration and would appear to have a “hard-to-soft” behavior.

  5. Laser Sensing of Vegetation Based on Dual Spectrum Measurements of Reflection Coefficients

    Directory of Open Access Journals (Sweden)

    M. L. Belov

    2017-01-01

    Full Text Available Currently, a promising trend in remote sensing of environment is to monitor the vegetative cover: evaluate the productivity of agricultural crops; evaluate the moisture content of soils and the state of ecosystems; provide mapping the sites of bogging, desertification, drought, etc.; control the phases of vegetation of crops, etc.Development of monitoring systems for remote detection of vegetation sites being under unfavorable conditions (low or high temperature, excess or lack of water, soil salinity, disease, etc. is of relevance. Optical methods are the most effective for this task. These methods are based on the physical features of reflection spectra in the visible and near infrared spectral range for vegetation under unfavorable conditions and vegetation under normal conditions.One of the options of optoelectronic equipment for monitoring vegetation condition is laser equipment that allows remote sensing of vegetation from the aircraft and mapping of vegetation sites with abnormal (inactive periods of vegetation reflection spectra with a high degree of spatial resolution.The paper deals with development of a promising dual-spectrum method for laser remote sensing of vegetation. Using the experimentally measured reflection spectra of different vegetation types, mathematical modeling of probability for appropriate detection and false alarms to solve a problem of detecting the vegetation under unfavorable conditions (with abnormal reflection spectra is performed based on the results of dual-spectrum measurements of the reflection coefficient.In mathematical modeling, the lidar system was supposed to provide sensing at wavelengths of 0.532 μm and 0.85 μm. The noise of the measurement was supposed to be normal with zero mean value and mean-square value of 1% -10%.It is shown that the method of laser sensing of vegetation condition based on the results of dual-spectrum measurement of the reflection coefficient at wavelengths of 0.532 μm and 0

  6. Sensory determinants of stated liking for vegetable names and actual liking for canned vegetables

    DEFF Research Database (Denmark)

    Dinnella, Caterina; Morizet, David; Masi, Camilla

    2016-01-01

    tastes (sweet, umami), delicate flavour and bright appealing colour. A second group of highly disliked vegetables consists of cauliflowers and broccoli, characterized by disliked sensations such as bitter taste and objectionable flavour. Internal Preference Maps from actual liking scores indicate...

  7. HYPERSPECTRAL HYPERION IMAGERY ANALYSIS AND ITS APPLICATION USING SPECTRAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    W. Pervez

    2015-03-01

    Full Text Available Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data consists of 242 bands out of which 196 calibrated/useful bands are available for hyperspectral applications. Atmospheric correction applied to the hyperspectral calibrated bands make the data more useful for its further processing/ application. Principal component (PC analysis applied to the hyperspectral calibrated bands reduced the dimensionality of the data and it is found that 99% of the data is held in first 10 PCs. Feature extraction is one of the important application by using vegetation delineation and normalized difference vegetation index. The machine learning classifiers uses the technique to identify the pixels having significant difference in the spectral signature which is very useful for classification of an image. Supervised machine learning classifier technique has been used for classification of hyperspectral image which resulted in overall efficiency of 86.6703 and Kappa co-efficient of 0.7998.

  8. Terrestrial Water Storage and Vegetation Resilience to Drought

    Science.gov (United States)

    Meyer, V.; Reager, J. T., II; Konings, A. G.

    2017-12-01

    The expected increased occurrences of hydrologic extreme events such as droughts in the coming decades motivates studies to better understand and predict the response of vegetation to such extreme conditions. Previous studies have addressed vegetation resilience to drought, defined as its ability to recover from a perturbation (Hirota et al., 2011; Vicente-Serrano et al., 2012), but appear to only focus on precipitation and a couple of vegetation indices, hence lacking a key element: terrestrial water storage (TWS). In this study, we combine and compare multiple remotely-sensed hydro-ecological datasets providing information on climatic and hydrological conditions (Tropical Rainfall Measuring Mission (TRMM), Gravity Recovery and Climate Experiment (GRACE)) and indices characterizing the state of the vegetation (vegetation water content using Vegetation Optical Depth (VOD) from SMAP (Soil Moisture Active and Passive), Gross Primary Production (GPP) from FluxCom and Specific Fluorescence Intensity (SFI, from GOSat)) to assess the ability of vegetation to face and recover from droughts across the globe. Our results suggest that GRACE hydrological data bridge the knowledge gap between precipitation deficit and vegetation response. All products are aggregated at a 0.5º spatial resolution and a monthly temporal resolution to match the GRACE Mascon product. Despite these coarse spatiotemporal resolutions, we find that the relationship between existing remotely-sensed eco-hydrologic data varies spatially, both in terms of strength of relationship and time lag, showing the response time of vegetation characteristics to hydrological changes and highlighting the role of water storage. A special attention is given to the Amazon river basin, where two well documented droughts occurred in 2005 and 2010, and where a more recent drought occurred in 2015/2016. References : Hirota, Marina, et al. "Global resilience of tropical forest and savanna to critical transitions." Science

  9. Estimated inventory of plutonium and uranium radionuclides for vegetation in aged fallout areas

    International Nuclear Information System (INIS)

    Romney, E.M.; Gilbert, R.O.; Wallace, A.; Kinnear, J.

    1976-02-01

    Data are presented on the contamination of vegetation by 239 Pu, 240 Pu, and other radionuclides in aged fallout areas on the Nevada Test Site (NTS) and the Tonopah Test Range (TTR). Comparisons of soil and vegetation inventory estimates indicate that the standing vegetation contributes an insignificant portion of the total amount of 239-240 Pu present in these aged fallout areas. The amounts of Pu available for vegetation-transport to animals grazing on-site would appear to be relatively small in comparison to the total amounts deposited upon soil. Findings indicate that most of the contaminant found on vegetation probably is attributable to resuspendable materials

  10. Relationship between leaf optical properties, chlorophyll fluorescence and pigment changes in senescing Acer saccharum leaves.

    Science.gov (United States)

    Junker, Laura Verena; Ensminger, Ingo

    2016-06-01

    The ability of plants to sequester carbon is highly variable over the course of the year and reflects seasonal variation in photosynthetic efficiency. This seasonal variation is most prominent during autumn, when leaves of deciduous tree species such as sugar maple (Acer saccharum Marsh.) undergo senescence, which is associated with downregulation of photosynthesis and a change of leaf color. The remote sensing of leaf color by spectral reflectance measurements and digital repeat images is increasingly used to improve models of growing season length and seasonal variation in carbon sequestration. Vegetation indices derived from spectral reflectance measurements and digital repeat images might not adequately reflect photosynthetic efficiency of red-senescing tree species during autumn due to the changes in foliar pigment content associated with autumn phenology. In this study, we aimed to assess how effectively several widely used vegetation indices capture autumn phenology and reflect the changes in physiology and photosynthetic pigments during autumn. Chlorophyll fluorescence and pigment content of green, yellow, orange and red leaves were measured to represent leaf senescence during autumn and used as a reference to validate and compare vegetation indices derived from leaf-level spectral reflectance measurements and color analysis of digital images. Vegetation indices varied in their suitability to track the decrease of photosynthetic efficiency and chlorophyll content despite increasing anthocyanin content. Commonly used spectral reflectance indices such as the normalized difference vegetation index and photochemical reflectance index showed major constraints arising from a limited representation of gradual decreases in chlorophyll content and an influence of high foliar anthocyanin levels. The excess green index and green-red vegetation index were more suitable to assess the process of senescence. Similarly, digital image analysis revealed that vegetation

  11. Terrestrial transect study on driving mechanism of vegetation changes

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In terms of Chinese climate-vegetation model based on the classification of plant functional types, to- gether with climatic data from 1951 to 1980 and two future climatic scenarios (SRES-A2 and SRES-B2) in China from the highest and the lowest emission scenarios of greenhouse gases, the distribution patterns of vegetation types and their changes along the Northeast China Transect (NECT) and the North-South Transect of Eastern China (NSTEC) were simulated in order to understand the driving mechanisms of vegetation changes under climatic change. The results indicated that the vegetation distribution patterns would change significantly under future climate, and the major factors driving the vegetation changes were water and heat. However, the responses of various vegetation types to the changes in water and heat factors were obviously different. The vegetation changes were more sensi- tive to heat factors than to water factors. Thus, in the future climate warming will significantly affect vegetation distribution patterns.

  12. Relationships between vegetation and climate change in Transbaikalia, Siberia

    Energy Technology Data Exchange (ETDEWEB)

    Tchebakova, N.M.; Parfenova, E.I. [V.N. Sukachev Inst. of Forest, Russian Academy of Sciences, Siberian Branch, Akademgorodok, Krasnoyarsk (Russian Federation)

    2002-10-01

    This paper demonstrated how vegetation of the Lake Baikal basin may respond to climate change at a mountain biome (an orobiome over the entire basin) and a stand in a locality. An orobiome vegetation model was developed along with a higher resolution stand model based on climatic parameters. Regional climates were modeled based on physiology and site climates based on topography. Bioclimatic multiple regression models were then developed to predict regional vegetation and forest stand characteristics distribution over a mountain range in Central Transbaikalia under current and future climate scenarios. Bioclimatic models were combined with climatic layers of different resolutions. Tree species composition and wood volume was predicted based on 2 climate indices - temperature sums (base 5 degrees C) and the dryness index. Results indicate that lowland vegetation will shift 250 m upslope and highland vegetation will shift 450 m upslope. This will significantly reduce the tundra and light-needled taiga, and will expand the forest-steppe. Results also indicate that the total phytomass within the entire basin will not change much. Stand phytomass across the basin will, however, increase. The model used in this study does not include climate-forcing factors such as wind, snow and permafrost. The model is open to new development to include a dynamic components that would inject vitality into the model. 13 refs., 2 tabs., 3 figs.

  13. Effect of Phosphate levels on vegetables irrigated with wastewater

    Science.gov (United States)

    Oladeji, S. O.; Saeed, M. D.

    2018-04-01

    This study examined accumulation of phosphate ions in wastewater and vegetables through man-made activities. Phosphate level was determined in wastewater and vegetables collected on seasonal basis along Kubanni stream in Zaria using UV/Visible and Smart Spectro Spectrophotometers for their analyses. Results obtained show that phosphate concentrations ranged from 3.85 – 42.33 mg/L in the first year and 15.60 – 72.80 mg/L in the second year for wastewater whereas the vegetable had levels of 3.80 – 23.65 mg/kg in the year I and 7.48 – 27.15 mg/kg in the year II. Further statistical tests indicated no significant difference in phosphate levels across the locations and seasons for wastewater and vegetables evaluated. Correlation results for these two years indicated negative (r = -0.062) relationship for wastewater while low (r = 0.339) relationship noticed for vegetables planted in year I to that of year II. Phosphate concentrations obtained in this study was higher than Maximum Contaminant Levels set by Standard Organization such as WHO and FAO for wastewater whereas vegetables of the sampling sites were not contaminated with phosphate ions. Irrigating farmland with untreated wastewater has negative consequence on the crops grown with it.

  14. Canopy Vegetation Indices from In situ Hyperspectral Data to Assess Plant Water Status of Winter Wheat under Powdery Mildew Stress.

    Science.gov (United States)

    Feng, Wei; Qi, Shuangli; Heng, Yarong; Zhou, Yi; Wu, Yapeng; Liu, Wandai; He, Li; Li, Xiao

    2017-01-01

    Plant disease and pests influence the physiological state and restricts the healthy growth of crops. Physiological measurements are considered the most accurate way of assessing plant health status. In this paper, we researched the use of an in situ hyperspectral remote sensor to detect plant water status in winter wheat infected with powdery mildew. Using a diseased nursery field and artificially inoculated open field experiments, we detected the canopy spectra of wheat at different developmental stages and under different degrees of disease severity. At the same time, destructive sampling was carried out for physical tests to investigate the change of physiological parameters under the condition of disease. Selected vegetation indices (VIs) were mostly comprised of green bands, and correlation coefficients between these common VIs and plant water content (PWC) were generally 0.784-0.902 ( p powdery mildew stress. The Photochemical Reflectance Index (PRI) was sensitive to physiological response influenced by powdery mildew, and the relationships of PRI with chlorophyll content, the maximum quantum efficiency of PSII photochemistry (Fv/Fm), and the potential activity of PSII photochemistry (Fv/Fo) were good with R 2 = 0.639, 0.833, 0.808, respectively. Linear regressions showed PRI demonstrated a steady relationship with PWC across different growth conditions, with R 2 = 0.817 and RMSE = 2.17. The acquired PRI model of wheat under the powdery mildew stress has a good compatibility to different experimental fields from booting stage to filling stage compared with the traditional water signal vegetation indices, WBI, FWBI 1 , and FWBI 2 . The verification results with independent data showed that PRI still performed better with R 2 = 0.819 between measured and predicted, and corresponding RE = 8.26%. Thus, PRI is recommended as a potentially reliable indicator of PWC in winter wheat with powdery mildew stress. The results will help to understand the physical state of

  15. Estimativa da disponibilidade de forragem do bioma Campos Sulinos a partir de dados radiométricos orbitais: parametrização do submodelo espectral Forecast the available forage of natural pastures of Campos Sulinos biome using satellite spectral data: parameterization for the spectral submodel

    Directory of Open Access Journals (Sweden)

    Eliana Lima da Fonseca

    2007-12-01

    Full Text Available Este trabalho apresenta a parametrização do submodelo espectral do modelo JONG, um modelo agrometeorológico-espectral para a previsão da disponibilidade de forragem das pastagens naturais do bioma Campos Sulinos. A parametrização foi feita testando-se a capacidade de diferentes variáveis espectrais obtidas a partir de imagens do sensor ETM+/Landsat 7 representando a disponibilidade de forragem em diferentes fases do ciclo fenológico da vegetação campestre natural do bioma Campos Sulinos. Verificou-se que as variáveis Wetness e reflectância da banda ETM+7/Landsat 7 representam o status inicial da vegetação de forma eficiente, mas não tiveram sensibilidade suficiente para eliminar os efeitos do tipo de solo na resposta espectral da vegetação.This research presents the parameterization for the spectral submodel of JONG model, an agrometeorologic-spectral model to forecast the available forage of natural pastures of Campos Sulinos biome. Tthe capacity of different spectral variables, gotten from images of the sensor ETM+/Landsat 7, to represent the forage availability in different phases of its fenologic cycle was realized. The Wetness variable and reflectance of the band ETM+7/Landsat 7 represent the initial status of vegetation of efficient form was verified, however had no sensitivity enough to eliminate the effect of soil type in the spectral response of the vegetation.

  16. Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose.

    Science.gov (United States)

    Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K; Abaidoo, Robert C; Dalsgaard, Anders; Hald, Tine

    2017-12-01

    The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10 -5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data. In some cases the difference was >2 orders of magnitude. All scenarios using genome copies met the 10 -4 DALY per person per year for consumption of vegetables irrigated with wastewater, although these results are considered to be highly conservative risk estimates. The fecal indicator conversion ratio model of stream-water and drain-water sources of wastewater achieved the 10 -6 DALY per person per year threshold, which tends to indicate an underestimation of health risk when compared to using genome copies for estimating the dose. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Irrigation Requirement Estimation Using Vegetation Indices and Inverse Biophysical Modeling

    Science.gov (United States)

    Bounoua, Lahouari; Imhoff, Marc L.; Franks, Shannon

    2010-01-01

    We explore an inverse biophysical modeling process forced by satellite and climatological data to quantify irrigation requirements in semi-arid agricultural areas. We constrain the carbon and water cycles modeled under both equilibrium, balance between vegetation and climate, and non-equilibrium, water added through irrigation. We postulate that the degree to which irrigated dry lands vary from equilibrium climate conditions is related to the amount of irrigation. The amount of water required over and above precipitation is considered as an irrigation requirement. For July, results show that spray irrigation resulted in an additional amount of water of 1.3 mm per occurrence with a frequency of 24.6 hours. In contrast, the drip irrigation required only 0.6 mm every 45.6 hours or 46% of that simulated by the spray irrigation. The modeled estimates account for 87% of the total reported irrigation water use, when soil salinity is not important and 66% in saline lands.

  18. Pepper seed variety identification based on visible/near-infrared spectral technology

    Science.gov (United States)

    Li, Cuiling; Wang, Xiu; Meng, Zhijun; Fan, Pengfei; Cai, Jichen

    2016-11-01

    Pepper is a kind of important fruit vegetable, with the expansion of pepper hybrid planting area, detection of pepper seed purity is especially important. This research used visible/near infrared (VIS/NIR) spectral technology to detect the variety of single pepper seed, and chose hybrid pepper seeds "Zhuo Jiao NO.3", "Zhuo Jiao NO.4" and "Zhuo Jiao NO.5" as research sample. VIS/NIR spectral data of 80 "Zhuo Jiao NO.3", 80 "Zhuo Jiao NO.4" and 80 "Zhuo Jiao NO.5" pepper seeds were collected, and the original spectral data was pretreated with standard normal variable (SNV) transform, first derivative (FD), and Savitzky-Golay (SG) convolution smoothing methods. Principal component analysis (PCA) method was adopted to reduce the dimension of the spectral data and extract principal components, according to the distribution of the first principal component (PC1) along with the second principal component(PC2) in the twodimensional plane, similarly, the distribution of PC1 coupled with the third principal component(PC3), and the distribution of PC2 combined with PC3, distribution areas of three varieties of pepper seeds were divided in each twodimensional plane, and the discriminant accuracy of PCA was tested through observing the distribution area of samples' principal components in validation set. This study combined PCA and linear discriminant analysis (LDA) to identify single pepper seed varieties, results showed that with the FD preprocessing method, the discriminant accuracy of pepper seed varieties was 98% for validation set, it concludes that using VIS/NIR spectral technology is feasible for identification of single pepper seed varieties.

  19. Visual Method for Spectral Energy Distribution Calculation of ...

    Indian Academy of Sciences (India)

    Abstract. In this work, we propose to use 'The Geometer's Sketchpad' to the fitting of a spectral energy distribution of blazar based on three effective spectral indices, αRO, αOX, and αRX and the flux density in the radio band. It can make us to see the fitting in detail with both the peak frequency and peak luminosity given ...

  20. Vegetation Change in Interior Alaska Over the Last Four Decades

    Science.gov (United States)

    Huhman, H.; Dewitz, J.; Cristobal, J.; Prakash, A.

    2017-12-01

    The Arctic has become a generally warmer place over the past decades leading to earlier snowmelt, permafrost degradation and changing plant communities. One area in particular, vegetation change, is responding relatively rapidly to climate change, impacting the surrounding environment with changes to forest fire regime, forest type, forest resiliency, habitat availability for subsistence flora and fauna, hydrology, among others. To quantify changes in vegetation in the interior Alaska boreal forest over the last four decades, this study uses the National Land Cover Database (NLCD) decision-tree based classification methods, using both C5 and ERDAS Imagine software, to classify Landsat Surface Reflectance Images into the following NLCD-consistent vegetation classes: planted, herbaceous, shrubland, and forest (deciduous, evergreen and mixed). The results of this process are a total of four vegetation cover maps, that are freely accessible to the public, one for each decade in the 1980's, 1990's, 2000's, and a current map for 2017. These maps focus on Fairbanks, Alaska and the surrounding area covering approximately 36,140 square miles. The maps are validated with over 4,000 ground truth points collected through organizations such as the Landfire Project and the Long Term Ecological Research Network, as well as vegetation and soil spectra collected from the study area concurrent with the Landsat satellite over-passes with a Spectral Evolution PSR+ 3500 spectro-radiometer (0.35 - 2.5 μm). We anticipate these maps to be viewed by a wide user-community and may aid in preparing the residents of Alaska for changes in their subsistence food sources and will contribute to the scientific community in understanding the variety of changes that can occur in response to changing vegetation.

  1. COMPARISON BETWEEN SPECTRAL, SPATIAL AND POLARIMETRIC CLASSIFICATION OF URBAN AND PERIURBAN LANDCOVER USING TEMPORAL SENTINEL – 1 IMAGES

    Directory of Open Access Journals (Sweden)

    K. Roychowdhury

    2016-06-01

    Full Text Available Landcover is the easiest detectable indicator of human interventions on land. Urban and peri-urban areas present a complex combination of landcover, which makes classification challenging. This paper assesses the different methods of classifying landcover using dual polarimetric Sentinel-1 data collected during monsoon (July and winter (December months of 2015. Four broad landcover classes such as built up areas, water bodies and wetlands, vegetation and open spaces of Kolkata and its surrounding regions were identified. Polarimetric analyses were conducted on Single Look Complex (SLC data of the region while ground range detected (GRD data were used for spectral and spatial classification. Unsupervised classification by means of K-Means clustering used backscatter values and was able to identify homogenous landcovers over the study area. The results produced an overall accuracy of less than 50% for both the seasons. Higher classification accuracy (around 70% was achieved by adding texture variables as inputs along with the backscatter values. However, the accuracy of classification increased significantly with polarimetric analyses. The overall accuracy was around 80% in Wishart H-A-Alpha unsupervised classification. The method was useful in identifying urban areas due to their double-bounce scattering and vegetated areas, which have more random scattering. Normalized Difference Built-up index (NDBI and Normalized Difference Vegetation Index (NDVI obtained from Landsat 8 data over the study area were used to verify vegetation and urban classes. The study compares the accuracies of different methods of classifying landcover using medium resolution SAR data in a complex urban area and suggests that polarimetric analyses present the most accurate results for urban and suburban areas.

  2. Irrigation Requirement Estimation using MODIS Vegetation Indices and Inverse Biophysical Modeling; A Case Study for Oran, Algeria

    Science.gov (United States)

    Bounoua, L.; Imhoff, M.L.; Franks, S.

    2008-01-01

    Human demand for food influences the water cycle through diversion and extraction of fresh water needed to support agriculture. Future population growth and economic development alone will substantially increase water demand and much of it for agricultural uses. For many semi-arid lands, socio-economic shifts are likely to exacerbate changes in climate as a driver of future water supply and demand. For these areas in particular, where the balance between water supply and demand is fragile, variations in regional climate can have potentially predictable effect on agricultural production. Satellite data and biophysically-based models provide a powerful method to quantify the interactions between local climate, plant growth and water resource requirements. In irrigated agricultural lands, satellite observations indicate high vegetation density while the precipitation amount indicates otherwise. This inconsistency between the observed precipitation and the observed canopy leaf density triggers the possibility that the observed high leaf density is due to an alternate source of water, irrigation. We explore an inverse process approach using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), climatological data, and the NASA's Simple Biosphere model, SiB2, to quantitatively assess water demand in a semi-arid agricultural land by constraining the carbon and water cycles modeled under both equilibrium (balance between vegetation and prevailing local climate) and nonequilibrium (water added through irrigation) conditions. We postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. We added water using two distribution methods: The first method adds water on top of the canopy and is a proxy for the traditional spray irrigation. The second method allows water to be applied directly into the soil layer and serves as proxy for drip irrigation. Our approach indicates that over

  3. VISIBE AND INFRARED SPECTRAL CHARACTERISATION OF CHINESE CABBAGE (BRASSICA RAPA L. SUBSPECIES CHINENSIS, GROWN UNDER DIFFERENT NITROGEN, POTASSIUM AND PHOSPHORUS CONCENTRATIONS

    Directory of Open Access Journals (Sweden)

    B. B. Mokoatsi

    2017-11-01

    Full Text Available There is a need to intensify research efforts on improving productivity of indigenous vegetables in South Africa. One research avenue is operationalizing remote sensing techniques to monitor crop health status. This study aimed at characterising the spectral properties of Chinese cabbage (Brassica Rapa L. subspecies Chinensis grown under varying fertilizer treatments: nitrogen (0 kg/ha, 75 kg/ha, 125 kg/ha, 175 kg/ha and 225 kg/ha, phosphorus (0 kg/ha, 9.4 kg/ha, 15.6, 21.9 kg/ha and 28.1 kg/ha and potassium (0 kg/ha, 9.4  kg/ha, 15.6 kg/ha, 21.9 kg/ha and 28.1 kg/ha. Visible and infrared spectral measurements were taken from a total of 60 samples inside the laboratory. Contiguous spectral regions were plotted to show spectral profiles of the different fertilizer treatments and then classified using gradient boosting and random forest classifiers. ANOVA revealed the potential of spectral reflectance data in discriminating different fertiliser treatments from crops. There was also a significant difference between the capabilities of the two classifiers. Gradient boost model (GBM yielded higher classification accuracies than random forest (RF. The important variables identified by each model improved the classification accuracy. Overall, the results indicate a potential for the use of spectroscopy in monitoring food quality parameters, thereby reducing the cost of traditional methods. Further research into advanced statistical analysis techniques is needed to improve the accuracy with which fertiliser concentrations in crops could be quantified. The random forest model particularly requires improvements.

  4. Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

    Science.gov (United States)

    Poitras, Travis; Villarreal, Miguel; Waller, Eric K.; Nauman, Travis; Miller, Mark E.; Duniway, Michael C.

    2018-01-01

    Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

  5. Spectral properties of 441 radio pulsars

    Science.gov (United States)

    Jankowski, F.; van Straten, W.; Keane, E. F.; Bailes, M.; Barr, E. D.; Johnston, S.; Kerr, M.

    2018-02-01

    We present a study of the spectral properties of 441 pulsars observed with the Parkes radio telescope near the centre frequencies of 728, 1382 and 3100 MHz. The observations at 728 and 3100 MHz were conducted simultaneously using the dual-band 10-50 cm receiver. These high-sensitivity, multifrequency observations provide a systematic and uniform sample of pulsar flux densities. We combine our measurements with spectral data from the literature in order to derive the spectral properties of these pulsars. Using techniques from robust regression and information theory, we classify the observed spectra in an objective, robust and unbiased way into five morphological classes: simple or broken power law, power law with either low- or high-frequency cut-off and log-parabolic spectrum. While about 79 per cent of the pulsars that could be classified have simple power-law spectra, we find significant deviations in 73 pulsars, 35 of which have curved spectra, 25 with a spectral break and 10 with a low-frequency turn-over. We identify 11 gigahertz-peaked spectrum (GPS) pulsars, with 3 newly identified in this work and 8 confirmations of known GPS pulsars; 3 others show tentative evidence of GPS, but require further low-frequency measurements to support this classification. The weighted mean spectral index of all pulsars with simple power-law spectra is -1.60 ± 0.03. The observed spectral indices are well described by a shifted log-normal distribution. The strongest correlations of spectral index are with spin-down luminosity, magnetic field at the light-cylinder and spin-down rate. We also investigate the physical origin of the observed spectral features and determine emission altitudes for three pulsars.

  6. Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions.

    Science.gov (United States)

    Fraga, Helder; Malheiro, Aureliano C; Moutinho-Pereira, José; Cardoso, Rita M; Soares, Pedro M M; Cancela, Javier J; Pinto, Joaquim G; Santos, João A

    2014-01-01

    The Iberian viticultural regions are convened according to the Denomination of Origin (DO) and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation) were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

  7. Understanding the radio spectral indices of galaxy cluster relics by superdiffusive shock acceleration

    Science.gov (United States)

    Zimbardo, Gaetano; Perri, Silvia

    2018-06-01

    Galaxy cluster merger shocks are the likely source of relativistic electrons, but many observations do not fit into the standard acceleration models. In particular, there is a long-standing discrepancy between the radio derived Mach numbers M_radio and the Mach numbers derived from X-ray measurements, M_X. Here, we show how superdiffusive electron transport and superdiffusive shock acceleration (SSA) can help to solve this problem. We present a heuristic derivation of the superlinear time growth of the mean square displacement of particles, ⟨Δx2⟩∝tβ, and of the particle energy spectral index in the framework of SSA. The resulting expression for the radio spectral index α is then used to determine the superdiffusive exponent β from the observed values of α and of the compression ratio for a number of radio relics. Therefore, the fact that M_radio>M_X can be explained by SSA without the need to make assumptions on the energy spectrum of the seed electrons to be re-accelerated. We also consider the acceleration times obtained in the diffusive case, based both on the Bohm diffusion coefficient and on the quasilinear diffusion coefficient. While in the latter case the acceleration time is consistent with the estimated electron energy loss time, the former case it is much shorter.

  8. Effects of spectral smearing on performance of the spectral ripple and spectro-temporal ripple tests.

    Science.gov (United States)

    Narne, Vijaya Kumar; Sharma, Mridula; Van Dun, Bram; Bansal, Shalini; Prabhu, Latika; Moore, Brian C J

    2016-12-01

    The main aim of this study was to use spectral smearing to evaluate the efficacy of a spectral ripple test (SRt) using stationary sounds and a recent variant with gliding ripples called the spectro-temporal ripple test (STRt) in measuring reduced spectral resolution. In experiment 1 the highest detectable ripple density was measured using four amounts of spectral smearing (unsmeared, mild, moderate, and severe). The thresholds worsened with increasing smearing and were similar for the SRt and the STRt across the three conditions with smearing. For unsmeared stimuli, thresholds were significantly higher (better) for the STRt than for the SRt. An amplitude fluctuation at the outputs of simulated (gammatone) auditory filters centered above 6400 Hz was identified as providing a potential detection cue for the STRt stimuli. Experiment 2 used notched noise with energy below and above the passband of the SRt and STRt stimuli to reduce confounding cues in the STRt. Thresholds were almost identical for the STRt and SRt for both unsmeared and smeared stimuli, indicating that the confounding cue for the STRt was eliminated by the notched noise. Thresholds obtained with notched noise present could be predicted reasonably accurately using an excitation-pattern model.

  9. Presence of indicator plant species as a predictor of wetland vegetation integrity

    Science.gov (United States)

    Stapanian, Martin A.; Adams, Jean V.; Gara, Brian

    2013-01-01

    We fit regression and classification tree models to vegetation data collected from Ohio (USA) wetlands to determine (1) which species best predict Ohio vegetation index of biotic integrity (OVIBI) score and (2) which species best predict high-quality wetlands (OVIBI score >75). The simplest regression tree model predicted OVIBI score based on the occurrence of three plant species: skunk-cabbage (Symplocarpus foetidus), cinnamon fern (Osmunda cinnamomea), and swamp rose (Rosa palustris). The lowest OVIBI scores were best predicted by the absence of the selected plant species rather than by the presence of other species. The simplest classification tree model predicted high-quality wetlands based on the occurrence of two plant species: skunk-cabbage and marsh-fern (Thelypteris palustris). The overall misclassification rate from this tree was 13 %. Again, low-quality wetlands were better predicted than high-quality wetlands by the absence of selected species rather than the presence of other species using the classification tree model. Our results suggest that a species’ wetland status classification and coefficient of conservatism are of little use in predicting wetland quality. A simple, statistically derived species checklist such as the one created in this study could be used by field biologists to quickly and efficiently identify wetland sites likely to be regulated as high-quality, and requiring more intensive field assessments. Alternatively, it can be used for advanced determinations of low-quality wetlands. Agencies can save considerable money by screening wetlands for the presence/absence of such “indicator” species before issuing permits.

  10. Hyperspectral detection of a subsurface CO2 leak in the presence of water stressed vegetation.

    Directory of Open Access Journals (Sweden)

    Gabriel J Bellante

    Full Text Available Remote sensing of vegetation stress has been posed as a possible large area monitoring tool for surface CO2 leakage from geologic carbon sequestration (GCS sites since vegetation is adversely affected by elevated CO2 levels in soil. However, the extent to which remote sensing could be used for CO2 leak detection depends on the spectral separability of the plant stress signal caused by various factors, including elevated soil CO2 and water stress. This distinction is crucial to determining the seasonality and appropriateness of remote GCS site monitoring. A greenhouse experiment tested the degree to which plants stressed by elevated soil CO2 could be distinguished from plants that were water stressed. A randomized block design assigned Alfalfa plants (Medicago sativa to one of four possible treatment groups: 1 a CO2 injection group; 2 a water stress group; 3 an interaction group that was subjected to both water stress and CO2 injection; or 4 a group that received adequate water and no CO2 injection. Single date classification trees were developed to identify individual spectral bands that were significant in distinguishing between CO2 and water stress agents, in addition to a random forest classifier that was used to further understand and validate predictive accuracies. Overall peak classification accuracy was 90% (Kappa of 0.87 for the classification tree analysis and 83% (Kappa of 0.77 for the random forest classifier, demonstrating that vegetation stressed from an underground CO2 leak could be accurately discerned from healthy vegetation and areas of co-occurring water stressed vegetation at certain times. Plants appear to hit a stress threshold, however, that would render detection of a CO2 leak unlikely during severe drought conditions. Our findings suggest that early detection of a CO2 leak with an aerial or ground-based hyperspectral imaging system is possible and could be an important GCS monitoring tool.

  11. Hyperspectral detection of a subsurface CO2 leak in the presence of water stressed vegetation.

    Science.gov (United States)

    Bellante, Gabriel J; Powell, Scott L; Lawrence, Rick L; Repasky, Kevin S; Dougher, Tracy

    2014-01-01

    Remote sensing of vegetation stress has been posed as a possible large area monitoring tool for surface CO2 leakage from geologic carbon sequestration (GCS) sites since vegetation is adversely affected by elevated CO2 levels in soil. However, the extent to which remote sensing could be used for CO2 leak detection depends on the spectral separability of the plant stress signal caused by various factors, including elevated soil CO2 and water stress. This distinction is crucial to determining the seasonality and appropriateness of remote GCS site monitoring. A greenhouse experiment tested the degree to which plants stressed by elevated soil CO2 could be distinguished from plants that were water stressed. A randomized block design assigned Alfalfa plants (Medicago sativa) to one of four possible treatment groups: 1) a CO2 injection group; 2) a water stress group; 3) an interaction group that was subjected to both water stress and CO2 injection; or 4) a group that received adequate water and no CO2 injection. Single date classification trees were developed to identify individual spectral bands that were significant in distinguishing between CO2 and water stress agents, in addition to a random forest classifier that was used to further understand and validate predictive accuracies. Overall peak classification accuracy was 90% (Kappa of 0.87) for the classification tree analysis and 83% (Kappa of 0.77) for the random forest classifier, demonstrating that vegetation stressed from an underground CO2 leak could be accurately discerned from healthy vegetation and areas of co-occurring water stressed vegetation at certain times. Plants appear to hit a stress threshold, however, that would render detection of a CO2 leak unlikely during severe drought conditions. Our findings suggest that early detection of a CO2 leak with an aerial or ground-based hyperspectral imaging system is possible and could be an important GCS monitoring tool.

  12. THE SPECTRAL INDEX PROPERTIES OF FERMI BLAZARS

    Energy Technology Data Exchange (ETDEWEB)

    Fan, J. H.; Yang, J. H.; Yuan, Y. H.; Wang, J.; Gao, Y., E-mail: jhfan_cn@yahoo.com.cn [Center for Astrophysics, Guangzhou University, Guangzhou 510006 (China)

    2012-12-20

    In this paper, a sample of 451 blazars (193 flat spectrum radio quasars (FSRQs), 258 BL Lacertae objects) with corresponding X-ray and Fermi {gamma}-ray data is compiled to investigate the correlation both between the X-ray spectral index and the {gamma}-ray spectral index and between the spectral index and the luminosity, and to compare the spectral indexes {alpha}{sub X}, {alpha}{sub {gamma}}, {alpha}{sub X{gamma}}, and {alpha}{sub {gamma}X{gamma}} for different subclasses. We also investigated the correlation between the X-ray and the {gamma}-ray luminosity. The following results have been obtained. Our analysis indicates that an anti-correlation exists between the X-ray and the {gamma}-ray spectral indexes for the whole sample. However, when we considered the subclasses of blazars (FSRQs, the low-peaked BL Lacertae objects (LBLs) and the high-peaked BL Lacertae objects (HBLs)) separately, there is not a clear relationship for each subclass. Based on the Fermi-detected sources, we can say that the HBLs are different from FSRQs, while the LBLs are similar to FSRQs.

  13. Dimension Reduction of Multi-Spectral Satellite Image Time Series to Improve Deforestation Monitoring

    Directory of Open Access Journals (Sweden)

    Meng Lu

    2017-10-01

    Full Text Available In recent years, sequential tests for detecting structural changes in time series have been adapted for deforestation monitoring using satellite data. The input time series of such sequential tests is typically a vegetation index (e.g., NDVI, which uses two or three bands and ignores all other bands. Being limited to a vegetation index will not benefit from the richer spectral information provided by newly launched satellites and will bring two bottle-necks for deforestation monitoring. Firstly, it is hard to select a suitable vegetation index a priori. Secondly, a single vegetation index is typically affected by seasonal signals, noise and other natural dynamics, which decrease its power for deforestation detection. A novel multispectral time series change monitoring method that combines dimension reduction methods with a sequential hypothesis test is proposed to address these limitations. For each location, the proposed method automatically chooses a “suitable” index for deforestation monitoring. To demonstrate our approach, we implemented it in two study areas: a dry tropical forest in Bolivia (time series length: 444 with strong seasonality and a moist tropical forest in Brazil (time series length: 225 with almost no seasonality. Our method significantly improves accuracy in the presence of strong seasonality, in particular the temporal lag between disturbance and its detection.

  14. Understanding Soliton Spectral Tunneling as a Spectral Coupling Effect

    DEFF Research Database (Denmark)

    Guo, Hairun; Wang, Shaofei; Zeng, Xianglong

    2013-01-01

    Soliton eigenstate is found corresponding to a dispersive phase profile under which the soliton phase changes induced by the dispersion and nonlinearity are instantaneously counterbalanced. Much like a waveguide coupler relying on a spatial refractive index profile that supports mode coupling...... between channels, here we suggest that the soliton spectral tunneling effect can be understood supported by a spectral phase coupler. The dispersive wave number in the spectral domain must have a coupler-like symmetric profile for soliton spectral tunneling to occur. We show that such a spectral coupler...

  15. Marketing system analysis of vegetables and fruits in Amhara ...

    African Journals Online (AJOL)

    This study attempted to analyze the different aspects of marketing system of vegetable and fruit in Raya Kobo and Harbu woredas, Amhara regional state using different indicators. Probit estimation for determinant of participation probability in vegetable and fruit production and OLS estimation technique were also applied for ...

  16. Monitoring phenology of photosynthesis in temperate evergreen and mixed deciduous forests using the normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI) at leaf and canopy scales

    Science.gov (United States)

    Wong, C. Y.; Arain, M. A.; Ensminger, I.

    2016-12-01

    Evergreen conifers in boreal and temperate regions undergo strong seasonal changes in photoperiod and temperatures, which determines their phenology of high photosynthetic activity in the growing season and downregulation during the winter. Monitoring the timing of the transition between summer activity and winter downregulation in evergreens is difficult since this is a largely invisible process, unlike in deciduous trees that have a visible budding and a sequence of leaf unfolding in the spring and leaf abscission in the fall. The light-use efficiency (LUE) model estimates gross primary productivity (GPP) and may be parameterized using remotely sensed vegetation indices. Using spectral reflectance data, we derived the normalized difference vegetation index (NDVI), a measure of leaf "greenness", and the photochemical reflectance index (PRI), a proxy for chlorophyll:carotenoid ratios which is related to photosynthetic activity. To better understand the relationship between these vegetation indices and photosynthetic activity and to contrast this relationship between plant functional types, the phenology of NDVI, PRI and photosynthesis was monitored in an evergreen forest and a mixed deciduous forest at the leaf and canopy scale. Our data indicates that the LUE model can be parameterized by NDVI and PRI to track forest phenology. Differences in the sensitivity of PRI and NDVI will be discussed. These findings have implications to address the phenology of evergreen conifers by using PRI to complement NDVI in the LUE model, potentially improving model productivity estimates in northern hemisphere forests, that are dominated by conifers.

  17. Soil classification basing on the spectral characteristics of topsoil samples

    Science.gov (United States)

    Liu, Huanjun; Zhang, Xiaokang; Zhang, Xinle

    2016-04-01

    Soil taxonomy plays an important role in soil utility and management, but China has only course soil map created based on 1980s data. New technology, e.g. spectroscopy, could simplify soil classification. The study try to classify soils basing on the spectral characteristics of topsoil samples. 148 topsoil samples of typical soils, including Black soil, Chernozem, Blown soil and Meadow soil, were collected from Songnen plain, Northeast China, and the room spectral reflectance in the visible and near infrared region (400-2500 nm) were processed with weighted moving average, resampling technique, and continuum removal. Spectral indices were extracted from soil spectral characteristics, including the second absorption positions of spectral curve, the first absorption vale's area, and slope of spectral curve at 500-600 nm and 1340-1360 nm. Then K-means clustering and decision tree were used respectively to build soil classification model. The results indicated that 1) the second absorption positions of Black soil and Chernozem were located at 610 nm and 650 nm respectively; 2) the spectral curve of the meadow is similar to its adjacent soil, which could be due to soil erosion; 3) decision tree model showed higher classification accuracy, and accuracy of Black soil, Chernozem, Blown soil and Meadow are 100%, 88%, 97%, 50% respectively, and the accuracy of Blown soil could be increased to 100% by adding one more spectral index (the first two vole's area) to the model, which showed that the model could be used for soil classification and soil map in near future.

  18. Spatial-Spectral Approaches to Edge Detection in Hyperspectral Remote Sensing

    Science.gov (United States)

    Cox, Cary M.

    also explores the concept of an edge within hyperspectral space, the relative importance of spatial and spectral resolutions as they pertain to HSI edge detection and how effectively compressed HSI data improves edge detection results. The HSI edge detection experiments yielded valuable insights into the algorithms' strengths, weaknesses and optimal alignment to remote sensing applications. The gradient-based edge operator produced strong edge planes across a range of evaluation measures and applications, particularly with respect to false negatives, unbroken edges, urban mapping, vegetation mapping and oil spill mapping applications. False positives and uncompressed HSI data presented occasional challenges to the algorithm. The HySPADE edge operator produced satisfactory results with respect to localization, single-point response, oil spill mapping and trace chemical detection, and was challenged by false positives, declining spectral resolution and vegetation mapping applications. The level set edge detector produced high-quality edge planes for most tests and demonstrated strong performance with respect to false positives, single-point response, oil spill mapping and mineral mapping. False negatives were a regular challenge for the level set edge detection algorithm. Finally, HSI data optimized for spectral information compression and noise was shown to improve edge detection performance across all three algorithms, while the gradient-based algorithm and HySPADE demonstrated significant robustness to declining spectral and spatial resolutions.

  19. Spectral dimension of quantum geometries

    International Nuclear Information System (INIS)

    Calcagni, Gianluca; Oriti, Daniele; Thürigen, Johannes

    2014-01-01

    The spectral dimension is an indicator of geometry and topology of spacetime and a tool to compare the description of quantum geometry in various approaches to quantum gravity. This is possible because it can be defined not only on smooth geometries but also on discrete (e.g., simplicial) ones. In this paper, we consider the spectral dimension of quantum states of spatial geometry defined on combinatorial complexes endowed with additional algebraic data: the kinematical quantum states of loop quantum gravity (LQG). Preliminarily, the effects of topology and discreteness of classical discrete geometries are studied in a systematic manner. We look for states reproducing the spectral dimension of a classical space in the appropriate regime. We also test the hypothesis that in LQG, as in other approaches, there is a scale dependence of the spectral dimension, which runs from the topological dimension at large scales to a smaller one at short distances. While our results do not give any strong support to this hypothesis, we can however pinpoint when the topological dimension is reproduced by LQG quantum states. Overall, by exploring the interplay of combinatorial, topological and geometrical effects, and by considering various kinds of quantum states such as coherent states and their superpositions, we find that the spectral dimension of discrete quantum geometries is more sensitive to the underlying combinatorial structures than to the details of the additional data associated with them. (paper)

  20. Piecewise spectrally band-pass for compressive coded aperture spectral imaging

    International Nuclear Information System (INIS)

    Qian Lu-Lu; Lü Qun-Bo; Huang Min; Xiang Li-Bin

    2015-01-01

    Coded aperture snapshot spectral imaging (CASSI) has been discussed in recent years. It has the remarkable advantages of high optical throughput, snapshot imaging, etc. The entire spatial-spectral data-cube can be reconstructed with just a single two-dimensional (2D) compressive sensing measurement. On the other hand, for less spectrally sparse scenes, the insufficiency of sparse sampling and aliasing in spatial-spectral images reduce the accuracy of reconstructed three-dimensional (3D) spectral cube. To solve this problem, this paper extends the improved CASSI. A band-pass filter array is mounted on the coded mask, and then the first image plane is divided into some continuous spectral sub-band areas. The entire 3D spectral cube could be captured by the relative movement between the object and the instrument. The principle analysis and imaging simulation are presented. Compared with peak signal-to-noise ratio (PSNR) and the information entropy of the reconstructed images at different numbers of spectral sub-band areas, the reconstructed 3D spectral cube reveals an observable improvement in the reconstruction fidelity, with an increase in the number of the sub-bands and a simultaneous decrease in the number of spectral channels of each sub-band. (paper)

  1. High-latitude tree growth and satellite vegetation indices: Correlations and trends in Russia and Canada (1982-2008)

    Science.gov (United States)

    Berner, Logan T.; Beck, Pieter S. A.; Bunn, Andrew G.; Lloyd, Andrea H.; Goetz, Scott J.

    2011-03-01

    Vegetation in northern high latitudes affects regional and global climate through energy partitioning and carbon storage. Spaceborne observations of vegetation, largely based on the normalized difference vegetation index (NDVI), suggest decreased productivity during recent decades in many regions of the Eurasian and North American boreal forests. To improve interpretation of NDVI trends over forest regions, we examined the relationship between NDVI from the advanced very high resolution radiometers and tree ring width measurements, a proxy of tree productivity. We collected tree core samples from spruce, pine, and larch at 22 sites in northeast Russia and northwest Canada. Annual growth rings were measured and used to generate site-level ring width index (RWI) chronologies. Correlation analysis was used to assess the association between RWI and summer NDVI from 1982 to 2008, while linear regression was used to examine trends in both measurements. The correlation between NDVI and RWI was highly variable across sites, though consistently positive (r = 0.43, SD = 0.19, n = 27). We observed significant temporal autocorrelation in both NDVI and RWI measurements at sites with evergreen conifers (spruce and pine), though weak autocorrelation at sites with deciduous conifers (larch). No sites exhibited a positive trend in both NDVI and RWI, although five sites showed negative trends in both measurements. While there are technological and physiological limitations to this approach, these findings demonstrate a positive association between NDVI and tree ring measurements, as well as the importance of considering lagged effects when modeling vegetation productivity using satellite data.

  2. Investigation into robust spectral indices for leaf chlorophyll estimation

    CSIR Research Space (South Africa)

    Main, R

    2011-11-01

    Full Text Available remote sensing data, new users are faced with a plethora of options when choosing an optical index to relate to their chosen or canopy parameter. The literature base regarding optical indices (particularly chlorophyll indices) is wide ranging...

  3. Measuring Identification and Quantification Errors in Spectral CT Material Decomposition

    Directory of Open Access Journals (Sweden)

    Aamir Younis Raja

    2018-03-01

    Full Text Available Material decomposition methods are used to identify and quantify multiple tissue components in spectral CT but there is no published method to quantify the misidentification of materials. This paper describes a new method for assessing misidentification and mis-quantification in spectral CT. We scanned a phantom containing gadolinium (1, 2, 4, 8 mg/mL, hydroxyapatite (54.3, 211.7, 808.5 mg/mL, water and vegetable oil using a MARS spectral scanner equipped with a poly-energetic X-ray source operated at 118 kVp and a CdTe Medipix3RX camera. Two imaging protocols were used; both with and without 0.375 mm external brass filter. A proprietary material decomposition method identified voxels as gadolinium, hydroxyapatite, lipid or water. Sensitivity and specificity information was used to evaluate material misidentification. Biological samples were also scanned. There were marked differences in identification and quantification between the two protocols even though spectral and linear correlation of gadolinium and hydroxyapatite in the reconstructed images was high and no qualitative segmentation differences in the material decomposed images were observed. At 8 mg/mL, gadolinium was correctly identified for both protocols, but concentration was underestimated by over half for the unfiltered protocol. At 1 mg/mL, gadolinium was misidentified in 38% of voxels for the filtered protocol and 58% of voxels for the unfiltered protocol. Hydroxyapatite was correctly identified at the two higher concentrations for both protocols, but mis-quantified for the unfiltered protocol. Gadolinium concentration as measured in the biological specimen showed a two-fold difference between protocols. In future, this methodology could be used to compare and optimize scanning protocols, image reconstruction methods, and methods for material differentiation in spectral CT.

  4. A morphometric analysis of vegetation patterns in dryland ecosystems

    Science.gov (United States)

    Mander, Luke; Dekker, Stefan C.; Li, Mao; Mio, Washington; Punyasena, Surangi W.; Lenton, Timothy M.

    2017-02-01

    Vegetation in dryland ecosystems often forms remarkable spatial patterns. These range from regular bands of vegetation alternating with bare ground, to vegetated spots and labyrinths, to regular gaps of bare ground within an otherwise continuous expanse of vegetation. It has been suggested that spotted vegetation patterns could indicate that collapse into a bare ground state is imminent, and the morphology of spatial vegetation patterns, therefore, represents a potentially valuable source of information on the proximity of regime shifts in dryland ecosystems. In this paper, we have developed quantitative methods to characterize the morphology of spatial patterns in dryland vegetation. Our approach is based on algorithmic techniques that have been used to classify pollen grains on the basis of textural patterning, and involves constructing feature vectors to quantify the shapes formed by vegetation patterns. We have analysed images of patterned vegetation produced by a computational model and a small set of satellite images from South Kordofan (South Sudan), which illustrates that our methods are applicable to both simulated and real-world data. Our approach provides a means of quantifying patterns that are frequently described using qualitative terminology, and could be used to classify vegetation patterns in large-scale satellite surveys of dryland ecosystems.

  5. Effects of Telecoupling on Global Vegetation Dynamics

    Science.gov (United States)

    Viña, A.; Liu, J.

    2016-12-01

    With the ever increasing trend in telecoupling processes, such as international trade, all countries around the world are becoming more interdependent. However, the effects of this growing interdependence on vegetation (e.g., shifts in the geographic extent and distribution) remain unknown even though vegetation dynamics are crucially important for food production, carbon sequestration, provision of other ecosystem services, and biodiversity conservation. In this study we evaluate the effects of international trade on the spatio-temporal trajectories of vegetation at national and global scales, using vegetation index imagery collected over more than three decades by the Advanced Very High Resolution Radiometer (AVHRR) satellite sensor series together with concurrent national and international data on international trade (and its associated movement of people, goods, services and information). The spatio-temporal trajectories of vegetation are obtained using the scale of fluctuation technique, which is based on the decomposition of the AVHRR image time series to obtain information on its spatial dependence structure over time. Similar to the correlation length, the scale of fluctuation corresponds to the range over which fluctuations in the vegetation index are spatially correlated. Results indicate that global vegetation has changed drastically over the last three decades. These changes are not uniform across space, with hotspots in active trading countries. This study not only has direct implications for understanding global vegetation dynamics, but also sheds important insights on the complexity of human-nature interactions across telecoupled systems.

  6. ULTRAVIOLET RAMAN SPECTRAL SIGNATURE ACQUISITION: UV RAMAN SPECTRAL FINGERPRINTS.

    Energy Technology Data Exchange (ETDEWEB)

    SEDLACEK,III, A.J.FINFROCK,C.

    2002-09-01

    As a member of the science-support part of the ITT-lead LISA development program, BNL is tasked with the acquisition of UV Raman spectral fingerprints and associated scattering cross-sections for those chemicals-of-interest to the program's sponsor. In support of this role, the present report contains the first installment of UV Raman spectral fingerprint data on the initial subset of chemicals. Because of the unique nature associated with the acquisition of spectral fingerprints for use in spectral pattern matching algorithms (i.e., CLS, PLS, ANN) great care has been undertaken to maximize the signal-to-noise and to minimize unnecessary spectral subtractions, in an effort to provide the highest quality spectral fingerprints. This report is divided into 4 sections. The first is an Experimental section that outlines how the Raman spectra are performed. This is then followed by a section on Sample Handling. Following this, the spectral fingerprints are presented in the Results section where the data reduction process is outlined. Finally, a Photographs section is included.

  7. Multi-Spectral Imaging from an Unmanned Aerial Vehicle Enables the Assessment of Seasonal Leaf Area Dynamics of Sorghum Breeding Lines

    Directory of Open Access Journals (Sweden)

    Andries B. Potgieter

    2017-09-01

    Full Text Available Genetic improvement in sorghum breeding programs requires the assessment of adaptation traits in small-plot breeding trials across multiple environments. Many of these phenotypic assessments are made by manual measurement or visual scoring, both of which are time consuming and expensive. This limits trial size and the potential for genetic gain. In addition, these methods are typically restricted to point estimates of particular traits, such as leaf senescence or flowering and do not capture the dynamic nature of crop growth. In water-limited environments in particular, information on leaf area development over time would provide valuable insight into water use and adaptation to water scarcity during specific phenological stages of crop development. Current methods to estimate plant leaf area index (LAI involve destructive sampling and are not practical in breeding. Unmanned aerial vehicles (UAV and proximal-sensing technologies open new opportunities to assess these traits multiple times in large small-plot trials. We analyzed vegetation-specific crop indices obtained from a narrowband multi-spectral camera on board a UAV platform flown over a small pilot trial with 30 plots (10 genotypes randomized within 3 blocks. Due to variable emergence we were able to assess the utility of these vegetation indices to estimate canopy cover and LAI over a large range of plant densities. We found good correlations between the Normalized Difference Vegetation Index (NDVI and the Enhanced Vegetation Index (EVI with plant number per plot, canopy cover and LAI both during the vegetative growth phase (pre-anthesis and at maximum canopy cover shortly after anthesis. We also analyzed the utility of time-sequence data to assess the senescence pattern of sorghum genotypes known as fast (senescent or slow senescing (stay-green types. The Normalized Difference Red Edge (NDRE index which estimates leaf chlorophyll content was most useful in characterizing the leaf area

  8. Mineral composition of non-conventional leafy vegetables.

    Science.gov (United States)

    Barminas, J T; Charles, M; Emmanuel, D

    1998-01-01

    Six non-conventional leafy vegetables consumed largely by the rural populace of Nigeria were analyzed for mineral composition. Mineral contents appeared to be dependent on the type of vegetables. Amaranthus spinosus and Adansonia digitata leaves contained the highest level of iron (38.4 mg/100 g and 30.6 mg/100 g dw, respectively). These values are low compared to those for common Nigerian vegetables but higher than those for other food sources. All the vegetables contained high levels of calcium compared to common vegetables, thus they could be a rich source of this mineral. Microelement content of the leaves varied appreciably. Zinc content was highest in Moringa oleifera, Adansonia digitata and Cassia tora leaves (25.5 mg/100 g, 22.4 mg/100 g and 20.9 mg/100 g dw, respectively) while the manganese content was comparatively higher in Colocasia esculenta. The concentrations of the mineral elements in the vegetables per serving portion are presented and these values indicate that the local vegetables could be valuable and important contributors in the diets of the rural and urban people of Nigeria. The mean daily intake of P, Mg, Ca, Fe, Cu and Zn were lower than their recommended dietary allowances (RDAs). However, the manganese daily intake was found not to differ significantly (p = 0.05) from the RDA value.

  9. Transfer of 137Cs to wild vegetables

    International Nuclear Information System (INIS)

    Ito, Nobuhiko; Natsuhori, Masahiro; Mezawa, Akane; Kawakami, Akira

    1998-01-01

    For the evaluation of internal radiation dose, it is needed to estimate the amount of radionuclide incorporated to human body using a simulation model. 137 Cesium (Cs) is easily transferred associating with food intake as well as potassium and so, Cs is an important nuclide for evaluation of internal radiation. 137 Cs concentrations in wild vegetables are higher than those of cultured vegetables and milk. Therefore, the transfer coefficients of 137 Cs from soil to wild vegetables were estimated in this study. Wild vegetables and soils of their farms were collected in the Hakkoda Mountain range of Aomori Prefecture. The levels of 137 Cs in wild vegetables were 0.42-18.35 (Bq/kg), whereas those in cabbage and spinach were 0.08 and 0.01 (Bq/kg), respectively, indicating that the Cs level is dozens to several hundreds times higher in wild vegetables than cultured ones. And the transfer coefficient was estimated as 0.003-0.94 for the former and 0.001-0.8 for the latter. On the other hand, 1 37 Cs levels of the soils on which wild vegetables grew was 28.0 Bq/kg and it was 3.9 Bq/kg for the farm soil. Furthermore, the effects of water content and pH of the soil on the transfer coefficient were studied. (M.N.)

  10. Integrated analysis of climate, soil, topography and vegetative growth in Iberian viticultural regions.

    Directory of Open Access Journals (Sweden)

    Helder Fraga

    Full Text Available The Iberian viticultural regions are convened according to the Denomination of Origin (DO and present different climates, soils, topography and management practices. All these elements influence the vegetative growth of different varieties throughout the peninsula, and are tied to grape quality and wine type. In the current study, an integrated analysis of climate, soil, topography and vegetative growth was performed for the Iberian DO regions, using state-of-the-art datasets. For climatic assessment, a categorized index, accounting for phenological/thermal development, water availability and grape ripening conditions was computed. Soil textural classes were established to distinguish soil types. Elevation and aspect (orientation were also taken into account, as the leading topographic elements. A spectral vegetation index was used to assess grapevine vegetative growth and an integrated analysis of all variables was performed. The results showed that the integrated climate-soil-topography influence on vine performance is evident. Most Iberian vineyards are grown in temperate dry climates with loamy soils, presenting low vegetative growth. Vineyards in temperate humid conditions tend to show higher vegetative growth. Conversely, in cooler/warmer climates, lower vigour vineyards prevail and other factors, such as soil type and precipitation acquire more important roles in driving vigour. Vines in prevailing loamy soils are grown over a wide climatic diversity, suggesting that precipitation is the primary factor influencing vigour. The present assessment of terroir characteristics allows direct comparison among wine regions and may have great value to viticulturists, particularly under a changing climate.

  11. Estimating urban vegetation fraction across 25 cities in pan-Pacific using Landsat time series data

    Science.gov (United States)

    Lu, Yuhao; Coops, Nicholas C.; Hermosilla, Txomin

    2017-04-01

    Urbanization globally is consistently reshaping the natural landscape to accommodate the growing human population. Urban vegetation plays a key role in moderating environmental impacts caused by urbanization and is critically important for local economic, social and cultural development. The differing patterns of human population growth, varying urban structures and development stages, results in highly varied spatial and temporal vegetation patterns particularly in the pan-Pacific region which has some of the fastest urbanization rates globally. Yet spatially-explicit temporal information on the amount and change of urban vegetation is rarely documented particularly in less developed nations. Remote sensing offers an exceptional data source and a unique perspective to map urban vegetation and change due to its consistency and ubiquitous nature. In this research, we assess the vegetation fractions of 25 cities across 12 pan-Pacific countries using annual gap-free Landsat surface reflectance products acquired from 1984 to 2012, using sub-pixel, spectral unmixing approaches. Vegetation change trends were then analyzed using Mann-Kendall statistics and Theil-Sen slope estimators. Unmixing results successfully mapped urban vegetation for pixels located in urban parks, forested mountainous regions, as well as agricultural land (correlation coefficient ranging from 0.66 to 0.77). The greatest vegetation loss from 1984 to 2012 was found in Shanghai, Tianjin, and Dalian in China. In contrast, cities including Vancouver (Canada) and Seattle (USA) showed stable vegetation trends through time. Using temporal trend analysis, our results suggest that it is possible to reduce noise and outliers caused by phenological changes particularly in cropland using dense new Landsat time series approaches. We conclude that simple yet effective approaches of unmixing Landsat time series data for assessing spatial and temporal changes of urban vegetation at regional scales can provide

  12. Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery

    Science.gov (United States)

    Navarro, Gabriel; Caballero, Isabel; Silva, Gustavo; Parra, Pedro-Cecilio; Vázquez, Águeda; Caldeira, Rui

    2017-06-01

    A forest fire started on August 8th, 2016 in several places on Madeira Island causing damage and casualties. As of August 10th the local media had reported the death of three people, over 200 people injured, over 950 habitants evacuated, and 50 houses damaged. This study presents the preliminary results of the assessment of several spectral indices to evaluate the burn severity of Madeira fires during August 2016. These spectral indices were calculated using the new European satellite Sentinel-2A launched in June 2015. The study confirmed the advantages of several spectral indices such as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVIreXn) using red-edge spectral bands to assess the post-fire conditions. Results showed high correlation between NDVI, GNDVI, NBR and NDVIre1n spectral indices and the analysis performed by Copernicus Emergency Management Service (EMSR175), considered as the reference truth. Regarding the red-edge spectral indices, the NDVIre1n (using band B5, 705 nm) presented better results compared with B6 (740 nm) and B7 (783 nm) bands. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for post-fire monitoring. In the future, the two twin Sentinel-2 satellites will offer global coverage of the Madeira Archipelago every five days, therefore allowing the simultaneous study of the evolution of the burnt area and reforestation information with high spatial (up to 10 m) and temporal resolution (5 days).

  13. Remote Sensing of Submerged Aquatic Vegetation in a Shallow Non-Turbid River Using an Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Kyle F. Flynn

    2014-12-01

    Full Text Available A passive method for remote sensing of the nuisance green algae Cladophora glomerata in rivers is presented using an unmanned aerial vehicle (UAV. Included are methods for UAV operation, lens distortion correction, image georeferencing, and spectral analysis to support algal cover mapping. Eighteen aerial photography missions were conducted over the summer of 2013 using an off-the-shelf UAV and three-band, wide-angle, red, green, and blue (RGB digital camera sensor. Images were post-processed, mosaicked, and georeferenced so automated classification and mapping could be completed. An adaptive cosine estimator (ACE and spectral angle mapper (SAM algorithm were used to complete the algal identification. Digital analysis of optical imagery correctly identified filamentous algae and background coverage 90% and 92% of the time, and tau coefficients were 0.82 and 0.84 for ACE and SAM, respectively. Thereafter, algal cover was characterized for a one-kilometer channel segment during each of the 18 UAV flights. Percent cover ranged from <5% to >50%, and increased immediately after vernal freshet, peaked in midsummer, and declined in the fall. Results indicate that optical remote sensing with UAV holds promise for completing spatially precise, and multi-temporal measurements of algae or submerged aquatic vegetation in shallow rivers with low turbidity and good optical transmission.

  14. Temporal analysis of vegetation indices related to biophysical parameters using Sentinel 2A images to estimate maize production

    Science.gov (United States)

    Macedo, Lucas Saran; Kawakubo, Fernando Shinji

    2017-10-01

    Agricultural production is one of the most important Brazilian economic activities accounting for about 21,5% of total Gross Domestic Product. In this scenario, the use of satellite images for estimating biophysical parameters along the phenological development of agricultural crops allows the conclusion about the sanity of planting and helps the projection on design production trends. The objective of this study is to analyze the temporal patterns and variation of six vegetion indexes obtained from the bands of Sentinel 2A satellite, associated with greenness (NDVI and ClRE), senescence (mARI and PSRI) and water content (DSWI and NDWI) to estimate maize production. The temporal pattern of the indices was analyzed in function of productivity data collected in-situ. The results obtained evidenced the importance of the SWIR and Red Edge ranges with Pearson correlation values of the temporal mean for NDWI 0.88 and 0.76 for CLRE.

  15. Decomposition of vegetation growing on metal mine waste

    Energy Technology Data Exchange (ETDEWEB)

    Williams, S T; McNeilly, T; Wellington, E M.H.

    1977-01-01

    Aspects of the decomposition of metal tolerant vegetation growing on mine waste containing high concentrations of lead and zinc were studied and compared with those on an adjacent uncontaminated site. High concentrations of Pb and, to a lesser extent, Zn, accumulated in metal-tolerant grass. Retarded decomposition of this vegetation as compared with that on the uncontaminated site was indicated by a greater accumulation of litter, less humus formation, reduced soil urease activity and smaller microbial and microfaunal populations. Some evidence for increased metal tolerance in microbes from the mine waste was obtained. Concentrations of lead tolerated under laboratory conditions were much lower than those extracted from the mine waste and its vegetation, probably due to the lack of an accurate method for assessing the availability of lead in soil and vegetation.

  16. Effects of Vegetables on Cardiovascular Diseases and Related Mechanisms

    Directory of Open Access Journals (Sweden)

    Guo-Yi Tang

    2017-08-01

    Full Text Available Epidemiological studies have shown that vegetable consumption is inversely related to the risk of cardiovascular diseases. Moreover, research has indicated that many vegetables like potatoes, soybeans, sesame, tomatoes, dioscorea, onions, celery, broccoli, lettuce and asparagus showed great potential in preventing and treating cardiovascular diseases, and vitamins, essential elements, dietary fibers, botanic proteins and phytochemicals were bioactive components. The cardioprotective effects of vegetables might involve antioxidation; anti-inflammation; anti-platelet; regulating blood pressure, blood glucose, and lipid profile; attenuating myocardial damage; and modulating relevant enzyme activities, gene expression, and signaling pathways as well as some other biomarkers associated to cardiovascular diseases. In addition, several vegetables and their bioactive components have been proven to protect against cardiovascular diseases in clinical trials. In this review, we analyze and summarize the effects of vegetables on cardiovascular diseases based on epidemiological studies, experimental research, and clinical trials, which are significant to the application of vegetables in prevention and treatment of cardiovascular diseases.

  17. Fruits, vegetables, 100% juices, and cognitive function.

    Science.gov (United States)

    Lamport, Daniel J; Saunders, Caroline; Butler, Laurie T; Spencer, Jeremy Pe

    2014-12-01

    Although reviews of the association between polyphenol intake and cognition exist, research examining the cognitive effects of fruit, vegetable, and juice consumption across epidemiological and intervention studies has not been previously examined. For the present review, critical inclusion criteria were human participants, a measure of fruit, vegetable, or 100% juice consumption, an objective measure of cognitive function, and a clinical diagnosis of neuropsychological disease. Studies were excluded if consumption of fruits, vegetables, or juice was not assessed in isolation from other food groups, or if there was no statistical control for education or IQ. Seventeen of 19 epidemiological studies and 3 of 6 intervention studies reported significant benefits of fruit, vegetable, or juice consumption for cognitive performance. The data suggest that chronic consumption of fruits, vegetables, and juices is beneficial for cognition in healthy older adults. The limited data from acute interventions indicate that consumption of fruit juices can have immediate benefits for memory function in adults with mild cognitive impairment; however, as of yet, acute benefits have not been observed in healthy adults. Conclusions regarding an optimum dietary intake for fruits, vegetables, and juices are difficult to quantify because of substantial heterogeneity in the categorization of consumption of these foods. © 2014 International Life Sciences Institute.

  18. Comparison of Methods for Estimating Fractional Cover of Photosynthetic and Non-Photosynthetic Vegetation in the Otindag Sandy Land Using GF-1 Wide-Field View Data

    OpenAIRE

    Xiaosong Li; Guoxiong Zheng; Jinying Wang; Cuicui Ji; Bin Sun; Zhihai Gao

    2016-01-01

    Photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) are important ground cover types for desertification monitoring and land management. Hyperspectral remote sensing has been proven effective for separating NPV from bare soil, but few studies determined fractional cover of PV (fpv) and NPV (fnpv) using multispectral information. The purpose of this study is to evaluate several spectral unmixing approaches for retrieval of fpv and fnpv in the Otindag Sandy Land using GF-1 wi...

  19. VEGETATION MAPPING IN WETLANDS

    Directory of Open Access Journals (Sweden)

    F. PEDROTTI

    2004-01-01

    Full Text Available The current work examines the main aspects of wetland vegetation mapping, which can be summarized as analysis of the ecological-vegetational (ecotone gradients; vegetation complexes; relationships between vegetation distribution and geomorphology; vegetation of the hydrographic basin lo which the wetland in question belongs; vegetation monitoring with help of four vegetation maps: phytosociological map of the real and potential vegetation, map of vegetation dynamical tendencies, map of vegetation series.

  20. Australian consumer awareness of health benefits associated with vegetable consumption.

    Science.gov (United States)

    Rekhy, Reetica; Khan, Aila; Eason, Jocelyn; Mactavish-West, Hazel; Lister, Carolyn; Mcconchie, Robyn

    2017-04-01

    The present study investigated the perceived health benefits of specific vegetable consumption to guide the use of nutrition and health claims on vegetable marketing collateral. Free elicitation and consumer ranking data were collected through an online survey of 1000 adults from across Australia and analysed for the perceived importance of vegetables in the daily diet, number of serves consumed per day, knowledge about health-related benefits of specific vegetables and perceived health benefits of vegetable consumption. The importance of vegetables in the diet and daily vegetable consumption was higher in people from an English-speaking background, females, people aged 45 years and over and people living in non-metropolitan areas. Digestion was selected as the major health benefit from consumption of specific vegetables. However, understanding of the health benefits of specific vegetable consumption was relatively low among consumers. Half of the respondents were not sure of the health benefits associated with specific vegetables, except for carrots and spinach. Some respondents volunteered nutrient content or other information. There was no clear indication that consumers understand the specific health benefits conferred by consumption of vegetables. Nutrient and health benefit labelling therefore has the capacity to enhance knowledge of vegetable consumers. It is recommended that health benefit labelling be tailored to promote greater consumption of vegetables in those demographic groups where vegetable consumption was lower. The present study assists the Australian vegetable industry in helping consumers make more informed consumption choices. © 2016 Dietitians Association of Australia.

  1. Identification of acetates in elasmopalpulus lignosellus pheromone glands using a newly created mass spectral database and kóvats retention indices

    Directory of Open Access Journals (Sweden)

    Gulab N. Jham

    2007-08-01

    Full Text Available Based on a specially created mass spectral database utilizing 23 tetradecenyl and 22 hexadecenyl acetate standards along with Kóvats retention indices obtained on a very polar stationary phase [poly (biscyanopropyl siloxane] (SP 2340, (Z-9-hexadecenyl acetate, (Z-11-hexadecenyl acetate and (E-8-hexadecenyl acetate were identified in active pheromone extracts of Elasmopalpus lignosellus. This identification was more efficient than our previous study using gas chromatography/mass spectrometry with a dimethyl disulfide derivative where we could only identify the first two acetates. The acetate composition of the pheromone gland differed from region to region in Brazil and from that from the Tifton (GA, USA population, suggesting polymorphism or a different sub-species.

  2. Modeling minimum temperature using adaptive neuro-fuzzy inference system based on spectral analysis of climate indices: A case study in Iran

    Directory of Open Access Journals (Sweden)

    Hojatollah Daneshmand

    2015-01-01

    Full Text Available Nowadays, a lot of attention is paid to the application of intelligent systems in predicting natural phenomena. Artificial neural network systems, fuzzy logic, and adaptive neuro-fuzzy inference are used in this field. Daily minimum temperature of the meteorology station of the city of Mashhad, in northeast of Iran, in a 42-year statistical period, 1966-2008, has been received from the Iranian meteorological organization. Adaptive neuro-fuzzy inference system is used for modeling and forecasting the monthly minimum temperature. To find appropriate inputs, three approaches, i.e. spectral analysis, correlation coefficient, and the knowledge of experts,are used. By applying fast Fourier transform to the parameter of monthly minimum temperature and climate indices, and by using correlation coefficient and the knowledge of experts, 3 indices, Nino 1 + 2, NP, and PNA, are selected as model inputs. A hybrid training algorithm is used to train the system. According to simulation results, a correlation coefficient of 0.987 between the observed values and the predicted values, as well as amean absolute percentage deviations of 27.6% indicate an acceptable estimation of the model.

  3. Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States

    Science.gov (United States)

    Prabhakara, Kusuma; Hively, W. Dean; McCarty, Gregory W.

    2015-07-01

    Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012-2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r2 = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r2 = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.

  4. Remote sensing of aquatic vegetation distribution in Taihu Lake using an improved classification tree with modified thresholds.

    Science.gov (United States)

    Zhao, Dehua; Jiang, Hao; Yang, Tangwu; Cai, Ying; Xu, Delin; An, Shuqing

    2012-03-01

    Classification trees (CT) have been used successfully in the past to classify aquatic vegetation from spectral indices (SI) obtained from remotely-sensed images. However, applying CT models developed for certain image dates to other time periods within the same year or among different years can reduce the classification accuracy. In this study, we developed CT models with modified thresholds using extreme SI values (CT(m)) to improve the stability of the models when applying them to different time periods. A total of 903 ground-truth samples were obtained in September of 2009 and 2010 and classified as emergent, floating-leaf, or submerged vegetation or other cover types. Classification trees were developed for 2009 (Model-09) and 2010 (Model-10) using field samples and a combination of two images from winter and summer. Overall accuracies of these models were 92.8% and 94.9%, respectively, which confirmed the ability of CT analysis to map aquatic vegetation in Taihu Lake. However, Model-10 had only 58.9-71.6% classification accuracy and 31.1-58.3% agreement (i.e., pixels classified the same in the two maps) for aquatic vegetation when it was applied to image pairs from both a different time period in 2010 and a similar time period in 2009. We developed a method to estimate the effects of extrinsic (EF) and intrinsic (IF) factors on model uncertainty using Modis images. Results indicated that 71.1% of the instability in classification between time periods was due to EF, which might include changes in atmospheric conditions, sun-view angle and water quality. The remainder was due to IF, such as phenological and growth status differences between time periods. The modified version of Model-10 (i.e. CT(m)) performed better than traditional CT with different image dates. When applied to 2009 images, the CT(m) version of Model-10 had very similar thresholds and performance as Model-09, with overall accuracies of 92.8% and 90.5% for Model-09 and the CT(m) version of Model

  5. Nightside studies of coherent HF Radar spectral width behaviour

    Directory of Open Access Journals (Sweden)

    E. E. Woodfield

    2002-09-01

    Full Text Available A previous case study found a relationship between high spectral width measured by the CUTLASS Finland HF radar and elevated electron temperatures observed by the EISCAT and ESR incoherent scatter radars in the post-midnight sector of magnetic local time. This paper expands that work by briefly re-examining that interval and looking in depth at two further case studies. In all three cases a region of high HF spectral width (>200 ms-1 exists poleward of a region of low HF spectral width (<200 ms-1. Each case, however, occurs under quite different geomagnetic conditions. The original case study occurred during an interval with no observed electrojet activity, the second study during a transition from quiet to active conditions with a clear band of ion frictional heating indicating the location of the flow reversal boundary, and the third during an isolated sub-storm. These case studies indicate that the relationship between elevated electron temperature and high HF radar spectral width appears on closed field lines after 03:00 magnetic local time (MLT on the nightside. It is not clear whether the same relationship would hold on open field lines, since our analysis of this relationship is restricted in latitude. We find two important properties of high spectral width data on the nightside. Firstly the high spectral width values occur on both open and closed field lines, and secondly that the power spectra which exhibit high widths are both single-peak and multiple-peak. In general the regions of high spectral width (>200 ms-1 have more multiple-peak spectra than the regions of low spectral widths whilst still maintaining a majority of single-peak spectra. We also find that the region of ion frictional heating is collocated with many multiple-peak HF spectra. Several mechanisms for the generation of high spectral width have been proposed which would produce multiple-peak spectra, these are discussed in relation to the data presented here. Since the

  6. Nightside studies of coherent HF Radar spectral width behaviour

    Directory of Open Access Journals (Sweden)

    E. E. Woodfield

    Full Text Available A previous case study found a relationship between high spectral width measured by the CUTLASS Finland HF radar and elevated electron temperatures observed by the EISCAT and ESR incoherent scatter radars in the post-midnight sector of magnetic local time. This paper expands that work by briefly re-examining that interval and looking in depth at two further case studies. In all three cases a region of high HF spectral width (>200 ms-1 exists poleward of a region of low HF spectral width (<200 ms-1. Each case, however, occurs under quite different geomagnetic conditions. The original case study occurred during an interval with no observed electrojet activity, the second study during a transition from quiet to active conditions with a clear band of ion frictional heating indicating the location of the flow reversal boundary, and the third during an isolated sub-storm. These case studies indicate that the relationship between elevated electron temperature and high HF radar spectral width appears on closed field lines after 03:00 magnetic local time (MLT on the nightside. It is not clear whether the same relationship would hold on open field lines, since our analysis of this relationship is restricted in latitude. We find two important properties of high spectral width data on the nightside. Firstly the high spectral width values occur on both open and closed field lines, and secondly that the power spectra which exhibit high widths are both single-peak and multiple-peak. In general the regions of high spectral width (>200 ms-1 have more multiple-peak spectra than the regions of low spectral widths whilst still maintaining a majority of single-peak spectra. We also find that the region of ion frictional heating is collocated with many multiple-peak HF spectra. Several mechanisms for the generation of high spectral width have been proposed which would produce multiple-peak spectra, these are discussed in relation to

  7. Relationship between channel interaction and spectral-ripple discrimination in cochlear implant users.

    Science.gov (United States)

    Jones, Gary L; Won, Jong Ho; Drennan, Ward R; Rubinstein, Jay T

    2013-01-01

    Cochlear implant (CI) users can achieve remarkable speech understanding, but there is great variability in outcomes that is only partially accounted for by age, residual hearing, and duration of deafness. Results might be improved with the use of psychophysical tests to predict which sound processing strategies offer the best potential outcomes. In particular, the spectral-ripple discrimination test offers a time-efficient, nonlinguistic measure that is correlated with perception of both speech and music by CI users. Features that make this "one-point" test time-efficient, and thus potentially clinically useful, are also connected to controversy within the CI field about what the test measures. The current work examined the relationship between thresholds in the one-point spectral-ripple test, in which stimuli are presented acoustically, and interaction indices measured under the controlled conditions afforded by direct stimulation with a research processor. Results of these studies include the following: (1) within individual subjects there were large variations in the interaction index along the electrode array, (2) interaction indices generally decreased with increasing electrode separation, and (3) spectral-ripple discrimination improved with decreasing mean interaction index at electrode separations of one, three, and five electrodes. These results indicate that spectral-ripple discrimination thresholds can provide a useful metric of the spectral resolution of CI users.

  8. Spatial relationship between climatologies and changes in global vegetation activity.

    Science.gov (United States)

    de Jong, Rogier; Schaepman, Michael E; Furrer, Reinhard; de Bruin, Sytze; Verburg, Peter H

    2013-06-01

    Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982-2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate-associated effects and a spatially correlated field representing the combined influence of other factors, including land-use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large-scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land-cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology). © 2013 Blackwell Publishing Ltd.

  9. GREENHOUSE PLASTIC FILMS CAPABLE OF MODIFYING THE SPECTRAL DISTRIBUTION OF SOLAR RADIATION

    Directory of Open Access Journals (Sweden)

    Evelia Schettini

    2010-03-01

    Full Text Available The aim of this paper was to investigate the radiometric properties of innovative covering films for protected cultivation capable of modifying the spectral distribution of the transmitted radiation and thus the vegetative activity. Two photoselective films, three photoluminescent films and one low-density polyethylene film were used as greenhouse coverings for cherry trees and peach trees, grown in pots. The photoselective films were characterised by a reduction of the R/FR ratio in comparison to the natural solar radiation. Tree growth parameters, such as the apical shoot of cherry trees and the shoot of peach trees, were monitored. Different responses to vegetative activities were observed under the films, depending on the species, with a higher shoots growth rate in the peach with respect to the cherry. The photoselective film characterised by the lowest R/FR ratio significantly enhanced the growth of cherry and peach trees in comparison to the trees cultivated under the other greenhouse films

  10. Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change.

    Directory of Open Access Journals (Sweden)

    Antonius G T Schut

    Full Text Available Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010 derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity.

  11. Vegetation dynamics and dynamic vegetation science

    NARCIS (Netherlands)

    Van der Maarel, E

    1996-01-01

    his contribution presents a review of the development of the study of vegetation dynamics since 1979, in the framework of a jubilee meeting on progress in the study of vegetation. However, an exhaustive review is both impossible and unnecessary. It is impossible within the few pages available

  12. Study on the air quality near vegetation along the highway

    International Nuclear Information System (INIS)

    Weijers, E.P.; Kos, G.P.A.; Van den Bulk, W.C.M.; Vermeulen, A.T.

    2007-08-01

    The results of downwind measurements of air quality around vegetation near a motorway are presented and discussed. The study (first ever in the Netherlands) was performed by order of the Innovation Programme Air Quality. At a carefully selected location measurements of PM and NOx were carried out downwind from a motorway in front of and (at various distances) behind a parallel orientated vegetation strip. Results are compared with synchronized data collected at a nearby location without vegetation (the 'reference' situation) and at the same distances from the motorway. Major findings are: Comparing measurements in front of and behind the vegetation strip show that the presence of vegetation tends to lower PM10 and PM2.5 concentrations immediately behind the vegetation. However, no such change is apparent in the concentrations of NO and NO2. The comparison with measurements executed without vegetation ('reference') indicate that concentration levels close to the vegetation strip are similar or somewhat higher. At a larger distance from motorway and vegetation (>30 m) NO and NO2 concentrations tend to be lower than what is observed in the reference situation. This could not be determined for PM [nl

  13. Vegetation survey: a new focus for Applied Vegetation Science

    NARCIS (Netherlands)

    Chytry, M.; Schaminee, J.H.J.; Schwabe, A.

    2011-01-01

    Vegetation survey is an important research agenda in vegetation science. It defines vegetation types and helps understand differences among them, which is essential for both basic ecological research and applications in biodiversity conservation and environmental monitoring. In this editorial, we

  14. [A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

    Science.gov (United States)

    Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

    2011-04-01

    An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

  15. Vegetation Cover based on Eagleson's Ecohydrological Optimality in Northeast China Transect (NECT)

    Science.gov (United States)

    Cong, Z.; Mo, K.; Qinshu, L.; Zhang, L.

    2016-12-01

    Vegetation is considered as the indicator of climate, thus the study of vegetation growth and distribution is of great importance to cognize the ecosystem construction and functions. Vegetation cover is used as an important index to describe vegetation conditions. In Eagleson's ecohydrological optimality, the theoretical optimal vegetation cover M* can be estimated by solving water balance equations. In this study, the theory is applied in the Northeast China Transect (NECT), one of International Geosphere-Biosphere Programs (IGBP) terrestrial transects. The spatial distribution of actual vegetation cover M, which is derived from Normalized Vegetation Index (NDVI) from Moderate-resolution Imaging Spectroradiometer (MODIS), shows that there is a significant gradient ranging from 1 in the east forests to 0 in the west desert. The result indicates that the theoretical M* fits the actual M well (for forest, M* = 0.822 while M = 0.826; for grassland, M* = 0.353 while M = 0.352; the correlation coefficient between M and M* is 0.81). The reasonable calculated proportion of water balance components further demonstrates the applicability of the ecohydrological optimality theory. M* increases with the increase of LAI, leaf angle, stem fraction and temperature, and decreases with the increase of precipitation amount. This method offers the possibility to analyze the impacts of climate change to vegetation cover quantitatively, thus providing advices for eco-restoration projects.

  16. A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

    Science.gov (United States)

    Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

    2017-12-01

    The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

  17. Particulate characterization by PIXE multivariate spectral analysis

    International Nuclear Information System (INIS)

    Antolak, Arlyn J.; Morse, Daniel H.; Grant, Patrick G.; Kotula, Paul G.; Doyle, Barney L.; Richardson, Charles B.

    2007-01-01

    Obtaining particulate compositional maps from scanned PIXE (proton-induced X-ray emission) measurements is extremely difficult due to the complexity of analyzing spectroscopic data collected with low signal-to-noise at each scan point (pixel). Multivariate spectral analysis has the potential to analyze such data sets by reducing the PIXE data to a limited number of physically realizable and easily interpretable components (that include both spectral and image information). We have adapted the AXSIA (automated expert spectral image analysis) program, originally developed by Sandia National Laboratories to quantify electron-excited X-ray spectroscopy data, for this purpose. Samples consisting of particulates with known compositions and sizes were loaded onto Mylar and paper filter substrates and analyzed by scanned micro-PIXE. The data sets were processed by AXSIA and the associated principal component spectral data were quantified by converting the weighting images into concentration maps. The results indicate automated, nonbiased, multivariate statistical analysis is useful for converting very large amounts of data into a smaller, more manageable number of compositional components needed for locating individual particles-of-interest on large area collection media

  18. Effective spectral index properties for Fermi blazars

    Science.gov (United States)

    Yang, JiangHe; Fan, JunHui; Liu, Yi; Zhang, YueLian; Tuo, ManXian; Nie, JianJun; Yuan, YuHai

    2018-05-01

    Blazars are a special subclass of active galactic nuclei with extreme observation properties. This subclass can be divided into two further subclasses of flat spectrum radio quasars (FSRQs) and BL Lacertae objects (BL Lacs) according to their emission line features. To compare the spectral properties of FSRQs and BL Lacs, the 1.4 GHz radio, optical R-band, 1 keV X-ray, and 1 GeV γ-ray flux densities for 1108 Fermi blazars are calculated to discuss the properties of the six effective spectral indices of radio to optical ( α RO), radio to X-ray ( α RX), radio to γ ray ( α Rγ), optical to X-ray ( α OX), optical to γ ray ( α Oγ), and X-ray to γ ray ( α Xγ). The main results are as follows: For the averaged effective spectral indices, \\overline {{α _{OX}}} > \\overline {{α _{Oγ }}} > \\overline {{α _{Xγ }}} > \\overline {{α _{Rγ }}} > \\overline {{α _{RX}}} > \\overline {{α _{RO}}} for samples of whole blazars and BL Lacs; \\overline {{α _{Xγ }}} ≈ \\overline {{α _{Rγ }}} ≈ \\overline {{α _{RX}}} for FSRQs and low-frequency-peaked BL Lacs (LBLs); and \\overline {{α _{OX}}} ≈ \\overline {{α _{Oγ }}} ≈ \\overline {{α _{Xγ }}} for high-synchrotron-frequency-peaked BL Lacs (HBLs). The distributions of the effective spectral indices involving optical emission ( α RO, α OX, and α Oγ) for LBLs are different from those for FSRQs, but if the effective spectral index does not involve optical emission ( α RX, α Rγ, and α Xγ), the distributions for LBLs and FSRQs almost come from the same parent population. X-ray emissions from blazars include both synchrotron and inverse Compton (IC) components; the IC component for FSRQs and LBLs accounts for a larger proportion than that for HBLs; and the radiation mechanism for LBLs is similar to that for FSRQs, but the radiation mechanism for HBLs is different from that for both FSRQs and LBLs in X-ray bands. The tendency of α Rγ decreasing from LBLs to HBLs suggests that the synchrotron self

  19. A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

    Directory of Open Access Journals (Sweden)

    Ying Cai

    2012-09-01

    Full Text Available In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT, the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3% and overall (92.0%–93.1% accuracies. Our

  20. A New Multichannel Spectral Imaging Laser Scanning Confocal Microscope

    Directory of Open Access Journals (Sweden)

    Yunhai Zhang

    2013-01-01

    Full Text Available We have developed a new multichannel spectral imaging laser scanning confocal microscope for effective detection of multiple fluorescent labeling in the research of biological tissues. In this paper, the design and key technologies of the system are introduced. Representative results on confocal imaging, 3-dimensional sectioning imaging, and spectral imaging are demonstrated. The results indicated that the system is applicable to multiple fluorescent labeling in biological experiments.

  1. Enteric Viruses in Raw Vegetables and Groundwater Used for Irrigation in South Korea▿

    Science.gov (United States)

    Cheong, Sooryun; Lee, Cheonghoon; Song, Sung Won; Choi, Weon Cheon; Lee, Chan Hee; Kim, Sang-Jong

    2009-01-01

    Raw vegetables irrigated with groundwater that may contain enteric viruses can be associated with food-borne viral disease outbreaks. In this study, we performed reverse transcription-PCR (RT-PCR) and cell culture-PCR to monitor the occurrence of enteric viruses in groundwater samples and in raw vegetables that were cultivated using that groundwater in South Korea. Samples were collected 10 times from three farms located in Gyeonggi Province, South Korea. RT-PCR and cell culture-PCR were performed to detect adenoviruses (AdVs), enteroviruses (EVs), noroviruses (NoVs), and rotaviruses, followed by sequence analyses of the detected strains. Of the 29 groundwater samples and the 30 vegetable samples, five (17%) and three (10%) were positive for enteric viruses, respectively. AdVs were the most frequently detected viruses in four groundwater and three vegetable samples. EVs and NoVs were detected in only one groundwater sample and one spinach sample, respectively. The occurrence of enteric viruses in groundwater and vegetable samples was not correlated with the water temperature and the levels of indicator bacteria, respectively. Phylogenetic analysis indicated that most of the detected AdVs were temporally distributed, irrespective of sample type. Our results indicate that raw vegetables may be contaminated with a broad range of enteric viruses, which may originate from virus-infected farmers and virus-contaminated irrigation water, and these vegetables may act as a potential vector of food-borne viral transmission. PMID:19854919

  2. Analysis of remote sensing data for evaluation of vegetation resources

    Science.gov (United States)

    1970-01-01

    Research has centered around: (1) completion of a study on the use of remote sensing techniques as an aid to multiple use management; (2) determination of the information transfer at various image resolution levels for wildland areas; and (3) determination of the value of small scale multiband, multidate photography for the analysis of vegetation resources. In addition, a substantial effort was made to upgrade the automatic image classification and spectral signature acquisition capabilities of the laboratory. It was found that: (1) Remote sensing techniques should be useful in multiple use management to provide a first-cut analysis of an area. (2) Imagery with 400-500 feet ground resolvable distance (GRD), such as that expected from ERTS-1, should allow discriminations to be made between woody vegetation, grassland, and water bodies with approximately 80% accuracy. (3) Barley and wheat acreages in Maricopa County, Arizona could be estimated with acceptable accuracies using small scale multiband, multidate photography. Sampling errors for acreages of wheat, barley, small grains (wheat and barley combined), and all cropland were 13%, 11%, 8% and 3% respectively.

  3. The role of vegetation in shaping dune morphology

    Science.gov (United States)

    Duran Vinent, O.; Moore, L. J.; Young, D.

    2012-12-01

    Aeolian dunes naturally emerge under strong winds and sufficient sand supply. They represent the most dynamical feature of the arid and/or coastal landscape and their evolution has the potential to either increase desertification or reduce coastal vulnerability to storms. Although large-scale dune morphology mainly depends on the wind regime and sand availability, vegetation plays an important role in semiarid and/or coastal areas. It is well known that under certain conditions vegetation is able to stabilize dunes, driving a morphological transformation from un-vegetated mobile crescent dunes to static vegetated "parabolic" dunes, de facto paralyzing desertification and initiating land recovery. Furthermore, vegetation is also the primary ingredient in the formation of coastal foredunes, which determine vulnerability to storms, as low dunes are prone to storm-induced erosion and overwash. In both cases, the coupling of biological and geomorphic (physical) processes, in particular vegetation growth and sand transport, governs the evolution of morphology. These processes were implemented in a computational model as part of a previous effort. It was shown that, for a migrating dune, this coupling leads to a negative feedback for dune motion, where an ever denser vegetation implies ever lesser sand transport. The model also predicted the existence of a "mobility index", defined by the vegetation growth rate to sand erosion rate ratio, that fully characterizes the morphological outcome: for indices above a certain threshold biological processes are dominant and dune motion slows after being covered by plants; for lower indices, the physical processes are the dominant ones and the dune remains mobile while vegetation is buried or rooted out. Here, we extend this model to better understand the formation of coastal dunes. We include new physical elements such as the shoreline and water table, as well as different grass species and potential competition among them

  4. Relationships between NDVI, canopy structure, and photosynthesis in three California vegetation types

    International Nuclear Information System (INIS)

    Gamon, J.A.; Field, C.B.; Goulden, M.L.; Griffin, K.L.; Hartley, A.E.; Joel, G.; Penuelas, J.; Valentini, R.

    1995-01-01

    In a range of plant species from three Californian vegetation types, we examined the widely used ''normalized difference vegetation index'' (NDVI) and ''simple ratio'' (SR) as indicators of canopy structure, light absorption, and photosynthetic activity. These indices, which are derived from canopy reflectance in the red and near-infrared wavebands, highlighted phenological differences between evergreen and deciduous canopies. They were poor indicators of total canopy biomass due to the varying abundance of non-green standing biomass in these vegetation types. However, in sparse canopies (leaf area index (LAI) apprxeq 0-2), NDVI was a sensitive indicator of canopy structure and chemical content (green biomass, green leaf area index, chlorophyll content, and foliar nitrogen content). At higher canopy green LAI values ( gt 2; typical of dense shrubs and trees), NDVI was relatively insensitive to changes in canopy structure. Compared to SR, NDVI was better correlated with indicators of canopy structure and chemical content, but was equivalent to the logarithm of SR. In agreement with theoretical expectations, both NDVI and SR exhibited near-linear correlations with fractional PAR intercepted by green leaves over a wide range of canopy densities. Maximum daily photosynthetic rates were positively correlated with NDVI and SR in annual grassland and semideciduous shrubs where canopy development and photosynthetic activity were in synchrony. The indices were also correlated with peak springtime canopy photosynthetic rates in evergreens. However, over most of the year, these indices were poor predictors of photosynthetic performance in evergreen species due to seasonal reductions in photosynthetic radiation-use efficiency that occurred without substantial declines in canopy greenness. Our results support the use of these vegetation indices as remote indicators of PAR absorption, and thus potential photosynthetic activity, even in

  5. Reanalysis of the gas-cooled fast reactor experiments at the zero power facility proteus - Spectral indices

    Energy Technology Data Exchange (ETDEWEB)

    Perret, G.; Pattupara, R. M. [Paul Scherrer Inst., 5232 Villigen (Switzerland); Girardin, G. [Ecole Polytechnique Federale de Lausanne, 1015 Lausanne (Switzerland); Chawla, R. [Paul Scherrer Inst., 5232 Villigen (Switzerland); Ecole Polytechnique Federale de Lausanne, 1015 Lausanne (Switzerland)

    2012-07-01

    The gas-cooled fast reactor (GCFR) concept was investigated experimentally in the PROTEUS zero power facility at the Paul Scherrer Inst. during the 1970's. The experimental program was aimed at neutronics studies specific to the GCFR and at the validation of nuclear data in fast spectra. A significant part of the program used thorium oxide and thorium metal fuel either distributed quasi-homogeneously in the reference PuO{sub 2}/UO{sub 2} lattice or introduced in the form of radial and axial blanket zones. Experimental results obtained at the time are still of high relevance in view of the current consideration of the Gas-cooled Fast Reactor (GFR) as a Generation-IV nuclear system, as also of the renewed interest in the thorium cycle. In this context, some of the experiments have been modeled with modern Monte Carlo codes to better account for the complex PROTEUS whole-reactor geometry and to allow validating recent continuous neutron cross-section libraries. As a first step, the MCNPX model was used to test the JEFF-3.1, JEFF-3.1.1, ENDF/B-VII.0 and JENDL-3.3 libraries against spectral indices, notably involving fission and capture of {sup 232}Th and {sup 237}Np, measured in GFR-like lattices. (authors)

  6. From spectral holeburning memory to spatial-spectral microwave signal processing

    International Nuclear Information System (INIS)

    Babbitt, Wm Randall; Barber, Zeb W; Harrington, Calvin; Mohan, R Krishna; Sharpe, Tia; Bekker, Scott H; Chase, Michael D; Merkel, Kristian D; Stiffler, Colton R; Traxinger, Aaron S; Woidtke, Alex J

    2014-01-01

    Many storage and processing systems based on spectral holeburning have been proposed that access the broad bandwidth and high dynamic range of spatial-spectral materials, but only recently have practical systems been developed that exceed the performance and functional capabilities of electronic devices. This paper reviews the history of the proposed applications of spectral holeburning and spatial-spectral materials, from frequency domain optical memory to microwave photonic signal processing systems. The recent results of a 20 GHz bandwidth high performance spectrum monitoring system with the additional capability of broadband direction finding demonstrates the potential for spatial-spectral systems to be the practical choice for solving demanding signal processing problems in the near future. (paper)

  7. Comparison of remote sensing indices for monitoring of desert cienegas

    Science.gov (United States)

    Wilson, Natalie R.; Norman, Laura M.; Villarreal, Miguel; Gass, Leila; Tiller, Ron; Salywon, Andrew

    2016-01-01

    This research considers the applicability of different vegetation indices at 30 m resolution for mapping and monitoring desert wetland (cienega) health and spatial extent through time at Cienega Creek in southeastern Arizona, USA. Multiple stressors including the risk of decadal-scale drought, the effects of current and predicted global warming, and continued anthropogenic pressures threaten aquatic habitats in the southwest and cienegas are recognized as important sites for conservation and restoration efforts. However, cienegas present a challenge to satellite-imagery based analysis due to their small size and mixed surface cover of open water, exposed soils, and vegetation. We created time series of five well-known vegetation indices using annual Landsat Thematic Mapper (TM) images retrieved during the April–June dry season, from 1984 to 2011 to map landscape-level distribution of wetlands and monitor the temporal dynamics of individual sites. Indices included the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Infrared Index (NDII). One topographic index, the Topographic Wetness Index (TWI), was analyzed to examine the utility of topography in mapping distribution of cienegas. Our results indicate that the NDII, calculated using Landsat TM band 5, outperforms the other indices at differentiating cienegas from riparian and upland sites, and was the best means to analyze change. As such, it offers a critical baseline for future studies that seek to extend the analysis of cienegas to other regions and time scales, and has broader applicability to the remote sensing of wetland features in arid landscapes.

  8. Directional Canopy Emissivity Estimation Based on Spectral Invariants

    Science.gov (United States)

    Guo, M.; Cao, B.; Ren, H.; Yongming, D.; Peng, J.; Fan, W.

    2017-12-01

    Land surface emissivity is a crucial parameter for estimating land surface temperature from remote sensing data and also plays an important role in the physical process of surface energy and water balance from local to global scales. To our knowledge, the emissivity varies with surface type and cover. As for the vegetation, its canopy emissivity is dependent on vegetation types, viewing zenith angle and structure that changes in different growing stages. Lots of previous studies have focused on the emissivity model, but few of them are analytic and suited to different canopy structures. In this paper, a new physical analytic model is proposed to estimate the directional emissivity of homogenous vegetation canopy based on spectral invariants. The initial model counts the directional absorption in six parts: the direct absorption of the canopy and the soil, the absorption of the canopy and soil after a single scattering and after multiple scattering within the canopy-soil system. In order to analytically estimate the emissivity, the pathways of photons absorbed in the canopy-soil system are traced using the re-collision probability in Fig.1. After sensitive analysis on the above six absorptions, the initial complicated model was further simplified as a fixed mathematic expression to estimate the directional emissivity for vegetation canopy. The model was compared with the 4SAIL model, FRA97 model, FRA02 model and DART model in Fig.2, and the results showed that the FRA02 model is significantly underestimated while the FRA97 model is a little underestimated, on basis of the new model. On the contrary, the emissivity difference between the new model with the 4SAIL model and DART model was found to be less than 0.002. In general, since the new model has the advantages of mathematic expression with accurate results and clear physical meaning, the model is promising to be extended to simulate the directional emissivity for the discrete canopy in further study.

  9. The broadband spectral energy distributions of SDSS blazars

    Science.gov (United States)

    Li, Huai-Zhen; Chen, Luo-En; Jiang, Yun-Guo; Yi, Ting-Feng

    2015-07-01

    We compiled the radio, optical and X-ray data of blazars from the Sloan Digital Sky Survey database, and presented the distribution of luminosities and broadband spectral indices. The distribution of luminosities shows that the averaged luminosity of flat spectrum radio quasars (FSRQs) is larger than that of BL Lacertae (BL Lac) objects. On the other hand, the broadband spectral energy distribution reveals that FSRQs and low energy peaked BL Lac objects have similar spectral properties, but high energy peaked BL Lac objects have a distinct spectral property. This may be due to the fact that different subclasses of blazars have different intrinsic environments and are at different cooling levels. Even so, a unified scheme is also revealed from the color-color diagram, which hints that there are similar physical processes operating in all objects under a range of intrinsic physical conditions or beaming parameters. Supported by the National Natural Science Foundation of China.

  10. Vegetation dynamics of the Tanbi Wetland National Park, The Gambia

    Science.gov (United States)

    Ceesay, A.

    2016-12-01

    Changes in mangrove vegetation have been identified as an important indicator of environmental change. The mangroves of the Tanbi Wetland National Park (TWNP) connect the Atlantic coast with the estuary of the River Gambia and as such, play an invaluable role in the agriculture, tourism and fisheries sectors of The Gambia. Our research seeks to understand the long-term changes in the mangrove vegetation to strengthen the formulation of sustainable alternative livelihoods and adaptation strategies to climate change. Mangrove vegetation dynamics was assessed by remote sensing, using decadal Landsat images covering 1973 - 2012. Physicochemical parameters were analyzed during the rainy and dry seasons of The Gambia for correlation with climate data. Our findings indicate that the long-term changes in salinity (24.5 and 35.8ppt) and water temperature (27.6oC and 30.2oC) during the rainy and dry seasons respectively are retarding mangrove growth. Mangrove vegetation cover declined by 6%, while grassland increased by 56.4%. This research concludes that long-term hyper-salinity is the cause for the stunted vegetation and lack of mangrove rejuvenation. We propose that specialized replanting systems such as the use of saplings be adopted instead of the conventional use of propagules. Alternative livelihoods also need to be diversified to support coastal communities.

  11. High-Throughput Phenotyping of Wheat and Barley Plants Grown in Single or Few Rows in Small Plots Using Active and Passive Spectral Proximal Sensing

    Directory of Open Access Journals (Sweden)

    Gero Barmeier

    2016-11-01

    Full Text Available In the early stages of plant breeding, breeders evaluate a large number of varieties. Due to limited availability of seeds and space, plot sizes may range from one to four rows. Spectral proximal sensors can be used in place of labour-intensive methods to estimate specific plant traits. The aim of this study was to test the performance of active and passive sensing to assess single and multiple rows in a breeding nursery. A field trial with single cultivars of winter barley and winter wheat with four plot designs (single-row, wide double-row, three rows, and four rows was conducted. A GreenSeeker RT100 and a passive bi-directional spectrometer were used to assess biomass fresh and dry weight, as well as aboveground nitrogen content and uptake. Generally, spectral passive sensing and active sensing performed comparably in both crops. Spectral passive sensing was enhanced by the availability of optimized ratio vegetation indices, as well as by an optimized field of view and by reduced distance dependence. Further improvements of both sensors in detecting the performance of plants in single rows can likely be obtained by optimization of sensor positioning or orientation. The results suggest that even in early selection cycles, enhanced high-throughput phenotyping might be able to assess plant performance within plots comprising single or multiple rows. This method has significant potential for advanced breeding.

  12. Serving vegetables first: A strategy to increase vegetable consumption in elementary school cafeterias.

    Science.gov (United States)

    Elsbernd, S L; Reicks, M M; Mann, T L; Redden, J P; Mykerezi, E; Vickers, Z M

    2016-01-01

    Vegetable consumption in the United States is low despite the wealth of evidence that vegetables play an important role in reducing risk of various chronic diseases. Because eating patterns developed in childhood continue through adulthood, we need to form healthy eating habits in children. The objective of this study was to determine if offering vegetables before other meal components would increase the overall consumption of vegetables at school lunch. We served kindergarten through fifth-grade students a small portion (26-33 g) of a raw vegetable (red and yellow bell peppers) while they waited in line to receive the rest of their lunch meal. They then had the options to take more of the bell peppers, a different vegetable, or no vegetable from the lunch line. We measured the amount of each vegetable consumed by each child. Serving vegetables first greatly increased the number of students eating vegetables. On intervention days most of the vegetables consumed came from the vegetables-first portions. Total vegetable intake per student eating lunch was low because most students chose to not eat vegetables, but the intervention significantly increased this value. Serving vegetables first is a viable strategy to increase vegetable consumption in elementary schools. Long-term implementation of this strategy may have an important impact on healthy eating habits, vegetable consumption, and the health consequences of vegetable intake. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose

    DEFF Research Database (Denmark)

    Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K.

    2017-01-01

    physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study......The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10− 5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different...... attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio...

  14. A new technique for extracting the red edge position from hyperspectral data : the linear extrapolation method

    NARCIS (Netherlands)

    Cho, M.A.; Skidmore, A.K.

    2006-01-01

    There is increasing interest in using hyperspectral data for quantitative characterization of vegetation in spatial and temporal scopes. Many spectral indices are being developed to improve vegetation sensitivity by minimizing the background influence. The chlorophyll absorption continuum index

  15. The US Geological Survey, digital spectral reflectance library: version 1: 0.2 to 3.0 microns

    Science.gov (United States)

    Clark, Roger N.; Swayze, Gregg A.; King, Trude V. V.; Gallagher, Andrea J.; Calvin, Wendy M.

    1993-01-01

    We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 500 spectra of 447 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 microns. The spectral resolution (Full Width Half Maximum) of the reflectance data is less than or equal to 4 nm in the visible (0.2-0.8 microns) and less than or equal 10 nm in the NIR (0.8-2.35 microns). All spectra were corrected to absolute reflectance using an NBS Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from sulfide, oxide, hydroxide, halide, carbonate, nitrate, borate, phosphate, and silicate groups are represented. X-ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses.

  16. Relationship between tourism development and vegetated landscapes in Luya Mountain Nature Reserve, Shanxi, China.

    Science.gov (United States)

    Cheng, Zhan-Hong; Zhang, Jin-Tun

    2005-09-01

    The relationship between tourism development and vegetated landscapes is analyzed for the Luya Mountain Nature Reserve (LMNR), Shanxi, China, in this study. Indices such as Sensitive Level (SL), Landscape Importance Value (LIV), information index of biodiversity (H'), Shade-tolerant Species Proportion (SSP), and Tourism Influencing Index (TII) are used to characterize vegetated landscapes, the impact of tourism, and their relationship. Their relationship is studied by Two-Way Indicator Species Analysis (TWINSPAN) and Detrended Correspondence Analysis (DCA). TWINSPAN gives correct and rapid partition to the classification, and DCA ordination shows the changing tendency of all vegetation types based on tourism development. These results reflect the ecological relationship between tourism development and vegetated landscapes. In Luya Mountain Nature Reserve, most plant communities are in good or medium condition, which shows that these vegetated landscapes can support more tourism. However, the occurrence of the bad condition shows that there is a severe contradiction between tourism development and vegetated landscapes.

  17. Environmental gradients across wetland vegetation groups in the arid slopes of Western Alborz Mountains, N. Iran

    Directory of Open Access Journals (Sweden)

    Asghar Kamrani

    2011-01-01

    Full Text Available Mountain wetlands are unique ecosystems in the arid southern slopes of Alborz range, the second largest range in Iran. The spatial distribution characteristics of wetland vegetation in the arid region of the Alborz and the main factors affecting their distributional patterns were studied. A classification of vegetation and ecological characteristics were carried out using data extracted from 430 relevés in 90 wetland sites. The data were analyzed using Two Way Indicator Species Analysis (TWINSPAN and detrended correspondence analysis (DCA. The wetland vegetation of Alborz Mountain was classified into four large groups. The first vegetation group was calcareous rich vegetation, mainly distributed in the river banks and characterized by helophytes such as Bolboschoenus affinis as indicator species. The second group was saline transitional vegetation, distributed in the ecotone areas and dominated by Phragmites australis. The third vegetation group is wet meadow vegetation which mainly consists of geophytes, endemic and Irano-Turanian species, distributed in the higher altitudes. This vegetation is mainly characterized by indicator species such as Carex orbicularis, high level concentration of Fe2+ and percentage of organic matter in the soil. The fourth vegetation group is aquatic vegetation, distributed in the lakeshores. The aquatic group species are mainly hydrophytic such as Batrachium trichophyllum. The TWINSPAN vegetation groups could be also recognized in the DCA graphs and ecologically differentiated by ANOVA of studied variables. Four vegetation groups can be differentiated on two first axes of indirect ordination. There is a gradient of pH, EC and organic matter associated with altitude on the DCA diagram. Correlation analysis between the axes of DCA and environmental factors shows that altitude, soil texture and other dependant environmental variables (e.g. pH are the main environmental factors affecting the distribution of wetland

  18. Ultraviolet spectral reflectance of carbonaceous materials

    Science.gov (United States)

    Applin, Daniel M.; Izawa, Matthew R. M.; Cloutis, Edward A.; Gillis-Davis, Jeffrey J.; Pitman, Karly M.; Roush, Ted L.; Hendrix, Amanda R.; Lucey, Paul G.

    2018-06-01

    A number of planetary spacecraft missions have carried instruments with sensors covering the ultraviolet (UV) wavelength range. However, there exists a general lack of relevant UV reflectance laboratory data to compare against these planetary surface remote sensing observations in order to make confident material identifications. To address this need, we have systematically analyzed reflectance spectra of carbonaceous materials in the 200-500 nm spectral range, and found spectral-compositional-structural relationships that suggest this wavelength region could distinguish between otherwise difficult-to-identify carbon phases. In particular (and by analogy with the infrared spectral region), large changes over short wavelength intervals in the refractive indices associated with the trigonal sp2π-π* transition of carbon can lead to Fresnel peaks and Christiansen-like features in reflectance. Previous studies extending to shorter wavelengths also show that anomalous dispersion caused by the σ-σ* transition associated with both the trigonal sp2 and tetrahedral sp3 sites causes these features below λ = 200 nm. The peak wavelength positions and shapes of π-π* and σ-σ* features contain information on sp3/sp2, structure, crystallinity, and powder grain size. A brief comparison with existing observational data indicates that the carbon fraction of the surface of Mercury is likely amorphous and submicroscopic, as is that on the surface of the martian satellites Phobos and Deimos, and possibly comet 67P/Churyumov-Gerasimenko, while further coordinated observations and laboratory experiments should refine these feature assignments and compositional hypotheses. The new laboratory diffuse reflectance data reported here provide an important new resource for interpreting UV reflectance measurements from planetary surfaces throughout the solar system, and confirm that the UV can be rich in important spectral information.

  19. Constancy of spectral-line bisectors

    International Nuclear Information System (INIS)

    Gray, D.F.

    1983-01-01

    Bisectors of spectral line profiles in cool stars indicate the strength of convection in the photospheres of these objects. The present investigation is concerned with the feasibility of studying time variations in line bisectors, the reality of apparent line-to-line differences within the same stellar spectrum, and bisector differences between stars of identical spectral types. The differences considered pertain to the shape of the bisector. The material used in the investigation was acquired at the McDonald Observatory using a 1728 diode Reticon array at the coudefocus of the 2.1-m telescope. Observed bisector errors are discussed. It is established that different lines in the same star show significantly different bisectors. The observed error bands are shown by the shaded regions. The slope and curvature are unique for each case

  20. Leaf-air transfer of organochlorine pesticides from three selected vegetables

    Energy Technology Data Exchange (ETDEWEB)

    Yang Xinglun [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 East Beijing Road, Nanjing 210008 (China); Jiang Xin [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 East Beijing Road, Nanjing 210008 (China)]. E-mail: jiangxin@issas.ac.cn; Yu Guifen [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 East Beijing Road, Nanjing 210008 (China); Yao Fenxia [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 East Beijing Road, Nanjing 210008 (China); Bian Yongrong [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 East Beijing Road, Nanjing 210008 (China); Wang Fang [State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, 71 East Beijing Road, Nanjing 210008 (China)

    2007-07-15

    The leaf-air transfer of organochlorine pesticides (OCPs) in three kinds of vegetables, namely lettuce, romaine and garlic leaves was investigated. It was found that although the uptake of OCPs by the three selected vegetables was similar under controlled conditions, the depuration varied significantly among chemicals and plant species in terms of elimination rate, final residue of each OCPs, as well as the effect of temperature on the residue of OCPs in the vegetables. The results indicated that neither QCB nor HCB could be trapped tightly by any of the three selected vegetables, in contrast, p,p'-DDT could be retained effectively by all of them; the retainment of {alpha}-HCH, {gamma}-HCH, p,p'-DDE, was dependent on the vegetable species, of which the garlic leaf had the biggest ability to trap them. Our work provided insight into the behavior of OCPs in the agroecosystem. - The leaf-air transfer of OCPs varied significantly among chemicals and the three selected vegetables.