WorldWideScience

Sample records for satellite vegetation indices

  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. 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

  3. 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 ...

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

    Science.gov (United States)

    Verbesselt, J.; Somers, B.; Lhermitte, S.; van Aardt, J.; Jonckheere, I.; Coppin, P.

    2005-10-01

    The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

  11. Vegetation coupling to global climate: Trajectories of vegetation change and phenology modeling from satellite observations

    Science.gov (United States)

    Fisher, Jeremy Isaac

    Important systematic shifts in ecosystem function are often masked by natural variability. The rich legacy of over two decades of continuous satellite observations provides an important database for distinguishing climatological and anthropogenic ecosystem changes. Examples from semi-arid Sudanian West Africa and New England (USA) illustrate the response of vegetation to climate and land-use. In Burkina Faso, West Africa, pastoral and agricultural practices compete for land area, while degradation may follow intensification. The Nouhao Valley is a natural experiment in which pastoral and agricultural land uses were allocated separate, coherent reserves. Trajectories of annual net primary productivity were derived from 18 years of coarse-grain (AVHRR) satellite data. Trends suggested that pastoral lands had responded rigorously to increasing rainfall after the 1980's droughts. A detailed analysis at Landsat resolution (30m) indicated that the increased vegetative cover was concentrated in the river basins of the pastoral region, implying a riparian wood expansion. In comparison, riparian cover was reduced in agricultural regions. We suggest that broad-scale patterns of increasing semi-arid West African greenness may be indicative of climate variability, whereas local losses may be anthropogenic in nature. The contiguous deciduous forests, ocean proximity, topography, and dense urban developments of New England provide an ideal landscape to examine influences of climate variability and the impact of urban development vegetation response. Spatial and temporal patterns of interannual climate variability were examined via green leaf phenology. Phenology, or seasonal growth and senescence, is driven by deficits of light, temperature, and water. In temperate environments, phenology variability is driven by interannual temperature and precipitation shifts. Average and interannual phenology analyses across southern New England were conducted at resolutions of 30m (Landsat

  12. Study of Wetland Ecosystem Vegetation Using Satellite Data

    Science.gov (United States)

    Dyukarev, E. A.; Alekseeva, M. N.; Golovatskaya, E. A.

    2017-12-01

    The normalized difference vegetation index (NDVI) is used to estimate the aboveground net production (ANP) of wetland ecosystems for the key area at the South Taiga zone of West Siberia. The vegetation index and aboveground production are related by linear dependence and are specific for each wetland ecosystem. The NDVI grows with an increase in the ANP at wooded oligotrophic ecosystems. Open oligotrophic bogs and eutrophic wetlands are characterized by an opposite relation. Maps of aboveground production for wetland ecosystems are constructed for each study year and for the whole period of studies. The average aboveground production for all wetland ecosystems of the key area, which was estimated with consideration for the area they occupy and using the data of satellite measurements of the vegetation index, is 305 g C/m2/yr. The total annual carbon accumulation in aboveground wetland vegetation in the key area is 794600 t.

  13. 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 ...

  14. 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

  15. CHARACTERISING VEGETATED SURFACES USING MODIS MULTIANGULAR SATELLITE DATA

    Directory of Open Access Journals (Sweden)

    G. McCamley

    2012-07-01

    Full Text Available Bidirectional Reflectance Distribution Functions (BRDF seek to represent variations in surface reflectance resulting from changes in a satellite's view and solar illumination angles. BRDF representations have been widely used to assist in the characterisation of vegetation. However BRDF effects are often noisy, difficult to interpret and are the spatial integral of all the individual surface features present in a pixel. This paper describes the results of an approach to understanding how BRDF effects can be used to characterise vegetation. The implementation of the Ross Thick Li Sparse BRDF model using MODIS is a stable, mature data product with a 10 year history and is a ready data source. Using this dataset, a geometric optical model is proposed that seeks to interpret the BRDF effects in terms of Normalised Difference Vegetation Index (NDVI and a height-to-width ratio of the vegetation components. The height-to-width ratio derived from this model seeks to represent the dependence of NDVI to changes in view zenith angle as a single numeric value. The model proposed within this paper has been applied to MODIS pixels in central Australia for areas in excess of 18,000 km2. The study area is predominantly arid and sparsely vegetated which provides a level of temporal and spatial homogeneity. The selected study area also minimises the effects associated with mutual obscuration of vegetation which is not considered by the model. The results are represented as a map and compared to NDVI derived from MODIS and NDVI derived from Landsat mosaics developed for Australia's National Carbon Accounting System (NCAS. The model reveals additional information not obvious in reflectance data. For example, the height-to-width ratio is able to reveal vegetation features in arid areas that do not have an accompanying significant increase in NDVI derived from MODIS, i.e. the height-to-width ratio reveals vegetation which is otherwise only apparent in NDVI derived

  16. 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...

  17. Detecting long-term changes to vegetation in northern Canada using the Landsat satellite image archive

    International Nuclear Information System (INIS)

    Fraser, R H; Olthof, I; Carrière, M; Deschamps, A; Pouliot, D

    2011-01-01

    Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM + satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1–25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.

  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. 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...

  20. 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.

  1. 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.

  2. 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.

  3. On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

    Science.gov (United States)

    Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

    2014-12-01

    Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

  4. Monitoring vegetation change in Abu Dhabi Emirate from 1996 to 2000 and 2004 using Landsat Satellite Imagery

    International Nuclear Information System (INIS)

    Starbuck, M.J.; Tamayo, J.

    2007-01-01

    In the fall of 2001, a study was initiated to investigate vegetation changes in the Abu Dhabi Emirates. The vast majority of vegetation present in the region is irrigated and analysis of vegetation change will support groundwater investigations in the region by indicating areas of increased water use. Satellite-based imaging systems provide a good source of data for such an analysis. The recent analysis was completed between February and November 2002 using Landsat 5 Thematic Mapper satellite imagery acquired in 1996 and Landsat 7 Enhanced Thematic Mapper Plus imagery acquired in 2000. These assessments were augmented in 2004with the study of Landsat 7 imagery acquired in early 2004. The total area of vegetation for each of seven study areas was calculated using the Normalized Difference Vegetation Index (NDVI) technique. Multiband image classification was used to differentiate general vegetation types. Change analysis consisted of simple NDVI image differencing and post-classification change matrices. Measurements of total vegetation are for the Abu Dhabi Emirate indicate an increase from 77,200 hectares in 1996 to 162,700 hectares in 2000 (110% increase). Based on comparison with manual interpretation of satellite imagery, the amount of under-reporting of irrigated land is estimated at about 15% of the actual area. From the assessment of 2004 Landset imagery, it was found that the growth of irrigated vegetation in most areas of Emirate had stabilized and had actually slightly decreased in some cases. The decreases are probably due to variability in the measurement technique and not due to actual decreases in area of vegetation. (author)

  5. 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.

  6. An optical sensor network for vegetation phenology monitoring and satellite data calibration

    DEFF Research Database (Denmark)

    Eklundh, L.; Jin, H.; Schubert, P.

    2011-01-01

    -board Aqua and Terra satellite platforms. PAR fluxes are partitioned into reflected and absorbed components for the ground and canopy. The measurements demonstrate that the instrumentation provides detailed information about the vegetation phenology and variations in reflectance due to snow cover variations......We present a network of sites across Fennoscandia for optical sampling of vegetation properties relevant for phenology monitoring and satellite data calibration. The network currently consists of five sites, distributed along an N-S gradient through Sweden and Finland. Two sites are located...... and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity....

  7. Ecological restoration of groundwater-dependent vegetation in the arid Ejina Delta: evidences from satellite evapotranspiration

    Science.gov (United States)

    Kai, Lu; Garcia, Monica; Yu, Jingjie; Zhang, Yichi; Wang, Ping; Wang, Sheng; Liu, Xiao

    2017-04-01

    The ecological water conveyance project (EWCP) in the Ejina delta, a typical hyper-arid area of China, aimed to restore degraded phreatophytic ecosystems. We assessed the degree of ecosystem recovery using as an ecohydrological indicator a ratio between actual and potential evapotranspiration derived from MODIS since the beginning of the project in 2001. The selected indicator was the Temperature Vegetation Dryness Index (TVDI) which was validated with Eddy covariance (EC) data confirming its applicability to monitor groundwater dependent vegetation. The spatial analyses of the evapotranspiration ratio show drying trends (2000-2015) which are stronger and also cover larger extensions than the wetting trends. Thus, the condition of key riparian areas relying mostly on surface water improved since the project began. However, groundwater dependent ecosystems located in lower river Xihe reaches present drying trends. It seems that despite of the runoff supplemented by the EWCP project, there is nowadays more inequality in the access to water by groundwater dependent ecosystems in the Ejina Delta. The study shows that energy-evaporation indices, relying on radiometric satellite temperature like the TVDI, can detect degradation signals that otherwise might go undetected by NDVI analyses especially in arid regions, where vegetation indices are greatly affected by the soil background signals. Additionally, they can provide timely information to water managers on how much water to allocate for a sustainable restoration program.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. 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 ...

  14. [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.

  15. [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.

  16. Estimation of vegetation cover resilience from satellite time series

    Directory of Open Access Journals (Sweden)

    T. Simoniello

    2008-07-01

    Full Text Available Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity.

    In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis

  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 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  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. 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

  5. Exploring Connections between Global Climate Indices and African Vegetation Phenology

    Science.gov (United States)

    Brown, Molly E.; deBeurs, Kirsten; Vrieling, Anton

    2009-01-01

    Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the continent in Africa. Agriculturally destructive droughts and floods are monitored from space using satellite remote sensing by organizations seeking to provide quantitative and predictive information about food security crises. Better knowledge on the relation between climate indices and food production may increase the use of these indices in famine early warning systems and climate outlook forums on the continent. Here we explore the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), the Multivariate ENSO Index (MEI) and the Southern Oscillation Index (SOI). We explore spatial relationships between growing conditions as measured by the NDVI and the five climate indices in Eastern, Western and Southern Africa to determine the regions and periods when they have a significant impact. The focus is to provide a clear indication as to which climate index has the most impact on the three regions during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by variations in the climate indices. The particular climate index and the timing showing highest correlation depended heavily on the region examined. The research shows that climate indices can contribute to understanding growing season variability in Eastern, Western and Southern Africa.

  6. 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.

  7. [Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

    Science.gov (United States)

    Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

    2015-11-01

    Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution

  8. 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...

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

    Science.gov (United States)

    Suepa, Tanita

    The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability

  14. 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

  15. 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.

  16. Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland

    Directory of Open Access Journals (Sweden)

    Sheng Chang

    2017-06-01

    Full Text Available In Mongolia, drought is a major natural disaster that can influence and devastate large regions, reduce livestock production, cause economic damage, and accelerate desertification in association with destructive human activities. The objective of this article is to determine the optimal satellite-derived drought indices for accurate and real-time expression of grassland drought in Mongolia. Firstly, an adaptability analysis was performed by comparing nine remote sensing-derived drought indices with reference indicators obtained from field observations using several methods (correlation, consistency percentage (CP, and time-space analysis. The reference information included environmental data, vegetation growth status, and region drought-affected (RDA information at diverse scales (pixel, county, and region for three types of land cover (forest steppe, steppe, and desert steppe. Second, a meteorological index (PED, a normalized biomass (NorBio reference indicator, and the RDA-based drought CP method were adopted for describing Mongolian drought. Our results show that in forest steppe regions the normalized difference water index (NDWI is most sensitive to NorBio (maximum correlation coefficient (MAX_R: up to 0.92 and RDA (maximum CP is 87%, and is most consistent with RDA spatial distribution. The vegetation health index (VHI and temperature condition index (TCI are most correlated with the PED index (MAX_R: 0.75 and soil moisture (MAX_R: 0.58, respectively. In steppe regions, the NDWI is most closely related to soil moisture (MAX_R: 0.69 and the VHI is most related to the PED (MAX_R: 0.76, NorBio (MCC: 0.95, and RDA data (maximum CP is 89%, exhibiting the most consistency with RDA spatial distribution. In desert steppe areas, the vegetation condition index (VCI correlates best with NorBio (MAX_R: 0.92, soil moisture (MAX_R: 0.61, and RDA spatial distribution, while TCI correlates best with the PED (MAX_R: 0.75 and the RDA data (maximum CP is 79

  17. Evaluating derived vegetation indices and cover fraction to estimate ...

    African Journals Online (AJOL)

    Nahom

    This study was conducted to assess satellite data for quantifying and mapping the ... aboveground biomass using regression models of the sample aboveground ... especially in the context of drought, land degradation risk assessment and.

  18. Satellite-Based Assessment of the spatial extent of Aquatic Vegetation in Lake Victoria

    Science.gov (United States)

    Clark, W.; Aligeti, N.; Jeyaprakash, T.; Martins, M.; Stodghill, J.; Winstanley, H.

    2011-12-01

    Lake Victoria in Africa is the second largest freshwater lake in the world and is known for its abundance of aquatic wildlife. In particular over 200 different fish species are caught and sold by local fisherman. The lake is a major contributor to the local economy as a corridor of transportation, source of drinking water, and source of hydropower. However, the invasion of aquatic vegetation such as water hyacinth in the lake has disrupted each of these markets. Aquatic vegetation now covers a substantial area of the coastline blocking waterways, disrupting hydropower, hindering the collection of drinking water and decreasing the profitability of fishing. The vegetation serves as a habitat for disease carrying mosquitoes as well as snakes and snails that spread the parasitic disease bilharzia. The current control measures of invasive aquatic vegetation rely on biological, chemical and mechanical control. The objective of this study was to utilize remote sensing to map aquatic vegetation within Lake Victoria from 2000 to 2011. MODIS, Landsat 4-5TM, and Landsat 7-ETM imagery was employed to perform change detections in vegetation and identify the extent of aquatic vegetation throughout the years. The efficiency of containment efforts were evaluated and ideal time for application of such efforts were suggested. A methodology for aquatic vegetation surveillance was created. The results of this project were presented as a workshop to the Lake Victoria Fisheries Organization, SERVIR, and other partner organizations. The workshop provided instruction into the use of NASA and other satellite derived products. Time series animations of the spatial extent of aquatic vegetation within the lake were created. By identifying seasons of decreased aquatic vegetation, ideal times to employ control efforts were identified. SERVIR will subsequently utilize the methodologies and mapping results of this study to develop operational aquatic vegetation surveillance for Lake Victoria.

  19. Single Tree Vegetation Depth Estimation Tool for Satellite Services Link Design

    Directory of Open Access Journals (Sweden)

    Z. Hasirci

    2016-04-01

    Full Text Available Attenuation caused by tree shadowing is an important factor for describing the propagation channel of satellite services. Thus, vegetation effects should be determined by experimental studies or empirical formulations. In this study, tree types in the Black Sea Region of Turkey are classified based on their geometrical shapes into four groups such as conic, ellipsoid, spherical and hemispherical. The variations of the vegetation depth according to different tree shapes are calculated with ray tracing method. It is showed that different geometrical shapes have different vegetation depths even if they have same foliage volume for different elevation angles. The proposed method is validated with the related literature in terms of average single tree attenuation. On the other hand, due to decrease system requirements (speed, memory usage etc. of ray tracing method, an artificial neural network is proposed as an alternative. A graphical user interface is created for the above processes in MATLAB environment named vegetation depth estimation tool (VdET.

  20. The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange

    Science.gov (United States)

    Joiner, J.; Yoshida, Y.; Vasilkov, A. P.; Schaefer, K.; Jung, M.; Guanter, L.; Zhang, Y; Garrity, S.; Middleton, E. M.; Huemmrich, K. F.; hide

    2014-01-01

    Mapping of terrestrial chlorophyll uorescence from space has shown potentialfor providing global measurements related to gross primary productivity(GPP). In particular, space-based fluorescence may provide information onthe length of the carbon uptake period that can be of use for global carboncycle modeling. Here, we examine the seasonal cycle of photosynthesis asestimated from satellite fluorescence retrievals at wavelengths surroundingthe 740nm emission feature. These retrievals are from the Global OzoneMonitoring Experiment 2 (GOME-2) flying on the MetOp A satellite. Wecompare the fluorescence seasonal cycle with that of GPP as estimated froma diverse set of North American tower gas exchange measurements. Because the GOME-2 has a large ground footprint (40 x 80km2) as compared with that of the flux towers and requires averaging to reduce random errors, we additionally compare with seasonal cycles of upscaled GPP in the satellite averaging area surrounding the tower locations estimated from the Max Planck Institute for Biogeochemistry (MPI-BGC) machine learning algorithm. We also examine the seasonality of absorbed photosynthetically-active radiation(APAR) derived with reflectances from the MODerate-resolution Imaging Spectroradiometer (MODIS). Finally, we examine seasonal cycles of GPP as produced from an ensemble of vegetation models. Several of the data-driven models rely on satellite reflectance-based vegetation parameters to derive estimates of APAR that are used to compute GPP. For forested sites(particularly deciduous broadleaf and mixed forests), the GOME-2 fluorescence captures the spring onset and autumn shutoff of photosynthesis as delineated by the tower-based GPP estimates. In contrast, the reflectance-based indicators and many of the models tend to overestimate the length of the photosynthetically-active period for these and other biomes as has been noted previously in the literature. Satellite fluorescence measurements therefore show potential for

  1. 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

  2. Evaluating derived vegetation indices and cover fraction to estimate ...

    African Journals Online (AJOL)

    This study was conducted to assess satellite data for quantifying and mapping the spatial distribution of rangeland biophysical parameters (aboveground biomass) from different geographic locations in the North West province, South Africa. Two major factors affecting the quality and conditions of the rangelands, namely ...

  3. Vegetation mapping with satellite data of the Forsmark and Tierp regions

    Energy Technology Data Exchange (ETDEWEB)

    Boresjoe-Bronge, Laine; Wester, Kjell [SwedPower, Stockholm (Sweden)

    2002-04-01

    SKB (Swedish Nuclear Fuel and Waste Management Co) performs a siting program for deep repository of spent nuclear fuel that includes survey of three potential sites. The SKB siting process has now reached the site investigation phase. There are several fields of investigations performed in this phase. One of them is description of the surface ecosystems. The surface ecosystems are mapped both on a regional (50-100 km{sup 2} ) and a local level (1 km{sup 2} ). Two inventory methods are used, remote sensing (satellite data/aerial photographs) for the regional level, and field inventory for the detailed level. As a part of the surface ecosystem characterisation on the regional level vegetation mapping using satellite data has been performed over the three potential deep depository sites, Forsmark, Tierp and Oskarshamn. The user requirements for the vegetation mapping of the potential sites are the following: Dominated species in the tree layer, shrub layer, field layer and ground layer shall be described both on regional and local level; Dominated species in all layers shall be quantified regarding share and percentage of ground cover, or absence of cover (vegetation free ground); The regional and the local inventory shall have identical or comparable classification systems; The classification system and the method used shall make it possible to scale the results from local to regional level and vice versa; The produced layers shall be presented in digital form and make it possible to model biomass and turnover of organic matter (carbon, nutrients, water); The produced information shall in a first phase be of use for planning and for making nature and environmental considerations. Data sources used in the study include geo-referenced SPOT4 XI data (20 m ground resolution), geo-referenced Landsat TM data (30 m ground resolution), soil type data, topographic map data and colour infrared aerial photographs. The production of vegetation layers has been carried out in two

  4. Vegetation mapping with satellite data of the Forsmark and Tierp regions

    International Nuclear Information System (INIS)

    Boresjoe-Bronge, Laine; Wester, Kjell

    2002-04-01

    SKB (Swedish Nuclear Fuel and Waste Management Co) performs a siting program for deep repository of spent nuclear fuel that includes survey of three potential sites. The SKB siting process has now reached the site investigation phase. There are several fields of investigations performed in this phase. One of them is description of the surface ecosystems. The surface ecosystems are mapped both on a regional (50-100 km 2 ) and a local level (1 km 2 ). Two inventory methods are used, remote sensing (satellite data/aerial photographs) for the regional level, and field inventory for the detailed level. As a part of the surface ecosystem characterisation on the regional level vegetation mapping using satellite data has been performed over the three potential deep depository sites, Forsmark, Tierp and Oskarshamn. The user requirements for the vegetation mapping of the potential sites are the following: Dominated species in the tree layer, shrub layer, field layer and ground layer shall be described both on regional and local level; Dominated species in all layers shall be quantified regarding share and percentage of ground cover, or absence of cover (vegetation free ground); The regional and the local inventory shall have identical or comparable classification systems; The classification system and the method used shall make it possible to scale the results from local to regional level and vice versa; The produced layers shall be presented in digital form and make it possible to model biomass and turnover of organic matter (carbon, nutrients, water); The produced information shall in a first phase be of use for planning and for making nature and environmental considerations. Data sources used in the study include geo-referenced SPOT4 XI data (20 m ground resolution), geo-referenced Landsat TM data (30 m ground resolution), soil type data, topographic map data and colour infrared aerial photographs. The production of vegetation layers has been carried out in two steps. In

  5. 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

  6. 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...

  7. 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.

  8. 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

  9. 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

  10. Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

    Science.gov (United States)

    Boken, Vijendra K.; Easson, Gregory L.; Rowland, James

    2010-01-01

    The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t-test, and the coefficient of determination, R 2. The per cent difference was found to be within 3%, the p-value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

  11. 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.

  12. Assessing Sahelian vegetation and stress from seasonal time series of polar orbiting and geostationary satellite imagery

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard

    that short term variations in anomalies from seasonally detrended time series of indices could carry information on vegetation stress was examined and confirmed. However, it was not found sufficiently robust on pixel level to be implemented for monitoring vegetation water stress on a per-pixel basis...... provide good sensitivity to canopy water content, which can make vegetation stress detection possible. Furthermore, the high frequency observations in the optical spectrum now available from geostationary instruments have the potential for detection of changes in vegetation related surface properties...... on short timescales, which are challenging from polar orbiting instruments. Geostationary NDVI and the NIR and SWIR based Shortwave Infrared Water Stress Index (SIWSI) indices are compared with extensive field data from the Dahra site, supplemented by data from the Agoufou and Demokeya sites. The indices...

  13. 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.

  14. 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

  15. [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.

  16. 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.

  17. 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)

  18. Vegetation classification and quatification by satellite image processing. A case study in north Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Aranha, J.T. [Dept. Florestal, UTAD, 5001-801 Vila Real (Portugal); Viana, H.F. [Instituto Politecnico de Viseu, Escola Superior Agraria, Viseu (Portugal); Rodrigues, R. [Bioflag - Consulting - Santo Tirso (Portugal)

    2008-07-01

    The expected increase in Forest Biomass demand for energy production leads to derive expeditious and non-expensive techniques in order to classify vegetal land cover and evaluate the available biomass like to be harvested. Satellite image processing and classification, combined to field work, is a suitable tool to achieve these aims. A vegetation index (NDVI) was created by means of a Landsat TM image, from 2006, manipulation, in order to create a general vegetation map. Then, the same image was submitted to a supervised classification process in order to produce a land cover map (overall accuracy of 85%). In a second stage, they were collected NDVI values for each sampling plot, in order to update the database previous developed with data collected within forestry stands and shrubland. This data merging enabled to transform general vegetation map into available biomass within forestry stands and shrubland. The results showed a range of values from 0.25 up to 6.00 dry ton./ha for recent and former burnt areas recovered by Pinus pinaster (maritime pine) young trees and from 2.00 up to 9.00 dry ton./ha for recent and former burnt areas recovered by shrubs (e.g. genista or broom).

  19. 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.

  20. Satellite remote sensing of limnological indicators of global change

    International Nuclear Information System (INIS)

    Wynne, R.H.; Lillesand, T.M.

    1991-01-01

    The paper examines the general hypothesis that large-scale and long-term trends in lake ice formation and breakup, along with changes in the optical properties of lakes, can serve as robust integrated measures of regional and global climate change. Recent variation in the periodicity of lake ice formation and breakup is investigated using the AVHRR aboard the NOAA/TIROS series of polar orbiting satellites. The study area consists of 44 lakes and reservoirs with a surface area of greater than 1000 hectares in Wisconsin. The utility of AVHRR for lake ice detection with high temporal resolution is demonstrated, the relationship between ice phenology and periodicity with lake morphometry for the lakes in the study is elucidated, and remotely sensed measures of ice periodicity are correlated with local and regional temperature trends. 31 refs

  1. 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

  2. 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...

  3. Global changes in dryland vegetation dynamics (1988–2008 assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data

    Directory of Open Access Journals (Sweden)

    N. Andela

    2013-10-01

    Full Text Available Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008 vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI and the recently developed passive-microwave-based Vegetation Optical Depth (VOD. The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.

  4. 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

  5. Patchiness in semi-arid dwarf shrublands: evidence from satellite ...

    African Journals Online (AJOL)

    ... Plants; Remote sensing; Rhigozum obovatum Burch; Satellite-derived vegetation indices; Woody species; patchiness; semi-arid; dwarf shrubland; shrublands; co2; assimilation; karoo; south africa; ndvi; satellite imagery; geochemical mound; rhigozum obovatum; eriocephalus ericoides; pentzia incana; vegetation; botany

  6. Estimation of Global Vegetation Productivity from Global LAnd Surface Satellite Data

    Directory of Open Access Journals (Sweden)

    Tao Yu

    2018-02-01

    Full Text Available Accurately estimating vegetation productivity is important in research on terrestrial ecosystems, carbon cycles and climate change. Eight-day gross primary production (GPP and annual net primary production (NPP are contained in MODerate Resolution Imaging Spectroradiometer (MODIS products (MOD17, which are considered the first operational datasets for monitoring global vegetation productivity. However, the cloud-contaminated MODIS leaf area index (LAI and Fraction of Photosynthetically Active Radiation (FPAR retrievals may introduce some considerable errors to MODIS GPP and NPP products. In this paper, global eight-day GPP and eight-day NPP were first estimated based on Global LAnd Surface Satellite (GLASS LAI and FPAR products. Then, GPP and NPP estimates were validated by FLUXNET GPP data and BigFoot NPP data and were compared with MODIS GPP and NPP products. Compared with MODIS GPP, a time series showed that estimated GLASS GPP in our study was more temporally continuous and spatially complete with smoother trajectories. Validated with FLUXNET GPP and BigFoot NPP, we demonstrated that estimated GLASS GPP and NPP achieved higher precision for most vegetation types.

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006

    DEFF Research Database (Denmark)

    Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.

    2014-01-01

    A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of veg...

  13. Satellite-based hybrid drought monitoring tool for prediction of vegetation condition in Eastern Africa: A case study for Ethiopia

    Science.gov (United States)

    Tadesse, Tsegaye; Demisse, Getachew Berhan; Zaitchik, Ben; Dinku, Tufa

    2014-03-01

    An experimental drought monitoring tool has been developed that predicts the vegetation condition (Vegetation Outlook) using a regression-tree technique at a monthly time step during the growing season in Eastern Africa. This prediction tool (VegOut-Ethiopia) is demonstrated for Ethiopia as a case study. VegOut-Ethiopia predicts the standardized values of the Normalized Difference Vegetation Index (NDVI) at multiple time steps (weeks to months into the future) based on analysis of "historical patterns" of satellite, climate, and oceanic data over historical records. The model underlying VegOut-Ethiopia capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation (ENSO)) expressed over the 24 year data record and also considers several environmental characteristics (e.g., land cover and elevation) that influence vegetation's response to weather conditions to produce 8 km maps that depict future general vegetation conditions. VegOut-Ethiopia could provide vegetation monitoring capabilities at local, national, and regional levels that can complement more traditional remote sensing-based approaches that monitor "current" vegetation conditions. The preliminary results of this case study showed that the models were able to predict the vegetation stress (both spatial extent and severity) in drought years 1-3 months ahead during the growing season in Ethiopia. The correlation coefficients between the predicted and satellite-observed vegetation condition range from 0.50 to 0.90. Based on the lessons learned from past research activities and emerging experimental forecast models, future studies are recommended that could help Eastern Africa in advancing knowledge of climate, remote sensing, hydrology, and water resources.

  14. 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.

  15. 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.

  16. Integration of satellite-induced fluorescence and vegetation optical depth to improve the retrieval of land evaporation

    Science.gov (United States)

    Pagán, B. R.; Martens, B.; Maes, W. H.; Miralles, D. G.

    2017-12-01

    Global satellite-based data sets of land evaporation overcome limitations in coverage of in situ measurements while retaining some observational nature. Although their potential for real world applications are promising, their value during dry conditions is still poorly understood. Most evaporation retrieval algorithms are not directly sensitive to soil moisture. An exception is the Global Land Evaporation Amsterdam Model (GLEAM), which uses satellite surface soil moisture and precipitation to account for land water availability. The existing methodology may greatly benefit from the optimal integration of novel observations of the land surface. Microwave vegetation optical depth (VOD) and near-infrared solar-induced fluorescence (SIF) are expected to reflect different aspects of evaporative stress. While the former is considered to be a proxy of vegetation water content, the latter is indicative of the activity of photosynthetic machinery. As stomata regulate both photosynthesis and transpiration, we expect a relationship between SIF and transpiration. An important motivation to incorporate observations in land evaporation calculations is that plant transpiration - usually the largest component of the flux - is extremely challenging to model due to species-dependent responses to drought. Here we present an innovative integration of VOD and SIF into the GLEAM evaporative stress function. VOD is utilized as a measurement of isohydricity to improve the representation of species specific drought responses. SIF is used for transpiration modelling, a novel application, and standardized by incoming solar radiation to better account for radiation-limited periods. Results are validated with global FLUXNET and International Soil Moisture Network data and demonstrate that the incorporation of VOD and SIF can yield accurate estimates of transpiration over large-scales, which are essential to further understand ecosystem-atmosphere feedbacks and the response of terrestrial

  17. 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.

  18. Satellites

    International Nuclear Information System (INIS)

    Burns, J.A.; Matthews, M.S.

    1986-01-01

    The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

  19. 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

  20. 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.

  1. 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.

  2. Estimation of absorbed photosynthetically active radiation and vegetation net production efficiency using satellite data

    International Nuclear Information System (INIS)

    Hanan, N.P.; Prince, S.D.; Begue, A.

    1995-01-01

    The amount of photosynthetically active radiation (PAR) absorbed by green vegetation is an important determinant of photosynthesis and growth. Methods for the estimation of fractional absorption of PAR (iff PAR ) for areas greater than 1 km 2 using satellite data are discussed, and are applied to sites in the Sahel that have a sparse herb layer and tree cover of less than 5%. Using harvest measurements of seasonal net production, net production efficiencies are calculated. Variation in estimates of seasonal PAR absorption (APAR) caused by the atmospheric correction method and relationship between surface reflectances and iff PAR is considered. The use of maximum value composites of satellite NDVI to reduce the effect of the atmosphere is shown to produce inaccurate APAR estimates. In this data set, however, atmospheric correction using average optical depths was found to give good approximations of the fully corrected data. A simulation of canopy radiative transfer using the SAIL model was used to derive a relationship between canopy NDVI and iff PAR . Seasonal APAR estimates assuming a 1:1 relationship between iff PAR and NDVI overestimated the SAIL modeled results by up to 260%. The use of a modified 1:1 relationship, where iff PAR was assumed to be linearly related to NDVI scaled between minimum (soil) and maximum (infinite canopy) values, underestimated the SAIL modeled results by up to 35%. Estimated net production efficiencies (ϵ n , dry matter per unit APAR) fell in the range 0.12–1.61 g MJ −1 for above ground production, and in the range 0.16–1.88 g MJ −1 for total production. Sites with lower rainfall had reduced efficiencies, probably caused by physiological constraints on photosynthesis during dry conditions. (author)

  3. Long-term change analysis of satellite-based evapotranspiration over Indian vegetated surface

    Science.gov (United States)

    Gupta, Shweta; Bhattacharya, Bimal K.; Krishna, Akhouri P.

    2016-05-01

    In the present study, trend of satellite based annual evapotranspiration (ET) and natural forcing factors responsible for this were analyzed. Thirty years (1981-2010) of ET data at 0.08° grid resolution, generated over Indian region from opticalthermal observations from NOAA PAL and MODIS AQUA satellites, were used. Long-term data on gridded (0.5° x 0.5°) annual rainfall (RF), annual mean surface soil moisture (SSM) ERS scatterometer at 25 km resolution and annual mean incoming shortwave radiation from MERRA-2D reanalysis were also analyzed. Mann-Kendall tests were performed with time series data for trend analysis. Mean annual ET loss from Indian ago-ecosystem was found to be almost double (1100 Cubic Km) than Indian forest ecosystem (550 Cubic Km). Rainfed vegetation systems such as forest, rainfed cropland, grassland showed declining ET trend @ - 4.8, -0.6 &-0.4 Cubic Kmyr-1, respectively during 30 years. Irrigated cropland initially showed ET decline upto 1995 @ -0.8 cubic Kmyr-1 which could possibly be due to solar dimming followed by increasing ET @ 0.9 cubic Kmyr-1 after 1995. A cross-over point was detected between forest ET decline and ET increase in irrigated cropland during 2008. During 2001-2010, the four agriculturally important Indian states eastern, central, western and southern showed significantly increasing ET trend with S-score of 15-25 and Z-score of 1.09-2.9. Increasing ET in western and southern states was found to be coupled with increase in annual rainfall and SSM. But in eastern and central states no significant trend in rainfall was observed though significant increase in ET was noticed. The study recommended to investigate the influence of anthropogenic factors such as increase in area under irrigation, increased use of water for irrigation through ground water pumping, change in cropping pattern and cultivars on increasing ET.

  4. 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.

  5. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

    International Nuclear Information System (INIS)

    Nikolov, Ned; Zeller, Karl

    2006-01-01

    Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. - The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale

  6. Efficient retrieval of vegetation leaf area index and canopy clumping factor from satellite data to support pollutant deposition assessments

    Energy Technology Data Exchange (ETDEWEB)

    Nikolov, Ned [Natural Resource Research Center, 2150 Centre Avenue, Building A, Room 368, Fort Collins, CO 80526 (United States)]. E-mail: nnikolov@fs.fed.us; Zeller, Karl [USDA FS Rocky Mountain Research Station, 240 W. Prospect Road, Fort Collins, CO 80526 (United States)]. E-mail: kzeller@fs.fed.us

    2006-06-15

    Canopy leaf area index (LAI) is an important structural parameter of the vegetation controlling pollutant uptake by terrestrial ecosystems. This paper presents a computationally efficient algorithm for retrieval of vegetation LAI and canopy clumping factor from satellite data using observed Simple Ratios (SR) of near-infrared to red reflectance. The method employs numerical inversion of a physics-based analytical canopy radiative transfer model that simulates the bi-directional reflectance distribution function (BRDF). The algorithm is independent of ecosystem type. The method is applied to 1-km resolution AVHRR satellite images to retrieve a geo-referenced data set of monthly LAI values for the conterminous USA. Satellite-based LAI estimates are compared against independent ground LAI measurements over a range of ecosystem types. Verification results suggest that the new algorithm represents a viable approach to LAI retrieval at continental scale, and can facilitate spatially explicit studies of regional pollutant deposition and trace gas exchange. - The paper presents a physics-based algorithm for retrieval of vegetation LAI and canopy-clumping factor from satellite data to assist research of pollutant deposition and trace-gas exchange. The method is employed to derive a monthly LAI dataset for the conterminous USA and verified at a continental scale.

  7. 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.

  8. 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

  9. 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)

  10. 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.

  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. Automated Recognition of Vegetation and Water Bodies on the Territory of Megacities in Satellite Images of Visible and IR Bands

    Science.gov (United States)

    Mozgovoy, Dmitry k.; Hnatushenko, Volodymyr V.; Vasyliev, Volodymyr V.

    2018-04-01

    Vegetation and water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. A methodology of automated recognition of vegetation and water bodies on the territory of megacities in satellite images of sub-meter spatial resolution of the visible and IR bands is proposed. By processing multispectral images from the satellite SuperView-1A, vector layers of recognized plant and water objects were obtained. Analysis of the results of image processing showed a sufficiently high accuracy of the delineation of the boundaries of recognized objects and a good separation of classes. The developed methodology provides a significant increase of the efficiency and reliability of updating maps of large cities while reducing financial costs. Due to the high degree of automation, the proposed methodology can be implemented in the form of a geo-information web service functioning in the interests of a wide range of public services and commercial institutions.

  13. Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

    Science.gov (United States)

    Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

    2015-04-01

    Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

  14. Vegetation cover and their functioning in dependence on the reclamation of the Velka podkrusnohorska dump during last 20 years using satellite data analysis

    International Nuclear Information System (INIS)

    Prochazka, J.; Nedbal, V.; Pecharova, E.; Brom, J.

    2010-01-01

    Vegetation plays a significant role in mass retention, solar energy dissipation, water cycle forming and local climate changes on reclamation plots of mining areas. This paper discussed the use of Landsat satellite data in order to evaluate different types of reclamation and their development for the last 20 years in the case of the Velka podkrusnohorska dump. Biophysical parameters which can be indicators of solar energy dissipation that were utilized to analyse changes of temporal development from 1991 to 2009 included land surface temperature, surface moisture expressed as wetness index tasseled cap, and normalized difference vegetation index. From these parameters, a functional index was then developed. The paper discussed the development of these parameters and their relationship to solar energy dissipation. It was concluded that since 1995, the observed parameters significantly changed, gradually converging to the state of the surrounding landscape. 16 refs., 2 tabs., 2 figs.

  15. Vegetation cover and their functioning in dependence on the reclamation of the Velka podkrusnohorska dump during last 20 years using satellite data analysis

    Energy Technology Data Exchange (ETDEWEB)

    Prochazka, J.; Nedbal, V.; Pecharova, E. [South Bohemia Univ., Ceske Budejovice (Czech Republic); Brom, J. [Enki o.p.s., Trebon (Czech Republic)

    2010-07-01

    Vegetation plays a significant role in mass retention, solar energy dissipation, water cycle forming and local climate changes on reclamation plots of mining areas. This paper discussed the use of Landsat satellite data in order to evaluate different types of reclamation and their development for the last 20 years in the case of the Velka podkrusnohorska dump. Biophysical parameters which can be indicators of solar energy dissipation that were utilized to analyse changes of temporal development from 1991 to 2009 included land surface temperature, surface moisture expressed as wetness index tasseled cap, and normalized difference vegetation index. From these parameters, a functional index was then developed. The paper discussed the development of these parameters and their relationship to solar energy dissipation. It was concluded that since 1995, the observed parameters significantly changed, gradually converging to the state of the surrounding landscape. 16 refs., 2 tabs., 2 figs.

  16. Mangrove forests submitted to depositional processes and salinity variation investigated using satellite images and vegetation structure surveys

    OpenAIRE

    Cunha-Lignon, M.; Kampel, M.; Menghini, R.P.; Schaeffer-Novelli, Y.; Cintrón, G.; Dahdouh-Guebas, F.

    2011-01-01

    The current paper examines the growth and spatio-temporal variation of mangrove forests in response to depositional processes and different salinity conditions. Data from mangrove vegetation structure collected at permanent plots and satellite images were used. In the northern sector important environmental changes occurred due to an artificial channel producing modifications in salinity. The southern sector is considered the best conserved mangrove area along the coast of São Paulo State, Br...

  17. 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.

  18. Analysis of vegetation from satellite images correlated to the bird species presence and the state of health of the ecosystems of Bucharest during the period from 1991 to 2006

    Directory of Open Access Journals (Sweden)

    Dragoș Mirela

    2017-01-01

    Full Text Available The urban vegetation needs adequate monitoring and conservation, being a critical resource of urban landscape. To its deeply esthetic values, the practical values and, respectively, ecosystem services delivered by the urban biodiversity are added (amelioration of the environment and urban microclimate, flood control, diminishing of the environmental pollution, increasing of biodiversity and habitats etc.. Accurate remote sensing techniques have been used widely in locating and mapping urban vegetation (Light Detection And Ranging-LiDAR, satellite images. The purpose of this study is to point out the vegetation status in correlation with the number of the bird species (as indicator of the ecosystem's health, using remote sensing techniques (Landsat satellite images, between 1991-2006 in Bucharest, Romania's capital. Rapid urban evolution of Bucharest led to important changes within the structure of the city, underlined by the increasing of the built area to the detriment of the green one. The intensity of the urbanization rate also led to the decreasing of the number of the bird species. The results obtained through analysis of satellite images indicate the necessity to acquire the up-to-date information related to the vegetation status in order to establish in the future, through urban landscape projects, protection measures for the vegetation cover and for the bird habitats in Bucharest Municipality.

  19. Trend shifts in satellite-derived vegetation growth in Central Eurasia, 1982-2013.

    Science.gov (United States)

    Xu, Hao-Jie; Wang, Xin-Ping; Yang, Tai-Bao

    2017-02-01

    Central Eurasian vegetation is critical for the regional ecological security and the global carbon cycle. However, climatic impacts on vegetation growth in Central Eurasia are uncertain. The reason for this uncertainty lies in the fact that the response of vegetation to climate change showed nonlinearity, seasonality and differences among plant functional types. Based on remotely sensed vegetation index and in-situ meteorological data for the years 1982-2013, in conjunction with the latest land cover type product, we analyzed how vegetation growth trend varied across different seasons and evaluated vegetation response to climate variables at regional, biome and pixel scales. We found a persistent increase in the growing season NDVI over Central Eurasia during 1982-1994, whereas this greening trend has stalled since the mid-1990s in response to increased water deficit. The stalled trend in the growing season NDVI was largely attributed by summer and autumn NDVI changes. Enhanced spring vegetation growth after 2002 was caused by rapid spring warming. The response of vegetation to climatic factors varied in different seasons. Precipitation was the main climate driver for the growing season and summer vegetation growth. Changes in temperature and precipitation during winter and spring controlled the spring vegetation growth. Autumn vegetation growth was mainly dependent on the vegetation growth in summer. We found diverse responses of different vegetation types to climate drivers in Central Eurasia. Forests were more responsive to temperature than to precipitation. Grassland and desert vegetation responded more strongly to precipitation than to temperature in summer but more strongly to temperature than to precipitation in spring. In addition, the growth of desert vegetation was more dependent on winter precipitation than that of grasslands. This study has important implications for improving the performance of terrestrial ecosystem models to predict future vegetation

  20. 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.

  1. 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

  2. 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

  3. 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.

  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. 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

  6. Satellite Leaf Area Index: Global Scale Analysis of the Tendencies Per Vegetation Type Over the Last 17 Years

    Directory of Open Access Journals (Sweden)

    Simon Munier

    2018-03-01

    Full Text Available The main objective of this study is to detect and quantify changes in the vegetation dynamics of each vegetation type at the global scale over the last 17 years. With recent advances in remote sensing techniques, it is now possible to study the Leaf Area Index (LAI seasonal and interannual variability at the global scale and in a consistent way over the last decades. However, the coarse spatial resolution of these satellite-derived products does not permit distinguishing vegetation types within mixed pixels. Considering only the dominant type per pixel has two main drawbacks: the LAI of the dominant vegetation type is contaminated by spurious signal from other vegetation types and at the global scale, significant areas of individual vegetation types are neglected. In this study, we first developed a Kalman Filtering (KF approach to disaggregate the satellite-derived LAI from GEOV1 over nine main vegetation types, including grasslands and crops as well as evergreen, broadleaf and coniferous forests. The KF approach permits the separation of distinct LAI values for individual vegetation types that coexist within a pixel. The disaggregated LAI product, called LAI-MC (Multi-Cover, consists of world-wide LAI maps provided every 10 days for each vegetation type over the 1999–2015 period. A trend analysis of the original GEOV1 LAI product and of the disaggregated LAI time series was conducted using the Mann-Kendall test. Resulting trends of the GEOV1 LAI (which accounts for all vegetation types compare well with previous regional or global studies, showing a greening over a large part of the globe. When considering each vegetation type individually, the largest global trend from LAI-MC is found for coniferous forests (0.0419 m 2 m − 2 yr − 1 followed by summer crops (0.0394 m 2 m − 2 yr − 1 , while winter crops and grasslands show the smallest global trends (0.0261 m 2 m − 2 yr − 1 and 0.0279 m 2 m − 2 yr − 1 , respectively. The LAI

  7. 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...

  8. 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)

  9. 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

  10. 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

  11. 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

  12. A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

    Science.gov (United States)

    Yagci, Ali Levent; Santanello, Joseph A.; Rodell, Matthew; Deng, Meixia; Di, Liping

    2018-01-01

    The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

  13. 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.

  14. Extending a field-based Sonoran desert vegetation classification to a regional scale using optical and microwave satellite imagery

    Science.gov (United States)

    Shupe, Scott Marshall

    2000-10-01

    Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers

  15. 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.

  16. An Intercomparison of Vegetation Products from Satellite-based Observations used for Soil Moisture Retrievals

    Science.gov (United States)

    Vreugdenhil, Mariette; de Jeu, Richard; Wagner, Wolfgang; Dorigo, Wouter; Hahn, Sebastian; Bloeschl, Guenter

    2013-04-01

    Vegetation and its water content affect active and passive microwave soil moisture retrievals and need to be taken into account in such retrieval methodologies. This study compares the vegetation parameterisation that is used in the TU-Wien soil moisture retrieval algorithm to other vegetation products, such as the Vegetation Optical Depth (VOD), Net Primary Production (NPP) and Leaf Area Index (LAI). When only considering the retrieval algorithm for active microwaves, which was developed by the TU-Wien, the effect of vegetation on the backscattering coefficient is described by the so-called slope [1]. The slope is the first derivative of the backscattering coefficient in relation to the incidence angle. Soil surface backscatter normally decreases quite rapidly with the incidence angle over bare or sparsely vegetated soils, whereas the contribution of dense vegetation is fairly uniform over a large range of incidence angles. Consequently, the slope becomes less steep with increasing vegetation. Because the slope is a derivate of noisy backscatter measurements, it is characterised by an even higher level of noise. Therefore, it is averaged over several years assuming that the state of the vegetation doesn't change inter-annually. The slope is compared to three dynamic vegetation products over Australia, the VOD, NPP and LAI. The VOD was retrieved from AMSR-E passive microwave data using the VUA-NASA retrieval algorithm and provides information on vegetation with a global coverage of approximately every two days [2]. LAI is defined as half the developed area of photosynthetically active elements of the vegetation per unit horizontal ground area. In this study LAI is used from the Geoland2 products derived from SPOT Vegetation*. The NPP is the net rate at which plants build up carbon through photosynthesis and is a model-based estimate from the BiosEquil model [3, 4]. Results show that VOD and slope correspond reasonably well over vegetated areas, whereas in arid

  17. 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).

  18. 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)

  19. Satellite Lithium-Ion Battery Remaining Cycle Life Prediction with Novel Indirect Health Indicator Extraction

    Directory of Open Access Journals (Sweden)

    Haitao Liao

    2013-07-01

    Full Text Available Prognostics and remaining useful life (RUL estimation for lithium-ion batteries play an important role in intelligent battery management systems (BMS. The capacity is often used as the fade indicator for estimating the remaining cycle life of a lithium-ion battery. For spacecraft requiring high reliability and long lifetime, in-orbit RUL estimation and reliability verification on ground should be carefully addressed. However, it is quite challenging to monitor and estimate the capacity of a lithium-ion battery on-line in satellite applications. In this work, a novel health indicator (HI is extracted from the operating parameters of a lithium-ion battery to quantify battery degradation. Moreover, the Grey Correlation Analysis (GCA is utilized to evaluate the similarities between the extracted HI and the battery’s capacity. The result illustrates the effectiveness of using this new HI for fading indication. Furthermore, we propose an optimized ensemble monotonic echo state networks (En_MONESN algorithm, in which the monotonic constraint is introduced to improve the adaptivity of degradation trend estimation, and ensemble learning is integrated to achieve high stability and precision of RUL prediction. Experiments with actual testing data show the efficiency of our proposed method in RUL estimation and degradation modeling for the satellite lithium-ion battery application.

  20. Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

    Science.gov (United States)

    Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

    2017-12-01

    In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields

  1. Dynamic Response of Satellite-Derived Vegetation Growth to Climate Change in the Three North Shelter Forest Region in China

    Directory of Open Access Journals (Sweden)

    Bin He

    2015-08-01

    Full Text Available Since the late 1970s, the Chinese government has initiated ecological restoration programs in the Three North Shelter Forest System Project (TNSFSP area. Whether accelerated climate change will help or hinder these efforts is still poorly understood. Using the updated and extended AVHRR NDVI3g dataset from 1982 to 2011 and corresponding climatic data, we investigated vegetation variations in response to climate change. The results showed that the overall state of vegetation in the study region has improved over the past three decades. Vegetation cover significantly decreased in 23.1% and significantly increased in 21.8% of the study area. An increase in all three main vegetation types (forest, grassland, and cropland was observed, but the trend was only statistically significant in cropland. In addition, bare and sparsely vegetated areas, mainly located in the western part of the study area, have significantly expanded since the early 2000s. A moisture condition analysis indicated that the study area experienced significant climate variations, with warm-wet conditions in the western region and warm-dry conditions in the eastern region. Correlation analysis showed that variations in the Normalized Difference Vegetation Index (NDVI were positively correlated with precipitation and negatively correlated with temperature. Ultimately, climate change influenced vegetation growth by controlling the availability of soil moisture. Further investigation suggested that the positive impacts of precipitation on NDVI have weakened in the study region, whereas the negative impacts from temperature have been enhanced in the eastern study area. However, over recent years, the negative temperature impacts have been converted to positive impacts in the western region. Considering the variations in the relationship between NDVI and climatic variables, the warm–dry climate in the eastern region is likely harmful to vegetation growth, whereas the warm

  2. Satellite remote sensing of submerged aquatic vegetation distribution and status in the Currituck Sound, NC.

    Science.gov (United States)

    2012-11-01

    Submerged Aquatic Vegetation (SAV) is an important component in any estuarine ecosystem. As such, it is regulated by federal and state agencies as a jurisdictional resource, where impacts to SAV are compensated through mitigation. Historically, tradi...

  3. 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.

  4. 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.

  5. Mapping Submerged Aquatic Vegetation Using RapidEye Satellite Data: The Example of Lake Kummerow (Germany

    Directory of Open Access Journals (Sweden)

    Christine Fritz

    2017-07-01

    Full Text Available Submersed aquatic vegetation (SAV is sensitive to changes in environmental conditions and plays an important role as a long-term indictor for the trophic state of freshwater lakes. Variations in water level height, nutrient condition, light availability and water temperature affect the growth and species composition of SAV. Detailed information about seasonal variations in littoral bottom coverage are still unknown, although these effects are expected to mask climate change-related long-term changes, as derived by snapshots of standard monitoring methods included in the European Water Framework Directive. Remote sensing offers concepts to map SAV quickly, within large areas, and at short intervals. This study analyses the potential of a semi-empirical method to map littoral bottom coverage by a multi-seasonal approach. Depth-invariant indices were calculated for four Atmospheric & Topographic Correction (ATCOR2 atmospheric corrected RapidEye data sets acquired at Lake Kummerow, Germany, between June and August 2015. RapidEye data evaluation was supported by in situ measurements of the diffuse attenuation coefficient of the water column and bottom reflectance. The processing chain was able to differentiate between SAV and sandy sediment. The successive increase of SAV coverage from June to August was correctly monitored. Comparisons with in situ and Google Earth imagery revealed medium accuracies (kappa coefficient = 0.61, overall accuracy = 72.2%. The analysed time series further revealed how water constituents and temporary surface phenomena such as sun glint or algal blooms influence the identification success of lake bottom substrates. An abundant algal bloom biased the interpretability of shallow water substrate such that a differentiation of sediments and SAV patches failed completely. Despite the documented limitations, mapping of SAV using RapidEye seems possible, even in eutrophic lakes.

  6. 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

  7. 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.

  8. 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.

  9. Satellite Monitoring of Vegetation Response to Precipitation and Dust Storm Outbreaks in Gobi Desert Regions

    Directory of Open Access Journals (Sweden)

    Yuki Sofue

    2018-02-01

    Full Text Available Recently, droughts have become widespread in the Northern Hemisphere, including in Mongolia. The ground surface condition, particularly vegetation coverage, affects the occurrence of dust storms. The main sources of dust storms in the Asian region are the Taklimakan and Mongolian Gobi desert regions. In these regions, precipitation is one of the most important factors for growth of plants especially in arid and semi-arid land. The purpose of this study is to clarify the relationship between precipitation and vegetation cover dynamics over 29 years in the Gobi region. We compared the patterns between precipitation and Normalized Difference Vegetation Index (NDVI for a period of 29 years. The precipitation and vegetation datasets were examined to investigate the trends during 1985–2013. Cross correlation analysis between the precipitation and the NDVI anomalies was performed. Data analysis showed that the variations of NDVI anomalies in the east region correspond well with the precipitation anomalies during this period. However, in the southwest region of the Gobi region, the NDVI had decreased regardless of the precipitation amount, especially since 2010. This result showed that vegetation in this region was more degraded than in the other areas.

  10. Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

    Science.gov (United States)

    Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

    2016-09-01

    Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

  11. Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

    Science.gov (United States)

    Jeong, Su-Jong; Schimel, David; Frankenberg, Christian; Drewry, Darren T.; Fisher, Joshua B.; Verma, Manish; Berry, Joseph A.; Lee, Jung-Eun; Joiner, Joanna

    2016-01-01

    This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

  12. 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...

  13. 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

  14. Vegetation

    DEFF Research Database (Denmark)

    Epstein, H.E.; Walker, D.A.; Bhatt, U.S.

    2012-01-01

    increased 20-26%. • Increasing shrub growth and range extension throughout the Low Arctic are related to winter and early growing season temperature increases. Growth of other tundra plant types, including graminoids and forbs, is increasing, while growth of mosses and lichens is decreasing. • Increases...... in vegetation (including shrub tundra expansion) and thunderstorm activity, each a result of Arctic warming, have created conditions that favor a more active Arctic fire regime....

  15. How hazardous is the Sahara Desert crossing for migratory birds? Indications from satellite tracking of raptors

    Science.gov (United States)

    Strandberg, Roine; Klaassen, Raymond H. G.; Hake, Mikael; Alerstam, Thomas

    2010-01-01

    We investigated the risk associated with crossing the Sahara Desert for migrating birds by evaluating more than 90 journeys across this desert by four species of raptors (osprey Pandion haliaetus, honey buzzard Pernis apivorus, marsh harrier Circus aeruginosus and Eurasian hobby Falco subbuteo) recorded by satellite telemetry. Forty per cent of the crossings included events of aberrant behaviours, such as abrupt course changes, slow travel speeds, interruptions, aborted crossings followed by retreats from the desert and failed crossings due to death, indicating difficulties for the migrants. The mortality during the Sahara crossing was 31 per cent per crossing attempt for juveniles (first autumn migration), compared with only 2 per cent for adults (autumn and spring combined). Mortality associated with the Sahara passage made up a substantial fraction (up to about half for juveniles) of the total annual mortality, demonstrating that this passage has a profound influence on survival and fitness of migrants. Aberrant behaviours resulted in late arrival at the breeding grounds and an increased probability of breeding failure (carry-over effects). This study also demonstrates that satellite tracking can be a powerful method to reveal when and where birds are exposed to enhanced risk and mortality during their annual cycles. PMID:19955169

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

    Directory of Open Access Journals (Sweden)

    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.

  17. 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.

  18. Discrimination of Vegetation Height Categories With Passive Satellite Sensor Imagery Using Texture Analysis

    NARCIS (Netherlands)

    Petrou, Z.; Manakos, I.; Stathaki, T.; Mücher, C.A.; Adamo, M.

    2015-01-01

    Vegetation height is a crucial factor in environmental studies, landscape analysis, and mapping applications. Its estimation may prove cost and resource demanding, e.g., employing light detection and ranging (LiDAR) data. This study presents a cost-effective framework for height estimation, built

  19. 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.

  20. 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

  1. Mapping Aquatic Vegetation in a Tropical Wetland Using High Spatial Resolution Multispectral Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Timothy G. Whiteside

    2015-09-01

    Full Text Available Vegetation plays a key role in the environmental function of wetlands. The Ramsar-listed wetlands of the Magela Creek floodplain in Northern Australia are identified as being at risk from weeds, fire and climate change. In addition, the floodplain is a downstream receiving environment for the Ranger Uranium Mine. Accurate methods for mapping wetland vegetation are required to provide contemporary baselines of annual vegetation dynamics on the floodplain to assist with analysing any potential change during and after minesite rehabilitation. The aim of this study was to develop and test the applicability of geographic object-based image analysis including decision tree classification to classify WorldView-2 imagery and LiDAR-derived ancillary data to map the aquatic vegetation communities of the Magela Creek floodplain. Results of the decision tree classification were compared against a Random Forests classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010. The decision tree classification method provided an overall accuracy of 78% which was significantly higher than the overall accuracy of the Random Forests classification (67%. Most of the error in both classifications was associated with confusion between spectrally similar classes dominated by grasses, such as Hymenachne and Pseudoraphis. In addition, the extent of the sedge Eleocharis was under-estimated in both cases. This suggests the method could be useful for mapping wetlands where statistical-based supervised classifications have achieved less than satisfactory results. Based upon the results, the decision tree method will form part of an ongoing operational monitoring program.

  2. Demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data

    Science.gov (United States)

    Butera, M. K.

    1979-01-01

    The success of remotely mapping wetland vegetation of the southwestern coast of Florida is examined. A computerized technique to process aircraft and LANDSAT multispectral scanner data into vegetation classification maps was used. The cost effectiveness of this mapping technique was evaluated in terms of user requirements, accuracy, and cost. Results indicate that mangrove communities are classified most cost effectively by the LANDSAT technique, with an accuracy of approximately 87 percent and with a cost of approximately 3 cent per hectare compared to $46.50 per hectare for conventional ground survey methods.

  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. Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations

    Directory of Open Access Journals (Sweden)

    Chiara Corbari

    2017-11-01

    Full Text Available The Food and Agricultural Organization (FAO method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data.

  5. Assessing Crop Coefficients for Natural Vegetated Areas Using Satellite Data and Eddy Covariance Stations.

    Science.gov (United States)

    Corbari, Chiara; Ravazzani, Giovanni; Galvagno, Marta; Cremonese, Edoardo; Mancini, Marco

    2017-11-18

    The Food and Agricultural Organization (FAO) method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data.

  6. Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data.

    Science.gov (United States)

    Patel, N R; Parida, B R; Venus, V; Saha, S K; Dadhwal, V K

    2012-12-01

    The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T (s)) from MODIS 8-day composite data during cloud-free period (September-October) were adopted to construct an NDVI-T (s) space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.

  7. The 2005 and 2012 major drought events in Iberia: monitoring vegetation dynamics and crop yields using satellite data.

    Science.gov (United States)

    Gouveia, Célia M.; Trigo, Ricardo M.

    2014-05-01

    The Iberian Peninsula is recurrently affected by drought episodes and therefore by the adverse effects associated that range from severe water shortages to economic losses and related social impacts. During the hydrological years of 2004/2005 and 2011/2012, Iberia was hit by two of the worst drought episodes ever recording in this semi-arid region (Garcia-Herrera at al., 2007; Trigo et al., 2013). These two drought episodes were extreme in both its magnitude and spatial extent. A tendency towards a drier Mediterranean for the period 1970-2010 in comparison with 1901-70 has been identified (Hoerling et al., 2012), reinforcing the need for a continuous monitoring of vegetation stress and reliable estimates of the drought impacts. The strong effect of water scarcity on vegetation dynamics is well documented in Mediterranean and other semi-arid regions. Despite the usual link established between the decrease of vegetation greenness and the lack of precipitation during a considerably long period, the impact on vegetation activity may be amplified by other climatic anomalies, such as high temperature, high wind, and low relative humidity. The recent availability of consistent satellite imagery covering large regions over long periods of time has progressively reinforced the role of remote sensing in environmental studies, in particular in those related to drought episodes (e.g. Gouveia et al., 2009). The aim of the present work is to assess and monitor the cumulative impact over time of drought conditions on vegetation over Iberian Peninsula. For this purpose we have used the regional fields of the Normalized Difference Vegetation Index (NDVI) as obtained from the VEGETATION-SPOT5 instrument, from 1999 to 2013. The entire 15-yr long period was analysed, but particular attention was devoted to the two extreme drought episodes of 2004-2005 and 2011-2012. During the hydrological years of 2004-2005 and 2011-2012 drought episodes negative anomalies of NDVI were observed over

  8. Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

    Science.gov (United States)

    Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

    2017-12-01

    Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and

  9. Monitoring Corals and Submerged Aquatic Vegetation in Western Pacific Using Satellite Remote Sensing Integrated with Field Data

    Science.gov (United States)

    Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.

    2013-12-01

    Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to

  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. LAND SURFACE TEMPERATURES ESTIMATED ON GROUNDOBSERVED DATA AND SATELLITE IMAGES, DURING THE VEGETATION PERIOD IN THE OLTENIA PLAIN

    Directory of Open Access Journals (Sweden)

    ONŢEL IRINA

    2015-03-01

    Full Text Available The purpose of this study is to analyze the land surface temperatures by using climatological and remote sensing data during the vegetation period in the Oltenia Plain. The data used in this study refer both to climatological data (namely monthly and seasonal air and soil temperatures, and to remote sensing data delivered by MODIS Land Surface Temperature (LST, with a spatial resolution of 1 km. The analyzed period spans from 2000 to 2013 and the vegetation period considered is April-September. As main results, there were observed four years with high temperatures, namely 2000 (20.4oC-air T, 24.6oC soil T, and 26oC LST, 2003 (20.2oC air T, 23.9oC soil T and 24.5oC LST, 2007 (20.5oC air T, 24.3oC soil T and 25oC LST and 2012 (21.3oC air T, 25.7oC soil T and 26.5oC LST. The correlations between air temperature, soil temperature and LST were statisticaly significant. The diference between air temperature and soil temperature values ranked within 3-4oC, while the difference between soil temperature and land surface temperature obtained from MODIS images was about 0.8oC. Spatially, the highest temperatures were recorded on the Leu-Rotunda Field, the Caracal Plain and the Nedeia Field, and pretty high variations of observed temperatures seemed to depend on vegetation cover. The MODIS images represent one of the most important types of satellite data available for free, which can be successfully used in determining the climatic parameters and can help to predict the changes in plant activity, due to weather phenomena.

  12. Normalized difference vegetation index for the South American continent used as a climatic variability indicator

    International Nuclear Information System (INIS)

    Liu, W.T.; Massambani, O.; Festa, M.

    1992-01-01

    The NOAA AVHRR GAC data set was used to produce Normalized Difference Vegetation Index (NDVI) maps for the South American Continent covering the period from August 1, 1981 to June 30, 1987. A 15-day maximum value composite procedure was used to partially eliminate the cloud contamination and atmospheric attenuation. Monthly evolution of NDVI for a dry and a wet year within the period studied was used to estimate the area covered by NDVI value less than 0.223, This value was used as an indicator of the drought area and the delineation of the Low rainfall areas in the continent. It was observed a well defined regional dependence of the drought area variability for the Northeast, Southwest and Northwest continent and also for the Amazon region. It is shown a relative estimation of the area coverage with NDVI less than 0.223 for the years 1982/83 and 1984/85. The dynamics of the drought area evolution in the continent is discussed. It is also presented a diagnosis of regional variability of the continental distribution of drought area from 1981 to 1987 for the months of May and September. This information is also used to discuss its relationship with the EL-Nino-Southern Oscillation (ENSO) and the South American Precipitation patterns during this period. It is suggested that the use of NDVI image to identify the dynamics of the drought induced by low rainfall may provide us valuable information to study the large scale climatic variation

  13. Understanding the relationship between vegetation phenology and productivity across key dryland ecosystem types through the integration of PhenoCam, satellite, and eddy covariance data

    Science.gov (United States)

    Yan, D.; Scott, R. L.; Moore, D. J.; Biederman, J. A.; Smith, W. K.

    2017-12-01

    Land surface phenology (LSP) - defined as remotely sensed seasonal variations in vegetation greenness - is intrinsically linked to seasonal carbon uptake, and is thus commonly used as a proxy for vegetation productivity (gross primary productivity; GPP). Yet, the relationship between LSP and GPP remains uncertain, particularly for understudied dryland ecosystems characterized by relatively large spatial and temporal variability. Here, we explored the relationship between LSP and the phenology of GPP for three dominant dryland ecosystem types, and we evaluated how these relationships change as a function of spatial and temporal scale. We focused on three long-term dryland eddy covariance flux tower sites: Walnut Gulch Lucky Hills Shrubland (WHS), Walnut Gulch Kendall Grassland (WKG), and Santa Rita Mesquite (SRM). We analyzed daily canopy-level, 16-day 30m, and 8-day 500m time series of greenness indices from PhenoCam, Landsat 7 ETM+/Landsat 8 OLI, and MODIS, respectively. We first quantified the impact of spatial scale by temporally resampling canopy-level PhenoCam, 30m Landsat, and 500m MODIS to 16-day intervals and then comparing against flux tower GPP estimates. We next quantified the impact of temporal scale by spatially resampling daily PhenoCam, 16-day Landsat, and 8-day MODIS to 500m time series and then comparing against flux tower GPP estimates. We find evidence of critical periods of decoupling between LSP and the phenology of GPP that vary according to the spatial and temporal scale, and as a function of ecosystem type. Our results provide key insight into dryland LSP and GPP dynamics that can be used in future efforts to improve ecosystem process models and satellite-based vegetation productivity algorithms.

  14. 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.

  15. 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

  16. Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change.

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    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.

  17. Monitoring and Assessing the 2012 Drought in the Great Plains: Analyzing Satellite-Retrieved Solar-Induced Chlorophyll Fluorescence, Drought Indices, and Gross Primary Production

    Directory of Open Access Journals (Sweden)

    Siheng Wang

    2016-01-01

    Full Text Available We examined the relationship between satellite measurements of solar-induced chlorophyll fluorescence (SIF and several meteorological drought indices, including the multi-time-scale standard precipitation index (SPI and the Palmer drought severity index (PDSI, to evaluate the potential of using SIF to monitor and assess drought. We found significant positive relationships between SIF and drought indices during the growing season (from June to September. SIF was found to be more sensitive to short-term SPIs (one or two months and less sensitive to long-term SPI (three months than were the normalized difference vegetation index (NDVI or the normalized difference water index (NDWI. Significant correlations were found between SIF and PDSI during the growing season for the Great Plains. We found good consistency between SIF and flux-estimated gross primary production (GPP for the years studied, and synchronous declines of SIF and GPP in an extreme drought year (2012. We used SIF to monitor and assess the drought that occurred in the Great Plains during the summer of 2012, and found that although a meteorological drought was experienced throughout the Great Plains from June to September, the western area experienced more agricultural drought than the eastern area. Meanwhile, SIF declined more significantly than NDVI during the peak growing season. Yet for senescence, during which time the reduction of NDVI still went on, the reduction of SIF was eased. Our work provides an alternative to traditional reflectance-based vegetation or drought indices for monitoring and assessing agricultural drought.

  18. Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher

    2013-01-01

    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

  19. 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.

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

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    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

  1. 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.

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

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    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.

  3. 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.

  4. Evaluation of Above Ground Biomass Estimation Accuracy for Alpine Meadow Based on MODIS Vegetation Indices

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    Meng Bao-Ping

    2017-01-01

    Full Text Available Animal husbandry is the main agricultural type over the Tibetan Plateau, above ground biomass (AGB is very important to monitor the productivity for administration of grassland resources and grazing balance. The MODIS vegetation indices have been successfully used in numerous studies on grassland AGB estimation in the Tibetan Plateau area. However, there are considerable differences of AGB estimation models both in the form of the models and the accuracy of estimation. In this study, field measurements of AGB data at Sangke Town, Gansu Province, China in four years (2013-2016 and MODIS indices (NDVI and EVI are combined to construct AGB estimation models of alpine meadow grassland. The field measured AGB are also used to evaluate feasibility of models developed for large scale in applying to small area. The results show that (1 the differences in biomass were relatively large among the 5 sample areas of alpine meadow grassland in the study area during 2013-2016, with the maximum and minimum biomass values of 3,963 kg DW/ha and 745.5 kg DW/ha, respectively, and mean value of 1,907.7 kg DW/ha; the mean of EVI value range (0.42-0.60 are slightly smaller than the NDVI’s (0.59-0.75; (2 the optimum estimation model of grassland AGB in the study area is the exponential model based on MODIS EVI, with root mean square error of 656.6 kg DW/ha and relative estimation errors (REE of 36.3%; (3 the estimation errors of grassland AGB models previously constructed at different spatial scales (the Tibetan Plateau, the Gannan Prefecture, and Xiahe County are higher than those directly constructed based on the small area of this study by 9.5%–31.7%, with the increase of the modeling study area scales, the REE increasing as well. This study presents an improved monitoring algorithm of alpine natural grassland AGB estimation and provides a clear direction for future improvement of the grassland AGB estimation and grassland productivity from remote sensing

  5. A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE for Satellite-Based Actual Evapotranspiration Estimation

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    Hua Zhang

    2016-09-01

    Full Text Available The estimation of spatially-variable actual evapotranspiration (AET is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE, to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges. Compared to traditional triangle methods, TAVE introduces three unique features: (i the discretization of the domain as overlapping elevation zones; (ii a variable wet edge that is a function of elevation zone; and (iii variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA and a global AET product (MOD16 over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%, in contrast to substantial overestimation by TA (+234% and underestimation by MOD16 (−50%. In forested (non-irrigated, water consuming regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

  6. Angular Normalization of Ground and Satellite Observations of Sun-induced Chlorophyll Fluorescence for Assessing Vegetation Productivity

    Science.gov (United States)

    Chen, J. M.; He, L.; Chou, S.; Ju, W.; Zhang, Y.; Joiner, J.; Liu, J.; Mo, G.

    2017-12-01

    Sun-induced chlorophyll fluorescence (SIF) measured from plant canopies originates mostly from sunlit leaves. Observations of SIF by satellite sensors, such as GOME-2 and GOSAT, are often made over large view zenith angle ranges, causing large changes in the viewed sunlit leaf fraction across the scanning swath. Although observations made by OCO-2 are near nadir, the observed sunlit leaf fraction could still vary greatly due to changes in the solar zenith angle with latitude and time of overpass. To demonstrate the importance of considering the satellite-target-view geometry in using SIF for assessing vegetation productivity, we conducted multi-angle measurements of SIF using a hyperspectral sensor mounted on an automated rotating system over a rice field near Nanjing, China. A method is developed to separate SIF measurements at each angle into sunlit and shaded leaf components, and an angularly normalized canopy-level SIF is obtained as the weighted sum of sunlit and shaded SIF. This normalized SIF is shown to be a much better proxy of GPP of the rice field measured by an eddy covariance system than the unnormalized SIF observations. The same normalization scheme is also applied to the far-red GOME-2 SIF observations on sunny days, and we found that the normalized SIF is better correlated with model-simulated GPP than the original SIF observations. The coefficient of determination (R2) is improved by 0.07±0.04 on global average using the normalization scheme. The most significant improvement in R2 by 0.09±0.04 is found in deciduous broadleaf forests, where the observed sunlit leaf fraction is highly sensitive to solar zenith angle.

  7. 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.

  8. 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.)

  9. 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.

  10. VEGETATIVE PROVISION INDICATORS OF CARDIOVASCULAR SYSTEM AND PHYSICAL EFFICIENCY OF WOMEN ATHLET-SPRINTERS

    Directory of Open Access Journals (Sweden)

    M. V. Didenko

    2014-02-01

    Full Text Available In recent decades there has been a significant increase in physical activity during the preparation of qualified athletes-sprinters. However, it is clear that a simple increase in volume and intensity of training loads in preparation can not be infinite. Russian sport trainers see tactics mistakes. Some authors consider that optimum technique construction of training is possible when taking into account normalizing the volume and load intensity based on the types of circulation (TC. The aim of work was to study the bioelectrical activity of the heart, heart rate variability (HRV, central hemodynamics and physical performance (PP in sportswomen-sprinters qualifications from II-III level to HMS. Materials and research methods. Carried out a comprehensive survey of 30 sportswomen-sprinters, qualifications from II-III level to HMS. For the analysis of vegetative cardiovascular regulation mathematical methods of HRV were used. Central hemodynamics were studied by automated tetrapolar rheography. Determination of PP was performed by using a submaximal cycle ergometer test PWC170. The index of the functional state (IFC was counted on a formula suggested and patented by us. Results of research. The correct sinus rhythm is found in all sportswomen with sufficient voltage and not rejected electrical axis of the heart. Comparison of the mean values of HRV showed the presence in all groups of runners prevalence of a parasympathetic link of VNS. At sportswomen-sprinters qualifications MS-HMS had prevailed hypokinetic TC and the lowering of qualifications the ratio of TC varied: as a runner of qualification I level prevailed eukinetic TC, while the runners of qualifications II-III level has have appeared sportswomen-sprinters with hyperkinetic TC. PP was bigger in sprinters qualifications MS-HMS and tended to decrease with decreasing of the qualifications. Correlation analysis revealed a positive correlation between SI and CI, negative – between the CI and

  11. 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.

  12. Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

    Science.gov (United States)

    Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

    2017-05-01

    Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.

  13. Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

    Directory of Open Access Journals (Sweden)

    MARIA IOANA VLAD

    2011-01-01

    Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

  14. Satellite-based monitoring of tropical seagrass vegetation: current techniques and future developments

    NARCIS (Netherlands)

    Ferwerda, J.G.; Leeuw, de J.; Atzberger, C.; Vekerdy, Z.

    2007-01-01

    Decline of seagrasses has been documented in many parts of the world. Reduction in water clarity, through increased turbidity and increased nutrient concentrations, is considered to be the primary cause of seagrass loss. Recent studies have indicated the need for new methods that will enable early

  15. 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.

  16. 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.

  17. Assessment of Land Use-Cover Changes and Successional Stages of Vegetation in the Natural Protected Area Altas Cumbres, Northeastern Mexico, Using Landsat Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Uriel Jeshua Sánchez-Reyes

    2017-07-01

    Full Text Available Loss of vegetation cover is a major factor that endangers biodiversity. Therefore, the use of geographic information systems and the analysis of satellite images are important for monitoring these changes in Natural Protected Areas (NPAs. In northeastern Mexico, the Natural Protected Area Altas Cumbres (NPAAC represents a relevant floristic and faunistic patch on which the impact of loss of vegetation cover has not been assessed. This work aimed to analyze changes of land use and coverage (LULCC over the last 42 years on the interior and around the exterior of the area, and also to propose the time of succession for the most important types of vegetation. For the analysis, LANDSAT satellite images from 1973, 1986, 2000, 2005 and 2015 were used, they were classified in seven categories through a segmentation and maximum likelihood analysis. A cross-tabulation analysis was performed to determine the succession gradient. Towards the interior of the area, a significant reduction of tropical vegetation and, to a lesser extent, temperate forests was found, as well as an increase in scrub cover from 1973 to 2015. In addition, urban and vegetation-free areas, as well as modified vegetation, increased to the exterior. Towards the interior of the NPA, the processes of perturbation and recovery were mostly not linear, while in the exterior adjacent area, the presence of secondary vegetation with distinct definite time of succession was evident. The analysis carried out is the first contribution that evaluates LULCC in this important NPA of northeastern Mexico. Results suggest the need to evaluate the effects of these modifications on species.

  18. Comparative Analysis of Diversity and Similarity Indices with Special Relevance to Vegetations around Sewage Drains

    OpenAIRE

    Ekta Singh

    2012-01-01

    Indices summarizing community structure are used to evaluate fundamental community ecology, species interaction, biogeographical factors, and environmental stress. Some of these indices are insensitive to gross community changes induced by contaminants of pollution. Diversity indices and similarity indices are reviewed considering their ecological application, both theoretical and practical. For some useful indices, empirical equations are given to calculate the expected ...

  19. 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.

  20. Long-term energy balance and vegetation water stress monitoring of Mediterranean oak savanna using satellite thermal data

    Science.gov (United States)

    González-Dugo, Maria P.; Chen, Xuelong; Andreu, Ana; Carpintero, Elisabet; Gómez-Giraldez, Pedro; Su, Z.(Bob)

    2017-04-01

    Drought is one of the major hazards faced by natural and cropped vegetation in the Mediterranean Sea Basin. Water scarcity is likely to be worsened under the predicted conditions of climate change, which is expected to make this region both warmer and drier. A Holm oak savanna, known as dehesa in Spain and montado in Portugal, is an agro-silvo-pastoral system occupying more than 3 million hectares the Iberian Peninsula and Greece. It consists of widely-spaced oak trees (mostly Quercus ilex L.), combined with crops, pasture and Mediterranean shrubs. This ecosystem is considered an example of sustainable land use, supporting a large number of species and diversity of habitats and for its importance in rural economy. A similar ecosystem is worldwide distributed in areas with Mediterranean climate (as California or South Africa) and shares structural and functional properties with tropical savannas in Africa, Australia and South America. Remote sensing time series can assist the monitoring of the energy balance components, with special attention to the evapotranspiration and vegetation water stress over these areas. Long-term data analysis may improve our understanding of the functioning of the system, helping to assess drought impacts and leading to reduce the economic and environmental vulnerability of this ecosystem. This work analyzes the evolution the surface energy balance components, mapping the evapotranspiration and moisture stress of holm oak woodlands of Spain and Portugal during the last 15 years (2001-2015). The surface energy balance model (SEBS) has been applied over the Iberian Peninsula on a monthly time scale and 0.05° spatial resolution, using multi-satellite and meteorological forcing data. Modelled energy and water fluxes have been validated using ground measurements of two eddy covariance towers located in oak savanna sites during 3 years, resulting in moderate deviations from observations (10-25 W/m2). The departure of actual ET from the

  1. Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

    2017-04-01

    The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of

  2. 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

  3. Detecting inter-annual variability in the phenological characteristics of southern Africa’s vegetation using satellite imagery

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2011-01-01

    Full Text Available provides consistent measurements of vegetation greenness which captures phenological cycles and vegetation function. Understanding the inter-annual variability in phenology is imperative, as phenological changes will be one of the first signs of the impact...

  4. 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

  5. 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.

  6. 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.

  7. Estimating carbon dioxide fluxes from temperate mountain grasslands using broad-band vegetation indices

    Directory of Open Access Journals (Sweden)

    G. Wohlfahrt

    2010-02-01

    Full Text Available The broad-band normalised difference vegetation index (NDVI and the simple ratio (SR were calculated from measurements of reflectance of photosynthetically active and short-wave radiation at two temperate mountain grasslands in Austria and related to the net ecosystem CO2 exchange (NEE measured concurrently by means of the eddy covariance method. There was no significant statistical difference between the relationships of midday mean NEE with narrow- and broad-band NDVI and SR, measured during and calculated for that same time window, respectively. The skill of broad-band NDVI and SR in predicting CO2 fluxes was higher for metrics dominated by gross photosynthesis and lowest for ecosystem respiration, with NEE in between. A method based on a simple light response model whose parameters were parameterised based on broad-band NDVI allowed to improve predictions of daily NEE and is suggested to hold promise for filling gaps in the NEE time series. Relationships of CO2 flux metrics with broad-band NDVI and SR however generally differed between the two studied grassland sites indicting an influence of additional factors not yet accounted for.

  8. 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.

  9. The use of remotely-sensed snow, soil moisture and vegetation indices to develop resilience to climate change in Kazakhstan

    Science.gov (United States)

    Saidaliyeva, Zarina; Davenport, Ian; Nobakht, Mohamad; White, Kevin; Shahgedanova, Maria

    2017-04-01

    Kazakhstan is a major producer of grain. Large scale grain production dominates in the north, making Kazakhstan one of the largest exporters of grain in the world. Agricultural production accounts for 9% of the national GDP, providing 25% of national employment. The south relies on grain production from household farms for subsistence, and has low resilience, so is vulnerable to reductions in output. Yields in the south depend on snowmelt and glacier runoff. The major limit to production is water supply, which is affected by glacier retreat and frequent droughts. Climate change is likely to impact all climate drivers negatively, leading to a decrease in crop yield, which will impact Kazakhstan and countries dependent on importing its produce. This work makes initial steps in modelling the impact of climate change on crop yield, by identifying the links between snowfall, soil moisture and agricultural productivity. Several remotely-sensed data sources are being used. The availability of snowmelt water over the period 2010-2014 is estimated by extracting the annual maximum snow water equivalent (SWE) from the Globsnow dataset, which assimilates satellite microwave observations with field observations to produce a spatial map. Soil moisture over the period 2010-2016 is provided by the ESA Soil Moisture and Ocean Salinity (SMOS) mission. Vegetation density is approximated by the Normalised Difference Vegetation Index (NDVI) produced from NASA's MODIS instruments. Statistical information on crop yields is provided by the Ministry of National Economy of the Republic of Kazakhstan Committee on Statistics. Demonstrating the link between snowmelt yield and agricultural productivity depends on showing the impact of snow mass during winter on remotely-sensed soil moisture, the link between soil moisture and vegetation density, and finally the link between vegetation density and crop yield. Soil moisture maps were extracted from SMOS observations, and resampled onto a 40km x

  10. Satellite and ground-based analysis of the effects on vegetation of continuous SO2 degassing at Turrialba volcano (Costa Rica) and its application to hazard management

    Science.gov (United States)

    Tortini, R.; van Manen, S. M.; Burson, B.; Carn, S. A.

    2014-12-01

    Turrialba is an active stratovolcano located 35 km northeast of San Jose, Costa Rica's capital city and socioeconomic hub. After over 100 years of quiescence Turrialba resumed activity in 1996 progressively increasing its degassing and seismic activity, showing continuous gas emissions since 2007. Intermittent phreatic explosions with ash emissions that have reached the capital have occurred since 2010. This activity has resulted in the temporary evacuation of two villages, closure of the National Park that comprises the summit region of the volcano and devastation of the local ecosystem. We combined a variety of satellite-based time series with ground-based measurements of ambient gas concentrations, element deposition and surveys of species richness to enable a comprehensive assessment of SO2 emissions and changes in vegetation. Satellite-based time-series were obtained from Landsat ETM+, Terra ASTER, Terra/Aqua MODIS and Aura OMI, with some of the data dating back to 2000. From 2007-2010 we observed emissions of SO2 and loss of vegetation healthiness (i.e. decrease of EVI2) downwind of the vents. From 2010 onwards these stabilized, but we observe an apparent decrease in agriculture. Other multi-temporal products, such as the ALOS PALSAR FNF data, confirm our observations. The exposure to the volcanic plume resulted in high soil acidity and significant uptake of certain heavy metals by vegetation; in contrast other elements are leached from the soil as a result of the acid deposition. These factors are likely to be responsible for decreased species richness and physiological damage observed at Turrialba. Our study shows ecological impacts, in terms of soil characteristics, vegetation composition and diversity and physiological damage of vegetation, which all correlate to fumigation by Turrialba's plume. Analyzing and relating the remote observations to conditions and impacts on the ground provides a better understanding of volcanic degassing, its impacts on

  11. 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.

  12. Satellite assessment of early-season forecasts for vegetation conditions of grazing allotments in Nevada, United States

    Science.gov (United States)

    Fifteen years of enhanced vegetation index data from the MODIS sensor are examined in conjunction with precipitation and the Palmer drought severity index to assess how well growing season conditions for vegetation within grazing allotments of Nevada can be predicted at different times of the year. ...

  13. Epiphytic vegetation of Populus balsamifera and its significance as an air pollution indicator in Sudbury, Ontario

    Energy Technology Data Exchange (ETDEWEB)

    Leblanc, F; Rao, D N; Comeau, G

    1972-01-01

    Indices of atmospheric purity (IAP) of 31 sites, selected in the SO/sub 2/-polluted as well as in the nonpolluted areas around Sudbury were determined on the basis of number, frequency-coverage, and resistance factor of the epiphytes of Populus balsamifera. Based on these indices, arranged into convenient ranges, the investigated area was delimited into five different IAP zones. These zones were then compared with SO/sub 2/ pollution zones based on the ground-level average concentration of the gas prevailing in the area. From this comparison it is clear that the biological method provides a valid, quick, and economical way for assessing and mapping the long-range effect of pollution of a given area.

  14. 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.

  15. Comparison of ground based indices (API and AQI) with satellite based aerosol products.

    Science.gov (United States)

    Zheng, Sheng; Cao, Chun-Xiang; Singh, Ramesh P

    2014-08-01

    Air quality in mega cities is one of the major concerns due to serious health issues and its indirect impact to the climate. Among mega cities, Beijing city is considered as one of the densely populated cities with extremely poor air quality. The meteorological parameters (wind, surface temperature, air temperature and relative humidity) control the dynamics and dispersion of air pollution. China National Environmental Monitoring Centre (CNEMC) started air pollution index (API) as of 2000 to evaluate air quality, but over the years, it was felt that the air quality is not well represented by API. Recently, the Ministry of Environmental Protection (MEP) of the People's Republic of China (PRC) started using a new index "air quality index (AQI)" from January 2013. We have compared API and AQI with three different MODIS (MODIS - Moderate Resolution Imaging SpectroRadiometer, onboard the Terra/Aqua satellites) AOD (aerosol optical depth) products for ten months, January-October, 2013. The correlation between AQI and Aqua Deep Blue AOD was found to be reasonably good as compared with API, mainly due to inclusion of PM2.5 in the calculation of AQI. In addition, for every month, the correlation coefficient between AQI and Aqua Deep Blue AOD was found to be relatively higher in the month of February to May. According to the monthly average distribution of precipitation, temperature, and PM10, the air quality in the months of June-September was better as compared to those in the months of February-May. AQI and Aqua Deep Blue AOD show highly polluted days associated with dust event, representing true air quality of Beijing. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

    Science.gov (United States)

    Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2010-05-01

    The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

  17. Detecting robust signals of interannual variability of gross primary productivity in Asia from multiple terrestrial carbon cycle models and long-term satellite-based vegetation data

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.

    2014-12-01

    Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently

  18. 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

  19. 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.

  20. Seasonal dynamics of surface chlorophyll concentration and sea surface temperature, as indicator of hydrological structure of the ocean (by satellite data)

    Science.gov (United States)

    Shevyrnogov, Anatoly; Vysotskaya, Galina

    Continuous monitoring of phytopigment concentrations and sea surface temperature in the ocean by space-borne methods makes possible to estimate ecological condition of biocenoses in critical areas. Unlike land vegetation, hydrological processes largely determine phytoplank-ton dynamics, which may be either recurrent or random. The types of chlorophyll concentration dynamics and sea surface temperature can manifest as zones quasistationary by seasonal dynamics, quasistationary areas (QSA). In the papers of the authors (A. Shevyrnogov, G. Vysotskaya, E. Shevyrnogov, A study of the stationary and the anomalous in the ocean surface chlorophyll distribution by satellite data. International Journal of Remote Sensing, Vol. 25, No.7-8, pp. 1383-1387, April 2004 & A. P. Shevyrnogov, G. S. Vysotskaya, J. I. Gitelson, Quasistationary areas of chlorophyll concentra-tion in the world ocean as observed satellite data Advances in Space Research, Volume 18, Issue 7, Pages 129-132, 1996) existence of zones, which are quasi-stationary with similar seasonal dynamics of chlorophyll concentration at surface layer of ocean, was shown. Results were obtained on the base of processing of time series of satellite images SeaWiFS. It was shown that fronts and frontal zones coincide with dividing lines between quasi-stationary are-as, especially in areas of large oceanic streams. To study the dynamics of the ocean for the period from 1985 through 2012 we used data on the temperature of the surface layer of the ocean and chlorophyll concentration (AVHRR, SeaWiFS and MODIS). Biota of surface oceanic layer is more stable in comparison with quickly changing surface tem-perature. It gives a possibility to circumvent influence of high-frequency component (for exam-ple, a diurnal cycle) in investigation of dynamics of spatial distribution of surface streams. In addition, an analyses of nonstable ocean productivity phenomena, stood out time series of satellite images, showed existence of areas with

  1. Modeling water and heat balance components of large territory for vegetation season using information from polar-orbital and geostationary meteorological satellites

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2015-04-01

    To date, physical-mathematical modeling processes of land surface-atmosphere interaction is considered to be the most appropriate tool for obtaining reliable estimates of water and heat balance components of large territories. The model of these processes (Land Surface Model, LSM) developed for vegetation period is destined for simulating soil water content W, evapotranspiration Ev, vertical latent LE and heat fluxes from land surface as well as vertically distributed soil temperature and moisture, soil surface Tg and foliage Tf temperatures, and land surface skin temperature (LST) Ts. The model is suitable for utilizing remote sensing data on land surface and meteorological conditions. In the study these data have been obtained from measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/geostationary satellites Meteosat-9, -10 (MSG-2, -3). The heterogeneity of the land surface and meteorological conditions has been taken into account in the model by using soil and vegetation characteristics as parameters and meteorological characteristics as input variables. Values of these characteristics have been determined from ground observations and remote sensing information. So, AVHRR data have been used to build the estimates of effective land surface temperature (LST) Ts.eff and emissivity E, vegetation-air temperature (temperature at the vegetation level) Ta, normalized vegetation index NDVI, vegetation cover fraction B, the leaf area index LAI, and precipitation. From MODIS data the values of LST Tls, Å, NDVI, LAI have been derived. From SEVIRI data there have been retrieved Tls, E, Ta, NDVI, LAI and precipitation. All named retrievals covered the vast territory of the part of the agricultural Central Black Earth Region located in the steppe-forest zone of European Russia. This territory with coordinates 49°30'-54°N, 31°-43°E and a total area of 227,300 km2 has been chosen for investigation. It has been carried out for years 2009

  2. Effects of Salicylic acid and Humic acid on Vegetative Indices of Periwinkle (Catharanthus roseusL.

    Directory of Open Access Journals (Sweden)

    E. Chamani

    2016-07-01

    greatest impact on the number of pods. The results showed that treatment with 1000 mg/l salicylic acid and humic acid had the greatest effect on stem diameter. Conclusion: The results of this study indicated that low concentrations of salicylic acid increased plant height, the number of leaves, chlorophyll content and stomatal conductance, which can increase plant resistance against unfavorable environmental conditions. As a result, the plants treated with salicylic acid can be increased two driven in adverse environmental conditions. The treatment of humic acid by increasing the rate of photosynthesis and increases the amount of material available for plant growth. This increase can accelerate the growth of the main branch and side periwinkle plant medicinal plants and enhances the appearance of the plant.

  3. The 2010 Russian Drought Impact on Satellite Measurements of Solar-Induced Chlorophyll Fluorescence: Insights from Modeling and Comparisons with the Normalized Differential Vegetation Index (NDVI)

    Science.gov (United States)

    Yoshida, Y.; Joiner, J.; Tucker, C.; Berry, J.; Lee, J. -E.; Walker, G.; Reichle, R.; Koster, R.; Lyapustin, A.; Wang, Y.

    2015-01-01

    We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).

  4. Estimating soil moisture from 6.6 GHz dual polarization, and/or satellite derived vegetation index

    International Nuclear Information System (INIS)

    Ahmed, N.U.

    1995-01-01

    Eight and a half years (January 1979 to August 1987) of Scanning Multichannel Microwave Radiometer (SMMR) data taken at a frequency of 6.6 GHz for both day and night observations at both polarizations were processed, documented and used to study the relationship between brightness temperature (T(B)) and antecedent precipitation index (API) in a wide range of vegetation index (normalized difference vegetation index (NDVI) varies from 0.2 to 0.6) in the mid-west and southern United States. In general, this study validates the model structure for soil wetness developed by Choudhury and Golus. For NDVI greater than 0.45 the resultant microwave signal is substantially affected by the vegetation. The night-time observations by both polarizations gave a better correlation between T(B) and API. The horizontal polarization is more sensitive to vegetation. For the least and greatest vegetated areas, night-time observations by vertical polarization showed less scatter in the T(B) versus API relation. A non-linear model was developed for soil wetness using horizontal and vertical polarization and their difference. The estimate of error for this model is better than previous models, and can be used to obtain six levels of soil moisture. (author)

  5. Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences

    Energy Technology Data Exchange (ETDEWEB)

    Beck, Pieter S A; Goetz, Scott J, E-mail: pbeck@whrc.org [Woods Hole Research Center, 149 Woods Hole Road, Falmouth, MA 02540 (United States)

    2011-10-15

    To assess ongoing changes in high latitude vegetation productivity we compared spatiotemporal patterns in remotely sensed vegetation productivity in the tundra and boreal zones of North America and Eurasia. We compared the long-term GIMMS (Global Inventory Modeling and Mapping Studies) NDVI (Normalized Difference Vegetation Index) to the more recent and advanced MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI data set, and mapped circumpolar trends in a gross productivity metric derived from the former. We then analyzed how temporal changes in productivity differed along an evergreen-deciduous gradient in boreal Alaska, along a shrub cover gradient in Arctic Alaska, and during succession after fire in boreal North America and northern Eurasia. We find that the earlier reported contrast between trends of increasing tundra and decreasing boreal forest productivity has amplified in recent years, particularly in North America. Decreases in boreal forest productivity are most prominent in areas of denser tree cover and, particularly in Alaska, evergreen forest stands. On the North Slope of Alaska, however, increases in tundra productivity do not appear restricted to areas of higher shrub cover, which suggests enhanced productivity across functional vegetation types. Differences in the recovery of post-disturbance vegetation productivity between North America and Eurasia are described using burn chronosequences, and the potential factors driving regional differences are discussed.

  6. Satellite observations of high northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences

    International Nuclear Information System (INIS)

    Beck, Pieter S A; Goetz, Scott J

    2011-01-01

    To assess ongoing changes in high latitude vegetation productivity we compared spatiotemporal patterns in remotely sensed vegetation productivity in the tundra and boreal zones of North America and Eurasia. We compared the long-term GIMMS (Global Inventory Modeling and Mapping Studies) NDVI (Normalized Difference Vegetation Index) to the more recent and advanced MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI data set, and mapped circumpolar trends in a gross productivity metric derived from the former. We then analyzed how temporal changes in productivity differed along an evergreen-deciduous gradient in boreal Alaska, along a shrub cover gradient in Arctic Alaska, and during succession after fire in boreal North America and northern Eurasia. We find that the earlier reported contrast between trends of increasing tundra and decreasing boreal forest productivity has amplified in recent years, particularly in North America. Decreases in boreal forest productivity are most prominent in areas of denser tree cover and, particularly in Alaska, evergreen forest stands. On the North Slope of Alaska, however, increases in tundra productivity do not appear restricted to areas of higher shrub cover, which suggests enhanced productivity across functional vegetation types. Differences in the recovery of post-disturbance vegetation productivity between North America and Eurasia are described using burn chronosequences, and the potential factors driving regional differences are discussed.

  7. 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

  8. Satellite derived phenology of southern Africa for 1985-2000 and functional classification of vegetation based on phenometrics

    CSIR Research Space (South Africa)

    Steenkamp, K

    2009-05-01

    Full Text Available analyzed vegetation phenometrics across South Africa (SA) in order to characterize phenological patterns and their inter-annual variability. A second objective is to distinguish biomes and sub-biome “bioregions” based on functional patterns. The long term...

  9. Early drought detection by spectral analysis of satellite time series of precipitation and Normalized Difference Vegetation Index (NDVI)

    NARCIS (Netherlands)

    Van Hoek, Mattijn; Jia, Li; Zhou, J.; Zheng, Chaolei; Menenti, M.

    2016-01-01

    The time lag between anomalies in precipitation and vegetation activity plays a critical role in early drought detection as agricultural droughts are caused by precipitation shortages. The aim of this study is to explore a new approach to estimate the time lag between a forcing (precipitation)

  10. A simple model for yield prediction of rice based on vegetation index derived from satellite and AMeDAS data during ripening period

    International Nuclear Information System (INIS)

    Wakiyama, Y.; Inoue, K.; Nakazono, K.

    2003-01-01

    The present study was conducted to show a simple model for rice yield predicting by using a vegetation index (NDVI) derived from satellite and meteorological data. In a field experiment, the relationship between the vegetation index and radiation absorbed by the rice canopy was investigated from transplanting to maturity. Their correlation held. This result revealed that the vegetation index could be used as a measure of absorptance of solar radiation by rice canopy. NDVI multiplied by solar radiation (SR) every day was accumulated (Σ(SR·NDVI)) from the field experiment. Σ(SR·NDVI) was plotted against above ground dry matter. It was obvious that they had a strong relationship. Rice yield largely depends on solar radiation and air temperature during the ripening period. Air temperature affects dry matter production. Relationships between Y SR -1 (Y: rice yield, SR: solar radiation) and mean air temperature were investigated from meteorological data and statistical data on rice yield. There was an optimum air temperature, 21.3°C, for ripening. When it was near 21.3°C in the ripening period, the rice yield was higher. We proposed a simple model for yield prediction of rice based on these results. The model is composed with SR·NDVI and the optimum air temperature. Vegetation index was derived from 3 years, LANDSAT TM data in Toyama, Ishikawa, Fukui and Nagano prefectures at heading. The meteorological data was used from AMeDAS data. The model was described as follows: Y = 0.728 SR·NDVI−2.04(T−21.3) 2 + 282 (r 2 = 0.65, n = 43) where Y is rice yield (kg 10a -1 ), SR is solar radiation (MJ m -2 ) during the ripening period (from 10 days before heading to 30 days after heading), T is mean air temperature (°C) during the ripening period. RMSE was 33.7kg 10a -1 . The model revealed good precision. (author)

  11. Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery

    Science.gov (United States)

    Mitri, George H.; Gitas, Ioannis Z.

    2013-02-01

    Careful evaluation of forest regeneration and vegetation recovery after a fire event provides vital information useful in land management. The use of remotely sensed data is considered to be especially suitable for monitoring ecosystem dynamics after fire. The aim of this work was to map post-fire forest regeneration and vegetation recovery on the Mediterranean island of Thasos by using a combination of very high spatial (VHS) resolution (QuickBird) and hyperspectral (EO-1 Hyperion) imagery and by employing object-based image analysis. More specifically, the work focused on (1) the separation and mapping of three major post-fire classes (forest regeneration, other vegetation recovery, unburned vegetation) existing within the fire perimeter, and (2) the differentiation and mapping of the two main forest regeneration classes, namely, Pinus brutia regeneration, and Pinus nigra regeneration. The data used in this study consisted of satellite images and field observations of homogeneous regenerated and revegetated areas. The methodology followed two main steps: a three-level image segmentation, and, a classification of the segmented images. The process resulted in the separation of classes related to the aforementioned objectives. The overall accuracy assessment revealed very promising results (approximately 83.7% overall accuracy, with a Kappa Index of Agreement of 0.79). The achieved accuracy was 8% higher when compared to the results reported in a previous work in which only the EO-1 Hyperion image was employed in order to map the same classes. Some classification confusions involving the classes of P. brutia regeneration and P. nigra regeneration were observed. This could be attributed to the absence of large and dense homogeneous areas of regenerated pine trees in the study area.

  12. 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

  13. Pollen core assemblages as indicator of Polynesian and European impact on the vegetation cover of Auckland Isthmus catchment, New Zealand

    Science.gov (United States)

    Abrahim, Ghada M. S.; Parker, Robin J.; Horrocks, Mark

    2013-10-01

    Tamaki Estuary is an arm of the Hauraki Gulf situated on the eastern side of central Auckland. Over the last 100 years, Tamaki catchment has evolved from a nearly rural landscape to an urbanised and industrialised area. Pollen, 14C and glass shards analyses, were carried out on three cores collected along the estuary with the aim to reconstruct the estuary's history over the last ˜8000 years and trace natural and anthropogenic effects recorded in the sediments. Glass shard analysis was used to establish key tephra time markers such as the peralkaline eruption of Mayor Island, ˜6000 years BP. During the pre-Polynesian period (since at least 8000 years BP), regional vegetation was podocarp/hardwood forest dominated by Dacrydium cupressinun, Prumnopits taxifolia, and Metrosideros. Major Polynesian settler impact (commencing ˜700 yr BP) was associated with forest clearance as indicated by a sharp decline in forest pollen types. This coincided with an increase in bracken (Pteridium esculentum) spores and grass pollen. Continuing landscape disturbance during European settlement (commencing after 1840 AD) was accompanied by the distinctive appearance of exotic pollen taxa such as Pinus.

  14. Using VEGETATION satellite data and the crop model STICS-Prairie to estimate pasture production at the national level in France

    Science.gov (United States)

    Di Bella, C.; Faivre, R.; Ruget, F.; Seguin, B.

    In France, pastures constitute an important land cover type, sustaining principally husbandry production. The absence of low-cost methods applicable to large regions has conducted to the use of simulation models, as in the ISOP system. Remote sensing data may be considered as a potential tool to improve a correct diagnosis in a real time framework. Thirteen forage regions (FR) of France, differing in their soil, climatic and productive characteristics were selected for this purpose. SPOT4-VEGETATION images have been used to provide, using subpixel estimation models, the spectral signature corresponding to pure pasture conditions. This information has been related with some growth variables estimated by STICS-Prairie model (inside ISOP system). Beyond the good general agreement between the two types of data, we found that the best relations were observed between NDVI middle infrared based index (SWVI) and leaf area index. The results confirm the capacities of the satellite data to provide complementary productive variables and help to identify the spatial and temporal differences between satellite and model information, mainly during the harvesting periods. This could contribute to improve the evaluations of the model on a regional scale.

  15. Towards a more objective evaluation of modelled land-carbon trends using atmospheric CO2 and satellite-based vegetation activity observations

    Directory of Open Access Journals (Sweden)

    D. Dalmonech

    2013-06-01

    Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular the net land–atmosphere carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to better understand the reasons for this disagreement. Here, we develop an extension for existing benchmarking systems by making use of the complementary information contained in the observational records of atmospheric CO2 and remotely sensed vegetation activity to provide a novel set of diagnostics of ecosystem responses to climate variability in the last 30 yr at different temporal and spatial scales. The selection of observational characteristics (traits specifically considers the robustness of information given that the uncertainty of both data and evaluation methodology is largely unknown or difficult to quantify. Based on these considerations, we introduce a baseline benchmark – a minimum test that any model has to pass – to provide a more objective, quantitative evaluation framework. The benchmarking strategy can be used for any land surface model, either driven by observed meteorology or coupled to a climate model. We apply this framework to evaluate the offline version of the MPI Earth System Model's land surface scheme JSBACH. We demonstrate that the complementary use of atmospheric CO2 and satellite-based vegetation activity data allows pinpointing of specific model deficiencies that would not be possible by the sole use of atmospheric CO2 observations.

  16. Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

    Science.gov (United States)

    Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan

    2003-12-01

    explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.

  17. Sensitivity study of land biosphere CO2 exchange through an atmospheric tracer transport model using satellite-derived vegetation index data

    International Nuclear Information System (INIS)

    Knorr, W.; Heimann, M.

    1994-01-01

    We develop a simple, globally uniform model of CO 2 exchange between the atmosphere and the terrestrial biosphere by coupling the model with a three-dimensional atmospheric tracer transport model using observed winds, and checking results against observed concentrations of CO 2 at various monitoring sites. CO 2 fluxes are derived from observed greenness using satellite-derived Global Vegetation Index data, combined with observations of temperature, radiation, and precipitation. We explore a range of CO 2 flux formulations together with some modifications of the modelled atmospheric transport. We find that while some formulations can be excluded, it cannot be decided whether or not to make CO 2 uptake and release dependent on water stress. It appears that the seasonality of net CO 2 fluxes in the tropics, which would be expected to be driven by water availability, is small and is therefore not visible in the seasonal cycle of atmospheric CO 2 . The latter is dominated largely by northern temperate and boreal vegetation, where seasonality is mostly temperature determined. We find some evidence that there is still considerable CO 2 release from soils during northern-hemisphere winter. An exponential air temperature dependence of soil release with a Q 10 of 1.5 is found to be most appropriate, with no cutoff at low freezing temperatures. This result is independent of the year from which observed winds were taken. This is remarkable insofar as year-to-year changes in modelled CO 2 concentrations caused by changes in the wind data clearly outweigh those caused by year-to-year variability in the climate and vegetation index data. (orig.)

  18. A demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data

    Science.gov (United States)

    Butera, M. K. (Principal Investigator)

    1978-01-01

    The author has identified the following significant results. Major vegetative classes identified by the remote sensing technique were cypress swamp, pine, wetland grasses, salt grass, mixed mangrove, black mangrove, Brazilian pepper. Australian pine and melaleuca were not satisfactorily classified from LANDSAT. Aircraft scanners provided better resolution resulting in a classification of finer surface detail. An edge effect, created by the integration of diverse spectral responses within boundary elements of digital data, affected the wetlands classification. Accuracy classification for aircraft was 68% and for LANDSAT was 74%.

  19. Advantages of Using Microwave Satellite Soil Moisture over Gridded Precipitation Products and Land Surface Model Output in Assessing Regional Vegetation Water Availability and Growth Dynamics for a Lateral Inflow Receiving Landscape

    NARCIS (Netherlands)

    Chen, T.; McVicar, T.R.; Wang, G.J.; Chen, X.; de Jeu, R.A.M.; Liu, Y.; Shen, H.; Zhang, F.; Dolman, A.J.

    2016-01-01

    To improve the understanding of water-vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow

  20. 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

  1. 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.

  2. 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

  3. Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

    Science.gov (United States)

    Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

    2015-01-01

    The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.

  4. Ecosystem processes at the watershed scale: hydrologic vegetation gradient as an indicator for lateral hydrologic connectivity of headwater catchments

    Science.gov (United States)

    Taehee Hwang; James M. Vose; Christina. Tague

    2012-01-01

    Lateral water flow in catchments can produce important patterns in water and nutrient fluxes and stores and also influences the long-term spatial development of forest ecosystems. Specifically, patterns of vegetation type and density along hydrologic flow paths can represent a signal of the redistribution of water and nitrogen mediated by lateral hydrologic flow. This...

  5. Comparison of satellite imagery and infrared aerial photography as vegetation mapping methods in an arctic study area: Jameson Land, East Greenland

    DEFF Research Database (Denmark)

    Hansen, Birger Ulf; Mosbech, Anders

    1994-01-01

    Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland......Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland...

  6. 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.

  7. A change detection strategy for monitoring vegetative and land-use cover types using remotely-sensed, satellite-based data

    International Nuclear Information System (INIS)

    Hallum, C.

    1993-01-01

    Changes to the environment are of critical concern in the world today; consequently, monitoring such changes and assessing their impacts are tasks demanding considerably higher priority. The ecological impacts of the natural global cycles of gases and particulates in the earth's atmosphere are highly influenced by the extent of changes to vegetative canopy characteristics which dictates the need for capability to detect and assess the magnitude of such changes. The primary emphasis of this paper is on the determination of the size and configuration of the sampling unit that maximizes the probability of its intersection with a 'change' area. Assessment of the significance of the 'change' in a given locality is also addressed and relies on a statistical approach that compares the number of elemental units exceeding a reflectance threshold when compared to a previous point in time. Consideration is also given to a technical framework that supports quantifying the magnitude of the 'change' over large areas (i.e., the estimated area changing from forest to agricultural land-use). The latter entails a multistage approach which utilizes satellite-based and other related data sources

  8. NDVI indicated long-term interannual changes in vegetation activities and their responses to climatic and anthropogenic factors in the Three Gorges Reservoir Region, China.

    Science.gov (United States)

    Wen, Zhaofei; Wu, Shengjun; Chen, Jilong; Lü, Mingquan

    2017-01-01

    Natural and social environmental changes in the China's Three Gorges Reservoir Region (TGRR) have received worldwide attention. Identifying interannual changes in vegetation activities in the TGRR is an important task for assessing the impact these changes have on the local ecosystem. We used long-term (1982-2011) satellite-derived Normalized Difference Vegetation Index (NDVI) datasets and climatic and anthropogenic factors to analyze the spatiotemporal patterns of vegetation activities in the TGRR, as well as their links to changes in temperature (TEM), precipitation (PRE), downward radiation (RAD), and anthropogenic activities. At the whole TGRR regional scale, a statistically significant overall uptrend in NDVI variations was observed in 1982-2011. More specifically, there were two distinct periods with different trends split by a breakpoint in 1991: NDVI first sharply increased prior to 1991, and then showed a relatively weak rate of increase after 1991. At the pixel scale, most parts of the TGRR experienced increasing NDVI before the 1990s but different trend change types after the 1990s: trends were positive in forests in the northeastern parts, but negative in farmland in southwest parts of the TGRR. The TEM warming trend was the main climate-related driver of uptrending NDVI variations pre-1990s, and decreasing PRE was the main climate factor (42%) influencing the mid-western farmland areas' NDVI variations post-1990s. We also found that anthropogenic factors such as population density, man-made ecological restoration, and urbanization have notable impacts on the TGRR's NDVI variations. For example, large overall trend slopes in NDVI were more likely to appear in TGRR regions with large fractions of ecological restoration within the last two decades. The findings of this study may help to build a better understanding of the mechanics of NDVI variations in the periods before and during TGDP construction for ongoing ecosystem monitoring and assessment in the

  9. Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data

    Directory of Open Access Journals (Sweden)

    Stuart E. Marsh

    2010-01-01

    Full Text Available Climate change and variability are expected to impact the synchronicity and interactions between the Sonoran Desert and the forested sky islands which represent steep biological and environmental gradients. The main objectives were to examine how well satellite greenness time series data and derived phenological metrics (e.g., season start, peak greenness can characterize specific vegetation communities across an elevation gradient, and to examine the interactions between climate and phenological metrics for each vegetation community. We found that representative vegetation types (11, varying between desert scrub, mesquite, grassland, mixed oak, juniper and pine, often had unique seasonal and interannual phenological trajectories and spatial patterns. Satellite derived land surface phenometrics (11 for each of the vegetation communities along the cline showed numerous distinct significant relationships in response to temperature (4 and precipitation (7 metrics. Satellite-derived sky island vegetation phenology can help assess and monitor vegetation dynamics and provide unique indicators of climate variability and patterns of change.

  10. Effects of organic, biological and chemical fertilizers on vegetative indices and essential oil content of coriander (Coriandrum sativum L.

    Directory of Open Access Journals (Sweden)

    M Aghhavani Shajari

    2016-05-01

    Full Text Available This experiment was conducted to study the effects of single and combined application of organic, biological and chemical fertilizers on qualitative and quantitative characteristics of vegetative part of coriander, (Coriandrum sativum L.. The experiment was carried out as split plot in time based on Complete Randomized Block Design with three replications and 12 treatments at Research Station, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran, during growing season of 2010-2011. Treatments included: (1 mycorrhiza (Glomus mosseae, (2 biosulfur (Thiobacillus sp., (3 chemical fertilizer (NPK, (4 cow manure, (5 vermicompost, (6 mycorrhiza + chemical fertilizer, (7 mycorrhiza + cow manure, (8 mycorrhiza + vermicompost, (9 biosulfur + chemical fertilizer, (10 biosulfur + cow manure, (11 biosulfur + vermicompost and (12 control. Vegetative parts of coriander were cut at 5% of flowering stage in two dates (19 May and 5 June. Results showed that the highest plant height (28 cm and lateral branches (5.2 were obtained in combined application of biosulfur with cow manure treatment. The highest fresh and dry leaf weight, fresh and dry matter yield and stem dry matter weight were obtained in single application of chemical fertilizer. Single application of biosulfur increased leaf/stem ratio. The highest essential oil percentage and essential oil yield were observed in cow manure treatment (0.2% and 1753 g.ha-1, respectively. The maximum leaf/stem ratio were observed in the first cutting, while the highest lateral branches, stem fresh and dry matter yield, essential oil percentage and essential oil yield were obtained in second cut. Overall, results of this study showed that the plant vegetative yield increased by using chemical fertilizer, while essential oil percentage and essential oil yield of coriander were improved by using organic and biological fertilizers.

  11. 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

  12. [Dynamics of vegetative indicators induced by low-frequency magnetotherapy and EHF-puncture in hypertensive workers exposed to vibration].

    Science.gov (United States)

    Drobyshev, V A; Efremov, A V; Loseva, M I; Sukharevskaia, T M; Michurin, A I

    2002-01-01

    Low-frequency magnetic fields and EHF-therapy have been used in correction of autonomic homeostasis in workers exposed to vibration for different periods of time. The workers suffered from early arterial hypertension. Vegetative status and central hemodynamics improved best in workers exposed to vibration for less than 5 years. If the exposure was 6-15 years, a positive trend occurred in the tension of regulatory mechanisms. Workers with long exposure to vibration suffering from vagotonia showed an inadequate response of the autonomic parameters to treatment. This necessitates enhancement of therapeutic measures with medicines.

  13. 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.

  14. Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

    OpenAIRE

    Ulsig, Laura; Nichol, Caroline J.; Huemmrich, Karl F.; Landis, David R.; Middleton, Elizabeth M.; Lyapustin, Alexei I.; Mammarella, Ivan; Levula, Janne; Porcar-Castell, Albert

    2017-01-01

    Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MO...

  15. Detecting inter-annual variations in the phenology of evergreen conifers using long-term MODIS vegetation index time series.

    OpenAIRE

    Ulsig, Laura

    2016-01-01

    Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalised Difference Vegetation Index (NDVI). This study investigates the potential of the Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of ...

  16. Climate change impacts detection in dry forested ecosystem as indicated by vegetation cover change in -Laikipia, of Kenya.

    Science.gov (United States)

    M'mboroki, Kiambi Gilbert; Wandiga, Shem; Oriaso, Silas Odongo

    2018-03-29

    The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grasslands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 °C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the

  17. Investigating the Relationship between the Inter-Annual Variability of Satellite-Derived Vegetation Phenology and a Proxy of Biomass Production in the Sahel

    Directory of Open Access Journals (Sweden)

    Michele Meroni

    2014-06-01

    Full Text Available In the Sahel region, moderate to coarse spatial resolution remote sensing time series are used in early warning monitoring systems with the aim of detecting unfavorable crop and pasture conditions and informing stakeholders about impending food security risks. Despite growing evidence that vegetation productivity is directly related to phenology, most approaches to estimate such risks do not explicitly take into account the actual timing of vegetation growth and development. The date of the start of the season (SOS or of the peak canopy density can be assessed by remote sensing techniques in a timely manner during the growing season. However, there is limited knowledge about the relationship between vegetation biomass production and these variables at the regional scale. This study describes the first attempt to increase our understanding of such a relationship through the analysis of phenological variables retrieved from SPOT-VEGETATION time series of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR. Two key phenological variables (growing season length (GSL; timing of SOS and the maximum value of FAPAR attained during the growing season (Peak are analyzed as potentially related to a proxy of biomass production (CFAPAR, the cumulative value of FAPAR during the growing season. GSL, SOS and Peak all show different spatial patterns of correlation with CFAPAR. In particular, GSL shows a high and positive correlation with CFAPAR over the whole Sahel (mean r = 0.78. The negative correlation between delays in SOS and CFAPAR is stronger (mean r = −0.71 in the southern agricultural band of the Sahel, while the positive correlation between Peak FAPAR and CFAPAR is higher in the northern and more arid grassland region (mean r = 0.75. The consistency of the results and the actual link between remote sensing-derived phenological parameters and biomass production were evaluated using field measurements of aboveground herbaceous biomass

  18. 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.

  19. Evaluation of Hyperspectral Multi-Band Indices to Estimate Chlorophyll-A Concentration Using Field Spectral Measurements and Satellite Data in Dianshan Lake, China

    Directory of Open Access Journals (Sweden)

    Linna Li

    2013-04-01

    Full Text Available Chlorophyll-a (Chl-a concentration is considered as a key indicator of the eutrophic status of inland water bodies. Various algorithms have been developed for estimating Chl-a in order to improve the accuracy of predictive models. The objective of this study is to assess the potential of hyperspectral multi-band indices to estimate the Chl-a concentration in Dianshan Lake, which is the largest lake in Shanghai, an international metropolis of China. Based on field spectral measurements and in-situ Chl-a concentration collected on 7–8 September 2010, hyperspectral multi-band indices were calibrated to estimate the Chl-a concentration with optimal wavelengths selected by model tuning. A three-band index accounts for 87.36% (R2 = 0.8736 of the Chl-a variation. A four-band index, which adds a wavelength in the near infrared (NIR region, results in a higher R2 (0.8997 by removing the absorption and backscattering effects of suspended solids. To test the applicability of the proposed indices for routinely monitoring of Chl-a in inland lakes, simulated Hyperion and real HJ-1A satellite data were selected to estimate the Chl-a concentration. The results show that the explanatory powers of these satellite hyperspectral multi-band indices are relatively high with R2 = 0.8559, 0.8945, 0.7969, and 0.8241 for simulated Hyperion and real HJ-1A satellite data, respectively. All of the results provide strong evidence that hyperspectral multi-band indices are promising and applicable to estimate Chl-a in eutrophic inland lakes.

  20. 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

  1. 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.

  2. 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...

  3. Satellite observation of bio-optical indicators related to North-Western Black Sea coastal zone changes

    Science.gov (United States)

    Zoran, Maria

    Satellite remote sensing provides a means for locating, identifying and mapping certain coastal zone features and assessing of spatio-temporal changes.The Romanian coastal zone of the Black Sea is a mosaic of complex, interacting ecosystems, exposed to dramatic changes due to natural and anthropogenic causes (increase in the nutrient and pollutant load of rivers input, industrial and municipal wastewater pollution along the coast, and dumping on the open sea). This study focuses on the assessment of coastal zone land cover changes based on the fusion of satellite remote sensing data.The evaluation of coastal zone landscapes is based upon different sub-functions which refer to landscape features such as water, soil, land-use, buildings, groundwater, biotope types. Mixed pixels result when the sensor's instantaneous field-of-view includes more than one land cover class on the ground. Based on different satellite data (Landsat TM, ETM, SAR ERS, IKONOS, Quickbird, and MODIS) was performed object recognition for North-Western Black Sea coastal zone. Preliminary results show significant coastline position changes of North Western Black Sea during the period of 1987-2007 and urban growth of Constantza town. Also the change in the position of the coastline is examined and linked to the urban expansion in order to determine if the changes are natural or anthropogenic. A distinction is made between landfill/sedimentation processes on the one hand and dredging/erosion processes on the other. Waves play an important role for shoreline configuration. Wave pattern could induce erosion and sedimentation. A quasi-linear model was used to model the rate of shoreline change. The vectors of shoreline were used to compare with wave spectra model in order to examine the accuracy of the coastal erosion model. The shoreline rate modeled from vectors data of SAR ERS-1 has a good correlation with a quasi-linear model. Wave refraction patterns are a good index for shoreline erosion. A coast

  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. Associations between access to farmers’ markets and supermarkets, shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, USA

    Science.gov (United States)

    Pitts, Stephanie B Jilcott; Wu, Qiang; McGuirt, Jared T; Crawford, Thomas W; Keyserling, Thomas C; Ammerman, Alice S

    2013-01-01

    Objective We examined associations between access to food venues (farmers’ markets and supermarkets), shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, USA. Design Access to food venues was measured using a Geographic Information System incorporating distance, seasonality and business hours, to quantify access to farmers’ markets. Produce consumption was assessed by self-report of eating five or more fruits and vegetables daily. BMI and blood pressure were assessed by clinical measurements. Poisson regression with robust variance was used for dichotomous outcomes and multiple linear regression was used for continuous outcomes. As the study occurred in a university town and university students are likely to have different shopping patterns from non-students, we stratified analyses by student status. Setting Eastern North Carolina. Subjects Low-income women of reproductive age (18–44 years) with valid address information accessing family planning services at a local health department (n 400). Results Over a quarter reported ever shopping at farmers’ markets (114/400). A larger percentage of women who shopped at farmers’ markets consumed five or more fruits and vegetables daily (42·1%) than those who did not (24·0%; P<0·001). The mean objectively measured distance to men reported shopping was 11·4 (SD 9·0) km (7·1 (SD 5·6) miles), while the mean distance to the farmers’ market closest to the residence was 4·0 (SD 3·7) km (2·5 (SD 2·3) miles). Conclusions Among non-students, those who shopped at farmers’ markets were more likely to consume five or more servings of fruits and vegetables daily. Future research should further explore potential health benefits of farmers’ markets. PMID:23701901

  6. 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.

  7. Changes in vegetation types and Ellenberg indicator values after 65 years of fertilizer application in the Rengen Grassland Experiment, Germany

    NARCIS (Netherlands)

    Chytry, M.; Hejcman, M.; Hennekens, S.M.; Schellberg, J.

    2009-01-01

    Question: How does semi-natural grassland diversify after 65 years of differential application of Ca, N, P, and K fertilizers? Is fertilizer application adequately reflected by the Ellenberg indicator values (EIVs)? Location: Eifel Mountains, West Germany. Methods: The Rengen Grassland Experiment

  8. 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.

  9. Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

    Science.gov (United States)

    Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team

    2003-04-01

    &P-model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the inter-site variability, regardless whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly time scale we developed a simple T&P&LAI-model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time-step model and explained 50 % of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index.

  10. Describing the spatio-temporal variability of vines and soil by satellite-based spectral indices: A case study in Apulia (South Italy)

    Science.gov (United States)

    Borgogno-Mondino, E.; Novello, V.; Lessio, A.; de Palma, L.

    2018-06-01

    A time series of Landsat 8 OLI (L8 OLI) multispectral images acquired between May 2013 and February 2016 were used to investigate vigour, vine and soil water content in a vineyard of Moscato Reale (syn. Moscato Bianco) sited in the Castel del Monte DOCG area. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated and compared with vine midday stem water potential (ΨMDstem) and soil volume water content (VWC), to calibrate estimation models. Estimation models were calibrated using already existing ground observation datasets from previous ordinary vineyard management operations: ΨMDstem was measured at two different locations in vineyard at 6 different dates in summer 2014; VWC was continuously measured from June to October 2014 and from January to September 2015. Results showed that: a) vine stem water potential can be locally estimated with an accuracy ranging from ±0.046 (high vigour vines) to ±0.127 (low vigour vines) MPa; b) soil volume water content can be locally estimated with an accuracy of about ±1.7%. Medium resolution satellite imagery proved, therefore, to be effective, at vineyard level, to describe vigour, vine and soil water status and their seasonality. This is an important issue to focus on since, as Landsat 8 images are free, the entire process is economic enough to be consistent with cost and incoming of the farming system.

  11. Using High Resolution Commercial Satellite Imagery to Quantify Spatial Features of Urban Areas and their Relationship to Quality of Life Indicators in Accra, Ghana

    Science.gov (United States)

    Sandborn, A.; Engstrom, R.; Yu, Q.

    2014-12-01

    Mapping urban areas via satellite imagery is an important task for detecting and anticipating land cover and land use change at multiple scales. As developing countries experience substantial urban growth and expansion, remotely sensed based estimates of population and quality of life indicators can provide timely and spatially explicit information to researchers and planners working to determine how cities are changing. In this study, we use commercial high spatial resolution satellite imagery in combination with fine resolution census data to determine the ability of using remotely sensed data to reveal the spatial patterns of quality of life in Accra, Ghana. Traditionally, spectral characteristics are used on a per-pixel basis to determine land cover; however, in this study, we test a new methodology that quantifies spatial characteristics using a variety of spatial features observed in the imagery to determine the properties of an urban area. The spatial characteristics used in this study include histograms of oriented gradients, PanTex, Fourier transform, and line support regions. These spatial features focus on extracting structural and textural patterns of built-up areas, such as homogeneous building orientations and straight line indices. Information derived from aggregating the descriptive statistics of the spatial features at both the fine-resolution census unit and the larger neighborhood level are then compared to census derived quality of life indicators including information about housing, education, and population estimates. Preliminary results indicate that there are correlations between straight line indices and census data including available electricity and literacy rates. Results from this study will be used to determine if this methodology provides a new and improved way to measure a city structure in developing cities and differentiate between residential and commercial land use zones, as well as formal versus informal housing areas.

  12. 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.

  13. Satellite- versus temperature-derived green wave indices for predicting the timing of spring migration of avian herbivores

    NARCIS (Netherlands)

    Shariati Najafabadi, M.; Najafabadi, M.S.; Darvishzadeh, R.; Skidmore, A.K.; Kölzsch, Andrea; Vrieling, A.; Nolet, Bart A.; Exo, Klaus-Michael; Meratnia, Nirvana; Havinga, Paul J.M.; Stahl, Julia; Toxopeus, A.G.

    2015-01-01

    According to the green wave hypothesis, herbivores follow the flush of spring growth of forage plants during their spring migration to northern breeding grounds. In this study we compared two green wave indices for predicting the timing of the spring migration of avian herbivores: the

  14. Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

    Science.gov (United States)

    In global agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability an...

  15. The Effect of Irrigation Regimes and Mulch Application on Vegetative Indices and Essential Oil Content of Peppermint (Mentha piperita L.

    Directory of Open Access Journals (Sweden)

    M. Azizi

    2016-02-01

    Full Text Available Peppermint (Mentha piperita L. from Lamiaceae family is one of the most important medicinal plants, used in food, sanitary and cosmetic industries. A field experiment was carried out in Ferdowsi University of Mashhad in 2010-2011 to evaluate the effects of three irrigation levels (100, 80 and 60 percent of water requirements calculated by evaporation pan class A and two mulch types (black plastic and wood chips in comparison to control (without mulch on physiological parameter and essential oils content in a factorial experiments on the basis of Randimised Complete Block Desing with four replications. The data obtained from each harvest analyzed as a factorial experiment on the basis of randomized complete block design with four replications and the results of two harvests analyzed as split plot on time. The results of two harvest indicated that peppermint plants grow better in the first harvest than the second harvest. Plants collected in the first harvest showed higher dry matter and essential oil yield. The highest dry herb yield (44.12 g/plant, the highest percentage of essential oil (2.835 %v/w and the highest essential oil yield (116.7 l/ha detected in plots treated with third level of irrigation and use of wood chips mulch. In conclusion the results also confirmed that the highest dry herb and the highest oil yield per area unit were observed in plots treated with third level of irrigation with use of wood chips mulch.

  16. 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)

  17. Late Pleistocene Vegetation, Climate and Relative Sea Level Changes in the Southeastern Brazilian Coast, Based on C and N Isotopes and Bio Indicator Analysis of Mangrove Organic Matter

    Energy Technology Data Exchange (ETDEWEB)

    Pessenda, L. C.R.; Vidotto, E.; Buso, Jr., A. A.; Assarini, Jr., J. P.; Bendassollia, J. A. [Center for Nuclear Energy in Agriculture (CENA), University of Sao Paulo (USP), Piracicaba, Sao Paulo (Brazil); De Oliveira, P. E. [University of Guarulhos (UNG), Guarulhos, Sao Paulo (Brazil); Macias, F. [' ' Luiz de Queiroz' ' College of Agriculture/USP, Piracicaba, Sao Paulo (Brazil); Ricardi-Branco, F. [University of Campinas - Geosciences Institute, Campinas, Sao Paulo (Brazil)

    2013-07-15

    On the southeastern Brazilian coast, mangrove organic matter records have been studied by C and N isotopes, pollen and diatom analysis to reconstruct 40 ka of vegetation and climatic history. The {delta}{sup 13}C and {delta}{sup 15}N presented more depleted values from 40 to 19 ka BP. The high C/N ratios and depleted isotopic values indicate the predominance of C3 land plants in the location presently occupied by the mangrove vegetation, and a lower sea level than today. The presence of pollen of Ilex, Weinmannia, Symplocos, Drimys and Podocarpus suggest a colder and more humid climate than present. From 19 to 2.2 ka BP a sedimentary hiatus is associated with a sea level rise. The presence of mangrove in its present position since at least 2.200 a BP and the return of the marine coastline are associated with the lowest C/N ratio, more enriched {delta}{sup 13}C and {delta}{sup 15}N values and the presence of marine diatoms. (author)

  18. 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

  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. Investigation of environmental indices from the Earth Resources Technology Satellite. [environmental trends in land use water quality, and air quality in Pennsylvania

    Science.gov (United States)

    Greeley, R. S. (Principal Investigator); Ward, E. A.; Elliott, J. C.; Friedman, E. J.; Riley, E. L.; Stryker, S.

    1974-01-01

    The author has identified the following significant results. Land use change, water quality, and air quality indices have been calculated from analysis of ERTS-1 multispectral scanning imagery and computer compatible tapes. Specifications have been developed and discussed for an ERTS-1 environmental monitoring system which help to serve the information needs of environmental managers at the Federal, state, regional, and local level. General conclusions of the investigation are that ERTS-1 data is very useful in land use mapping and updating to 10-15 categories, and can provide an overall measure of air and water turbidity; however, more and better ground truth and possibly additional spacecraft sensors will be required if specific air and water pollutants are to be quantified from satellite data.

  1. 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

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

    Directory of Open Access Journals (Sweden)

    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. 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.

  4. High-Velocity Cloud Complex H and Weaver's "Jet": Two candidate dwarf satellite galaxies for which dark matter halo models indicate distances of ~27 kpc and ~108 kpc

    Science.gov (United States)

    Simonson, S. Christian

    2018-04-01

    Two anomalous-velocity H I features, High-Velocity Cloud Complex H (HVC H) (Blitz et al. 1999), and Weaver's "jet" (Weaver 1974), appear to be good candidates for dwarf satellites. In this work they are modeled as H I disks in dark matter halos that move in 3D orbits in the combined time-dependent gravitational fields of the Milky Way and M31. As they orbit in the Local Group they develop tidal distortions and produce debris. The current l,b,V appearance of the tidal features as they approach the Milky Way indicate distances of 27 ± 9 kpc for HVC H and 108 ± 36 kpc for Weaver's "jet". As these are within the distances to known Milky Way satellites, finding stellar components would be of interest for the star formation history of the Milky Way. This work uses recent Hubble Space Telescope results on M31 (van der Marel et al. 2012) to calculate the center-of-mass (COM) locations and the dark matter mass distributions of the Milky-Way—M31 system since the Big Bang. Time-dependent COM orbits of the satellites have been computed in 3D, along with rings of test particles representing their disks. Tidal effects that develop on these rings have been compared with published 21-cm line data from Lockman (2003) and Simonson (1975). For HVC H at l = 130.5°, b = +1.5°, V = -200 km/s, the dark matter mass (in solar masses) is estimated as 5.2 ± 3.5E8. The previously estimated H I mass is 6.4E6, or 1.2% of the newly derived satellite mass. For Weaver's "jet", which covers 2° by 7° at l = 197.3°, b = +2.1°, V = -30 to -87 km/s, the dark matter mass is estimated as 1.8 ± 0.6E9. The H I mass is 1.8 ± 1.1E8, or 6% to 12% of the satellite mass. In the case of HVC H, owing to its disk angle of 45°, tidal debris is thrown upward. This would presumably contribute to a halo star stream. In the case of Weaver's "jet", the streamer represents accreting material for the disk. I am grateful to Leo Blitz for bringing Lockman's work on HVC H to my attention and for many helpful

  5. 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

  6. 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.

  7. The value of different vegetative indices (NDVI, GAI for the assessment of yield potential of pea (Pisum sativum L. at different growth stages and under varying management practices

    Directory of Open Access Journals (Sweden)

    Agnieszka Klimek-Kopyra

    2018-03-01

    Full Text Available This research evaluated the NDVI (normalized difference vegetation index and GAI (green area index in order to indicate the productivity and developmental effects of Rhizobium inoculants and microelement foliar fertilizer on pea crops. Two inoculants, Nitragina (a commercial inoculant and IUNG (a noncommercial inoculant gel and a foliar fertilizer (Photrel were studied over a 4-year period, 2009–2012. The cultivars chosen for the studies were characterized by different foliage types, namely a semileafless pea ‘Tarchalska’ and one with regular foliage, ‘Klif’. Foliar fertilizer significantly increased the length of the generative shoots and the number of fruiting nodes in comparison to the control, which in turn had a negative impact on the harvest index. Pea seed yield was highly dependent on the interaction between the years of growth and the microbial inoculant, and was greater for ‘Tarchalska’ (4.33 t ha−1. Presowing inoculation of seeds and foliar fertilization resulted in a significantly higher value of GAI at the flowering (3.91 and 3.81, respectively and maturity stages (4.82 and 4.77, respectively, whereas the value of NDVI was higher for these treatments only at the maturity stage (0.67 and 0.79, respectively. A significantly greater yield (5.0–5.4 t ha−1 was obtained after inoculation with IUNG during the dry years.

  8. 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.

  9. Detecting Historical Vegetation Changes in the Dunhuang Oasis Protected Area Using Landsat Images

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    Xiuxia Zhang

    2017-09-01

    Full Text Available Abstract: Given its proximity to an artificial oasis, the Donghu Nature Reserve in the Dunhuang Oasis has faced environmental pressure and vegetation disturbances in recent decades. Satellite vegetation indices (VIs can be used to detect such changes in vegetation if the satellite images are calibrated to surface reflectance (SR values. The aim of this study was to select a suitable VI based on the Landsat Climate Data Record (CDR products and the absolute radiation-corrected results of Landsat L1T images to detect the spatio-temporal changes in vegetation for the Donghu Reserve during 1986–2015. The results showed that the VI difference (ΔVI images effectively reduced the changes in the source images. Compared with the other VIs, the soil-adjusted vegetation index (SAVI displayed greater robustness to atmospheric effects in the two types of SR images and was more responsive to vegetation changes caused by human factors. From 1986 to 2015, the positive changes in vegetation dominated the overall change trend, with changes in vegetation in the reserve decreasing during 1990–1995, increasing until 2005–2010, and then decreasing again. The vegetation changes were mainly distributed at the edge of the artificial oasis outside the reserve. The detected changes in vegetation in the reserve highlight the increased human pressure on the reserve.

  10. Methodology for bioremediation monitoring of oil wastes contaminated soils by using vegetal bio indicators; Metodologia para monitoramento de biorremediacao de solos contaminados com residuos oleosos com bioindicadores vegetais

    Energy Technology Data Exchange (ETDEWEB)

    Nascimento Neto, Durval; Carvalho, Francisco Jose Pereira de Campos [Parana Univ., Curitiba, PR (Brazil). Curso de Pos-Graduacao em Ciencia do Solo]. E-mail: fjcampos@cce.ufpr.br

    1998-07-01

    This work studies the development of a methodology for the evaluation of the bioremediation status of oil waste contaminated soils, by using vegetal bioindicators for the bioremediation process monitoring, and evaluation of the environmental impacts on the contaminated areas.

  11. Precision Viticulture from Multitemporal, Multispectral Very High Resolution Satellite Data

    Science.gov (United States)

    Kandylakis, Z.; Karantzalos, K.

    2016-06-01

    In order to exploit efficiently very high resolution satellite multispectral data for precision agriculture applications, validated methodologies should be established which link the observed reflectance spectra with certain crop/plant/fruit biophysical and biochemical quality parameters. To this end, based on concurrent satellite and field campaigns during the veraison period, satellite and in-situ data were collected, along with several grape samples, at specific locations during the harvesting period. These data were collected for a period of three years in two viticultural areas in Northern Greece. After the required data pre-processing, canopy reflectance observations, through the combination of several vegetation indices were correlated with the quantitative results from the grape/must analysis of grape sampling. Results appear quite promising, indicating that certain key quality parameters (like brix levels, total phenolic content, brix to total acidity, anthocyanin levels) which describe the oenological potential, phenolic composition and chromatic characteristics can be efficiently estimated from the satellite data.

  12. Local Vegetation Trends in the Sahel of Mali and Senegal Using Long Time Series FAPAR Satellite Products and Field Measurement (1982–2010

    Directory of Open Access Journals (Sweden)

    Martin Brandt

    2014-03-01

    Full Text Available Local vegetation trends in the Sahel of Mali and Senegal from Geoland Version 1 (GEOV1 (5 km and the third generation Global Inventory Modeling and Mapping Studies (GIMMS3g (8 km Fraction of Absorbed Photosynthetically Active Radiation (FAPAR time series are studied over 29 years. For validation and interpretation of observed greenness trends, two methods are applied: (1 a qualitative approach using in-depth knowledge of the study areas and (2 a quantitative approach by time series of biomass observations and rainfall data. Significant greening trends from 1982 to 2010 are consistently observed in both GEOV1 and GIMMS3g FAPAR datasets. Annual rainfall increased significantly during the observed time period, explaining large parts of FAPAR variations at a regional scale. Locally, GEOV1 data reveals a heterogeneous pattern of vegetation change, which is confirmed by long-term ground data and site visits. The spatial variability in the observed vegetation trends in the Sahel area are mainly caused by varying tree- and land-cover, which are controlled by human impact, soil and drought resilience. A large proportion of the positive trends are caused by the increment in leaf biomass of woody species that has almost doubled since the 1980s due to a tree cover regeneration after a dry-period. This confirms the re-greening of the Sahel, however, degradation is also present and sometimes obscured by greening. GEOV1 as compared to GIMMS3g made it possible to better characterize the spatial pattern of trends and identify the degraded areas in the study region.

  13. Mineral and Vegetation Maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, Generated from ASTER Satellite Data

    Science.gov (United States)

    Rockwell, Barnaby W.

    2010-01-01

    Multispectral remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were analyzed to identify and map minerals, vegetation groups, and volatiles (water and snow) in support of geologic studies of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada. Digital mineral and vegetation mapping results are presented in both portable document format (PDF) and ERDAS Imagine format (.img). The ERDAS-format files are suitable for integration with other geospatial data in Geographic Information Systems (GIS) such as ArcGIS. The ERDAS files showing occurrence of 1) iron-bearing minerals, vegetation, and water, and 2) clay, sulfate, mica, carbonate, Mg-OH, and hydrous quartz minerals have been attributed according to identified material, so that the material detected in a pixel can be queried with the interactive attribute identification tools of GIS and image processing software packages (for example, the Identify Tool of ArcMap and the Inquire Cursor Tool of ERDAS Imagine). All raster data have been orthorectified to the Universal Transverse Mercator (UTM) projection using a projective transform with ground-control points selected from orthorectified Landsat Thematic Mapper data and a digital elevation model from the U.S. Geological Survey (USGS) National Elevation Dataset (1/3 arc second, 10 m resolution). Metadata compliant with Federal Geographic Data Committee (FGDC) standards for all ERDAS-format files have been included, and contain important information regarding geographic coordinate systems, attributes, and cross-references. Documentation regarding spectral analysis methodologies employed to make the maps is included in these cross-references.

  14. Using NASA Earth Observing Satellites and Statistical Model Analysis to Monitor Vegetation and Habitat Rehabilitation in Southwest Virginia's Reclaimed Mine Lands

    Science.gov (United States)

    Tate, Z.; Dusenge, D.; Elliot, T. S.; Hafashimana, P.; Medley, S.; Porter, R. P.; Rajappan, R.; Rodriguez, P.; Spangler, J.; Swaminathan, R. S.; VanGundy, R. D.

    2014-12-01

    The majority of the population in southwest Virginia depends economically on coal mining. In 2011, coal mining generated $2,000,000 in tax revenue to Wise County alone. However, surface mining completely removes land cover and leaves the land exposed to erosion. The destruction of the forest cover directly impacts local species, as some are displaced and others perish in the mining process. Even though surface mining has a negative impact on the environment, land reclamation efforts are in place to either restore mined areas to their natural vegetated state or to transform these areas for economic purposes. This project aimed to monitor the progress of land reclamation and the effect on the return of local species. By incorporating NASA Earth observations, such as Landsat 8 Operational Land Imager (OLI) and Landsat 5 Thematic Mapper (TM), re-vegetation process in reclamation sites was estimated through a Time series analysis using the Normalized Difference Vegetation Index (NDVI). A continuous source of cloud free images was accomplished by utilizing the Spatial and Temporal Adaptive Reflectance Fusion Model (STAR-FM). This model developed synthetic Landsat imagery by integrating the high-frequency temporal information from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and high-resolution spatial information from Landsat sensors In addition, the Maximum Entropy Modeling (MaxENT), an eco-niche model was used to estimate the adaptation of animal species to the newly formed habitats. By combining factors such as land type, precipitation from Tropical Rainfall Measuring Mission (TRMM), and slope from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the MaxENT model produced a statistical analysis on the probability of species habitat. Altogether, the project compiled the ecological information which can be used to identify suitable habitats for local species in reclaimed mined areas.

  15. Socioeconomic indicators and frequency of traditional food, junk food, and fruit and vegetable consumption amongst Inuit adults in the Canadian Arctic.

    Science.gov (United States)

    Hopping, B N; Erber, E; Mead, E; Sheehy, T; Roache, C; Sharma, S

    2010-10-01

    Increasing consumption of non-nutrient-dense foods (NNDF), decreasing consumption of traditional foods (TF) and low consumption of fruit and vegetables (FV) may contribute to increasing chronic disease rates amongst Inuit. The present study aimed to assess the daily frequency and socioeconomic and demographic factors influencing consumption of TF, FV and NNDF amongst Inuit adults in Nunavut, Canada. Using a cross-sectional study design and random household sampling in three communities in Nunavut, a food frequency questionnaire developed for the population was used to assess frequency of NNDF, TF and FV consumption amongst Inuit adults. Socioeconomic status (SES) was assessed by education level, ownership of items in working condition, and whether or not people in the household were employed or on income support. Mean frequencies of daily consumption were compared across gender and age groups, and associations with socioeconomic indicators were analysed using logistic regression. Two hundred and eleven participants (36 men, 175 women; mean (standard deviation) ages 42.1 (15.0) and 42.2 (13.2) years, respectively; response rate 69-93%) completed the study. Mean frequencies of consumption for NNDF, TF and FV were 6.3, 1.9 and 1.6 times per day, respectively. On average, participants ≤50 years consumed NNDF (P=0.003) and FV (P=0.01) more frequently and TF (P=0.01) less frequently than participants >50 years. Education was positively associated with FV consumption and negatively associated with TF consumption. Households on income support were more likely to consume TF and NNDF. These results support the hypothesis that the nutrition transition taking place amongst Inuit in Nunavut results in elevated consumption of NNDF compared with TF and FV. © 2010 The Authors. Journal compilation © 2010 The British Dietetic Association Ltd.

  16. Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images

    International Nuclear Information System (INIS)

    Arellano, Paul; Tansey, Kevin; Balzter, Heiko; Boyd, Doreen S.

    2015-01-01

    The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI 705 ) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. - Highlights: • Leaf biochemical alterations in the rainforest are caused by petroleum pollution. • Lower levels of chlorophyll content are symptom of vegetation stress in polluted sites. • Increased foliar water content was found in vegetation near polluted sites. • Vegetation stress was detected by using vegetation indices from satellite images. • Polluted sites and hydrocarbon seepages in rainforest can be identified from space. - Hydrocarbon pollution in the Amazon forest is observed for first time from satellite data

  17. 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.

  18. Comment on "Satellites reveal contrasting responses of regional climate to the widespread greening of Earth".

    Science.gov (United States)

    Li, Yue; Zeng, Zhenzhong; Huang, Ling; Lian, Xu; Piao, Shilong

    2018-06-15

    Forzieri et al (Reports, 16 June 2017, p. 1180) used satellite data to show that boreal greening caused regional warming. We show that this positive sensitivity of temperature to the greening can be derived from the positive response of vegetation to boreal warming, which indicates that results from a statistical regression with satellite data should be carefully interpreted. Copyright © 2018, American Association for the Advancement of Science.

  19. Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

    Science.gov (United States)

    Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

    2017-10-01

    In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil-biosphere-atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000-2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of

  20. Impacts of climate change on the microbial safety of pre-harvest leafy green vegetables as indicated by Escherichia coli O157 and Salmonella spp.

    NARCIS (Netherlands)

    Liu, C.; Hofstra, N.; Franz, E.

    2013-01-01

    The likelihood of leafy green vegetable (LGV) contamination and the associated pathogen growth and survival are strongly related to climatic conditions. Particularly temperature increase and precipitation pattern changes have a close relationship not only with the fate and transport of enteric

  1. Changing landscape in the Three Gorges Reservoir Area of Yangtze River from 1977 to 2005: Land use/land cover, vegetation cover changes estimated using multi-source satellite data

    Science.gov (United States)

    Zhang, Jixian; Zhengjun, Liu; Xiaoxia, Sun

    2009-12-01

    The eco-environment in the Three Gorges Reservoir Area (TGRA) in China has received much attention due to the construction of the Three Gorges Hydropower Station. Land use/land cover changes (LUCC) are a major cause of ecological environmental changes. In this paper, the spatial landscape dynamics from 1978 to 2005 in this area are monitored and recent changes are analyzed, using the Landsat TM (MSS) images of 1978, 1988, 1995, 2000 and 2005. Vegetation cover fractions for a vegetation cover analysis are retrieved from MODIS/Terra imagery from 2000 to 2006, being the period before and after the rising water level of the reservoir. Several analytical indices have been used to analyze spatial and temporal changes. Results indicate that cropland, woodland, and grassland areas reduced continuously over the past 30 years, while river and built-up area increased by 2.79% and 4.45% from 2000 to 2005, respectively. The built-up area increased at the cost of decreased cropland, woodland and grassland. The vegetation cover fraction increased slightly. We conclude that significant changes in land use/land cover have occurred in the Three Gorges Reservoir Area. The main cause is a continuous economic and urban/rural development, followed by environmental management policies after construction of the Three Gorges Dam.

  2. Benefits of China's efforts in gaseous pollutant control indicated by the bottom-up emissions and satellite observations 2000-2014

    Science.gov (United States)

    Xia, Yinmin; Zhao, Yu; Nielsen, Chris P.

    2016-07-01

    To evaluate the effectiveness of national air pollution control policies, the emissions of SO2, NOX, CO and CO2 in China are estimated using bottom-up methods for the most recent 15-year period (2000-2014). Vertical column densities (VCDs) from satellite observations are used to test the temporal and spatial patterns of emissions and to explore the ambient levels of gaseous pollutants across the country. The inter-annual trends in emissions and VCDs match well except for SO2. Such comparison is improved with an optimistic assumption in emission estimation that the emission standards for given industrial sources issued after 2010 have been fully enforced. Underestimation of emission abatement and enhanced atmospheric oxidization likely contribute to the discrepancy between SO2 emissions and VCDs. As suggested by VCDs and emissions estimated under the assumption of full implementation of emission standards, the control of SO2 in the 12th Five-Year Plan period (12th FYP, 2011-2015) is estimated to be more effective than that in the 11th FYP period (2006-2010), attributed to improved use of flue gas desulfurization in the power sector and implementation of new emission standards in key industrial sources. The opposite was true for CO, as energy efficiency improved more significantly from 2005 to 2010 due to closures of small industrial plants. Iron & steel production is estimated to have had particularly strong influence on temporal and spatial patterns of CO. In contrast to fast growth before 2011 driven by increased coal consumption and limited controls, NOX emissions decreased from 2011 to 2014 due to the penetration of selective catalytic/non-catalytic reduction systems in the power sector. This led to reduced NO2 VCDs, particularly in relatively highly polluted areas such as the eastern China and Pearl River Delta regions. In developed areas, transportation is playing an increasingly important role in air pollution, as suggested by the increased ratio of NO2 to SO

  3. Using the satellite-derived normalized difference vegetation index (NDVI) to explain ranging patterns in a lek-breeding antelope: the importance of scale.

    Science.gov (United States)

    Bro-Jørgensen, Jakob; Brown, Molly E; Pettorelli, Nathalie

    2008-11-01

    Lek-breeding species are characterized by a negative association between territorial resource availability and male mating success; however, the impact of resources on the overall distribution patterns of the two sexes in lek systems is not clear. The normalized difference vegetation index (NDVI) has recently emerged as a powerful proxy measure for primary productivity, allowing the links between the distributions of animals and resources to be explored. Using NDVI at four spatial resolutions, we here investigate how the distribution of the two sexes in a lek-breeding population of topi antelopes relates to resource abundance before and during the rut. We found that in the dry season preceding the rut, topi density correlated positively with NDVI at the large, but not the fine, scale. This suggests that before the rut, when resources were relatively scant, topi preferred pastures where green grass was widely abundant. The pattern was less pronounced in males, suggesting that the need for territorial attendance prevents males from tracking resources as freely as females do. During the rut, which occurs in the wet season, both male and female densities correlated negatively with NDVI at the fine scale. At this time, resources were generally plentiful and the results suggest that, rather than by resource maximization, distribution during the rut was determined by benefits of aggregating on relatively resource-poor leks for mating, and possibly antipredator, purposes. At the large scale, no correlation between density and NDVI was found during the rut in either sex, which can be explained by leks covering areas too small to be reflected at this resolution. The study illustrates that when investigating spatial organization, it is important: (1) to choose the appropriate analytic scale, and (2) to consider behavioural as well as strictly ecological factors.

  4. Identical assemblage of Giardia duodenalis in humans, animals and vegetables in an urban area in southern Brazil indicates a relationship among them.

    Directory of Open Access Journals (Sweden)

    Cristiane Maria Colli

    Full Text Available Giardia duodenalis infects humans and other mammals by ingestion of cysts in contaminated water or food, or directly in environments with poor hygiene. Eight assemblages, designated A-H, are described for this species.We investigated by microscopy or by direct immunofluorescence technique the occurrence of G. duodenalis in 380 humans, 34 animals, 44 samples of water and 11 of vegetables. G. duodenalis cysts present in samples were genotyped through PCR-RFLP of β giardin and glutamate dehydrogenase (gdh genes and sequencing of gdh. The gdh gene was amplified in 76.5% (26/34 of the human faeces samples with positive microscopy and in 2.9% (1/34 of negative samples. In 70.4% (19/27 of the positive samples were found BIV assemblage. In two samples from dogs with positive microscopy and one negative sample, assemblages BIV, C, and D were found. Cysts of Giardia were not detected in water samples, but three samples used for vegetable irrigation showed total coliforms above the allowed limit, and Escherichia coli was observed in one sample. G. duodenalis BIV was detected in two samples of Lactuca sativa irrigated with this sample of water. BIV was a common genotype, with 100% similarity, between different sources or hosts (humans, animals and vegetables, and the one most often found in humans.This is the first study in Brazil that reports the connection among humans, dogs and vegetables in the transmission dynamics of G. duodenalis in the same geographic area finding identical assemblage. BIV assemblage was the most frequently observed among these different links in the epidemiological chain.

  5. 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

    Full Text Available Composições de dezesseis dias de índices de vegetação do sensor Moderate Resolution Imaging Spectroradiometer (MODIS, com resolução espacial de 250 metros, a bordo do satélite TERRA, foram utilizadas para caracterizar a dinâmica sazonal no ano de 2008 de duas fitofisionomias do bioma Mata Atlântica e analisar a sua dinâmica espectral. Os índices Normalized Difference Vegetation Index (NDVI e Enhanced Vegetation Index (EVI, calculados a partir dos dados do sensor MODIS e uma base comum de pixels, foram comparados entre si e com uma base de dados de ordem climática (temperatura e precipitação, para cada fitofisionomia. Os resultados indicaram que os fragmentos de floresta estacional decídua e floresta ombrófila mista apresentam um padrão sazonal comum, porém, com variações de amplitude em relação a cada índice. O EVI apresentou-se mais sensível às variações anuais da vegetação em relação ao NDVI, demonstrando-se mais eficiente. Para ambas as formações florestais se estabelece uma correlação positiva entre o perfil EVI e NDVI com as variações de temperatura. A dinâmica espectral/temporal revelou um contraste marcante sob condições sazonais distintas convergindo com o padrão apresentado pelos índices de vegetação. Os dados produzidos indicam potencialidades da utilização do sensor MODIS para o monitoramento contínuo das formações florestais sulinas com resolução espacial moderada e alta resolução temporal. AbstractModerate resolution imaging spectroradiometer (MODIS 16-day vegetation index composites with 250 meters of spatial resolution from TERRA satellites were used to characterize the seasonal dynamics in the period of 2008 of two physiognomies of Atlantic Forest biome and to analyze its spectral dynamics. The Normalized Difference Vegetation Index (NDVI and Enhanced Vegetation Index (EVI, calculated from the data of MODIS sensor and a common base of pixels, were compared between themselves

  6. Vegetation change and terrestrial carbon storage in eastern Asia during the Last Glacial Maximum as indicated by a new pollen record from central Taiwan

    Energy Technology Data Exchange (ETDEWEB)

    Liew, P.M.; Kuo, C.M.; Huang, S.Y.; Tseng, M.H. [Geological Department, National Taiwan Univ. 245, Chou-shan Rd., Taipei (Taiwan, Province of China)

    1998-05-01

    Last Glacial Maximum (LGM) carbon storage in eastern Asia is a key issue for understanding the sinks and sources of paleocarbon. Palynological data with good time constraint for the LGM in a peat bog from a site at 650 m above mean sea level in central Taiwan, together with data from low-lying deltaic and basin deposits of Taiwan and South China, increase our understanding about vegetational evolution and possible terrestrial carbon storage in this area and probably eastern Asia. Contrasting to today`s Machilus-Castanopsis forest zone around the peat bog, the vegetation before the LGM was dominated by Alnus, a relatively xerophytic element in Taiwan. An increase in herbs and decrease in spores during the LGM is recognized when compared with Holocene and modern assemblages. A less humid interval dominated by herbs (>50%) occurred between 21 and 15.8 ka. Basin deposits in northern Taiwan and deltaic deposits in central Taiwan show that during the LGM Artemisia, Umbelliferae and Gramineae were the main components contrasting with the Pinus or Cyclobalanopsis-dominant assemblages in the rest of the last glacial. Thus, less humid conditions lasted about 5000 to 6000 years in the LGM even on this very humid island. This may also be true in eastern Asia where a large area of the widely exposed continental shelf may have been occupied by grasslands and the uplands of South China were occupied by less dense coniferous or temperate forests during the LGM in contrast to the modern subtropical forest. This scenario improves our understanding of the terrestrial paleocarbon storage

  7. Vegetation change and terrestrial carbon storage in eastern Asia during the Last Glacial Maximum as indicated by a new pollen record from central Taiwan

    Science.gov (United States)

    Liew, P. M.; Kuo, C. M.; Huang, S. Y.; Tseng, M. H.

    1998-05-01

    Last Glacial Maximum (LGM) carbon storage in eastern Asia is a key issue for understanding the sinks and sources of paleocarbon. Palynological data with good time constraint for the LGM in a peat bog from a site at 650 m above mean sea level in central Taiwan, together with data from low-lying deltaic and basin deposits of Taiwan and South China, increase our understanding about vegetational evolution and possible terrestrial carbon storage in this area and probably eastern Asia. Contrasting to today's Machilus-Castanopsis forest zone around the peat bog, the vegetation before the LGM was dominated by Alnus, a relatively xerophytic element in Taiwan. An increase in herbs and decrease in spores during the LGM is recognized when compared with Holocene and modern assemblages. A less humid interval dominated by herbs (>50%) occurred between 21 and 15.8 ka. Basin deposits in northern Taiwan and deltaic deposits in central Taiwan show that during the LGM Artemisia, Umbelliferae and Gramineae were the main components contrasting with the Pinus or Cyclobalanopsis-dominant assemblages in the rest of the last glacial. Thus, less humid conditions lasted about 5000 to 6000 years in the LGM even on this very humid island. This may also be true in eastern Asia where a large area of the widely exposed continental shelf may have been occupied by grasslands and the uplands of South China were occupied by less dense coniferous or temperate forests during the LGM in contrast to the modern subtropical forest. This scenario improves our understanding of the terrestrial paleocarbon storage.

  8. Home availability of fruit and vegetables and obesogenic foods as an indicator of nutrient intake in 50 year olds from Canterbury, New Zealand.

    Science.gov (United States)

    Grant, Emily; Gearry, Richard Blair; Wilson, Renée; Pearson, John; Skidmore, Paula Marie Louise

    2017-05-01

    The home food environment is known to influence children's diet and selected health outcomes. However, similar research in adults is scarce. The home is arguably the most important food environment for New Zealand adults as the majority of food consumed is stored and prepared in the home. Therefore we investigated relationships between home food availability and nutrient intake in 50 year olds from Canterbury, New Zealand. A cross-sectional study where participants completed a home food inventory and a four-day estimated food diary. Regression analysis was used to investigate relationships between home availability of 'Fruit and Vegetables' and 'Obesogenic Foods' and intake of selected nutrients, adjusting for Body Mass Index and demographic factors. Men and women (n=216) aged 50 were randomly selected from Canterbury District Health Board area electoral rolls. Women with a high 'Obesogenic Foods' score were significantly more likely to have a high intake of saturated fat (OR 5.8, CI: 1.67, 19.6) and high sugar intake (OR 3.1, CI: 1.23, 7.58). Men with a high 'Obesogenic Foods' score were less likely to have high folate (OR 0.14, CI: 0.05, 0.40) and fibre intake (OR 0.21, CI: 0.07, 0.60). Men and women with a higher 'Fruit and Vegetables' score were more likely to have high vitamin C intake (OR 5.6 and 4.5 respectively). Home Food Inventory scores are associated with selected nutrient intakes, particularly in women, suggesting that they are useful for identifying those groups with less favourable nutrient intakes. Future research should investigate whether these scores can predict health outcomes.

  9. Spatiotemporal analysis of the effect of climate change on vegetation health in the Drakensberg Mountain Region of South Africa.

    Science.gov (United States)

    Mukwada, Geoffrey; Manatsa, Desmond

    2018-05-24

    The impact of climate change on mountain ecosystems has been in the spotlight for the past three decades. Climate change is generally considered to be a threat to ecosystem health in mountain regions. Vegetation indices can be used to detect shifts in ecosystem phenology and climate change in mountain regions while satellite imagery can play an important role in this process. However, what has remained problematic is determining the extent to which ecosystem phenology is affected by climate change under increasingly warming conditions. In this paper, we use climate and vegetation indices that were derived from satellite data to investigate the link between ecosystem phenology and climate change in the Namahadi Catchment Area of the Drakensberg Mountain Region of South Africa. The time series for climate indices as well as those for gridded precipitation and temperature data were analyzed in order to determine climate shifts, and concomitant changes in vegetation health were assessed in the resultant epochs using vegetation indices. The results indicate that vegetation indices should only be used to assess trends in climate change under relatively pristine conditions, where human influence is limited. This knowledge is important for designing climate change monitoring strategies that are based on ecosystem phenology and vegetation health.

  10. Peculiarities of psychological, clinical and instrumental indicators in children with vegetative dysfunction and hypotension under the influence of innovative psychocorrective program

    Directory of Open Access Journals (Sweden)

    I.O. Mitjurjajeva

    2017-03-01

    Full Text Available Background. To study the features of psychological state, clinical and instrumental parameters in children with vegetative dysfunction (VD and hypotension influenced by comprehensive treatment with the inclusion of the innovative psychocorrective program with elements of music therapy, visual art therapy and gelotology. Materials and methods. The study included 57 patients with VD and hypotension aged 12 to 17 years, 37 of them received psychotherapy with innovative program “Our drugs — music, laughter, creativity” in comprehensive treatment, 20 children (control group received basic treatment without psychological assistance. General clinical, laboratory, instrumental and psychodiagnostic studies were performed both in main and control groups. Results. Using innovative psychocorrective program in children with VD and hypotension as a part of comprehensive treatment contributed to the improvement of clinical and instrumental data: number of cases with autonomic influences on the heart reduced (from 22.1 to 5.25 %, р < 0.05, orthostatic test autonomic provision was normalized in 40.5 % of children, psychological state improvement was observed in 74.1 % of cases. Conclusions. Innovative psychocorrective program with elements of music therapy, visual art therapy and gelotology can be recommended as a part of comprehensive treatment of children with VD and hypotension in hospital environment and in future psychological support of patients.

  11. 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.

  12. The relationship of field burn severity measures to satellite-derived Burned Area Reflectance Classification (BARC) maps

    Science.gov (United States)

    Andrew Hudak; Penelope Morgan; Carter Stone; Pete Robichaud; Terrie Jain; Jess Clark

    2004-01-01

    Preliminary results are presented from ongoing research on spatial variability of fire effects on soils and vegetation from the Black Mountain Two and Cooney Ridge wildfires, which burned in western Montana during the 2003 fire season. Extensive field fractional cover data were sampled to assess the efficacy of quantitative satellite image-derived indicators of burn...

  13. Associations between access to farmers' markets and supermarkets, shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, U.S.A.

    Science.gov (United States)

    Jilcott Pitts, Stephanie B; Wu, Qiang; McGuirt, Jared T; Crawford, Thomas W; Keyserling, Thomas C; Ammerman, Alice S

    2013-11-01

    We examined associations between access to food venues (farmers’ markets and supermarkets), shopping patterns, fruit and vegetable consumption and health indicators among women of reproductive age in eastern North Carolina, U.S.A. Access to food venues was measured using a Geographic Information System incorporating distance, seasonality and business hours, to quantify access to farmers’ markets. Produce consumption was assessed by self-report of eating five or more fruits and vegetables daily. BMI and blood pressure were assessed by clinical measurements. Poisson regression with robust variance was used for dichotomous outcomes and multiple linear regression was used for continuous outcomes. As the study occurred in a university town and university students are likely to have different shopping patterns from non-students, we stratified analyses by student status. Eastern North Carolina. Low-income women of reproductive age (18–44 years) with valid address information accessing family planning services at a local health department (n 400). Over a quarter reported ever shopping at farmers’ markets (114/400). A larger percentage of women who shopped at farmers’ markets consumed five or more fruits and vegetables daily (42.1%) than those who did not (24.0%; P women reported shopping was 11.4 (SD 9.0) km (7.1 (SD 5.6) miles), while the mean distance to the farmers’ market closest to the residence was 4.0 (SD 3.7) km (2.5 (SD 2.3) miles). Among non-students, those who shopped at farmers’ markets were more likely to consume five or more servings of fruits and vegetables daily. Future research should further explore potential health benefits of farmers’ markets.

  14. Saturn satellites

    International Nuclear Information System (INIS)

    Ruskol, E.L.

    1981-01-01

    The characteristics of the Saturn satellites are discussed. The satellites close to Saturn - Janus, Mimas, Enceladus, Tethys, Dione and Rhea - rotate along the circular orbits. High reflectivity is attributed to them, and the density of the satellites is 1 g/cm 3 . Titan is one of the biggest Saturn satellites. Titan has atmosphere many times more powerful than that of Mars. The Titan atmosphere is a peculiar medium with a unique methane and hydrogen distribution in the whole Solar system. The external satellites - Hyperion, Japetus and Phoebe - are poorly investigated. Neither satellite substance density, nor their composition are known. The experimental data on the Saturn rings obtained on the ''Pioneer-11'' and ''Voyager-1'' satellites are presented [ru

  15. Vegetation Dynamics and Rainfall Sensitivity of the Amazon

    Science.gov (United States)

    Hilker, Thomas; Lyapustin, Alexei I.; Tucker, Compton J.; Hall, Forrest G.; Myneni, Ranga B.; Wang, Yujie; Bi, Jian; Mendes de Moura, Yhasmin; Sellers, Piers J.

    2014-01-01

    We show that the vegetation canopy of the Amazon rainforest is highly sensitive to changes in precipitation patterns and that reduction in rainfall since 2000 has diminished vegetation greenness across large parts of Amazonia. Large-scale directional declines in vegetation greenness may indicate decreases in carbon uptake and substantial changes in the energy balance of the Amazon. We use improved estimates of surface reflectance from satellite data to show a close link between reductions in annual precipitation, El Nino southern oscillation events, and photosynthetic activity across tropical and subtropical Amazonia. We report that, since the year 2000, precipitation has declined across 69% of the tropical evergreen forest (5.4 million sq km) and across 80% of the subtropical grasslands (3.3 million sq km). These reductions, which coincided with a decline in terrestrial water storage, account for about 55% of a satellite-observed widespread decline in the normalized difference vegetation index (NDVI). During El Nino events, NDVI was reduced about 16.6% across an area of up to 1.6 million sq km compared with average conditions. Several global circulation models suggest that a rise in equatorial sea surface temperature and related displacement of the intertropical convergence zone could lead to considerable drying of tropical forests in the 21st century. Our results provide evidence that persistent drying could degrade Amazonian forest canopies, which would have cascading effects on global carbon and climate dynamics.

  16. Centriolar satellites

    DEFF Research Database (Denmark)

    Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon

    2015-01-01

    Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....

  17. Satellites You Can See for Homework

    Science.gov (United States)

    Broderick, Stephen

    2012-01-01

    Artificial satellites are easily observed most nights when the weather is fine. The website called "Heavens Above" at www.heavens-above.com will help locate these satellites flying over one's location. It also includes how bright they will appear. The direction of travel of each satellite in the night sky also indicates the type of satellite. For…

  18. AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    P. Kupidura

    2016-06-01

    Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

  19. ALPINE VEGETATION ECOTONE DYNAMICS IN GANGOTRI CATCHMENT USING REMOTE SENSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    C. P. Singh

    2012-09-01

    Full Text Available Analysis of the satellite imagery reveals two different perspectives of the vegetation ecotone dynamics in Gangotri catchment. On one hand, there is evidence of upward shift in the alpine tree and vegetation ecotone over three decades. On the other hand, there has been densification happening at the past treeline. The time series fAPAR data of two decades from NOAA-AVHRR confirms the greening trend in the area. The density of trees in Chirbasa has gone up whereas in Bhojbasa there is no significant change in NDVI but the number of groves has increased. Near Gaumukh the vegetal activity has not shown any significant change. We found that the treeline extracted from satellite imagery has moved up about 327±80m and other vegetation line has moved up about 401±77m in three decades. The vertical rate of treeline shift is found to be 11m/yr with reference to 1976 treeline; however, this can be 5m/yr if past toposheet records (1924 – 45 are considered as reliable reference. However, the future IPCC scenario based bioclimatic fundamental niche modelling of the Betula utilis (a surrogate to alpine treeline suggests that treeline could be moving upward with an average rate of 3m/yr. This study not only confirms that there is an upward shift of vegetation in the alpine zone of Himalayas, but also indicate that old vegetation ecotones have grown denser

  20. Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

    Science.gov (United States)

    Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

    2016-08-01

    Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

  1. Kuchler Vegetation

    Data.gov (United States)

    California Natural Resource Agency — Digital version of potential natural plant communites as compiled and published on 'Map of the Natural Vegetation of California' by A. W. Kuchler, 1976. Source map...

  2. Wieslander Vegetation

    Data.gov (United States)

    California Natural Resource Agency — Digital version of the 1945 California Vegetation Type Maps by A. E. Wieslander of the U.S. Forest Service. Source scale of maps are 1:100,000. These compiled maps...

  3. Satellite Communications

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Satellite Communications. Arthur C Clarke wrote a seminal paper in 1945 in wireless world. Use three satellites in geo-synchronous orbit to enable intercontinental communications. System could be realised in '50 to 100 years'

  4. Observational Quantification of Climatic and Human Influences on Vegetation Greening in China

    Directory of Open Access Journals (Sweden)

    Wenjian Hua

    2017-04-01

    Full Text Available This study attempts to quantify the relative contributions of vegetation greening in China due to climatic and human influences from multiple observational datasets. Satellite measured vegetation greenness, Normalized Difference Vegetation Index (NDVI, and relevant climate, land cover, and socioeconomic data since 1982 are analyzed using a multiple linear regression (MLR method. A statistically significant positive trend of average growing-season (April–October NDVI is found over more than 34% of the vegetated areas, mainly in North China, while significant decreases in NDVI are only seen in less than 5% of the areas. The relationships between vegetation and climate (temperature, precipitation, and radiation vary by geographical location and vegetation type. We estimate the NDVI changes in association with the non-climatic effects by removing the climatic effects from the original NDVI time series using the MLR analysis. Our results indicate that land use change is the dominant factor driving the long-term changes in vegetation greenness. The significant greening in North China is due to the increase in crops, grasslands, and forests. The socioeconomic datasets provide consistent and supportive results for the non-climatic effects at the provincial level that afforestation and reduced fire events generally have a major contribution. This study provides a basis for quantifying the non-climatic effects due to possible human influences on the vegetation greening in China.

  5. Assessing Riparian Vegetation Condition and Function in Disturbed Sites of the Arid Northwestern Mexico

    Directory of Open Access Journals (Sweden)

    Lara Cornejo-Denman

    2018-01-01

    Full Text Available Transformation or modification of vegetation distribution and structure in arid riparian ecosystems can lead to the loss of ecological function. Mexico has 101,500,000 ha of arid lands, however there is a general lack of information regarding how arid riparian ecosystems are being modified. To assess these modifications, we use eight sites in the San Miguel River (central Sonora to analyze (1 riparian vegetation composition, structure and distribution using field sampling and remote sensing data from Unmanned Aerial Vehicles (UAV; (2 productivity (proxies, using vegetation indices derived from satellite data; and (3 variability posed by riparian vegetation and vegetation adjacent to riparian habitats. The development of a simple yet informative Anthropogenic-disturbance Index (ADI allowed us to classify and describe each study site. We found sharp differences in vegetation composition and structure between sites due to the absence/presence of obligate-riparian species. We also report significant difference between EVI (Enhanced Vegetation Index values for the dry season among vegetation types that develop near the edges of the river but differ in composition, suggesting that land cover changes form obligate-riparian to facultative-riparian species can lead to a loss in potential productivity. Finally, our tests suggest that sites with higher disturbance present lower photosynthetic activity.

  6. Earlier vegetation green-up has reduced spring dust storms.

    Science.gov (United States)

    Fan, Bihang; Guo, Li; Li, Ning; Chen, Jin; Lin, Henry; Zhang, Xiaoyang; Shen, Miaogen; Rao, Yuhan; Wang, Cong; Ma, Lei

    2014-10-24

    The observed decline of spring dust storms in Northeast Asia since the 1950s has been attributed to surface wind stilling. However, spring vegetation growth could also restrain dust storms through accumulating aboveground biomass and increasing surface roughness. To investigate the impacts of vegetation spring growth on dust storms, we examine the relationships between recorded spring dust storm outbreaks and satellite-derived vegetation green-up date in Inner Mongolia, Northern China from 1982 to 2008. We find a significant dampening effect of advanced vegetation growth on spring dust storms (r = 0.49, p = 0.01), with a one-day earlier green-up date corresponding to a decrease in annual spring dust storm outbreaks by 3%. Moreover, the higher correlation (r = 0.55, p storm outbreak ratio (the ratio of dust storm outbreaks to times of strong wind events) indicates that such effect is independent of changes in surface wind. Spatially, a negative correlation is detected between areas with advanced green-up dates and regional annual spring dust storms (r = -0.49, p = 0.01). This new insight is valuable for understanding dust storms dynamics under the changing climate. Our findings suggest that dust storms in Inner Mongolia will be further mitigated by the projected earlier vegetation green-up in the warming world.

  7. Identification of High-Variation Fields based on Open Satellite Imagery

    DEFF Research Database (Denmark)

    Jeppesen, Jacob Høxbroe; Jacobsen, Rune Hylsberg; Nyholm Jørgensen, Rasmus

    2017-01-01

    . The categorization is based on vegetation indices derived from Sentinel-2 satellite imagery. A case study on 7678 winter wheat fields is presented, which employs open data and open source software to analyze the satellite imagery. Furthermore, the method can be automated to deliver categorizations at every update......This paper proposes a simple method for categorizing fields on a regional level, with respect to intra-field variations. It aims to identify fields where the potential benefits of applying precision agricultural practices are highest from an economic and environmental perspective...

  8. On the characterization of vegetation recovery after fire disturbance using Fisher-Shannon analysis and SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series

    Science.gov (United States)

    Lasaponara, Rosa; Lanorte, Antonio; Lovallo, Michele; Telesca, Luciano

    2015-04-01

    characterize vegetation recovery after fire disturbanceInternational Journal of Applied Earth Observation and Geoinformation 26 441-446 Lanorte A, M Danese, R Lasaponara, B Murgante 2014 Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis International Journal of Applied Earth Observation and Geoinformation 20, 42-51 Tuia D, F Ratle, R Lasaponara, L Telesca, M Kanevski 2008 Scan statistics analysis of forest fire clusters Communications in Nonlinear Science and Numerical Simulation 13 (8), 1689-1694 Telesca L, R Lasaponara 2006 Pre and post fire behavioral trends revealed in satellite NDVI time series Geophysical Research Letters 33 (14) Lasaponara R 2005 Intercomparison of AVHRR based fire susceptibility indicators for the Mediterranean ecosystems of southern Italy International Journal of Remote Sensing 26 (5), 853-870

  9. Environmental changes and microbiological health risks. Satellite-derived turbidity: an indicator of "health hazard" for surface water in West Africa (Bagre lake, Burkina Faso).

    Science.gov (United States)

    Robert, E.; Grippa, M.; Kergoat, L.; Martinez, J.; Pinet, S.; Gal, L.; Soumaguel, N.

    2015-12-01

    A significant correlation exists between the concentration of parasites, bacteria and some water quality parameters including surface suspended solids (SSS) and turbidity. Suspended particles can carry viruses and pathogenic bacteria affecting human health and foster their development. High SSS, associated with high turbidity, can therefore be considered as a vector of microbiological contaminants, causing diarrheal diseases. Few studies have focused on the turbidity parameter in rural Africa, while many cases of intestinal parasitic infections are due to the consumption of unsafe water from ponds, lakes, and rivers. Monitoring turbidity may therefore contribute to health hazard monitoring. Turbidity refers to the optical properties of water and is known to impact water reflectance in the visible and near-infrared domain. Ideally, its spatial and temporal variability requires the use of high temporal resolution (MODIS) and spatial resolution (Landsat, SPOT, Sentinel-2). Here we investigate turbidity in West-Africa. Various algorithms and indices proposed in the literature for inland waters are applied to MODIS series and to Landsat 7 and 8 CDR images, and SPOT5 images. The data and algorithms are evaluated with field measurements: turbidity, SSS, and hyperspectral ground radiometry. We show that turbidity of the Bagre Lake displays a strong increase over 2000-2015, associated with the corresponding increase of the red and NIR reflectances, as well as a reduction of the seasonal variations. Water level derived from the Jason 2 altimeter does not explain such variations. The most probable hypothesis is a change in land use (increase in bare and degraded soils), that leads to an increase in the particles transported by surface runoff to the lake. Such an increase in turbidity reinforces the health risk. We will discuss the link between turbidity and health in view of data from health centers on diarrheal diseases as well as data on practices and uses of populations.

  10. Satellite Communications

    CERN Document Server

    Pelton, Joseph N

    2012-01-01

    The field of satellite communications represents the world's largest space industry. Those who are interested in space need to understand the fundamentals of satellite communications, its technology, operation, business, economic, and regulatory aspects. This book explains all this along with key insights into the field's future growth trends and current strategic challenges. Fundamentals of Satellite Communications is a concise book that gives all of the key facts and figures as well as a strategic view of where this dynamic industry is going. Author Joseph N. Pelton, PhD, former Dean of the International Space University and former Director of Strategic Policy at Intelstat, presents a r

  11. Analysis of series temporal vegetation obtained by tele detection as tool for a tracking processes of desertification

    International Nuclear Information System (INIS)

    Melendez-Pastor, I.; Navarro-Pedreno, J.; Gomez, I.; Koch, M.

    2009-01-01

    This risk of desertification in the Mediterranean Basin, is evident in the southeast of the Iberian Peninsula, where land degradation reaches unsustainable levels. this study aims to analyse the temporal evolution of land covers as an indicator of soil desertification. time series of vegetation indices derived from satellite remote sensing images were analysed. Various climatic variables as possible causes of land covers behaviour were considered. The existence of a large inter-annual and intra-annual variability for all land covers and precipitation was observed. It is showed an association between temporal patterns of vegetation series of different land uses and rainfall. (Author) 8 refs.

  12. The ecology of malaria--as seen from Earth-observation satellites.

    Science.gov (United States)

    Thomson, M C; Connor, S J; Milligan, P J; Flasse, S P

    1996-06-01

    Data from sensors on board geostationary and polar-orbiting, meteorological satellites (Meteosat and NOAA series) are routinely obtained free, via local reception systems, in an increasing number of African countries. Data collected by these satellites are processed to produce proxy ecological variables which have been extensively investigated for monitoring changes in the distribution and condition of different natural resources, including rainfall and vegetation state. How these data products (once incorporated, along with other data, into a geographical information system) could contribute to the goals of monitoring patterns of malaria transmission, predicting epidemics and planning control strategies is the subject of the present review. By way of illustration, an analysis of two of these products, normalized difference vegetation index (NVDI) and cold-cloud duration (CCD), is given in conjunction with epidemiological and entomological data from The Gambia, a country where extensive studies on malaria transmission have been undertaken in recent years. Preliminary results indicate that even simple analysis of proxy ecological variables derived from satellite data can indicate variation in environmental factors affecting malaria-transmission indices. However, it is important to note that the associations observed will vary depending on the local ecology, season and species of vector. Whilst further quantitative research is required to validate the relationship between satellite-data products and malaria-transmission indices, this approach offers a means by which detailed knowledge of the underlying spatial and temporal variation in the environment can be incorporated into a decision-support system for malaria control.

  13. Vegetation impoverishment despite greening: a case study from central Senegal

    Science.gov (United States)

    Herrmann, Stefanie M.; Tappan, G. Gray

    2013-01-01

    Recent remote sensing studies have documented a greening trend in the semi-arid Sahel and Sudan zones of West Africa since the early 1980s, which challenges the mainstream paradigm of irreversible land degradation in this region. What the greening trend means on the ground, however, has not yet been explored. This research focuses on a region in central Senegal to examine changes in woody vegetation abundance and composition in selected sites by means of a botanical inventory of woody vegetation species, repeat photography, and perceptions of local land users. Despite the greening, an impoverishment of the woody vegetation cover was observed in the studied sites, indicated by an overall reduction in woody species richness, a loss of large trees, an increasing dominance of shrubs, and a shift towards more arid-tolerant, Sahelian species since 1983. Thus, interpretation of the satellite-derived greening trend as an improvement or recovery is not always justified. The case of central Senegal represents only one of several possible pathways of greening throughout the region, all of which result in similar satellite-derived greening signals.

  14. Vegetation anomalies caused by antecedent precipitation in most of the world

    Science.gov (United States)

    Papagiannopoulou, C.; Miralles, D. G.; Dorigo, W. A.; Verhoest, N. E. C.; Depoorter, M.; Waegeman, W.

    2017-07-01

    Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981-2010. This included semiarid climates but also transitional ecoregions. Intra-annually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, non-linear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981-2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth

  15. Satellite myths

    Science.gov (United States)

    Easton, Roger L.; Hall, David

    2008-01-01

    Richard Corfield's article “Sputnik's legacy” (October 2007 pp23-27) states that the satellite on board the US Vanguard rocket, which exploded during launch on 6 December 1957 two months after Sputnik's successful take-off, was “a hastily put together contraption of wires and circuitry designed only to send a radio signal back to Earth”. In fact, the Vanguard satellite was developed over a period of several years and put together carefully using the best techniques and equipment available at the time - such as transistors from Bell Laboratories/Western Electric. The satellite contained not one but two transmitters, in which the crystal-controlled oscillators had been designed to measure both the temperature of the satellite shell and of the internal package.

  16. Satellite Geomagnetism

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia

    2012-01-01

    Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade....... The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites....

  17. Vegetation indices as indicators of damage by the sunn pest ...

    African Journals Online (AJOL)

    The sunn pest, Eurygaster integriceps Put. (Hemiptera: Scutelleridae), also known as sting or cereal pest, is one of the most economically important pests of wheat in the world. In this study, a collapsible nylon cloth cage experiments were conducted to determine the feasibility of using remote sensing techniques to detect ...

  18. 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.

  19. Boomerang Satellites

    Science.gov (United States)

    Hesselbrock, Andrew; Minton, David A.

    2017-10-01

    We recently reported that the orbital architecture of the Martian environment allows for material in orbit around the planet to ``cycle'' between orbiting the planet as a ring, or as coherent satellites. Here we generalize our previous analysis to examine several factors that determine whether satellites accreting at the edge of planetary rings will cycle. In order for the orbiting material to cycle, tidal evolution must decrease the semi-major axis of any accreting satellites. In some systems, the density of the ring/satellite material, the surface mass density of the ring, the tidal parameters of the system, and the rotation rate of the primary body contribute to a competition between resonant ring torques and tidal dissipation that prevent this from occurring, either permanently or temporarily. Analyzing these criteria, we examine various bodies in our solar system (such as Saturn, Uranus, and Eris) to identify systems where cycling may occur. We find that a ring-satellite cycle may give rise to the current Uranian ring-satellite system, and suggest that Miranda may have formed from an early, more massive Uranian ring.

  20. Vegetative regeneration

    Science.gov (United States)

    George A. Schier; John R. Jones; Robert P. Winokur

    1985-01-01

    Aspen is noted for its ability to regenerate vegetatively by adventitious shoots or suckers that arise on its long lateral roots. It also produces sprouts from stumps and root collars; but they are not common. In a survey of regeneration after clearcutting mature aspen in Utah. Baker (1918b) found that 92% of the shoots originated from roots, 7% from root collars, and...

  1. Understory vegetation

    Science.gov (United States)

    Steve Sutherland; Todd F. Hutchinson; Jennifer L. Windus

    2003-01-01

    This chapter documents patterns of species composition and diversity within the understory vegetation layer and provides a species list for the four study areas in southern Ohio. Within each of 108 plots, we recorded the frequency of all vascular plant species in sixteen 2-m² quadrats. We recorded 297 species, including 187 forbs (176 perennials, 9 annuals, 2...

  2. Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery

    Directory of Open Access Journals (Sweden)

    M. C. Anderson

    2011-01-01

    Full Text Available Thermal infrared (TIR remote sensing of land-surface temperature (LST provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil + canopy land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5 to 10-km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions on the order of 10 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe, Africa

  3. Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

    Science.gov (United States)

    Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

    2017-04-01

    Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger

  4. Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt

    Science.gov (United States)

    Gamon, John A.; Huemmrich, K. Fred; Stone, Robert S.; Tweedie, Craig E.

    2015-01-01

    In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.

  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. 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. Asteroid Satellites

    Science.gov (United States)

    Merline, W. J.

    2001-11-01

    Discovery and study of small satellites of asteroids or double asteroids can yield valuable information about the intrinsic properties of asteroids themselves and about their history and evolution. Determination of the orbits of these moons can provide precise masses of the primaries, and hence reliable estimates of the fundamental property of bulk density. This reveals much about the composition and structure of the primary and will allow us to make comparisons between, for example, asteroid taxonomic type and our inventory of meteorites. The nature and prevalence of these systems will also give clues as to the collisional environment in which they formed, and have further implications for the role of collisions in shaping our solar system. A decade ago, binary asteroids were more of a theoretical curiosity. In 1993, the Galileo spacecraft allowed the first undeniable detection of an asteroid moon, with the discovery of Dactyl, a small moon of Ida. Since that time, and particularly in the last year, the number of known binaries has risen dramatically. Previously odd-shaped and lobate near-Earth asteroids, observed by radar, have given way to signatures indicating, almost certainly, that at least four NEAs are binary systems. The tell-tale lightcurves of several other NEAs reveal a high likelihood of being double. Indications are that among the NEAs, there may be a binary frequency of several tens of percent. Among the main-belt asteroids, we now know of 6 confirmed binary systems, although their overall frequency is likely to be low, perhaps a few percent. The detections have largely come about because of significant advances in adaptive optics systems on large telescopes, which can now reduce the blurring of the Earth's atmosphere to compete with the spatial resolution of space-based imaging (which itself, via HST, is now contributing valuable observations). Most of these binary systems have similarities, but there are important exceptions. Searches among other

  8. Recent Vegetation Fire Incidence in Russia

    OpenAIRE

    Hayasaka, Hiroshi

    2011-01-01

    MODIS hotspot data from NASA have now become a standard means of evaluating vegetation fires worldwide. Remote sensing is the most effective tool for large countries like Russia because it is hard to obtain exact, detailed forest fire data. Accumulated MODIS hotspot data of the nine years from 2002 to 2010 may allow us to assess recent changes in the vegetation fire incidence in Russia. This kind of analysis using various satellites is useful in estimating fire intensity and sever...

  9. Assessing global vegetation activity using spatio-temporal Bayesian modelling

    Science.gov (United States)

    Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

    2016-04-01

    This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support

  10. Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

    Science.gov (United States)

    McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

    2008-01-01

    The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify

  11. Par Pond vegetation status Summer 1995 -- Summary

    International Nuclear Information System (INIS)

    Mackey, H.E. Jr.; Riley, R.S.

    1996-01-01

    The water level of Par Pond was lowered approximately 20 feet in mid-1991 in order to protect downstream residents from possible dam failure suggested by subsidence on the downstream slope of the dam and to repair the dam. This lowering exposed both emergent and nonemergent macrophyte beds to drying conditions resulting in extensive losses. A survey of the newly emergent, shoreline aquatic plant communities of Par Pond began in June 1995, three months after the refilling of Par Pond to approximately 200 feet above mean sea level. These surveys continued in July, September, and late October, 1995. Communities similar to the pre-drawdown, Par Pond aquatic plant communities are becoming re-established. Emergent beds of maidencane, lotus, waterlily, and watershield are extensive and well developed. Cattail occurrence continued to increase during the summer, but large beds common to Par Pond prior to the drawdown have not formed. Estimates from SPOT HRV, remote sensing satellite data indicated that as much as 120 hectares of emergent wetlands vegetation may have been present along the Par Pond shoreline by early October, 1995. To track the continued development of macrophytes in Par Pond, future surveys throughout 1996 and 1997, along with the continued evaluation of satellite data to map the areal extent of the macrophyte beds of Par Pond, are planned

  12. Satellite Radio

    Indian Academy of Sciences (India)

    Satellites have been a highly effective platform for multi- form broadcasts. This has led to a ... diversity offormats, languages, genre, and a universal reach that cannot be met by .... programs can be delivered to whom it is intended. In the case of.

  13. The Effect of Vegetation Productivity on Millet Prices in the Informal Markets of Mali, Burkina Faso and Niger

    Energy Technology Data Exchange (ETDEWEB)

    Brown, M.E. [Department of Geography, University of Maryland, NASA Goddard Space Flight Center, Code 923, Greenbelt, MD 20771 (United States); Pinzon, J.E. [Science Systems and Applications Inc., NASA Goddard Space Flight Center, Code 923, Greenbelt, MD (United States); Prince, S.D. [Department of Geography, University of Maryland, College Park, MD (United States)

    2006-09-15

    Systematic evaluation of food security throughout the Sahel has been attempted for nearly two decades. Food security analyses have used both food prices to determine the ability of the population to access food, and satellite-derived vegetation indices that measure vegetation production to establish how much food is available each year. The relationship between these two food security indicators is explored here using correspondence analysis and through the use of Markov chain models. Two sources of quantitative data were used: 8 km normalized difference vegetation index (NDVI) data from the Advanced Very High Resolution Radiometers (AVHRR) carried on the NOAA series of satellites, and monthly millet prices from 445 markets in Mali, Niger and Burkina Faso. The results show that the growing season vegetation production is related to the price of millet at the annual and the seasonal time scales. If the growing season was characterized by erratic, sparse rainfall, it resulted in higher prices, and well-distributed, abundant rainfall resulted in lower prices. The correspondence between vegetation production and millet prices is used to produce maps of millet prices for West Africa.

  14. 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.

  15. Trends in mobile satellite communication

    Science.gov (United States)

    Johannsen, Klaus G.; Bowles, Mike W.; Milliken, Samuel; Cherrette, Alan R.; Busche, Gregory C.

    1993-01-01

    Ever since the U.S. Federal Communication Commission opened the discussion on spectrum usage for personal handheld communication, the community of satellite manufacturers has been searching for an economically viable and technically feasible satellite mobile communication system. Hughes Aircraft Company and others have joined in providing proposals for such systems, ranging from low to medium to geosynchronous orbits. These proposals make it clear that the trend in mobile satellite communication is toward more sophisticated satellites with a large number of spot beams and onboard processing, providing worldwide interconnectivity. Recent Hughes studies indicate that from a cost standpoint the geosynchronous satellite (GEOS) is most economical, followed by the medium earth orbit satellite (MEOS) and then by the low earth orbit satellite (LEOS). From a system performance standpoint, this evaluation may be in reverse order, depending on how the public will react to speech delay and collision. This paper discusses the trends and various mobile satellite constellations in satellite communication under investigation. It considers the effect of orbital altitude and modulation/multiple access on the link and spacecraft design.

  16. Improved drought monitoring in the Greater Horn of Africa by combining meteorological and remote sensing based indicators

    DEFF Research Database (Denmark)

    Horion, Stéphanie Marie Anne F; Kurnik, Blaz; Barbosa, Paulo

    2010-01-01

    , and therefore to better trigger timely and appropriate actions on the field. In this study, meteorological and remote sensing based drought indicators were compared over the Greater Horn of Africa in order to better understand: (i) how they depict historical drought events ; (ii) if they could be combined...... distribution. Two remote sensing based indicators were tested: the Normalized Difference Water Index (NDWI) derived from SPOT-VEGETATION and the Global Vegetation Index (VGI) derived form MERIS. The first index is sensitive to change in leaf water content of vegetation canopies while the second is a proxy...... of the amount and vigour of vegetation. For both indexes, anomalies were estimated using available satellite archives. Cross-correlations between remote sensing based anomalies and SPI were analysed for five land covers (forest, shrubland, grassland, sparse grassland, cropland and bare soil) over different...

  17. Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI composite data using agricultural measurements: an example at corn fields in western Mexico.

    Science.gov (United States)

    Chen, Pei-Yu; Fedosejevs, Gunar; Tiscareño-López, Mario; Arnold, Jeffrey G

    2006-08-01

    Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data.

  18. Migratory herbivorous waterfowl track satellite-derived green wave index.

    Directory of Open Access Journals (Sweden)

    Mitra Shariatinajafabadi

    Full Text Available Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI, has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7. Data were collected over three years (2008-2010. Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%, while the Greenland geese followed an earlier stage (GWI 20-40%. Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration, thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

  19. EVALUATING THE POTENTIAL OF SATELLITE HYPERSPECTRAL RESURS-P DATA FOR FOREST SPECIES CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    O. Brovkina

    2016-06-01

    Full Text Available Satellite-based hyperspectral sensors provide spectroscopic information in relatively narrow contiguous spectral bands over a large area which can be useful in forestry applications. This study evaluates the potential of satellite hyperspectral Resurs-P data for forest species mapping. Firstly, a comparative study between top of canopy reflectance obtained from the Resurs-P, from the airborne hyperspectral scanner CASI and from field measurement (FieldSpec ASD 4 on selected vegetation cover types is conducted. Secondly, Resurs-P data is tested in classification and verification of different forest species compartments. The results demonstrate that satellite hyperspectral Resurs-P sensor can produce useful informational and show good performance for forest species classification comparable both with forestry map and classification from airborne CASI data, but also indicate that developments in pre-processing steps are still required to improve the mapping level.

  20. 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, P.S.; Mariotto, I.; Gumma, M.K.; Middleton, E.M.; Landis, D.R.; Huemmrich, K.F.

    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 ~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 ~20 HNBs. The accuracy of classifying these 8 crops using HNBs was around 95%, which was ~ 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.g., biophysi- al

  1. Use of UAVs for Remote Measurement of Vegetation Canopy Variables

    Science.gov (United States)

    Rango, A.; Laliberte, A.; Herrick, J.; Steele, C.; Bestelmeyer, B.; Chopping, M. J.

    2006-12-01

    Remote sensing with different sensors has proven useful for measuring vegetation canopy variables at scales ranging from landscapes down to individual plants. For use at landscape scales, such as desert grasslands invaded by shrubs, it is possible to use multi-angle imagery from satellite sensors, such as MISR and CHRIS/Proba, with geometric optical models to retrieve fractional woody plant cover. Vegetation community states can be mapped using visible and near infrared ASTER imagery at 15 m resolution. At finer scales, QuickBird satellite imagery with approximately 60 cm resolution and piloted aircraft photography with 25-80 cm resolution can be used to measure shrubs above a critical size. Tests conducted with the QuickBird data in the Jornada basin of southern New Mexico have shown that 87% of all shrubs greater than 2 m2 were detected whereas only about 29% of all shrubs less than 2 m2 were detected, even at these high resolutions. Because there is an observational gap between satellite/aircraft measurements and ground observations, we have experimented with Unmanned Aerial Vehicles (UAVs) producing digital photography with approximately 5 cm resolution. We were able to detect all shrubs greater than 2 m2, and we were able to map small subshrubs indicative of rangeland deterioration, as well as remnant grass patches, for the first time. None of these could be identified on the 60 cm resolution data. Additionally, we were able to measure canopy gaps, shrub patterns, percent bare soil, and vegetation cover over mixed rangeland vegetation. This approach is directly applicable to rangeland health monitoring, and it provides a quantitative way to assess shrub invasion over time and to detect the depletion or recovery of grass patches. Further, if the UAV images have sufficient overlap, it may be possible to exploit the stereo viewing capabilities to develop a digital elevation model from the orthophotos, with a potential for extracting canopy height. We envision two

  2. A MODIS-based vegetation index climatology

    Science.gov (United States)

    Our motivation here is to provide information for the NASA Soil Moisture Active Passive (SMAP) satellite soil moisture retrieval algorithms (launch in 2014). Vegetation attenuates the signal and the algorithms must correct for this effect. One approach is to use data that describes the canopy water ...

  3. Scientific Satellites

    Science.gov (United States)

    1967-01-01

    noise signal level exceeds 10 times the normal background. EXPERIMENTS FOR SATELLITE ASTRONOMY 615 ANTENNA MONOPOLE -., PREAMPLFE = BANDPASS-FILTER...OUTPUT TO AND DETECTOR TELEMETRYCHANNELS (18) CALIBRATION NOISE MATRIX CLOCK NOISE SOURCE ’ON’ SOURCE COMMAND F ROM PROGRAMERP ANTENNA MONOPOLE FIGURE 13...Animal Tempera- ture Sensing for Studying the Effect of Prolonged Orbital Flight on the Circadian Rhythms of Pocket Mice . Unmanned Spacecraft Meeting

  4. The MODIS Vegetation Canopy Water Content product

    Science.gov (United States)

    Ustin, S. L.; Riano, D.; Trombetti, M.

    2008-12-01

    Vegetation water stress drives wildfire behavior and risk, having important implications for biogeochemical cycling in natural ecosystems, agriculture, and forestry. Water stress limits plant transpiration and carbon gain. The regulation of photosynthesis creates close linkages between the carbon, water, and energy cycles and through metabolism to the nitrogen cycle. We generated systematic weekly CWC estimated for the USA from 2000-2006. MODIS measures the sunlit reflectance of the vegetation in the visible, near-infrared, and shortwave infrared. Radiative transfer models, such as PROSPECT-SAILH, determine how sunlight interacts with plant and soil materials. These models can be applied over a range of scales and ecosystem types. Artificial Neural Networks (ANN) were used to optimize the inversion of these models to determine vegetation water content. We carried out multi-scale validation of the product using field data, airborne and satellite cross-calibration. An Algorithm Theoretical Basis Document (ATBD) of the product is under evaluation by NASA. The CWC product inputs are 1) The MODIS Terra/Aqua surface reflectance product (MOD09A1/MYD09A1) 2) The MODIS land cover map product (MOD12Q1) reclassified to grassland, shrub-land and forest canopies; 3) An ANN trained with PROSPECT-SAILH; 4) A calibration file for each land cover type. The output is an ENVI file with the CWC values. The code is written in Matlab environment and is being adapted to read not only the 8 day MODIS composites, but also daily surface reflectance data. We plan to incorporate the cloud and snow mask and generate as output a geotiff file. Vegetation water content estimates will help predicting linkages between biogeochemical cycles, which will enable further understanding of feedbacks to atmospheric concentrations of greenhouse gases. It will also serve to estimate primary productivity of the biosphere; monitor/assess natural vegetation health related to drought, pollution or diseases

  5. Solar satellites

    Energy Technology Data Exchange (ETDEWEB)

    Poher, C.

    1982-01-01

    A reference system design, projected costs, and the functional concepts of a satellite solar power system (SSPS) for converting sunlight falling on solar panels of a satellite in GEO to a multi-GW beam which could be received by a rectenna on earth are outlined. Electricity transmission by microwaves has been demonstrated, and a reference design system for supplying 5 GW dc to earth was devised. The system will use either monocrystalline Si or concentrator GaAs solar cells for energy collection in GEO. Development is still needed to improve the lifespan of the cells. Currently, the cell performance degrades 50 percent in efficiency after 7-8 yr in space. Each SSPS satellite would weigh either 34,000 tons (Si) or 51,000 tons (GaAs), thereby requiring the fabrication of a heavy lift launch vehicle or a single-stage-to-orbit transport in order to minimize launch costs. Costs for the solar panels have been estimated at $500/kW using the GaAs technology, with transport costs for materials to GEO being $40/kg.

  6. Solar satellites

    Science.gov (United States)

    Poher, C.

    A reference system design, projected costs, and the functional concepts of a satellite solar power system (SSPS) for converting sunlight falling on solar panels of a satellite in GEO to a multi-GW beam which could be received by a rectenna on earth are outlined. Electricity transmission by microwaves has been demonstrated, and a reference design system for supplying 5 GW dc to earth was devised. The system will use either monocrystalline Si or concentrator GaAs solar cells for energy collection in GEO. Development is still needed to improve the lifespan of the cells. Currently, the cell performance degrades 50 percent in efficiency after 7-8 yr in space. Each SSPS satellite would weigh either 34,000 tons (Si) or 51,000 tons (GaAs), thereby requiring the fabrication of a heavy lift launch vehicle or a single-stage-to-orbit transport in order to minimize launch costs. Costs for the solar panels have been estimated at $500/kW using the GaAs technology, with transport costs for materials to GEO being $40/kg.

  7. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  8. Assessing satellite-based start-of-season trends in the US High Plains

    International Nuclear Information System (INIS)

    Lin, X; Sassenrath, G F; Hubbard, K G; Mahmood, R

    2014-01-01

    To adequately assess the effects of global warming it is necessary to address trends and impacts at the local level. This study examines phenological changes in the start-of-season (SOS) derived from satellite observations from 1982–2008 in the US High Plains region. The surface climate-based SOS was also evaluated. The averaged profiles of SOS from 37° to 49°N latitude by satellite- and climate-based methods were in reasonable agreement, especially for areas where croplands were masked out and an additional frost date threshold was adopted. The statistically significant trends of satellite-based SOS show a later spring arrival ranging from 0.1 to 4.9 days decade −1 over nine Level III ecoregions. We found the croplands generally exhibited larger trends (later arrival) than the non-croplands. The area-averaged satellite-based SOS for non-croplands (i.e. mostly grasslands) showed no significant trends. We examined the trends of temperatures, precipitation, and standardized precipitation index (SPI), as well as the strength of correlation between the satellite-based SOS and these climatic drivers. Our results indicate that satellite-based SOS trends are spatially and primarily related to annual maximum normalized difference vegetation index (NDVI, mostly in summertime) and/or annual minimum NDVI (mostly in wintertime) and these trends showed the best correlation with six-month SPI over the period 1982–2008 in the US High Plains region. (letter)

  9. Quantifying the Vegetation Health Based on the Resilience in an Arid System

    Directory of Open Access Journals (Sweden)

    Ranjbar Abolfazl

    2018-03-01

    Full Text Available Proper management of natural ecosystems is not possible without the knowledge of the health status of its components. Vegetation, as the main component of the ecosystem, plays an important role in its health. One of the key determinants of vegetation health is its resilience in the face of environmental disorders. This research was conducted in parts of the Namakzar-e Khaf watershed in Northeast of South Khorasan Province with the aim of quantifying the vegetative resilience on behalf of the ecosystem health in response to long-term precipitation changes. First, the annual precipitation standardization was performed during a thirty-year period by the SPI method. Then, the average variation in TNDVI index obtained from the Landsat satellite images was examined and the resilience was tested by calculating the four effective factors (amplitude, malleability, damping and hysteresis. According to the results, the amplitude in the survey period was 6.04% and the vegetation has had different values of damping over the years. The most prominent example of vegetation resilience occurred between 1986 and 1996, with malleability of 0.7 and damping of zero. Vegetation in this period, after the elimination of drought effects (1986, has not only returned to the amount of vegetation of reference year with severe precipitation (1996 but also increased by 0.25%. This increase, as the index of hysteresis, has been presented for the first time in the ecosystem health discussion quantitatively in the present study. A set of quantitative calculations showed that despite reduced annual precipitation and drought events, the vegetation has been able to maintain its resilience, which indicates the health of vegetation in the studied ecosystem.

  10. 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.

  11. Assessment of Urban Vegetation using Remote Sensing Data: a Case Study in Seoul, Korea

    Science.gov (United States)

    Kim, H.; Kim, J.; Yeom, J.; Kim, Y.

    2011-12-01

    Vegetation in the city has various positive effects on the entire urban ecosystem: it reduces CO2 and air temperature, improves air quality, helps to maintain the water balance of natural ground, decreases surface overflow during floods, and provides food source as well as living space for diverse wildlife. Urban green areas also have a social and educational role, e.g. for recreational activity, positive experience in a natural environment, and perception of seasonal changes. In addition, citizens can find a balance between urban green and built up spaces. However, the very high intensity of land use in urban areas changes the local urban ecosystem to a large degree and leads to enormous stress for the urban vegetation. In this study, we aim to develop a method for assessing effects of urban vegetation on ecosystem function using remote sensing technology. We use multispectral RapidEye satellite and LiDAR data for the classification of urban vegetation types in metropolitan area Seoul and test different kinds of vegetation indices focusing on the red edge of RapidEye data to assess the stress degree of the vegetation.

  12. 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.

  13. 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.

  14. Generic index of aquatic vegetation (IVAM) for a rapid assessment of ecological quality of Spanish rivers: taxonomic resolution and application to Castilla-La Mancha region; Indice Generico de Vegetacion Acuatica (IVAM): Propuesta de evaluacion rapida del estado ecologico de los rios ibericos en aplicacion de la Directiva Marco del Agua

    Energy Technology Data Exchange (ETDEWEB)

    Moreno, J. L.; Navarro, C.; Hera, J. de las

    2005-07-01

    The Water Framework Directive proposes the use of aquatic flora as a valid bio indicator for assessing the ecological status of European rivers. Due to the lack of an aquatic vegetation index for Spanish rivers, we present an index to assess trophic status or eutrophication in rivers and streams. Thus, we calculated tolerance scores and indicator values for tax from nutrient levels. the index is called IVAM (Macroscopic Aquatic Vegetation Index). The index takes into account either macrophyte or microphytes (the latter making up macroscopic growth forms) including briophytes. The IVAM showed the best correlation with nutrients besides other quality indices, indicating a solid tool to assess trophic status or eutrophication. (Author) 15 refs.

  15. Using Satellite Remote Sensing Data in a Spatially Explicit Price Model

    Science.gov (United States)

    Brown, Molly E.; Pinzon, Jorge E.; Prince, Stephen D.

    2007-01-01

    Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.

  16. Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach

    Science.gov (United States)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah

    2016-06-01

    The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

  17. ANALYSIS OF YEAR 2002 SEASONAL FOREST DYNAMICS USING TIME SERIES IN SITU LAI MEASUREMENTS AND MODIS LAI SATELLITE PRODUCTS

    Science.gov (United States)

    Multitemporal satellite images are the standard basis for regional-scale land-cover (LC) change detection. However, embedded in the data are the confounding effects of vegetation dynamics (phenology). As photosynthetic vegetation progresses through its annual cycle, the spectral ...

  18. Northern Everglades, Florida, satellite image map

    Science.gov (United States)

    Thomas, Jean-Claude; Jones, John W.

    2002-01-01

    These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

  19. South Florida Everglades: satellite image map

    Science.gov (United States)

    Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

    2001-01-01

    These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

  20. Estimating Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations

    Directory of Open Access Journals (Sweden)

    Bradley C. Reed

    2013-02-01

    Full Text Available Winter annual plants in southwestern North America influence fire regimes, provide forage, and help prevent erosion. Exotic annuals may also threaten native species. Monitoring winter annuals is difficult because of their ephemeral nature, making the development of a satellite monitoring tool valuable. We mapped winter annual aboveground biomass in the Desert Southwest from satellite observations, evaluating 18 algorithms using time-series vegetation indices (VI. Field-based biomass estimates were used to calibrate and evaluate each algorithm. Winter annual biomass was best estimated by calculating a base VI across the period of record and subtracting it from the peak VI for each winter season (R2 = 0.92. The normalized difference vegetation index (NDVI derived from 8-day reflectance data provided the best estimate of winter annual biomass. It is important to account for the timing of peak vegetation when relating field-based estimates to satellite VI data, since post-peak field estimates may indicate senescent biomass which is inaccurately represented by VI-based estimates. Images generated from the best-performing algorithm show both spatial and temporal variation in winter annual biomass. Efforts to manage this variable resource would be enhanced by a tool that allows the monitoring of changes in winter annual resources over time.

  1. Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

    Directory of Open Access Journals (Sweden)

    C. Albergel

    2017-10-01

    Full Text Available In this study, a global land data assimilation system (LDAS-Monde is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM and leaf area index (LAI observations to constrain the interactions between soil–biosphere–atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere land surface model (LSM coupled with the CNRM (Centre National de Recherches Météorologiques version of the Total Runoff Integrating Pathways (ISBA-CTRIP continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF, which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth. A sensitivity test of the Jacobians over 2000–2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm. The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A

  2. Lake Bathymetric Aquatic Vegetation

    Data.gov (United States)

    Minnesota Department of Natural Resources — Aquatic vegetation represented as polygon features, coded with vegetation type (emergent, submergent, etc.) and field survey date. Polygons were digitized from...

  3. Global Crop Monitoring: A Satellite-Based Hierarchical Approach

    Directory of Open Access Journals (Sweden)

    Bingfang Wu

    2015-04-01

    Full Text Available Taking advantage of multiple new remote sensing data sources, especially from Chinese satellites, the CropWatch system has expanded the scope of its international analyses through the development of new indicators and an upgraded operational methodology. The approach adopts a hierarchical system covering four spatial levels of detail: global, regional, national (thirty-one key countries including China and “sub-countries” (for the nine largest countries. The thirty-one countries encompass more that 80% of both production and exports of maize, rice, soybean and wheat. The methodology resorts to climatic and remote sensing indicators at different scales. The global patterns of crop environmental growing conditions are first analyzed with indicators for rainfall, temperature, photosynthetically active radiation (PAR as well as potential biomass. At the regional scale, the indicators pay more attention to crops and include Vegetation Health Index (VHI, Vegetation Condition Index (VCI, Cropped Arable Land Fraction (CALF as well as Cropping Intensity (CI. Together, they characterize crop situation, farming intensity and stress. CropWatch carries out detailed crop condition analyses at the national scale with a comprehensive array of variables and indicators. The Normalized Difference Vegetation Index (NDVI, cropped areas and crop conditions are integrated to derive food production estimates. For the nine largest countries, CropWatch zooms into the sub-national units to acquire detailed information on crop condition and production by including new indicators (e.g., Crop type proportion. Based on trend analysis, CropWatch also issues crop production supply outlooks, covering both long-term variations and short-term dynamic changes in key food exporters and importers. The hierarchical approach adopted by CropWatch is the basis of the analyses of climatic and crop conditions assessments published in the quarterly “CropWatch bulletin” which

  4. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  5. 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

  6. Satellite cells in human skeletal muscle plasticity.

    Science.gov (United States)

    Snijders, Tim; Nederveen, Joshua P; McKay, Bryon R; Joanisse, Sophie; Verdijk, Lex B; van Loon, Luc J C; Parise, Gianni

    2015-01-01

    Skeletal muscle satellite cells are considered to play a crucial role in muscle fiber maintenance, repair and remodeling. Our knowledge of the role of satellite cells in muscle fiber adaptation has traditionally relied on in vitro cell and in vivo animal models. Over the past decade, a genuine effort has been made to translate these results to humans under physiological conditions. Findings from in vivo human studies suggest that satellite cells play a key role in skeletal muscle fiber repair/remodeling in response to exercise. Mounting evidence indicates that aging has a profound impact on the regulation of satellite cells in human skeletal muscle. Yet, the precise role of satellite cells in the development of muscle fiber atrophy with age remains unresolved. This review seeks to integrate recent results from in vivo human studies on satellite cell function in muscle fiber repair/remodeling in the wider context of satellite cell biology whose literature is largely based on animal and cell models.

  7. Evaluation of a Linear Mixing Model to Retrieve Soil and Vegetation Temperatures of Land Targets

    International Nuclear Information System (INIS)

    Yang, Jinxin; Jia, Li; Cui, Yaokui; Zhou, Jie; Menenti, Massimo

    2014-01-01

    A simple linear mixing model of heterogeneous soil-vegetation system and retrieval of component temperatures from directional remote sensing measurements by inverting this model is evaluated in this paper using observations by a thermal camera. The thermal camera was used to obtain multi-angular TIR (Thermal Infra-Red) images over vegetable and orchard canopies. A whole thermal camera image was treated as a pixel of a satellite image to evaluate the model with the two-component system, i.e. soil and vegetation. The evaluation included two parts: evaluation of the linear mixing model and evaluation of the inversion of the model to retrieve component temperatures. For evaluation of the linear mixing model, the RMSE is 0.2 K between the observed and modelled brightness temperatures, which indicates that the linear mixing model works well under most conditions. For evaluation of the model inversion, the RMSE between the model retrieved and the observed vegetation temperatures is 1.6K, correspondingly, the RMSE between the observed and retrieved soil temperatures is 2.0K. According to the evaluation of the sensitivity of retrieved component temperatures on fractional cover, the linear mixing model gives more accurate retrieval accuracies for both soil and vegetation temperatures under intermediate fractional cover conditions

  8. Unravelling long-term vegetation change patterns in a binational watershed using multitemporal land cover data and historical photography

    Science.gov (United States)

    Villarreal, Miguel L.; Norman, Laura M.; Webb, Robert H.; Boyer, Diane E.; Turner, Raymond M.

    2011-01-01

    A significant amount of research conducted in the Sonoran Desert of North America has documented, both anecdotally and empirically, major vegetation changes over the past century due to human land use activities. However, many studies lack coincidental landscape-scale data characterizing the spatial and temporal manifestation of these changes. Vegetation changes in a binational (USA and Mexico) watershed were documented using a series of four land cover maps (1979-2009) derived from multispectral satellite imagery. Cover changes are compared to georeferenced, repeat oblique photographs dating from the late 19th century to present. Results indicate the expansion of grassland over the past 20 years following nearly a century of decline. Historical repeat photography documents early-mid 20th century mesquite invasions, but recent land cover data and rephotography demonstrate declines in xeroriparian/riparian mesquite communities in recent decades. These vegetation changes are variable over the landscape and influenced by topography and land management.

  9. New Approaches to Irrigation Scheduling of Vegetables

    Directory of Open Access Journals (Sweden)

    Michael D. Cahn

    2017-04-01

    Full Text Available Using evapotranspiration (ET data for scheduling irrigations on vegetable farms is challenging due to imprecise crop coefficients, time consuming computations, and the need to simultaneously manage many fields. Meanwhile, the adoption of soil moisture monitoring in vegetables has historically been limited by sensor accuracy and cost, as well as labor required for installation, removal, and collection of readings. With recent improvements in sensor technology, public weather-station networks, satellite and aerial imaging, wireless communications, and cloud computing, many of the difficulties in using ET data and soil moisture sensors for irrigation scheduling of vegetables can now be addressed. Web and smartphone applications have been developed that automate many of the calculations involved in ET-based irrigation scheduling. Soil moisture sensor data can be collected through wireless networks and accessed using web browser or smartphone apps. Energy balance methods of crop ET estimation, such as eddy covariance and Bowen ratio, provide research options for further developing and evaluating crop coefficient guidelines of vegetables, while recent advancements in surface renewal instrumentation have led to a relatively low-cost tool for monitoring crop water requirement in commercial farms. Remote sensing of crops using satellite, manned aircraft, and UAV platforms may also provide useful tools for vegetable growers to evaluate crop development, plant stress, water consumption, and irrigation system performance.

  10. Crop classification based on multi-temporal satellite remote sensing data for agro-advisory services

    Science.gov (United States)

    Karale, Yogita; Mohite, Jayant; Jagyasi, Bhushan

    2014-11-01

    In this paper, we envision the use of satellite images coupled with GIS to obtain location specific crop type information in order to disseminate crop specific advises to the farmers. In our ongoing mKRISHI R project, the accurate information about the field level crop type and acreage will help in the agro-advisory services and supply chain planning and management. The key contribution of this paper is the field level crop classification using multi temporal images of Landsat-8 acquired during November 2013 to April 2014. The study area chosen is Vani, Maharashtra, India, from where the field level ground truth information for various crops such as grape, wheat, onion, soybean, tomato, along with fodder and fallow fields has been collected using the mobile application. The ground truth information includes crop type, crop stage and GPS location for 104 farms in the study area with approximate area of 42 hectares. The seven multi-temporal images of the Landsat-8 were used to compute the vegetation indices namely: Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR) and Difference Vegetation Index (DVI) for the study area. The vegetation indices values of the pixels within a field were then averaged to obtain the field level vegetation indices. For each crop, binary classification has been carried out using the feed forward neural network operating on the field level vegetation indices. The classification accuracy for the individual crop was in the range of 74.5% to 97.5% and the overall classification accuracy was found to be 88.49%.

  11. Comparing MODIS and near-surface vegetation indexes for monitoring tropical dry forest phenology along a successional gradient using optical phenology towers

    Science.gov (United States)

    Rankine, C.; Sánchez-Azofeifa, G. A.; Guzmán, J. Antonio; Espirito-Santo, M. M.; Sharp, Iain

    2017-10-01

    Tropical dry forests (TDFs) present strong seasonal greenness signals ideal for tracking phenology and primary productivity using remote sensing techniques. The tightly synchronized relationship these ecosystems have with water availability offer a valuable natural experiment for observing the complex interactions between the atmosphere and the biosphere in the tropics. To investigate how well the MODIS vegetation indices (normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI)) represented the phenology of different successional stages of naturally regenerating TDFs, within a widely conserved forest fragment in the semi-arid southeast of Brazil, we installed several canopy towers with radiometric sensors to produce high temporal resolution near-surface vegetation greenness indices. Direct comparison of several years of ground measurements with a combined Aqua/Terra 8 day satellite product showed similar broad temporal trends, but MODIS often suffered from cloud contamination during the onset of the growing season and occasionally during the peak growing season. The strength of the in-situ and MODIS linear relationship was greater for NDVI than for EVI across sites but varied with forest stand age. Furthermore, we describe the onset dates and duration of canopy development phases for three years of in-situ monitoring. A seasonality analysis revealed significant discrepancies between tower and MODIS phenology transitions dates, with up to five weeks differences in growing season length estimation. Our results indicate that 8 and 16 day MODIS satellite vegetation monitoring products are suitable for tracking general patterns of tropical dry forest phenology in this region but are not temporally sufficient to characterize inter-annual differences in phenology phase onset dates or changes in productivity due to mid-season droughts. Such rapid transitions in canopy greenness are important indicators of climate change sensitivity of these

  12. Analysis of series temporal vegetation obtained by tele detection as tool for a tracking processes of desertification; Analisis de series temporales de vegetacion obtenidas mediante teledeteccion como herramienta para el seguimiento de procesos de desertificacion

    Energy Technology Data Exchange (ETDEWEB)

    Melendez-Pastor, I.; Navarro-Pedreno, J.; Gomez, I.; Koch, M.

    2009-07-01

    This risk of desertification in the Mediterranean Basin, is evident in the southeast of the Iberian Peninsula, where land degradation reaches unsustainable levels. this study aims to analyse the temporal evolution of land covers as an indicator of soil desertification. time series of vegetation indices derived from satellite remote sensing images were analysed. Various climatic variables as possible causes of land covers behaviour were considered. The existence of a large inter-annual and intra-annual variability for all land covers and precipitation was observed. It is showed an association between temporal patterns of vegetation series of different land uses and rainfall. (Author) 8 refs.

  13. Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel.

    Science.gov (United States)

    Brandt, Martin; Mbow, Cheikh; Diouf, Abdoul A; Verger, Aleixandre; Samimi, Cyrus; Fensholt, Rasmus

    2015-04-01

    After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal. © 2014 John Wiley & Sons Ltd.

  14. Iodine Satellite

    Science.gov (United States)

    Kamhawi, Hani; Dankanich, John; Martinez, Andres; Petro, Andrew

    2015-01-01

    The Iodine Satellite (iSat) spacecraft will be the first CubeSat to demonstrate high change in velocity from a primary propulsion system by using Hall thruster technology and iodine as a propellant. The mission will demonstrate CubeSat maneuverability, including plane change, altitude change and change in its closest approach to Earth to ensure atmospheric reentry in less than 90 days. The mission is planned for launch in fall 2017. Hall thruster technology is a type of electric propulsion. Electric propulsion uses electricity, typically from solar panels, to accelerate the propellant. Electric propulsion can accelerate propellant to 10 times higher velocities than traditional chemical propulsion systems, which significantly increases fuel efficiency. To enable the success of the propulsion subsystem, iSat will also demonstrate power management and thermal control capabilities well beyond the current state-of-the-art for spacecraft of its size. This technology is a viable primary propulsion system that can be used on small satellites ranging from about 22 pounds (10 kilograms) to more than 1,000 pounds (450 kilograms). iSat's fuel efficiency is ten times greater and its propulsion per volume is 100 times greater than current cold-gas systems and three times better than the same system operating on xenon. iSat's iodine propulsion system consists of a 200 watt (W) Hall thruster, a cathode, a tank to store solid iodine, a power processing unit (PPU) and the feed system to supply the iodine. This propulsion system is based on a 200 W Hall thruster developed by Busek Co. Inc., which was previously flown using xenon as the propellant. Several improvements have been made to the original system to include a compact PPU, targeting greater than 80 percent reduction in mass and volume of conventional PPU designs. The cathode technology is planned to enable heaterless cathode conditioning, significantly increasing total system efficiency. The feed system has been designed to

  15. A Robust Inversion Algorithm for Surface Leaf and Soil Temperatures Using the Vegetation Clumping Index

    Directory of Open Access Journals (Sweden)

    Zunjian Bian

    2017-07-01

    Full Text Available The inversion of land surface component temperatures is an essential source of information for mapping heat fluxes and the angular normalization of thermal infrared (TIR observations. Leaf and soil temperatures can be retrieved using multiple-view-angle TIR observations. In a satellite-scale pixel, the clumping effect of vegetation is usually present, but it is not completely considered during the inversion process. Therefore, we introduced a simple inversion procedure that uses gap frequency with a clumping index (GCI for leaf and soil temperatures over both crop and forest canopies. Simulated datasets corresponding to turbid vegetation, regularly planted crops and randomly distributed forest were generated using a radiosity model and were used to test the proposed inversion algorithm. The results indicated that the GCI algorithm performed well for both crop and forest canopies, with root mean squared errors of less than 1.0 °C against simulated values. The proposed inversion algorithm was also validated using measured datasets over orchard, maize and wheat canopies. Similar results were achieved, demonstrating that using the clumping index can improve inversion results. In all evaluations, we recommend using the GCI algorithm as a foundation for future satellite-based applications due to its straightforward form and robust performance for both crop and forest canopies using the vegetation clumping index.

  16. Appraisal of Hygiene Indicators and Farming Practices in the Production of Leafy Vegetables by Organic Small-Scale Farmers in uMbumbulu (Rural KwaZulu-Natal, South Africa)

    Science.gov (United States)

    Mdluli, Fezile; Thamaga-Chitja, Joyce; Schmidt, Stefan

    2013-01-01

    During October, November and December 2011 (when highest sales of Agri-Hub fresh produce are observed), irrigation water, compost, lettuce and spinach sampled from four different farmer cooperatives supplying the local Agri-Hub in uMbumbulu (KwaZulu-Natal, South Africa) were analyzed monthly for the presence of total and fecal coliforms and Escherichia coli using the most probable number (MPN) technique. The pH values for all irrigation water samples analyzed were within the acceptable range of 6.5–8.5 for agricultural use. Fecal coliform levels were vegetables produced by Agri-Hub small-scale farmers met the requirements for total coliforms of vegetables were below the limit of detection. In addition, the farming practices of 73 farmers were assessed via a survey. The results revealed that more than 40% of farmers used microbiologically safe tap water for irrigation and that trained farmers have a significantly better understanding of the importance of production hygiene than untrained farmers. These results reiterate the importance of interventions that build capacity in the area of food safety and hygiene of small-scale farmers for market access of formal value chains. PMID:24065036

  17. Appraisal of hygiene indicators and farming practices in the production of leafy vegetables by organic small-scale farmers in uMbumbulu (Rural KwaZulu-Natal, South Africa).

    Science.gov (United States)

    Mdluli, Fezile; Thamaga-Chitja, Joyce; Schmidt, Stefan

    2013-09-13

    During October, November and December 2011 (when highest sales of Agri-Hub fresh produce are observed), irrigation water, compost, lettuce and spinach sampled from four different farmer cooperatives supplying the local Agri-Hub in uMbumbulu (KwaZulu-Natal, South Africa) were analyzed monthly for the presence of total and fecal coliforms and Escherichia coli using the most probable number (MPN) technique. The pH values for all irrigation water samples analyzed were within the acceptable range of 6.5-8.5 for agricultural use. Fecal coliform levels were vegetables produced by Agri-Hub small-scale farmers met the requirements for total coliforms of vegetables were below the limit of detection. In addition, the farming practices of 73 farmers were assessed via a survey. The results revealed that more than 40% of farmers used microbiologically safe tap water for irrigation and that trained farmers have a significantly better understanding of the importance of production hygiene than untrained farmers. These results reiterate the importance of interventions that build capacity in the area of food safety and hygiene of small-scale farmers for market access of formal value chains.

  18. Advances in monitoring vegetation and land use dynamics in the Sahel

    DEFF Research Database (Denmark)

    Mbow, Cheikh; Fensholt, Rasmus; Nielsen, Thomas Theis

    2014-01-01

    of CO2 in the atmosphere, grazing pressure, bush fires and agricultural expansion or contraction. The use of satellite data in combination with field data played a major role in the monitoring of vegetation dynamics and land use in the Sahel, since the mega drought of the 1970s and the 1980s. This paper...... briefly reviews the advance of satellite-based monitoring of vegetation dynamics over these 40 years. We discuss the promises of current and likely future data sources and analysis tools, as well as the need to strengthen in situ data collection to support and validate satellite-based vegetation and land...

  19. 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)

  20. 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.

  1. Recent Change of Vegetation Growth Trend in China

    Science.gov (United States)

    Peng, Shushi; Chen, Anping; Xu, Liang; Cao, Chunxiang; Fang, Jingyun; Myneni, Ranga B.; Pinzon, Jorge E.; Tucker, COmpton J.; Piao, Shilong

    2011-01-01

    Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982-99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April-October) NDVI significantly increased by 0.0007/yr from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982-99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013/yr is larger than those in June, July and August (JJA) (0.0003/yr) and September and October (SO) (0.0008/yr). This relatively small increasing trend of JJA NDVI during 1982-2010 compared with that during 1982-99 (0.0012/yr) (Piao et al 2003 J. Geophys. Res.-Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039/yr) to slightly decreasing (0:0002/yr) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020/yr) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

  2. Recent change of vegetation growth trend in China

    International Nuclear Information System (INIS)

    Peng Shushi; Fang Jingyun; Piao Shilong; Chen, Anping; Xu Liang; Myneni, Ranga B; Cao Chunxiang; Pinzon, Jorge E; Tucker, Compton J

    2011-01-01

    Using satellite-derived normalized difference vegetation index (NDVI) data, several previous studies have indicated that vegetation growth significantly increased in most areas of China during the period 1982–99. In this letter, we extended the study period to 2010. We found that at the national scale the growing season (April–October) NDVI significantly increased by 0.0007 yr −1 from 1982 to 2010, but the increasing trend in NDVI over the last decade decreased in comparison to that of the 1982–99 period. The trends in NDVI show significant seasonal and spatial variances. The increasing trend in April and May (AM) NDVI (0.0013 yr −1 ) is larger than those in June, July and August (JJA) (0.0003 yr −1 ) and September and October (SO) (0.0008 yr −1 ). This relatively small increasing trend of JJA NDVI during 1982–2010 compared with that during 1982–99 (0.0012 yr −1 ) (Piao et al 2003 J. Geophys. Res.—Atmos. 108 4401) implies a change in the JJA vegetation growth trend, which significantly turned from increasing (0.0039 yr −1 ) to slightly decreasing ( − 0.0002 yr −1 ) in 1988. Regarding the spatial pattern of changes in NDVI, the growing season NDVI increased (over 0.0020 yr −1 ) from 1982 to 2010 in southern China, while its change was close to zero in northern China, as a result of a significant changing trend reversal that occurred in the 1990s and early 2000s. In northern China, the growing season NDVI significantly increased before the 1990s as a result of warming and enhanced precipitation, but decreased after the 1990s due to drought stress strengthened by warming and reduced precipitation. Our results also show that the responses of vegetation growth to climate change vary across different seasons and ecosystems.

  3. Patterns of vegetation and grasshopper community composition.

    Science.gov (United States)

    Kemp, W P; Harvey, S J; O'Neill, K M

    1990-06-01

    A study was conducted to evaluate differences in rangeland grasshopper communities over environmental gradients in Gallatin Valley, Montana, USA. The concept of habitat type (Daubenmire 1966) was used as a basis for discriminating between groupings of patches based on vegetation. A total of 39 patches were selected that represented five recognized grassland habitat types (Mueggler and Stewart 1980), as well as two disturbed types (replanting within a known habitat type). Repeated sampling in 1988 of both the insect and plant communities yielded a total of 40 grasshopper (19 664 individuals) and 97 plant species. Detrended Correspondence Analysis (DCA) indicated that patch classifications based on presence and percent cover of plants were appropriate and showed good between-group (habitat type) separation for patches along gradients of precipitation/elevation and plant community complexity. Results from undisturbed habitats showed that plant and grasshopper species composition changed over observed environmental gradients and suggested that habitat type influenced not only species presence, but also relative abundance. Discussion is presented that relates results with patch-use and core and satellite species paradigms.

  4. Monitoring Seasonal Evapotranspiration in Vulnerable Agriculture using Time Series VHSR Satellite Data

    Science.gov (United States)

    Dalezios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

    2015-04-01

    The research work stems from the hypothesis that it is possible to perform an estimation of seasonal water needs of olive tree farms under drought periods by cross correlating high spatial, spectral and temporal resolution (~monthly) of satellite data, acquired at well defined time intervals of the phenological cycle of crops, with ground-truth information simultaneously applied during the image acquisitions. The present research is for the first time, demonstrating the coordinated efforts of space engineers, satellite mission control planners, remote sensing scientists and ground teams to record at specific time intervals of the phenological cycle of trees from ground "zero" and from 770 km above the Earth's surface, the status of plants for subsequent cross correlation and analysis regarding the estimation of the seasonal evapotranspiration in vulnerable agricultural environment. The ETo and ETc derived by Penman-Montieth equation and reference Kc tables, compared with new ETd using the Kc extracted from the time series satellite data. Several vegetation indices were also used especially the RedEdge and the chlorophyll one based on WorldView-2 RedEdge and second NIR bands to relate the tree status with water and nutrition needs. Keywords: Evapotransipration, Very High Spatial Resolution - VHSR, time series, remote sensing, vulnerability, agriculture, vegetation indeces.

  5. Satellite-based detection of global urban heat-island temperature influence

    Science.gov (United States)

    Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

    2002-01-01

    This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

  6. Trends in communications satellites

    CERN Document Server

    Curtin, Denis J

    1979-01-01

    Trends in Communications Satellites offers a comprehensive look at trends and advances in satellite communications, including experimental ones such as NASA satellites and those jointly developed by France and Germany. The economic aspects of communications satellites are also examined. This book consists of 16 chapters and begins with a discussion on the fundamentals of electrical communications and their application to space communications, including spacecraft, earth stations, and orbit and wavelength utilization. The next section demonstrates how successful commercial satellite communicati

  7. 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.

  8. Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland.

    Science.gov (United States)

    Cong, Nan; Shen, Miaogen; Yang, Wei; Yang, Zhiyong; Zhang, Gengxin; Piao, Shilong

    2017-08-01

    Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (R NDVI-T ) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing R NDVI-T in spring (May-June) and autumn (September) and decreasing R NDVI-T in summer (July-August). Growing season R NDVI-T for alpine steppe increased slightly, mainly due to increasing R NDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (R NDVI-P ) for alpine meadow increased slightly, mainly in spring and summer, and R NDVI-P for alpine steppe increased, mainly in spring. Moreover, R NDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. R NDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity

  9. Ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca on the basis of indices of remote sensing of land images

    Directory of Open Access Journals (Sweden)

    O. M. Kunah

    2016-03-01

    Full Text Available The patterns of variation in vegetative indices received by means of data of remote land sensing are described as being dependant on geomorphological predictors and the sizes of agricultural fields in an experimental polygon within Poltava region. The possibilities of application of vegetative indices have been explored through ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca L. and other weeds. On the basis of images of the land surface taken on 23 March and 27 August 2015 by the sensor control Operational Land Imager (OLI, installed on the satellite Landsat 8, vegetative indices have been calculated (AC-Index – aerosol/coastal index, Hydrothermal Composite, NDTI – Normalized Difference Tillage Index, NDVI – Normalized Difference Vegetation Index, VI – Vegetation Index, MNDW – Modified Normalized Difference Water Index, LSWI – Land Surface Water Index, NBR – Normalized Burn Ratio, M15. The data obtained have been subjected to principal component analysis and the revealed principal components have been interpreted with the help of regression analysis, in which geomorphological variables have been applied as predictors. It was possible to explain the trends of variability of the vegetative cover, formalized in the form of the principal component, by means of indices which quantitatively characterise features of relief. The various aspects of variation of vegetative cover have been shown to be characterised by the specificity of the influence of relief factors. A prominent aspect of the variation of the vegetative cover of agroecosystems is variability within a field. The degree of a variation of conditions is proportional to the size of a field. Large fields occupy level plain positions. In turn, within small fields sources of variation are changes in ecological conditions which arise owing to unevenness of relief, which increases in proximity to gullies and ravines. We have identified

  10. 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

  11. 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.

  12. 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.

  13. Estimating vegetation vulnerability to detect areas prone to land degradation in the Mediterranean basin

    Science.gov (United States)

    Imbrenda, Vito; Coluzzi, Rosa; D'Emilio, Mariagrazia; Lanfredi, Maria; Simoniello, Tiziana

    2013-04-01

    Vegetation is one of the key components to study land degradation vulnerability because of the complex interactions and feedbacks that link it to soil. In the Mediterranean region, degradation phenomena are due to a mix of predisposing factors (thin soil horizons, low soil organic matter, increasing aridity, etc.) and bad management practices (overgrazing, deforestation, intensification of agriculture, tourism development). In particular, in areas threatened by degradation processes but still covered by vegetation, large scale soil condition evaluation is a hard task and the detection of stressed vegetation can be useful to identify on-going soil degradation phenomena and to reduce their impacts through interventions for recovery/rehabilitation. In this context the use of satellite time series can increase the efficacy and completeness of the land degradation assessment, providing precious information to understand vegetation dynamics. In order to estimate vulnerability levels in Basilicata (a Mediterranean region of Southern Italy) in the framework of PRO-LAND project (PO-FESR Basilicata 2007-2013), we crossed information on potential vegetation vulnerability with information on photosynthetic activity dynamics. Potential vegetation vulnerability represents the vulnerability related to the type of present cover in terms of fire risk, erosion protection, drought resistance and plant cover distribution. It was derived from an updated land cover map by separately analyzing each factor, and then by combining them to obtain concise information on the possible degradation exposure. The analysis of photosynthetic activity dynamics provides information on the status of vegetation, that is fundamental to discriminate the different vulnerability levels within the same land cover, i.e. the same potential vulnerability. For such a purpose, we analyzed a time series (2000-2010) of a satellite vegetation index (MODIS NDVI) with 250m resolution, available as 16-day composite

  14. Use of satellite imagery to assess the trophic state of Miyun Reservoir, Beijing, China

    International Nuclear Information System (INIS)

    Wang Zhengjun; Hong Jianming; Du Guisen

    2008-01-01

    The objective of this research is to explore an appropriate way of monitoring and assessing water quality by satellite remote sensing techniques in the Miyun reservoir of Beijing, China. Two scene Thematic Mapper images in May and October of 2003 were acquired and simultaneous in situ measurements, sampling and analysis were conducted. Statistical analysis indicates that satellite-based normalized ratio vegetation index (NRVI) and in situ measured water chlorophyll a (Chl-a) concentration have very high correlation. Two linear regression models with high determination coefficients were constructed for NRVI and Chl-a of sample points. According to the modified trophic state index map, water quality in the western section of Miyun reservoir was consistently higher than in the eastern section during the two months tested. The trophic grade of the eastern reservoir remained mesotrophic with a tendency for eutrophication. - Remote sensing techniques can effectively monitor the change of water quality with time and space

  15. Seasonally asymmetric enhancement of northern vegetation productivity

    Science.gov (United States)

    Park, T.; Myneni, R.

    2017-12-01

    Multiple evidences of widespread greening and increasing terrestrial carbon uptake have been documented. In particular, enhanced gross productivity of northern vegetation has been a critical role leading to observed carbon uptake trend. However, seasonal photosynthetic activity and its contribution to observed annual carbon uptake trend and interannual variability are not well understood. Here, we introduce a multiple-source of datasets including ground, atmospheric and satellite observations, and multiple process-based global vegetation models to understand how seasonal variation of land surface vegetation controls a large-scale carbon exchange. Our analysis clearly shows a seasonally asymmetric enhancement of northern vegetation productivity in growing season during last decades. Particularly, increasing gross productivity in late spring and early summer is obvious and dominant driver explaining observed trend and variability. We observe more asymmetric productivity enhancement in warmer region and this spatially varying asymmetricity in northern vegetation are likely explained by canopy development rate, thermal and light availability. These results imply that continued warming may facilitate amplifying asymmetric vegetation activity and cause these trends to become more pervasive, in turn warming induced regime shift in northern land.

  16. Fruits and vegetables (image)

    Science.gov (United States)

    A healthy diet includes adding vegetables and fruit every day. Vegetables like broccoli, green beans, leafy greens, zucchini, cauliflower, cabbage, carrots, and tomatoes are low in calories and high in fiber, vitamins, and minerals. ...

  17. Vegetable Production System (Veggie)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Vegetable Production System (Veggie) was developed to be a simple, easily stowed, high growth volume, low resource facility capable of producing fresh vegetables...

  18. Soil salinity assessment through satellite thermography for different irrigated and rainfed crops

    Science.gov (United States)

    Ivushkin, Konstantin; Bartholomeus, Harm; Bregt, Arnold K.; Pulatov, Alim; Bui, Elisabeth N.; Wilford, John

    2018-06-01

    The use of canopy thermography is an innovative approach for salinity stress detection in plants. But its applicability for landscape scale studies using satellite sensors is still not well investigated. The aim of this research is to test the satellite thermography soil salinity assessment approach on a study area with different crops, grown both in irrigated and rainfed conditions, to evaluate whether the approach has general applicability. Four study areas in four different states of Australia were selected to give broad representation of different crops cultivated under irrigated and rainfed conditions. The soil salinity map was prepared by the staff of Geoscience Australia and CSIRO Land and Water and it is based on thorough soil sampling together with environmental modelling. Remote sensing data was captured by the Landsat 5 TM satellite. In the analysis we used vegetation indices and brightness temperature as an indicator for canopy temperature. Applying analysis of variance and time series we have investigated the applicability of satellite remote sensing of canopy temperature as an approach of soil salinity assessment for different crops grown under irrigated and rainfed conditions. We concluded that in all cases average canopy temperatures were significantly correlated with soil salinity of the area. This relation is valid for all investigated crops, grown both irrigated and rainfed. Nevertheless, crop type does influence the strength of the relations. In our case cotton shows only minor temperature difference compared to other vegetation classes. The strongest relations between canopy temperature and soil salinity were observed at the moment of a maximum green biomass of the crops which is thus considered to be the best time for application of the approach.

  19. Satellite image collection optimization

    Science.gov (United States)

    Martin, William

    2002-09-01

    Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

  20. Handbook of satellite applications

    CERN Document Server

    Madry, Scott; Camacho-Lara, Sergio

    2017-01-01

    The first edition of this ground breaking reference work was the most comprehensive reference source available about the key aspects of the satellite applications field. This updated second edition covers the technology, the markets, applications and regulations related to satellite telecommunications, broadcasting and networking—including civilian and military systems; precise satellite navigation and timing networks (i.e. GPS and others); remote sensing and meteorological satellite systems. Created under the auspices of the International Space University based in France, this brand new edition is now expanded to cover new innovative small satellite constellations, new commercial launching systems, innovation in military application satellites and their acquisition, updated appendices, a useful glossary and more.

  1. European Vegetation Archive (EVA)

    NARCIS (Netherlands)

    Chytrý, Milan; Hennekens, S.M.; Jiménez-Alfaro, Borja; Schaminée, J.H.J.; Haveman, Rense; Janssen, J.A.M.

    2016-01-01

    The European Vegetation Archive (EVA) is a centralized database of European vegetation plots developed by the IAVS Working Group European Vegetation Survey. It has been in development since 2012 and first made available for use in research projects in 2014. It stores copies of national and

  2. Shadow imaging of geosynchronous satellites

    Science.gov (United States)

    Douglas, Dennis Michael

    Geosynchronous (GEO) satellites are essential for modern communication networks. If communication to a GEO satellite is lost and a malfunction occurs upon orbit insertion such as a solar panel not deploying there is no direct way to observe it from Earth. Due to the GEO orbit distance of ~36,000 km from Earth's surface, the Rayleigh criteria dictates that a 14 m telescope is required to conventionally image a satellite with spatial resolution down to 1 m using visible light. Furthermore, a telescope larger than 30 m is required under ideal conditions to obtain spatial resolution down to 0.4 m. This dissertation evaluates a method for obtaining high spatial resolution images of GEO satellites from an Earth based system by measuring the irradiance distribution on the ground resulting from the occultation of the satellite passing in front of a star. The representative size of a GEO satellite combined with the orbital distance results in the ground shadow being consistent with a Fresnel diffraction pattern when observed at visible wavelengths. A measurement of the ground shadow irradiance is used as an amplitude constraint in a Gerchberg-Saxton phase retrieval algorithm that produces a reconstruction of the satellite's 2D transmission function which is analogous to a reverse contrast image of the satellite. The advantage of shadow imaging is that a terrestrial based redundant set of linearly distributed inexpensive small telescopes, each coupled to high speed detectors, is a more effective resolved imaging system for GEO satellites than a very large telescope under ideal conditions. Modeling and simulation efforts indicate sub-meter spatial resolution can be readily achieved using collection apertures of less than 1 meter in diameter. A mathematical basis is established for the treatment of the physical phenomena involved in the shadow imaging process. This includes the source star brightness and angular extent, and the diffraction of starlight from the satellite

  3. Expansion rate and geometry of floating vegetation mats on the margins of thermokarst lakes, northern Seward Peninsula, Alaska, USA

    Science.gov (United States)

    Parsekian, A.D.; Jones, Benjamin M.; Jones, M.; Grosse, G.; Walter, Anthony K.M.; Slater, L.

    2011-01-01

    Investigations on the northern Seward Peninsula in Alaska identified zones of recent (geometry is determined using geophysical and remote sensing measurements. The vegetation mats were observed to have an average thickness of 0.57m and petrophysical modeling indicated that gas content of 1.5-5% enabled floatation above the lake surface. Furthermore, geophysical investigation provides evidence that the mats form by thaw and subsidence of the underlying permafrost rather than terrestrialization. The temperature of the water below a vegetation mat was observed to remain above freezing late in the winter. Analysis of satellite and aerial imagery indicates that these features have expanded at maximum rates of 1-2myr-1 over a 56year period. Including the spatial coverage of floating 'thermokarst mats' increases estimates of lake area by as much as 4% in some lakes. ?? 2011 John Wiley & Sons, Ltd.

  4. Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

    Directory of Open Access Journals (Sweden)

    Laura Ulsig

    2017-01-01

    Full Text Available Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI. This study investigates the potential of a Photochemical Reflectance Index (PRI, which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R2 = 0.36–0.8, which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R2 > 0.6 in all cases. The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

  5. Validation of Vegetation Index Time Series from Suomi NPP Visible Infrared Imaging Radiometer Suite Using Tower Radiation Flux Measurements

    Science.gov (United States)

    Miura, T.; Kato, A.; Wang, J.; Vargas, M.; Lindquist, M.

    2015-12-01

    Satellite vegetation index (VI) time series data serve as an important means to monitor and characterize seasonal changes of terrestrial vegetation and their interannual variability. It is, therefore, critical to ensure quality of such VI products and one method of validating VI product quality is cross-comparison with in situ flux tower measurements. In this study, we evaluated the quality of VI time series derived from Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft by cross-comparison with in situ radiation flux measurements at select flux tower sites over North America and Europe. VIIRS is a new polar-orbiting satellite sensor series, slated to replace National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer in the afternoon overpass and to continue the highly-calibrated data streams initiated with Moderate Resolution Imaging Spectrometer of National Aeronautics and Space Administration's Earth Observing System. The selected sites covered a wide range of biomes, including croplands, grasslands, evergreen needle forest, woody savanna, and open shrublands. The two VIIRS indices of the Top-of-Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI) and the atmospherically-corrected, Top-of-Canopy (TOC) Enhanced Vegetation Index (EVI) (daily, 375 m spatial resolution) were compared against the TOC NDVI and a two-band version of EVI (EVI2) calculated from tower radiation flux measurements, respectively. VIIRS and Tower VI time series showed comparable seasonal profiles across biomes with statistically significant correlations (> 0.60; p-value 0.95), with mean differences of 2.3 days and 5.0 days for the NDVI and the EVI, respectively. These results indicate that VIIRS VI time series can capture seasonal evolution of vegetated land surface as good as in situ radiometric measurements. Future studies that address biophysical or physiological interpretations

  6. Calibration of UAS imagery inside and outside of shadows for improved vegetation index computation

    Science.gov (United States)

    Bondi, Elizabeth; Salvaggio, Carl; Montanaro, Matthew; Gerace, Aaron D.

    2016-05-01

    Vegetation health and vigor can be assessed with data from multi- and hyperspectral airborne and satellite- borne sensors using index products such as the normalized difference vegetation index (NDVI). Recent advances in unmanned aerial systems (UAS) technology have created the opportunity to access these same image data sets in a more cost effective manner with higher temporal and spatial resolution. Another advantage of these systems includes the ability to gather data in almost any weather condition, including complete cloud cover, when data has not been available before from traditional platforms. The ability to collect in these varied conditions, meteorological and temporal, will present researchers and producers with many new challenges. Particularly, cloud shadows and self-shadowing by vegetation must be taken into consideration in imagery collected from UAS platforms to avoid variation in NDVI due to changes in illumination within a single scene, and between collection flights. A workflow is presented to compensate for variations in vegetation indices due to shadows and variation in illumination levels in high resolution imagery collected from UAS platforms. Other calibration methods that producers may currently be utilizing produce NDVI products that still contain shadow boundaries and variations due to illumination, whereas the final NDVI mosaic from this workflow does not.

  7. Genetic improvement of vegetables

    International Nuclear Information System (INIS)

    Jaramillo Vasquez, J.G.

    2001-01-01

    Some genetic bases of the improvement of vegetables are given. The objectives of the genetic improvement and the fundamental stages of this process are done. The sources of genetic variation are indicated and they are related the reproduction systems of the main horticultural species. It is analyzed the concept of genetic inheritance like base to determine the procedures more appropriate of improvement. The approaches are discussed, has more than enough phenotypic value, genetic action and genotypic variance; Equally the heredability concepts and value of improvement. The conventional methods of improvement are described, like they are: the introduction of species or varieties, the selection, the pure line, the pedigree method, the selection for families, the recurrent selection, the selection for unique seed, the haploids method, the selection for heterosis and the synthetic varieties

  8. Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product

    Directory of Open Access Journals (Sweden)

    Zhiqiang Xiao

    2016-04-01

    Full Text Available The fractional vegetation cover (FCover is an essential biophysical variable and plays a critical role in the carbon cycle studies. Existing FCover products from satellite observations are spatially incomplete and temporally discontinuous, and also inaccurate for some vegetation types to meet the requirements of various applications. In this study, an operational method is proposed to calculate high-quality, accurate FCover from the Global LAnd Surface Satellite (GLASS leaf area index (LAI product to ensure physical consistency between LAI and FCover retrievals. As a result, a global FCover product (denoted by TRAGL were generated from the GLASS LAI product from 2000 to present. With no missing values, the TRAGL FCover product is spatially complete. A comparison of the TRAGL FCover product with the Geoland2/BioPar version 1 (GEOV1 FCover product indicates that these FCover products exhibit similar spatial distribution pattern. However, there were relatively large discrepancies between these FCover products over equatorial rainforests, broadleaf crops in East-central United States, and needleleaf forests in Europe and Siberia. Temporal consistency analysis indicates that TRAGL FCover product has continuous trajectories. Direct validation with ground-based FCover estimates demonstrated that TRAGL FCover values were more accurate (RMSE = 0.0865, and R2 = 0.8848 than GEOV1 (RMSE = 0.1541, and R2 = 0.7621.

  9. 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.

  10. GPS Satellite Simulation Facility

    Data.gov (United States)

    Federal Laboratory Consortium — The GPS satellite simulation facility consists of a GPS satellite simulator controlled by either a Silicon Graphics Origin 2000 or PC depending upon unit under test...

  11. Physics teaching by infrared remote sensing of vegetation

    Science.gov (United States)

    Schüttler, Tobias; Maman, Shimrit; Girwidz, Raimund

    2018-05-01

    Context- and project-based teaching has proven to foster different affective and cognitive aspects of learning. As a versatile and multidisciplinary scientific research area with diverse applications for everyday life, satellite remote sensing is an interesting context for physics education. In this paper we give a brief overview of satellite remote sensing of vegetation and how to obtain your own, individual infrared remote sensing data with affordable converted digital cameras. This novel technique provides the opportunity to conduct individual remote sensing measurement projects with students in their respective environment. The data can be compared to real satellite data and is of sufficient accuracy for educational purposes.

  12. Radiation exposure near Chernobyl based on analysis of satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Goldman, Marvin; Ustin, Susan [University of California, Laboratory for Energy-related Health Research, CA (United States); Warman, Edward A [Stone and Webster Engineering Corp., Boston, MA (United States)

    1987-12-01

    Radiation-induced damage in conifers adjacent to the damaged Chernobyl nuclear power plant has been evaluated using LANDSAT Thematic Mapper satellite images. Eight images acquired between April 22, 1986 and May 15, 1987 were used to assess the extent and magnitude of radiation effects on pine trees within 10 km of the reactor site. The timing and spatial extent of vegetation damaged was used to estimate the radiation doses in the near field around the Chernobyl nuclear power station and to derive dose rates as a function of time during and after the accident. A normalized vegetation index was developed from the TM spectral band data to visually demonstrate the damage and mortality to nearby conifer stands. The earliest date showing detectable injury 1 km west of the reactor unit was June 16, 1986. Subsequent dates revealed continued expansion of the affected areas to the west, north, and south. The greatest aerial expansion of this area occurred by October 15, 1986, with vegetation changes evident up to 5 km west, 2 km south, and 2 km north of the damaged Reactor Unit 4. By May 11, 1987, further scene changes were due principally to removal and mitigation efforts by the Soviet authorities. Areas showing spectral evidence of vegetation damage during the previous growing season do not show evidence of recovery and reflectance in the TM Bands 4 and 3 remain higher than surrounding vegetation, which infers that the trees are dead. The patterns of spectral change indicative of vegetation stress are consistent with changes expected for radiation injury and mortality. The extent and the timing of these effects enabled developing an integrated radiation dose estimate, which was combined with the information regarding the characteristics of radionuclide mix to provide an estimate of maximum dose rates during the early period of the accident. The derived peak dose rates during the 10-day release in the accident are high and are estimated at about 0.5 to 1 rad per hour. These

  13. Analysis of Behavior of Vegetation in the Year of 2016 for the Municipality of Remanso- BA

    OpenAIRE

    Ismael Farias de Freitas; Laurizio E. R. Alves; Heliofábio B. Gomes; Jeová R. S. Júnior; Dimas B. Santiago; Rafael A. Silva

    2017-01-01

    Droughts are a natural problem in the Northeastern Brazilian region, in addition the rainfall distribution poorly distributed spatially and temporally results in seasonal changes in the surface vegetation. Consequently, the monitoring and evaluation of vegetation in the northeast region of Brazil has become increasingly constant. For this evaluation several techniques are used, but the use of environmental satellites is increasingly applied, such as the Landsat 8 satellite, where the products...

  14. Expansion rate and geometry of floating vegetation mats on the margins of thermokarst lakes, northern Seward Peninsula, Alaska, USA

    Science.gov (United States)

    Parsekian, A.D.; Jones, Benjamin M.; Jones, M.; Grosse, G.; Walter, Anthony K.M.; Slater, L.

    2011-01-01

    Investigations on the northern Seward Peninsula in Alaska identified zones of recent (<50years) permafrost collapse that led to the formation of floating vegetation mats along thermokarst lake margins. The occurrence of floating vegetation mat features indicates rapid degradation of near-surface permafrost and lake expansion. This paper reports on the recent expansion of these collapse features and their geometry is determined using geophysical and remote sensing measurements. The vegetation mats were observed to have an average thickness of 0.57m and petrophysical modeling indicated that gas content of 1.5-5% enabled floatation above the lake surface. Furthermore, geophysical investigation provides evidence that the mats form by thaw and subsidence of the underlying permafrost rather than terrestrialization. The temperature of the water below a vegetation mat was observed to remain above freezing late in the winter. Analysis of satellite and aerial imagery indicates that these features have expanded at maximum rates of 1-2myr-1 over a 56year period. Including the spatial coverage of floating 'thermokarst mats' increases estimates of lake area by as much as 4% in some lakes. ?? 2011 John Wiley & Sons, Ltd.

  15. Past and future effects of climate change on spatially heterogeneous vegetation activity in China

    Science.gov (United States)

    Gao, Jiangbo; Jiao, Kewei; Wu, Shaohong; Ma, Danyang; Zhao, Dongsheng; Yin, Yunhe; Dai, Erfu

    2017-07-01

    Climate change is a major driver of vegetation activity but its complex ecological relationships impede research efforts. In this study, the spatial distribution and dynamic characteristics of climate change effects on vegetation activity in China from the 1980s to the 2010s and from 2021 to 2050 were investigated using a geographically weighted regression (GWR) model. The GWR model was based on combined datasets of satellite vegetation index, climate observation and projection, and future vegetation productivity simulation. Our results revealed that the significantly positive precipitation-vegetation relationship was and will be mostly distributed in North China. However, the regions with temperature-dominated distribution of vegetation activity were and will be mainly located in South China. Due to the varying climate features and vegetation cover, the spatial correlation between vegetation activity and climate change may be altered. There will be different dominant climatic factors for vegetation activity distribution in some regions such as Northwest China, and even opposite correlations in Northeast China. Additionally, the response of vegetation activity to precipitation will move southward in the next three decades. In contrast, although the high warming rate will restrain the vegetation activity, precipitation variability could modify hydrothermal conditions for vegetation activity. This observation is exemplified in the projected future enhancement of vegetation activity in the Tibetan Plateau and weakened vegetation activity in East and Middle China. Furthermore, the vegetation in most parts of North China may adapt to an arid environment, whereas in many southern areas, vegetation will be repressed by water shortage in the future.

  16. Modeling mechanisms of vegetation change due to fire in a semi-arid ecosystem

    Science.gov (United States)

    White, J.D.; Gutzwiller, K.J.; Barrow, W.C.; Randall, L.J.; Swint, P.

    2008-01-01

    Vegetation growth and community composition in semi-arid environments is determined by water availability and carbon assimilation mechanisms specific to different plant types. Disturbance also impacts vegetation productivity and composition dependent on area affected, intensity, and frequency factors. In this study, a new spatially explicit ecosystem model is presented for the purpose of simulating vegetation cover type changes associated with fire disturbance in the northern Chihuahuan Desert region. The model is called the Landscape and Fire Simulator (LAFS) and represents physiological activity of six functional plant types incorporating site climate, fire, and seed dispersal routines for individual grid cells. We applied this model for Big Bend National Park, Texas, by assessing the impact of wildfire on the trajectory of vegetation communities over time. The model was initialized and calibrated based on landcover maps derived from Landsat-5 Thematic Mapper data acquired in 1986 and 1999 coupled with plant biomass measurements collected in the field during 2000. Initial vegetation cover change analysis from satellite data showed shrub encroachment during this time period that was captured in the simulated results. A synthetic 50-year climate record was derived from historical meteorological data to assess system response based on initial landcover conditions. This simulation showed that shrublands increased to the detriment of grass and yucca-ocotillo vegetation cover types indicating an ecosystem-level trajectory for shrub encroachment. Our analysis of simulated fires also showed that fires significantly reduced site biomass components including leaf area, stem, and seed biomass in this semi-arid ecosystem. In contrast to other landscape simulation models, this new model incorporates detailed physiological responses of functional plant types that will allow us to simulated the impact of increased atmospheric CO2 occurring with climate change coupled with fire

  17. 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.

  18. Green leaf phenology at Landsat resolution: scaling from the plot to satellite

    Science.gov (United States)

    Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

    2005-12-01

    Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (example, our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. In preliminary work, we validated the Landsat-derived metrics with similar analyses of MODIS and AVHRR, and demonstrate that aggregating diverse local phenologies into coarse grids may convolute interpretations. Despite these complications, the platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows us to effectively scale

  19. A temperature and vegetation adjusted NTL urban index for urban area mapping and analysis

    Science.gov (United States)

    Zhang, Xiya; Li, Peijun

    2018-01-01

    Accurate and timely information regarding the extent and spatial distribution of urban areas on regional and global scales is crucially important for both scientific and policy-making communities. Stable nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) provides a unique proxy of human settlement and activity, which has been used in the mapping and analysis of urban areas and urbanization dynamics. However, blooming and saturation effects of DMSP/OLS NTL data are two unresolved problems in regional urban area mapping and analysis. This study proposed a new urban index termed the Temperature and Vegetation Adjusted NTL Urban Index (TVANUI). It is intended to reduce blooming and saturation effects and to enhance urban features by combining DMSP/OLS NTL data with Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer onboard the Terra satellite. The proposed index was evaluated in two study areas by comparison with established urban indices. The results demonstrated the proposed TVANUI was effective in enhancing the variation of DMSP/OLS light in urban areas and in reducing blooming and saturation effects, showing better performance than three established urban indices. The TVANUI also significantly outperformed the established urban indices in urban area mapping using both the global-fixed threshold and the local-optimal threshold methods. Thus, the proposed TVANUI provides a useful variable for urban area mapping and analysis on regional scale, as well as for urbanization dynamics using time-series DMSP/OLS and related satellite data.

  20. 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

  1. Understanding the Seasonal Greenness Trends and Controls in South Asia Using Satellite Based Observations

    Science.gov (United States)

    Sarmah, S.; Jia, G.; Zhang, A.; Singha, M.

    2017-12-01

    South Asia (SA) is one of the most remarkable regions in changing vegetation greenness along with its major expansion of agricultural activity, especially irrigated farming. However, SA is predicted to be a vulnerable agricultural regions to future climate changes. The influence of monsoon climate on the seasonal trends and anomalies of vegetation greenness are not well understood in the region which can provide valuable information about climate-ecosystem interaction. This study analyzed the spatio-temporal patterns of seasonal vegetation trends and variability using satellite vegetation indices (VI) including AVHRR Normalized Difference Vegetation Index (NDVI) (1982-2013) and MODIS Enhanced Vegetation Index (EVI) (2000-2013) in summer monsoon (SM) (June-Sept) and winter monsoon (WM) (Dec-Apr) seasons among irrigated cropland (IC), rainfed cropland (RC) and natural vegetation (NV). Seasonal VI variations with climatic factors (precipitation and temperature) and LULC changes have been investigated to identify the forcings behind the vegetation trends and variability. We found that major greening occurred in the last three decades due to the increase in IC productivity noticeably in WM, however, recent (2000-2013) greening trends were lower than the previous decades (1982-1999) in both the IC and RC indicating the stresses on them. The browning trends, mainly concentrated in NV areas were prominent during WM and rigorous since 2000, confirmed from the moderate resolution EVI and LULC datasets. Winter time maximal temperature had been increasing tremendously whereas precipitation trend was not significant over SA. Both the climate variability and LULC changes had integrated effects on the vegetation changes in NV areas specifically in hilly regions. However, LULC impact was intensified since 2000, mostly in north east India. This study also revealed a distinct seasonal variation in spatial distribution of correlation between VI's and climate anomalies over SA

  2. Improving satellite-based post-fire evapotranspiration estimates in semi-arid regions

    Science.gov (United States)

    Poon, P.; Kinoshita, A. M.

    2017-12-01

    Climate change and anthropogenic factors contribute to the increased frequency, duration, and size of wildfires, which can alter ecosystem and hydrological processes. The loss of vegetation canopy and ground cover reduces interception and alters evapotranspiration (ET) dynamics in riparian areas, which can impact rainfall-runoff partitioning. Previous research evaluated the spatial and temporal trends of ET based on burn severity and observed an annual decrease of 120 mm on average for three years after fire. Building upon these results, this research focuses on the Coyote Fire in San Diego, California (USA), which burned a total of 76 km2 in 2003 to calibrate and improve satellite-based ET estimates in semi-arid regions affected by wildfire. The current work utilizes satellite-based products and techniques such as the Google Earth Engine Application programming interface (API). Various ET models (ie. Operational Simplified Surface Energy Balance Model (SSEBop)) are compared to the latent heat flux from two AmeriFlux eddy covariance towers, Sky Oaks Young (US-SO3), and Old Stand (US-SO2), from 2000 - 2015. The Old Stand tower has a low burn severity and the Young Stand tower has a moderate to high burn severity. Both towers are used to validate spatial ET estimates. Furthermore, variables and indices, such as Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and the Normalized Burn Ratio (NBR) are utilized to evaluate satellite-based ET through a multivariate statistical analysis at both sites. This point-scale study will able to improve ET estimates in spatially diverse regions. Results from this research will contribute to the development of a post-wildfire ET model for semi-arid regions. Accurate estimates of post-fire ET will provide a better representation of vegetation and hydrologic recovery, which can be used to improve hydrologic models and predictions.

  3. Vegetation index methods for estimating evapotranspiration by remote sensing

    Science.gov (United States)

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

    2010-01-01

    Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ETa) and meteorological data to project ETa over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ETa and measured ETa are in the range of 0.45–0.95, and root mean square errors are in the range of 10–30% of mean ETa values across biomes, similar to methods that use thermal infrared bands to estimate ETa and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational algorithms for ET in agricultural and natural ecosystems are presented. The goal of the review is to enable potential end-users from different disciplines to adapt these methods to new applications that require spatially-distributed ET estimates.

  4. Tundra vegetation effects on pan-Arctic albedo

    International Nuclear Information System (INIS)

    Loranty, Michael M; Goetz, Scott J; Beck, Pieter S A

    2011-01-01

    Recent field experiments in tundra ecosystems describe how increased shrub cover reduces winter albedo, and how subsequent changes in surface net radiation lead to altered rates of snowmelt. These findings imply that tundra vegetation change will alter regional energy budgets, but to date the effects have not been documented at regional or greater scales. Using satellite observations and a pan-Arctic vegetation map, we examined the effects of shrub vegetation on albedo across the terrestrial Arctic. We included vegetation classes dominated by low shrubs, dwarf shrubs, tussock-dominated graminoid tundra, and non-tussock graminoid tundra. Each class was further stratified by bioclimate subzones. Low-shrub tundra had higher normalized difference vegetation index values and earlier albedo decline in spring than dwarf-shrub tundra, but for tussock tundra, spring albedo declined earlier than for low-shrub tundra. Our results illustrate how relatively small changes in vegetation properties result in differences in albedo dynamics, regardless of shrub growth, that may lead to differences in net radiation upwards of 50 W m -2 at weekly time scales. Further, our findings imply that changes to the terrestrial Arctic energy budget during this important seasonal transition are under way regardless of whether recent satellite observed productivity trends are the result of shrub expansion. We conclude that a better understanding of changes in vegetation productivity and distribution in Arctic tundra is essential for accurately quantifying and predicting carbon and energy fluxes and associated climate feedbacks.

  5. Meteorological satellite systems

    CERN Document Server

    Tan, Su-Yin

    2014-01-01

    “Meteorological Satellite Systems” is a primer on weather satellites and their Earth applications. This book reviews historic developments and recent technological advancements in GEO and polar orbiting meteorological satellites. It explores the evolution of these remote sensing technologies and their capabilities to monitor short- and long-term changes in weather patterns in response to climate change. Satellites developed by various countries, such as U.S. meteorological satellites, EUMETSAT, and Russian, Chinese, Japanese and Indian satellite platforms are reviewed. This book also discusses international efforts to coordinate meteorological remote sensing data collection and sharing. This title provides a ready and quick reference for information about meteorological satellites. It serves as a useful tool for a broad audience that includes students, academics, private consultants, engineers, scientists, and teachers.

  6. Theory of geostationary satellites

    CERN Document Server

    Zee, Chong-Hung

    1989-01-01

    Geostationary or equatorial synchronous satellites are a daily reminder of our space efforts during the past two decades. The nightly television satellite weather picture, the intercontinental telecommunications of television transmissions and telephone conversations, and the establishrnent of educational programs in remote regions on Earth are constant reminders of the presence of these satellites. As used here, the term 'geo­ stationary' must be taken loosely because, in the long run, the satellites will not remain 'stationary' with respect to an Earth-fixed reference frame. This results from the fact that these satellites, as is true for all satellites, are incessantly subject to perturbations other than the central-body attraction of the Earth. Among the more predominant pertur­ bations are: the ellipticity of the Earth's equator, the Sun and Moon, and solar radiation pressure. Higher harmonics of the Earth's potential and tidal effects also influence satellite motion, but they are of second­ order whe...

  7. A Drone-based Tropical Forest Experiment to Estimate Vegetation Properties

    Science.gov (United States)

    Henke, D.

    2017-12-01

    In mid-latitudes, remote sensing technology is intensively used to monitor vegetation properties. However, in the tropics, high cloud-cover and saturation effects of vegetation indices (VI) hamper the reliability of vegetation parameters derived from satellite data. A drone experiment over the Barro Colorado Island (BCI), Panama, with high temporal repetition rates was conducted in spring 2017 to investigate the robustness and stability of remotely sensed vegetation parameters in tropical environments. For this purpose, three 10-day flight windows in February, March and April were selected and drone flights were repeated on daily intervals when weather conditions and equipment allowed it. In total, 18 days were recorded with two different optical cameras on sensefly's eBee drone: one red, green, blue (RGB) camera and one camera with near infra-red (NIR), green and blue channels. When possible, the data were acquired at the same time of day. Pix4D and Agisoft software were used to calculate the Normalized Difference VI (NDVI) and forest structure. In addition, leave samples were collected ones per month from 16 different plant species and the relative water content was measured as ground reference. Further data sources for the analysis are phenocam images (RGB & NIR) on BCI and satellite images of MODIS (NDVI; Enhanced VI EVI) and Sentinel-1 (radar backscatter). The attached figure illustrates the main data collected on BCI. Initial results suggest that the coefficient of determination (R2) is relatively high between ground samples and drone data, Sentinel-1 backscatter and MODIS EVI with R2 values ranging from 0.4 to 0.6; on the contrary, R2 values between ground measurements and MODIS NDVI or phenocam images are below 0.2. As the experiment took place mainly during dry season on BCI, cloud-cover rates are less dominate than during wet season. Under these conditions, MODIS EVI, which is less vulnerable to saturation effects, seems to be more reliable than MODIS

  8. Vegetation Cover Changes in Selected Pastoral Villages in Mkata ...

    African Journals Online (AJOL)

    Arid and semi-arid savannah ecosystems of Tanzania are subjected to increasing pressure from pastoral land-use systems. A spatial temporal study involving analysis of satellite imageries and range surveys was carried out to determine the effects of high stocking levels on savannah vegetation cover types in Mkata plains.

  9. Determinants of patchiness of woody vegetation in an African savanna

    NARCIS (Netherlands)

    Veldhuis, Michiel P.; Rozen-Rechels, David; le Roux, Elizabeth; Cromsigt, Joris P.G.M.; Berg, Matheus P.; Olff, Han

    2016-01-01

    How is woody vegetation patchiness affected by rainfall, fire and large herbivore biomass? Can we predict woody patchiness and cover over large-scale environmental gradients? We quantified variation in local patchiness as the lacunarity of woody cover on satellite-derived images. Using Random Forest

  10. River flow response to changes in vegetation cover in a South ...

    African Journals Online (AJOL)

    It was hypothesised in this study that annual river yield (river flow as a fraction of rainfall) in the Molenaars catchment near Paarl, South Africa co-varies with an index of green vegetation cover derived from satellite data (the normalised difference vegetation index, NDVI). The catchment was partitioned into 'upland' and ...

  11. Monitoring of Conservation Tillage and Tillage Intensity by Ground and Satellite Imagery

    Directory of Open Access Journals (Sweden)

    M.A Rostami

    2014-09-01

    Full Text Available Local information about tillage intensity and ground residue coverage is useful for policies in agricultural extension, tillage implement design and upgrading management methods. The current methods for assessing crop residue coverage and tillage intensity such as residue weighing methods, line-transect and photo comparison methods are tedious and time-consuming. The present study was devoted to investigate accurate methods for monitoring residue management and tillage practices. The satellite imagery technique was used as a rapid and spatially explicit method for delineating crop residue coverage and as an estimator of conservation tillage adoption and intensity. The potential of multispectral high-spatial resolution WorldView-2 local data was evaluated using the total of eleven satellite spectral indices and Linear Spectral Unmixing Analysis (LSUA. The total of ninety locations was selected for this study and for each location the residue coverage was measured by the image processing method and recorded as ground control. The output of indices and LSUA method were individually correlated to the control and the relevant R2 was calculated. Results indicated that crop residue cover was related to IPVI, RVI1, RVI2 and GNDVI spectral indices and satisfactory correlations were established (0.74 - 0.81. The crop residue coverage estimated from the LSUA approach was found to be correlated with the ground residue data (0.75. Two effective indices named as Infrared Percentage Vegetation Index (IPVI and Ratio Vegetation Index (RVI with maximum R2 were considered for classification of tillage intensity. Results indicated that the classification accuracy with IPVI and RVI indices in different conditions varied from 78-100 percent and therefore in good agreement with ground measurement, observations and field records.

  12. Regional vegetation dynamics and its response to climate change—a case study in the Tao River Basin in Northwestern China

    International Nuclear Information System (INIS)

    Li, Changbin; Yang, Linshan; Wang, Shuaibing; Yang, Wenjin; Zhu, Gaofeng; Qi, Jiaguo; Zou, Songbing; Zhang, Feng

    2014-01-01

    The 30-year normalized-difference vegetation index (NDVI) time series from AVHRR/MODIS satellite sensors was used in this study to assess the regional vegetation dynamic changes in the Tao River Basin, which cuts across the Eastern Tibetan Plateau (ETP) and the Southwestern Loess Plateau (SLP). First, principal component and correlation analyses were carried out to determine the key climatic variables driving ecological change in the region. Then, regression models were tested to correlate NDVI with the selected climatic variables to determine their predictive power. Finally, Sen’s slope method was used to determine how terrestrial vegetation has responded to regional climate change in the region. The results indicated an average winter season NDVI value of 0.14 in the ETP but only 0.04 in the SLP. Primarily driven by increasing temperature, vegetation growth has generally been enhanced since 1981; spring NDVI increased by 0.03 every 10 years in the ETP and 0.02 in the SLP. Further, results from trend analyses suggest vegetation growth in the ETP shifted to earlier-start and earlier-end dates, however in the SLP, the growing season has been extended with an earlier-start and later-end date. The precipitation threshold for vegetation germination, measured by the cumulative spring rainfall, was found to be 44 mm for both the ETP and SLP. (paper)

  13. Detecting 3D Vegetation Structure with the Galileo Space Probe: Can a Distant Probe Detect Vegetation Structure on Earth?

    Science.gov (United States)

    Doughty, Christopher E; Wolf, Adam

    2016-01-01

    Sagan et al. (1993) used the Galileo space probe data and first principles to find evidence of life on Earth. Here we ask whether Sagan et al. (1993) could also have detected whether life on Earth had three-dimensional structure, based on the Galileo space probe data. We reanalyse the data from this probe to see if structured vegetation could have been detected in regions with abundant photosynthetic pigments through the anisotropy of reflected shortwave radiation. We compare changing brightness of the Amazon forest (a region where Sagan et al. (1993) noted a red edge in the reflectance spectrum, indicative of photosynthesis) as the planet rotates to a common model of reflectance anisotropy and found measured increase of surface reflectance of 0.019 ± 0.003 versus a 0.007 predicted from only anisotropic effects. We hypothesize the difference was due to minor cloud contamination. However, the Galileo dataset had only a small change in phase angle (sun-satellite position) which reduced the observed anisotropy signal and we demonstrate that theoretically if the probe had a variable phase angle between 0-20°, there would have been a much larger predicted change in surface reflectance of 0.1 and under such a scenario three-dimensional vegetation structure on Earth could possibly have been detected. These results suggest that anisotropic effects may be useful to help determine whether exoplanets have three-dimensional vegetation structure in the future, but that further comparisons between empirical and theoretical results are first necessary.

  14. Detecting 3D Vegetation Structure with the Galileo Space Probe: Can a Distant Probe Detect Vegetation Structure on Earth?

    Directory of Open Access Journals (Sweden)

    Christopher E Doughty

    Full Text Available Sagan et al. (1993 used the Galileo space probe data and first principles to find evidence of life on Earth. Here we ask whether Sagan et al. (1993 could also have detected whether life on Earth had three-dimensional structure, based on the Galileo space probe data. We reanalyse the data from this probe to see if structured vegetation could have been detected in regions with abundant photosynthetic pigments through the anisotropy of reflected shortwave radiation. We compare changing brightness of the Amazon forest (a region where Sagan et al. (1993 noted a red edge in the reflectance spectrum, indicative of photosynthesis as the planet rotates to a common model of reflectance anisotropy and found measured increase of surface reflectance of 0.019 ± 0.003 versus a 0.007 predicted from only anisotropic effects. We hypothesize the difference was due to minor cloud contamination. However, the Galileo dataset had only a small change in phase angle (sun-satellite position which reduced the observed anisotropy signal and we demonstrate that theoretically if the probe had a variable phase angle between 0-20°, there would have been a much larger predicted change in surface reflectance of 0.1 and under such a scenario three-dimensional vegetation structure on Earth could possibly have been detected. These results suggest that anisotropic effects may be useful to help determine whether exoplanets have three-dimensional vegetation structure in the future, but that further comparisons between empirical and theoretical results are first necessary.

  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. Irradiation of dehydrated vegetables

    International Nuclear Information System (INIS)

    Esterhuyse, A; Esterhuizen, T.

    1985-01-01

    The reason for radurization was to decreased the microbial count of dehydrated vegetables. The average absorbed irradiation dose range between 2kGy and 15kGy. The product catagories include a) Green vegetables b) White vegetables c) Powders of a) and b). The microbiological aspects were: Declining curves for the different products of T.P.C., Coliforms, E. Coli, Stap. areus, Yeast + Mold at different doses. The organoleptical aspects were: change in taste, flavour, texture, colour and moisture. The aim is the marketing of irradiated dehydrated vegetables national and international basis

  17. Satellite switched FDMA advanced communication technology satellite program

    Science.gov (United States)

    Atwood, S.; Higton, G. H.; Wood, K.; Kline, A.; Furiga, A.; Rausch, M.; Jan, Y.

    1982-01-01

    The satellite switched frequency division multiple access system provided a detailed system architecture that supports a point to point communication system for long haul voice, video and data traffic between small Earth terminals at Ka band frequencies at 30/20 GHz. A detailed system design is presented for the space segment, small terminal/trunking segment at network control segment for domestic traffic model A or B, each totaling 3.8 Gb/s of small terminal traffic and 6.2 Gb/s trunk traffic. The small terminal traffic (3.8 Gb/s) is emphasized, for the satellite router portion of the system design, which is a composite of thousands of Earth stations with digital traffic ranging from a single 32 Kb/s CVSD voice channel to thousands of channels containing voice, video and data with a data rate as high as 33 Mb/s. The system design concept presented, effectively optimizes a unique frequency and channelization plan for both traffic models A and B with minimum reorganization of the satellite payload transponder subsystem hardware design. The unique zoning concept allows multiple beam antennas while maximizing multiple carrier frequency reuse. Detailed hardware design estimates for an FDMA router (part of the satellite transponder subsystem) indicate a weight and dc power budget of 353 lbs, 195 watts for traffic model A and 498 lbs, 244 watts for traffic model B.

  18. Odyssey, an optimized personal communications satellite system

    Science.gov (United States)

    Rusch, Roger J.

    Personal communications places severe demands on service providers and transmission facilities. Customers are not satisfied with the current levels of service and want improvements. Among the characteristics that users seek are: lower service rates, hand held convenience, acceptable time delays, ubiquitous service, high availability, reliability, and high quality. The space industry is developing commercial space systems for providing mobile communications to personal telephones. Provision of land mobile satellite service is fundamentally different from the fixed satellite service provided by geostationary satellites. In fixed service, the earth based antennas can depend on a clear path from user to satellite. Mobile users in a terrestrial environment commonly encounter blockage due to vegetation, terrain or buildings. Consequently, high elevation angles are of premium value. TRW studied the issues and concluded that a Medium Earth Orbit constellation is the best solution for Personal Communications Satellite Service. TRW has developed Odyssey, which uses twelve satellites in medium altitude orbit to provide personal communications satellite service. The Odyssey communications system projects a multibeam antenna pattern to the Earth. The attitude control system orients the satellites to ensure constant coverage of land mass and coastal areas. Pointing can be reprogrammed by ground control to ensure optimized coverage of the desired service areas. The payload architecture features non-processing, "bent pipe" transponders and matrix amplifiers to ensure dynamic power delivery to high demand areas. Circuit capacity is 3000 circuits per satellite. Each satellite weighs 1917 kg (4226 pounds) at launch and the solar arrays provide 3126 Watts of power. Satellites are launched in pairs on Ariane, Atlas, or other vehicles. Each satellite is placed in a circular orbit at an altitude of 10,354 km. There are three orbit planes inclined at 55° to the equatorial plane