WorldWideScience

Sample records for satellite vegetation indices

  1. Correlation between satellite vegetation indices and crop coefficients

    Science.gov (United States)

    Russo, A. L.; Simoniello, T.; Greco, M.; Squicciarrino, G.; Lanfredi, M.; Macchiato, M.

    2010-05-01

    Accurate estimations of plant evapotranspiration and its spatial distribution are fundamental for the evaluation of vegetation water stress. Satellite remote sensing techniques represent precious tools for the evapotranspiration estimations at large scale. Many studies are based on the use of thermal signals as inputs for energy balance equations that are solved to estimate evapotranspiration (e.g., Bastiaanssen et al., 1998; Ayenew, 2003). This approach requires many inputs and a detailed theoretical background knowledge. Other works (e.g., Calera at al., 2005; Gonzalez-Dugo and Mateos, 2008) explored a second approach based on the FAO method that estimates the plant evapotranspiration by weighting the reference evapotranspiration with a crop coefficient (Kc) derived from satellite based vegetation indices. Such studies mainly investigated the usefulness of high resolution satellite data, such as Quickbird, Ikonos, TM, that in spite of the high spatial sampling, are not suitable for a dense temporal sampling. In order to generate spatially distributed values of Kc that capture field-specific crop development, we investigated the usefulness of vegetation indices derived from a time series (2005-2008) of medium resolution MODIS data. We analyzed the spatial and temporal correlation of different indices (NDVI, EVI, and WDVI) with crop coefficients available in literature for different herbaceous and arboreal cultivations present in the study area (Basilicata region, southern Italy). To take into account the background of the cultivation covers, we weighted the Kc by considering the vegetation fraction within each the pixel. By evaluating altogether the cultivations, we found that the correlation increases during the growing season (R2 > 0.80) whereas it decreases during the winter period (R2 cultivation highlighted that NDVI provided quite high correlation for all the investigated cultivation with maximum values for wheat (R2 = 0.89) and vineyards (R2 = 0.83). For

  2. Sensitivity of vegetation indices to different burn and vegetation ratios using LANDSAT-5 satellite data

    Science.gov (United States)

    Pleniou, M.; Koutsias, N.

    2013-08-01

    The application of vegetation indices is a very common approach in remote sensing of burned areas to either map the fire scar or estimate burn severity since they minimize the effect of exogenous factors and enhance the correlation with the internal parameters of vegetation. In a recent study we found that the original spectral channels, based on which these indices are estimated, are sensitive to external parameters of the vegetation as for example the spectral reflectance of the background soil. In such cases, the influence of the soil in the reflectance values is different in the various spectral regions depending on its type. These problems are further enhanced by the non-homogeneous pixels, as created from fractions of different types of land cover. Parnitha (Greece), where a wildfire occurred on July 2007, was established as test site. The purpose of this work is to explore the sensitivity of vegetation indices when used to estimate and map different fractions of fire-scorched (burned) and non fire-scorched (vegetated) areas. IKONOS, a very high resolution satellite imagery, was used to create a three-class thematic map to extract the percentages of vegetation, burned surfaces, and bare soil. Using an overlaid fishnet we extracted samples of completely "burned", completely "vegetated" pixels and proportions with different burn/vegetation ratios (45%-55% burned - 45%-55% vegetation, 20%-30% burned - 70%- 80% vegetation, 70%-80% burned - 20%-30% vegetation). Vegetation indices were calculated (NDVI, IPVI, SAVI) and their values were extracted to characterize the mentioned classes. The main findings of our recent research were that vegetation indices are less sensitive to external parameters of the vegetation by minimizing external effects. Thus, the semi-burned classes were spectrally more consistent to their different fractions of scorched and non-scorched vegetation, than the original spectral channels based on which these indices are estimated.

  3. Use of spectral channels and vegetation indices from satellite VEGETATION time series for the Post-Fire vegetation recovery estimation

    Science.gov (United States)

    Coluzzi, Rosa; Lasaponara, Rosa; Montesano, Tiziana; Lanorte, Antonio; de Santis, Fortunato

    2010-05-01

    Satellite data can help monitoring the dynamics of vegetation in burned and unburned areas. Several methods can be used to perform such kind of analysis. This paper is focused on the use of different satellite-based parameters for fire recovery monitoring. In particular, time series of single spectral channels and vegetation indices from SPOT-VEGETATION have investigated. The test areas is the Mediterranean ecosystems of Southern Italy. For this study we considered: 1) the most widely used index to follow the process of recovery after fire: normalized difference vegetation index (NDVI) obtained from the visible (Red) and near infrared (NIR) by using the following formula NDVI = (NIR_Red)/(NIR + Red), 2) moisture index MSI obtained from the near infrared and Mir for characterization of leaf and canopy water content. 3) NDWI obtained from the near infrared and Mir as in the case of MSI, but with the normalization (as the NDVI) to reduce the atmospheric effects. All analysis for this work was performed on ten-daily normalized difference vegetation index (NDVI) image composites (S10) from the SPOT- VEGETATION (VGT) sensor. The final data set consisted of 279 ten-daily, 1 km resolution NDVI S1O composites for the period 1 April 1998 to 31 December 2005 with additional surface reflectance values in the blue (B; 0.43-0.47,um), red (R; 0.61-0.68,um), near-infrared (NIR; 0.78-0.89,um) and shortwave-infrared (SWIR; 1.58-1.75,um) spectral bands, and information on the viewing geometry and pixel status. Preprocessing of the data was performed by the Vlaamse Instelling voor Technologisch Onderzoek (VITO) in the framework of the Global Vegetation Monitoring (GLOVEG) preprocessing chain. It consisted of the Simplified Method for Atmospheric Correction (SMAC) and compositing at ten-day intervals based on the Maximum Value Compositing (MVC) criterion. All the satellite time series were analysed using the Detrended Fluctuation Analysis (DFA) to estimate post fire vegetation recovery

  4. The role of spatial and spectral resolution on the effectiveness of satellite-based vegetation indices

    Science.gov (United States)

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

    2016-10-01

    Remote Sensing applications are designed to provide farmers with timely crop monitoring and production information. Such information can be used to identify crop needs or health problems and provide solutions for a better crop management. Vegetation indices (VIs) derived from satellite data have been widely used to assess variations in the physiological state and biophysical properties of vegetation. In the present study, the experimental area is located near the village Eleftherion of Larissa Prefecture in the Thessaly Plain, and consisted of two adjacent agricultural fields of cotton and corn. Imagery from WorldView-2 (WV2) satellite platform was obtained from European Space Imaging and Landsat-8 (L8) free of charge data were downloaded from the United States Geological Survey (USGS) archive. The images were selected for a four month span to evaluate continuity with respect to vegetation growth variation. VIs for each satellite platform data such as the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI) and the Fraction Photosynthetically Radiation (FPAR) were calculated. The comparison of these VIs produced from the two satellite systems with different spatial and spectral resolution was made for each growth stage of the crops and their results were analyzed in order to examine their correlation. Utilizing the WV2 new spectral data, several innovative chlorophyll and vegetation indices were created and evaluated so as to reveal their effectiveness in the detection of problematic plant growth areas. The Green Chlorophyll index appeared to be the most efficient index for the delineation of these areas.

  5. Atmospheric correction for satellite remotely sensed data intended for agricultural applications: impact on vegetation indices

    Directory of Open Access Journals (Sweden)

    D. G. Hadjimitsis

    2010-01-01

    Full Text Available Solar radiation reflected by the Earth's surface to satellite sensors is modified by its interaction with the atmosphere. The objective of applying an atmospheric correction is to determine true surface reflectance values and to retrieve physical parameters of the Earth's surface, including surface reflectance, by removing atmospheric effects from satellite images. Atmospheric correction is arguably the most important part of the pre-processing of satellite remotely sensed data. Such a correction is especially important in cases where multi-temporal images are to be compared and analyzed. For agricultural applications, in which several vegetation indices are applied for monitoring purposes, multi-temporal images are used. The integration of vegetation indices from remotely sensed images with other hydro-meteorological data is widely used for monitoring natural hazards such as droughts. Indeed, the most important task is to retrieve the true values of the vegetation status from the satellite-remotely sensed data. Any omission of considering the effects of the atmosphere when vegetation indices from satellite images are used, may lead to major discrepancies in the final outcomes. This paper highlights the importance of considering atmospheric effects when vegetation indices, such as DVI, NDVI, SAVI, MSAVI and SARVI, are used (or considered and presents the results obtained by applying the darkest-pixel atmospheric correction method on ten Landsat TM/ETM+ images of Cyprus acquired from July to December 2008. Finally, in this analysis, an attempt is made to determine evapotranspiration and to examine its dependence on the consideration of atmospheric effects when multi-temporal image data are used. It was found that, without applying any atmospheric correction, the real daily evapotranspiration was less than the one found after applying the darkest pixel atmospheric correction method.

  6. 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

    2015-03-01

    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. 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. 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. 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. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

    Science.gov (United States)

    Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

    2010-09-01

    In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional

  8. 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 ...

  9. Identification of Forest Vegetation Using Vegetation Indices

    Institute of Scientific and Technical Information of China (English)

    Yuan Jinguo; Wang Wei

    2004-01-01

    Spectral feature of forest vegetation with remote sensing techniques is the research topic all over the world, because forest plays an important role in human beings' living environment. Research on vegetation classification with vegetation index is still very little recently. This paper proposes a method of identifying forest types based on vegetation indices,because the contrast of absorbing red waveband with reflecting near-infrared waveband strongly for different vegetation types is recognized as the theoretic basis of vegetation analysis with remote sensing. Vegetation index is highly related to leaf area index, absorbed photosynthetically active radiation and vegetation cover. Vegetation index reflects photosynthesis intensity of plants and manifests different forest types. According to reflectance data of forest canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun of China, many vegetation indices are calculated and analyzed. The result shows that the relationships between vegetation indices and forest types are that perpendicular vegetation index (PVI) identifies broadleaf forest and coniferous forest the most easily;the next is transformed soil-adjusted vegetation index(TSVI) and modified soil-adjusted vegetation index(MSVI), but their calculation is complex. Ratio vegetation index (RVT) values of different coniferous forest vary obviously, so RVI can classify conifers.Therefore, the combination of PVI and RVI is evaluated to classify different vegetation types.

  10. Combining Satellite-Based Precipitation and Vegetation Indices to Achieve a Mid-Summer Agricultural Forecast in Jamaica

    Science.gov (United States)

    Curtis, S.; Allen, T. L.; Gamble, D.

    2009-12-01

    In this study global Earth observations of precipitation and Normalized Difference Vegetation Indices (NDVI) are used to assess the mid-summer dry spell’s (MSD) strength and subsequent impact on agriculture in the St. Elizabeth parish of Jamaica. St. Elizabeth is known as the ‘bread basket’ of Jamaica and has been the top or second highest producer of domestic food crops in the last twenty years. Yet, St. Elizabeth sits in the Jamaican rain shadow and is highly affected by drought. In addition, the summer rainy season is regularly interrupted by an MSD, which often occurs in July, has strong interannual variability, and greatly affects cropping strategies and yields. The steps undertaken to achieve a mid-summer agricultural forecast are: 1) use relationships between Global Precipitation Climatology Project v2.1 data over western Jamaica and predictive climate modes from 1979 to present to develop a forecast of July rainfall 2) downscale the rainfall variability in time to sub-monthly and space to the St. Elizabeth parish using the Tropical Rainfall Measuring Mission 3) link rainfall variability to vegetation vigor with the MODIS NDVI data 4) communicate with St. Elizabeth farmers via the University of West Indies, Mona. An important finding from this study is a decrease in vegetative vigor follows the MSD by two to four weeks in St. Elizabeth and the vegetation in the southern portion of the parish appears to be more sensitive to the MSD than vegetation elsewhere in the country.

  11. 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 factor in reducing river flows. Climate change, regional groundwater pumping, changes in the intensity of monsoon rain events and lack of overbank flooding are feasible explanations for deterioration of the riparian forest in the northern reach.

  12. Interet de l'indice de vegetation des satellites NOAA-AVHRR pour le suivi des cultures (resultats d'une etude dans la Basse Vallee du Rhone)

    OpenAIRE

    Lagouarde, Jean-Pierre; SEGUIN, Bernard; Clinet, S.; Gandia, S.; Kerr, Y.

    1986-01-01

    Par rapport aux satellites d’observation de la Terre (Landsat, SPOT) à forte résolution spatiale, mais faible répétitivité temporelle, les satellites météorologiques NOAA-AVHRR ont l’avantage de permettre, grâce à 4 passages par jour, un suivi des cultures au cours de la saison de végétation. L’inconvénient majeur est la résolution spatiale limitée à 1 km2. Une étude a été effectuée sur les années 1983 et 1984 pour évaluer l’intérêt des indices de végétation dérivés des données NOAA, para...

  13. Global relation between microwave satellite vegetation products and vegetation productivity

    Science.gov (United States)

    Teubner, Irene E.; Forkel, Matthias; Jung, Martin; Miralles, Diego G.; Dorigo, Wouter A.

    2017-04-01

    The occurrence of unfavourable environmental conditions like droughts commonly reduces the photosynthetic activity of ecosystems and, hence, their potential to take up carbon from the atmosphere. Ecosystem photosynthetic activity is commonly determined using remote sensing observations in the optical domain, which however have limitations particularly in regions of frequent cloud cover, e.g. the tropics. In this study, we explore the potential of vegetation optical depth (VOD) from microwave satellite observations as an alternative source for assessing vegetation productivity. VOD serves as an estimate for vegetation density and water content, which has an impact on plant physiological processes and hence should potentially provide a link to gross primary production (GPP). However, to date, it is unclear how microwave-retrieved VOD data and GPP data are related. We compare seasonal dynamics and anomalies of VOD retrievals from different satellite sensors and microwave frequencies with site level and global GPP estimates. We use VOD observations from active (ASCAT) and passive microwave sensors (AMSR-E, SMOS). We include eddy covariance measurements from the FLUXNET2015 dataset to assess the VOD products at site level. For a global scale analysis, we use the solar-induced chlorophyll fluorescence (SIF) observations from GOME-2 as a proxy for GPP and the FLUXCOM GPP product, which presents an upscaling of site measurements based on remote sensing data. Our results demonstrate that in general a good agreement between VOD and GPP or SIF exists. However, the strength of these relations depends on the microwave frequency, land cover type, and the time within the growing season. Correlations between anomalies of VOD and GPP or SIF support the assumption that microwave-derived VOD can be used to monitor vegetation productivity dynamics. The study is performed as part of the EOWAVE project funded by the Vienna University of Technology (http://eowave.geo.tuwien.ac.at/) and

  14. Amazon vegetation greenness as measured by satellite sensors over the last decade

    OpenAIRE

    Atkinson, P.M.; Dash, J.; Jeganathan, C.

    2011-01-01

    [1] During the last decade two major drought events, one in 2005 and another in 2010, occurred in the Amazon basin. Several studies have claimed the ability to detect the effect of these droughts on Amazon vegetation response, measured through satellite sensor vegetation indices (VIs). Such monitoring capability is important as it potentially links climate changes (increasing frequency and severity of drought), vegetation response as observed through vegetation greenness, and land-atmosphere ...

  15. Using satellite vegetation and compound topographic indices to map highly erodible cropland buffers for cellulosic biofuel crop developments in eastern Nebraska, USA

    Science.gov (United States)

    Gu, Yingxin; Wylie, Bruce K.

    2015-01-01

    Cultivating annual row crops in high topographic relief waterway buffers has negative environmental effects and can be environmentally unsustainable. Growing perennial grasses such as switchgrass (Panicum virgatum L.) for biomass (e.g., cellulosic biofuel feedstocks) instead of annual row crops in these high relief waterway buffers can improve local environmental conditions (e.g., reduce soil erosion and improve water quality through lower use of fertilizers and pesticides) and ecosystem services (e.g., minimize drought and flood impacts on production; improve wildlife habitat, plant vigor, and nitrogen retention due to post-senescence harvest for cellulosic biofuels; and serve as carbon sinks). The main objectives of this study are to: (1) identify cropland areas with high topographic relief (high runoff potentials) and high switchgrass productivity potential in eastern Nebraska that may be suitable for growing switchgrass, and (2) estimate the total switchgrass production gain from the potential biofuel areas. Results indicate that about 140,000 hectares of waterway buffers in eastern Nebraska are suitable for switchgrass development and the total annual estimated switchgrass biomass production for these suitable areas is approximately 1.2 million metric tons. The resulting map delineates high topographic relief croplands and provides useful information to land managers and biofuel plant investors to make optimal land use decisions regarding biofuel crop development and ecosystem service optimization in eastern Nebraska.

  16. Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

    Science.gov (United States)

    Ji, Lei; Peters, Albert J.

    2003-01-01

    The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989–2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI–SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.

  17. Satellite-based Studies on Large-Scale Vegetation Changes in China

    Institute of Scientific and Technical Information of China (English)

    Xia Zhao; Daojing Zhou; Jingyun Fang

    2012-01-01

    Remotely-sensed vegetation indices,which indicate the density and photosynthetic capacity of vegetation,have been widely used to monitor vegetation dynamics over broad areas.In this paper,we reviewed satellite-based studies on vegetation cover changes,biomass and productivity variations,phenological dynamics,desertification,and grassland degradation in China that occurred over the past 2-3 decades.Our review shows that the satellite-derived index (Normalized Difference Vegetation Index,NDVI) during growing season and the vegetation net primary productivity in major terrestrial ecosystems (for example forests,grasslands,shrubs,and croplands) have significantly increased,while the number of fresh lakes and vegetation coverage in urban regions have experienced a substantial decline.The start of the growing season continually advanced in China's temperate regions until the 1990s,with a large spatial heterogeneity.We also found that the coverage of sparsely-vegetated areas declined,and the NDVI per unit in vegetated areas increased in arid and semi-arid regions because of increased vegetation activity in grassland and oasis areas.However,these results depend strongly not only on the periods chosen for investigation,but also on factors such as data sources,changes in detection methods,and geospatial heterogeneity.Therefore,we should be cautious when applying remote sensing techniques to monitor vegetation structures,functions,and changes.

  18. Derivative vegetation indices as a new approach in remote sensing of vegetation

    Institute of Scientific and Technical Information of China (English)

    Svetlana M.KOCHUBEY; Taras A.KAZANTSEV

    2012-01-01

    This paper focuses on the advantages of derivative vegetation indices over simple reflectancebased indices that are traditionally used for remote sensing of vegetation.The idea of using reflectance derivatives instead of simple reflectance spectra was proposed several decades ago.Despite this,it has not been widely used in monitoring systems because the derivatives lack reliable parameters.In addition,most satellite monitoring systems are not equipped with hyperspectral sensors,which are considered necessary for operating with the reflectance derivatives.Here,we present original data indicating that the chlorophyll-related derivative index D725/D702 we derived can be accurately estimated from a reflectance spectrum of 10 nm resolution that would be suitable for most satellite-based sensors.Furthermore,the index is not sensitive to soil reflectance and can therefore be used for testing of open crops.Presence of blanc reflectance is also unnecessary.Preliminary results of index testing are presented.Perspectives on using this and other derivative indices are discussed.

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

    Science.gov (United States)

    AlShamsi, Meera R.

    2016-10-01

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

  20. 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.

  1. 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

  2. Quantifying landscape resilience using vegetation indices

    Science.gov (United States)

    Eddy, I. M. S.; Gergel, S. E.

    2014-12-01

    Landscape resilience refers to the ability of systems to adapt to and recover from disturbance. In pastoral landscapes, degradation can be measured in terms of increased desertification and/or shrub encroachment. In many countries across Central Asia, the use and resilience of pastoral systems has changed markedly over the past 25 years, influenced by centralized Soviet governance, private property rights and recently, communal resource governance. In Kyrgyzstan, recent governance reforms were in response to the increasing degradation of pastures attributed to livestock overgrazing. Our goal is to examine and map the landscape-level factors that influence overgrazing throughout successive governance periods. Here, we map and examine some of the spatial factors influencing landscape resilience in agro-pastoral systems in the Kyrgyzstan Republic where pastures occupy >50% of the country's area. We ask three questions: 1) which mechanisms of pasture degradation (desertification vs. shrub encroachment), are detectable using remote sensing vegetation indices?; 2) Are these degraded pastures associated with landscape features that influence herder mobility and accessibility (e.g., terrain, distance to other pastures)?; and 3) Have these patterns changed through successive governance periods? Using a chronosequence of Landsat imagery (1999-2014), NDVI and other VIs were used to identify trends in pasture condition during the growing season. Least-cost path distances as well as graph theoretic indices were derived from topographic factors to assess landscape connectivity (from villages to pastures and among pastures). Fieldwork was used to assess the feasibility and accuracy of this approach using the most recent imagery. Previous research concluded that low herder mobility hindered pasture use, thus we expect the distance from pasture to village to be an important predictor of pasture condition. This research will quantify the magnitude of pastoral degradation and test

  3. MODIS/TERRA MOD44A Vegetation Indices

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  4. Parameterization of Vegetation Aerodynamic Roughness of Natural Regions Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard; Stewart, Pamela

    1998-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. The parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  5. State Indicator Report on Fruits and Vegetables, 2009

    Science.gov (United States)

    Centers for Disease Control and Prevention, 2009

    2009-01-01

    The "State Indicator Report on Fruits and Vegetables, 2009" provides for the first time information on fruit and vegetable (F&V) consumption and policy and environmental support within each state. Fruits and vegetables, as part of a healthy diet, are important for optimal child growth, weight management, and chronic disease…

  6. Relationships between vegetation indices and different burn and vegetation ratios: a multi-scale approach applied in a fire affected area

    Science.gov (United States)

    Pleniou, M.; Koutsias, N.

    2013-08-01

    Vegetation indices have been widely used in remote sensing literature for burned land mapping and monitoring. In the present study we used satellite data (IKONOS, LANDSAT, ASTER, MODIS) of multiple spectral (visible, near, shortwave infrared) and spatial (1-500 meters) resolutions, acquired shortly after a very destructive fire occurred in the mountain of Parnitha in Attica, Greece the summer of 2007. The aim of our study is to examine and evaluate the performance of some vegetation indices for burned land mapping and also to characterize the relationships between vegetation indices and the percent of fire-scorched (burned) and non fire-scorched (vegetated) areas. The available satellite images were processed geometrically, radiometrically and atmospherically. The very high resolution IKONOS imagery was served as a base to estimate the percent of cover of burned areas, bare soil and vegetation by applying the maximum likelihood classification algorithm. The percent of cover for each type was then correlated to vegetation indices for all the satellite images, and regression models were fit to characterize those relationships. In total 57 versions of some classical vegetation indices were computed using LANDSAT, ASTER and MODIS data. Most of them were modified by replacing Red with SWIR channel, as the latter has been proved sensitive to burned area discrimination. IPVI and NDVI showed a better performance among the indices tested to estimate the percent of vegetation, while most of the modified versions of the indices showed highest performance to estimate the percent of burned areas.

  7. Sensitivity Analysis of Remote Sensing Data: Comparing the Response of Vegetation Indices in Tropical Areas.

    Science.gov (United States)

    Bonifaz, R.

    2005-12-01

    During the past two decades, satellite remote sensing systems possessing high temporal resolution, but typically moderate or coarse spatial resolution, have increasingly been used to characterize and map vegetation dynamics. Assessing the seasonality of tropical vegetation has, however, been especially challenging. Tropical regimes of temperature and precipitation are generally less variable and pronounced than those in other biomes, and variations in plant growth are often more subtle. Using samples from selected tropical land cover types (tropical rain forest, tropical grasses, tropical deciduous forest, mixed forest and agricultural areas), sensitivity analysis will be carried out comparing different 'greenness' indices such as the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI) and the Wide Dynamic Range Vegetation Index (WDRVI) derived from the MODIS/TERRA sensor. This analysis will potentially allow the selection of the best index to describe the particular behavior of tropical vegetation for further characterization of seasonal changes of such areas.

  8. 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

  9. Comparison of Some Vegetation Indices in Seasonal Information

    Institute of Scientific and Technical Information of China (English)

    HAO Chengyuan; WU Shaohong; XU Chuanyang

    2008-01-01

    With the development of vegetation indices,the reflection capability of vegetation indices to the state of vegetation has been improved in various degrees.Especially,the vegetation index of Terra/MODIS-EVI is believed to have the highest sensitivity to the seasonality of vegetation.This study compares the reflection susceptibility of three vegetation indices (NOAA/AVHRR-NDVI,Teffa/MODIS-NDVI and Terra/MODIS-EVI) to the seasonal variations of vegetation in the mid-south of Yutman Province of China.It has been found that Terra/MODIS-EVI does best in the elimination of external disturbance.Firstly,it obviously improves the linear relationship with vegetation cover degree,especially in the high vegetation coverage area.Secondly,it avoids the emergence of vegetation index saturation.Thirdly,it reduces the environmental influence including both effects of atmosphere and soil.So it is believed that the Terra/MODIS-EVI can offer excellent tool for quantitative research of remote sensing and has realized to be oriented by data with high quality.

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

    African Journals Online (AJOL)

    SERVER

    2008-01-18

    Jan 18, 2008 ... structure insensitive pigment index (SIPI) were chosen out of 19 indices initially tested. The NDVI ... Because chlorophyll content plays a direct role in photosynthesis ... near infrared (NIR) reflectance from its leaves. Jensen.

  11. Retrieval of vegetation hydrodynamic parameters from satellite multispectral data

    Science.gov (United States)

    Forzieri, Giovanni; Degetto, Massimo; Righetti, Maurizio; Castelli, Fabio; Preti, Federico

    2013-04-01

    Riparian vegetation plays a crucial role on affecting the floodplain hydraulic roughness, which in turn significantly influences the dynamics of flood waves. This work explores the potential accuracies of retrieving vegetation hydrodynamic parameters through satellite multispectral data. The method is focused on estimation of vegetation height and flexural rigidity for herbaceous patterns and of plant density, tree height, stem diameter, crown base height and crown diameter of high-forest and coppice consociations for arboreal and shrub patterns. The retrieval algorithm performs: (1) classification procedure of riparian corridor; (2) land cover-based Principal Component Analysis of spectral channels; (3) explorative analysis of correlation structure between principal components and biomechanical properties and (4) model identification/estimation/validation for floodplain roughness parameterization. To capture the impacts of stiff/flexible vegetation, a GIS hydrodynamic model has been coupled with a flow resistance external routine that estimates the hydraulic roughness by using simulated water stages and the remote sensing-derived vegetation parameters. The procedure is tested along a 3-km reach of the Avisio river (Trentino Alto Adige, Italy) by comparing extended field surveys and a synchronous SPOT-5 multispectral image acquired on 28/08/2004. Results showed significant correlation values between spectral-derived information and hydrodynamic parameters. Predictive models provided high coefficients of determination, especially for mixed arboreal and shrub land covers. The generated structural parameter maps represent spatially explicit data layers that can be used as inputs to hydrodynamic models to analyze flow resistance effects in different submergence conditions of vegetation. The hydraulic modelling results showed that the new method is able to provide accurate hydraulic output data and to enhance the roughness estimation up to 73% with respect to a

  12. 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...

  13. Mapping Arctic Tundra Vegetation Communities Using Field Spectroscopy and Multispectral Satellite Data in North Alaska, USA

    Directory of Open Access Journals (Sweden)

    Scott J. Davidson

    2016-11-01

    Full Text Available The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements. The objectives of this study were: (1 to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2 to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450–510 nm, 630–690 nm and 705–745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450–510 nm and 630–690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using

  14. Monitoring vegetation responses to drought -- linking Remotely-sensed Drought Indices with Meteorological drought indices

    Science.gov (United States)

    Wang, H.; Lin, H.; Liu, D.

    2013-12-01

    Abstract: Effectively monitoring vegetation drought is of great significance in ecological conservation and agriculture irrigation at the regional scale. Combining meteorological drought indices with remotely sensed drought indices can improve tracking vegetation dynamic under the threat of drought. This study analyzes the dynamics of spatially-defined Temperature Vegetation Dryness Index (TVDI) and temporally-defined Vegetation Health Index (VHI) from remotely sensed NDVI and LST datasets in the dry spells in Southwest China. We analyzed the correlation between remotely sensed drought indices and meteorological drought index of different time scales. The results show that TVDI was limited by the spatial variations of LST and NDVI, while VHI was limited by the temporal variations of LST and NDVI. Station-based buffering analysis indicates that the extracted remotely sensed drought indices and Standard Precipitation Index (SPI) could reach stable correlation with buffering radius larger than 35 km. Three factors affect the spatiotemporal relationship between remotely sensed drought indices and SPI: i) different vegetation types; ii) the timescale of SPI; and iii) remote sensing data noise. Vegetation responds differently to meteorological drought at various time scales. The correlation between SPI6 and VHI is more significant than that between SPI6 and TVDI. Spatial consistency between VHI and TVDI varies with drought aggravation. In early drought period from October to December, VHI and TVDI show limited consistency due to the low quality of remotely sensed images. The study helps to improve monitoring vegetation drought using both meteorological drought indices and remotely sensed drought indices.

  15. 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.

  16. Satellite image analysis for surveillance, vegetation and climate change

    Energy Technology Data Exchange (ETDEWEB)

    Cai, D Michael [Los Alamos National Laboratory

    2011-01-18

    Recently, many studies have provided abundant evidence to show the trend of tree mortality is increasing in many regions, and the cause of tree mortality is associated with drought, insect outbreak, or fire. Unfortunately, there is no current capability available to monitor vegetation changes, and correlate and predict tree mortality with CO{sub 2} change, and climate change on the global scale. Different survey platforms (methods) have been used for forest management. Typical ground-based forest surveys measure tree stem diameter, species, and alive or dead. The measurements are low-tech and time consuming, but the sample sizes are large, running into millions of trees, covering large areas, and spanning many years. These field surveys provide powerful ground validation for other survey methods such as photo survey, helicopter GPS survey, and aerial overview survey. The satellite imagery has much larger coverage. It is easier to tile the different images together, and more important, the spatial resolution has been improved such that close to or even higher than aerial survey platforms. Today, the remote sensing satellite data have reached sub-meter spatial resolution for panchromatic channels (IKONOS 2: 1 m; Quickbird-2: 0.61 m; Worldview-2: 0.5 m) and meter spatial resolution for multi-spectral channels (IKONOS 2: 4 meter; Quickbird-2: 2.44 m; Worldview-2: 2 m). Therefore, high resolution satellite imagery can allow foresters to discern individual trees. This vital information should allow us to quantify physiological states of trees, e.g. healthy or dead, shape and size of tree crowns, as well as species and functional compositions of trees. This is a powerful data resource, however, due to the vast amount of the data collected daily, it is impossible for human analysts to review the imagery in detail to identify the vital biodiversity information. Thus, in this talk, we will discuss the opportunities and challenges to use high resolution satellite imagery and

  17. Foliar anthocyanin content - Sensitivity of vegetation indices using green reflectance

    Science.gov (United States)

    Vina, A.; Gitelson, A. A.

    2009-12-01

    The amount and composition of photosynthetic and non-photosynthetic foliar pigments varies primarily as a function of species, developmental and phenological stages, and environmental stresses. Information on the absolute and relative amounts of these pigments thus provides insights onto the physiological conditions of plants and their responses to stress, and has the potential to be used for evaluating plant species composition and diversity across broad geographic regions. Anthocyanins in particular, are non-photosynthetic pigments associated with the resistance of plants to environmental stresses (e.g., drought, low soil nutrients, high radiation, herbivores, and pathogens). As they absorb radiation primarily in the green region of the electromagnetic spectrum (around 540-560 nm), broad-band vegetation indices that use this region in their formulation will respond to their presence. We evaluated the sensitivity of three vegetation indices using reflectance in the green spectral region (the green Normalized Difference Vegetation Index, gNDVI, the green Chlorophyll Index, CIg, and the Visible Atmospherically Resistant Vegetation Index, VARI) to foliar anthocyanins in five different species. For comparison purposes the widely used Normalized Difference Vegetation Index, NDVI was also evaluated. Among the four indices tested, the VARI, which uses only spectral bands in the visible region of the electromagnetic spectrum, was found to be inversely and linearly related to the relative amount of foliar anthocyanins. While this result was obtained at leaf level, it opens new possibilities for analyzing anthocyanin content across multiple scales, by means of currently operational aircraft- and spacecraft-mounted broad-band sensor systems. Further studies that evaluate the sensitivity of the VARI to the relative content of anthocyanins across space (e.g., at canopy and regional scales) and time, and its relationship with plant biodiversity and vegetation stresses, are

  18. The Impact of Sunlight Conditions on the Consistency of Vegetation Indices in Croplands—Effective Usage of Vegetation Indices from Continuous Ground-Based Spectral Measurements

    Directory of Open Access Journals (Sweden)

    Mitsunori Ishihara

    2015-10-01

    Full Text Available A ground-based network of spectral observations is useful for ecosystem monitoring and validation of satellite data. However, these observations contain inherent uncertainties due to the change of sunlight conditions. This study investigated the impact of changing solar zenith angles and diffuse/direct light conditions on the consistency of vegetation indices (normalized difference vegetation index (NDVI and green-red vegetation index (GRVI derived from ground-based spectral measurements in three different types of cropland (paddy field, upland field, cultivated grassland in Japan. In general, the vegetation indices decreased with decreasing solar zenith angle. This response was affected significantly by the growth stage and diffuse/direct light conditions. The decreasing response of the NDVI to the decreasing solar zenith angle was high during the middle growth stage (0.4 < NDVI < 0.8. On the other hand, a similar response of the GRVI was evident except in the early growth stage (GRVI < 0. The response of vegetation indices to the solar zenith angle was evident under clear sky conditions but almost negligible under cloudy sky conditions. At large solar zenith angles, neither the NDVI nor the GRVI were affected by diffuse/direct light conditions in any growth stage. These experimental results were supported well by the results of simulations based on a physically-based canopy reflectance model (PROSAIL. Systematic selection of the data from continuous diurnal spectral measurements in consideration of the solar light conditions would be effective for accurate and consistent assessment of the canopy structure and functioning.

  19. A New EO-Based Indicator for Assessing and Monitoring Climate-Related Vegetation Stress

    Science.gov (United States)

    McCormick, Niall; Gobron, Nadine

    2016-08-01

    This paper describes a study in which a new environmental indicator, called Annual Vegetation Stress (AVS), has been developed, based on annual anomalies of satellite-measured Fraction of Absorbed Photosynthetically Active Radiation (FAPAR ), and used to map the area affected annually by vegetation stress during the period 2003-2014, for 108 selected developing countries. Analysis of the results for six countries in the "tropical and subtropical forests" ecoregion, reveals good correspondence between high AVS values, and the occurrence of climatic extremes (droughts) and anthropogenic disturbance (deforestation). The results for Equatorial Guinea suggest that the recent trend of large-scale droughts and rainfall deficits in Central and Western Africa, contribute to increased vegetation stress in the region's tropical rainforests. In East Timor there is evidence of a "biological lag" effect, whereby the main impacts of drought on the country's seasonally dry tropical forests are delayed until the year following the climate event.

  20. Response of spectral vegetation indices to soil moisture in grasslands and shrublands

    Science.gov (United States)

    Zhang, L.; Ji, L.; Wylie, B.K.

    2011-01-01

    The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture. ?? 2011 Taylor & Francis.

  1. Phenological dynamics of arctic tundra vegetation and its implications on satellite imagery interpretation

    Science.gov (United States)

    Juutinen, Sari; Aurela, Mika; Mikola, Juha; Räsänen, Aleksi; Virtanen, Tarmo

    2016-04-01

    Remote sensing is a key methodology when monitoring the responses of arctic ecosystems to climatic warming. The short growing season and rapid vegetation development, however, set demands to the timing of image acquisition in the arctic. We used multispectral very high spatial resolution satellite images to study the effect of vegetation phenology on the spectral reflectance and image interpretation in the low arctic tundra in coastal Siberia (Tiksi, 71°35'39"N, 128°53'17"E). The study site mainly consists of peatlands, tussock, dwarf shrub, and grass tundra, and stony areas with some lichen and shrub patches. We tested the hypotheses that (1) plant phenology is responsive to the interannual weather variation and (2) the phenological state of vegetation has an impact on satellite image interpretation and the ability to distinguish between the plant communities. We used an empirical transfer function with temperature sums as drivers to reconstruct daily leaf area index (LAI) for the different plant communities for years 2005, and 2010-2014 based on measured LAI development in summer 2014. Satellite images, taken during growing seasons, were acquired for two years having late and early spring, and short and long growing season, respectively. LAI dynamics showed considerable interannual variation due to weather variation, and particularly the relative contribution of graminoid dominated communities was sensitive to these phenology shifts. We have also analyzed the differences in the reflectance values between the two satellite images taking account the LAI dynamics. These results will increase our understanding of the pitfalls that may arise from the timing of image acquisition when interpreting the vegetation structure in a heterogeneous tundra landscape. Very high spatial resolution multispectral images are available at reasonable cost, but not in high temporal resolution, which may lead to compromises when matching ground truth and the imagery. On the other hand

  2. Global-scale analysis of vegetation indices for moderate resolution monitoring of terrestrial vegetation

    Science.gov (United States)

    Huete, Alfredo R.; Didan, Kamel; van Leeuwen, Willem J. D.; Vermote, Eric F.

    1999-12-01

    Vegetation indices have emerged as important tools in the seasonal and inter-annual monitoring of the Earth's vegetation. They are radiometric measures of the amount and condition of vegetation. In this study, the Sea-viewing Wide Field-of-View sensor (SeaWiFS) is used to investigate coarse resolution monitoring of vegetation with multiple indices. A 30-day series of SeaWiFS data, corrected for molecular scattering and absorption, was composited to cloud-free, single channel reflectance images. The normalized difference vegetation index (NDVI) and an optimized index, the enhanced vegetation index (EVI), were computed over various 'continental' regions. The EVI had a normal distribution of values over the continental set of biomes while the NDVI was skewed toward higher values and saturated over forested regions. The NDVI resembled the skewed distributions found in the red band while the EVI resembled the normal distributions found in the NIR band. The EVI minimized smoke contamination over extensive portions of the tropics. As a result, major biome types with continental regions were discriminable in both the EVI imagery and histograms, whereas smoke and saturation considerably degraded the NDVI histogram structure preventing reliable discrimination of biome types.

  3. 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.

  4. Classification of mangroves vegetation species using texture analysis on Rapideye satellite imagery

    Science.gov (United States)

    Roslani, M. A.; Mustapha, M. A.; Lihan, T.; Juliana, W. A. Wan

    2013-11-01

    Mangroves are unique ecosystem structures that are typically made up of salt tolerant species of vegetation that can be found in tropical and subtropical climate country. Mangrove ecosystem plays important role and also is known as highly productive ecosystem with high diversity of flora and fauna. However, these ecosystems have been declining over time due to the various kinds of direct and indirect pressures. Thus, there is an increasing need to monitor and assess this ecosystem for better conservation and management efforts. The multispectral RapidEye satellite image was used to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia using texture analysis. Classification was implemented using the maximum likelihood classifier (MLC) method. Total of eleven main mangrove species were found in the satellite image of the study site which includes Rhizophora mucronata, Rhizophora apiculata, Bruguiera parviflora, Bruguiera cylindrica, Bruguiera gymnorrhiza, Avicennia alba, Avicennia officinalis, Sonneratia alba, Sonneratia caseolaris, Sonneratia ovata and Xylocarpus granatum. The classification results showed that the textured image produced high overall classification assessment recorded at 84% and kappa statistic of 0.8016. Meanwhile, the non-textured image produces 80% of overall accuracy and kappa statistic of 0.7061. The classification result indicated the capability of high resolution satellite image to classify the mangrove species and inclusion of texture information in the classification increased the classification accuracy.

  5. Cryptogamic covers control spectral vegetation indices and their seasonal variation in dryland systems

    Science.gov (United States)

    Rodriguez-Caballero, Emilio; Knerr, Tanja; Büdel, Burkhard; Hill, Joachim; Weber, Bettina

    2016-04-01

    Remote sensing data provide spatially continuous information on vegetation dynamics by means of long-term series of vegetation indices (VI). However, most of these indices show problematic results in drylands, as a consequence of the scarce vegetation cover and the strong effect of the open space between plants. Open soil between plants as well as rock surfaces in dryland ecosystems are often covered by complex communities of cyanobacteria, algae, lichens and mosses. These cryptogamic covers show a faster phenological response to water pulses than vascular vegetation, turning green almost immediately after the first rain following a dry period and modifying their spectral response. However, only few studies quantified the effects of cryptogamic covers on VI, and none of them considered them in the analysis of temporal series of satellite images, where differences in physiology and reflectance between cryptogamic covers and vascular vegetation interact. For this reason, we quantified how cryptogamic covers modify the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), based on field and lab spectral measurements. For two different biocrust-dominated ecosystems within the South African Karoo, we analyzed the effect of biocrusts on spectrally analyzed vegetation dynamics using multi-temporal series of VI obtained from LANDSAT and MODIS images . Cryptogamic covers exerted a considerable effect on both NDVI and EVI calculated from field and lab spectra. As previously described for vegetation, also increasing cryptogam cover caused an increase of both VI values, and this effect also became apparent at LANDSAT image scale. However, the response of VI extracted from LANDSAT images upon environmental factors differed between pixels dominated by cryptogams and vascular vegetation. Whereas vegetation showed the highest changes in VI values in response to water availability and temperature, cryptogamic covers, which are the main surface

  6. Soil Line Influences on Two-Band Vegetation Indices and Vegetation Isolines: A Numerical Study

    Directory of Open Access Journals (Sweden)

    Alfredo R. Huete

    2010-02-01

    Full Text Available Influences of soil line variations on two-band vegetation indices (VIs and their vegetation isolines in red and near-infrared (NIR reflectance space are investigated based on recently derived relationships between the relative variations of VIs with variations of the soil line parameters in the accompanying paper by Yoshioka et al. [1]. The soil line influences are first demonstrated numerically in terms of variations of vegetation isolines and VI values along with the isolines. A hypothetical case is then analyzed by assuming the discrepancies between the general and regional soil lines for a Southern Brazil area reported elsewhere. The results indicate the validity of our analytical approach for the evaluation of soil line influences and the applicability for adjustment of VI errors using external data sources of soil reflectance spectra.

  7. Evaluation of satellite based indices for primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2008-07-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modelling within a water limited environment. Results show a strong correlation between EVI against gross primary production (GPP, demonstrating the significance of EVI for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modelling in similar semi-arid ecosystems is limited.

  8. Evaluation of satellite based indices for gross primary production estimates in a sparse savanna in the Sudan

    Directory of Open Access Journals (Sweden)

    M. Sjöström

    2009-01-01

    Full Text Available One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE approach. Satellite indices such as the Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI and the Shortwave Infrared Water Stress Index (SIWSI have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate NDVI, EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modeling within a water limited environment. Results show a strong correlation between vegetation indices and gross primary production (GPP, demonstrating the significance of vegetation indices for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modeling in similar semi-arid ecosystems is limited.

  9. 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.

  10. Toward the Estimation of Surface Soil Moisture Content Using Geostationary Satellite Data over Sparsely Vegetated Area

    Directory of Open Access Journals (Sweden)

    Pei Leng

    2015-04-01

    Full Text Available Based on a novel bare surface soil moisture (SSM retrieval model developed from the synergistic use of the diurnal cycles of land surface temperature (LST and net surface shortwave radiation (NSSR (Leng et al. 2014. “Bare Surface Soil Moisture Retrieval from the Synergistic Use of Optical and Thermal Infrared Data”. International Journal of Remote Sensing 35: 988–1003., this paper mainly investigated the model’s capability to estimate SSM using geostationary satellite observations over vegetated area. Results from the simulated data primarily indicated that the previous bare SSM retrieval model is capable of estimating SSM in the low vegetation cover condition with fractional vegetation cover (FVC ranging from 0 to 0.3. In total, the simulated data from the Common Land Model (CoLM on 151 cloud-free days at three FLUXNET sites that with different climate patterns were used to describe SSM estimates with different underlying surfaces. The results showed a strong correlation between the estimated SSM and the simulated values, with a mean Root Mean Square Error (RMSE of 0.028 m3·m−3 and a coefficient of determination (R2 of 0.869. Moreover, diurnal cycles of LST and NSSR derived from the Meteosat Second Generation (MSG satellite data on 59 cloud-free days were utilized to estimate SSM in the REMEDHUS soil moisture network (Spain. In particular, determination of the model coefficients synchronously using satellite observations and SSM measurements was explored in detail in the cases where meteorological data were not available. A preliminary validation was implemented to verify the MSG pixel average SSM in the REMEDHUS area with the average SSM calculated from the site measurements. The results revealed a significant R2 of 0.595 and an RMSE of 0.021 m3·m−3.

  11. [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.

  12. Use of satellite imagery to map and monitor vegetation in New Zealand

    OpenAIRE

    Stephens, P. R.; Dymond, J. R.; Brown, L J

    1995-01-01

    研究概要:Land resource and environmental decision makers require quantitative information on the spatial distribution of vegetation types and their condition, and changes in these over time. Such vegetation mapping and monitoring is often required to be undertaken quickly. Remotely-sensed satellite imagery, in conjunction with other data sources, have been used to satisfy this need. This paper describes the uses of satellite imagery by reference to three regional mapping projects in New Zealand. ...

  13. Derivation of Relationships between Spectral Vegetation Indices from Multiple Sensors Based on Vegetation Isolines

    Directory of Open Access Journals (Sweden)

    Kenta Obata

    2012-02-01

    Full Text Available An analytical form of relationship between spectral vegetation indices (VI is derived in the context of cross calibration and translation of vegetation index products from different sensors. The derivation has been carried out based on vegetation isoline equations that relate two reflectance values observed at different wavelength ranges often represented by spectral band passes. The derivation was first introduced and explained conceptually by assuming a general functional form for VI model equation. This process is universal by which two VIs of different sensors and/or different model equations can be related conceptually. The general process was then applied to the actual case of normalized difference vegetation index (NDVI from two sensors in a framework of inter-sensor continuity. The derivation results indicate that the NDVI from one sensor can be approximated by a rational function of NDVI from the other sensor as a parameter. Similar result was obtained for the case of soil adjusted VI, enhanced VI, and two-band variance of enhanced VI.

  14. 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

  15. 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.

  16. Sources of Divergence in Remote Sensing of Vegetation Phenology From Multiple Long Term Satellite Data Records

    Science.gov (United States)

    Barreto, A.; Didan, K.; Miura, T.

    2008-12-01

    Changes in vegetation phenology depict an integrated response to change in environmental factors and provide valuable information to global change research. Typically, remote sensing of vegetation phenology is based on the analysis of vegetation index temporal profiles, because of their simplicity, stability, and inherent resistant to noise. Most phenology estimates are, however, limited to using one sensor owing to the inter-sensor continuity challenges. Although, phenology is used for a variety of research and application topics, the central premise remains the study of vegetation dynamics change in response to change in climate and other factors. Consequently, the consistency and length of data records are key requirements. With satellite missions lasting few years only, long term phenology measures will have to be based on a mixture of satellite data records. In this study we compared phenology parameters from the AVHRR-GIMMS and MODIS NDVI records (1982- 2007). We analyzed both records globally using a cluster approach to abate noise and focus on the landscape level vegetation dynamic. The cluster approach, assumes that phenology is controlled by a complex set of factors that could be encapsulated by homogeneous climate, soil, elevational gradient, sun- shade exposure, and biophysical capacity. We applied this method to each of the sensors and examined three fundamental phenology parameters: the start and end of the growing season and the cumulative seasonal signal. These parameters are sensitive to, and are capable of capturing changes in the underlying environmental factors. Our results indicate that a large divergence exist over the dense forest of the tropics. This divergence was attributed to MODIS saturation rather than NDVI saturation. Boreal forests exhibited also large disagreement owing to snow cover and related differences in data processing. Furthermore, agricultural areas showed the most irregular phenological signals. This noise resulted from the

  17. 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.

  18. Derivation of Soil Line Influence on Two-Band Vegetation Indices and Vegetation Isolines

    Directory of Open Access Journals (Sweden)

    Hiroki Yoshioka

    2009-11-01

    Full Text Available This paper introduces derivations of soil line influences on two-band vegetation indices (VIs and vegetation isolines in the red and near infra-red reflectance space. Soil line variations are described as changes in the soil line parameters (slope and offset and the red reflectance of the soil surface. A general form of a VI model equation written as a ratio of two linear functions (e.g., NDVI and SAVI was assumed. It was found that relative VI variations can be approximated by a linear combination of the three soil parameters. The derived expressions imply the possibility of estimating and correcting for soil-induced bias errors in VIs and their derived biophysical parameters, caused by the assumption of a general soil line, through the use of external data sources such as regional soil maps.

  19. Use of Landsat land surface temperature and vegetation indices for monitoring drought in the Salt Lake Basin Area, Turkey.

    Science.gov (United States)

    Orhan, Osman; Ekercin, Semih; Dadaser-Celik, Filiz

    2014-01-01

    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.

  20. 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.

  1. Remote sensing-based vegetation indices for monitoring vegetation change in the semi-arid region of Sudan

    Science.gov (United States)

    R. A., Majdaldin; Osunmadewa, B. A.; Csaplovics, E.; Aralova, D.

    2016-10-01

    Land degradation, a phenomenon referring to (drought) in arid, semi-arid and dry sub-humid regions as a result of climatic variations and anthropogenic activities most especially in the semi-arid lands of Sudan, where vast majority of the rural population depend solely on agriculture and pasture for their daily livelihood, the ecological pattern had been greatly influenced thereby leading to loss of vegetation cover coupled with climatic variability and replacement of the natural tree composition with invasive mesquite species. The principal aim of this study is to quantitatively examine the vigour of vegetation in Sudan through different vegetation indices. The assessment was done based on indicators such as soil adjusted vegetation index (SAVI). Cloud free multi-spectral remotely sensed data from LANDSAT imagery for the dry season periods of 1984 and 2009 were used in this study. Results of this study shows conversion of vegetation to other land use type. In general, an increase in area covered by vegetation was observed from the NDVI results of 2009 which is a contrast of that of 1984. The results of the vegetation indices for NDVI in 1984 (vegetated area) showed that about 21% was covered by vegetation while 49% of the area were covered with vegetation in 2009. Similar increase in vegetated area were observed from the result of SAVI. The decrease in vegetation observed in 1984 is as a result of extensive drought period which affects vegetation productivity thereby accelerating expansion of bare surfaces and sand accumulation. Although, increase in vegetated area were observed from the result of this study, this increase has a negative impact as the natural vegetation are degraded due to human induced activities which gradually led to the replacement of the natural vegetation with invasive tree species. The results of the study shows that NDVI perform better than by SAVI.

  2. 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...

  3. Multisensor Comparisons for Validation of MODIS Vegetation Indices

    Institute of Scientific and Technical Information of China (English)

    CHENG Qian

    2006-01-01

    Vegetation indices (Ⅵ) are one of the standard science products available from the Moderate Resolution Imaging Spectroradiometer (MODIS). Validation of MODIS-Ⅵ products was an important prerequisite to using these variables for global modeling. In this study, validation of the MODIS-VI products including single-day MODIS, level 2 (gridded) daily MODIS surface reflectance (MOD09), 16-day composited MODIS (MOD13) was performed utilizing multisensor data from MODIS, Thematic Mapper (TM), and field radiometer, for a rice-planting region in southern China. The validation approach involved scaling up independent fine-grained datasets, including ground measurement and high spatial resolution imagery, to the coarser MODIS spatial resolutions. The 16-day composited MODIS reflectance and Ⅵ matched well with the ground measurement reflectance and Ⅵ. The Ⅵ of TM and MODIS were lower than the ground Ⅵ. The results demonstrated the accuracy, reliability, and utility of the MODIS-Ⅵ products for the study region.

  4. Automatic Extraction of Mangrove Vegetation from Optical Satellite Data

    Science.gov (United States)

    Agrawal, Mayank; Sushma Reddy, Devireddy; Prasad, Ram Chandra

    2016-06-01

    Mangrove, the intertidal halophytic vegetation, are one of the most significant and diverse ecosystem in the world. They protect the coast from sea erosion and other natural disasters like tsunami and cyclone. In view of their increased destruction and degradation in the current scenario, mapping of this vegetation is at priority. Globally researchers mapped mangrove vegetation using visual interpretation method or digital classification approaches or a combination of both (hybrid) approaches using varied spatial and spectral data sets. In the recent past techniques have been developed to extract these coastal vegetation automatically using varied algorithms. In the current study we tried to delineate mangrove vegetation using LISS III and Landsat 8 data sets for selected locations of Andaman and Nicobar islands. Towards this we made an attempt to use segmentation method, that characterize the mangrove vegetation based on their tone and the texture and the pixel based classification method, where the mangroves are identified based on their pixel values. The results obtained from the both approaches are validated using maps available for the region selected and obtained better accuracy with respect to their delineation. The main focus of this paper is simplicity of the methods and the availability of the data on which these methods are applied as these data (Landsat) are readily available for many regions. Our methods are very flexible and can be applied on any region.

  5. 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 Vegetation phenology refers to the timing of seasonal biological events (for example, bud burst, leaf unfolding, vegetation growth and leaf senescence) and biotic and abiotic forces that control these. Daily, coarse-resolution satellite imagery...

  6. Potential for early warning of maalria in India using NOAA-AVHRR based vegetation health indices

    Science.gov (United States)

    Dhiman, R. C.; Kogan, Felix; Singh, Neeru; Singh, R. P.; Dash, A. P.

    Malaria is still a major public health problem in India with about 1 82 million cases annually and 1000 deaths As per World Health Organization WHO estimates about 1 3 million Disability Adjusted Life Years DALYs are lost annually due to malaria in India Central peninsular region of India is prone to malaria outbreaks Meteorological parameters changes in ecological conditions development of resistance in mosquito vectors development of resistance in Plasmodium falciparum parasite and lack of surveillance are the likely reasons of outbreaks Based on satellite data and climatic factors efforts have been made to develop Early Warning System EWS in Africa but there is no headway in this regard in India In order to find out the potential of NOAA satellite AVHRR derived Vegetation Condition Index VCI Temperature Condition Index TCI and a cumulative indicator Vegetation Health Index VHI were attempted to find out their potential for development of EWS Studies were initiated by analysing epidemiological data of malaria vis-a-vis VCI TCI and VHI from Bikaner and Jaisalmer districts of Rajasthan and Tumkur and Raichur districts of Karnataka Correlation coefficients between VCI and monthly malaria cases for epidemic years were computed Positive correlation 0 67 has been found with one-month lag between VCI and malaria incidence in respect of Tumkur while a negative correlation with TCI -0 45 is observed In Bikaner VCI is found to be negatively related -0 71 with malaria cases in epidemic year of 1994 Weekly

  7. Drought and vegetation stress monitoring in Portugal using satellite data

    Directory of Open Access Journals (Sweden)

    C. Gouveia

    2009-02-01

    Full Text Available Remote sensed information on vegetation and soil moisture, namely the Normalised Difference Vegetation Index (NDVI and the Soil Water Index (SWI, is employed to monitor the spatial extent, severity and persistence of drought episodes over Continental Portugal, from 1999 to 2006. The severity of a given drought episode is assessed by evaluating the cumulative impact over time of drought conditions on vegetation. Special attention is given to the drought episodes that have occurred in the last decade, i.e., 1999, 2002 and particularly the major event of 2005. During both the 1999 and 2005 drought episodes negative anomalies of NDVI are observed over large sectors of Southern Portugal for up to nine months (out of eleven of the vegetative cycle. On the contrary, the 2002 event was characterized by negative anomalies in the northern half of Portugal and for a shorter period (eight out of eleven months. The impact of soil moisture on vegetation dynamics is evaluated by analyzing monthly anomalies of SWI and by studying the annual cycle of SWI vs. NDVI. While in the case of the drought episode of 1999 the scarcity of water in the soil persisted until spring, in the recent episode of 2005 the deficit in greenness was already apparent at the end of summer. The impact of dry periods on vegetation is clearly observed in both arable land and forest, and it is found that arable land presents a higher sensitivity. From an operational point of view, obtained results reveal the possibility of using the developed methodology to monitor, in quasi real-time, vegetation stress and droughts in Mediterranean ecosystems.

  8. Drought and vegetation stress monitoring in Portugal using satellite data

    Science.gov (United States)

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

    2009-02-01

    Remote sensed information on vegetation and soil moisture, namely the Normalised Difference Vegetation Index (NDVI) and the Soil Water Index (SWI), is employed to monitor the spatial extent, severity and persistence of drought episodes over Continental Portugal, from 1999 to 2006. The severity of a given drought episode is assessed by evaluating the cumulative impact over time of drought conditions on vegetation. Special attention is given to the drought episodes that have occurred in the last decade, i.e., 1999, 2002 and particularly the major event of 2005. During both the 1999 and 2005 drought episodes negative anomalies of NDVI are observed over large sectors of Southern Portugal for up to nine months (out of eleven) of the vegetative cycle. On the contrary, the 2002 event was characterized by negative anomalies in the northern half of Portugal and for a shorter period (eight out of eleven months). The impact of soil moisture on vegetation dynamics is evaluated by analyzing monthly anomalies of SWI and by studying the annual cycle of SWI vs. NDVI. While in the case of the drought episode of 1999 the scarcity of water in the soil persisted until spring, in the recent episode of 2005 the deficit in greenness was already apparent at the end of summer. The impact of dry periods on vegetation is clearly observed in both arable land and forest, and it is found that arable land presents a higher sensitivity. From an operational point of view, obtained results reveal the possibility of using the developed methodology to monitor, in quasi real-time, vegetation stress and droughts in Mediterranean ecosystems.

  9. 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

  10. [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

  11. Narrow band vegetation indices overcome the saturation problem in biomass estimation

    NARCIS (Netherlands)

    Mutanga, O.; Skidmore, A.K.

    2004-01-01

    Remotely sensed vegetation indices such as NDVI, computed using the red and near infrared bands have been used to estimate pasture biomass. These indices are of limited value since they saturate in dense vegetation. In this study, we evaluated the potential of narrow band vegetation indices for char

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

    OpenAIRE

    HASIRCI, Z.; Cavdar, I. H.; Ozturk, M

    2016-01-01

    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 ...

  13. Constrained projections of high northern latitudinal photosynthesis increase by satellite observations of vegetation greenness

    Science.gov (United States)

    Winkler, Alexander J.; Myneni, Ranga; Brovkin, Victor

    2017-04-01

    Satellite observations of the last three decades provide strong evidence that the Earth is greening. Especially in northern high latitudes, a substantial increase of the leaf area index (LAI), an indicator of greening, is observed. For these regions, it is assumed that plant growth benefits from higher temperature (radiative effect) and rising atmospheric CO2 concentration (CO2 fertilization effect). This greening trend, in terms of increasing LAI, is also simulated by various global ecosystem models. We also found a persistent greening trend analyzing historical simulations of Earth system models (ESM) participating in Phase 5 of the Coupled Model Intercomparison Project (CMIP5). However, a wide spread in magnitude of an associated increase of terrestrial gross primary production (GPP) among the ESMs is found, and thus contributes to pronounced uncertainties in projections of future climate change. Here we demonstrate that the tight correlation between enhanced GPP of high northern latitudinal ecosystems and their LAI sensitivity to both key environmental factors, temperature and CO2 concentration, opens up the possibility of an Emergent Constraint on plant photosynthesis. Combining this almost linear relationship across the ensemble of CMIP5 models with the LAI trends in the long-term satellite records, we are able to constrain projections of vegetation growth increase for respective ecosystems.

  14. Integration of vegetation indices into a water balance model to estimate evapotranspiration of wheat and corn

    Directory of Open Access Journals (Sweden)

    F. L. M. Padilla

    2010-10-01

    Full Text Available Vegetation indices (VIs have been traditionally used for quantitative monitoring of vegetation. Remotely sensed radiometric measurements of visible and infrared solar energy, which is reflected or emitted by plant canopies, can be used to obtain rapid, non-destructive estimates of certain canopy attributes and parameters. One parameter of special interest for water management applications, is the crop coefficient employed by the FAO-56 model to derive actual crop evapotranspiration (ET. The aim of this study was to evaluate a methodology that combines the basal crop coefficient derived from VIs with a daily soil water balance in the root zone to estimate daily evapotranspiration rates for corn and wheat crops at field scale. The ability of the model to trace water stress in these crops was also assessed. Vegetation indices were first retrieved from field hand-held radiometer measurements and then from Landsat 5 and 7 satellite images. The results of the model were validated using two independent measurement systems for ET and regular soil moisture monitoring, in order to evaluate the behavior of the soil and atmosphere components of the model. ET estimates were compared with latent heat flux measured by an eddy covariance system and with weighing lysimeter measurements. Average overestimates of daily ET of 8 and 11% were obtained for corn and wheat, respectively, with good agreement between the estimated and measured root-zone water deficit for both crops when field radiometry was employed. Satellite remote-sensing inputs overestimated ET by 4 to 9%, showing a non-significant lost of accuracy when the satellite sensor data replaced the field radiometry data. The model was also used to monitor the water stress during the 2009 growing season, detecting several periods of water stress in both crops. Some of these stresses occurred during stages like grain filling, when the water stress is know to have a negative effect on yield. This fact could

  15. Advantages of using satellite soil moisture estimates over precipitation products to assess regional vegetation water availability and activity

    Science.gov (United States)

    Chen, Tiexi

    2017-04-01

    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 receiving area in northeastern Australia during December 2008 to May 2009. In January 2009, monthly precipitation showed strong positive anomalies, which led to strong positive soil moisture anomalies. The precipitation anomalies disappeared within a month. In contrast, the soil moisture anomalies persisted for months. Positive anomalies of Normalized Difference Vegetation Index (NDVI) appeared in February, in response to water supply, and then persisted for several months. In addition to these temporal characteristics, the spatial patterns of NDVI anomalies were more similar to soil moisture patterns than to those of precipitation and land surface model output. The long memory of soil moisture mainly relates to the presence of clay-rich soils. Modeled soil moisture from four of five global land surface models failed to capture the memory length of soil moisture and all five models failed to present the influence of lateral inflow. This case study indicates that satellite-based soil moisture is a better predictor of vegetation water availability than precipitation in environments having a memory of several months and thus is able to persistently affect vegetation dynamics. These results illustrate the usefulness of satellite remotely sensed soil moisture in ecohydrology studies. This case study has the potential to be used as a benchmark for global land surface model evaluations. The advantages of using satellite remotely sensed soil moisture over gridded precipitation products are mainly expected in lateral-inflow and/or clay-rich regions worldwide.

  16. Estimation of Crop Gross Primary Production (GPP). 2; Do Scaled (MODIS) Vegetation Indices Improve Performance?

    Science.gov (United States)

    Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Zhang, Xiaoyang; Suyker, Andrew; Verma, Shashi; Shuai, Yanmin; Middleton, Elizabeth M.

    2015-01-01

    Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the

  17. MODIS/TERRA MOD13A3 Vegetation Indices Monthly L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  18. MODIS/AQUA MYD13A2 Vegetation Indices 16-Day L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  19. MODIS/AQUA MYD13A3 Vegetation Indices Monthly L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  20. MODIS/TERRA MOD13A2 Vegetation Indices 16-Day L3 Global 1km

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  1. MODIS/TERRA MOD13A1 Vegetation Indices 16-Day L3 Global 500m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  2. MODIS/AQUA MYD13Q1 Vegetation Indices 16-Day L3 Global 250m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  3. MODIS/AQUA MYD13A1 Vegetation Indices 16-Day L3 Global 500m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  4. MODIS/TERRA MOD13Q1 Vegetation Indices 16-Day L3 Global 250m

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  5. Soil moisture and evapotranspiration of wetlands vegetation habitats retrieved from satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Budzynska, M.; Kowalik, W.; Turlej, K.

    2010-08-01

    The research has been carried out in Biebrza Ramsar Convention test site situated in the N-E part of Poland. Data from optical and microwave satellite images have been analysed and compared to the detailed soil-vegetation ground truth measurements conducted during the satellite overpasses. Satellite data applied for the study include: ENVISAT.ASAR, ENVISAT.MERIS, ALOS.PALSAR, ALOS.AVNIR-2, ALOS.PRISM, TERRA.ASTER, and NOAA.AVHRR. Optical images have been used for classification of wetlands vegetation habitats and vegetation surface roughness expressed by LAI. Also, heat fluxes have been calculated using NOAA.AVHRR data and meteorological data. Microwave images have been used for the assessment of soil moisture. For each of the classified wetlands vegetation habitats the relationship between soil moisture and backscattering coefficient has been examined, and the best combination of microwave variables (wave length, incidence angle, polarization) has been used for mapping and monitoring of soil moisture. The results of this study give possibility to improve models of water cycle over wetlands ecosystems by adding information about soil moisture and surface heat fluxes derived from satellite images. Such information is very essential for better protection of the European sensitive wetland ecosystems. ENVISAT and ALOS images have been obtained from ESA for AO ID 122 and AOALO.3742 projects.

  6. Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2015-01-01

    Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).

  7. Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

    Science.gov (United States)

    Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

    2007-01-01

    An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

  8. Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

    Science.gov (United States)

    Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

    2007-01-01

    An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

  9. Analysis of the role of urban vegetation in local climate of Budapest using satellite measurements

    Science.gov (United States)

    Pongracz, Rita; Bartholy, Judit; Dezso, Zsuzsanna; Fricke, Cathy

    2016-08-01

    Urban areas significantly modify the natural environment due to the concentrated presence of humans and the associated anthropogenic activities. In order to assess this effect, it is essential to evaluate the relationship between urban and vegetated surface covers. In our study we focused on the Hungarian capital, Budapest, in which about 1.7 million inhabitants are living nowadays. The entire city is divided by the river Danube into the hilly, greener Buda side on the west, and the flat, more densely built-up Pest side on the east. Most of the extended urban vegetation, i.e., forests are located in the western Buda side. The effects of the past changing of these green areas are analyzed using surface temperature data calculated from satellite measurements in the infrared channels, and NDVI (Normalized Difference Vegetation Index) derived from visible and near-infrared satellite measurements. For this purpose, data available from sensor MODIS (Moderate Resolution Imaging Spectroradiometer) of NASA satellites (i.e., Terra and Aqua) are used. First, the climatological effects of forests on the urban heat island intensity are evaluated. Then, we also aim to evaluate the relationship of surface temperature and NDVI in this urban environment with special focus on vegetation-related sections of the city where the vegetation cover either increased or decreased remarkably.

  10. Satellite-scale Estimates of the "b Parameter" Relating Vegetation Water Content and SMOS Optical Thickness

    Science.gov (United States)

    Patton, J. C.; Hornbuckle, B. K.

    2013-12-01

    Microwave radiation emitted by Earth's land surface is primarily determined by soil moisture and vegetation. One of the effects of vegetation on surface microwave emissions is often termed the "vegetation optical thickness" or "vegetation opacity" and is often abbreviated as tau. Retrievals of soil moisture from microwave radiometer measurements requires knowledge of tau. The Soil Moisture and Ocean Salinity (SMOS) satellite measures microwave radiation at multiple incidence angles, enabling the simultaneous retrieval of soil moisture and tau. Other soil moisture satellites, such as the upcoming Soil Moisture Active Passive (SMAP) satellite, only measure at single incidence angles and may need auxiliary sources of tau data in order to retrieve soil moisture. One proposed method for estimating tau for these satellites is by relating reflectance data, e.g. the normalized difference vegetation index, to vegetation water content (VWC), then relating VWC to tau. VWC and tau can be related through the b parameter, i.e. tau = b x VWC. Values of b for different land cover types have been estimated from tower (~1 m) and airplane (~10-100 m) data, but have not been measured at the satellite scale (~10 km). Estimating b at the satellite scale from measurements at smaller scales is difficult because the effective value of b in a satellite pixel may not be well represented by linear weighted average based on the fraction of each land cover type in the pixel. However, by relating county crop yields, estimated by the USDA National Agricultural Statistics Service, to measurements of SMOS tau, and by using certain allometric relationships, such as the ratio of water to dry matter and the harvest index of crops, we can estimate b at the satellite scale. We have used this method to estimate b for each Iowa county for the years 2010-2012. Initial results suggest that b may change year to year; our current estimates for b in Iowa range from 0.065 in 2010 to 0.100 in 2012. These

  11. Performance of Vegetation Indices for Wheat Yield Forecasting for Punjab, Pakistan

    Science.gov (United States)

    Dempewolf, J.; Becker-Reshef, I.; Adusei, B.; Barker, B.

    2013-12-01

    Forecasting wheat yield in major producer countries early in the growing season allows better planning for harvest deficits and surplus with implications for food security, world market transactions, sustaining adequate grain stocks, policy making and other matters. Remote sensing imagery is well suited for yield forecasting over large areas. The Normalized Difference Vegetation Index (NDVI) has been the most-used spectral index derived from remote sensing imagery for assessing crop condition of major crops and forecasting crop yield. Many authors have found that the highest correlation between NDVI and yield of wheat crops occurs at the height of the growing season when NDVI values and photosynthetic activity of the wheat plants are at their relative maximum. At the same time NDVI saturates in very dense and vigorous (healthy, green) canopies such as wheat fields during the seasonal peak and shows significantly reduced sensitivity to further increases in photosynthetic activity. In this study we compare the performance of different vegetation indices derived from space-borne red and near-infrared spectral reflectance measurements for wheat yield forecasting in the Punjab Province, Pakistan. Areas covered by wheat crop each year were determined using a time series of MODIS 8-day composites at 250 m resolution converted to temporal metrics and classified using a bagged decision tree approach, driven by classified multi-temporal Landsat scenes. Within the wheat areas we analyze and compare wheat yield forecasts derived from three different satellite-based vegetation indices at the peak of the growing season. We regressed in turn NDVI, Wide Dynamic Range Vegetation Index (WDRVI) and the Vegetation Condition Index (VCI) from the four years preceding the wheat growing season 2011/12 against reported yield values and applied the regression equations to forecast wheat yield for the 2011/12 season per district for each of 36 Punjab districts. Yield forecasts overall

  12. Modeling vegetation reflectance from satellite and in-situ monitoring data

    Science.gov (United States)

    Zoran, Maria; Florin Zoran, Liviu; Ionescu Golovanov, Carmen; Dida, Adrian

    2010-05-01

    Vegetation can be distinguished using remote sensing data from most other (mainly inorganic) materials by virtue of its notable absorption in the red and blue segments of the visible spectrum, its higher green reflectance and, especially, its very strong reflectance in the near-IR. Different types of vegetation show often distinctive variability from one another owing to such parameters as leaf shape and size, overall plant shape, water content, and associated background (e.g., soil types and spacing of the plants (density of vegetative cover within the scene). Different three-dimensional numerical models explicitly represent the vegetation canopy and use numerical methods to calculate reflectance. These models are computationally intensive and are therefore not generally suited to the correction of satellite imagery containing millions of pixels. Physically based models do provide understanding and are potentially more robust in extrapolation. They consider the vegetation canopy to comprise thin layers of leaves, suspended in air like sediment particles in water forming a turbid medium. Monitoring of vegetation cover changes by remote sensing data is one of the most important applications of satellite imagery. Vegetation reflectance has variations with sun zenith angle, view zenith angle, and terrain slope angle. To provide corrections of these effects, for visible and near-infrared light, was used a three parameters model and developed a simple physical model of vegetation reflectance, by assuming homogeneous and closed vegetation canopy with randomly oriented leaves. Multiple scattering theory was used to extend the model to function for both near-infrared and visible light. This vegetation reflectance model may be used to correct satellite imagery for bidirectional and topographic effects. For two ASTER images over Cernica forested area, placed to the East of Bucharest town , Romania, acquired within minutes from one another ,a nadir and off-nadir for band 3

  13. Estimation of arsenic in agricultural soils using hyperspectral vegetation indices of rice.

    Science.gov (United States)

    Shi, Tiezhu; Liu, Huizeng; Chen, Yiyun; Wang, Junjie; Wu, Guofeng

    2016-05-05

    This study systematically analyzed the performance of multivariate hyperspectral vegetation indices of rice (Oryza sativa L.) in estimating the arsenic content in agricultural soils. Field canopy reflectance spectra was obtained in the jointing-booting growth stage of rice. Newly developed and published multivariate vegetation indices were initially calculated to estimate soil arsenic content. The well-performing vegetation indices were then selected using successive projections algorithm (SPA), and the SPA selected vegetation indices were adopted to calibrate a multiple linear regression model for estimating soil arsenic content. Results showed that a three-band vegetation index (R716-R568)/(R552-R568) performed best in the newly developed vegetation indices in estimating soil arsenic content. The photochemical reflectance index (PRI) and red edge position (REP) performed well in the published vegetation indices. Moreover, the linear combination of two vegetation indices ((R716-R568)/(R552-R568) and REP) selected using SPA improved the estimation of soil arsenic content. These results indicated that the newly developed three-band vegetation index (R716-R568)/(R552-R568) might be recommended as an indicator for estimating soil arsenic content in the study area. PRI and REP could be used as universal vegetation indices for monitoring soil arsenic contamination.

  14. Radar vegetation indices for estimating the vegetation water content of rice and soybean

    Science.gov (United States)

    Vegetation water content (VWC) is an important biophysical parameter and has a significant role in the retrieval of soil moisture using microwave remote sensing. In this study, the Radar Vegetation Index (RVI) was evaluated for estimating VWC. Analysis utilized a data set obtained using a ground-bas...

  15. Estimating potato leaf chlorophyll content using ratio vegetation indices

    NARCIS (Netherlands)

    Kooistra, Lammert; Clevers, Jan G.P.W.

    2016-01-01

    Chlorophyll content at leaf level is an important variable because of its crucial role in photosynthesis and in understanding plant functioning. In this study, we tested the hypothesis that the ratio of a vegetation index (VI) for estimating canopy chlorophyll content (CCC) and one for estimating le

  16. Time series of vegetation indices and the modifiable temporal unit problem

    Directory of Open Access Journals (Sweden)

    R. de Jong

    2011-08-01

    Full Text Available Time series of vegetation indices (VI derived from satellite imagery provide a consistent monitoring system for terrestrial plant systems. They enable detection and quantification of gradual changes within the time frame covered, which are of crucial importance in global change studies, for example. However, VI time series typically contain a strong seasonal signal which complicates change detection. Commonly, trends are quantified using linear regression methods, while the effect of serial autocorrelation is remediated by temporal aggregation over bins having a fixed width. Aggregating the data in this way produces temporal units which are modifiable. Analogous to the well-known Modifiable Area Unit Problem (MAUP, the way in which these temporal units are defined may influence the fitted model parameters and therefore the amount of change detected. This paper illustrates the effect of this Modifiable Temporal Unit Problem (MTUP on a synthetic data set and a real VI data set. Large variation in detected changes was found for aggregation over bins that mismatched full lengths of vegetative cycles, which demonstrates that aperiodicity in the data may influence model results. Using 26 yr of VI data and aggregation over full-length periods, deviations in VI gains of less than 1 % were found for annual periods, while deviations (with respect to seasonally adjusted data increased up to 24 % for aggregation windows of 5 yr. This demonstrates that temporal aggregation needs to be carried out with care in order to avoid spurious model results.

  17. 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.

  18. Mutual influence between climate and vegetation cover through satellite data in Egypt

    Science.gov (United States)

    El-Shirbeny, Mohammed A.; Aboelghar, Mohamed A.; Arafat, Sayed M.; El-Gindy, Abdel-Ghany M.

    2011-11-01

    The effect of vegetation cover on climatic change has not yet observed in Egypt. In the current study, Ismailia Governorate was selected as a case study to assess the impact of the vegetation cover expansion on both land surface and air temperature during twenty-eight years from 1983 to 2010. This observation site was carefully selected as a clear example for the highly rate of reclamation and vegetation expansion process in Egypt. Land Surface Temperature (LST) that were extracted from NOAA/AVHRR satellite data and air temperature (Tair) data that were collected from ground stations, were correlated with the expansion of vegetation cover that was delineated using Landsat TM and Landsat ETM+ data. The result showed that (LST) decreased by about 2.3°C while (Tair) decreased by about 1.6°C with the expansion of the cultivated land during twenty-eight years.

  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. Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

    Science.gov (United States)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  1. Spatial-temporal variations of vegetation and drought severity across Tharparkar, Pakistan, using remote sensing-derived indices

    Science.gov (United States)

    Shah, Sami Ullah; Iqbal, Javed

    2016-07-01

    Tharparkar is an arid region in the southeastern province of Sindh, Pakistan, and experienced drought as a regular phenomenon in the past. The complex nature of drought and sparsely located network of met stations handicapped reliable spatial and temporal analysis of drought severity across Tharparkar. Freely available tropical rainfall measuring mission rainfall satellite data and moderate-resolution imaging spectroradiometer normalized difference vegetation index (NDVI) satellite data fulfilled this gap and were used to generate drought indices. Commonly used NDVI and NDVI anomalies pose problems when compared with standardized meteorological drought indices such as standardized precipitation index (SPI) and standardized precipitation and evapotranspiration index (SPEI) for drought characterization. This study compared standardized vegetation index (SVI) with traditionally used, i.e., SPI and SPEI, for modeling drought severity in the arid and fragile agro-ecosystem of Tharparkar. SVI significantly correlated with standardized meteorological drought indices (SPI and SPEI) and revealed vegetation dynamics under rainfall and temperature variations. Weighted overlay analysis in geographical information systems depicted an accurate onset of the 2014 drought. This study provides useful information for drought characterization that can be used for drought monitoring and early warning systems in data scarce, arid, and semiarid regions.

  2. Vegetation Index and Phenology (VIP) Vegetation Indices 15Days Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  3. Vegetation Index and Phenology (VIP) Vegetation Indices Daily Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

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

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The NASA MEaSUREs Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer...

  6. 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

  7. 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.; Gu, L.; Marchesini, L. Belelli

    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

  8. Trends in a satellite-derived vegetation index and environmental variables in a restored brackish lagoon

    Directory of Open Access Journals (Sweden)

    Ji Yoon Kim

    2015-07-01

    Full Text Available We evaluated relative influence of climatic variables on the plant productivity after lagoon restoration. Chilika Lagoon, the largest brackish lake ecosystem in East Asia, experienced severe problems such as excessive dominance of freshwater exotic plants and rapid debasement of biodiversity associated with decreased hydrologic connectivity between the lagoon and the ocean. To halt the degradation of the lagoon ecosystem, the Chilika Development Authority implemented a restoration project, creating a new channel to penetrate the barrier beach of the lagoon. Using a satellite-derived normalized difference vegetation index (NDVI dataset, we compared the trend of vegetation changes after the lagoon restoration, from April 1998 to May 2014. The time series of NDVI data were decomposed into trend, seasonal, and random components using a local regression method. The results were visualized to understand the traits of spatial distribution in the lagoon. The NDVI trend, indicative of primary productivity, decreased rapidly during the restoration period, and gradually increased (slope coefficient: 2.1×10−4, p<0.05 after two years of restoration. Level of seawater exchange had more influences on plant productivity than local precipitation in the restored lagoon. Higher El Niño/Southern Oscillation increased sea level pressure, and caused intrusion of seawater into the lagoon, and the subsequently elevated salinity decreased the annual mean NDVI. Our findings suggest that lagoon restoration plans for enhancing interconnectivity with the ocean should consider oceanographic effects due to meteorological forcing, and long-term NDVI results can be used as a valuable index for adaptive management of the restoration site.

  9. Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

    Science.gov (United States)

    Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

    2014-05-01

    Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil

  10. Application of Vegetation Indices to Estimate Acorn Production at Iberian Peninsula

    Science.gov (United States)

    Escribano, Juan A.; Díaz-Ambrona, Carlos G. H.; Recuero, Laura; Huesca, Margarita; Cicuendez, Victor; Palacios, Alicia; Tarquis, Ana M.

    2014-05-01

    The Iberian pig valued natural resources of the pasture when fattened in mountain. The variability of acorn production is not contained in any line of Spanish agricultural insurance. However, the production of arable pasture is covered by line insurance number 133 for loss of pasture compensation. This scenario is only contemplated for breeding cows and brave bulls, sheep, goats and horses, although pigs are not included. This insurance is established by monitoring ten-day composites Normalized Difference Vegetation Index (NDVI) measured by satellite over treeless pastures, using MODIS TERRA satellite. The aim of this work is to check if we can use a satellite vegetation index to estimate the production of acorns. In order to do so, two Spanish grassland locations have been analyzed: regions of Olivenza (Jerez-Oliva) and Merida (Badajoz). The acorns production was evaluated through 2002-2005 gauging conducted by the Grupo Habitat de la Orden (Badajoz). Medium resolution (500x500 m2) MODIS images were used during the same time period to estimate the ten-day composites NDVI at these locations. Finally, meteorological data was obtained from SIAR and MAGRAMA network stations, calculating the ten-day averaged temperature and ten day accumulated precipitation. Considering two accumulated factors, NDVI and temperature, three phenological stages were well defined being the second one which pointed differences among campaigns. Then, accumulated precipitation versus accumulated NDVI was plot for this second phenological stage obtaining maximum differences at 300 mm of cumulative rainfall. Analyzing acorn production with accumulated NDVI in that moment a production function was obtained with a correlation coefficient of 0.71. These results will be discussed in detail. References J.A. Escribano, C.G.H. Diaz-Ambrona, L. Recuero, M. Huesca, V. Cicuendez, A. Palacios-Orueta y A.M. Tarquis. Aplicacion de Indices de Vegetacion para evaluar la falta de produccion de pastos y

  11. Using Small Drone (UAS) Imagery to Bridge the Gap Between Field- and Satellite-Based Measurements of Vegetation Structure and Change

    Science.gov (United States)

    Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.

    2016-12-01

    Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.

  12. 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

  13. Climate Change Impacts and Vulnerabilities Assessment on Forest Vegetation Through Time-Series Multisensor Satellite Data

    Science.gov (United States)

    Zoran, Maria; Savastru, Dan; Dida, Adrian

    2016-08-01

    Sustaining forest resources in Romania requires a better understanding of forest ecosystem processes, and how management decisions and climate and anthropogenic change may affect these processes in the future. Spatio- temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI LAI satellite images over 2000 - 2015 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from MODIS Terra/Aqua, LANDSAT TM/ETM and Sentinel satellite and meteorological data. For investigated test area, considerable NDVI decline was observed for drought events during 2003, 2007 and 2010 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. EO-based estimates of forest biophysical variables were shown to be similar to predictions derived from forest field inventories.

  14. Evapotranspiration estimation using a normalized difference vegetation index transformation of satellite data

    Science.gov (United States)

    Seevers, P.M.; Ottmann, R. W.

    1994-01-01

    Evapotranspiration of irrigated crops on two irrigation service areas along the lower Colorado River was estimated using a normalized difference vegetation index of satellite data. A procedure was developed which equated the index to crop coefficients. Evapotranspiration estimates for fields for three dates of thematic mapper data were highly correlated with ground estimates. Service area estimates using thematic mapper and Advanced Very High Resolution Radiometer data agreed well with estimates based on US Geological Survey gauging station data.

  15. 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.

  16. Evaluation of vegetation indices for rangeland biomass estimation in the Kimberley area of Western Australia

    NARCIS (Netherlands)

    Mundava, C.; Helmholtz, P.; Schut, A.G.T.; Corner, R.; McAtee, B.; Lamb, D.W.

    2014-01-01

    The objective of this paper is to test the relationships between Above Ground Biomass (AGB) and remotely sensed vegetation indices for AGB assessments in the Kimberley area in Western Australia. For 19 different sites, vegetation indices were derived from eight Landsat ETM+ scenes over a period of t

  17. A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations

    Directory of Open Access Journals (Sweden)

    Markus Enenkel

    2016-04-01

    Full Text Available Governments, aid organizations and researchers are struggling with the complexity of detecting and monitoring drought events, which leads to weaknesses regarding the translation of early warnings into action. Embedded in an advanced decision-support framework for Doctors without Borders (Médecins sans Frontières, this study focuses on identifying the added-value of combining different satellite-derived datasets for drought monitoring and forecasting in Ethiopia. The core of the study is the improvement of an existing drought index via methodical adaptations and the integration of various satellite-derived datasets. The resulting Enhanced Combined Drought Index (ECDI links four input datasets (rainfall, soil moisture, land surface temperature and vegetation status. The respective weight of each input dataset is calculated for every grid point at a spatial resolution of 0.25 degrees (roughly 28 kilometers. In the case of data gaps in one input dataset, the weights are automatically redistributed to other available variables. Ranking the years 1992 to 2014 according to the ECDI-based warning levels allows for the identification of all large-scale drought events in Ethiopia. Our results also indicate a good match between the ECDI-based drought warning levels and reported drought impacts for both the start and the end of the season.

  18. An Optical Sensor Network for Vegetation Phenology Monitoring and Satellite Data Calibration

    Directory of Open Access Journals (Sweden)

    Michal Heliasz

    2011-08-01

    Full Text Available 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 in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-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 and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity.

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

    Science.gov (United States)

    Eklundh, Lars; Jin, Hongxiao; Schubert, Per; Guzinski, Radoslaw; Heliasz, Michal

    2011-01-01

    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 in coniferous forests, one in a deciduous forest, and two on peatland. The instrumentation consists of dual-beam sensors measuring incoming and reflected red, green, NIR, and PAR fluxes at 10-min intervals, year-round. The sensors are mounted on separate masts or in flux towers in order to capture radiation reflected from within the flux footprint of current eddy covariance measurements. Our computations and model simulations demonstrate the validity of using off-nadir sampling, and we show the results from the first year of measurement. NDVI is computed and compared to that of the MODIS instrument on-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 and vegetation development. Valuable information about PAR absorption of ground and canopy is obtained that may be linked to vegetation productivity.

  20. [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.

  1. High resolution mapping of Normalized Difference Vegetation Indices (NDVI) of biological soil crusts

    Science.gov (United States)

    Fischer, T.; Veste, M.; Eisele, A.; Bens, O.; Spyra, W.; Hüttl, R. F.

    2012-04-01

    Normalized Difference Vegetation Indices (NDVI) are typically determined using satellite or airborne remote sensing, or field portable spectrometers, which give an averaged signal on centimetre to meter scale plots. Biological soil crust (BSC) patches may have smaller sizes, and ecophysiological, hydrological as well as pedological processes may be heterogeneously distributed within this level of resolution. A ground-based NDVI imaging procedure using low-cost equipment (Olympus Camedia 5000z digital camera equipped with a Hoya R72 infrared filter) was developed in this study to fill this gap at the level of field research, where carrying costly and bulky equipment to remote locations is often the limiting factor for data collection. A commercially available colour rendition chart (GretagMacbeth ColorChecker®) with known red (600-700 nm) and NIR (800-900 nm) reflectances was placed into each scene and used for calibration purposes on a per-image basis. Generation of NDVI images involved (i) determination of red and NIR reflectances from the pixel values of the red and NIR channels, respectively, and (ii) calculation and imaging of the NDVI, where NDVI values of -1 to +1 were mapped to grey values of 0 to 255. The correlation between NDVI values retrieved from these images and NDVI values determined using conventional field spectrometry (ASD FieldSpec 3 portable spectroradiometer) was close (r2 =0.91), the 95% confidence interval amounted to 0.10 NDVI units. The pixel resolution was 0.8 mm in the field and 0.2 mm in the laboratory, but can still be improved significantly with closer distance to the crust or with higher camera resolution. Geostatistical analysis revealed that both spatial variability as well as size of individual objects characterized by the NDVI increased with crust development. The latter never exceeded 4 mm in the investigated crusts, which points to the necessity of high resolution imaging for linking remote sensing with ecophysiology

  2. Application of advanced very high resolution radiometer (AVHRR)-based vegetation health indices for estimation of malaria cases.

    Science.gov (United States)

    Rahman, Atiqur; Krakauer, Nir; Roytman, Leonid; Goldberg, Mitch; Kogan, Felix

    2010-06-01

    Satellite data may be used to map climatic conditions conducive to malaria outbreaks, assisting in the targeting of public health interventions to mitigate the worldwide increase in incidence of the mosquito-transmitted disease. This work analyzes correlation between malaria cases and vegetation health (VH) indices derived from satellite remote sensing for each week over a period of 14 years for Bandarban, Bangladesh. Correlation analysis showed that years with a high summer temperature condition index (TCI) tended to be those with high malaria incidence. Principal components regression was performed on patterns of weekly TCI during each of the two annual malaria seasons to construct a model as a function of the TCI. These models reduced the malaria estimation error variance by 57% if first-peak (June-July) TCI was used as the estimator and 74% if second-peak (August-September) was used, compared with an estimation of average number of malaria cases for each year.

  3. 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.

  4. MODIS/AQUA MYD13A3 Vegetation Indices Monthly L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  5. MODIS/AQUA MYD13A2 Vegetation Indices 16-Day L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  6. MODIS/TERRA MOD13C2 Vegetation Indices Monthly L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  7. MODIS/AQUA MYD13C2 Vegetation Indices Monthly L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  8. MODIS/TERRA MOD13Q1 Vegetation Indices 16-Day L3 Global 250m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  9. MODIS/AQUA MYD13Q1 Vegetation Indices 16-Day L3 Global 250m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  10. MODIS/AQUA MYD13A1 Vegetation Indices 16-Day L3 Global 500m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  11. MODIS/TERRA MOD13A1 Vegetation Indices 16-Day L3 Global 500m Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  12. MODIS/TERRA MOD13A2 Vegetation Indices 16-Day L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  13. MODIS/TERRA MOD13A3 Vegetation Indices Monthly L3 Global 1km Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  14. A Weekly Indicator of Surface Moisture Status from Satellite Data for Operational Monitoring of Crop Conditions

    Directory of Open Access Journals (Sweden)

    Francesco Nutini

    2017-06-01

    Full Text Available The triangle method has been applied to derive a weekly indicator of evaporative fraction on vegetated areas in a temperate region in Northern Italy. Daily MODIS Aqua Land Surface Temperature (MYD11A1 data has been combined with air temperature maps and 8-day composite MODIS NDVI (MOD13Q1/MYD13Q1 data to estimate the Evaporative Fraction (EF at 1 km resolution, on a daily basis. Measurements at two eddy covariance towers located within the study area have been exploited to assess the reliability of satellite based EF estimations as well as the robustness of input data. Weekly syntheses of the daily EF indicator (EFw were then derived at regional scale for the years 2010, 2011 and 2012 as a proxy of overall surface moisture condition. EFw showed a temporal behavior consistent with growing cycles and agro-practices of the main crops cultivated in the study area (rice, forages and corn. Comparison with official regional corn yield data showed that variations in EFw cumulated over summer are related with crop production shortages induced by water scarcity. These results suggest that weekly-averaged EF estimated from MODIS data is sensible to water stress conditions and can be used as an indicator of crops’ moisture conditions at agronomical district level. Advantages and disadvantages of the proposed approach to provide information useful to issue operational near real time bulletins on crop conditions at regional scale are discussed.

  15. 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

    Impervious surfaces (IS) are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy...... 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

  16. 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

  17. How well do we characterize the biophysical effects of vegetation cover change? Benchmarking land surface models against satellite observations.

    Science.gov (United States)

    Duveiller, Gregory; Forzieri, Giovanni; Robertson, Eddy; Georgievski, Goran; Li, Wei; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

    2017-04-01

    Changes in vegetation cover can affect the climate by altering the carbon, water and energy cycles. The main tools to characterize such land-climate interactions for both the past and future are land surface models (LSMs) that can be embedded in larger Earth System models (ESMs). While such models have long been used to characterize the biogeochemical effects of vegetation cover change, their capacity to model biophysical effects accurately across the globe remains unclear due to the complexity of the phenomena. The result of competing biophysical processes on the surface energy balance varies spatially and seasonally, and can lead to warming or cooling depending on the specific vegetation change and on the background climate (e.g. presence of snow or soil moisture). Here we present a global scale benchmarking exercise of four of the most commonly used LSMs (JULES, ORCHIDEE, JSBACH and CLM) against a dedicated dataset of satellite observations. To facilitate the understanding of the causes that lead to discrepancies between simulated and observed data, we focus on pure transitions amongst major plant functional types (PFTs): from different tree types (evergreen broadleaf trees, deciduous broadleaf trees and needleleaf trees) to either grasslands or crops. From the modelling perspective, this entails generating a separate simulation for each PFT in which all 1° by 1° grid cells are uniformly covered with that PFT, and then analysing the differences amongst them in terms of resulting biophysical variables (e.g net radiation, latent and sensible heat). From the satellite perspective, the effect of pure transitions is obtained by unmixing the signal of different 0.05° spatial resolution MODIS products (albedo, latent heat, upwelling longwave radiation) over a local moving window using PFT maps derived from the ESA Climate Change Initiative land cover map. After aggregating to a common spatial support, the observation and model-driven datasets are confronted and

  18. From Satellite Imagery to Peatland Vegetation Diversity: How Reliable Are Habitat Maps?

    Directory of Open Access Journals (Sweden)

    Monique F. Poulin

    2002-12-01

    Full Text Available Although satellite imagery is becoming a basic component of the work of ecologists and conservationists, its potential and reliability are still relatively unknown for a large number of ecosystems. Using Landsat 7/ETM+ (Enhanced Thematic Mapper Plus data, we tested the accuracy of two types of supervised classifications for mapping 13 peatland habitats in southern Quebec, Canada. Before classifying peatland habitats, we applied a mask procedure that revealed 629 peatlands covering a total of 18,103 ha; 26% of them were larger than 20 ha. We applied both a simple maximum likelihood (ML function and a weighted maximum likelihood (WML function that took into account the proportion of each habitat class within each peatland when classifying the habitats on the image. By validating 626 Global Positioning System locations within 92 peatlands, we showed that both classification procedures provided an accurate representation of the 13 peatland habitat classes. For all habitat classes except lawn with pools, the predominant classified habitat within 45 m of the center of the validation location was of the same type as the one observed in the field. There were differences in the performance of the two classification procedures: ML was a better tool for mapping rare habitats, whereas WML favored the most common habitats. Based on ordinations, peatland habitat classes were as effective as environmental variables such as humidity indicators and water chemistry components at explaining the distribution of plant species and performed 1.6 times better when it came to accounting for vegetation structure patterns. Peatland habitats with pools had the most distinct plant assemblages, and the habitats dominated by herbs were moderately distinct from those characterized by ericaceous shrubs. Habitats dominated by herbs were the most variable in terms of plant species assemblages. Because peatlands are economically valuable wetlands, the maps resulting from the new

  19. Evaluation of Radar Vegetation Indices for Vegetation Water Content Estimation Using Data from a Ground-Based SMAP Simulator

    Science.gov (United States)

    Srivastava, Prashant K.; O'Neill, Peggy; Cosh, Michael; Lang, Roger; Joseph, Alicia

    2015-01-01

    Vegetation water content (VWC) is an important component of microwave soil moisture retrieval algorithms. This paper aims to estimate VWC using L band active and passive radar/radiometer datasets obtained from a NASA ground-based Soil Moisture Active Passive (SMAP) simulator known as ComRAD (Combined Radar/Radiometer). Several approaches to derive vegetation information from radar and radiometer data such as HH, HV, VV, Microwave Polarization Difference Index (MPDI), HH/VV ratio, HV/(HH+VV), HV/(HH+HV+VV) and Radar Vegetation Index (RVI) are tested for VWC estimation through a generalized linear model (GLM). The overall analysis indicates that HV radar backscattering could be used for VWC content estimation with highest performance followed by HH, VV, MPDI, RVI, and other ratios.

  20. Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

    Science.gov (United States)

    Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

    2017-01-01

    This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

  1. Impacts of Snow Cover on Vegetation Phenology in the Arctic from Satellite Data

    Institute of Scientific and Technical Information of China (English)

    ZENG Heqing; JIA Gensuo

    2013-01-01

    The dynamics of snow cover is considered an essential factor in phenological changes in Arctic tundra and other northern biomes.The Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra satellite data were selected to monitor the spatial and temporal heterogeneity of vegetation phenology and the timing of snow cover in western Arctic Russia (the Yamal Peninsula) during the period 2000-10.The magnitude of changes in vegetation phenology and the timing of snow cover were highly heterogeneous across latitudinal gradients and vegetation types in western Arctic Russia.There were identical latitudinal gradients for "start of season" (SOS) (r2 =0.982,p<0.0001),"end of season" (EOS) (r2 =0.938,p<0.0001),and "last day of snow cover" (LSC) (r2 =0.984,p<0.0001),while slightly weaker relationships between latitudinal gradients and "first day of snow cover" (FSC) were observed (r2 =0.48,p<0.0042).Delayed SOS and FSC,and advanced EOS and LSC were found in the south of the region,while there were completely different shifts in the north.SOS for the various land cover features responded to snow cover differently,while EOS among different vegetation types responded to snowfall almost the same.The timing of snow cover is likely a key driving factor behind the dynamics of vegetation phenology over the Arctic tundra.The present study suggests that snow cover urgently needs more attention to advance understanding of vegetation phenology in the future.

  2. Long-Term Satellite Detection of Post-Fire Vegetation Trends in Boreal Forests of China

    Directory of Open Access Journals (Sweden)

    Kunpeng Yi

    2013-12-01

    Full Text Available This paper describes the long-term effects on vegetation following the catastrophic fire in 1987 on the northern Great Xing’an Mountain by analyzing the AVHRR GIMMS 15-day composite normalized difference vegetation index (NDVI dataset. Both temporal and spatial characteristics were analyzed for natural regeneration and tree planting scenarios from 1984 to 2006. Regressing post-fire NDVI values on the pre-fire values helped identify the NDVI for burnt pixels in vegetation stands. Stand differences in fire damage were classified into five levels: Very High (VH, High (H, Moderate (M, Low (L and Slight (S. Furthermore, intra-annual and inter-annual post-fire vegetation recovery trajectories were analyzed by deriving a time series of NDVI and relative regrowth index (RRI values for the entire burned area. Finally, spatial pattern and trend analyses were conducted using the pixel-based post-fire annual stands regrowth index (SRI with a nonparametric Mann-Kendall (MK statistics method. The results show that October was a better period compared to other months for distinguishing the post- and pre-fire vegetation conditions using the NDVI signals in boreal forests of China because colored leaves on grasses and shrubs fall down, while the leaves on healthy trees remain green in October. The MK statistics method is robustly capable of detecting vegetation trends in a relatively long time series. Because tree planting primarily occurred in the severely burned area (approximately equal to the Medium, High and Very High fire damage areas following the Daxing’anling fire in 1987, the severely burned area exhibited a better recovery trend than the lightly burned regions. Reasonable tree planting can substantially quicken the recovery and shorten the restoration time of the target species. More detailed satellite analyses and field data will be required in the future for a more convincing validation of the results.

  3. 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

  4. Soil TPH concentration estimation using vegetation indices in an oil polluted area of eastern China

    National Research Council Canada - National Science Library

    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

    ... (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...

  5. Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis

    Science.gov (United States)

    Choudhury, Bhaskar J.

    1987-01-01

    A two-stream approximation to the radiative-transfer equation is used to calculate the vegetation indices (simple ratio and normalized difference), the fraction of incident photosynthetically active radiation (PAR) absorbed by the canopy, and the daily mean canopy net photosynthesis under clear-sky conditions. The model calculations are tested against field observations over wheat, cotton, corn, and soybean. The relationships between the vegetation indices and radiation absorption or net photosynthesis are generally found to be curvilinear, and changes in the soil reflectance affected these relationships. The curvilinearity of the relationship between normalized differences and PAR absorption decreases as the magnitude of soil reflectance increases. The vegetation indices might provide the fractional radiation absorption with some a priori knowledge about soil reflectance. The relationship between the vegetation indices and net photosynthesis must be distinguished for C3 and C4 crops. Effects of spatial heterogeneity are discussed.

  6. Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis

    Science.gov (United States)

    Choudhury, Bhaskar J.

    1987-01-01

    A two-stream approximation to the radiative-transfer equation is used to calculate the vegetation indices (simple ratio and normalized difference), the fraction of incident photosynthetically active radiation (PAR) absorbed by the canopy, and the daily mean canopy net photosynthesis under clear-sky conditions. The model calculations are tested against field observations over wheat, cotton, corn, and soybean. The relationships between the vegetation indices and radiation absorption or net photosynthesis are generally found to be curvilinear, and changes in the soil reflectance affected these relationships. The curvilinearity of the relationship between normalized differences and PAR absorption decreases as the magnitude of soil reflectance increases. The vegetation indices might provide the fractional radiation absorption with some a priori knowledge about soil reflectance. The relationship between the vegetation indices and net photosynthesis must be distinguished for C3 and C4 crops. Effects of spatial heterogeneity are discussed.

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

    Directory of Open Access Journals (Sweden)

    N. Andela

    2013-05-01

    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 use 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 seems 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, bringing new insights on vegetation dynamics.

  8. 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.

  9. 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

  10. Spatio-temporal features of vegetation restoration and variation after the Wenchuan earthquake with satellite images

    Science.gov (United States)

    Peng, Hou; Qiao, Wang; Yipeng, Yang; Weiguo, Jiang; Bingfeng, Yang; Qiang, Chen; Lihua, Yuan; Fanming, Kong; Xi, Chen; Guanjie, Wang

    2014-01-01

    The Wenchuan earthquake was a deadly earthquake that occurred on May 12, 2008, in Sichuan province of China. With the help of classic statistic methods, including arithmetic mean, standard deviation and linear trend estimation, vegetation restoration was recognized by analyzing spatio-temporal features of normalized difference vegetation index (NDVI) before and after this earthquake. Results indicate: (1) spatial distribution of NDVI mean values remains similar from 1998 to 2011. Higher values are mainly found in north, whereas lower values are mainly distributed over southeast, which is in good correlation with elevation and landform. Vegetation damage is at different levels in different seismic intensity (SI) regions: the higher SI is, the worse vegetation damage is. (2) Over the whole region, standard deviation is bigger after earthquake than before. Both absolute and relative changes in ecosystem stability increase with increasing SI. In different counties, variation of ecosystem stability is more obvious after earthquake, increase of standard deviation is approximately 6.5 times. Relatively, vegetation regionalization is the smallest analysis unit. Consequently, changes resulting from earthquake are unobvious. (3) Linear trend estimation coefficient increases from 0.0079 before the earthquake to 0.0359 after the earthquake in this whole region. This indicates that the plant ecosystem is rapidly restored between 2009 and 2011. The biggest linear trend is for the hill region, indicating good plant restoration and increase after earthquake. Fluctuation of linear trend estimation coefficient in different counties is more obvious after earthquake. Vegetation restoration after earthquake is most obvious in the regions that suffered the greatest SI (SI10 and SI11). In contrast, fluctuation in linear trend estimation coefficient of annual NDVI mean value for different classes of vegetation is more obvious before earthquake.

  11. LEAF AREA INDEX CHANGE DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN USING IKOMOS AND LANDSAT ETM+ SATELLITE DATA

    Science.gov (United States)

    The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

  12. LEAF AREA INDEX (LAI) CHANGES DETECTION OF UNDERSTORY VEGETATION IN THE ALBEMARLE-PAMLICO BASIN IKONOS AND LANDSAT ETM+ SATELLITE DATA

    Science.gov (United States)

    The advent of remotely sensed data from satellite platforms has enabled the research community to examine vegetative spatial distributions over regional and global scales. This assessment of ecosystem condition through the synoptic monitoring of terrestrial vegetation extent, bio...

  13. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains.

    Science.gov (United States)

    Kooistra, L; Salas, E A L; Clevers, J G P W; Wehrens, R; Leuven, R S E W; Nienhuis, P H; Buydens, L M C

    2004-01-01

    This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The relations were evaluated using simple linear regression in combination with two spectral vegetation indices: the Difference Vegetation Index (DVI) and the Red-Edge Position (REP). In addition, a multivariate regression approach using partial least squares (PLS) regression was adopted. The three methods achieved comparable results. The best R(2) values for the relation between metals concentrations and vegetation reflectance were obtained for grass vegetation and ranged from 0.50 to 0.73. Herbaceous species displayed a larger deviation from the established relationships, resulting in lower R(2) values and larger cross-validation errors. The results corroborate the potential of hyperspectral remote sensing to contribute to the survey of elevated metal concentrations in floodplain soils under grassland using the spectral response of the vegetation as an indicator. Additional constraints will, however, have to be taken into account, as results are resolution- and location-dependent.

  14. Backscattering and vegetation water content response of paddy crop at C-band using RISAT-1 satellite data

    Science.gov (United States)

    Kumar, Pradeep; Prasad, Rajendra; Choudhary, Arti; Gupta, Dileep Kumar; Narayan Mishra, Varun; Srivastava, Prashant K.

    2016-04-01

    The study about the temporal behaviour of vegetation water content (VWC) is essential for monitoring the growth of a crop to improve agricultural production. In agriculture, VWC could possibly provide information that can be used to infer water stress for irrigation decisions, vegetation health conditions, aid in yield estimation and assessment of drought conditions (Penuelas et al., 1993). The VWC is an important parameter for soil moisture retrieval in microwave remote sensing (Srivastava et al., 2014). In the present study, the backscattering and VWC response of paddy crop has been investigated using medium resolution (MRS) radar imaging satellite-1 (RISAT-1) synthetic aperture radar (SAR) data in Varanasi, India. The VWC of paddy crop was measured at its five different growth stages started from 15 July 2013 to 23 October 2013 from the transplanting to maturity stage during Kharif season. The whole life of paddy crop was divided into three different major growth stages like vegetative stage, reproductive stage and ripening stage. During vegetative stage, the backscattering coefficients were found increasing behaviour until the leaves became large and dense due to major contribution of stems and the interaction between the stems and water underneath the paddy crop. During reproductive stage, the backscattering coefficients were found to increase slowly due to random scattering by vertical leaves. The increase in the size of leaves cause to cover most of the spaces between plants resulted to quench the contributions from the stems and the water underneath. At the maturity stage, the backscattering showed its decreasing behaviour. The VWC of paddy crop was found increasing up to vegetative to reproductive stages (28 September 2013) and then started decreasing during the ripening (maturity) stage. Similar behaviour was obtained between backscattering coefficients and VWC that showed an increasing trend from vegetative to reproductive stage and then lowering down at

  15. Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms

    Science.gov (United States)

    Qayyum, A.; Malik, A. S.; Saad, M. N. M.; Iqbal, M.; Abdullah, F.; Rahseed, W.; Abdullah, T. A. R. B. T.; Ramli, A. Q.

    2015-04-01

    Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more time consuming and expensive. In this paper, we have proposed a novel approach to monitor the vegetation/trees near or under the power transmission poles using satellite stereo images, which were acquired using Pleiades satellites. The 3D depth of vegetation has been measured near power transmission lines using stereo algorithms. The area of interest scanned by Pleiades satellite sensors is 100 square kilometer. Our dataset covers power transmission poles in a state called Sabah in East Malaysia, encompassing a total of 52 poles in the area of 100 km. We have compared the results of Pleiades satellite stereo images using dynamic programming and Graph-Cut algorithms, consequently comparing satellites' imaging sensors and Depth-estimation Algorithms. Our results show that Graph-Cut Algorithm performs better than dynamic programming (DP) in terms of accuracy and speed.

  16. Angular sensitivity of vegetation indices derived from CHRIS/PROBA data

    NARCIS (Netherlands)

    Verrelst, J.; Schaepman, M.E.; Kötz, B.; Kneubühler, M.

    2008-01-01

    View angle effects present in spectral vegetation indices can either be regarded as an added source of uncertainty for variable retrieval or as a source of additional information, enhancing the variable retrieval; however, the magnitude of these angular effects remains for most indices unknown or un

  17. Modelling high arctic percent vegetation cover using field digital images and high resolution satellite data

    Science.gov (United States)

    Liu, Nanfeng; Treitz, Paul

    2016-10-01

    In this study, digital images collected at a study site in the Canadian High Arctic were processed and classified to examine the spatial-temporal patterns of percent vegetation cover (PVC). To obtain the PVC of different plant functional groups (i.e., forbs, graminoids/sedges and mosses), field near infrared-green-blue (NGB) digital images were classified using an object-based image analysis (OBIA) approach. The PVC analyses comparing different vegetation types confirmed: (i) the polar semi-desert exhibited the lowest PVC with a large proportion of bare soil/rock cover; (ii) the mesic tundra cover consisted of approximately 60% mosses; and (iii) the wet sedge consisted almost exclusively of graminoids and sedges. As expected, the PVC and green normalized difference vegetation index (GNDVI; (RNIR - RGreen)/(RNIR + RGreen)), derived from field NGB digital images, increased during the summer growing season for each vegetation type: i.e., ∼5% (0.01) for polar semi-desert; ∼10% (0.04) for mesic tundra; and ∼12% (0.03) for wet sedge respectively. PVC derived from field images was found to be strongly correlated with WorldView-2 derived normalized difference spectral indices (NDSI; (Rx - Ry)/(Rx + Ry)), where Rx is the reflectance of the red edge (724.1 nm) or near infrared (832.9 nm and 949.3 nm) bands; Ry is the reflectance of the yellow (607.7 nm) or red (658.8 nm) bands with R2's ranging from 0.74 to 0.81. NDSIs that incorporated the yellow band (607.7 nm) performed slightly better than the NDSIs without, indicating that this band may be more useful for investigating Arctic vegetation that often includes large proportions of senescent vegetation throughout the growing season.

  18. Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards

    Directory of Open Access Journals (Sweden)

    Jonathan Van Beek

    2015-08-01

    Full Text Available Yield and quality estimations provide vital information to fruit growers, yet require accurate monitoring throughout the growing season. To this end, the temporal dependency of fruit yield and quality estimations through spectral vegetation indices was investigated in irrigated and rainfed pear orchards. Both orchards were monitored throughout three consecutive growing seasons, including spectral measurements (i.e., hyperspectral canopy reflectance measurements as well as yield determination (i.e., total yield and number of fruits per tree and quality assessment (i.e., fruit firmness, total soluble solids and fruit color. The results illustrated a clear association between spectral vegetation indices and both fruit yield and fruit quality (|r| > 0.75; p < 0.001. However, the correlations between vegetation indices and production variables varied throughout the growing season, depending on the phenological stage of fruit development. In the irrigated orchard, index values showed a strong association with production variables near time of harvest (|r| > 0.6; p < 0.001, while in the rainfed orchard, index values acquired during vegetative growth periods presented stronger correlations with fruit parameters (|r| > 0.6; p < 0.001. The improved planning of remote sensing missions during (rainfed orchards and after (irrigated orchards vegetative growth periods could enable growers to more accurately predict production outcomes and improve the production process.

  19. 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.

  20. MODIS/TERRA MOD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  1. MODIS/AQUA MYD13C2 Vegetation Indices Monthly L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  2. MODIS/AQUA MYD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  3. MODIS/TERRA MOD13C1 Vegetation Indices Monthly L3 Global 0.05Deg CMG

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Global MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared...

  4. Satellite NDVI Assisted Monitoring of Vegetable Crop Evapotranspiration in California’s San Joaquin Valley

    Directory of Open Access Journals (Sweden)

    Thomas J. Trout

    2012-02-01

    Full Text Available Reflective bands of Landsat-5 Thematic Mapper satellite imagery were used to facilitate the estimation of basal crop evapotranspiration (ETcb, or potential crop water use, in San Joaquin Valley fields during 2008. A ground-based digital camera measured green fractional cover (Fc of 49 commercial fields planted to 18 different crop types (row crops, grains, orchard, vineyard of varying maturity over 11 Landsat overpass dates. Landsat L1T terrain-corrected images were transformed to surface reflectance and converted to normalized difference vegetation index (NDVI. A strong linear relationship between NDVI and Fc was observed (r2 = 0.96, RMSE = 0.062. The resulting regression equation was used to estimate Fc for crop cycles of broccoli, bellpepper, head lettuce, and garlic on nominal 7–9 day intervals for several study fields. Prior relationships developed by weighing lysimeter were used to transform Fc to fraction of reference evapotranspiration, also known as basal crop coefficient (Kcb. Measurements of grass reference evapotranspiration from the California Irrigation Management Information System were then used to calculate ETcb for each overpass date. Temporal profiles of Fc, Kcb, and ETcb were thus developed for the study fields, along with estimates of seasonal water use. Daily ETcb retrieval uncertainty resulting from error in satellite-based Fc estimation was < 0.5 mm/d, with seasonal uncertainty of 6–10%. Results were compared with FAO-56 irrigation guidelines and prior lysimeter observations for reference.

  5. Monitoring the hydrologic and vegetation dynamics of arid land with satellite remote sensing and mathematic modeling

    Science.gov (United States)

    Zhan, Xiwu; Gao, Wei; Pan, Xiaoling; Ma, Yingjun

    2003-07-01

    Terrestrial ecosystems, in which carbon is retained in live biomass, play an important role in the global carbon cycling. Among these ecological systems, vegetation and soils in deserts and semi deserts control significant proportions in the total carbon stocks on the land surface and the carbon fluxes between the land surface and the atmosphere (IPCC special report: Land Use, Land Use Change and Forestry, June 2000). Therefore, accurate assessment of the carbon stocks and fluxes of the desert and semi desert areas at regional scales is required in global carbon cycle studies. In addition, vegetative ecosystem in semi-arid and arid land is strongly dependent on the water resources. Monitoring the hydrologic processes of the land is thus also required. This work explores the methodology for the sequential continuous estimation of the carbon stocks, CO2 flux, evapotranspiration, and sensible heat fluxes over desert and semidesert area using data from the Jornada desert in New Mexico, USA. A CO2 and energy flux coupled model is used to estimate CO2, water vapor and sensible heat fluxes over the desert area. The model is driven by the observed meteorological data. Its input land surface parameters are derived from satellite images. Simulated energy fluxes are validated for specific sites with eddy covariance observations. Based on the output of spatially distributed CO2 fluxes, carbon accumulations over the desert area during a period of time is calculated and the contribution of the desert ecosystem to the atmospheric carbon pool is discussed.

  6. 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.

  7. Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data

    Energy Technology Data Exchange (ETDEWEB)

    Chandola, Varun [ORNL; Vatsavai, Raju [ORNL; Hui, Dafeng [ORNL; Gu, Lianhong [ORNL; Bhaduri, Budhendra L [ORNL

    2010-01-01

    Characterizing vegetation phenology is a highly significant problem, due to its importance in regulating ecosystem carbon cycling, interacting with climate changes, and decision-making of croplands managements. While ground based sensors, such as the AmeriFlux sensors, can provide measurements at high temporal resolution (every hour) and can be used to accurately calculate vegetation phenology indices, they are limited to only a few sites. Remote sensing data, such as the Normalized Difference Vegetation Index (NDVI), collected using the MODerate Resolution Imaging Spectroradiometer (MODIS), can provide global coverage, though at a much coarser temporal resolution (16 days). In this study we use data mining based time series segmentation methods to derive phenology indices from NDVI data, and compare it with the phenology indices derived from the AmeriFlux data using a widely used model fitting approach. Results show a significant correlation (as high as 0.60) between the indices derived from these two different data sources. This study demonstrates that data driven methods can be effectively employed to provide realistic estimates of vegetation phenology indices using periodic time series data and has the potential to be used at large spatial scales and for long-term remote sensing data.

  8. Effects of Simulated Acid Rain on Main Nutritional Indicators of Three Leafy Vegetables

    Institute of Scientific and Technical Information of China (English)

    MENG He; DONG De-ming; WANG Ju; YANG Kai-ning; TIAN Lei; SUN Wei; FANG Chun-sheng

    2011-01-01

    The purpose of this paper was to identify content changes in the main nutritional indicators of three common leafy vegetables, and to provide a theoretical basis for the protection of leafy vegetables from acid rain. The experiment investigated the effects of simulated acid rain on four main nutritional indicators, including soluble sugar,total free amino acid, soluble protein and vitamin C during the application of simulated acid rain(SAR) in pakchoi( Brassica rapa chihensis), rape(Brassica campestris L.) and lettuce( Lactuca sativa Linn. var. ramnosa Hort). The vegetables were respectively exposed to SAR of pH=7.0, 5.6, 5.0, 4.0, 3.0 and a control level of pH=6.5. The concentrations of the four main nutritional indicators were determined at harvest. The results show that nutritional quality of the three leafy vegetable species decreased with the declining of pH values of SAR. The higher the acidity of SAR was, the more significant the inhibitions were. Nutritional quality of lettuce was the most affected by simulated acid rain, followed by pakchoi and rape. The change range of soluble protein content was higher than those of the other three indicators' contents, which indicates that soluble protein is most sensitive to simulated acid rain.

  9. A Satellite-Based Estimation of Evapotranspiration Using Vegetation Index-Temperature Trapezoid Concept: A Case Study in Southern Florida, U.S.A.

    Science.gov (United States)

    Yagci, A. L.; Santanello, J. A., Jr.; Jones, J. W.

    2015-12-01

    One of the key surface variables for hydrological applications, monitoring of natural and anthropogenic water consumption, closing energy balance and water budgets and drought identification is evapotranspiration (ET). There is currently a strong need for high temporal and spatial resolution ET products for climate and hydrological modelers. A satellite-based retrieval method based on vegetation index-temperature trapezoid (VITT) concept has been developed. This model has the ability to generate accurate ET estimates at high temporal and spatial resolutions by taking advantage of key remotely sensed parameters such as vegetation indices (VIs) and land surface temperature (LST) acquired by satellites as well as routinely-measured meteorological variables such as air temperature (Ta) and net radiation. For local-scale applications, the model has been successfully implemented in Python programming language and tested using Landsat satellite products at an eddy covariance flux tower in Florida. It is fully functional and automated such that there is no need of user intervention to run the model. The model development for continental-scale applications using VI and LST products from NASA satellites such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) is currently in progress. The results for local-scale application and early results for continental-scale (US) will be presented and discussed.

  10. 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...

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

    Directory of Open Access Journals (Sweden)

    Per Skougaard Kaspersen

    2015-06-01

    Full Text Available Impervious surfaces (IS are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy 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 < 2% of sub-pixel imperviousness, and are found to be applicable for cities with dissimilar climatic and vegetative conditions. The VI/IS relationship across cities is examined by quantifying the MAEs and MBEs between all combinations of models and urban areas. Also, regional regression models are developed by compiling data from multiple cities to examine 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 the regional models. SAVI is identified as a superior index for the development of regional quantification models. The findings of this study highlight that IS fractions, and spatiotemporal changes herein, can be mapped by use of simple regression models based on VIs from remote sensors, and that the method presented enables simple, accurate and resource efficient quantification of IS.

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

    Directory of Open Access Journals (Sweden)

    Carlos Iñiguez-Armijos

    Full Text Available 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.

  13. 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.

  14. Extracting seasonal cropping patterns using multi-temporal vegetation indices from IRS LISS-III data in Muzaffarpur District of Bihar, India

    Directory of Open Access Journals (Sweden)

    Saptarshi Mondal

    2014-12-01

    Full Text Available The advancement in satellite technology in terms of spatial, temporal, spectral and radiometric resolutions leads, successfully, to more specific and intensified research on agriculture. Automatic assessment of spatio-temporal cropping pattern and extent at multi-scale (community level, regional level and global level has been a challenge to researchers. This study aims to develop a semi-automated approach using Indian Remote Sensing (IRS satellite data and associated vegetation indices to extract annual cropping pattern in Muzaffarpur district of Bihar, India at a fine scale (1:50,000. Three vegetation indices (VIs – NDVI, EVI2 and NDSBVI, were calculated using three seasonal (Kharif, Rabi and Zaid IRS Resourcesat 2 LISS-III images. Threshold reference values for vegetation and non-vegetation thematic classes were extracted based on 40 training samples over each of the seasonal VI. Using these estimated value range a decision tree was established to classify three seasonal VI stack images which reveals seven different cropping patterns and plantation. In addition, a digitised reference map was also generated from multi-seasonal LISS-III images to check the accuracy of the semi-automatically extracted VI based classified image. The overall accuracies of 86.08%, 83.1% and 83.3% were achieved between reference map and NDVI, EVI2 and NDSBVI, respectively. Plantation was successfully identified in all cases with 96% (NDVI, 95% (EVI2 and 91% (NDSBVI accuracy.

  15. Using vegetation indices as input into ramdom forest for soybean and weed classification

    Science.gov (United States)

    Weed management is a major component of a soybean (Glycine max L.) production system; thus, managers need tools to help them distinguish soybean from weeds. Vegetation indices derived from light reflectance properties of plants have shown promise as tools to enhance differences among plants. The o...

  16. Effects of Simulated Acid Rain on Main Nutritional Indicators of Three Leafy Vegetables

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The purpose of this paper was to identify content changes in the main nutritional indicators of three common leafy vegetables, and to provide a theoretical basis for the protection of leafy vegetables from acid rain. The experiment investigated the effects of simulated acid rain on four main nutritional indicators, including soluble sugar, total free amino acid, soluble protein and vitamin C during the application of simulated acid rain(SAR) in pakchoi(Brassica rapa chinensis), rape(Brassica campestris L.) and lettuce(Lactuca sativa Linn. var. ramosa Hort). The vegetables were respectively exposed to SAR of pH=7.0, 5.6, 5.0, 4.0, 3.0 and a control level of pH=6.5. The concentrations of the four main nutritional indicators were determined at harvest. The results show that nutritional quality of the three leafy vegetable species decreased with the declining of pH values of SAR. The higher the acidity of SAR was, the more significant the inhibitions were. Nutritional quality of lettuce was the most affected by simulated acid rain, followed by pakchoi and rape. The change range of soluble protein content was higher than those of the other three indicators' contents, which indicates that soluble protein is most sensitive to simulated acid rain.

  17. 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 < 0.01), and two distinct periods with different trends can be identified, 1982-1990 and 1990-2006. NDVI(u) did not show statistically significant trend before 1990 but decrease remarkably after 1990 (P < 0.01). Different regions also showed difference in the timing of 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.

  18. Integrating Terrain and Vegetation Indices for Identifying Potential Soil Erosion Risk Area

    Institute of Scientific and Technical Information of China (English)

    Arabinda Sharma

    2010-01-01

    The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.

  19. [Effects and indications of spinal cord stimulation on the vegetative syndrome].

    Science.gov (United States)

    Funahashi, K; Komai, N; Ogura, M; Kuwata, T; Nakai, M; Tsuji, N

    1989-10-01

    The effects of spinal cord stimulation (SCS) on the vegetative syndrome were studied in six patients. Factors affecting the results were mentioned with a view to establishing indications as to whether or not the SCS should be performed. "Persistent vegetative states" were thought to be identical with Ohta's "vegetative syndrome" which consists of eleven signs. Six of these signs--polyphasic cycle of waking and sleeping, urinary incontinence, being bedridden and being tube fed etc--were important criteria of the vegetative syndrome. SCS was thought to be effective if one or more of the 6 signs disappeared after SCS. SCS was performed at level from C2 to C4 with a frequency of 25 to 120 Hz, an intensity of 2.5 to 6 volts, a pulse duration of 0.3 to 0.5 msec. and a duration of 3 to 11 hours per day. Neurological signs, ABR, CT/MRI, EEG and the grade of the vegetative syndrome were estimated before and after SCS. In the course of SCS, 2 of the 6 patients recovered from the vegetative syndrome. Both had a localized lesion in the brain stem without a cerebral lesion on CT/MRI, with bilateral appearance of the fifth peak with prolonged latency and decreased amplitude of main peaks on ABR. The other 4 patients showed little or no improvement. They all had diffuse cerebral atrophy or low density areas on CT and almost normal ABR. One of these patients, who suffered a cerebral contusion leading to transtentorial herniation with unilateral cerebral contusion on CT and unilateral disappearance of the fifth peak on ABR, showed no recovery from the vegetative syndrome.(ABSTRACT TRUNCATED AT 250 WORDS)

  20. Effects of saltwater intrusion on pinewood vegetation using satellite ASTER data: the case study of Ravenna (Italy).

    Science.gov (United States)

    Barbarella, M; De Giglio, M; Greggio, N

    2015-04-01

    The San Vitale pinewood (Ravenna, Italy) is part of the remaining wooded areas within the southeastern Po Valley. Several studies demonstrated a widespread saltwater intrusion in the phreatic aquifer caused by natural and human factors in this area as the whole complex coastal system. Groundwater salinization affects soils and vegetation, which takes up water from the shallow aquifer. Changes in groundwater salinity induce variations of the leaf properties and vegetation cover, recognizable by satellite sensors as a response to different spectral bands. A procedure to identify stressed areas from satellite remote sensing data, reducing the expensive and time-consuming ground monitoring campaign, was developed. Multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, acquired between May 2005 and August 2005, were used to calculate Normalized Difference Vegetation Index (NDVI). Within the same vegetation type (thermophilic deciduous forest), the areas with the higher vegetation index were taken as reference to identify the most stressed areas using a statistical approach. To confirm the findings, a comparison was conducted using contemporary groundwater salinity data. The results were coherent in the areas with highest and lowest average NDVI values. Instead, to better understand the behavior of the intermediate areas, other parameters influencing vegetation (meteorological data, water table depth, and tree density) were added for the interpretation of the results.

  1. Soil phosphorus forms as quality indicators of soils under different vegetation covers.

    Science.gov (United States)

    Turrión, María-Belén; López, Olga; Lafuente, Francisco; Mulas, Rafael; Ruipérez, César; Puyo, Alberto

    2007-05-25

    The type of vegetation cover determines the physicochemical and biological properties of the soil over which they are developing. The objective of this study was to determine the effect of different vegetation covers on the forms of soil phosphorus, in order to know which of these forms can be used as a soil quality indicator. The experimental area was located on the acidic plateau at the North of Palencia (North Spain), where an area was selected vegetation covers very close to each other: pine (Pinus sylvestris), oak (Quercus pyrenaica), and three different shrub species (Arctostaphylos uva-ursi, Erica australis and Halimium alyssoides). The Ah horizon was sampled and pH, total organic C (C(org)), total N (N), cationic exchange capacity (CEC), sum of bases (S) and P forms by a sequential fractionation were analysed. Results showed that oak and A. uva-ursi improve the considered soil parameters (pH, C(org)/N ratio, CEC, and S) and provide soils of better quality. Inorganic soil P forms were influenced in greater extent by the vegetation cover than were P organic forms. Labile inorganic P forms could be used as indicators of soil quality. The organic P forms were less sensitive than inorganic ones to the indicated improvements.

  2. Evaluating Multispectral Images and Vegetation Indices for Precision Farming Applications from UAV Images

    Directory of Open Access Journals (Sweden)

    Sebastian Candiago

    2015-04-01

    Full Text Available Unmanned Aerial Vehicles (UAV-based remote sensing offers great possibilities to acquire in a fast and easy way field data for precision agriculture applications. This field of study is rapidly increasing due to the benefits and advantages for farm resources management, particularly for studying crop health. This paper reports some experiences related to the analysis of cultivations (vineyards and tomatoes with Tetracam multispectral data. The Tetracam camera was mounted on a multi-rotor hexacopter. The multispectral data were processed with a photogrammetric pipeline to create triband orthoimages of the surveyed sites. Those orthoimages were employed to extract some Vegetation Indices (VI such as the Normalized Difference Vegetation Index (NDVI, the Green Normalized Difference Vegetation Index (GNDVI, and the Soil Adjusted Vegetation Index (SAVI, examining the vegetation vigor for each crop. The paper demonstrates the great potential of high-resolution UAV data and photogrammetric techniques applied in the agriculture framework to collect multispectral images and evaluate different VI, suggesting that these instruments represent a fast, reliable, and cost-effective resource in crop assessment for precision farming applications.

  3. Comparison of Vegetation Indices and Red-edge Parameters for Estimating Grassland Cover from Canopy Reflectance Data

    Institute of Scientific and Technical Information of China (English)

    Zhan-Yu Liu; Jing-Feng Huang; Xin-Hong Wu; Yong-Ping Dong

    2007-01-01

    There has been a great deal of interests in the estimation of grassland biophysical parameters such as percentage of vegetation cover (PVC), aboveground biomass, and leaf-area index with remote sensing data at the canopy scale. In this paper, the percentage of vegetation cover was estimated from vegetation indices using Moderate Resolution Imaging Spectroradiometer (MODIS) data and red-edge parameters through the first derivative spectrum from in situ hypserspectral reflectance data. Hyperspectral reflectance measurements were made on grasslands in Inner Mongolia, China, using an Analytical Spectral Devices spectroradiometer. Vegetation indices such as the difference, simple ratio, normalized difference,renormalized difference, soil-adjusted and modified soil-adjusted vegetation indices (DVI, RVI, NDVI, RDVI,SAVIL = 0.5 and MSAVI2) were calculated from the hyperspectral reflectance of various vegetation covers. The percentage of vegetation cover was estimated using an unsupervised spectral-contextual classifier automatically. Relationships between percentage of vegetation cover and various vegetation indices and red-edge parameters were compared using a linear and second-order polynomial regression. Our analysis indicated that MSAVI2 and RVI yielded more accurate estimations for a wide range of vegetation cover thanother vegetation indices and red-edge parameters for the linear and second-order polynomial regression,respectively.

  4. 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 R(2) 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.

  5. Soil TPH concentration estimation using vegetation indices in an oil polluted area of eastern China.

    Directory of Open Access Journals (Sweden)

    Linhai Zhu

    Full Text Available 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 R(2 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.

  6. 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 (R2 = 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 (R2 = 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

  7. Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA/CHRIS Data Over an Agricultural Area

    OpenAIRE

    Pablo Martinez; José Moreno; Luis Guanter; Antonio Plaza; José A Sobrino; Jiménez-Muñoz, Juan C.

    2009-01-01

    Abstract: In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC) retrieval from Compact High Resolution Imaging Spectrometer (CHRIS) data onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs), in particular the Normalized Difference Vegetation Index (NDVI) and the Variable Atmospherically Resistant Index (VARI). The second methodology is b...

  8. A Dynamic Vegetation Senescence Indicator for Near-Real-Time Desert Locust Habitat Monitoring with MODIS

    Directory of Open Access Journals (Sweden)

    Cécile Renier

    2015-06-01

    Full Text Available Desert locusts (Schistocerca gregaria represent a major threat for agro-pastoral resources and food security over almost 30 million km2 from northern Africa to the Arabian peninsula and India. Given the differential food preferences of this insect pest and the extent and remoteness of the their distribution area, near-real-time remotely-sensed information on potential habitats support control operations by narrowing down field surveys to areas favorable for their development and prone to gregarization and outbreaks. The development of dynamic greenness maps, which detect the onset of photosynthetic vegetation, allowed national control centers to identify potential habitats to survey, as locusts prefer green and fresh vegetation. Their successful integration into the daily control operations led to a new need: the near-real-time identification of the onset of dryness, a synonym for the loss of habitat attractiveness, likely to be abandoned by locusts. The timely availability of this information would enable control centers to focus their surveys on areas more prone to gregarization, leading to more efficiency in the allocation of resources and in decision making. In this context, this work developed an original method to detect in near-real-time the onset of vegetation senescence. The design of the detection relies on the temporal behavior of two indices: the Normalized Difference Vegetation Index, depending on the green vegetation, and the Normalized Difference Tillage Index, sensitive to both green and dry vegetation. The method is demonstrated in Mauritania, an ever-affected country, with 10-day MODIS mean composites for the years 2010 and 2011. The discrimination performance of three classes (“growth”, “density reduction” and “drying” were analyzed for three classification methods: maximum likelihood (61.4% of overall accuracy, decision tree (71.5% and support vector machine (72.3%. The classification accuracy is heterogeneous in

  9. Evaluating Landsat 8 Satellite Sensor Data for Improved Vegetation Mapping Accuracy of the New Hampshire Coastal Watershed Area

    Science.gov (United States)

    Ledoux, Lindsay

    the previous Landsat sensor (Landsat 7). Once classification had been performed, traditional and area-based accuracy assessments were implemented. Comparison measures were also calculated (i.e. Kappa, Z test statistic). The results from this study indicate that, while using Landsat 8 imagery is useful, the additional spectral bands provided in the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) do not provide an improvement in vegetation classification accuracy in this study.

  10. 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.

  11. Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography

    Science.gov (United States)

    Moore, Caitlin E.; Brown, Tim; Keenan, Trevor F.; Duursma, Remko A.; van Dijk, Albert I. J. M.; Beringer, Jason; Culvenor, Darius; Evans, Bradley; Huete, Alfredo; Hutley, Lindsay B.; Maier, Stefan; Restrepo-Coupe, Natalia; Sonnentag, Oliver; Specht, Alison; Taylor, Jeffrey R.; van Gorsel, Eva; Liddell, Michael J.

    2016-09-01

    Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia's vegetation phenology is a challenge due to its diverse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semi-arid scrublands, and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e. drought, flooding, cyclones, and fire) that can alter ecosystem composition, structure, and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology on the continental scale using the enhanced vegetation index (EVI), calculated from MODerate resolution Imaging Spectroradiometer (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e. tropical savannas) to regions where seasonal variation is minimal (i.e. tropical rainforests) or high but irregular (i.e. arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understorey, as well as strong seasonal dynamics of individual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that

  12. How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

    Directory of Open Access Journals (Sweden)

    Yanghui Kang

    2016-07-01

    Full Text Available Leaf Area Index (LAI is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs. We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR, Normalized Difference Vegetation Index (NDVI, two versions of the Enhanced Vegetation Index (EVI and EVI2, and Green Chlorophyll Index (CIGreen. Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 > 0.5, and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

  13. Quantitative Determination of Bandpasses for Producing Vegetation Indices from Recombined NEON Hyperspectral Imagery

    Science.gov (United States)

    Hulslander, D.

    2015-12-01

    Hyperspectral imaging systems can be used to produce spectral reflectance curves giving rich information about composition, relative abundances of materials, mixes and combinations. However, as each spectral return from these systems is a vector with several hundred elements, they can be very difficult to process and analyze, and problemeatic to compare within, across, and between datasets over time and space. Vegetation indices (e.g. NDVI, ARVI, EVI, et al) attempt to combine spectral features in to single-value scores. When derived from calibrated and atmospherically compensated reflectance data, these indices can be quantitatively compared. Historically, these indices have been calculated from multispectral sensor data. These sensors have a handful (4 to 16 or so) of bandbasses ranging from 20 nm to 200 nm FWHM covering specific spectral regions for a variety of reasons, including both intended applications and system limitations. Hyperspectral sensors, however, cover the spectrum with many, many narrow (5 to 10 nm) bandpasses. This allows for analyses using the full, detailed spectral curve, or combination of the bands in to regions by averaging or in to composites using transforms or other techniques. This raises the question of exactly which bands should be used and combined in what manner for ideally deriving well-known vegetation indices typically made from multispectral data. In this study we use derivatives and other curve and signal analysis techniques to analyze vegetation reflectance spectra to quantitatively define optimal bandpasses for several vegetation indices and combine the 5 nm hypserspectral bandpasses of the NEON Imaging Spectrometer to synthesize them.

  14. Spatial patterns and trends in remotely sensed vegetation indices 1981-2016

    Science.gov (United States)

    Spinoni, Jonathan; Duveiller, Gregory; Cescatti, Alessandro

    2017-04-01

    The current global state of vegetation and its evolution through the last decades is related with climate change issues. A few recent studies investigated the greening or browning vegetation tendencies at global and continental scales using remotely sensed data. However, the relatively short length of such data made it difficult to detect statistically robust trends in vegetation indicators. This study investigates global high-resolution (0.05°) spatial patterns and trends of vegetation conditions at a seasonal scale and over the period 1981-2016, by means of three indicators, the measured Normalized Difference Vegetation Index (NDVI) and the modelled Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FAPAR). Using very high-resolution (300 m) land cover grids, this study tries to decompose such trends into the contributions from the single different plant functional types (PFTs). Moreover, this study investigates the correlations between the trends of selected PFTs with other proxies as aggregated land cover classes, climate classification schemes, and single types of trees (this last feature over parts of Europe only). Then NDVI, LAI, and FAPAR input data used are from the Climate Data Record Program (CDR) of the National Oceanic and Atmospheric Administration (NOOA) and were subjected to extensive quality-checks. The land cover grids (2000, 2005, and 2010) are from the Climate Change Initiative (CCI) of the European Space Agency (ESA). Tree species over Europe are from European Atlas of Forest Tree Species of the Joint research Centre (JRC). Climate classification schemes used follow the Köppen-Geiger and the Holdridge life zones formulations. Seasonal trends in NDVI, LAI, and FAPAR, together with their statistical significance, are presented in global maps to focus at seasonal greening and browning tendencies. Trends in single PFTs and their relationships with land cover, climate classes, and tree species are shown in tables and

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

    Science.gov (United States)

    An, Xiaohong; Lu, Houyuan; Chu, Guoqiang

    2015-10-01

    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.

  16. 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

    Impervious surfaces (IS) are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy and applic......Impervious surfaces (IS) are a key indicator of environmental quality, and mapping of urban IS is important for a wide range of applications including hydrological modelling, water management, urban and environmental planning and urban climate studies. This paper addresses the accuracy...... 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 ... to be applicable for cities with dissimilar climatic and vegetative conditions. The VI/IS relationship across cities is examined by quantifying the MAEs and MBEs between all combinations of models and urban areas. Also, regional regression models are developed by compiling data from multiple cities to examine...

  17. 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.

  18. 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

  19. Changes in the distribution of South Korean forest vegetation simulated using thermal gradient indices

    Institute of Scientific and Technical Information of China (English)

    CHOI; Sungho; LEE; Woo-Kyun; SON; Yowhan; YOO; Seongjin; LIM; Jong-Hwan

    2010-01-01

    To predict changes in South Korean vegetation distribution,the Warmth Index(WI) and the Minimum Temperature of the Coldest Month Index(MTCI) were used.Historical climate data of the past 30 years,from 1971 to 2000,was obtained from the Korea Meteorological Administration.The Fifth-Generation National Center for Atmospheric Research(NCAR) /Penn State Mesoscale Model(MM5) was used as a source for future climatic data under the A1B scenario from the Special Report on Emission Scenario(SRES) of the Intergovernmental Panel on Climate Change(IPCC).To simulate future vegetation distribution due to climate change,the optimal habitat ranges of Korean tree species were delimited by the thermal gradient indices,such as WI and MTCI.To categorize the Thermal Analogy Groups(TAGs) for the tree species,the WI and MTCI were orthogonally plotted on a two-dimensional grid map.The TAGs were then designated by the analogue composition of tree species belonging to the optimal WI and MTCI ranges.As a result of the clustering process,22 TAGs were generated to explain the forest vegetation distribution in Korea.The primary change in distribution for these TAGs will likely be in the shrinkage of areas for the TAGs related to Pinus densiflora and P.koraiensis,and in the expansion of the other TAG areas,mainly occupied by evergreen broad-leaved trees,such as Camellia japonica,Cyclobalanopsis glauca,and Schima superba.Using the TAGs to explain the effects of climate change on vegetation distribution on a more regional scale resulted in greater detail than previously used global or continental scale vegetation models.

  20. Seasonal Biophysical Dynamics of the Amazon from Space Using MODIS Vegetation Indices

    Science.gov (United States)

    Huete, A. R.; Didan, K.; Ratana, P.; Ferreira, L.

    2002-12-01

    We utilized the Terra- Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) products to analyze the seasonal and spatial patterns of photosynthetic vegetation activity over the Amazon Basin and surrounding regions of Brazil. The seasonal patterns of vegetation activity were studied along two, eco-climatic transects extending from (1) the cerrado region (Brasilia National Park) to the seasonal tropical forest (Tapajos National Forest) and (2) the caatinga biome to the seasonal and per-humid tropical forests. In addition to the climatic transects, we also investigated the seasonal dynamics of altered, land conversion areas associated with pastures and clearcutting land use activities. Both the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) at 250-m, 500-m, and 1-km were used to extract seasonal profile curves. The quality assurance (QA) information of the output products was used in noise removal and data filtering prior to the generation of the seasonal profiles. Histogram analyses were also performed at coarse (biome) scale and fine, site intensive (flux towers) scale. The seasonal patterns of the cerrado and caatinga were very pronounced with distinct dry and wet seasonal trends. We observed decreasing dry-wet seasonal patterns in the transitional areas near Araguaia National Park. In contrast, the seasonal behavior of the tropical forests were much harder to assess, but indicated slight seasonal trends that ran counter to rainfall activity. This may be attributed to new leaf growth in the dry season. We further found MODIS VI seasonal patterns to vary significantly in land converted and land degraded areas.

  1. 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

  2. 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.

  3. Performance of vegetation indices from Landsat time series in deforestation monitoring

    Science.gov (United States)

    Schultz, Michael; Clevers, Jan G. P. W.; Carter, Sarah; Verbesselt, Jan; Avitabile, Valerio; Quang, Hien Vu; Herold, Martin

    2016-10-01

    The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies.

  4. 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.

  5. Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques

    Directory of Open Access Journals (Sweden)

    Suranjan Panigrahi

    2010-03-01

    Full Text Available Spatial variability in a crop field creates a need for precision agriculture. Economical and rapid means of identifying spatial variability is obtained through the use of geotechnology (remotely sensed images of the crop field, image processing, GIS modeling approach, and GPS usage and data mining techniques for model development. Higher-end image processing techniques are followed to establish more precision. The goal of this paper was to investigate the strength of key spectral vegetation indices for agricultural crop yield prediction using neural network techniques. Four widely used spectral indices were investigated in a study of irrigated corn crop yields in the Oakes Irrigation Test Area research site of North Dakota, USA. These indices were: (a red and near-infrared (NIR based normalized difference vegetation index (NDVI, (b green and NIR based green vegetation index (GVI, (c red and NIR based soil adjusted vegetation index (SAVI, and (d red and NIR based perpendicular vegetation index (PVI. These four indices were investigated for corn yield during 3 years (1998, 1999, and 2001 and for the pooled data of these 3 years. Initially, Back-propagation Neural Network (BPNN models were developed, including 16 models (4 indices * 4 years including the data from the pooled years to test for the efficiency determination of those four vegetation indices in corn crop yield prediction. The corn yield was best predicted using BPNN models that used the means and standard deviations of PVI grid images. In all three years, it provided higher prediction accuracies, coefficient of determination (r2, and lower standard error of prediction than the models involving GVI, NDVI, and SAVI image information. The GVI, NDVI, and SAVI models for all three years provided average testing prediction accuracies of 24.26% to 94.85%, 19.36% to 95.04%, and 19.24% to 95.04%, respectively while the PVI models for all three years provided average testing prediction accuracies

  6. Soil salinity detection from satellite image analysis: an integrated approach of salinity indices and field data.

    Science.gov (United States)

    Morshed, Md Manjur; Islam, Md Tazmul; Jamil, Raihan

    2016-02-01

    This paper attempts to detect soil salinity from satellite image analysis using remote sensing and geographic information system. Salinity intrusion is a common problem for the coastal regions of the world. Traditional salinity detection techniques by field survey and sampling are time-consuming and expensive. Remote sensing and geographic information system offer economic and efficient salinity detection, monitoring, and mapping. To predict soil salinity, an integrated approach of salinity indices and field data was used to develop a multiple regression equation. The correlations between different indices and field data of soil salinity were calculated to find out the highly correlated indices. The best regression model was selected considering the high R (2) value, low P value, and low Akaike's Information Criterion. About 20% variation was observed between the field data and predicted EC from the satellite image analysis. The precision of this salinity detection technique depends on the accuracy and uniform distribution of field data.

  7. Analysis of the changes in vegetation of the Sapanca Lake Basin (in Turkey using multitemporal satellite data

    Directory of Open Access Journals (Sweden)

    Cercis İkiel

    2015-04-01

    Full Text Available The Lake Sapanca Basin is located in an area where urbanization and industrialization is rapidly increasing because of its geographical location. The Sapanca Lake Basin was opened to settlement densely after 1980 due to recreational activities for urbanization and industrialization. The aim of this study is to investigate and evaluate the changes in natural vegetation and settlement caused by the effects of human activities in the Sapanca Lake Basin. For this purpose, Landsat 5 TM (1987 and Landsat 8 (2013 satellite images have been used. These images have been analyzed using ERDAS and ArcGIS software’s and this was supported and confirmed by the carried land studies. The results showed that there has been an % 12.8 decrease in the high density green vegetation areas. It is concluded that the natural vegetation of Sapanca Lake Basin damaged rapidly in the period between the years of 1987-2013.

  8. Vegetation

    DEFF Research Database (Denmark)

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

    2012-01-01

    • Over the past 30 years (1982-2011), the Normalized Difference Vegetation Index (NDVI), an index of green vegetation, has increased 15.5% in the North American Arctic and 8.2% in the Eurasian Arctic. In the more southern regions of Arctic tundra, the estimated aboveground plant biomass has...

  9. Non-destructive estimation of foliar carotenoid content of tree species using merged vegetation indices.

    Science.gov (United States)

    Fassnacht, Fabian E; Stenzel, Stefanie; Gitelson, Anatoly A

    2015-03-15

    Leaf pigment content is an important indicator of plant status and can serve to assess the vigor and photosynthetic activity of plants. The application of spectral information gathered from laboratory, field and remote sensing-based spectrometers to non-destructively assess total chlorophyll (Chl) content of higher plants has been demonstrated in earlier studies. However, the precise estimation of carotenoid (Car) content with non-destructive spectral measurements has so far not reached accuracies comparable to the results obtained for Chl content. Here, we examined the potential of a recently developed angular vegetation index (AVI) to estimate total foliar Car content of three tree species. Based on an iterative search of all possible band combinations, we identified a best candidate AVIcar. The identified index showed quite close but essentially not linear relation with Car contents of the examined species with increasing sensitivity to high Car content and a lack of sensitivity to low Car content for which earlier proposed vegetation indices (VI) performed better. To make use of the advantages of both VI types, we developed a simple merging procedure, which combined the AVIcar with two earlier proposed carotenoid indices. The merged indices had close linear relationship with total Car content and outperformed all other examined indices. The merged indices were able to accurately estimate total Car content with a percental root mean square error (%RMSE) of 8.12% and a coefficient of determination of 0.88. Our findings were confirmed by simulations using the radiative transfer model PROSPECT-5. For simulated data, the merged indices again showed a quasi linear relationship with Car content. This strengthens the assumption that the proposed merged indices have a general ability to accurately estimate foliar Car content. Further examination of the proposed merged indices to estimate foliar Car content of other plant species is desirable to prove the general

  10. Seasonal and interannual variability of climate and vegetation indices across the Amazon.

    Science.gov (United States)

    Brando, Paulo M; Goetz, Scott J; Baccini, Alessandro; Nepstad, Daniel C; Beck, Pieter S A; Christman, Mary C

    2010-08-17

    Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996-2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002-2005. Using improved enhanced vegetation index (EVI) measurements (2000-2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development.

  11. Exploration of Loggerhead Shrike Habitats in Grassland National Park of Canada Based on in Situ Measurements and Satellite-Derived Adjusted Transformed Soil-Adjusted Vegetation Index (ATSAVI

    Directory of Open Access Journals (Sweden)

    Li Shen

    2013-01-01

    Full Text Available The population of loggerhead shrike (Lanius ludovicianus excubutirudes in Grassland National Park of Canada (GNPC has undergone a severe decline due to habitat loss and limitation. Shrike habitat availability is highly impacted by the biophysical characteristics of grassland landscapes. This study was conducted in the west block of GNPC. The overall purpose was to extract important biophysical and topographical variables from both SPOT satellite imagery and in situ measurements. Statistical analysis including Analysis of Variance (ANOVA, measuring Coefficient Variation (CV, and regression analysis were applied to these variables obtained from both imagery and in situ measurement. Vegetation spatial variation and heterogeneity among active, inactive and control nesting sites at 20 m × 20 m, 60 m × 60 m and 100 m × 100 m scales were investigated. Results indicated that shrikes prefer to nest in open areas with scattered shrubs, particularly thick or thorny species of smaller size, to discourage mammalian predators. The most important topographical characteristic is that active sites are located far away from roads at higher elevation. Vegetation index was identified as a good indicator of vegetation characteristics for shrike habitats due to its significant relation to most relevant biophysical factors. Spatial variation analysis showed that at all spatial scales, active sites have the lowest vegetation abundance and the highest heterogeneity among the three types of nesting sites. For all shrike habitat types, vegetation abundance decreases with increasing spatial scales while habitat heterogeneity increases with increasing spatial scales. This research also indicated that suitable shrike habitat for GNPC can be mapped using a logistical model with ATSAVI and dead material in shrub canopy as the independent variables.

  12. Improving the representation of fire disturbance in dynamic vegetation models by assimilating satellite data

    Science.gov (United States)

    Kantzas, E. P.; Quegan, S.; Lomas, M.

    2015-03-01

    Fire provides an impulsive and stochastic pathway for carbon from the terrestrial biosphere to enter the atmosphere. Despite fire emissions being of similar magnitude to Net Ecosystem Exchange in many biomes, even the most complex Dynamic Vegetation Models (DVMs) embedded in General Circulation Models contain poor representations of fire behaviour and dynamics such as propagation and distribution of fire sizes. A model-independent methodology is developed which addresses this issue. Its focus is on the Arctic where fire is linked to permafrost dynamics and on occasion can release great amounts of carbon from carbon-rich organic soils. Connected Component Labeling is used to identify individual fire events across Canada and Russia from daily, low-resolution burned area satellite products, and the results are validated against historical data. This allows the creation of a fire database holding information on area burned and temporal evolution of fires in space and time. A method of assimilating the statistical distribution of fire area into a DVM whilst maintaining its Fire Return Interval is then described. The algorithm imposes a regional scale spatially dependent fire regime on a sub-scale spatially independent model (point model); the fire regime is described by large scale statistical distributions of fire intensity and spatial extent, and the temporal dynamics (fire return intervals) are determined locally. This permits DVMs to estimate many aspects of post-fire dynamics that cannot occur under their current representations of fire, as is illustrated by considering the evolution of land cover, biomass and Net Ecosystem Exchange after a fire.

  13. Improving the representation of fire disturbance in dynamic vegetation models by assimilating satellite data

    Directory of Open Access Journals (Sweden)

    E. P. Kantzas

    2015-03-01

    Full Text Available Fire provides an impulsive and stochastic pathway for carbon from the terrestrial biosphere to enter the atmosphere. Despite fire emissions being of similar magnitude to Net Ecosystem Exchange in many biomes, even the most complex Dynamic Vegetation Models (DVMs embedded in General Circulation Models contain poor representations of fire behaviour and dynamics such as propagation and distribution of fire sizes. A model-independent methodology is developed which addresses this issue. Its focus is on the Arctic where fire is linked to permafrost dynamics and on occasion can release great amounts of carbon from carbon-rich organic soils. Connected Component Labeling is used to identify individual fire events across Canada and Russia from daily, low-resolution burned area satellite products, and the results are validated against historical data. This allows the creation of a fire database holding information on area burned and temporal evolution of fires in space and time. A method of assimilating the statistical distribution of fire area into a DVM whilst maintaining its Fire Return Interval is then described. The algorithm imposes a regional scale spatially dependent fire regime on a sub-scale spatially independent model (point model; the fire regime is described by large scale statistical distributions of fire intensity and spatial extent, and the temporal dynamics (fire return intervals are determined locally. This permits DVMs to estimate many aspects of post-fire dynamics that cannot occur under their current representations of fire, as is illustrated by considering the evolution of land cover, biomass and Net Ecosystem Exchange after a fire.

  14. 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

  15. 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

  16. 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

  17. 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

  18. Information extraction with object based support vector machines and vegetation indices

    Science.gov (United States)

    Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

    2016-07-01

    Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

  19. Analysing vegetation phenology in response to climate change using enhanced bioclimatic indices in Iraq

    Science.gov (United States)

    Daham, Afrah; Han, Dawei; Jolly, William M.; Rico-Ramirez, Miguel

    2017-04-01

    Exchanges of momentum, heat, carbon dioxide, energy, water and mass between the land's surface and the atmosphere are significantly affected by the phenological state of vegetation. Although, most phenology models have the function in analysing and predicting future trends in response to climate change, a bioclimatic index including precipitation in has not been adequately considered in the existing phenology models. In this study a new variable is added to the common set of variables found in the literature review and it is demonstrated how these variables could be combined into an index to quantify the greenness of vegetation throughout the three different years that have been selected (2001, 2006, and 2010). These four selected variables are: Suboptimal (minimum) temperatures, evaporative demand (vapour pressure deficit), photoperiod (daylength), and precipitation. Threshold limits (a lower threshold and an upper threshold) have been set for individual variables, within which the relative phenological performance of the vegetation is assumed to vary from inactive (0) to unconstrained (1). A combined Growing Season Index (GSI) is derived as the product of the four indices. The mean GSI values over twenty one days for the study area during the study period showed a good correlation with the MODerate-resolution Imaging Spectroradiometer (MODIS) and the derived Normalized Difference Vegetation Index (NDVI). The model has been tested for different locations in Iraq (Sulaymaniyah in the north, Wasit in the centre and Basrah in the south) by comparing the model results for these areas with the addition of the precipitation variable and without. The correlation for this model has been improved significantly after adding precipitation as an index in the GSI model. The modified model appears sufficiently robust to reconstruct historical variation as well as to forecast possible future phenological responses to changing climatic conditions. This study is of important value

  20. Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale.

    Science.gov (United States)

    Xu, Chi; Li, Yutong; Hu, Jian; Yang, Xuejiao; Sheng, Sheng; Liu, Maosong

    2012-03-01

    Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.

  1. Application of a simple dynamic vegetation model to an experimental plot and validation through satellite data and field observations

    Science.gov (United States)

    Ruiz-Pérez, Guiomar; Pasquato, Marta; Medici, Chiara; González-Sanchis, María; Molina, Antonio; Fernandes, Tarcísio José Gualberto; del Campo, Antonio; Francés, Félix

    2014-05-01

    It is well known that the vegetation plays a key role in the catchment's water balance particularly for semi-arid areas that generally are water-controlled ecosystems. For this reason, the number of hydrological models which include vegetation as a state variable has increased substantially in the last decade. However, many of the available dynamic vegetation models are quite complex.To cope with the difficulty of estimating a large number of parameters and inputs, the authors focused on the use of a parsimonious model called LUE-model. This model is based on the amount of photosynthetically active radiation absorbed by green vegetation (APAR) and the Light Use Efficiency index (the efficiency by which that radiation is converted to plant biomass increment) in order to compute the gross primary production (GPP). The advantages of this simple conceptualization are: (1) the low number of parameters, (2) it could be easily coupled with a hydrological model and, (3) as it is based on APAR, it is directly connected with satellite data. This model has been calibrated and validated using remote sensing data and afterwards further tested against field observations. Plant transpiration and soil moisture were obtained in an experimental plot of a semi-arid catchment (La Hunde, East of Spain), during the period from 27/03/2009 to 31/05/2011, covered by Aleppo pine.The satellite data used in this study were: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), both included in the products MOD13Q1 and MYD13Q1. Concerning NDVI, its own definition links this index to the "greenness" of the target, so that it appears highly linked to chlorophyll content and vegetation condition. Recent studies about Aleppo pine have shown that NDVI is sensitive to water stress, because the photosynthetic pigment is it. For this reason, the model simulated LAI was corrected by a plant water-stress factor. After such correction, the correlation coefficient with

  2. MODIS/TERRA MOD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  3. MODIS/AQUA MYD13C1 Vegetation Indices 16-Day L3 Global 0.05Deg CMG Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The MODIS Vegetation Indices Version 6 product provides a Vegetation Index (VI) value at a per pixel basis. There are 2 primary vegetation layers. The algorithm for...

  4. 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.

  5. 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.

  6. Land Cover Classification in an Ecuadorian Mountain Geosystem Using a Random Forest Classifier, Spectral Vegetation Indices, and Ancillary Geographic Data

    Directory of Open Access Journals (Sweden)

    Johanna E. Ayala-Izurieta

    2017-05-01

    Full Text Available We presented a methodology to accurately classify mountainous regions in the tropics. These landscapes are complex in terms of their geology, ecosystems, climate and land use. Obtaining accurate maps to assess land cover change is essential. The objectives of this study were to (1 map vegetation using the Random Forest Classifier (RFC, spectral vegetation index (SVI, and ancillar geographic data (2 identify important variables that help differentiate vegetation cover, and (3 assess the accuracy of the vegetation cover classification in hard-to-reach Ecuadorian mountain region. We used Landsat 7 ETM+ satellite images of the entire scene, a RFC algorithm, and stratified random sampling. The altitude and the two band enhanced vegetation index (EVI2 provide more information on vegetation cover than the traditional and often use normalized difference vegetation index (NDVI in other settings. We classified the vegetation cover of mountainous areas within the 1016 km2 area of study, at 30 m spatial resolution, using RFC that yielded a land cover map with an overall accuracy of 95%. The user´s accuracy and the half-width of the confidence interval for 95% of the basic map units, forest (FOR, páramo (PAR, crop (CRO and pasture (PAS were 95.85% ± 2.86%, 97.64% ± 1.24%, 91.53% ± 3.35% and 82.82% ± 7.74%, respectively. The overall disagreement was 4.47%, which results from adding 0.43% of quantity disagreement and 4.04% of allocation disagreement. The methodological framework presented in this paper and the combined use of SVIs, ancillary geographic data, and the RFC allowed the accurate mapping of hard-to-reach mountain landscapes as well as uncovering the underlying factors that help differentiate vegetation cover in the Ecuadorian mountain geosystem.

  7. Evaluation of Fecal Indicators and Pathogens in a Beef Cattle Feedlot Vegetative Treatment System.

    Science.gov (United States)

    Durso, Lisa M; Miller, Daniel N; Snow, Daniel D; Henry, Christopher G; Santin, Monica; Woodbury, Bryan L

    2017-01-01

    Runoff from open-lot animal feeding areas contains microorganisms that may adversely affect human and animal health if not properly managed. One alternative to full manure containment systems is a vegetative treatment system (VTS) that collects runoff in a sediment basin and then applies it to a perennial vegetation (grass) treatment area that is harvested for hay. Little is known regarding the efficacy of large-scale commercial VTSs for the removal of microbial contaminants. In this study, an active, pump-based VTS designed and built for a 1200-head beef cattle feedlot operation was examined to determine the effects of repeated feedlot runoff application on fecal indicator microorganisms and pathogens over short-term (2 wk) and long-term (3 yr) operations and whether fecal bacteria were infiltrating into deeper soils within the treatment area. In a short-term study, fecal bacteria and pathogen numbers declined over time in soil. Measurements of total coliforms and Enterococcus counts taken on control soils were not effective as fecal indicators. The repeated application of manure-impacted runoff as irrigation water did not enrich the pathogens or fecal indicators in the soil, and no evidence was seen to indicate that pathogens were moving into the deeper soil at this site. These results indicate that large-scale, active VTSs reduce the potential for environmental contamination by manure-associated bacteria. Also, this study has implications to full-containment systems that apply runoff water to land application areas (cropland) and the fate of pathogens in the soils of land application sites.

  8. Correlation of basic oil quality indices and electrical properties of model vegetable oil systems.

    Science.gov (United States)

    Prevc, Tjaša; Cigić, Blaž; Vidrih, Rajko; Poklar Ulrih, Nataša; Šegatin, Nataša

    2013-11-27

    Model vegetable oil mixtures with significantly different basic oil quality indices (free fatty acid, iodine, and Totox values) were prepared by adding oleic acids, synthetic saturated triglycerides, or oxidized safflower oil ( Carthamus tinctorius ) to the oleic type of sunflower oil. Dielectric constants, dielectric loss factors, quality factors, and electrical conductivities of model lipids were determined at frequencies from 50 Hz to 2 MHz and at temperatures from 293.15 to 323.15 K. The dependence of these dielectric parameters on basic oil quality indices was investigated. Adding oleic acids to sunflower oil resulted in lower dielectric constants and conductivities and higher quality factors. Reduced iodine values resulted in increased dielectric constants and quality factors and decreased conductivities. Higher Totox values resulted in higher dielectric constants and conductivities at high frequencies and lower quality factors. Dielectric constants decreased linearly with temperature, whereas conductivities followed the Arrhenius law.

  9. Hydrometeorological and vegetation indices for the drought monitoring system in Tuscany Region, Italy

    Directory of Open Access Journals (Sweden)

    F. Caparrini

    2009-03-01

    Full Text Available We present here the first experiments for an integrated system that is under development for drought monitoring and water resources assessment in Tuscany Region in central Italy. The system is based on the cross-evaluation of the Standardized Precipitation Index (SPI, Vegetation Indices from remote sensing (from MODIS and SEVIRI-MSG, and outputs from the distributed hydrological model MOBIDIC, that is used in real-time for water balance evaluation and hydrological forecast in the major basins of Tuscany.

    Furthermore, a telemetric network of aquifer levels is near completion in the region, and data from nearly 50 stations are already available in real-time.

    Preliminary estimates of drought indices over Tuscany in the first eight months of 2007 are shown, and pathway for further studies on the correlation between patterns of crop water stress, precipitation deficit and groundwater conditions is discussed.

  10. Assessing the Relationship Between Spectral Vegetation Indices and Shrub Cover in the Jornada Basin, New Mexico

    Science.gov (United States)

    Duncan, Jeff; Stow, D.; Franklin, J.; Hope, A.

    1993-01-01

    We assessed the statistical relations between Spectral Vegetation Indices (SVI's) derived from SPOT multi-spectral data and semi-arid shrub cover at the Jornada LTER site in New Mexico. Despite a limited range of shrub cover in the sample the analyses resulted in r(sup 2) values as high as 0 central dot 77. Greenness SVI's (e.g., Simple Ratio, NDVI, SAVI, PVI and an orthogonal Greenness index) were shown to be more sensitive to shrub type and phenology than brightness SVis (e.g., green, red and near-infrared reflectances and a Brightness index). The results varied substantially with small-scale changes in plot size (60m by 60m to 100m by 100m) as a consequence of landscape heterogeneity. The results also indicated the potential for the spectral differentiation of shrub types, and shrubs from grass, using multi-temporal, multi-spectral analysis.

  11. 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.

  12. Analysis of trends in fused AVHRR and MODIS NDVI data for 1982-2006: Indication for a CO2 fertilization effect in global vegetation

    Science.gov (United States)

    Los, S. O.

    2013-04-01

    Recent studies report an increase in vegetation greenness in mid-to-high northern latitudes. This increase is observed in leaf-out data in Europe and North America since the 1950s and in satellite data since the 1980s. Increased vegetation greenness is potentially a factor contributing to a land CO2 sink. Various causes for increased vegetation greenness are suggested, but their relative importance is uncertain. In the present study, the effect of climate and CO2 fertilization on increased vegetation greenness and the land CO2 sink are investigated. The study is organized as follows: (1) A model is used to simulate monthly global normalized difference vegetation index (NDVI) fields for 1901-2006. The model is derived from NDVI, precipitation, and temperature data for 1982-1999. The modeled fields, referred to as reconstructed vegetation index (RVI), are tested back in time on phenological data (1950s-1990s) and forward in time on Moderate Resolution Imaging Spectrometer (MODIS) data (2001-2006). The RVI represents the response of NDVI to variations in climate. (2) Residuals between RVI and NDVI are analyzed for associations with variations in downwelling solar radiation, nitrogen deposition, satellite-related artifacts, and CO2 fertilization. CO2 fertilization was the only factor that improved RVI modeling. (3) The effect of climate variations and CO2 fertilization on the land CO2 sink, as manifested in the RVI, is explored with the Carnegie Ames Stanford Assimilation (CASA) model. Climate (temperature and precipitation) and CO2 fertilization each explain approximately 40% of the observed global trend in NDVI for 1982-2006. For 1901-2006, estimated trends in NDVI related to CO2 fertilization are four to five times larger than climate-related trends. CASA simulations indicate that the CO2 fertilization effect on vegetation greenness contributes about 0.7 Pg C per year to the recent land CO2 sink. This is a conservative estimate and is likely larger. This effect of

  13. Can key vegetation parameters be retrieved at the large-scale using LAI satellite products and a generic modelling approach ?

    Science.gov (United States)

    Dewaele, Helene; Calvet, Jean-Christophe; Carrer, Dominique; Laanaia, Nabil

    2016-04-01

    In the context of climate change, the need to assess and predict the impact of droughts on vegetation and water resources increases. The generic approaches permitting the modelling of continental surfaces at large-scale has progressed in recent decades towards land surface models able to couple cycles of water, energy and carbon. A major source of uncertainty in these generic models is the maximum available water content of the soil (MaxAWC) usable by plants which is constrained by the rooting depth parameter and unobservable at the large-scale. In this study, vegetation products derived from the SPOT/VEGETATION satellite data available since 1999 are used to optimize the model rooting depth over rainfed croplands and permanent grasslands at 1 km x 1 km resolution. The inter-annual variability of the Leaf Area Index (LAI) is simulated over France using the Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) generic land surface model and a two-layer force-restore (FR-2L) soil profile scheme. The leaf nitrogen concentration directly impacts the modelled value of the maximum annual LAI. In a first step this parameter is estimated for the last 15 years by using an iterative procedure that matches the maximum values of LAI modelled by ISBA-A-gs to the highest satellite-derived LAI values. The Root Mean Square Error (RMSE) is used as a cost function to be minimized. In a second step, the model rooting depth is optimized in order to reproduce the inter-annual variability resulting from the drought impact on the vegetation. The evaluation of the retrieved soil rooting depth is achieved using the French agricultural statistics of Agreste. Retrieved leaf nitrogen concentrations are compared with values from previous studies. The preliminary results show a good potential of this approach to estimate these two vegetation parameters (leaf nitrogen concentration, MaxAWC) at the large-scale over grassland areas. Besides, a marked impact of the

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

    Directory of Open Access Journals (Sweden)

    María Amparo Gilabert

    2017-02-01

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

  15. Satellite images as primers to target priority areas for field surveys of indicators of ecological sustainability in tropical forests

    Science.gov (United States)

    Aguilar-Amuchastegui, Naikoa

    Sustainable management of tropical forests has been identified as one of the main objectives for global conservation of carbon stocks. In order to achieve this, managers need tools to establish whether or not their management practices are sustainable. Several tool development initiatives have undertaken the creation of sets of criteria and indicators to aid managers to target, if not achieve, sustainability. The question of how to assess these indicators remains to be answered from an operational viewpoint, where logistical constraints become critical and priorization becomes necessary. The present dissertation sought to determine whether satellite imagery can be used, in conjunction with standard forest management data, to identify priority areas for field surveys of indicators of ecological sustainability of managed tropical forests. It presents a novel approach to the assessment of CIFOR indicator I.2.1.2: "The change in diversity of habitats as a result of human interventions is maintained within critical limits as defined by natural variation and/or regional conservation objectives" by means of semivariography of remote sensing data. It shows the Wide Dynamic Range Vegetation Index (WDRVI) is a good alternative for the detection and quantification of tropical forests structural heterogeneity and its dynamic change. The differences observed between forest management units and natural areas forest structural heterogeneity were used to identify priority areas for field survey of ecological sustainability indicators and evaluate how these priorities were reflected in dung beetles community structure and composition. The link between forest structural heterogeneity dynamic change, forest logging intensity and dung beetle community structure and composition is established. A logging intensity threshold of 4 trees per hectare is identified as the limit between significant or not significant differences in forest structure dynamic changes and dung beetles community

  16. Modeling of Percentage of Canopy in Merawu Catchment Derived From Various Vegetation Indices of Remotely Sensed Data

    Directory of Open Access Journals (Sweden)

    Bambang Sulistyo

    2013-07-01

    Full Text Available The research was aimed at studying Percentage of Canopy mapping derived from various vegetation indices of remotely-sensed data int Merawu Catchment. Methodology applied was by analyzing remote sensing data of Landsat 7 ETM+ image to obtain various vegetation indices for correlation analysis with Percentage of Canopy measured directly on the field (PTactual at 48 locations. These research used 11 (eleven vegetation indices of remotely-sensed data, namely ARVI, MSAVI, TVI, VIF, NDVI, TSAVI, SAVI, EVI, RVI, DVI and PVI. The analysis resulted models (PTmodel for Percentage of Canopy mapping. The vegetation indices selected are those having high coefficient of correlation (>=0.80 to PTactual. Percentage of Canopy maps were validated using 39 locations on the field to know their accuracies. Percentage of Canopy map (PTmodel is said to be accurate when its coefficient of correlation value to PTactual is high (>=0.80. The research result in Merawu Catchment showed that from 11 vegetation indices under studied, there were 6 vegetation indices resulted high accuracy of Percentage of Canopy maps (as shown in the value of coefficient of correlation as >=0.80, i.e. TVI, VIF, NDVI, TSAVI, RVI dan SAVI, while the rest, namely ARVI, PVI, DVI, EVI and MSAVI, have r values of < 0.80.

  17. 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...

  18. How can satellite imagery be used for mineral exploration in thick vegetation areas?

    Science.gov (United States)

    Hede, Arie Naftali Hawu; Koike, Katsuaki; Kashiwaya, Koki; Sakurai, Shigeki; Yamada, Ryoichi; Singer, Donald A.

    2017-02-01

    The Hokuroku district, northern Japan, is globally recognized for rich ore deposits (kuroko and vein types), which have been thoroughly explored under thick vegetation cover. This situation is ideal to evaluate the effects of ore deposits on vegetation anomalies through geobotanical remote sensing. Here we present novel methods to detect vegetation anomalies caused by ore deposits and verify their usefulness by comparing the anomalies with a deposit potential map produced from multiple geological data. We use the reflectance spectra of Landsat ETM+ images acquired in summer and autumn to calculate a vegetation index for plant physiological activity. A key variable to detect the anomalies is a variation of vegetation index with time at each pixel. Difference in variation is enlarged by a sequence of image enhancement methods for the detection. We find that the vegetation anomalies, defined by the large ratios, correspond well to the high potential zones of ore deposits and known major deposits. Consequently, our methods can extend the applicability of remote sensing-based mineral exploration to the areas covered by thick vegetation, in addition to traditional arid and semiarid areas.

  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. The relationship between satellite-derived indices and species diversity across African savanna ecosystems

    Science.gov (United States)

    Mapfumo, Ratidzo B.; Murwira, Amon; Masocha, Mhosisi; Andriani, R.

    2016-10-01

    The ability to use remotely sensed diversity is important for the management of ecosystems at large spatial extents. However, to achieve this, there is still need to develop robust methods and approaches that enable large-scale mapping of species diversity. In this study, we tested the relationship between species diversity measured in situ with the Normalized Difference Vegetation Index (NDVI) and the Coefficient of Variation in the NDVI (CVNDVI) derived from high and medium spatial resolution satellite data at dry, wet and coastal savanna woodlands. We further tested the effect of logging on NDVI along the transects and between transects as disturbance may be a mechanism driving the patterns observed. Overall, the results of this study suggest that high tree species diversity is associated with low and high NDVI and at intermediate levels is associated with low tree species diversity and NDVI. High tree species diversity is associated with high CVNDVI and vice versa and at intermediate levels is associated with high tree species diversity and CVNDVI.

  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. Casa Grande Ruins National Monument Vegetation Mapping Project - Quickbird Satellite Imagery

    Data.gov (United States)

    National Park Service, Department of the Interior — This imagery was acquired on December 3, 2007 by DigitalGlobe, Inc.'s Quickbird satellite. Its 4 multispectral bands (blue, green, red, near infrared), together with...

  3. Evaluating interannual vegetation anomalies in the Basilicata region using satellite spot vegetation 1999-2011 time series: preliminary results from the Mitra project

    Science.gov (United States)

    Lasaponara, Rosa; Desantis, Fortunato; Aromando, Angelo; Lanorte, Antonio

    2013-04-01

    The Basilicata region funded a fesr project, MITRA to develop reliable low cost technologies to preserve and enhance natural and cultural heritage in some relevant areas selected as test cases. " Cultural heritage and the natural heritage are increasingly threatened with destruction not only by the traditional causes of decay, but also by changing social and economic conditions which aggravate the situation with even more formidable phenomena of damage or destruction, from THE GENERAL CONFERENCE of the United Nations Educational, Scientific and Cultural Organization meeting in Paris from 17 October to 21 November 1972, at its seventeenth session, available on line " (http://whc.unesco.org/en/conventiontext/). This paper is focused on the preliminary results obtained in the framework of the Mitra project. In particular, a temporal series (1999-2011) of the yearly Maximum Value Composit of SPOT/VEGETATION NDVI was used to carried out investigation on the whole Basilicata region. The PCA was used as a first step of data transform to enhance regions of localized change in multi-temporal data sets (Lasaponara 2006). Results from PCA were further processed using Support Vector machine (SVM) to identify and map land degradation phenomenon Both naturally vegetated areas (forest, shrub-land, herbaceous cover) and agricultural lands have been investigated in order to extract the most prominent natural and/or man induced alterations affecting vegetation behavior. Such analyses can provide valuable information for monitoring the status of vegetation which is an indicator of the degree of stress namely any disturbance that adversely influences plants in response to natural hazards and/or anthropogenic activities. Our findings suggest that the jointly use of PCA and SVM PCA can provide valuable information for environmental management policies involving biodiversity preservation and rational exploitation of natural and agricultural resources. Rosa Lasaponara 2006, On the use of

  4. 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....

  5. 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.

  6. Satellite remote sensing of rangelands in Botswana. II - NOAA AVHRR and herbaceous vegetation

    Science.gov (United States)

    Prince, S. D.; Tucker, C. J.

    1986-01-01

    The relation between the normalized difference vegetation index (NDVI) and the herbaceous vegetation in Tamasane, Shakwe, and Masama in eastern Botswana is studied using 1983-1984 AVHRR data. The procedures for Landsat MSS interpolation of ground measurements and the data processing of the AVHRR data are described. The temporal sequence AVHRR global-area coverage (GAC) composite NDVI is examined. The AVHRR GAC composite NDVI and biomass and Landsat MSS interpolations of field measurements are analyzed and compared.

  7. The use of climatic parameters and indices in vegetation distribution. A case study in the Spanish Sistema Central.

    Science.gov (United States)

    Gavilán, Rosario G

    2005-11-01

    In this study, over 100 phytoclimatic indices and other climatic parameters were calculated using the climatic data from 260 meteorological stations in a Mediterranean territory located in the centre of the Iberian Peninsula. The nature of these indices was very different; some of them expressed general climatic features (e.g. continentality), while others were formulated for different Mediterranean territories and included particular limits of those indices that expressed differences in vegetation distribution. We wanted to know whether all of these indices were able to explain changes in vegetation on a spatial scale, and whether their boundaries worked similarly to the original territory. As they were so numerous, we investigated whether any of them were redundant. To relate vegetation to climate parameters we preferred to use its hierarchical nature, in discrete units (characterized by one or more dominant or co-dominant species), although it is known to vary continuously. These units give clearer results in this kind of phytoclimatic study. We have therefore used the main communities that represent natural potential vegetation. Multivariate and estimative analyses were used as statistical methods. The classification showed different levels of correlation among climatic parameters, but all of them were over 0.5. One hundred and eleven parameters were grouped into five larger groups: temperature (T), annual pluviothermic indices (PTY), summer pluviothermic indices (SPT), winter potential evapotranspiration (WPET) and thermal continentality indices (K). The remaining parameters showed low correlations with these five groups; some of them revealed obvious spatial changes in vegetation, such as summer hydric parameters that were zero in most vegetation types but not in high mountain vegetation. Others showed no clear results. For example, the Kerner index, an index of thermal continentality, showed lower values than expected for certain particular types of

  8. NDVI from Landsat 8 Vegetation Indices to Study Movement Dynamics of Capra Ibex in Mountain Areas

    Science.gov (United States)

    Pirotti, F.; Parraga, M. A.; Stuaro, E.; Dubbini, M.; Masiero, A.; Ramanzin, M.

    2014-09-01

    In this study we analyse the correlation between the spatial positions of Capra ibex (mountain goat) on an hourly basis and the information obtained from vegetation indices extracted from Landsat 8 datasets. Eight individuals were tagged with a collar with a GNSS receiver and their position was recorded every hour since the beginning of 2013 till 2014 (still ongoing); a total of 16 Landsat 8 cloud-free datasets overlapped that area during that time period. All images were brought to a reference radiometric level and NDVI was calculated. To assess behaviour of animal movement, NDVI values were extracted at each position (i.e. every hour). A daily "area of influence" was calculated by spatially creating a convex hull perimeter around the 24 points relative to each day, and then applying a 120 m buffer (figure 4). In each buffer a set of 24 points was randomly chosen and NDVI values again extracted. Statistical analysis and significance testing supported the hypothesis of the pseudo-random NDVI values to be have, in average, lower values than the real NDVI values, with a p value of 0.129 for not paired t test and p value of < 0.001 for pairwise t test. This is still a first study which will go more in depth in near future by testing models to see if the animal movements in different periods of the year follow in some way the phenological stage of vegetation. Different aspects have to be accounted for, such as the behaviour of animals when not feeding (e.g. resting) and the statistical significance of daily distributions, which might be improved by analysing broader gaps of time.

  9. Satellites Based Annual Carbon Dynamics of Africa Tropical Vegetation During the 2003-2014 Period

    Science.gov (United States)

    Baccini, A.

    2015-12-01

    Tracking terrestrial carbon fluxes and predicting how tropical forests will respond to continuous global change requires accurate estimates of annual changes in the density and distribution of carbon stocks at local to global scales. Existing evidence for tropical forests as a carbon sink is based on a limited number of repeated field measurements (Phillips et al. 1998,Lewis et al. 2009, Brienen et al. 2015), while spatially explicit estimates over large areas are limited to emissions derived from deforestation without being able to account for degradation and gain (Harris et al. 2012, Hansen et al. 2013). Here we use 12 years (2003-2014) of satellite data to quantify wall-to-wall annual net changes in aboveground carbon density, showing that Africa tropical forests are a net carbon source on the order of 72.1 ± 32.9 Tg C yr-1. This net release of carbon consists of losses of 205.0 ± 24.7 Tg C yr1 and gains of -132.9 ± 19.3 Tg C yr1. The net gains result from forest growth; net losses result from both reductions in forest area due to deforestation and in biomass density within forests due to degradation; this last accounting overall for 68.9 % of the losses. We anticipate several advantages over the traditional estimates. It measures carbon lost from forest degradation as well as from deforestation. It measures the gains of carbon in forest growth. Data are available to determine annual changes with associated uncertainty. The approach focuses directly on changes in carbon. While global emissions from fossil fuel stabilized in 2014 for the first time in the past 40 years, results from this study indicate that the annual rate of emissions from tropical forests has tended upward over the latest years of the 2003-2014 period.

  10. Technical Note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation

    Directory of Open Access Journals (Sweden)

    E. Peled

    2010-02-01

    Full Text Available In the past years there have been many attempts to produce and improve global soil-moisture datasets and drought indices. However, comparing and validating these various datasets is not straightforward. Here, interannual variations in drought indices are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which drought index describes most realistically the actual changes in vegetation. Strong correlation between NDVI and the drought indices were found in areas that are classified as warm temperate climate with hot or warm dry summers. In these areas we ranked the PDSI, PSDI-SC, SPI3, and NSM indices, based on the interannual correlation with NDVI, and found that NSM outperformed the rest. Using this best performing index, and the ICA (Independent Component Analysis technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

  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. Vegetation Cover Change in the Upper Kings River Basin of the Sierra Nevada Detected Using Landsat Satellite Image Analysis

    Science.gov (United States)

    Potter, Christopher S.

    2015-01-01

    The Sierra Nevada of California is a region where large wildfires have been suppressed for over a century. A detailed geographic record of recent changes in vegetation cover across the Sierra Nevada remains a gap that can be filled with satellite remote sensing data. Results from Landsat image analysis over the past 25 years in the Upper Kings River basin showed that consistent, significant increases in the normalized difference vegetation index (NDVI) have not extended above 2000 m elevation, where cold temperatures presumably limit the growing season. Moreover, mean increases in NDVI since 1986 at elevations below 2000 m (which cover about half of the total basin area) have not exceeded 9%, even in the most extreme precipitation yearly comparisons. NDVI has decreased significantly at elevations above 2000 m throughout the basin in relatively wet year comparisons since the mid-1980s. These findings conflict with any assumptions that ET fluxes and river flows downstream could have been markedly altered by vegetation change over most of the Upper Kings River basin in recent decades.

  13. 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.

  14. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains.

    NARCIS (Netherlands)

    Kooistra, L.; Salas, E.A.; Clevers, J.G.; Wehrens, H.R.M.J.; Leuven, R.S.E.W.; Nienhuis, P.H.; Buydens, L.M.C.

    2004-01-01

    This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The rela

  15. Exploring field vegetation reflectance as an indicator of soil contamination in river floodplains

    NARCIS (Netherlands)

    Kooistra, L.; Salas, E.A.L.; Clevers, J.G.P.W.; Wehrens, H.R.M.J.; Leuven, R.S.E.W.; Nienhuis, P.H.; Buydens, L.M.C.

    2004-01-01

    This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The rela

  16. Comparison and Intercalibration of Vegetation Indices from Different Sensors for Monitoring Above-Ground Plant Nitrogen Uptake in Winter Wheat

    Directory of Open Access Journals (Sweden)

    Yan Zhu

    2013-03-01

    Full Text Available Various sensors have been used to obtain the canopy spectral reflectance for monitoring above-ground plant nitrogen (N uptake in winter wheat. Comparison and intercalibration of spectral reflectance and vegetation indices derived from different sensors are important for multi-sensor data fusion and utilization. In this study, the spectral reflectance and its derived vegetation indices from three ground-based sensors (ASD Field Spec Pro spectrometer, CropScan MSR 16 and GreenSeeker RT 100 in six winter wheat field experiments were compared. Then, the best sensor (ASD and its normalized difference vegetation index (NDVI (807, 736 for estimating above-ground plant N uptake were determined (R2 of 0.885 and RMSE of 1.440 g·N·m−2 for model calibration. In order to better utilize the spectral reflectance from the three sensors, intercalibration models for vegetation indices based on different sensors were developed. The results indicated that the vegetation indices from different sensors could be intercalibrated, which should promote application of data fusion and make monitoring of above-ground plant N uptake more precise and accurate.

  17. 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

    2010-06-23

    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.

  18. Calibrating Satellite-Based Indices of Burn Severity from UAV-Derived Metrics of a Burned Boreal Forest in NWT, Canada

    Directory of Open Access Journals (Sweden)

    Robert H. Fraser

    2017-03-01

    Full Text Available Wildfires are a dominant disturbance to boreal forests, and in North America, they typically cause widespread tree mortality. Forest fire burn severity is often measured at a plot scale using the Composite Burn Index (CBI, which was originally developed as a means of assigning severity levels to the Normalized Burn Ratio (NBR computed from Landsat satellite imagery. Our study investigated the potential to map biophysical indicators of burn severity (residual green vegetation and charred organic surface at very high (3 cm resolution, using color orthomosaics and vegetation height models derived from UAV-based photographic surveys and Structure from Motion methods. These indicators were scaled to 30 m resolution Landsat pixel footprints and compared to the post-burn NBR (post-NBR and differenced NBR (dNBR ratios computed from pre- and post-fire Landsat imagery. The post-NBR showed the strongest relationship to both the fraction of charred surface (exponential R2 = 0.79 and the fraction of green crown vegetation above 5 m (exponential R2 = 0.81, while the dNBR was more closely related to the total green vegetation fraction (exponential R2 = 0.69. Additionally, the UAV green fraction and Landsat indices could individually explain more than 50% of the variance in the overall CBI measured in 39 plots. These results provide a proof-of-concept for using low-cost UAV photogrammetric mapping to quantify key measures of boreal burn severity at landscape scales, which could be used to calibrate and assign a biophysical meaning to Landsat spectral indices for mapping severity at regional scales.

  19. Ecosystem evaluation (1989-2012) of Ramsar wetland Deepor Beel using satellite-derived indices.

    Science.gov (United States)

    Mozumder, Chitrini; Tripathi, N K; Tipdecho, Taravudh

    2014-11-01

    The unprecedented urban growth especially in developing countries has laid immense pressure on wetlands, finally threatening their existence altogether. A long-term monitoring of wetland ecosystems is the basis of planning conservation measures for a sustainable development. Deepor Beel, a Ramsar wetland and major storm water basin of the River Brahmaputra in the northeastern region of India, needs particular attention due to its constant degradation over the past decades. A rule-based classification algorithm was developed using Landsat (2011)-derived indices, namely Normalised Difference Water Index (NDWI), Modified Normalised Difference Water Index (MNDWI), Normalised Difference Pond Index (NDPI), Normalised Difference Vegetation Index (NDVI) and field data as ancillary information. Field data, ALOS AVNIR and Google Earth images were used for accuracy assessment. A fuzzy accuracy assessment of the classified data sets showed an overall accuracy of 82 % for MAX criteria and 90 % for RIGHT criteria. The rules were used to classify major wetland cover types during low water season (January) in 1989, 2001 and 2012. The statistical analysis of the classified wetland showed heavy manifestation in aquatic vegetation and other features indicating severe eutrophication over the past 23 years. This degradation was closely related to major contributing anthropogenic factors, such as a railway line construction, growing croplands, waste disposal and illegal human settlements in the wetland catchment. In addition, the landscape development index (LDI) indicated a rapid increase in the impact of the surrounding land use on the wetland from 1989 to 2012. The techniques and results from this study may prove useful for top-down landscape analyses of this and other freshwater wetlands.

  20. Analysis of Geosynchronous Satellite-air Bistatic SAR Clutter Characteristics from the Point of View of Ground Moving Target Indication

    Directory of Open Access Journals (Sweden)

    Zhang Dan-dan

    2013-09-01

    Full Text Available Under the geometry of geosynchronous satellite-air bistatic SAR where the geosynchronous satellite is the transmitter and aerostat is the receiver, in order to suppress clutter and detect slowly moving target using Space Time Adaptive Processing (STAP, it is necessary to analyze the clutter characteristics. From the point of view of ground moving target indication, the theory model of the clutter characteristics under the geometry of geosynchronous satellite-space bistatic SAR is analyzed and established in this paper; especially, the range-dependence characteristics of the angle-Doppler curve of the clutter is analyzed. Finally, the simulation verifies correctness of the analysis. The theory model and the conclusion in this paper indicates the clutter characteristics of the new geosynchronous satellite-air bistatic SAR mode, and provide theory basis for the selection and research of ground moving target indication method under this mode.

  1. 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 ar

  2. Mapping crop evapotranspiration by integrating vegetation indices into a soil water balance model

    Science.gov (United States)

    Consoli, Simona; Vanella, Daniela

    2015-04-01

    The approach combines the basal crop coefficient (Kcb) derived from vegetation indices (VIs) with the daily soil water balance, as proposed in the FAO-56 paper, to estimate daily crop evapotranspiration (ETc) rates of orange trees. The reliability of the approach to detect water stress was also assessed. VIs were simultaneously retrieved from WorldView-2 imagery and hyper-spectral data collected in the field for comparison. ETc estimated were analysed at the light of independent measurements of the same fluxes by an eddy covariance (EC) system located in the study area. The soil water depletion in the root zone of the crop simulated by the model was also validated by using an in situ soil water monitoring. Average overestimate of daily ETc of 6% was obtained from the proposed approach with respect to EC measurements, evidencing a quite satisfactory agreement between data. The model also detected several periods of light stress for the crop under study, corresponding to an increase of the root zone water deficit matching quite well the in situ soil water monitoring. The overall outcomes of this study showed that the FAO-56 approach with remote sensing-derived basal crop coefficient can have the potential to be applied for estimating crop water requirements and enhancing water management strategies in agricultural contexts.

  3. 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.

  4. Satellite observations indicate rapid warming trend for lakes in California and Nevada

    Science.gov (United States)

    Schneider, P.; Hook, S. J.; Radocinski, R. G.; Corlett, G. K.; Hulley, G. C.; Schladow, S. G.; Steissberg, T. E.

    2009-11-01

    Large lake temperatures are excellent indicators of climate change; however, their usefulness is limited by the paucity of in situ measurements and lack of long-term data records. Thermal infrared satellite imagery has the potential to provide frequent and accurate retrievals of lake surface temperatures spanning several decades on a global scale. Analysis of seventeen years of data from the Along-Track Scanning Radiometer series of sensors and data from the Moderate Resolution Imaging Spectroradiometer shows that six lakes situated in California and Nevada have exhibited average summer nighttime warming trends of 0.11 ± 0.02°C yr-1 (p < 0.002) since 1992. A comparison with air temperature observations suggests that the lake surface temperature is warming approximately twice as fast as the average minimum surface air temperature.

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

    Directory of Open Access Journals (Sweden)

    Antonius G T Schut

    Full Text Available Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010 derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity.

  6. Satellite detection of Northern Hemisphere Non-Frozen season changes and associated impacts to vegetation growing seasons

    Science.gov (United States)

    Kim, Y.; Kimball, J. S.; Zhang, K.; McDonald, K. C.

    2011-12-01

    The landscape freeze-thaw (FT) signal from satellite microwave remote sensing is closely linked to vegetation phenology, productivity and land-atmosphere trace gas exchange where seasonal frozen temperatures are a major constraint to plant growth. We applied a temporal change classification of 37 GHz, vertically polarized brightness temperature (Tb) measurements from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) to classify daily FT status over global land areas where seasonal frozen temperatures influence ecosystem processes. A temporally consistent, long-term (>30 year) FT record was created ensuring cross-sensor consistency through pixel-wise adjustment of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements. The resulting FT record showed mean annual spatial classification accuracies of 91 (+/-8.6) and 84 (+/-9.3) percent for PM and AM overpass retrievals relative to air temperature measurements from global weather stations. The FT results were also compared against other measures of biosphere activity including satellite derived vegetation greenness (NDVI) and terrestrial net primary productivity (NPP), tower CO2 flux measurements and seasonal patterns of atmospheric CO2 concentrations from northern (>50°N) monitoring sites. A strong (P45°N) latitudes and upper elevations. The FT record also shows a positive (0.199 days yr-1) trend in the number of transitional (AM frozen and PM non-frozen) frost days, resulting in reduced photosynthetic activity inferred from tower and NDVI measurements. The relative benefits of earlier and longer non-frozen seasons for vegetation growth and productivity under global warming may be declining due to opposing increases in disturbance, drought and frost damage related impacts. Portions of this work were conducted at the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space

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

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard

    index (NDVI), which combines red and near infrared (NIR) spectral regions. From NDVI data a greening of the Sahel have been identified since the 80s and attributed to increasing trends in annual rainfall for large parts of the region. One part of this thesis analyses time series of parameterized MODIS...... that the varying NPP/NDVI relationships, combined with the large increase in livestock of the Sahel in recent decades, means that the greening of the Sahel cannot uncritically be interpreted as a positive trend in vegetation productivity due to increasing rainfall. It can also represent grazing induced changes...... in species composition which covers neutral or even decreasing trends in biomass production. For monitoring vegetation status on a shorter time scale in the Sahel, the NDVI may not be the most appropriate index. From previous research it has been suggested that the Shortwave infrared (SWIR) spectral region...

  9. The application of very high resolution satellite image in urban vegetation cover investigation: a case study of Xiamen City

    Institute of Scientific and Technical Information of China (English)

    CHENGChengqi; LiBin; MATing

    2003-01-01

    With the technological improvements of satellite sensors, we will acquire more information about the earth so that we have reached a new application epoch of observation on earth environmental change and cartography. But with the enhancement of spatial resolution, some questions have arisen in the application of using traditional image processing and classification methods. Aiming for such questions, we studied the application of IKONOS very high resolution image (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the difference between the very high resolution image and traditional low spatial resolution image at classification,information abstraction etc. It is an advantageous test for the large-scale application of very high resolution data in the future.

  10. Cross-Comparison of Vegetation Indices Derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+ and Landsat-8 Operational Land Imager (OLI Sensors

    Directory of Open Access Journals (Sweden)

    Peng Li

    2013-12-01

    Full Text Available Landsat-7 Enhanced Thematic Mapper Plus (ETM+ and Landsat-8 Operational Land Imager (OLI and Thermal Infrared Sensor (TIRS are currently operational for routine Earth observation. There are substantial differences between instruments onboard both satellites. The enhancements achieved with Landsat-8 refer to the scanning technology (replacing of whisk-broom scanners with two separate push-broom OLI and TIRS scanners, an extended number of spectral bands (two additional bands provided and narrower bandwidths. Therefore, cross-comparative analysis is very necessary for the combined use of multi-decadal Landsat imagery. In this study, 3,311 independent sample points of four major land cover types (primary forest, unplanted cropland, swidden cultivation and water body were used to compare the spectral bands of ETM+ and OLI. Eight sample plots with different land cover types were manually selected for comparison with the Normalized Difference Vegetation Index (NDVI, the Modified Normalized Difference Water Index (MNDWI, the Land Surface Water Index (LSWI and the Normalized Burn Ratio (NBR. These indices were calculated with six pairs of ETM+ and OLI cloud-free images, which were acquired over the border area of Myanmar, Laos and Thailand just two days apart, when Landsat-8 achieved operational obit. Comparative results showed that: (1 the average surface reflectance of each band differed slightly, but with a high degree of similarities between both sensors. In comparison with ETM+, the OLI had higher values for the near-infrared band for vegetative land cover types, but lower values for non-vegetative types. The new sensor had lower values for the shortwave infrared (2.11–2.29 µm band for all land cover types. In addition, it also basically had higher values for the shortwave infrared (1.57–1.65 µm band for non-water land cover types. (2 The subtle differences of vegetation indices derived from both sensors and their high linear correlation

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

    Directory of Open Access Journals (Sweden)

    Dirk Hoyer

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

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

    Directory of Open Access Journals (Sweden)

    Nora Tilly

    2015-09-01

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

  13. 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

  14. Constraints from atmospheric CO2 and satellite-based vegetation activity observations on current land carbon cycle trends

    Directory of Open Access Journals (Sweden)

    S. Zaehle

    2012-11-01

    Full Text Available Terrestrial ecosystem models used for Earth system modelling show a significant divergence in future patterns of ecosystem processes, in particular carbon exchanges, despite a seemingly common behaviour for the contemporary period. An in-depth evaluation of these models is hence of high importance to achieve a better understanding of 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 firm 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 the uncertainties in both data and evaluation analysis. In addition, we provide a baseline benchmark, a minimum test that the model under consideration 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 to pinpoint specific model failures that would not be possible by the sole use of atmospheric CO2 observations.

  15. Comparison of Different Vegetation Indices for Very High-Resolution Images, Specific Case Ultracam-D Imagery

    Science.gov (United States)

    Barzegar, M.; Ebadi, H.; Kiani, A.

    2015-12-01

    Today digital aerial images acquired with UltraCam sensor are known to be a valuable resource for producing high resolution information of land covers. In this research, different methods for extracting vegetation from semi-urban and agricultural regions were studied and their results were compared in terms of overall accuracy and Kappa statistic. To do this, several vegetation indices were first tested on three image datasets with different object-based classifications in terms of presence or absence of sample data, defining other features and also more classes. The effects of all these cases were evaluated on final results. After it, pixel-based classification was performed on each dataset and their accuracies were compared to optimum object-based classification. The importance of this research is to test different indices in several cases (about 75 cases) and to find the quantitative and qualitative effects of increasing or decreasing auxiliary data. This way, researchers who intent to work with such high resolution data are given an insight on the whole procedure of detecting vegetation species as one of the outstanding and common features from such images. Results showed that DVI index can better detect vegetation regions in test images. Also, the object-based classification with average 93.6% overall accuracy and 86.5% Kappa was more suitable for extracting vegetation rather than the pixel-based classification with average 81.2% overall accuracy and 59.7% Kappa.

  16. COMPARISON OF DIFFERENT VEGETATION INDICES FOR VERY HIGH-RESOLUTION IMAGES, SPECIFIC CASE ULTRACAM-D IMAGERY

    Directory of Open Access Journals (Sweden)

    M. Barzegar

    2015-12-01

    Full Text Available Today digital aerial images acquired with UltraCam sensor are known to be a valuable resource for producing high resolution information of land covers. In this research, different methods for extracting vegetation from semi-urban and agricultural regions were studied and their results were compared in terms of overall accuracy and Kappa statistic. To do this, several vegetation indices were first tested on three image datasets with different object-based classifications in terms of presence or absence of sample data, defining other features and also more classes. The effects of all these cases were evaluated on final results. After it, pixel-based classification was performed on each dataset and their accuracies were compared to optimum object-based classification. The importance of this research is to test different indices in several cases (about 75 cases and to find the quantitative and qualitative effects of increasing or decreasing auxiliary data. This way, researchers who intent to work with such high resolution data are given an insight on the whole procedure of detecting vegetation species as one of the outstanding and common features from such images. Results showed that DVI index can better detect vegetation regions in test images. Also, the object-based classification with average 93.6% overall accuracy and 86.5% Kappa was more suitable for extracting vegetation rather than the pixel-based classification with average 81.2% overall accuracy and 59.7% Kappa.

  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. Monitoring Vegetation Phenological Cycles in Two Different Semi-Arid Environmental Settings Using a Ground-Based NDVI System: A Potential Approach to Improve Satellite Data Interpretation

    Directory of Open Access Journals (Sweden)

    Malika Baghzouz

    2010-04-01

    Full Text Available In semi-arid environmental settings with sparse canopy covers, obtaining remotely sensed information on soil and vegetative growth characteristics at finer spatial and temporal scales than most satellite platforms is crucial for validating and interpreting satellite data sets. In this study, we used a ground-based NDVI system to provide continuous time series analysis of individual shrub species and soil surface characteristics in two different semi-arid environmental settings located in the Great Basin (NV, USA. The NDVI system was a dual channel SKR-1800 radiometer that simultaneously measured incident solar radiation and upward reflectance in two broadband red and near-infrared channels comparable to Landsat-5 TM band 3 and band 4, respectively. The two study sites identified as Spring Valley 1 site (SV1 and Snake Valley 1 site (SNK1 were chosen for having different species composition, soil texture and percent canopy cover. NDVI time-series of greasewood (Sarcobatus vermiculatus from the SV1 site allowed for clear distinction between the main phenological stages of the entire growing season during the period from January to November, 2007. NDVI time series values were significantly different between sagebrush (Artemisia tridentata and rabbitbrush (Chrysothamnus viscidiflorus at SV1 as well as between the two bare soil types at the two sites. Greasewood NDVI from the SNK1 site produced significant correlations with chlorophyll index (r = 0.97, leaf area index (r = 0.98 and leaf xylem water potential (r = 0.93. Whereas greasewood NDVI from the SV1 site produced lower correlations (r = 0.89, r = 0.73, or non significant correlations (r = 0.32 with the same parameters, respectively. Total percent cover was estimated at 17.5% for SV1 and at 63% for SNK1. Results from this study indicated the potential capabilities of using this ground-based NDVI system to extract spatial and temporal details of soil and vegetation optical properties not possible

  19. LSA-SAF evapotranspiration products based on MSG/SEVIRI: improvement opportunities from moderate spatial resolution satellites sensors for vegetation (SPOT-VGT, MODIS, PROBA-V)

    Science.gov (United States)

    Ghilain, N.; De Roo, F.; Arboleda, A.; Gellens-Meulenberghs, F.

    2012-04-01

    The Satellite Application Facility on Land Surface Analysis (LSA-SAF) proposes a panel of land surface related products derived from the EUMETSAT satellites, MSG (Meteosat Second Generation) and EPS/METOP, and produced in near-real time over Europe, Africa and part of South America. With LSA-SAF products, key surface variables are observed, and allows to characterizing the main processes governing land atmosphere processes. Land evapotranspiration (ET) is one of the variables monitored within LSA-SAF. ET at a spatial resolution of approximately 3 km at the sub-satellite point above the equator is derived in near-real time, every 30 minutes, using a simplified land surface model, forced by LSA-SAF radiation products derived from MSG/SEVIRI data. Given that spatial resolution, some smaller scale processes cannot be resolved, though their contribution may affect the total MSG pixel area ET estimates. Besides, information with an increased resolution is expected to have a positive impact on the total accuracy of the modeled ET. A variety of new remote sensing products derived from EO data at a higher spatial resolution are now publicly available. This is an opportunity to assess the improvement that moderate spatial resolution (250 m to 1 km) satellites sensors for surface and vegetation characterization could offer to the evapotranspiration monitoring at the MSG/SEVIRI scale in the context of LSA-SAF. On the basis of a global analysis and on test cases, we show the usefulness of EO data acquired from moderate resolution satellites sensors (SPOT-VGT, MODIS/Terra&Aqua, MERIS) towards the improvement of the LSA-SAF ET products derived from MSG/SEVIRI. In particular, 4 different variables/indices (land cover map, LAI, surface albedo, open water bodies detection) are assessed regarding the LSA-SAF ET products: 1) the investigated processes at small scales unresolved by the geostationary satellite, e.g. open water bodies dynamics, are better taken into account in the final

  20. 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

  1. 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.

  2. Impact analysis of pansharpening Landsat ETM+, Landsat OLI, WorldView-2, and Ikonos images on vegetation indices

    Science.gov (United States)

    Jovanović, Dušan; Govedarica, Miro; Sabo, Filip; Važić, Radmila; Popović, Dragana

    2016-08-01

    The aim of our study was to verify the impact that pansharpening (PS) methods produce on vegetation indices. We used images with both moderate (Landsat 7, Landsat 8) and high (World View2, Ikonos) spatial resolution on which we performed three methods of PS (Brovey transform, Gram-Schmidt and Principal component). The study is based on the differences of vegetation indices (VI) values before and after the pansharpening method is applied. The difference is quantified as an root mean square error. Vegetation indices used in this study were: NDVI, MSAVI2, EVI2, GNDVI, OSAVI and SAVI. Statistical analysis is carried out by calculating coefficients of correlation, root mean square errors and bias calculations for every vegetation index before and after pansharpening procedure is done. The results imply that the BT gave the most diverse results between original VI values and the PS VI values, while the GS and PC methods preserved the values of pixel bands, and that the effect of any PS method is most evident when using Ikonos bands.

  3. Narrow-band and derivative-based vegetation indices for hyperspectral data

    NARCIS (Netherlands)

    Thorp, K.R.; Tian, L.F.; Yao, H.; Tang, L.

    2004-01-01

    Hyperspectral remote sensing imagery was collected over a soybean field in central Illinois in mid-June 2001 before canopy closure. Estimates of percent vegetation cover were generated through the processing of RGB (red, green, blue) digital images collected on the ground with an automated crop mapp

  4. Visual processing during recovery from vegetative state to consciousness: Comparing behavioral indices to brain responses

    NARCIS (Netherlands)

    Wijnen, V.J.; Eilander, H.J.; Gelder, B. de; Boxtel, G.J. Van

    2014-01-01

    BACKGROUND: Auditory stimulation is often used to evoke responses in unresponsive patients who have suffered severe brain injury. In order to investigate visual responses, we examined visual evoked potentials (VEPs) and behavioral responses to visual stimuli in vegetative patients during recovery to

  5. 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.

  6. Satellite-observed changes in vegetation sensitivities to surface soil moisture and total water storage variations since the 2011 Texas drought

    Science.gov (United States)

    A, Geruo; Velicogna, Isabella; Kimball, John S.; Du, Jinyang; Kim, Youngwook; Colliander, Andreas; Njoku, Eni

    2017-05-01

    We combine soil moisture (SM) data from AMSR-E and AMSR-2, and changes in terrestrial water storage (TWS) from time-variable gravity data from GRACE to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE-derived TWS provides spatially continuous observations of changes in overall water supply and regional drought extent, persistence and severity, while satellite-derived SM provides enhanced delineation of shallow-depth soil water supply. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depths in relation to satellite-based enhanced vegetation index (EVI) and gross primary productivity (GPP) from MODIS and solar-induced fluorescence (SIF) from GOME-2, during and following major drought events observed in the state of Texas, USA and its surrounding semiarid area for the past decade. We find that in normal years the spatial pattern of the vegetation-moisture relationship follows the gradient in mean annual precipitation. However since the 2011 hydrological drought, vegetation growth shows enhanced sensitivity to surface SM variations in the grassland area located in central Texas, implying that the grassland, although susceptible to drought, has the capacity for a speedy recovery. Vegetation dependency on TWS weakens in the shrub-dominated west and strengthens in the grassland and forest area spanning from central to eastern Texas, consistent with changes in water supply pattern. We find that in normal years GRACE TWS shows strong coupling and similar characteristic time scale to surface SM, while in drier years GRACE TWS manifests stronger persistence, implying longer recovery time and prolonged water supply constraint on vegetation growth. The synergistic combination of GRACE TWS and surface SM, along with remote-sensing vegetation observations provides new insights into drought impact on

  7. Biophysical indicators based on satellite images in an irrigated area at the São Francisco River Basin, Brazil

    Science.gov (United States)

    Leivas, Janice F.; Teixeira, Antônio Heriberto C.; Bayma-Silva, Gustavo; Ronquim, Carlos Cesar; Ribeiro da Silva Reis, João. Batista

    2016-10-01

    The Jaíba Irrigated Perimeter is a large irrigated agriculture area, located in the region Forest Jaíba between the São Francisco and Verde Grande rivers, in the Brazilian semi-arid region. In 2014, irrigators this the region face losses in the interruption of new plantings in irrigated areas due to water scarcity. The objective of this study is combine the model to estimate the Monteith BIO with the SAFER algorithm in the case of obtaining ET, to analyze the dynamics of natural vegetation and irrigated crops in water scarcity period. For application of the model are necessary data from meteorological stations and satellite images. Were used 23 satellite images of MODIS with spatial resolution of 250m and temporal 16 days, of 2014 year. For analyze the results, we used central pivots irrigation mask of Minas Gerais state, Brazil. In areas with irrigated agriculture with central pivot, the mean values of BIO over the year 2014 were 88.96 kg.ha-1.d-1. The highest values occurred between April 23 and May 8, with BIO 139 kg.ha-1.d-1. For areas with natural vegetation, the average BIO was 88.34 kg.ha-1.d-1 with lower values in September. Estimates of ET varied with the lowest values of ET observed in natural vegetation 1.91+/-1.22 mm.d-1 and the highest values in irrigated area is observed 3.51+/-0.97 mm.d-1. Results of this study can assist in monitoring of river basins, contributing to the management irrigated agriculture, with the trend of scarcity of water resources and increasing conflicts for the water use.

  8. Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

    Directory of Open Access Journals (Sweden)

    Wenwen Cai

    2014-09-01

    Full Text Available Terrestrial gross primary production (GPP is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000–2010 varied from 95.10 to 139.71 Pg C∙yr−1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. Dust indicator maps for improving solar radiation estimation from satellite data

    Science.gov (United States)

    Marpu, P. R.; Eissa, Y.; Al Meqbali, N.; Ghedira, H.

    2012-12-01

    Measurement of solar radiation from ground-based sensors is an expensive process as it requires large number of ground measurement stations to account for the spatial variability. Moreover, the instruments require regular maintenance. Satellite data can be used to model solar radiation and produce maps in regular intervals, which can be used for solar resource assessment. The models can either be empirical, physics-based or statistical models. However, in environments such as the United Arab Emirates (UAE) which are characterized by heavy dust, the results obtained by the models will lead to lower accuracies. In this study, we build on the model developed in [1], where ensembles of ANNs are used separately for cloudy and cloud-free pixels to derive solar radiation maps using the data acquired in the thermal channels of the Meteosat SEVIRI instrument. The model showed good accuracies for the estimation of direct normal irradiance (DNI), diffuse horizontal irradiance (DHI) and global horizontal irradiance (GHI); where the relative root mean square error (rRMSE) values for the DNI, DHI and GHI were 15.7, 23.6 and 7.2%, respectively, while the relative mean bias error (rMBE) values were +0.8, +8.3 and +1.9%, respectively. However, an analysis of the results on different dusty days showed varying accuracy. To further improve the model, we propose to use the dust indicator maps as inputs to the model. An interception index was proposed in [2] to detect dust over desert regions using visible channels of the SEVIRI instrument. The index has a range of 0 to 1 where the value of 1 corresponds to heavy dust and 0 corresponds to clear conditions. There is ongoing work to use the measurements from AERONET stations to derive dust indicator maps based on canonical correlation analysis, which relates the thermal channels to the aerosol optical depth (AOD) derived at different wavelengths from the AERONET measurements. There is also an ongoing work to analyze the time series of the

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

    DEFF Research Database (Denmark)

    Olsen, Jørgen Lundegaard

    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...

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

    NARCIS (Netherlands)

    Shariati Najafabadi, M.; Darvishzadeh, R.; Skidmore, A.K.; Kölzsch, A.; Vrieling, A.; Nolet, B.A.; Exo, K.; Meratnia, N.; Havinga, P.J.M.; Stahl, J.; 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 satellite-deri

  13. 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

  14. Technical Note: Comparing and ranking soil-moisture indices performance over Europe, through remote-sensing of vegetation

    OpenAIRE

    Peled, E.; Dutra, E.; Viterbo, P; A. Angert

    2009-01-01

    Climate change induces long-term changes in soil-moisture. These changes can have important effects on the terrestrial biosphere, which can feedback into the climate system. In the past years there have been many attempts to produce and improve global soil-moisture datasets, however, comparing and validating these various datasets is not an easy task. Here, interannual variations in indices of soil moisture are compared to interannual changes in vegetation, as captured by NDVI. By comparing t...

  15. 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.

  16. 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.

  17. Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA/CHRIS Data Over an Agricultural Area

    Directory of Open Access Journals (Sweden)

    Pablo Martinez

    2009-02-01

    Full Text Available In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC retrieval from Compact High Resolution Imaging Spectrometer (CHRIS data onboard the European Space Agency (ESA Project for On-Board Autonomy (PROBA platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs, in particular the Normalized Difference Vegetation Index (NDVI and the Variable Atmospherically Resistant Index (VARI. The second methodology is based on the Spectral Mixture Analysis (SMA technique, in which a Linear Spectral Unmixing model has been considered in order to retrieve the abundance of the different constituent materials within pixel elements, called Endmembers (EMs. These EMs were extracted from the image using three different methods: i manual extraction using a land cover map, ii Pixel Purity Index (PPI and iii Automated Morphological Endmember Extraction (AMEE. The different methodologies for FVC retrieval were applied to one PROBA/CHRIS image acquired over an agricultural area in Spain, and they were calibrated and tested against in situ measurements of FVC estimated with hemispherical photographs. The results obtained from VIs show that VARI correlates better with FVC than NDVI does, with standard errors of estimation of less than 8% in the case of VARI and less than 13% in the case of NDVI when calibrated using the in situ measurements. The results obtained from the SMA-LSU technique show Root Mean Square Errors (RMSE below 12% when EMs are extracted from the AMEE method and around 9% when extracted from the PPI method. A RMSE value below 9% was obtained for manual extraction of EMs using a land cover use map.

  18. On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

    Science.gov (United States)

    Kingfield, D.; de Beurs, K.

    2014-12-01

    It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

  19. 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

  20. 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 d

  1. 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

  2. Monitoring and Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and In-situ Observations.

    Science.gov (United States)

    A, G.; Velicogna, I.; Kimball, J. S.; Kim, Y.; Colliander, A.; Njoku, E. G.

    2015-12-01

    We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE, in-situ groundwater measurements and atmospheric moisture data to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depth in relation to satellite based vegetation metrics, including vegetation greenness (NDVI) measures from MODIS and related higher order productivity (GPP) before, during and following the major drought events observed in the continental US for the past 14 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, NDVI and GPP. We study how changes in atmosphere moisture stress and coupling of water storage components at different depth impact on the spatial and temporal correlation between TWS, SM and vegetation metrics. In Texas, we find that surface SM and GRACE TWS agree with each other in general, and both capture the underlying water supply constraints to vegetation growth. Triggered by a transit increase in precipitation following the 2011 hydrological drought, vegetation productivity in Texas shows more sensitivity to surface SM than TWS. In the Great Plains, the correspondence between TWS and vegetation productivity is modulated by temperature-induced atmosphere moisture stress and by the coupling between surface soil moisture and groundwater through irrigation.

  3. 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.

  4. Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and Precipitation Observations

    Science.gov (United States)

    A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Njoku, E. G.; Colliander, A.

    2016-12-01

    We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE and precipitation measurements from GPCP to delineate and characterize drought and water supply pattern and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply and have important implications for water resource management. We use these data to investigate the supply changes from different water components in relation to satellite based vegetation productivity metrics from MODIS, before, during and following the major drought events observed in the continental US during the past 13 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, and vegetation productivity. In Texas and surrounding semi-arid areas, we find that the spatial pattern of the vegetation-moisture relation follows the gradient in mean annual precipitation. In Texas, GRACE TWS and surface SM show strong coupling and similar characteristic time scale in relatively normal years, while during the 2011 onward hydrological drought, GRACE TWS manifests a longer time scale than that of surface SM, implying stronger drought persistence in deeper water storage. In the Missouri watershed, we find a spatially varying vegetation-moisture relationship where in the drier northwestern portion of the basin, the inter-annual variability in summer vegetation productivity is closely associated with changes in carry-on GRACE TWS from spring, whereas in the moist southeastern portion of the basin, summer precipitation is the dominant controlling factor on vegetation growth.

  5. Satellite observations indicate substantial spatiotemporal variability in biomass burning NOx emission factors for South America

    Directory of Open Access Journals (Sweden)

    P. Castellanos

    2013-08-01

    Full Text Available Biomass burning is an important contributor to global total emissions of NOx (NO + NO2. Generally bottom-up fire emissions models calculate NOx emissions by multiplying fuel consumption estimates with static biome specific emission factors, defined in units of grams of NO per kilogram of dry matter consumed. Emission factors are a significant source of uncertainty in bottom-up fire emissions modeling because relatively few observations are available to characterize the large spatial and temporal variability of burning conditions. In this paper we use NO2 tropospheric column observations from the Ozone Monitoring Instrument (OMI from the year 2005 over South America to calculate monthly NOx emission factors for four fire types: deforestation, savanna/grassland, woodland, and agricultural waste burning. In general, the spatial trends in NOx emission factors calculated in this work are consistent with emission factors derived from in situ measurements from the region, but are more variable than published biome specific global average emission factors widely used in bottom up fire emissions inventories such as the Global Fire Emissions Database (GFED v3. Satellite based NOx emission factors also indicate substantial temporal variability in burning conditions. Overall, we found that deforestation fires have the lowest NOx emission factors, on average 30 % lower than the emission factors used in GFED v3. Agricultural fire NOx emission factors were the highest, on average a factor of 2 higher than GFED v3 values. For savanna, woodland, and deforestation fires early dry season NOx emission factors were a factor of ~1.5–2.0 higher than late dry season emission factors. A minimum in the NOx emission factor seasonal cycle for deforestation fires occurred in August, the time period of severe drought in South America in 2005. Our results support the hypothesis that prolonged dry spells may lead to an increase in the contribution of smoldering combustion

  6. 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...... 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...... 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...

  7. Identifying woody vegetation on coal surface mines using phenological indicators with multitemporal Landsat imagery

    Science.gov (United States)

    Oliphant, A. J.; Li, J.; Wynne, R. H.; Donovan, P. F.; Zipper, C. E.

    2014-11-01

    Surface mining for coal has disturbed large land areas in the Appalachian Mountains. Better information on mined lands' ecosystem recovery status is necessary for effective environmental management in mining-impacted regions. Because record quality varies between state mining agencies and much mining occurred prior to widespread use of geospatial technologies, accurate maps of mining extents, durations, and land cover effects are often not available. Landsat data are well suited to mapping and characterizing land cover and forest recovery on former coal surface mines. Past mine reclamation techniques have often failed to restore premining forest vegetation but natural processes may enable native forests to re-establish on mined areas with time. However, the invasive species autumn olive (Elaeagnus umbellate) is proliferating widely on former coal surface mines, often inhibiting reestablishment of native forests. Autumn olive outcompetes native vegetation because it fixes atmospheric nitrogen and benefits from a longer growing season than native deciduous trees. This longer growing season, along with Landsat 8's high signal to noise ratio, has enabled species-level classification of autumn olive using multitemporal Landsat 8 data at accuracy levels usually only obtainable using higher spatial or spectral resolution sensors. We have used classification and regression tree (CART®) and support vector machine (SVM) to classify five counties in the coal mining region of Virginia for presence and absence of autumn olive. The best model found was a CART® model with 36 nodes which had an overall accuracy of 84% and kappa of 0.68. Autumn olive had conditional kappa of 0.65 and a producers and users accuracy of 86% and 83% respectively. The best SVM model used a second order polynomial kernel and had an overall accuracy of 77%, an overall kappa of 0.54 and a producers and users accuracy of 60% and 90% respectively.

  8. Investigation of the recent recolonisation of Beech on Mont Ventoux using historical records, vegetation analyses from satellite image and landscape genetics

    OpenAIRE

    Prouillet-Leplat, Hélène

    2009-01-01

    In this study, we investigated the genetic structure and the recolonisation process of the European beech (Fagus sylvatica) over the north face of the Mont Ventoux Mountain, using of combination of historical record investigation, vegetation mapping from satellite image and unsupervised classification process, and a landscape genetic approach. Mont Ventoux has undergone large deforestation phases until the XIXth century due to over-grazing and over-logging for woof supply. Historical records ...

  9. 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.

  10. Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment.

    Science.gov (United States)

    Cole, Ella F; Long, Peter R; Zelazowski, Przemyslaw; Szulkin, Marta; Sheldon, Ben C

    2015-11-01

    Population-level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite-derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green-up for a 385-ha mixed-deciduous woodland. Using data spanning 13 years, we demonstrate that annual population-level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite-derived spring vegetation phenology. We go on to show that timing of local vegetation green-up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote-sensed vegetation phenology and reproductive phenology in both species. Marked within-population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small-scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within-population variation

  11. 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

  12. 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

  13. Satellite derived integrated water vapor and rain intensity patterns - Indicators of rapid cyclogenesis

    Science.gov (United States)

    Mcmurdie, Lynn; Katsaros, Kristina

    1992-01-01

    We examine integrated water vapor fields and rain intensity patterns derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) for several rapidly deepening and non-rapidly deepening midlatitude cyclones in the North Atlantic. Our goal is to identify features in the satellite data unique to the rapidly deepening cases, and to explore how these data can potentially be used in the analysis and forecasting of these events.

  14. Satellite derived integrated water vapor and rain intensity patterns: Indicators of rapid cyclogenesis

    Science.gov (United States)

    Mcmurdie, Lynn; Katsaros, Kristina

    1992-01-01

    We examine integrated water vapor fields and rain intensity patterns derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) for several rapidly deepening and non-rapidly deepening midlatitude cyclones in the North Atlantic. Our goal is to identify features in the satellite data unique to the rapidly deepening cases, and to explore how these data can potentially be used in the analysis and forecasting of these events.

  15. 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.

  16. Comparative Transcriptomics Indicates a Role for SHORT VEGETATIVE PHASE (SVP Genes in Mimulus guttatus Vernalization Response

    Directory of Open Access Journals (Sweden)

    Jill C. Preston

    2016-05-01

    Full Text Available The timing of reproduction in response to variable environmental conditions is critical to plant fitness, and is a major driver of taxon differentiation. In the yellow monkey flower, Mimulus guttatus, geographically distinct North American populations vary in their photoperiod and chilling (vernalization requirements for flowering, suggesting strong local adaptation to their surroundings. Previous analyses revealed quantitative trait loci (QTL underlying short-day mediated vernalization responsiveness using two annual M. guttatus populations that differed in their vernalization response. To narrow down candidate genes responsible for this variation, and to reveal potential downstream genes, we conducted comparative transcriptomics and quantitative PCR (qPCR in shoot apices of parental vernalization responsive IM62, and unresponsive LMC24 inbred lines grown under different photoperiods and temperatures. Our study identified several metabolic, hormone signaling, photosynthetic, stress response, and flowering time genes that are differentially expressed between treatments, suggesting a role for their protein products in short-day-mediated vernalization responsiveness. Only a small subset of these genes intersected with candidate genes from the previous QTL study, and, of the main candidates tested with qPCR under nonpermissive conditions, only SHORT VEGETATIVE PHASE (SVP gene expression met predictions for a population-specific short-day-repressor of flowering that is repressed by cold.

  17. Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images*

    Science.gov (United States)

    Wang, Jing; Huang, Jing-Feng; Wang, Xiu-Zhen; Jin, Meng-Ting; Zhou, Zhen; Guo, Qiao-Ying; Zhao, Zhe-Wen; Huang, Wei-Jiao; Zhang, Yao; Song, Xiao-Dong

    2015-01-01

    Accurate estimation of rice phenology is of critical importance for agricultural practices and studies. However, the accuracy of phenological parameters extracted by remote sensing data cannot be guaranteed because of the influence of climate, e.g. the monsoon season, and limited available remote sensing data. In this study, we integrate the data of HJ-1 CCD and Landsat-8 operational land imager (OLI) by using the ordinary least-squares (OLS), and construct higher temporal resolution vegetation indices (VIs) time-series data to extract the phenological parameters of single-cropped rice. Two widely used VIs, namely the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2), were adopted to minimize the influence of environmental factors and the intrinsic difference between the two sensors. Savitzky-Golay (S-G) filters were applied to construct continuous VI profiles per pixel. The results showed that, compared with NDVI, EVI2 was more stable and comparable between the two sensors. Compared with the observed phenological data of the single-cropped rice, the integrated VI time-series had a relatively low root mean square error (RMSE), and EVI2 showed higher accuracy compared with NDVI. We also demonstrate the application of phenology extraction of the single-cropped rice in a spatial scale in the study area. While the work is of general value, it can also be extrapolated to other regions where qualified remote sensing data are the bottleneck but where complementary data are occasionally available. PMID:26465131

  18. Estimation of rice phenology date using integrated HJ-1 CCD and Landsat-8 OLI vegetation indices time-series images.

    Science.gov (United States)

    Wang, Jing; Huang, Jing-feng; Wang, Xiu-zhen; Jin, Meng-ting; Zhou, Zhen; Guo, Qiao-ying; Zhao, Zhe-wen; Huang, Wei-jiao; Zhang, Yao; Song, Xiao-dong

    2015-10-01

    Accurate estimation of rice phenology is of critical importance for agricultural practices and studies. However, the accuracy of phenological parameters extracted by remote sensing data cannot be guaranteed because of the influence of climate, e.g. the monsoon season, and limited available remote sensing data. In this study, we integrate the data of HJ-1 CCD and Landsat-8 operational land imager (OLI) by using the ordinary least-squares (OLS), and construct higher temporal resolution vegetation indices (VIs) time-series data to extract the phenological parameters of single-cropped rice. Two widely used VIs, namely the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2), were adopted to minimize the influence of environmental factors and the intrinsic difference between the two sensors. Savitzky-Golay (S-G) filters were applied to construct continuous VI profiles per pixel. The results showed that, compared with NDVI, EVI2 was more stable and comparable between the two sensors. Compared with the observed phenological data of the single-cropped rice, the integrated VI time-series had a relatively low root mean square error (RMSE), and EVI2 showed higher accuracy compared with NDVI. We also demonstrate the application of phenology extraction of the single-cropped rice in a spatial scale in the study area. While the work is of general value, it can also be extrapolated to other regions where qualified remote sensing data are the bottleneck but where complementary data are occasionally available.

  19. Is the patch size distribution of vegetation a suitable indicator of desertification processes? Comment

    NARCIS (Netherlands)

    Kefi, S.; Alados, C.L. y; Chaves, R.C.G.; Pueyo, Y.; Rietkerk, M.G.

    2010-01-01

    With ongoing climate change, the search for indicators of imminent ecosystem shifts is attracting increasing attention (e.g., Scheffer et al. 2009). Recently, the spatial organization of ecosystems has been suggested as a good candidate for such an indicator in spatially structured ecosystems (Rietk

  20. Feasibility to Detect Signs of Potential CO2 Leakage with Multi-Temporal SPOT Satellite Vegetation Imagery in Otway, Victoria

    Science.gov (United States)

    Cholathat, R.; Ge, L.; Li, X.; Hu, Z.

    2012-07-01

    This paper presents image processing results for the OtwayCO2storage site, a demonstration project of CO2 sequestration in south-western Victoria, Australia. These results were derived from SPOT-VGT S10 datasets of 2001 to mid 2011. Over 65,000 tonnes of CO2-rich gas stream was injected into a depleted gas reservoir at a depth of 2050 meters at the site since 2008. Over time, CO2 migration up-dip within the 31 m thick reservoir sandstone capped by the impervious thick seal rock has been recorded. But no top soil contamination has been discovered. This study has analysed the site vegetation growth using NDVI as a measure on a pixel by pixel basis. The multi-year time series result shows that NDVI values at the site regularly vary according to the seasons. Furthermore, precipitation levels were fluctuating in the past 10 years, especially in the years of 2002 and 2006, which correlated with low NDVI measuring results. But there are detected hot spots that cannot be linked with rainfall. Authors have found that some hot spots correspond with site well drilling and pipelines construction periods and locations. While others might be due to image data biased. Therefore, certain low NDVI spikes in the temporal evolution results cannot be attributed to only drought or pasture grazing. These subtle changes detected in the NDVI index prove the ability to use satellite image for providing valuable information to decision makers in relation to CO2 sequestration site environmental safety monitoring for searching CO2 leakage signals.

  1. Present and future water resources in India: Insights from satellite remote sensing and a dynamic global vegetation model

    Indian Academy of Sciences (India)

    S J Murray

    2013-02-01

    India is a country of particular interest with regard to its future water resources, as it is expected to undergo continued rapid population growth while also being especially sensitive to climate change. The Land-surface Processes and eXchanges Dynamic Global Vegetation Model (LPX-DGVM) is used here to simulate present and future runoff in India using ClimGen pattern-scaled scenarios of 1°, 2° and 4°C temperature increase (scaled to 2050) forced by six general circulation models (GCMs). As is the case with many DGVMs, groundwater storage is not simulated by LPX, so in order to form a more comprehensive understanding of water resources, Gravity Recovery and Climate Experiment (GRACE) satellite estimates for north-west India are incorporated into this study and compared to LPX runoff simulations. Runoff is simulated to have increased slightly (1.5 mm/year) in this region during 2002–2006, while groundwater extractions appear to have been made at rates of 40 ± 10 mm/year. North-west India is simulated to experience considerable increases in runoff by 2070–2099, with a mean change of 189 mm/year for 2°C climate change (although the range of model results, 247 mm/year, demonstrates high uncertainty among GCMs). Precipitation is shown to have an important bearing on runoff generation, while the degree of warming is shown to affect the magnitude of future runoff. This may subsequently influence the longevity of the local groundwater resource. However, at recent rates of depletion and in view of expected population growth, the long-term sustainability of groundwater reserves in north-west India is in doubt.

  2. Changes in satellite-derived spring vegetation green-up date and its linkage to climate in China from 1982 to 2010: a multimethod analysis.

    Science.gov (United States)

    Cong, Nan; Wang, Tao; Nan, Huijuan; Ma, Yuecun; Wang, Xuhui; Myneni, Ranga B; Piao, Shilong

    2013-03-01

    The change in spring phenology is recognized to exert a major influence on carbon balance dynamics in temperate ecosystems. Over the past several decades, several studies focused on shifts in spring phenology; however, large uncertainties still exist, and one understudied source could be the method implemented in retrieving satellite-derived spring phenology. To account for this potential uncertainty, we conducted a multimethod investigation to quantify changes in vegetation green-up date from 1982 to 2010 over temperate China, and to characterize climatic controls on spring phenology. Over temperate China, the five methods estimated that the vegetation green-up onset date advanced, on average, at a rate of 1.3 ± 0.6 days per decade (ranging from 0.4 to 1.9 days per decade) over the last 29 years. Moreover, the sign of the trends in vegetation green-up date derived from the five methods were broadly consistent spatially and for different vegetation types, but with large differences in the magnitude of the trend. The large intermethod variance was notably observed in arid and semiarid vegetation types. Our results also showed that change in vegetation green-up date is more closely correlated with temperature than with precipitation. However, the temperature sensitivity of spring vegetation green-up date became higher as precipitation increased, implying that precipitation is an important regulator of the response of vegetation spring phenology to change in temperature. This intricate linkage between spring phenology and precipitation must be taken into account in current phenological models which are mostly driven by temperature. © 2012 Blackwell Publishing Ltd.

  3. 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

  4. Technical Note: Comparing and ranking soil-moisture indices performance over Europe, through remote-sensing of vegetation

    Directory of Open Access Journals (Sweden)

    E. Peled

    2009-10-01

    Full Text Available Climate change induces long-term changes in soil-moisture. These changes can have important effects on the terrestrial biosphere, which can feedback into the climate system. In the past years there have been many attempts to produce and improve global soil-moisture datasets, however, comparing and validating these various datasets is not an easy task. Here, interannual variations in indices of soil moisture are compared to interannual changes in vegetation, as captured by NDVI. By comparing the correlations of the different indices with NDVI we evaluated which soil moisture index provides the most reliable soil moisture representation. We showed that NDVI can be used as an external validation dataset to soil moisture indices, in areas that are classified as warm temperate climate with hot or warm dry summers. Using the best performing index, NSM (Normalizes Soil Moisture, and the ICA (Independent Component Analysis technique, we analyzed the response of vegetation to temperature and soil-moisture stresses over Europe.

  5. First scalar magnetic anomaly map from CHAMP satellite data indicates weak lithospheric field

    DEFF Research Database (Denmark)

    Maus, S.; Rother, M.; Holme, R.;

    2002-01-01

    Satellite magnetic anomaly maps derived by different techniques from Magsat/POGO data vary by more than a factor of 2 in the deduced strength of the lithospheric magnetic field. Here, we present a first anomaly map from new CHAMP scalar magnetic field data. After subtracting a recent Ørsted main...... and external field model, we remove remaining unmodeled large-scale external contributions from 120 track segments by subtracting a best-fitting uniform field. In order to preserve N/S trending features, the data are not filtered along-track. Direct integration of the spherically gridded data yields the final...

  6. IN-SEASON ASSESSMENT OF WHEAT CROP HEALTH USING VEGETATION INDICES BASED ON GROUND MEASURED HYPER SPECTRAL DATA

    Directory of Open Access Journals (Sweden)

    Khalid Ali Al-Gaadi

    2014-01-01

    Full Text Available An experiment on a 50 ha center pivot field was conducted to determine the Vegetation Indices (VI’s that were helpful in assessing the in-season performance of wheat crop treated with graded levels of irrigation water and fertilizers. The irrigation levels were at 100, 90, 80 and 70% evapotranspiration (ETc; however, the fertilizer levels of N: P: K kg-1ha included 300:150:200 (low; 400:250:300 (medium and 500:300:300 (High. The crop was sown on January 1st and harvested on May 9th, 2012. Temporal data on biophysical parameters and reflectance of the crop in hyper spectral bands (350-2500 nm were collected at booting and ripening growth stages (February 17th and April 5th, 2012. Results of the study revealed that many of the tested spectral indices showed significant response to irrigation levels. Out of those, only two spectral indices (Plant Senescence Reflectance Index ‘PSRI’ and Photochemical Reflectance Index ‘PRI’ also exhibited significant response to fertilizer levels. The Middle Infrared-Based Vegetation Index (MIVI showed a significant response to the irrigation levels for both sampling dates. Among the tested spectral indices, Normalized Difference Infrared Index (NDII and Normalized Difference Nitrogen Index (NDNI exhibited the highest correlation to crop Leaf Area Index (LAI. Five indices showed the most response to wheat grain yield. These indices included Near Infrared band (NIR, Water Band Index (WBI, Normalized Water Index-1 (NWI-1, Normalized Water Index-3 (NWI-3 and Normalized Water Index-4 (NWI-4.

  7. A multi-sensor method for in-situ quantification of multiple biodiversity and ecosystem service indicators in wetland vegetation

    Science.gov (United States)

    Zlinszky, András; Prager, Katharina; Koma, Zsófia

    2017-04-01

    Biodiversity and ecosystem services are in the focus of biogeosciences research and conservation management worldwide. However, their quantification is notoriously difficult. Since full coverage of biodiversity and/or ecosystem services is unfeasible due to their complexity, indicators are recommended: biophysical quantities that are measureable and are expected to be closely related to biodiversity or to ecosystem processes. Nevertheless, many biodiversity and ecosystem service assessments are based on upscaling very few (if any) in-situ measurements using models driven by basic land cover data. Also, many assessments select only a single or very few indicators, which then does not enable analysis of trade-offs and interconnections. Here we propose a system of simple yet reliable field measurements, based on basic sensors, measurements, imaging and sampling technology, suitable for quantitatively representing many components of biodiversity and ecosystem services in emergent wetland vegetation. Along a transect from open water to the shore, sampling stations are laid out that include water temperature, air temperature and humidity sensors, zenith facing photographs and pole contact counts of vegetation in height intervals. Additionally, for some of these stations, small quadrats of vegetation are harvested, separated to individual species and weighed in height intervals above ground/water. Underwater surface of vegetation is estimated by counting stalks and registering average diameter. Finally, decomposition is quantified by leaving a standard amount of biomass in a plastic net bag and re-weighing it a year later. This system allows measuring alpha and beta diversity together with vertical structural diversity, leaf area (as a proxy of shading and pollution absorbtion), biomass (as a proxy of carbon sequestration), underwater surface (as a proxy of fish population sustaining), microclimate influence and soil provision. The necessary tools are temperature and

  8. Hyperspectral Imagery for Mapping Disease Infection in Oil Palm PlantationUsing Vegetation Indices and Red Edge Techniques

    Directory of Open Access Journals (Sweden)

    Helmi Z.M. Shafri

    2009-01-01

    Full Text Available Problem Statement: Large scale plantation of oil palm trees requires on-time detection of diseases as the ganoderma basal stem rot disease was present in more than 50% of the oil palm plantations in Peninsular Malaysia. Approach: To deal with this problem, airborne hyperspectral imagery offers a better solution in order to detect and map the oil palm trees that were affected by the disease on time. Airborne hyperspectral can provide data on user requirement and has the capability of acquiring data in narrow and contiguous spectral bands which makes it possible to discriminate between healthy and diseased plants better compared to multispectral imagery. By using vegetation indices and red edge techniques, the condition of oil palm trees could be determined accurately. Results: Generally, all of these techniques showed better results as they could give accuracy between 73 and 84%. The highest accuracy was achieved by using Lagrangian interpolation technique with 84% of overall accuracy. Conclusions/Recommendations: The red edge based techniques were more effective than vegetation indices in detecting Ganoderma-infected oil palm trees plantation since there were three out of four techniques that could yield high accuracy results.

  9. Influence of the Vegetation Type on CH2O and NO2 Tropospheric Emissions during Biomass Burning: Synergistic use of Satellite Observations

    Science.gov (United States)

    Marbach, T.; Beirle, S.; Hollwedel, J.; Khokhar, F.; Platt, U.; Wagner, T.

    Satellite observations are a helpful tool for the identification of the sources for tropospheric emissions by providing global observations of the different trace gases. We present case studies for the combined observations of CH2O and NO2 derived from observations made by the Global Ozone Monitoring Experiment (GOME). Launched on the ERS-2 satellite in April, 1995, GOME has already performed continuous operations over 8 years. The satellite CH2O observations provide information concerning the localization of biomass burning (intense source of CH2O). The principal biomass burning areas can be observed in the amazonian forest and in central Africa. Other high CH2O emissions can be correlated with climatic events like El Nino in 1997, which induced dry conditions in Indonesia causing many forest fires. Tree isoprene emissions contribute also for high CH2O concentrations especially in southwest United States. Biomass burning are also an important tropospheric source for NO2 emissions and can be compared with the CH2O emissions to discriminate the influence of the vegetation type on the tropospheric emissions of both trace gases during biomass burning: the change in the vegetation type can be followed with the change in the intensity of CH2O and NO2 emissions.

  10. Vegetation cyclic shift in eutrophic lagoon. Assessment of dystrophic risk indices based on standing crop evaluations

    Science.gov (United States)

    Lenzi, Mauro; Renzi, Monia; Nesti, Ugo; Gennaro, Paola; Persia, Emma; Porrello, Salvatore

    2013-11-01

    Orbetello lagoon (Tuscany, Italy) is a meso-eutrophic, shallow-water ecosystem which has undergone cyclic shifts in macrophyte dominance since 1970. Field data on the total standing crops of Chlorophyceae and Rhodophyceae (from 1983 to 2011) and Angiospermae (seagrass; from 1998 to 2007), produced each year by the ecosystem, was acquired. A general lagoon environment quality score (decay level DL, categories 0-4) was attributed (a posteriori) for each annual dataset examined. Univariate and multivariate statistical analyses were used to relate total macrophyte standing crops of 29 years of monitoring to the general quality score. Two indices were proposed (Abundance of Macroalgae Index, AMI, and Abundance of Seagrass Index, ASI, the latter in two versions, ASI-1 and ASI-2) and tested against DL. The results showed that biomass data did not accurately describe general environmental quality of the lagoon ecosystem, whereas the indices gave a better fit. AMI showed the best performance, demonstrating that macroalga data was much more informative than seagrass data. Values of AMI over 4.0 were significantly associated with critical general quality scores (DL > 2).

  11. Vegetation changes and timberline fluctuations in the Central Alps as indicators of holocene climatic oscillations

    Energy Technology Data Exchange (ETDEWEB)

    Wick, L.; Tinner, W. [Univ. of Bern (Switzerland)

    1997-11-01

    Pollen and plant-macrofossil data are presented for two lakes near the timberline in the Italian (Lago Basso, 2250 m) and Swiss Central Alps (Gouille Rion, 2343 m). The reforestation at both sites started at 9700-9500 BP with Pinus cembra, Larix decidua, and Betula. The timberline reached its highest elevation between 8700 and 5000 BP and retreated after 5000 BP, due to a mid-Holocene climatic change and increasing human impact since about 3500 BP (Bronze Age). The expansion of Picea abies at Lago Basso between ca. 7500 and 6200 BP was probably favored by cold phases accompanied by increased oceanicity, whereas in the area of Gouille Rion, where spruce expanded rather late (between 4500 and 3500 BP), human influence equality might have been important. The mass expansion of Alnus viridis between ca. 5000 and 3500 BP probably can be related to both climatic change and human activity at timberline. During the early and middle Holocene a series of timberline fluctuations is recorded as declines in pollen and macrofossil concentrations of the major tree species, and as increases in nonarboreal pollen in the pollen percentage diagram of Gouille Rion. Most of the periods of low timberline can be correlated by radiocarbon dating the climatic changes in the Alps as indicated by glacier advances in combination with palynological records, solifluction, and dendroclimatical data. Lago Basso and Gouille Rion are the only sites in the Alps showing complete palaeobotanical records of cold phases between 10,000 and 2000 BP with very good time control. The altitudinal range of the Holocene treeline fluctuations caused by climate most likely was not more than 100 to 150 m. A possible correlation of a cold period at ca. 7500-6500 BP (Misox oscillation) in the Alps is made with paleoecological data from North American and Scandinavia and a climate signal in the GRIP ice core from central Greenland 8200 yr ago (ca. 7400 yr uncal. BP).

  12. Exploring the Opportunities of a Balloon-Satellite in Bangladesh for Weather Data Collection and Vegetative Analysis

    Science.gov (United States)

    Shafique, Md. Ishraque Bin; Razzaq Halim, M. A.; Rabbi, Fazle; Khalilur Rhaman, Md.

    2016-07-01

    For a third world country like Bangladesh, satellite and space research is not feasible due to lack of funding. Therefore, in order to imitate the principles of such a satellite Balloon Satellite can easily and inexpensively be setup. Balloon satellites are miniature satellites, which are cheap and easy to construct. This paper discusses a BalloonSat developed using a Raspberry Pi, IMU module, UV sensor, GPS module, Camera and XBee Module. An interactive GUI was designed to display all the data collected after processing. To understand nitrogen concentration of a plant, a leaf color chart is used. This paper attempts to digitalize this process, which is applied on photos taken by the BallonSat.

  13. Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region.

    Science.gov (United States)

    Song, Youngkeun; Njoroge, John B; Morimoto, Yukihiro

    2013-05-01

    Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E ~ 1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period.

  14. 洞庭湖植被对降水的响应%Analysis of vegetation response to rainfall with satellite images in Dongting Lake

    Institute of Scientific and Technical Information of China (English)

    蒋卫国; 侯鹏; 朱晓华; 曹广真; 刘小曼; 曹入尹

    2011-01-01

    We analyzed the Normalized Difference Vegetation Index (NDVI) from satellite images and precipitation data from meteorological stations from 1998 to 2007 in the Dongting Lake wetland watershed to better understand the eco-hydrological effect of atmospheric precipitation and its relationship with vegetation. First, we analyzed its general spatio-temporal distribution using its mean, standard deviation and linear trend. Then, we used the Empirical Orthogonal Functions (EOF) method to decompose the NDVI and precipitation data into spatial and temporal modes. We selected four leading modes based on North and Scree test rules and analyzed the synchronous seasonal and inter-annual variability between the vegetation index and precipitation, distinguishing time-lagged correlations between EOF modes with the correlative degree analysis method. According to our detailed analyses, the vegetation index and precipitation exhibit a prominent correlation in spatial distribution and seasonal variation. At the 90% confidence level, the time lag is around 110 to 140 days,which matches well with the seasonal variation.

  15. 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.

  16. 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.

  17. 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

  18. Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral Measurements

    Directory of Open Access Journals (Sweden)

    Davoud Ashourloo

    2014-06-01

    Full Text Available Spectral Vegetation Indices (SVIs have been widely used to indirectly detect plant diseases. The aim of this research is to evaluate the effect of different disease symptoms on SVIs and introduce suitable SVIs to detect rust disease. Wheat leaf rust is one of the prevalent diseases and has different symptoms including yellow, orange, dark brown, and dry areas. The reflectance spectrum data for healthy and infected leaves were collected using a spectroradiometer in the 450 to 1000 nm range. The ratio of the disease-affected area to the total leaf area and the proportion of each disease symptoms were obtained using RGB digital images. As the disease severity increases, so does the scattering of all SVI values. The indices were categorized into three groups based on their accuracies in disease detection. A few SVIs showed an accuracy of more than 60% in classification. In the first group, NBNDVI, NDVI, PRI, GI, and RVSI showed the highest amount of classification accuracy. The second and third groups showed classification accuracies of about 20% and 40% respectively. Results show that few indices have the ability to indirectly detect plant disease.

  19. Examining the Satellite-Detected Urban Land Use Spatial Patterns Using Multidimensional Fractal Dimension Indices

    Directory of Open Access Journals (Sweden)

    Dongjie Fu

    2013-10-01

    Full Text Available Understanding the spatial patterns of urban land use at both the macro and the micro levels is a central issue in global change studies. Due to the nonlinear features associated with land use spatial patterns, it is currently necessary to provide some distinct analysis methods to analyze them across a range of remote sensing imagery resolutions. The objective of our study is to quantify urban land use patterns from various perspectives using multidimensional fractal methods. Three commonly used fractal dimensions, i.e., the boundary dimension, the radius dimension, and the information entropy dimension, are introduced as the typical indices to examine the complexity, centrality and balance of land use spatial patterns, respectively. Moreover, a new lacunarity dimension for describing the degree of self-organization of urban land use at the macro level is presented. A cloud-free Landsat ETM+ image acquired on 17 September 2010 was used to extract land use information in Wuhan, China. The results show that there are significant linear relationships represented by good statistical fitness related to these four indices. The results indicate that rapid urbanization has substantially affected the urban landscape pattern, and different land use types show different spatial patterns in response. This analysis reveals that multiple fractal/nonfractal indices provides a more comprehensive understanding of the spatial heterogeneity of urban land use spatial patterns than any single fractal dimension index. These findings can help us to gain deeper insight into the complex spatial patterns of urban land use.

  20. Characterising Vegetation Structural and Functional Differences Across Australian Ecosystems From a Network of Terrestrial Laser Scanning Survey Sites and Airborne and Satellite Image Archives

    Science.gov (United States)

    Phinn, S. R.; Armston, J.; Scarth, P.; Johansen, K.; Schaefer, M.; Suarez, L.; Soto-Berelov, M.; Muir, J.; Woodgate, W.; Jones, S.; Held, A. A.

    2015-12-01

    vertical and horizontal distribution of plant materials. TLS data are providing a step change in satellite image based vegetation mapping, and refining our knowledge of vegetation structure and its phenological variability. Open access plot scale TLS measurements are available through the TERN Auscover data portal.

  1. Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms

    OpenAIRE

    Qayyum, A; A. S. Malik; Saad, M. N. M.; Iqbal, M.; F. Abdullah; W. Rahseed; T. A. R. B. T. Abdullah; A. Q. Ramli

    2015-01-01

    Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more t...

  2. Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery

    Science.gov (United States)

    Zhou, X.; Zheng, H. B.; Xu, X. Q.; He, J. Y.; Ge, X. K.; Yao, X.; Cheng, T.; Zhu, Y.; Cao, W. X.; Tian, Y. C.

    2017-08-01

    Timely and non-destructive assessment of crop yield is an essential part of agricultural remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a novel approach for RS, and makes it possible to acquire high spatio-temporal resolution imagery on a regional scale. In this study, the rice grain yield was predicted with single stage vegetation indices (VIs) and multi-temporal VIs derived from the multispectral (MS) and digital images. The results showed that the booting stage was identified as the optimal stage for grain yield prediction with VIs at a single stage for both digital image and MS image. And corresponding optimal color index was VARI with R2 value of 0.71 (Log relationship). While the optimal vegetation index NDVI[800,720] based on MS images showed a linear relationship with the grain yield and gained a higher R2 value (0.75) than color index did. The multi-temporal VIs showed a higher correlation with grain yield than the single stage VIs did. And the VIs at two random growth stage with the multiple linear regression function [MLR(VI)] performed best. The highest correlation coefficient were 0.76 with MLR(NDVI[800,720]) at the booting and heading stages (for the MS image) and 0.73 with MLR(VARI) at the jointing and booting stages (for the digital image). In addition, the VIs that showed a high correlation with LAI performed well for yield prediction, and the VIs composed of red edge band (720 nm) and near infrared band (800 nm) were found to be more effective in predicting yield and LAI at high level. In conclusion, this study has demonstrated that both MS and digital sensors mounted on the UAV are reliable platforms for rice growth and grain yield estimation, and determined the best period and optimal VIs for rice grain yield prediction.

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

    OpenAIRE

    Haitao Liao; Wei Xie; Yu Peng; Datong Liu; Hong Wang

    2013-01-01

    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...

  4. Water bodies extraction from high resolution satellite images using water indices and optimal threshold

    Science.gov (United States)

    AlMaazmi, Alya

    2016-10-01

    Over the past years, remote sensing imagery made the earth monitoring more effective and valuable through developing different algorithms for feature extraction. One of the significant features are water surfaces. Water features extraction such as pools, lakes and gulfs gained a considerable attention over the past years, as water plays critical role for surviving, planning and protecting water resources. Past worth efforts in water extraction from remote sensed images mainly faced the challenge of misclassification, especially with shadows. Shadows are typical noise objects for water, extraction, as they have almost identical spectrum characteristics, which result difficulty to discriminate between water and shadows in a remote sensing image, especially in the urban region such as Dubai. Therefore, water extraction algorithm is developed in order to extract water surfaces accurately with shadows elimination. The detection is based on spectral information such as water indices (WIs), and morphological operations. Water indices are used to discriminate water surfaces from lands based on combining two or more water indices such as Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Normalized Saturation-value Difference Index (NSVDI), used at an optimum threshold. The morphological operators will be performed using opening by reconstruction to discriminate between water and shadows at an optimum threshold. Both Water Indices and morphological operation results will be infused together in one image that result a binary image of water objects. The algorithm and final results are compared with ground truth image for accuracy assessment, the results were satisfactory with an accuracy of 95% and higher and very minimum negligible shadows appeared. Moreover the resultant image transformed into vector features in order to create a shape file that can be used and viewed in google earth and Geo software.

  5. 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, №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

  6. The benefits of China's efforts on gaseous pollutant control indicated by the bottom-up emissions and satellite observation

    Science.gov (United States)

    Xia, Y.; Zhao, Y.

    2015-12-01

    To evaluate the effectiveness of national policies of air pollution control, the emissions of SO2, NOX, CO and CO2 in China are estimated with a bottom-up method from 2000 to 2014, and vertical column densities (VCD) from satellite observation are used to evaluate the inter-annual trends and spatial distribution of emissions and the temporal and spatial patterns of ambient levels of gaseous pollutants across the country. In particular, an additional emission case named STD case, which combines the most recent issued emission standards for specific industrial sources, is developed for 2012-2014. The inter-annual trends in emissions and VCDs match well except for SO2, and the revised emissions in STD case improve the comparison, implying the benefits of emission control for most recent years. Satellite retrieval error, underestimation of emission reduction and improved atmospheric oxidization caused the differences between emissions and VCDs trend of SO2. Coal-fired power plants play key roles in SO2 and NOX emission reduction. As suggested by VCD and emission inventory, the control of CO in 11th five year plan (FYP) period was more effective than that in the 12th FYP period, while the SO2 appeared opposite. As the new control target added in 12th FYP, NOX emissions have been clearly decreased 4.3 Mt from 2011 to 2014, in contrast to the fast growth before 2011. The inter-annual trends in NO2 VCDs has the poorest correlation with vehicle ownership (R=0.796), due to the staged emission standard of vehicles. In developed regions, transportation has become the main pollutants emission source and we prove this by comparing VCDs of NO2 to VCDs of SO2. Moreover, air quality in mega cities has been evaluated based on satellite observation and emissions, and results indicate that Beijing suffered heavily from the emissions from Hebei and Tianjin, while the local emissions tend to dominate in Shanghai.

  7. 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

  8. Assessment of surface dryness due to deforestation using satellite-based temperature-vegetation dryness index (TVDI) in Rondônia, Amazon

    Science.gov (United States)

    Ryu, J. H.; Cho, J.

    2016-12-01

    The Rondônia is the most deforested region in the Amazon due to human activities such as forest lumbering for the several decades. The deforestation affects to water cycle because evapotranspiration was reduced, and then soil moisture and precipitation will be changed. In this study, we assess surface dryness using satellite-based data such as moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), normalized difference vegetation index (NDVI), albedo, TRMM Multi-sensor Precipitation Analysis (TMPA) precipitation from 2002 to 2014, and Global Ozone Monitoring Experiment-2 (GOME-2) sun-induced fluorescence (SIF) from 2007 to 2014. Temperature-vegetation dryness index (TVDI) was calculated using LST and NDVI to evaluate surface dryness during dry season (June-July). TVDI relatively represents the surface dryness on specific area and period. Forest, deforesting and deforested regions were selected in the Rondônia to assess the relative changes on surface dryness occurred from human activity. The relative TVDI (rTVDI) at deforesting region increased because of deforestation, it means that surface in deforesting region became more dryness. We also found that to assess the impact of deforestation using satellite-based precipitation and vegetation conditions such as NDVI and sun-induced fluorescence (SIF) is possible. The relative NDVI (rNDVI) and SIF decreased when TVDI increased, and two variables (rTVDI-rNDVI, rTVDI-SIF) had linear correlation. Thesis results can be helpful to comprehend impact of deforestation in Amazon, and to validate simulations of deforestation from hydrological models.

  9. 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).

  10. Prognostic land surface albedo from a dynamic global vegetation model clumped canopy radiative transfer scheme and satellite-derived geographic forest heights

    Science.gov (United States)

    Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Aleinov, I. D.; Jonas, J.

    2014-12-01

    Vegetation cover was introduced into general circulations models (GCMs) in the 1980's to account for the effect of land surface albedo and water vapor conductance on the Earth's climate. Schemes assigning canopy albedoes by broad biome type have been superceded in 1990's by canopy radiative transfer schemes for homogeneous canopies obeying Beer's Law extinction as a function of leaf area index (LAI). Leaf albedo and often canopy height are prescribed by plant functional type (PFT). It is recognized that this approach does not effectively describe geographic variation in the radiative transfer of vegetated cover, particularly for mixed and sparse canopies. GCM-coupled dynamic global vegetation models (DGVMs) have retained these simple canopy representations, with little further evaluation of their albedos. With the emergence lidar-derived canopy vertical structure data, DGVM modelers are now revisiting albedo simulation. We present preliminary prognostic global land surface albedo produced by the Ent Terrestrial Biosphere Model (TBM), a DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. The Ent TBM is a next generation DGVM designed to incorporate variation in canopy heights, and mixed and sparse canopies. For such dynamically varying canopy structure, it uses the Analytical Clumped Two-Stream (ACTS) canopy radiative transfer model, which is derived from gap probability theory for canopies of tree cohorts with ellipsoidal crowns, and accounts for soil, snow, and bare stems. We have developed a first-order global vegetation structure data set (GVSD), which gives a year of satellite-derived geographic variation in canopy height, maximum canopy leaf area, and seasonal LAI. Combined with Ent allometric relations, this data set provides population density and foliage clumping within crowns. We compare the Ent prognostic albedoes to those of the previous GISS GCM scheme, and to satellite estimates. The impact of albedo differences on surface

  11. Research in remote sensing of vegetation

    Science.gov (United States)

    Schrumpf, Barry J.; Ripple, William J.; Isaacson, Dennis L.

    1988-01-01

    The research topics undertaken were primarily selected to further the understanding of fundamental relationships between electromagnetic energy measured from Earth orbiting satellites and terrestrial features, principally vegetation. Vegetation is an essential component in the soil formation process and the major factor in protecting and holding soil in place. Vegetation plays key roles in hydrological and nutrient cycles. Awareness of improvement or deterioration in the capacity of vegetation and the trends that those changes may indicate are, therefore, critical detections to make. A study of the relationships requires consideration of the various portions of the electromagnetic spectrum; characteristics of detector system; synergism that may be achieved by merging data from two or more detector systems or multiple dates of data; and vegetational characteristics. The vegetation of Oregon is sufficiently diverse as to provide ample opportunity to investigate the relationships suggested above several vegetation types.

  12. Dryness Indices Based on Remotely Sensed Vegetation and Land Surface Temperature for Evaluating the Soil Moisture Status in Cropland-Forest-Dominant Watersheds

    Directory of Open Access Journals (Sweden)

    Heewon Moon and Minha Choi

    2015-01-01

    Full Text Available The Temperature Vegetation Dryness Index (TVDI was derived from the relationship between remotely sensed vegetation indices and land surface temperature (TS in this study for assessing the soil moisture status at regional scale in South Korea. The Leaf Area Index (LAI is newly applied in this method to overcome the increasing uncertainty of using the Normalized Difference Vegetation Index (NDVI at high vegetation conditions. Both dryness indices were found to be well correlated with in situ soil moisture and 8-day average precipitation at most of the in situ measurement sites. The dryness indices accuracy was found to be influenced by rainfall events. An average correlation coefficient was improved from -0.253 to -0.329 when LAI was used instead of NDVI in calculating the TVDI. In the spatial analysis between the dryness indices and Advanced SCATterometer (ASCAT surface soil moisture (SSM using geographically weighted regression (GWR, the results showed the average negative correlation (R between the variables, while LAI-induced TVDI was more strongly correlated with SSM on average with the R value improved from -0.59 to -0.62. Both dryness indices and ASCAT SSM mappings generally showed coherent patterns under low vegetation and dry conditions. Based on these results, the LAI-induced TVDI accuracy as an index for soil moisture status was validated and found appropriate for use as an alternative and complementary method for NDVI-induced TVDI.

  13. Data service platform for MODIS Vegetation Indices time series processing at BOKU Vienna: current status and future perspectives

    Science.gov (United States)

    Vuolo, Francesco; Mattiuzzi, Matteo; Klisch, Anja; Atzberger, Clement

    2012-10-01

    The aim of this paper is to present a freely available data service platform (http://ivfl-info.boku.ac.at/) for executing preprocessing operations (such as data smoothing, spatial and temporal sub-setting, mosaicking and reprojection) of time series of Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices (NDVI and EVI) on request. The web-application is based on the integration of various software and hardware components: a web-interface and a MySQL database are used to collect and store user's requests. A server-side application schedules the user's requests and delivers the results. The core of the processing system is based on the "MODIS" package developed in R, which provides MODIS data collection and pre-processing capabilities. Smoothed and gap-filled data sets are derived using the state-ofthe- art Whittaker filter implemented in Matlab. After the processing, data are delivered directly via ftp access. An analysis of the performance of the web-application, along with processing capacity is presented. Results are discussed, in particular in view of an operative platform for real time filtering, phenology and land cover mapping.

  14. Regional scaling of soil moisture dynamics on the semiarid grasslands of Mexico through remotely sensed vegetation indices

    Science.gov (United States)

    Carrera-Hernandez, J. J.; Mata-Martinez, A.; Huber-Sannwald, E.; Arredondo, T.

    2014-12-01

    Soil moisture dynamics for both native (Bouteloa gracilis) and introduced (Eragrostis curvula) species within the semiarid grasslands in Mexico are analyzed. The semiarid grasslands of Mexico are part of the shortgrass steppe ecosystem, which extends from the North American midwest in the north to Llanos de Ojuelos in the south, where the study site is located. Soil moisture dynamics are measured on two homogeneous fields; one dominated by the native species (Bouteloa gracilis), and another with an introduced species (Eragrostis curvula) at three different depths with high temporal resolution along with standard climatological data. These data are related to measured Leaf Area Index (LAI) and spectra at 16 different wavelengths, both of which, in turn, are related to remotely sensed imagery through different vegetation indices (NDVI, SAVI, EVI and Modified Chlorophyll Absorption Ratio Index (MCARI)) for different sensors (LANDSAT, SPOT, Pleiades) at different growth stages. To date, the MCARI exhibits a larger correlation with LAI for all sensors and growing stages for both grass species (ongoing field work will provide additional data). Regionalization of soil moisture dynamics (i.e. recharge) will be done using a numerical model of the vadose zone that will be linked to the temporal variation of MCARI. Financial support by the Mexico's CONACYT (project CB 158370) and UNAM's PAPIIT program (project IA100613) is acknowledged.

  15. 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.

  16. 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...

  17. Monitoring of wetlands Ecosystems using satellite images

    Science.gov (United States)

    Dabrowska-Zielinska, K.; Gruszczynska, M.; Yesou, H.; Hoscilo, A.

    Wetlands are very sensitive ecosystems, functioning as habitat for many organisms. Protection and regeneration of wetlands has been the crucial importance in ecological research and in nature conservation. Knowledge on biophysical properties of wetlands vegetation retrieved from satellite images will enable us to improve monitoring of these unique areas, very often impenetrable. The study covers Biebrza wetland situated in the Northeast part of Poland and is considered as Ramsar Convention test site. The research aims at establishing of changes in biophysical parameters as the scrub encroachment, lowering of the water table, and changes of the farming activity caused ecological changes at these areas. Data from the optical and microwave satellite images collected for the area of Biebrza marshland ecosystem have been analysed and compared with the detailed soil-vegetation ground measurements conducted in conjunction with the overflights. Satellite data include Landsat ETM, ERS-2 ATSR and SAR, SPOT VEGETATION, ENVISAT MERIS and ASAR, and NOAA AVHRR. From the optical data various vegetation indices have been calculated, which characterize the vegetation surface roughness, its moisture conditions and stage of development. Landsat ETM image has been used for classification of wetlands vegetation. For each class of vegetation various moisture indices have been developed. Ground data collected include wet and dry biomass, LAI, vegetation height, and TDR soil moisture. The water cloud model has been applied for retrieval of soil vegetation parameters taking into account microwave satellite images acquired at VV, HV and HH polarisations at different viewing angles. The vegetation parameters have been used for to distinguish changes, which occurred at the area. For each of the vegetation class the soil moisture was calculated from microwave data using developed algorithms. Results of this study will help mapping and monitoring wetlands with the high spatial and temporal

  18. Atmospheric COS measurements and satellite-derived vegetation fluorescence data to evaluate the terrestrial gross primary productivity of CMIP5 model

    Science.gov (United States)

    Peylin, Philippe; MacBean, Natasha; Launois, Thomas; Belviso, Sauveur; Cadule, Patricia; Maignan, Fabienne

    2016-04-01

    Predicting the fate of the ecosystem carbon stocks and their sensitivity to climate change strongly relies on our ability to accurately model the gross carbon fluxes, i.e. photosynthesis and respiration. The Gross Primary Productivity (GPP) simulated by the different terrestrial models used in CMIP5 show large differences however, not only in terms of mean value but also in terms of phase and amplitude, thus hampering accurate investigations into carbon-climate feedbacks. While the net C flux of an ecosystem (NEE) can be measured in situ with the eddy covariance technique, the GPP is not directly accessible at larger scales and usually estimates are based on indirect measurements combining different tracers. Recent measurements of a new atmospheric tracer, the Carbonyl sulphide (COS), as well as the global measurement of Solar Induced Fluorescence (SIF) from satellite instruments (GOSAT, GOME2) open a new window for evaluating the GPP of earth system models. The use of COS relies on the fact that it is absorbed by the leaves in a similar manner to CO2, while there seems to be nothing equivalent to respiration for COS. Following recent work by Launois et al. (ACP, 2015), there is a potential to evaluate model GPP from atmospheric COS and CO2 measurements, using a transport model and recent parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of COS. Vegetation uptake of COS is modeled as a linear function of GPP and the ratio of COS to CO2 rate of uptake by plants. For the fluorescence, recent measurements of SIF from space appear to be highly correlated with monthly variations of data-driven GPP estimates (Guanter et al., 2012), following a strong dependence of vegetation SIF on photosynthetic activity. These global measurements thus provide new indications on the timing of canopy carbon uptake. In this work, we propose a dual approach that combines the strength of both COS and SIF

  19. Estimating and mapping chlorophyll content for a heterogeneous grassland: Comparing prediction power of a suite of vegetation indices across scales between years

    Science.gov (United States)

    Tong, Alexander; He, Yuhong

    2017-04-01

    This study investigates the performance of existing vegetation indices for retrieving chlorophyll content for a semi-arid mixed grass prairie ecosystem across scales using in situ data collected in 2012 and 2013. A 144 published broadband (21) and narrowband (123) vegetation indices are evaluated to estimate chlorophyll content. Results indicate that narrowband indices utilize reflectance data from one or more wavelengths in the red-edge region (∼690-750 nm) perform better. Broadband indices are found to be as effective as narrowband indices for chlorophyll content estimation at both leaf and canopy scales. The empirical relationships are generally stronger at the canopy than the leaf scale, attributable to the fact that leaf samples are collected during the peak growing season when chlorophyll in plant species are uniform. SPOT-5 and CASI-550 derived chlorophyll maps result in map accuracies of 63.56% and 78.88% respectively. The assessment of vegetation chlorophylls at the canopy level, especially using remote sensing imagery is important for providing information pertaining to ecosystem health such as the physiological status, productivity, or phenology of vegetation.

  20. Evaluating Biosphere Model Estimates of the Start of the Vegetation Active Season in Boreal Forests by Satellite Observations

    Directory of Open Access Journals (Sweden)

    Kristin Böttcher

    2016-07-01

    Full Text Available The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle- and deciduous broad-leaf, was obtained for the period 2003–2011 from regional JSBACH (Jena Scheme for Biosphere–Atmosphere Hamburg runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP determined from CO2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production.

  1. Attribution of satellite observed vegetation trends in a hyper-arid region of the Heihe River Basin, Central Asia

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2014-02-01

    4.5% in 2012. The largest contribution to the overall greening was due to changes in green vegetation cover of the extensive desert areas with a smaller contribution due to changes in the area of irrigated land. Comprehensive analysis with different precipitation data sources found that the greening of the desert was associated with increases in regional precipitation. We found that the area of land irrigated each year was mostly dependent on the runoff gauged one year earlier. Taken together, water availability both from precipitation in the desert and runoff inflow for the irrigation agricultural lands can explain at least 52% of the total variance in regional vegetation cover from 2000 to 2010.

  2. Assessment of acreage and vegetation change in Florida`s Big Bend tidal wetlands using satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Raabe, E.A.; Stumpf, R.P. [Geological Survey, St. Petersburg, FL (United States)

    1997-06-01

    Fluctuations in sea level and impending development on the west coast of Florida have aroused concern for the relatively pristine tidal marshes of the Big Bend. Landsat Thematic Mapper (TM) images for 1986 and 1995 are processed and evaluated for signs of change. The images cover 250 km of Florida`s Big Bend Gulf Coast, encompassing 160,000 acres of tidal marshes. Change is detected using the normalized difference vegetation index (NDVI) and land cover classification. The imagery shows negligible net loss or gain in the marsh over the 9-year period. However, regional changes in biomass are apparent and are due to natural disturbances such as low winter temperatures, fire, storm surge, and the conversion of forest to marsh. Within the marsh, the most prominent changes in NDVI and in land cover result from the recovery of mangroves from freezes, a decline of transitional upland vegetation, and susceptibility of the marsh edge and interior to variations in tidal flooding.

  3. Land mobile satellite transmission measurements at 869 MHz. A comparison of error probabilities for various message block durations and fade margins as a function of vegetation shadowing

    Science.gov (United States)

    Vogel, Wolfhard J.

    1985-01-01

    In order to give vehicles travelling in rural areas of the U.S. access to the telephone network, a Land Mobile Satellite System is being planned. Previously presented data by the author were analyzed for the probability that the received signal level dropped below a threshold during short time blocks of various signal durations and the conditional probability that such an event would reoccur after a given delay. If it assumed that a fade threshold crossing of even 1 msec would produce an error in the transmission, then the derived quantities can be considered error probabilities. Extensive tables and graphs are presented with the results from the analysis. They can be used to devise communication strategies which will provide improved link availability in the presence of vegetation shadowing.

  4. Timely monitoring of Asian Migratory locust habitats in the Amudarya delta, Uzbekistan using time series of satellite remote sensing vegetation index.

    Science.gov (United States)

    Löw, Fabian; Waldner, François; Latchininsky, Alexandre; Biradar, Chandrashekhar; Bolkart, Maximilian; Colditz, René R

    2016-12-01

    The Asian Migratory locust (Locusta migratoria migratoria L.) is a pest that continuously threatens crops in the Amudarya River delta near the Aral Sea in Uzbekistan, Central Asia. Its development coincides with the growing period of its main food plant, a tall reed grass (Phragmites australis), which represents the predominant vegetation in the delta and which cover vast areas of the former Aral Sea, which is desiccating since the 1960s. Current locust survey methods and control practices would tremendously benefit from accurate and timely spatially explicit information on the potential locust habitat distribution. To that aim, satellite observation from the MODIS Terra/Aqua satellites and in-situ observations were combined to monitor potential locust habitats according to their corresponding risk of infestations along the growing season. A Random Forest (RF) algorithm was applied for classifying time series of MODIS enhanced vegetation index (EVI) from 2003 to 2014 at an 8-day interval. Based on an independent ground truth data set, classification accuracies of reeds posing a medium or high risk of locust infestation exceeded 89% on average. For the 12-year period covered in this study, an average of 7504 km(2) (28% of the observed area) was flagged as potential locust habitat and 5% represents a permanent high risk of locust infestation. Results are instrumental for predicting potential locust outbreaks and developing well-targeted management plans. The method offers positive perspectives for locust management and treatment of infested sites because it is able to deliver risk maps in near real time, with an accuracy of 80% in April-May which coincides with both locust hatching and the first control surveys. Such maps could help in rapid decision-making regarding control interventions against the initial locust congregations, and thus the efficiency of survey teams and the chemical treatments could be increased, thus potentially reducing environmental pollution

  5. A Satellite-Based Assessment of the Distribution and Biomass of Submerged Aquatic Vegetation in the Optically Shallow Basin of Lake Biwa

    Directory of Open Access Journals (Sweden)

    Shweta Yadav

    2017-09-01

    Full Text Available Assessing the abundance of submerged aquatic vegetation (SAV, particularly in shallow lakes, is essential for effective lake management activities. In the present study we applied satellite remote sensing (a Landsat-8 image in order to evaluate the SAV coverage area and its biomass for the peak growth period, which is mainly in September or October (2013 to 2016, in the eutrophic and shallow south basin of Lake Biwa. We developed and validated a satellite-based water transparency retrieval algorithm based on the linear regression approach (R2 = 0.77 to determine the water clarity (2013–2016, which was later used for SAV classification and biomass estimation. For SAV classification, we used Spectral Mixture Analysis (SMA, a Spectral Angle Mapper (SAM, and a binary decision tree, giving an overall classification accuracy of 86.5% and SAV classification accuracy of 76.5% (SAV kappa coefficient 0.74, based on in situ measurements. For biomass estimation, a new Spectral Decomposition Algorithm was developed. The satellite-derived biomass (R2 = 0.79 for the SAV classified area gives an overall root-mean-square error (RMSE of 0.26 kg Dry Weight (DW m-2. The mapped SAV coverage area was 20% and 40% in 2013 and 2016, respectively. Estimated SAV biomass for the mapped area shows an increase in recent years, with values of 3390 t (tons, dry weight in 2013 as compared to 4550 t in 2016. The maximum biomass density (4.89 kg DW m-2 was obtained for a year with high water transparency (September 2014. With the change in water clarity, a slow change in SAV growth was noted from 2013 to 2016. The study shows that water clarity is important for the SAV detection and biomass estimation using satellite remote sensing in shallow eutrophic lakes. The present study also demonstrates the successful application of the developed satellite-based approach for SAV biomass estimation in the shallow eutrophic lake, which can be tested in other lakes.

  6. Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado

    Science.gov (United States)

    Rockwell, Barnaby W.

    2012-01-01

    The efficacy of airborne spectroscopic, or "hyperspectral," remote sensing for geoenvironmental watershed evaluations and deposit-scale mapping of exposed mineral deposits has been demonstrated. However, the acquisition, processing, and analysis of such airborne data at regional and national scales can be time and cost prohibitive. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried by the NASA Earth Observing System Terra satellite was designed for mineral mapping and the acquired data can be efficiently used to generate uniform mineral maps over very large areas. Multispectral remote sensing data acquired by the ASTER sensor were analyzed to identify and map minerals, mineral groups, hydrothermal alteration types, and vegetation groups in the western San Juan Mountains, Colorado, including the Silverton and Lake City calderas. This mapping was performed in support of multidisciplinary studies involving the predictive modeling of surface water geochemistry at watershed and regional scales. Detailed maps of minerals, vegetation groups, and water were produced from an ASTER scene using spectroscopic, expert system-based analysis techniques which have been previously described. New methodologies are presented for the modeling of hydrothermal alteration type based on the Boolean combination of the detailed mineral maps, and for the entirely automated mapping of alteration types, mineral groups, and green vegetation. Results of these methodologies are compared with the more detailed maps and with previously published mineral mapping results derived from analysis of high-resolution spectroscopic data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Such comparisons are also presented for other mineralized and (or) altered areas including the Goldfield and Cuprite mining districts, Nevada and the central Marysvale volcanic field, Wah Wah Mountains, and San Francisco Mountains, Utah. The automated

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

    Science.gov (United States)

    Beck, Pieter S. A.; Goetz, Scott J.

    2011-12-01

    In the first paragraph of the section '2. Data sets and methods', the Normalized Difference Vegetation Index (NDVI) data set used was incorrectly referred to as GIMMS-NDVI version 3G with a 0.084° spatial resolution. This should be corrected to GIMMS-NDVI version G with a 0.07° spatial resolution. Accordingly, the acknowledgement should state 'We would like to thank ... Jim Tucker and Jorge Pinzon for providing the GIMMS version G data', instead of 'We would like to thank ... Jorge Pinzon for providing the GIMMS 3G data'.

  8. Monitoring of the Spatial Distribution and Temporal Dynamics of the Green Vegetation Fraction of Croplands in Southwest Germany Using High-Resolution RapidEye Satellite Images

    Science.gov (United States)

    Imukova, Kristina; Ingwersen, Joachim; Streck, Thilo

    2014-05-01

    The green vegetation fraction (GVF) is a key input variable to the evapotranspiration scheme applied in the widely used NOAH land surface model (LSM). In standard applications of the NOAH LSM, the GVF is taken from a global map with a 15 km×15 km resolution. The central objective of the present study was (a) to derive gridded GVF data in a high spatial and temporal resolution from RapidEye images for a region in Southwest Germany, and (b) to improve the representation of the GVF dynamics of croplands in the NOAH LSM for a better simulation of water and energy exchange between land surface and atmosphere. For the region under study we obtained monthly RapidEye satellite images with a resolution 5 m×5 m by the German Aerospace Center (DLR). The images hold five spectral bands: blue, green, red, red-edge and near infrared (NIR). The GVF dynamics were determined based on the Normalized Difference Vegetation Index (NDVI) calculated from the red and near-infrared bands of the satellite images. The satellite GVF data were calibrated and validated against ground truth measurements. Digital colour photographs above the canopy were taken with a boom-mounted digital camera at fifteen permanently marked plots (1 m×1 m). Crops under study were winter wheat, winter rape and silage maize. The GVF was computed based on the red and the green band of the photographs according to Rundquist's method (2002). Based on the obtained calibration scheme GVF maps were derived in a monthly resolution for the region. Our results confirm a linear relationship between GVF and NDVI and demonstrate that it is possible to determine the GVF of croplands from RapidEye images based on a simple two end-member mixing model. Our data highlight the high variability of the GVF in time and space. At the field scale, the GVF was normally distributed with a coefficient of variation of about 32%. Variability was mainly caused by soil heterogeneities and management differences. At the regional scale the GVF

  9. The effect of image radiometric correction on the accuracy of vegetation canopy density estimate using several Landsat-8 OLI’s vegetation indices: A case study of Wonosari area, Indonesia

    Science.gov (United States)

    Dewa, R. P.; Danoedoro, P.

    2017-01-01

    Recent studies on the use of spectral indices have involved radiometric correction as a prerequisite. However, study on the effect of radiometric correction level on the accuracy of biophysical parameters’ estimate is still rare in Indonesia. This study tried to investigate the influence of various radiometric correction levels and the number of vegetation strata on the accuracy of vegetation density estimates using NDVI, MSAVI2 and GEMI of Landsat 8 OLI. In this study, the dataset covering vegetated area in Wonosari, Gunung Kidul Regency, Indonesia was processed radiometrically using eight different methods, i.e. spectral radiance, at sensor reflectance, sun elevation correction, histogram adjustments using original DN, spectal radiance, at sensor reflectance, and sun position correction respectively, as well as dark object subtraction (DOS). Every image with specific correction level was then transformed using the aforementioned indices, in order correlate with the field-measured canopy density. The analysis were carried out by considering the number of canopy layers. This found that different radiometric correction methods resulted canopy density estimates with different accuracies. The number of canopy strata also played an important role. Every vegetation index transformation performed its best accuracy by using different radiometric correction method and different number of canopy layers.

  10. Regional accumulation characteristics of cadmium in vegetables: Influencing factors, transfer model and indication of soil threshold content.

    Science.gov (United States)

    Yang, Yang; Chen, Weiping; Wang, Meie; Peng, Chi

    2016-12-01

    A regional investigation in the Youxian prefecture, southern China, was conducted to analyze the impact of environmental factors including soil properties and irrigation in conjunction with the use of fertilizers on the accumulation of Cd in vegetables. The Cd transfer potential from soil to vegetable was provided by the plant uptake factor (PUF), which varied by three orders of magnitude and was described by a Gaussian distribution model. The soil pH, content of soil organic matter (SOM), concentrations of Zn in the soil, pH of irrigation water and nitrogenous fertilizers contributed significantly to the PUF variations. A path model analysis, however, revealed the principal control of the PUF values resulted from the soil pH, soil Zn concentrations and SOM. Transfer functions were developed using the total soil Cd concentrations, soil pH, and SOM. They explained 56% of the variance for all samples irrespective of the vegetable genotypes. The transfer functions predicted the probability of exceeding China food safety standard concentrations for Cd in four major consumable vegetables under different soil conditions. Poor production practices in the study area involved usage of soil with pH values ≤ 5.5, especially for the cultivation of Raphanus sativus L., even with soil Cd concentrations below the China soil quality standard. We found the soil standard Cd concentrations for cultivating vegetables was not strict enough for strongly acidic (pH ≤ 5.5) and SOM-poor (SOM ≤ 10 g kg(-1)) soils present in southern China. It is thus necessary to address the effect of environmental variables to generate a suitable Cd threshold for cultivated soils. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. 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, X.; Vogelmann, J.E.; Rollins, M.; Ohlen, D.; Key, C.H.; Yang, L.; Huang, C.; Shi, H.

    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. ?? 2011 Taylor & Francis.

  12. Satellite-Based Observations of Inter-annual Variation of Vegetation Water Content and Productivity in Northern Asia During 1998-2001

    Science.gov (United States)

    Xiao, X.; Braswell, B. H.; Zhang, Q.; Boles, S.; Frolking, S.; Moore, B.

    2002-05-01

    The terrestrial biosphere was largely carbon neutral during the 1980s, but became a much stronger net carbon sink in the 1990s. It is also thought that the unusually large carbon sink in the early 1990s can be largely attributed to climate variability. We analyzed multi-temporal images (1-km spatial resolution, 10-day composites) from the SPOT-4 VEGETATION (VGT) sensor over the period of April 1, 1998 to September 30, 2001 to characterize spatial and temporal variations of vegetation and water indices for Northern Asia (40oN - 75oN, and 45oE - 179oE). Three remote sensing proxies were derived from the VGT data: Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI). We calculated anomalies of NDWI, NDVI and EVI at different temporal scales, i.e., 10-day, monthly, seasonal and plant growing season (April to September), and compared these with inter-annual variations in precipitation and temperature from the National Climate Data Center Global History Climate Network. Both anomalies of precipitation and NDWI over plant growing season (April to September) for Northern Asia were highest in 1998 but declined from 1999 to 2001. NDVI and EVI anomalies did not correlate well with each other overall. The EVI anomaly over plant growing season (April to September) was highest in 1998, and declined from 1999 to 2001,while the NDVI anomaly over plant growing season was lowest in 1998 and highest in 2000 for North Asia. The EVI includes information from the VGT blue band to account for the effects of residual atmospheric contamination (e.g., aerosols) and soil/vegetation background, while the NDVI does not. Large fires occurred in eastern Russia and Northeastern China in 1998 and may have increased the atmospheric aerosol burden; high precipitation in that year may have been associated with increased atmospheric water vapor. Both of these effects would lower the NDVI value in 1998. This continental-scale study

  13. Application of Hyperspectral Vegetation Indices to Detect Variations in High Leaf Area Index Temperate Shrub Thicket Canopies

    Science.gov (United States)

    2011-01-01

    Ray, D. (2004). Drought stress and carbon uptake in an Amazon forest measured with spaceborne imaging spectroscopy. Proceedings of the National...Academy of Science, 101, 6039−6044. Asner, G. P., Townsend, A. R., & Braswell, B. H. (2000). Satellite observation of El Niño effects on Amazon forest...physiological responses for detection of salt and drought stress in coastal plant species. Physiologia Plantarum, 131, 422−433. Naumann, J. C., Young

  14. Satellite derived 30-year trends in terrestrial frozen and non-frozen seasons and associated impacts to vegetation and atmospheric CO2

    Science.gov (United States)

    Kim, Y.; Kimball, J. S.; McDonald, K. C.; Glassy, J. M.

    2010-12-01

    Approximately 66 million km2 (52.5 %) of the global vegetated land area experiences seasonally frozen temperatures as a major constraint to ecosystem processes. The freeze-thaw (F/T) status of the landscape as derived from satellite microwave remote sensing is closely linked to surface energy budget and hydrological activity, vegetation phenology, terrestrial carbon budgets and land-atmosphere trace gas exchange. We utilized a seasonal threshold algorithm based temporal change classification of 37GHz frequency, vertically polarized brightness temperatures (Tb) from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) pathfinder and Special Sensor Microwave Imager (SSM/I) to classify daily F/T status for all global land areas where seasonal frozen temperatures are a major constraint to ecosystem processes. A temporally consistent, long-term (30 year) daily F/T record was created by pixel-wise correction of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements acquired during 1987. The resulting combined F/T record was validated against in situ temperature measurements from the global weather station network and applied to quantify regional patterns and trends in timing and length of frozen and non-frozen seasons. The F/T results were compared against other surrogate measures of biosphere activity including satellite AVHRR (GIMMS) based vegetation greenness (NDVI) and atmospheric CO2 concentrations over northern (>50N) land areas. The resulting F/T record showed mean annual classification accuracies of 91 (+/-1.0) and 84 (+/- 0.9) percent for PM and AM overpass retrievals relative to in situ weather station records. The F/T record showed significant (P=0.008) long-term trends in non-frozen period (0.207 days/yr) that were largely driven by earlier onset of spring thaw (-0.121 days/yr) and a small, delayed trend the arrival of the frozen period (0.107 days/yr). These results coincide with 0.025 C/yr warming trends in

  15. 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

  16. 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...

  17. 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.

  18. Analysis of Temporal and Spatial Changes in the Vegetation Density of Similipal Biosphere Reserve in Odisha (India Using Multitemporal Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Anima Biswal

    2013-01-01

    Full Text Available National parks and protected areas require periodic monitoring because of changing land cover types and variability of landscape contexts within and adjacent to their boundaries. In this study, remote sensing and GIS techniques were used to analyse the changes in the vegetation density particularly in the zones of higher anthropogenic pressure in the Similipal Biosphere Reserve (SBR of Odisha (India, using Landsat imagery from 1975 to 2005. A technique for the detection of postclassification changes was followed and the change in vegetation density as expressed by normalized difference vegetation index was computed. Results indicate that high dense forest in the core zone has been conserved and the highest reforestation has also occurred in this zone of SBR. The results also reveal that anthropological interventions are more in the less dense forest areas and along the roads, whereas high dense forest areas have remained undisturbed and rejuvenated. This study provides baseline data demonstrating alteration in land cover over the past three decades and also serves as a foundation for monitoring future changes in the national parks and protected areas.

  19. The Change Indices of Solar and Geomagnetic Activity and Their Influence on the Dynamics of Drag of Artificial Satellite

    Science.gov (United States)

    Komendant, V. H.; Koshkin, N. I.; Ryabov, M. I.; Sukharev, A. L.

    2016-12-01

    The time-frequency and multiple regression analysis of the orbital parameter characterizing the drag of satellites on circular and elliptical orbits with different perigees and orbital inclinations in the atmosphere of the Earth was being conducted in 23-24 cycles of solar activity. Among the factors influencing braking dynamics of satellites were taken: W - Wolf numbers; Sp - the total area of sunspot groups of the northern and southern hemispheres of the Sun, F10.7 - the solar radio flux at 10,7 cm; E - electron flux with energies more than 0,6 MeV è 2 MeV; planetary, high latitude and middle latitude geomagnetic index Ap. In the atmospheric drag dynamics of satellites, the following periods were detected: 6-year, 2.1-year, annual, semi-annual, 27-days, 13- and 11-days. Similar periods are identified in indexes of solar and geomagnetic activity. Dependence of the periods of satellites motion on extremes of solar activities and space weather conditions was conducted.

  20. Vegetation type classification and vegetation cover percentage estimation in urban green zone using pleiades imagery

    Science.gov (United States)

    Trisakti, Bambang

    2017-01-01

    Open green space in the urban area has aims to maintain the availability of land as a water catchment area, creating aspects of urban planning through a balance between the natural environment and the built environment that are useful for the public needs. Local governments have to make the green zone plan map and monitor the green space changes in their territory. Medium and high resolution satellite imageries have been widely utilized to map and monitor the changes of vegetation cover as an indicator of green space area. This paper describes the use of pleaides imagery to classify vegetation types and estimate vegetation cover percentage in the green zone. Vegetation cover was mapped using a combination of NDVI and blue band. Furthermore, vegetation types in the green space were classified using unsupervised and supervised (ISODATA and MLEN) methods. Vegetation types in the study area were divided into sparse vegetation, low-medium vegetation and medium-high vegetation. The classification accuracies were 97.9% and 98.9% for unsupervised and supervised method respectively. The vegetation cover percentage was determined by calculating the ratio between the vegetation type area and the green zone area. These information are useful to support green zone management activities.

  1. 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.

  2. Pollen and phytoliths from fired ancient potsherds as potential indicators for deciphering past vegetation and climate in Turpan, Xinjiang, NW China.

    Directory of Open Access Journals (Sweden)

    Yi-Feng Yao

    Full Text Available 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.

  3. An intercomparison of Satellite Burned Area Maps derived from MODIS, MERIS, SPOT-VEGETATION, and ATSR images. An application to the August 2006 Galicia (Spain forest fires

    Directory of Open Access Journals (Sweden)

    M. Huesca

    2013-07-01

    : Earth Observation System; ESA: European Space Agency; GBA2000: Global Burnt Area 2000; GLOBCARBON-BAE: GLOBCARBON Burnt Area Estimate Product; L3JRC: Terrestrial Ecosystem Monitoring Global Burnt Area Product; MCD45A1: MODIS Burned Area Product; MERIS: MEdium Resolution Imaging Spectrometer; MOD09GA: Terra MODIS Surface Reflectance Daily L2G Global 500 m; MOD09GQ: Terra MODIS Surface Reflectance Daily L2G Global 250 m; MODIS: MODerate resolution Imaging Spectrometer; NBR: Normalized Burn Ratio; NDVI: Normalized Difference Vegetation Index; NIR: near-infrared; SPOT: Satellite Pour l’Observation de la Terre; SWIR: short-wave infrared; UTM: Universal Transverse Mercator.

  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%; Pshopping 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. Can grass phytoliths and indices be relied on during vegetation and climate interpretations in the eastern Himalayas? Studies from Darjeeling and Arunachal Pradesh, India

    Science.gov (United States)

    Biswas, Oindrila; Ghosh, Ruby; Paruya, Dipak Kumar; Mukherjee, Biswajit; Thapa, Kishore Kumar; Bera, Subir

    2016-02-01

    While documenting the vegetation response to climatic changes in mountains, the use of grass phytolith data relies on the ability of phytolith assemblages or indices to differentiate the elevationally stratified vegetation zones. To infer the potential and limitations of grass phytolith assemblages and indices to reconstruct vegetation vis-à-vis climate in the Himalayan mountain regions, we analyzed phytolith assemblages from 66 dominant grasses and 153 surface soils from four different forest types along the c. 130-4000 m a.s.l. elevation gradients in the Darjeeling and Arunachal Himalayas. Grass short cell phytolith assemblages from modern grasses show significant variability with rising elevation. To test the reliability of the above observation, phytoliths from the soil samples were subjected to linear discriminant analysis (DA). DA classified 85.3% and 92.3% of the sites to their correct forest zones in the Darjeeling and Arunachal Himalayas respectively. Relative abundance of bilobate, cross, short saddle, plateau saddle, rondel and trapeziform types allow discrimination of the phytolith assemblage along the elevation gradient. Canonical correspondence analysis (CCA) on the soil phytolith data further revealed their relationships with the climatic variables. Temperature and evapotranspiration were found to be the most influential for differential distribution of grass phytolith assemblages with rising elevation in the eastern Himalayas. We also tested the reliability of phytolith indices (Ic, Iph and Fs) for tracing the dominance of different grass subfamilies in the eastern Himalayas. Ic proved to be most reliable in discriminating C3/C4 grass along the elevation gradient while Iph and Fs proved to be less reliable. We observed that in the monsoon dominated eastern Himalayas, a little adjustment in Ic index may enhance the accuracy of interpretations. In future studies more precise identification of phytolith sub-types from additional sites in the eastern

  7. Using precipitation, vertical root distribution, and satellite-retrieved vegetation information to parameterize water stress in a Penman-Monteith approach to evapotranspiration modeling under Mediterranean climate

    Science.gov (United States)

    Bai, Yun; Zhang, Jiahua; Zhang, Sha; Koju, Upama Ashish; Yao, Fengmei; Igbawua, Tertsea

    2017-03-01

    Recent studies have shown that global Penman-Monteith equation based (PM-based) models poorly simulate water stress when estimating evapotranspiration (ET) in areas having a Mediterranean climate (AMC). In this study, we propose a novel approach using precipitation, vertical root distribution (VRD), and satellite-retrieved vegetation information to simulate water stress in a PM-based model (RS-WBPM) to address this issue. A multilayer water balance module is employed to simulate the soil water stress factor (SWSF) of multiple soil layers at different depths. The water stress factor (WSF) for surface evapotranspiration is determined by VRD information and SWSF in each layer. Additionally, four older PM-based models (PMOV) are evaluated at 27 flux sites in AMC. Results show that PMOV fails to estimate the magnitude or capture the variation of ET in summer at most sites, whereas RS-WBPM is successful. The daily ET resulting from RS-WBPM incorporating recommended VI (NDVI for shrub and EVI for other biomes) agrees well with observations, with R2=0.60 (RMSE = 18.72 W m-2) for all 27 sites and R2=0.62 (RMSE = 18.21 W m-2) for 25 nonagricultural sites. However, combined results from the optimum older PM-based models at specific sites show R2 values of only 0.50 (RMSE = 20.74 W m-2) for all 27 sites. RS-WBPM is also found to outperform other ET models that also incorporate a soil water balance module. As all inputs of RS-WBPM are globally available, the results from RS-WBPM are encouraging and imply the potential of its implementation on a regional and global scale.

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

    DEFF Research Database (Denmark)

    Brandt, Martin Stefan; Mbow, Cheikh; Diouf, Abdoul A.

    2015-01-01

    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...... 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. Copyright...

  9. Analysis of Vegetation Behavior in a North African Semi-Arid Region, Using SPOT-VEGETATION NDVI Data

    Directory of Open Access Journals (Sweden)

    Abdelghani Chehbouni

    2011-11-01

    Full Text Available The analysis of vegetation dynamics is essential in semi-arid regions, in particular because of the frequent occurrence of long periods of drought. In this paper, multi-temporal series of the Normalized Difference of Vegetation Index (NDVI, derived from SPOT-VEGETATION satellite data between September 1998 and June 2010, were used to analyze the vegetation dynamics over the semi-arid central region of Tunisia. A study of the persistence of three types of vegetation (pastures, annual agriculture and olive trees is proposed using fractal analysis, in order to gain insight into the stability/instability of vegetation dynamics. In order to estimate the state of vegetation cover stress, we propose evaluating the properties of an index referred to as the Vegetation Anomaly Index (VAI. A positive VAI indicates high vegetation dynamics, whereas a negative VAI indicates the presence of vegetation stress. The VAI is tested for the above three types of vegetation, during the study period from 1998 to 2010, and is compared with other drought indices. The VAI is found to be strongly correlated with precipitation.

  10. 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.

  11. Environmental resilience of rangeland ecosystems: assessment drought indices and vegetation trends on arid and semi-arid zones of Central Asia

    Science.gov (United States)

    Aralova, Dildora; Toderich, Kristina; Jarihani, Ben; Gafurov, Dilshod; Gismatulina, Liliya; Osunmadewa, Babatunde A.; Rahamtallah Abualgasim, Majdaldin

    2016-10-01

    The Central Asian (CA) rangelands is a part of the arid and semi-arid ecological zones and spatial extent of drylands in CA (Tajikistan, Kazakhstan, Uzbekistan, Kyrgyzstan, and Turkmenistan) is vast. Projections averaged across a suite of climate models, as measured between 1950-2012 by Standardised Precipitation-Evapotranspiration Index (SPEI) estimated a progressively increasing drought risks across rangelands (Turkmenistan, Tajikistan and Uzbekistan) especially during late summer and autumn periods, another index: Potential Evapotranspiration (PET) indicated drought anomalies for Turkmenistan and partly in Uzbekistan (between 1950-2000). On this study, we have combined a several datasets of drought indices ( SPIE, PET, temperature_T°C and precipitation_P) for better estimation of resilience/non-resilience of the ecosystems after warming the temperature in the following five countries, meanwhile, warming of climate causing of increasing rating of degradations and extension of desertification in the lowland and foothill zones of the landscape and consequently surrounding experienced of a raising balance of evapotranspiration (ET0). The study concluded, increasing drought anomalies which is closely related with raising (ET0) in the lowland and foothill zones of CA indicated on decreasing of NDVI indices with occurred sandy and loamy soils it will resulting a loss of vegetation diversity (endangered species) and raising of wind speeds in lowlands of CA, but on regional level especially towards agricultural intensification (without rotation) it indicated no changes of greenness index. It was investigated to better interpret how vegetation feedback modifies the sensitivity of drought indices associated with raising tendency of air temperature and changes of cold and hot year seasons length in the territory of CA.

  12. [The indices of water-salt metabolism and of the endocrine status in monkeys after flights on the Kosmos biological satellites].

    Science.gov (United States)

    Korol'kov, V I; Dotsenko, M A; Larina, I M; Shakhmatova, E I; Natochin, Iu V

    1996-01-01

    Findings of studying the indices of water-salt metabolism and endocrine status of monkeys after their exposure in the weightless environment onboard the biological satellites of Earth have revealed a change in the blood serum concentrations of electrolytes which is indicative of instability of the system responsible for maintenance of the fluid-mineral homeostasis during readaptation. Results of studying the endocrine status of monkeys infer alteration in calcium metabolism, i.e. decreased levels of parathyroid hormone, calcitonin and the transport form of vitamin D3.

  13. 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

  14. Assessment of Vegetation Indices Derived by UAV Imagery for Durum Wheat Phenotyping under a Water Limited and Heat Stressed Mediterranean Environment.

    Science.gov (United States)

    Kyratzis, Angelos C; Skarlatos, Dimitrios P; Menexes, George C; Vamvakousis, Vasileios F; Katsiotis, Andreas

    2017-01-01

    There is growing interest for using Spectral Vegetation Indices (SVI) derived by Unmanned Aerial Vehicle (UAV) imagery as a fast and cost-efficient tool for plant phenotyping. The development of such tools is of paramount importance to continue progress through plant breeding, especially in the Mediterranean basin, where climate change is expected to further increase yield uncertainty. In the present study, Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR) and Green Normalized Difference Vegetation Index (GNDVI) derived from UAV imagery were calculated for two consecutive years in a set of twenty durum wheat varieties grown under a water limited and heat stressed environment. Statistically significant differences between genotypes were observed for SVIs. GNDVI explained more variability than NDVI and SR, when recorded at booting. GNDVI was significantly correlated with grain yield when recorded at booting and anthesis during the 1st and 2nd year, respectively, while NDVI was correlated to grain yield when recorded at booting, but only for the 1st year. These results suggest that GNDVI has a better discriminating efficiency and can be a better predictor of yield when recorded at early reproductive stages. The predictive ability of SVIs was affected by plant phenology. Correlations of grain yield with SVIs were stronger as the correlations of SVIs with heading were weaker or not significant. NDVIs recorded at the experimental site were significantly correlated with grain yield of the same set of genotypes grown in other environments. Both positive and negative correlations were observed indicating that the environmental conditions during grain filling can affect the sign of the correlations. These findings highlight the potential use of SVIs derived by UAV imagery for durum wheat phenotyping under low yielding Mediterranean conditions.

  15. Linking environmental gradients, species composition, and vegetation indicators of sugar maple health in the northeastern United States

    Science.gov (United States)

    Stephen B. Horsley; Scott W. Bailey; Todd E. Ristau; Robert P. Long; Richard A. Hallett

    2008-01-01

    Sugar maple (Acer saccharum Marsh.) decline has occurred throughout its range over the past 50 years, although decline symptoms are minimal where nutritional thresholds of Ca, Mg, and Mn are met. Here, we show that availability of these elements also controls vascular plant species composition in northern hardwood stands and we identify indicator...

  16. 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 (R

  17. 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

  18. Temporal Trends and Spatial Variability of Vegetation Phenology over the Northern Hemisphere during 1982-2012

    OpenAIRE

    Siyuan Wang; Bojuan Yang; Qichun Yang; Linlin Lu; Xiaoyue Wang; Yaoyao Peng

    2016-01-01

    Satellite-derived vegetation phenology has been recognized as a key indicator for detecting changes in the terrestrial biosphere in response to global climate change. However, multi-decadal changes and spatial variation of vegetation phenology over the Northern Hemisphere and their relationship to climate change have not yet been fully investigated. In this article, we investigated the spatial variability and temporal trends of vegetation phenology over the Northern Hemisphere by calibrating ...

  19. Vegetation Phenology and Intensity as a Function of Climate and River Flows for an Ephemeral Desert River, 2000 to 2010, Using MODIS Satellite Data

    Science.gov (United States)

    Nguyen, U.; Nagler, P. L.; Glenn, E. P.; Van Riper, C., III

    2011-12-01

    The San Pedro river, located along Sonoran and Chihuahuan desert, is one of the most biologically diverse ecosystems in the Rocky mountains of the Southwestern United States. Vegetation dynamics related to seasonal changes may affect the life and migration of many wildlife species. Furthermore, vegetation density is related to surface flows in the river and depth to groundwater, which vary year to year. The MODIS Vegetation Index products (EVI and NDVI) were used to monitor vegetation dynamics during 10 years (2000-2010) to examine the impact of climatic conditions (such as temperature from LST, precipitation from PRISM and rive flows from gaga data) on the onset of greenness, senescence, and maximum vegetation density. The phenology profiles from time series data and relationships between vegetation index and temperature not only show seasonal changes but also respond to moisture stress on vegetation in the riparian areas of the San Pedro River.

  20. Physiological and ecological studies of the vegetation on ore deposits. I. Zinc flora and indicator plants on the 2nd Yunwha mine. [Sedum sp. ; Dianthus sinensis

    Energy Technology Data Exchange (ETDEWEB)

    Chang, N.K.; Chang, S.M.

    1977-01-01

    During the period of 1975-76, a survey was carried out to find out zinc indicators in the natural vegetation in Korea. The symptoms of chlorosis were observed in flowering plants in the areas of zinc outcrop of Wolgok-A, Seokgok-9, and Sowolgok. Although 28 species were found to be chlorotic, the total quantity of chlorotic foliage observed was small. Reasons for chlorosis in the areas of zinc ore deposits is considered as effects of zinc, lead, copper and calcium ions. Sedum sp. and Dianthus sinensis were confined to soil containing more than exchangeable zinc of 30 ppm and to accumulation in the plants contained at least 1,300-14,000 ppm of zinc. Therefore, Sedum sp. and Dianthus sinensis might be used as zinc indicators in Korea. 12 references, 1 figure, 5 tables.

  1. Vegetation as an indicator of soil properties and water quality in the Akarçay stream (Turkey).

    Science.gov (United States)

    Serteser, Ahmet; Kargioğlu, Mustafa; Içağa, Yilmaz; Konuk, Muhsin

    2008-11-01

    In this study, the relationship among water quality, soil properties, and plant coverage in the region of the Akarçay stream was examined. Correlation analyses were carried out between soil samples taken from each of four plant communities in the Akarçay basin and water in the Akarçay stream. The four plant communities in the study area are as follows: Limonium lilacinum (Boiss. et Bal.) Wag., Alhagi pseudalhagi (M. Bieb.) Desv. Peganum harmala L., and Hordeum marinum Huds. subsp. marinum. B, Cl, EC, K, Mg, Na, pH, and SO4 data from both soil and water samples were subjected to statistical analysis, and significant correlations were obtained (p indicated that the chemical features of the soil had a major effect on water quality. The important parameters were B, Cl, EC, K, Mg, Na, pH, and SO4 for Limonium lilacinum communities; Ca, K, and pV for Peganum harmala; and B, Cl, Mg, pH, and pV for Alhagi pseudalhagi. There were also statistically significant relationships (p indicators for soil chemistry and water quality.

  2. 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.

  3. A comparative study of satellite and ground-based phenology.

    Science.gov (United States)

    Studer, S; Stöckli, R; Appenzeller, C; Vidale, P L

    2007-05-01

    Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.

  4. Preparation of a Microbial Time-temperature Indicator by Using the Vegetative Form of Bacillus amyloliquefaciens for Monitoring the Quality of Chilled Food Products

    Directory of Open Access Journals (Sweden)

    Samaneh Shahrokh Esfahani

    2017-04-01

    Full Text Available Background and Objective: Time-temperature indicators are used in smart packaging, and described as intelligent tools attached to the label of food products to monitor their timetemperature history. Since the previous studies on microbial time-temperature indicators were only based on pH-dependent changes, and they were long-time response indicators, in the present work, a new microbial time-temperature indicator was designed by using the alpha amylase activity of Bacillus amyloliquefaciens vegetative cells.Material and Methods: The designed time-temperature indicator system consists of Bacillus amyloliquefaciens, specific substrate medium and iodine reagent. The relation of the timetemperatureindicator’ response to the growth and metabolic activity (starch consumption and production of reduced sugars of Bacillus amyloliquefaciens was studied. In addition, the temperature dependence of the time-temperature indicator was considered at 8 and 28˚C. Finally, in order to adjust time-temperature indicator endpoint, the effect of the inoculum level was investigated at 8ºC.Results and Conclusion: In the designed system, a color change of an iodine reagent to yellow progressively occurs due to the starch hydrolysis. The effect of the inoculum level showed the negative linear relationship between the levels of Bacillus amyloliquefaciens inoculated in the medium and the endpoints of the time-temperature indicators. The endpoints were adjusted to 156, 72 and 36 hours at the inoculum levels of 102, 104 and 106 CFU ml-1, respectively. The main advantages of the time-temperature indicator is low cost and application for monitoring the quality of chilled food products.Conflict of interest: The authors declare no conflict of interest.

  5. 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.

  6. 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

  7. Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index Composites

    Science.gov (United States)

    ,

    2005-01-01

    The Advanced Very High Resolution Radiometer (AVHRR) is a broad-band scanner with four to six bands, depending on the model. The AVHRR senses in the visible, near-, middle-, and thermal- infrared portions of the electromagnetic spectrum. This sensor is carried on a series of National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites (POES), beginning with the Television InfraRed Observation Satellite (TIROS-N) in 1978. Since 1989, the United States Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) has been mapping the vegetation condition of the United States and Alaska using satellite information from the AVHRR sensor. The vegetation condition composites, more commonly called greenness maps, are produced every week using the latest information on the growth and condition of the vegetation. One of the most important aspects of USGS greenness mapping is the historical archive of information dating back to 1989. This historical stretch of information has allowed the USGS to determine a 'normal' vegetation condition. As a result, it is possible to compare the current week's vegetation condition with normal vegetation conditions. An above normal condition could indicate wetter or warmer than normal conditions, while a below normal condition could indicate colder or dryer than normal conditions. The interpretation of departure from normal will depend on the season and geography of a region.

  8. An indicator to map diffuse chemical river pollution considering buffer capacity of riparian vegetation--a pan-European case study on pesticides.

    Science.gov (United States)

    Weissteiner, Christof J; Pistocchi, Alberto; Marinov, Dimitar; Bouraoui, Fayçal; Sala, Serenella

    2014-06-15

    Vegetated riparian areas alongside streams are thought to be effective at intercepting and controlling chemical loads from diffuse agricultural sources entering water bodies. Based on a recently compiled European map of riparian zones and a simplified soil chemical balance model, we propose a new indicator at a continental scale. QuBES (Qualitative indicator of Buffered Emissions to Streams) allows a qualitative assessment of European rivers exposed to pesticide input. The indicator consists of normalised pesticide loads to streams computed through a simplified steady-state fate model that distinguishes various chemical groups according to physico-chemical behaviour (solubility and persistence). The retention of pollutants in the buffer zone is modelled according to buffer width and sorption properties. While the indicator may be applied for the study of a generic emission pattern and for a chemical of generic properties, we demonstrate it to the case of agricultural emissions of pesticides. Due to missing geo-spatial data of pesticide emissions, a total pesticide emission scenario is assumed. The QuBES indicator is easy to calculate and requires far less input data and parameterisation than typical chemical-specific models. At the same time, it allows mapping of (i) riparian buffer permeability, (ii) chemical runoff from soils, and (iii) the buffered load of chemicals to the stream network. When the purpose of modelling is limited to identifying chemical pollution patterns and understanding the relative importance of emissions and natural attenuation in soils and stream buffer strips, the indicator may be suggested as a screening level, cost-effective alternative to spatially distributed models of higher complexity.

  9. COMPARING BROAD-BAND AND RED EDGE-BASED SPECTRAL VEGETATION INDICES TO ESTIMATE NITROGEN CONCENTRATION OF CROPS USING CASI DATA

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2016-06-01

    Full Text Available 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.

  10. 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.

  11. Understanding Droughts and their Agricultural Impact in North America at the Basin Scale through the Development of Satellite Based Drought Indicators

    Science.gov (United States)

    Munoz Hernandez, A.; Lawford, R. G.

    2012-12-01

    Drought is a major constraint severely affecting numerous agricultural regions in North America. Decision makers need timely information on the existence of a drought as well as its intensity, frequency, likely duration, and economic and social effects in order to implement adaptation strategies and minimize its impacts. Countries like Mexico and Canada face a challenge associated with the lack of consistent and reliable in-situ data that allows the computation of drought indicators at resolutions that effectively supports decision makers at the watershed scale. This study focuses on (1) the development of near-real time drought indicators at high resolution utilizing various satellite data for use in improving adaptation plans and mitigation actions at the basin level; (2) the quantification of the relationships between current and historical droughts and their agricultural impacts by evaluating thresholds for drought impacts; and (3) the assessment of the effects of existing water policies, economic subsidies, and infrastructure that affect the vulnerability of a particular region to the economic impacts of a drought. A pilot study area located in Northwest Mexico and known as the Rio Yaqui Basin was selected for this study in order to make comparisons between the satellite based indicators derived from currently available satellite products to provide an assessment of the quality of the products generated. The Rio Yaqui Basin, also referred to as the "bread basket" of Mexico, is situated in an arid to semi-arid region where highly sophisticated irrigation systems have been implemented to support extensive agriculture. Although for many years the irrigation systems acted as a safety net for the farmers, recent droughts have significantly impacted agricultural output, affected thousands of people, and increase the dependence on groundwater. The drought indices generated are used in conjunction with a decision-support model to provide information on drought impacts

  12. 从高光谱卫星数据中提取植被覆盖区铜污染信息%Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area

    Institute of Scientific and Technical Information of China (English)

    屈永华; 焦思红; 刘素红; 朱叶青

    2015-01-01

    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 cer‐tain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegeta‐tion 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 re‐sources .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 hy‐perspectral 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

  13. 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.

  14. 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

  15. Drought impacts on vegetation activity in the Mediterranean region: An assessment using remote sensing data and multi-scale drought indicators

    Science.gov (United States)

    Gouveia, C. M.; Trigo, R. M.; Beguería, S.; Vicente-Serrano, S. M.

    2017-04-01

    The present work analyzes the drought impacts on vegetation over the entire Mediterranean basin, with the purpose of determining the vegetation communities, regions and seasons at which vegetation is driven by drought. Our approach is based on the use of remote sensing data and a multi-scalar drought index. Correlation maps between fields of monthly Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at different time scales (1-24 months) were computed for representative months of winter (Feb), spring (May), summer (Aug) and fall (Nov). Results for the period from 1982 to 2006 show large areas highly controlled by drought, although presenting high spatial and seasonal differences, with a maximum influence in August and a minimum in February. The highest correlation values are observed in February for 3 months' time scale and in May for 6 and 12 months. The higher control of drought on vegetation in February and May is obtained mainly over the drier vegetation communities (Mediterranean Dry and Desertic) at shorter time scales (3 to 9 months). Additionally, in February the impact of drought on vegetation is lower for Temperate Oceanic and Continental vegetation types and takes place at longer time scales (18-24). The dependence of drought time-scale response with water balance, as obtained through a simple difference between precipitation and reference evapotranspiration, varies with vegetation communities. During February and November low water balance values correspond to shorter time scales over dry vegetation communities, whereas high water balance values implies longer time scales over Temperate Oceanic and Continental areas. The strong control of drought on vegetation observed for Mediterranean Dry and Desertic vegetation types located over areas with high negative values of water balance emphasizes the need for an early warning drought system covering the entire Mediterranean basin. We are confident

  16. Plant Remains from an Archaeological Site as Indicators of Vegetation and Agricultural Practice Between (3320±400) and (2080±80) yr BP in Gangetic West Bengal, India

    Institute of Scientific and Technical Information of China (English)

    Ruby Ghosh; Subir Bera; Ashalata D'Rozario; Manju Banerjee; Supriyo Chakraborty

    2006-01-01

    Diverse plant remains recovered from an archaeological site of Chalcolithic-Early Historic age in the Bhairabdanga area of Pakhanna (latitude 23°25′N, longitude 87°23′E), situated on the west bank of the Damodar river, Bankura district, West Bengal, India, include food grains, wood charcoals, and palynomorphs. Radiocarbon dating of the recovered biological remains reveal the age of the site as (3320±400) to (2080±80) yr BP. The food grains were identified as Oryza sativa L. and Vigna mungo L, and seeds of Brassica cf.campestris L. were also found; these indicate the agricultural practice and food habits of the ancient people living at Pakhanna from the Chalcolithic to the Early Historic period. Sediments including plant remains have been broadly divided into two zones, considering archaeological findings and radiocarbon dating. Analysis of the plant remains (i.e. wood charcoals and palynomorphs) in addition to cultivated food grains has revealed that a rich vegetation cover existed in this area, with a prevailing tropical and humid climate,comprising the timber-yielding plants Shorea sp., Terminalia sp., and Tamarindus sp., with undergrowths of diverse shrubs and herbs during the Chalcolithic period (zone Ⅰ) dated (3320±400) yr BP. Comparatively poorer representation and frequency of plant remains indicate a drier climate during the Early Historic period (zone Ⅱ) dated as (2110±340) to (2080±80) yr BP. Comparisons of the archaeobotanical data recovered from the Chalcolithic and Early Historic period and also a principle components analysis indicate a change in the climate of the area from tropical and humid at (3 320 ± 400) yr BP to tropical and drier conditions at (2110±340) to (2080±80) yr BP. The present-day tropical, dry deciduous vegetation of the area suggests that climate change has occurred in the area since the contemporaneous past. The plant remains database has been utilized to reconstruct the settlement pattern of the community living

  17. The relationship of hyper-spectral vegetation indices with leaf area index (LAI) over the growth cycle of wheat and chickpea at 3 nm spectral resolution

    Science.gov (United States)

    Gupta, R. K.; Vijayan, D.; Prasad, T. S.

    2006-01-01

    Hyperspectral ratio and normalized difference vegetation indices were computed from the 3 nm bandwidth ground-based spectral data taken in 400-950 nm wave length region over the crop growth cycle (CGC) of wheat and chickpea. Synthesized broad band Landsat TM-RVI, TM-NDVI and TM-SAVI were also computed using this narrow bandwidth spectral observations. Regression analysis was carried out for these indices with leaf area index (LAI) for wheat and chickpea over CGC and the r2 values were found poor in 0.2-0.53 range for wheat and in 0.41-0.82 range for chickpea. Significant relationship with LAI were found for wheat ( r2 in 0.86-0.97 range) when growth and decline phases were analyzed independently. Here, r2 values for chickpea were less than that for wheat. The high difference in rate of change of slope for hRVI is a good discriminator for high ET (wheat) and low ET (chickpea) crops. To find out the potential hyperspectral ratios and normalized difference indices that could provide strong relationship with LAI, a correlation-based analysis was carried out for LAI with all the possible combinations of ratios and normalized difference indices in 400-950 nm region (at 3 nm spectral interval) independently for growth and decline phases of LAI and found that in addition to traditional near-IR and red pairs, the pairs within near-IR, near-IR and visible extending to near-IR were also significantly related to LAI.

  18. Holocene vegetation variation in the Daihai Lake region of north-central China: a direct indication of the Asian monsoon climatic history

    Science.gov (United States)

    Xiao, Jule; Xu, Qinghai; Nakamura, Toshio; Yang, Xiaolan; Liang, Wendong; Inouchi, Yoshio

    2004-07-01

    DH99a sediment core recovered at the center of Daihai Lake in north-central China was analyzed at 4-cm intervals for pollen assemblage and concentration. The pollen record spanning the last ca 10,000 yr revealed a detailed history of vegetation and climate changes over the Daihai Lake region during the Holocene. From ca 10,250 to 7900 cal yr BP, arid herbs and shrubs dominated the lake basin in company with patches of mixed pine and broadleaved forests, indicating a mild and dry climatic condition. Over this period, the woody plants displayed an increasing trend, which may suggest a gradual increase in warmth and humidity. The period between ca 7900 and 4450 cal yr BP exhibits large-scale covers of mixed coniferous and broadleaved forests, marking a warm and humid climate. Changes in the composition of the forests indicate that both temperature and precipitation displayed obvious fluctuations during this period, i.e., cool and humid ca 7900- 7250 cal yr BP, warm and slightly humid ca 7250- 6050 cal yr BP, warm and humid between ca 6050 and 5100 cal yr BP, mild and slightly humid ca 5100- 4800 cal yr BP, and mild and humid ca 4800- 4450 cal yr BP. The period can be viewed as the Holocene optimum (characterized by a warm and moist climate) of north-central China, with the maximum (dominated both by warmest temperatures and by richest precipitations) occurring from ca 6050 to 5100 cal yr BP. During the period of ca 4450- 2900 cal yr BP, the woody plants declined, and the climate generally became cooler and drier than the preceding period. This period is characterized by a cold, dry episode from ca 4450 to 3950 cal yr BP, a warm, slightly humid interval between ca 3950 and 3500 cal yr BP and a mild, slightly dry episode from ca 3500 to 2900 cal yr BP, and appears to be a transition from warm and humid to cold and dry climatic conditions. Since ca 2900 cal yr ago, the forests disappeared and the vegetation density decreased, reflecting a cool and dry climate. However, a

  19. 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.

  20. 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

    Directory of Open Access Journals (Sweden)

    Ricardo JPS Guimarães

    2010-07-01

    Full Text Available 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.

  1. Assessing the Impacts of the 2009/2010 Drought on Vegetation Indices, Normalized Difference Water Index, and Land Surface Temperature in Southwestern China

    Directory of Open Access Journals (Sweden)

    Xiaoqiang Zhang

    2017-01-01

    Full Text Available Droughts are projected to increase in severity and frequency on both regional and global scales. Despite the increasing occurrence and intensity of the 2009/2010 drought in southwestern China, the impacts of drought on vegetation in this region remain unclear. We examined the impacts of the 2009/2010 drought in southwestern China on vegetation by calculating the standardized anomalies of Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Normalized Difference Water Index (NDWI, and Land Surface Temperature (LST. The standardized anomalies of NDVI, EVI, and NDWI exhibited positively skewed frequency distributions, while the standardized anomalies of LST exhibited a negatively skewed frequency distribution. These results implied that the NDVI, EVI, and NDWI declined, while LST increased in the 2009/2010 drought-stricken vegetated areas during the drought period. The responses of vegetation to the 2009/2010 drought differed substantially among biomes. Savannas, croplands, and mixed forests were more vulnerable to the 2009/2010 drought than deciduous forest and grasslands, while evergreen forest was resistant to the 2009/2010 drought in southwestern China. We concluded that the 2009/2010 drought had negative impacts on vegetation in southwestern China. The resulting assessment on the impacts of drought assists in evaluating and mitigating its adverse effects in southwestern China.

  2. Rational groundwater table indicated by the eco-physiological parameters of the vegetation: A case study of ecological restoration in the lower reaches of the Tarim River

    Institute of Scientific and Technical Information of China (English)

    CHEN Yaning; WANG Qiang; LI Weihong; RUAN Xiao; CHEN Yapeng; ZHANG Lihua

    2006-01-01

    The eco-physiological response and adaptation of Populus euphratica Oliv and Tamarix ramosissima Ldb during water release period were investigated. Nine typical areas and forty-five transects were selected along the lower reaches of Tarim River. The groundwater table as well as plant performance and the contents of proline, soluble sugars,and plant endogenous hormone (ABA, CTK) in leaves were monitored and analyzed. The groundwater table was raised in different areas and transects by water release program. The physiological stress to P. euphratica and T. ramosissima had been reduced after water release. Our results suggested that the groundwater table in the studied region remained at-3.15 to -4.12 m, the proline content from 9.28 to 11.06 (mmol/L), the soluble sugar content from 224.71 to 252.16 (mmol/L), the ABA content from 3.59 to 5.01 (ng/g FW), and the CK content from 4.01 to 4.56 (ng/g FW), for the optimum growth and restoration of P. euphratica indicated by the plant performance parameters and the efficiency of water application was the highest. The groundwater table in the studied region remained at -2.16 to -3.38 m, the proline content from 12.15 to 14.17 (mmol/L), the soluble sugar content from 154.71 to 183.16 (mmol/L), the ABA content from 2.78 to 4.86 (ng/g FW), and the CK content from 3.78 to 4.22 (ng/g FW), for the optimum growth and restoration of T. ramosissima indicated by the plant performance parameters and the efficiency of water application was the highest. The rational groundwater table for the restoration of vegetation in the studied region was at -3.15 to -3.38 m.

  3. Vegetation Change Prediction with Geo-Information Techniques in the Three Gorges Area of China

    Institute of Scientific and Technical Information of China (English)

    M.T.JABBAR; SHI Zhi-Hua; WANG Tian-Wei; CAI Chong-Fa

    2006-01-01

    A computerized parametric methodology was applied to monitor, map, and estimate vegetation change in combination with "3S" (RS-remote sensing, GIS-geographic information systems, and GPS-global positioning system) technology and change detection techniques at a 1:50 000 mapping scale in the Letianxi Watershed of western Hubei Province, China.Satellite images (Landsat TM 1997 and Landsat ETM 2002) and thematic maps were used to provide comprehensive views of surface conditions such as vegetation cover and land use change. With ER Mapper and ERDAS software, the normalized difference vegetation index (NDVI) was computed and then classified into six vegetation density classes. ARC/INFO and ArcView software were used along with field observation data by GPS for analysis. Results obtained using spatial analysis methods showed that NDVI was a valuable first cut indicator for vegetation and land use systems. A regression analysis revealed that NDVI explained 94.5% of the variations for vegetation cover in the largest vegetation area, indicating that the relationship between vegetation and NDVI was not a simple linear process. Vegetation cover increased in four of areas.This meant 60.9% of land area had very slight to slight vegetation change, while 39.1% had moderate to severe vegetation change. Thus, the study area, in general, was exposed to a high risk of vegetation cover change.

  4. 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.

  5. Teleconnection between ENSO and Vegetation

    Science.gov (United States)

    Kogan, F.

    Since 1980s strong ENSO disturbed weather environment economy and human lives worldwide Total impact of these events on society is estimated in billions of dollars and consequences include famine human health problems loss of life property damage and destruction of the environment Areas sensitive to ENSO have been identified in some world areas from climatic records and recently from 15-year satellite data This presentation examines teleconnection between ENSO and terrestrial ecosystems worldwide using 24-year satellite and in situ data records ENSO events were characterized by monthly sea surface temperature SST anomalies in the tropical Pacific They were collected from the improved SST analysis data set Reynolds and Smith 1994 Average anomalies were calculated for the region 5 r N - 5 r S and 170 r - 120 r E 3 4 area Terrestrial ecosystems were presented by the vegetation health condition indices VHI Kogan 1997 The VHIs derived from AVHRR-based NDVI and 10-11 Phi m thermal radiances were designed to monitor moisture and thermal impacts on vegetation health greenness and vigor Two types of responses were identified In boreal winter ecosystems of northern South America southern Africa and Southeast Asia experienced severe moisture and thermal stress during El Ni n o and favorable conditions during La Ni n a years In central South America and the Horn of Africa regions the response was opposite World ecosystems are less sensitive to SSTs during boreal summer except for the areas in northern Brazil

  6. Vegetation Phenology Metrics Derived from Temporally Smoothed and Gap-filled MODIS Data

    Science.gov (United States)

    Tan, Bin; Morisette, Jeff; Wolfe, Robert; Esaias, Wayne; Gao, Feng; Ederer, Greg; Nightingale, Joanne; Nickeson, Jamie E.; Ma, Pete; Pedely, Jeff

    2012-01-01

    Smoothed and gap-filled VI provides a good base for estimating vegetation phenology metrics. The TIMESAT software was improved by incorporating the ancillary information from MODIS products. A simple assessment of the association between retrieved greenup dates and ground observations indicates satisfactory result from improved TIMESAT software. One application example shows that mapping Nectar Flow Phenology is tractable on a continental scale using hive weight and satellite vegetation data. The phenology data product is supporting more researches in ecology, climate change fields.

  7. 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.

  8. The experience of land cover change detection by satellite data

    Institute of Scientific and Technical Information of China (English)

    Lev SPIVAK; Irina VITKOVSKAYA; Madina BATYRBAYEVA; Alexey TEREKHOV

    2012-01-01

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan.As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan.The major process of desertification takes place in the arid and semi-arid areas.To allocate spots of stable degradation of vegetation,the transition zone was first identified.Productivity of vegetation in transfer zone is slightly dependent on climate conditions.Multi-year digital maps of vegetation index were generated with NOAA satellite images.According to the result,the territory of the republic was zoned by means of vegetation productivity criterion.All the arable lands in Kazakhstan are in the risky agriculture zone.Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture,where natural factors,such as wind and water erosion,can significantly change land quality in a relatively short time period.We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from lowresolution satellite data for all of Kazakhstan.This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  9. Análise da dinâmica sazonal e separabilidade espectral de algumas fitofisionomias do cerrado com índices de vegetação dos sensores MODIS/TERRA e AQUA Analysis of the seasonal dynamics and spectral separability of some savanna physiognomies with vegetation indices derived from MODIS/TERRA AND AQUA

    Directory of Open Access Journals (Sweden)

    Veraldo Liesenberg

    2007-04-01

    Full Text Available Composições de 16 dias de índices de vegetação do sensor MODerate resolution Imaging Spectroradiometer (MODIS, com resolução espacial de 1km, a bordo dos satélites TERRA e AQUA, foram usadas para caracterizar a dinâmica sazonal em 2004 de cinco fitofisionomias de Cerrado e analisar a sua separabilidade espectral. Os índices Normalized Difference Vegetation Index (NDVI e Enhanced Vegetation Index (EVI, calculados a partir dos dados dos sensores de ambas as plataformas e de uma base comum de pixels, foram comparados entre si. Os resultados indicaram que: (a dentre as fitofisionomias estudadas, a Floresta Estacional decídua apresentou uma dinâmica sazonal muito marcante em função da perda de folhas da estação chuvosa para a seca (substancial redução nos índices e do rápido verdejamento com o início da precipitação no final de outubro (rápido incremento de NDVI e EVI; (b o NDVI mostrou maior variabilidade entre as classes de vegetação do que o EVI apenas na estação seca; (c a discriminação entre as fitofisionomias melhorou da estação chuvosa para a seca; (d o NDVI foi mais eficiente do que o EVI para discriminar as classes de vegetação na estação seca, ocorrendo o contrário na estação chuvosa; e (e na maioria das datas selecionadas para estudo, não houve diferenças estatisticamente significativas entre os índices de vegetação gerados de ambas as plataformas, apesar das variações na qualidade dos pixels selecionados para as composições de 16 dias e na geometria de iluminação e de visada.MODerate-resolution Imaging Spectroradiometer (MODIS 16-day vegetation index composites with 1 km of spatial resolution from TERRA and AQUA satellites were used to characterize the seasonal dynamics of five Brazilian savanna physiognomies and to analyze their spectral separability in 2004. The Normalized Difference Vegetation Index (NDVI and Enhanced Vegetation Index (EVI, using data from both platforms and from a

  10. 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.

  11. 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.

  12. 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.

  13. Evapotranspiration estimation in heterogeneous urban vegetation

    Science.gov (United States)

    Nagler, P. L.; Nouri, H.; Beecham, S.; Anderson, S.; Sutton, P.; Chavoshi, S.

    2015-12-01

    Finding a valid approach to measure the water requirements of mixed urban vegetation is a challenge. Evapotranspiration (ET) is the main component of a plant's water requirement. A better understanding of the ET of urban vegetation is essential for sustainable urbanisation. Increased implementation of green infrastructure will be informed by this work. Despite promising technologies and sophisticated facilities, ET estimation of urban vegetation remains insufficiently characterized. We reviewed the common field, laboratory and modelling techniques for ET estimation, mostly agriculture and forestry applications. We opted for 3 approaches of ET estimation: 1) an observational-based method using adjustment factors applied to reference ET, 2) a field-based method of Soil Water Balance (SWB) and 3) a Remote Sensing (RS)-based method. These approaches were applied to an experimental site to evaluate the most suitable ET estimation approach for an urban parkland. To determine in-situ ET, 2 lysimeters and 4 Neutron Moisture Meter probes were installed. Based on SWB principles, all input water (irrigation, precipitation and upward groundwater movements) and output water (ET, drainage, soil moisture and runoff) were measured monthly for 14 months. The observation based approach and the ground-based approach (SWB) were compared. Our predictions were compared to the actual irrigation rates (data provided by the City Council). Results suggest the observational-based method is the most appropriate urban ET estimation. We examined the capability of RS to estimate ET for urban vegetation. Image processing of 5 WorldView2 satellite images enabled modelling of the relationship between urban vegetation and vegetation indices derived from high resolution images. Our results indicate that an ETobservational-based -NDVI modelling approach is a reliable method of ET estimation for mixed urban vegetation. It also has the advantage of not depending on extensive field data collection.

  14. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

    Science.gov (United States)

    Gu, Y.; Hunt, E.; Wardlow, B.; Basara, J.B.; Brown, J.F.; Verdin, J.P.

    2008-01-01

    The evaluation of the relationship between satellite-derived vegetation indices (normalized difference vegetation index and normalized difference water index) and soil moisture improves our understanding of how these indices respond to soil moisture fluctuations. Soil moisture deficits are ultimately tied to drought stress on plants. The diverse terrain and climate of Oklahoma, the extensive soil moisture network of the Oklahoma Mesonet, and satellite-derived indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) provided an opportunity to study correlations between soil moisture and vegetation indices over the 2002-2006 growing seasons. Results showed that the correlation between both indices and the fractional water index (FWI) was highly dependent on land cover heterogeneity and soil type. Sites surrounded by relatively homogeneous vegetation cover with silt loam soils had the highest correlation between the FWI and both vegetation-related indices (r???0.73), while sites with heterogeneous vegetation cover and loam soils had the lowest correlation (r???0.22). Copyright 2008 by the American Geophysical Union.

  15. 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.

  16. Assessing Leaf Area Index from High Resolution Satellite Datasets for Maize in Trans Nzoia County, Kenya

    Science.gov (United States)

    Bartolomew Thiongo, Kuria; Menz, Gunter; Thonfeld, Frank

    2016-08-01

    The Normalized Differenced Vegetation Index (NDVI) and the two band Enhanced vegetation Index (EVI2) derived from RapidEye and Landsat 8 satellite images were evaluated against the empirically derived terrestrial Leaf Area Index (LAI) acquired during the maize growth season April to November, 2015 and covering the phenological growth stages prescribed in the BBCH code. The results indicate a high correlation of the vegetation indices plotted over the entire maize season with R2 values of 88% and 83% for NDVI and EVI2 respectively. The maximum values were found to occur during the maize vegetative phase in the months of July and August. The correlation between the vegetation indices and the LAI had R2 values of 50% and 49% for NDVI and EVI2 respectively. Alternative methods of estimating and calculating the LAI values may improve the achieved results.

  17. 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

  18. Temporal Trends and Spatial Variability of Vegetation Phenology over the Northern Hemisphere during 1982-2012.

    Science.gov (United States)

    Wang, Siyuan; Yang, Bojuan; Yang, Qichun; Lu, Linlin; Wang, Xiaoyue; Peng, Yaoyao

    2016-01-01

    Satellite-derived vegetation phenology has been recognized as a key indicator for detecting changes in the terrestrial biosphere in response to global climate change. However, multi-decadal changes and spatial variation of vegetation phenology over the Northern Hemisphere and their relationship to climate change have not yet been fully investigated. In this article, we investigated the spatial variability and temporal trends of vegetation phenology over the Northern Hemisphere by calibrating and analyzing time series of the satellite-derived normalized difference vegetation index (NDVI) during 1982-2012, and then further examine how vegetation phenology responds to climate change within different ecological zones. We found that during the period from 1982 to 2012 most of the high latitude areas experienced an increase in growing period largely due to an earlier beginning of vegetation growing season (BGS), but there was no significant trend in the vegetation growing peaks. The spatial pattern of phenology within different eco-zones also experienced a large variation over the past three decades. Comparing the periods of 1982-1992, 1992-2002 with 2002-2012, the spatial pattern of change rate of phenology shift (RPS) shows a more significant trend in advancing of BGS, delaying of EGS (end of growing season) and prolonging of LGS (length of growing season) during 2002-2012, overall shows a trend of accelerating change. Temperature is a major determinant of phenological shifts, and the response of vegetation phenology to temperature varied across different eco-zones.

  19. Thermophilous fringe communities as an indicator of vegetation changes: a case study of the “Murawy Dobromierskie” steppe reserve (Poland

    Directory of Open Access Journals (Sweden)

    Szygendowski Tomasz

    2015-12-01

    Full Text Available In this paper, changes of the non-forest xerothermic vegetation of the “Murawy Dobromierskie” steppe reserve which occurred in the period 1993-2012 are examined. The material comprises 50 relevés, of which 43 date from 2012 and the other 7 - from 1993. Reléves were arranged in 5 analytic tables. A synoptic table was also compiled, and for each syntaxonomical species group distinguished, values of the cover coefficient (C, the collective group share index (G, and the systematic group value (D were estimated and compared. On the basis of the obtained results, a significant decline in abundancy and/or constancy was observed within the following groups: Ch. Artemisietea vulgaris, Ch. Cirsio-Brachypodion pinnati, Ch. Festuco-Brometea, Ch. Geranion sanguinei, Ch. Koelerio-Corynephoretea, and Ch. Origanetalia and Trifolio-Geranietea sanguinei, whereas for the taxa of the Rhamno-Prunetea, a notable increase in the share of the reserve vegetation was recorded. A sizeable expansion of the moss layer was also observed in this period. The results are discussed with special regard to differences in the methodical background of both field studies.

  20. 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

  1. 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.

  2. Analysis of rainfall deficit and its impact on the Oltenia Plain vegetation using satellite images from the period 2000-2009

    Directory of Open Access Journals (Sweden)

    IRINA ONTEL

    2012-04-01

    Full Text Available Análisis de los déficit de precipitación y su impacto sobre la vegetación de Oltenia Illano usando imágenes de satélite durante el período 2000-2009. Este investigación pretende evaluar el déficit de precipitaciones en temporada de verano y su impacto sobre la vegetación. Disminución de las precipitaciones en comparación con el valor medio representa el primer firme que precede el sequía. El análisis de los resultados de el Índice de Precipitación Estandarizado calculado por tres meses (SPI-3 y el mes (SPI-1, reveló que durante 2000-2009 en la Oltenia Illano tuvimos 5-6 años deficientes de precipitation de los cuales 2 años fueron calificados como los años secos y muy secos. Este déficit se observa en el análisis de satélite productos, NDVI y LAI obtenido por procesamiento de imágenes Spot-Vegetation y MODIS en la tercera década de cada mes de verano. Las imágenes de satélite revelan las diferencias temporales y espaciales de esta parametro meteorologico y el impacto que tiene en la vegetación de la llanura de Oltenia.

  3. Evaluating Vegetation Health Condition Using MODIS Data in the Three Gorges Area, China

    Institute of Scientific and Technical Information of China (English)

    韩贵锋; 谢雨丝; 蔡智

    2015-01-01

    The satellite-based vegetation condition index (VCI) and temperature condition index (TCI) have been used extensively for drought detection and tracking, the assessment of weather impacts on vegetation and evaluation of the health and productivity of vegetation. In this study, in order to detect and monitor the growth condition of vegetation, we have collected data on vegetation indices and land surface temperature derived from MODIS (2001-2012) and deifned a vegetation health index (VHI) based on VCI and TCI for assessing vegetation health condition in the Three Gorges Area, China (TGA). The results of the study show that temporal and spatial characteristics of vegetation health condition can be detected, tracked and mapped by the VHI index. In most parts of the TGA, the vegetation health condition showed an overall increasing trend during the study period, especially in Wulong, Fengdu, Shizhu and other regions located in the midstream sections of the Three Gorges Reservoir. In addition, the four studied vegetation types all showed clear increasing trends during the study period. The increasing trend in the vegetation health condition shows a strong positive correlation with topographical slope and altitude (below 500 m). Over the seasons, this trend is strongest in autumn, followed by spring. However, the correlations between vegetation health condition and climatic factors are more frequently significant in summer and winter than in autumn and spring. The vegetation health condition has been low in 2006 and 2011. This finding is consistent with the extreme weather conditions in those two years. However, only in the summer is vegetation health condition signiifcantly correlated with three climatic factors in most of the study area. This result implies that vegetation growth may show a lagged response to climatic factors and may also be affected by human activities, including agricultural activities, industrial activities and other economic activities.

  4. Satellite Communication.

    Science.gov (United States)

    Technology Teacher, 1985

    1985-01-01

    Presents a discussion of communication satellites: explains the principles of satellite communication, describes examples of how governments and industries are currently applying communication satellites, analyzes issues confronting satellite communication, links mathematics and science to the study of satellite communication, and applies…

  5. 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

    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...

  6. Quantifying influences of physiographic factors on temperate dryland vegetation, Northwest China

    Science.gov (United States)

    Du, Ziqiang; Zhang, Xiaoyu; Xu, Xiaoming; Zhang, Hong; Wu, Zhitao; Pang, Jing

    2017-01-01

    Variability in satellite measurements of terrestrial greenness in drylands is widely observed in land surface processes and global change studies. Yet the underlying causes differ and are not fully understood. Here, we used the GeogDetector model, a new spatial statistical approach, to examine the individual and combined influences of physiographic factors on dryland vegetation greenness changes, and to identify the most suitable characteristics of each principal factor for stimulating vegetation growth. Our results indicated that dryland greenness was predominantly affected by precipitation, soil type, vegetation type, and temperature, either separately or in concert. The interaction between pairs of physiographic factors enhanced the influence of any single factor and displayed significantly non-linear influences on vegetation greenness. Our results also implied that vegetation greenness could be promoted by adopting favorable ranges or types of major physiographical factors, thus beneficial for ecological conservation and restoration that aimed at mitigating environmental degradation. PMID:28067259

  7. US Forest Service LANDFIRE Existing Vegetation

    Data.gov (United States)

    US Forest Service, Department of Agriculture — LANDFIRE Existing Vegetation is mapped using predictive landscape models based on extensive field-referenced data, satellite imagery and biophysical gradient layers...

  8. Test of multi-spectral vegetation index for floating and canopy-forming submerged vegetation.

    Science.gov (United States)

    Cho, Hyun Jung; Kirui, Philemon; Natarajan, Harene

    2008-12-01

    Remote sensing of terrestrial vegetation has been successful thanks to the unique spectral characteristics of green vegetation, low reflectance in red and high reflectance in Near-InfraRed (NIR). These spectral characteristics were used to develop vegetation indices, including Normalized Difference Vegetation Index (NDVI). However, the NIR absorption by water and light scattering from suspended particles reduces the practical application of such indices in aquatic vegetation studies, especially for the Submerged Aquatic Vegetation (SAV) that grows below water surface. We experimentally tested if NDVI can be used to depict canopies of aquatic plants in shallow waters. A 100-gallonoutdoor tank was lined with black pond liners, a black panel or SAV shoots were mounted on the bottom, and filled with water up to 0.5 m. We used a GER 1500 spectroradiometer to collect spectral data over floating waterhyacinth (Eichhornia crassipes) and also over the tanks that contain SAV and black panel at varying water depths. The measured upwelling radiance was converted to % reflectance; and we integrated the hyperspectral reflectance to match the Red and NIR bands of three satellite sensors: Landsat 7 ETM, SPOT 5 HRG, and ASTER. NDVI values ranged 0.6-0.65 when the SAV canopy was at the water level, then they decreased linearly (slope of 0.013 NDVI/meter) with water depth increases in clear water. When corrected for water attenuation using the data obtained from the black panel, the NDVI values significantly increased at all depths that we tested (0.1 - 0.5 m). Our results suggest the conventional NDVI: (1) can be used to depict SAV canopies at water surface; (2) is not a good indicator for SAV that is adapted to live underwater or other aquatic plants that are submerged during flooding even at shallow waters (0.3 m); and (3) the index values can significantly improve if information on spectral reflectance attenuation caused by water volume increases is collected simultaneously

  9. 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

    2017-05-01

    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.

  10. Development of JPSS VIIRS Global Gridded Vegetation Index products for NOAA NCEP Environmental Modeling Systems

    Science.gov (United States)

    Vargas, Marco; Miura, Tomoaki; Csiszar, Ivan; Zheng, Weizhong; Wu, Yihua; Ek, Michael

    2017-04-01

    The first Joint Polar Satellite System (JPSS) mission, the Suomi National Polar-orbiting Partnership (S-NPP) satellite, was successfully launched in October, 2011, and it will be followed by JPSS-1, slated for launch in 2017. JPSS provides operational continuity of satellite-based observations and products for NOAA's Polar Operational Environmental Satellites (POES). Vegetation products derived from satellite measurements are used for weather forecasting, land modeling, climate research, and monitoring the environment including drought, the health of ecosystems, crop monitoring and forest fires. The operationally produced S-NPP VIIRS Vegetation Index (VI) Environmental Data Record (EDR) includes two vegetation indices: the Top of the Atmosphere (TOA) Normalized Difference Vegetation Index (NDVI), and the Top of the Canopy (TOC) Enhanced Vegetation Index (EVI). For JPSS-1, the S-NPP Vegetation Index EDR algorithm has been updated to include the TOC NDV. The current JPSS operational VI products are generated in granule style at 375 meter resolution at nadir, but these products in granule format cannot be ingested into NOAA operational monitoring and decision making systems. For that reason, the NOAA JPSS Land Team is developing a new global gridded Vegetation Index (VI) product suite for operational use by the NOAA National Centers for Environmental Prediction (NCEP). The new global gridded VIs will be used in the Multi-Physics (MP) version of the Noah land surface model (Noah-MP) in NCEP NOAA Environmental Modeling System (NEMS) for plant growth and data assimilation and to describe vegetation coverage and density in order to model the correct surface energy partition. The new VI 4km resolution global gridded products (TOA NDVI, TOC NDVI and TOC EVI) are being designed to meet the needs of directly ingesting vegetation index variables without the need to develop local gridding and compositing procedures. These VI products will be consistent with the already

  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. 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 < 0.001). The mean objectively measured distance to the farmers’ markets where 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.

  13. USE LANDSAT IMAGE TO EVALUATE VEGETATION STAGE IN SUNFLOWER CROPS

    Directory of Open Access Journals (Sweden)

    Mihai Valentin HERBEI

    2015-10-01

    Full Text Available Remote sensing is of great interest for the study and characterization of the vegetation and of the agricultural crops, in order to monitor them and to develop predictable patterns regarding the evolution of the crops and also for the purpose of the decision making process in real time. The main purpose of this research was the study of the sunflower crops dynamics based on spectral information obtained from satellite images. Vegetation dynamics was differently expressed by the indexes NDVI, NDBR and NDMI determined based on spectral information. NDVI has registered an ascending slope since the beginning of the vegetation period until the flowering (65 BBCH code when the maximum value was recorded (NDVIGS6 = 0.4074. Later the distribution of this indicator recorded a descending slope until the physiological maturity.

  14. The relationship between cloud condensation nuclei (CCN concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates

    Directory of Open Access Journals (Sweden)

    Y. Shinozuka

    2015-01-01

    Full Text Available We examine the relationship between the number concentration of boundary-layer cloud condensation nuclei (CCN and light extinction to investigate underlying aerosol processes and satellite-based CCN estimates. Regression applied to a variety of airborne and ground-based measurements identifies the CCN (cm−3 at 0.4 ± 0.1% supersaturation with 100.3α +1.3 σ0.75 where σ (M m−1 is the 500 nm extinction coefficient by dried particles and α is the Angstrom exponent. The deviation of one kilometer horizontal average data from this approximation is typically within a factor of 2.0. ∂ log CCN/∂ log σ is less than unity because, among other explanations, aerosol growth processes generally make particles scatter more light without increasing their number. This, barring extensive data aggregation and special meteorology-aerosol connect