Search results for "vegetation index"

showing 10 items of 170 documents

Exploring the validity of the long term data record V4 database for land surface monitoring

2015

The last (and final) version of the Long Term Data Record (LTDR) — Version 4 — has been released recently by NASA. This database includes daily information for all AVHRR (Advanced Very High Resolution Radiometer) channels, as well as ancillary data, since July 1981 up to present. This database is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the estimation of vegetation indices at daily resolution, as well as the daily estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring. To that end, we first estimated NDVI (Normalized Difference Vegetation Index), LST, as well as e…

Ancillary dataSeries (stratigraphy)GeographyDatabaseAdvanced very-high-resolution radiometerLong term dataSolar zenith angleVegetationTime seriescomputer.software_genrecomputerNormalized Difference Vegetation IndexRemote sensing2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp)
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Feasibility of hyperspectral vegetation indices for the detection of chlorophyll concentration in three high Arctic plants: Salix polaris, Bistorta v…

2018

Remote sensing, which is based on a reflected electromagnetic spectrum, offers a wide range of research methods. It allows for the identification of plant properties, e.g., chlorophyll, but a registered signal not only comes from green parts but also from dry shoots, soil, and other objects located next to the plants. It is, thus, important to identify the most applicable remote-acquired indices for chlorophyll detection in polar regions, which play a primary role in global monitoring systems but consist of areas with high and low accessibility. This study focuses on an analysis of in situ-acquired hyperspectral properties, which was verified by simultaneously measuring the chlorophyll conc…

Arctic plants010504 meteorology & atmospheric sciences0211 other engineering and technologiesRed edge:Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480 [VDP]02 engineering and technologyPlant Scienceremote sensing indices01 natural sciencesNormalized Difference Vegetation Indexchemistry.chemical_compoundremote sensinglcsh:BotanySalix polarisASD FieldSpecDryas octopetalaArctic vegetation021101 geological & geomatics engineering0105 earth and related environmental sciencesbiologyVegetationbiology.organism_classificationBistorta viviparalcsh:QK1-989chemistryChlorophyllEnvironmental sciencePhysical geographyActa Societatis Botanicorum Poloniae
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Discriminating irrigated and rainfed olive orchards with thermal ASTER imagery and DART 3D simulation

2009

Article in Press

Atmospheric Science010504 meteorology & atmospheric sciences0211 other engineering and technologiesBiometeorology02 engineering and technologyCanopy temperature01 natural sciencesNormalized Difference Vegetation IndexASTERAdvanced Spaceborne Thermal Emission and Reflection RadiometerVegetation indexEvapotranspirationRadiative transferIrrigatedSatellite imageryRainfed agricultureLeaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2. Zero hungerGlobal and Planetary ChangeForestry15. Life on landEnvironmental scienceDARTRainfedOrchardAgronomy and Crop ScienceAgricultural and Forest Meteorology
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Exploring the Validity of the Long-Term Data Record V4 Database for Land Surface Monitoring

2016

A new version of the long-term data record (LTDR)—Version 4—has been released recently by NASA. This database includes daily information for all advanced very high resolution radiometer channels, as well as ancillary data, from July 1981 up to present. This dataset is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the daily estimation of vegetation indices, as well as the estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring, especially as regards long-term trends and their validity. To that end, we estimated normalized difference vegetation index (NDVI), LST, as well …

Atmospheric Science010504 meteorology & atmospheric sciencesDatabaseAdvanced very-high-resolution radiometer0211 other engineering and technologiesSolar zenith angle02 engineering and technologyEnhanced vegetation indexVegetationcomputer.software_genre01 natural sciencesNormalized Difference Vegetation IndexAncillary dataEnvironmental scienceComputers in Earth SciencesTime seriescomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingInterpolationIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Evaluation of Disaggregation Methods for Downscaling MODIS Land Surface Temperature to Landsat Spatial Resolution in Barrax Test Site

2016

Thermal infrared (TIR) data are usually acquired at a coarser spatial resolution (CR) than visible and near infrared (VNIR). Several disaggregation methods have been recently developed to enhance the TIR spatial resolution using VNIR data. These approaches are based on the retrieval of a relation between TIR and VNIR data at CR, or training of a neural network, to be applied at the fine resolution afterward. In this work, different disaggregation methods are applied to the combination of two different sensors in the experimental test site of Barrax, Spain. The main objective is to test the feasibility of these techniques when applied to satellites provided with no TIR bands. Landsat and mod…

Atmospheric Science010504 meteorology & atmospheric sciencesMean squared errorNear-infrared spectroscopyTemperature0211 other engineering and technologies02 engineering and technology01 natural sciencesNormalized Difference Vegetation IndexVNIRRemote SensingSpectroradiometerImage resolutionImage enhancementLinear regressionEnvironmental scienceComputers in Earth SciencesImage resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingDownscalingIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran

2017

Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach…

Atmospheric Science010504 meteorology & atmospheric sciencesPhenology0211 other engineering and technologies1903 Computers in Earth Sciences02 engineering and technologyVegetationSeasonalitymedicine.disease01 natural sciencesNormalized Difference Vegetation IndexTrend analysis10122 Institute of GeographyClimatologyLinear regression1902 Atmospheric SciencemedicineEnvironmental sciencePrecipitationTime series910 Geography & travelComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciences
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A spatially consistent downscaling approach for SMOS using an adaptive window

2017

The European Space Agency (ESA)'s Soil Moisture and Ocean Salinity (SMOS) is the first spaceborne mission using L-band radiometry to monitor the Earth's global surface soil moisture (SM). After more than 7 years in orbit, many studies have contributed to improve the quality and applicability of SMOS-derived SM maps. In this research, a novel downscaling algorithm for SMOS is proposed to obtain high-resolution (HR) SM maps at 1 km (L4), from the ∼40 km native resolution of the instrument. This algorithm introduces the concept of a shape adaptive moving window as an improvement of the current semi-empirical downscaling approach at SMOS Barcelona Expert Center, based on the “universal triangle…

Atmospheric ScienceBrightnessTeledeteccióMean squared error010504 meteorology & atmospheric sciencesREMEDHUS0211 other engineering and technologiesHigh resolution02 engineering and technology01 natural sciencesNormalized Difference Vegetation IndexBECComputers in Earth SciencesImage resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingNative resolutionAdaptive moving windowLow resolutionMoving windowRemote sensing:Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció [Àrees temàtiques de la UPC]Orbit (dynamics)RadiometryEnvironmental scienceSpatial variabilitySoil moistureSòls -- HumitatDownscalingSMOS
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Analysis of winter dust activity off the coast of West Africa using a new 24-year over-water advanced very high resolution radiometer satellite dust …

2006

A 24-year (1982-2005) winter daytime advanced very high resolution radiometer (AVHRR) data set has been processed utilizing a new over-water dust detection algorithm. The dust data are for the oceanic regions surrounding West Africa and provide a long-term remotely sensed continuous record of dustiness in the region. These AVHRR dust observations are comparable to dust records produced via the Total Ozone Mapping Spectrometer and Meteosat instruments. Strong positive correlations between the wintertime Jones North Atlantic Oscillation index and this dust record are observed across the entire oceanic region, corroborating earlier studies on the relationship between the two. Also consistent w…

Atmospheric ScienceDaytimeEcologyAdvanced very-high-resolution radiometerTotal Ozone Mapping SpectrometerPaleontologySoil ScienceForestryVegetationAquatic ScienceOceanographyNormalized Difference Vegetation IndexGeophysicsSpace and Planetary ScienceGeochemistry and PetrologyNorth Atlantic oscillationClimatologyEarth and Planetary Sciences (miscellaneous)Environmental scienceSatellitePrecipitationEarth-Surface ProcessesWater Science and TechnologyJournal of Geophysical Research
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Integrated remote sensing approach to global agricultural drought monitoring

2018

Abstract This study explores the use of the Soil Moisture Agricultural Drought Index (SMADI) as a global estimator of agricultural drought. Previous research presented SMADI as a novel index based on the joint use of remotely sensed datasets of land surface temperature (LST) and normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) together with the surface soil moisture (SSM) from the Soil Moisture and Ocean Salinity (SMOS) mission. This study presents the results of applying SMADI at the global scale with a spatial resolution of 0.05° every 15 days. The period of the study spanned from 2010 to 2015. Three spatial scales (local, region…

Atmospheric ScienceGlobal and Planetary Changegeographygeography.geographical_feature_categoryIndex (economics)010504 meteorology & atmospheric sciencesWarning systembusiness.industry0211 other engineering and technologiesForestry02 engineering and technology01 natural sciencesNormalized Difference Vegetation IndexAgriculturePeninsulaClimatologyEnvironmental scienceModerate-resolution imaging spectroradiometerScale (map)businessAgronomy and Crop ScienceWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesAgricultural and Forest Meteorology
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Trend Analysis of Global MODIS-Terra Vegetation Indices and Land Surface Temperature Between 2000 and 2011

2013

Previous works have shown that the combination of vegetation indices with land surface temperature (LST) improves the analysis of vegetation changes. Here, global MODIS-Terra monthly data from 2000 to 2011 were downloaded and organized into LST, NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) time series. These time series were then corrected from cloud and atmospheric residual contamination through the IDR (iterative Interpolation for Data Reconstruction) method. Then, statistics were retrieved from both corrected time series, and the YLCD (Yearly Land Cover Dynamics) approach has been applied to data sources (NDVI-LST and EVI-LST) to analyze changes in th…

Atmospheric ScienceGlobal warmingEnhanced vegetation indexLand coverSpatial distributionNormalized Difference Vegetation IndexTrend analysisBorealClimatologymedicineEnvironmental scienceComputers in Earth Sciencesmedicine.symptomVegetation (pathology)IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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