Search results for "Vegetation Index"

showing 10 items of 170 documents

Comparison between SMOS Vegetation Optical Depth products and MODIS vegetation indices over crop zones of the USA

2014

The Soil Moisture and Ocean Salinity (SMOS) mission provides multi-angular, dual-polarised brightness temperatures at 1.4 GHz, from which global soil moisture and vegetation optical depth (tau) products are retrieved. This paper presents a study of SMOS' tau product in 2010 and 2011 for crop zones of the USA. Retrieved tau values for 504 crop nodes were compared to optical/IR vegetation indices from the MODES (Moderate Resolution Imaging Spectroradiometer) satellite sensor, including the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVE), Leaf Area Index (LAI), and a Normalised Difference Water Index (NOW!) product. tau values were observed to increase during the…

2. Zero hunger010504 meteorology & atmospheric sciences0211 other engineering and technologiesSoil ScienceGrowing seasonGeology02 engineering and technologyVegetationEnhanced vegetation index01 natural sciencesNormalized Difference Vegetation Indexvegetation optical depthLinear regressionEnvironmental scienceL-band radiometryModerate-resolution imaging spectroradiometerComputers in Earth SciencesLeaf area indexoptical vegetation indices[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingWater contentSMOS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Seasonal variations of leaf area index of agricultural fields retrieved from Landsat data

2008

Abstract The derivation of leaf area index (LAI) from satellite optical data has been the subject of a large amount of work. In contrast, few papers have addressed the effective model inversion of high resolution satellite images for a complete series of data for the various crop species in a given region. The present study is focused on the assessment of a LAI model inversion approach applied to multitemporal optical data, over an agricultural region having various crop types with different crop calendars. Both the inversion approach and data sources are chosen because of their wide use. Crops in the study region (Barrax, Castilla–La Mancha, Spain) include: cereal, corn, alfalfa, sugar bee…

2. Zero hunger010504 meteorology & atmospheric sciencesPhenology0211 other engineering and technologiesSoil ScienceInverse transform samplingGeologyInversion (meteorology)02 engineering and technology15. Life on land01 natural sciencesNormalized Difference Vegetation IndexCropEnvironmental sciencePlant coverComputers in Earth SciencesLeaf area indexEmpirical relationship021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Sentinel-1 & Sentinel-2 Data for Soil Tillage Change Detection

2018

In this paper, an algorithm using Sentinel-1 (S-1) and Sentinel-2 (S-2) data to identify changes of tillage over agricultural fields at approximately similar to 100m resolution is presented. The methodology implements a multiscale temporal change detection on S-1 VH backscatter in order to single out VH changes due to agricultural practices only. The algorithm can be applied over bare or scarcely vegetated agricultural fields, which are identified from S-2 NDVI measurements. An initial assessment at farm scale using in situ and S-1 and SPOT5-Take5 data, acquired over the Apulian Tavoliere in southern Italy in 2015, is illustrated. A full validation of the approach is in progress over three …

2. Zero hunger010504 meteorology & atmospheric sciencessoil tillage change identificationbusiness.industry04 agricultural and veterinary sciencesSoil tillage01 natural sciencesNormalized Difference Vegetation IndexTillageAgriculture040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceSentinel-1Temporal changePhysical geographyTime seriesSentinel-2Scale (map)businessChange detection0105 earth and related environmental sciencesIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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An agent-based model of a cutaneous leishmaniasis reservoir host, Meriones shawi

2021

International audience; Meriones shawi (M.shawi) is the main reservoir host for zoonotic cutaneous leishmaniasis (ZCL) in Central Tunisia. The incorporation of environmental and climatic effects on the spread of ZCL in M. shawi remains difficult. This study presents an agent-based model (ABM) to overcome these difficulties and examine the impact of environment (i.e. vegetation cover) and climate (i.e. temperature) on M. shawi movement and prevalence. The model simulation considers two agent types: rodent agent and field unit agent. We tested the model according to two types of rodent movement: random and thoughtful. We integrated time dependent normalized difference vegetation index (NDVI) …

2. Zero hunger0106 biological sciencesAgent-based model[SDV.EE]Life Sciences [q-bio]/Ecology environmentMeriones shawibiologyEcology010604 marine biology & hydrobiologyEcological ModelingLand covermedicine.diseasebiology.organism_classification010603 evolutionary biology01 natural sciencesNormalized Difference Vegetation IndexVegetation coverCutaneous leishmaniasis13. Climate actionModel simulationmedicineZoonotic cutaneous leishmaniasis[SDE.BE]Environmental Sciences/Biodiversity and Ecology
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Land use classification from multitemporal Landsat imagery using the Yearly Land Cover Dynamics (YLCD) method

2011

Abstract Several previous studies have shown that the inclusion of the LST (Land Surface Temperature) parameter to a NDVI (Normalized Difference Vegetation Index) based classification procedure is beneficial to classification accuracy. In this work, the Yearly Land Cover Dynamics (YLCD) approach, which is based on annual behavior of LST and NDVI, has been used to classify an agricultural area into crop types. To this end, a time series of Landsat-5 images for year 2009 of the Barrax (Spain) area has been processed: georeferenciation, destriping and atmospheric correction have been carried out to estimate NDVI and LST time series for year 2009, from which YLCD parameters were estimated. Then…

2. Zero hungerGlobal and Planetary Change010504 meteorology & atmospheric sciencesLand surface temperatureLand useVegetation classification0211 other engineering and technologiesAtmospheric correction02 engineering and technologyLand cover15. Life on landManagement Monitoring Policy and Law01 natural sciencesNormalized Difference Vegetation IndexCropGeographyComputers in Earth SciencesScale (map)021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesRemote sensingInternational Journal of Applied Earth Observation and Geoinformation
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Are remote sensing evapotranspiration models reliable across South American ecoregions?

2021

Many remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM-MOD), and Penman–Monteith Nagler model (PME-VI).…

ATMOSPHERE WATER FLUXVEGETATION INDEXCalibration (statistics)Penman-MonteithBiomeRIPARIAN EVAPOTRANSPIRATIONFluxLand coverSURFACE-TEMPERATUREtranspirationSEMIARID ENVIRONMENTCARBON-DIOXIDEENERGY-BALANCE CLOSUREEvapotranspirationPenman–Monteith equationWater Science and TechnologyRemote sensingRAINFALL INTERCEPTIONLand useWACMOS-ET PROJECTEDDY COVARIANCE MEASUREMENTSMODISEarth and Environmental SciencesEnvironmental sciencePriestley-TaylorScale (map)
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Multisensor comparison of NDVI for a semi‐arid environment in Spain

2009

The joint use of multiresolution sensors from different satellites offers many opportunities to describe vegetation and its dynamics. This paper introduces the concept of a virtual constellation (defined as an ensemble of all Earth Observation satellites in orbit that satisfy common requirements) for agricultural applications and contributes to providing the necessary inter-sensor calibration methodology for spectral reflectances and NDVI. For this purpose, we performed an observational study, comparing reflectances and the Normalized Difference Vegetation Index (NDVI), from near-synchronous image pairs of Landsat 7 Enhanced Thematic Mapper Plus (ETM+), as the reference sensor and Landsat 5…

Advanced Spaceborne Thermal Emission and Reflection RadiometerRadiometerAdvanced very-high-resolution radiometerThematic MapperGeneral Earth and Planetary SciencesEnvironmental scienceSatellite imageryVegetationPrecision agricultureNormalized Difference Vegetation IndexRemote sensingInternational Journal of Remote Sensing
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Improved land surface emissivities over agricultural areas using ASTER NDVI

2006

Abstract Land surface emissivity retrieval over agricultural regions is important for energy balance estimations, land cover assessment and other related environmental studies. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) produces images of sufficient spatial resolution (from 15 m to 90 m) to be of use in agricultural studies, in which fields of crops are too small to be well-resolved by low resolution sensors. The ASTER project generates land surface emissivity images as a Standard Product (AST05) using the Temperature/Emissivity Separation (TES) algorithm. However, the TES algorithm is prone to scaling errors in estimating emissivities for surfaces with low s…

Advanced Spaceborne Thermal Emission and Reflection RadiometerRadiometerMean squared errorAtmospheric correctionEmissivitySoil ScienceEnvironmental scienceGeologyLand coverComputers in Earth SciencesImage resolutionNormalized Difference Vegetation IndexRemote sensingRemote Sensing of Environment
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Vegetation dynamics from NDVI time series analysis using the wavelet transform

2009

A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to study NDVI time series. These series, which are non-stationary and present short-term, seasonal and long-term variations, can be decomposed using this MRA as a sum of series associated with different temporal scales. The main focus of the paper is to check the potential of this MRA to capture and describe both intra- and inter-annual changes in the data, i.e., to discuss the ability of the proposed procedure to monitor vegetation dynamics at regional scale. Our approach concentrates on what wavelet analysis can tell us about a NDVI time series. On the one hand, the intra-annual series, linked to th…

Advanced very-high-resolution radiometerSoil ScienceWavelet transformGeologyVegetationLand coverSeasonalitymedicine.diseaseNormalized Difference Vegetation IndexWaveletmedicineComputers in Earth SciencesTime seriesRemote sensingMathematicsRemote Sensing of Environment
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How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

2016

This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spanning 4 continents and covering 15 crop types with corresponding Landsat satellite images. Best-fit functions for the LAI-VI relationships were generated and assessed in terms of crop type, vegetation index, level of radiometric/atmospheric processing, method of LAI measurement, as well as the time difference between LAI measurements and satellite overpass. These global LAI-VI relationships were evalu…

Agroecosystemagroecosystem modeling010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesRobust statisticsLAI; Vegetation Index; agriculture; Landsat; agroecosystem modeling02 engineering and technologyCrop01 natural sciencesUniversalityNormalized Difference Vegetation IndexArticleLAI-VI relationshipLeaf area indexlcsh:Science021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingagriculture2. Zero hungerGlobalEnhanced vegetation index15. Life on landLAIGeneral Earth and Planetary Scienceslcsh:QSymbolic regressionLandsatAgricultural landscapesVegetation Index
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