Search results for "vegetation index"

showing 10 items of 170 documents

Spatio-temporal Vegetation Recuperation after a Grassland Fire in Lithuania

2013

The aim of this work is to study the spatio-temporal effects of a grassland fire in Lithuania. Immediately after the fire, a experimental plot was designed in a east-faced slope. Vegetation cover and height were measured 10, 17, 31 and 46 days after the fire (vegetation cover was only measured until 31 days after the fire because in the last measurement campaign the plot was completely covered). The results showed that vegetation recovered very fast. Ten days after the fire vegetation cover and height distribution were heterogeneous, decreasing with the time due to vegetation spread. Vegetation recovered was specially observed between 17 and 31 days after the fire due vegetation recuperatio…

Vegetation cover and heightHydrologygeographygeography.geographical_feature_categorySpatial structureVegetation recuperationLithuaniaSoil scienceEnhanced vegetation indexseparated by semicolonsspatial autocorrelationGrasslandVegetation coverNutrientGrassland firemedicineErosionType your keywords hereGeneral Earth and Planetary SciencesEnvironmental sciencemedicine.symptomVegetation (pathology)General Environmental ScienceProcedia Environmental Sciences
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A combined optical-microwave method to retrieve soil moisture over vegetated areas

2011

A simple approach for correcting for the effect of vegetation in the estimation of the surface soil moisture (wS) from L-band passive microwave observations is presented in this study. The approach is based on semi-empirical relationships between soil moisture and the polarized reflectivity including the effect of the vegetation optical depth which is parameterized as a function of the normalized vegetation difference index (NDVI). The method was tested against in situ measurements collected over a grass site from 2004 to 2007 (SMOSREX experiment). Two polarizations (horizontal/vertical) and five incidence angles (20◦, 30◦, 40◦, 50◦, and 60◦) were considered in the analysis. The best wS est…

Vegetation optical depthL band010504 meteorology & atmospheric sciencesNDVItélédétection0211 other engineering and technologiesSoil science02 engineering and technologyMicrowave methodsurface temperature01 natural sciencesNormalized Difference Vegetation Index[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsNDVI;LAI;LEAF AREA INDEX;SURFACE TEMPERATURE;SOIL MOISTURE;L-BAND medicineTraitement du signal et de l'imagenormalized vegetation difference index (NDVI)Electrical and Electronic EngineeringWater contentComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingSignal and Image processingsurface temperature.soil moisture (SM)Enhanced vegetation index15. Life on landLAIL-bandSOIL MOISTUREGeneral Earth and Planetary SciencesEnvironmental sciencemicrowave radiometrymedicine.symptomLEAF AREA INDEXVegetation (pathology)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMicrowave
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On the influences of vegetation biomass on COSMO-Skymed X-band

2011

The knowledge of spatial and temporal variability of land cover is important to manage water resources for yield forecasting, water stress prediction, irrigation water management and flood protection. Cloud cover dramatically reduces the temporal resolution of optical data thus limiting their operational use; in addition, the spatial resolution is often inadequate for applications in heterogeneous areas. On the other hand, algorithms based on Synthetic Aperture Radar (SAR) implemented to retrieve vegetation parameters are not yet fully validated. New SAR missions (COSMO-Skymed and Terrasar-X) may represent a suitable source of data for operational uses due to the high spatial and temporal r…

Water resourcesSynthetic aperture radarRemote Sensing HydrologyGeographyTemporal resolutionCloud coverSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaVegetationLand coverNormalized Difference Vegetation IndexOlive treesRemote sensingSPIE Proceedings
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CLEARMiner: a new algorithm for mining association patterns on heterogeneous time series from climate data

2010

International audience; Recently, improvements in sensor technology contributed to increasing in spatial data acquisition. The use of remote sensing in many countries and states, where agricultural business is a large part of their gross income, can provide a valuable source to improve their economy. The combination of climate and remote sensing data can reveal useful information, which can help researchers to monitor and estimate the production of agricultural crops. Data mining techniques are the main tools to analyze and extract relationships and patterns. In this context, this paper presents a new algorithm for mining association patterns in Geo-referenced databases of climate and satel…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Association rule learning[INFO.INFO-WB] Computer Science [cs]/WebComputer scienceAssociation (object-oriented programming)[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer scienceContext (language use)computer.software_genreNOAA-AVHRR imagesImage-based Information Systemsassociation rules[SCCO.COMP] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Spatial analysisAgricultural crops[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Series (mathematics)[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Remote sensing (archaeology)[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Data mining[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]Vegetation IndexAlgorithmcomputer
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Timing and patterns of ENSO impacts in Africa over the last 30 years: insights from Normalized Difference Vegetation Index data.

2012

International audience; In this study we reassess and provide a more complete picture of the timing and patterns of ENSO impacts for the whole of Africa over the three last decades. We analyse the vegetation photosynthetic activity estimated by the NOAA-AVHRR Normalized Difference Vegetation Index (NDVI) rather than rainfall itself, because NDVI allows us to document the impacts at fine space and time scales. The use of the monthly time-step adds important new insights to the findings of previous works based largely on annual or seasonal time-scales and on a regional spatial-scale: several dipolar and propagative patterns are highlighted. In addition, we show that the less-studied winter ra…

[ SDE.MCG ] Environmental Sciences/Global Changes[SDE.MCG] Environmental Sciences/Global Changes[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology[SDE.MCG]Environmental Sciences/Global ChangesAfricateleconnections[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/ClimatologyENSONormalized Difference Vegetation Index
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Different trends of neighboring populations of Lesser Kestrel: Effects of climate and other environmental conditions

2019

The sensitivity of population trends to the climate and environment is generally considered a species-specific trait. However, evidence that populations may show different responses to the climate and environmental conditions is growing. Whether this differential sensitivity may arise even among neighboring populations remains elusive. We compared the trends of two neighboring populations of the Lesser Kestrel Falco naumanni, using data from a 12-year survey of 158 colonies in Sicily, Italy; the two populations inhabiting a lowland and an highland area, respectively. Population trends were modeled through the TRIM algorithms implemented in R (package rtrim). A reversed U-shaped population t…

biologyEcologyglobal change migratory birds NAO NDVI population trend Sahel precipitation indexSettore BIO/05 - ZoologiaGlobal changeKestrelbiology.organism_classificationEcology Evolution Behavior and SystematicsNormalized Difference Vegetation Index
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Retrieving and broadcasting near-real-time biophysical parameters from MODIS and SEVIRI receiving stations at the global change unit of the Universit…

2015

We present here the automatic processing chains implemented at the Global Change Unit of the University of Valencia. These allow for a near-real-time retrieval of various biophysical parameters from both Sun-synchronous TERRA/AQUA Moderate Resolution Imaging Spectroradiometer MODIS and geostationary Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager MSG SEVIRI sensors. Retrieved parameters, namely sea and land surface temperatures SST and LST, respectively, normalized difference vegetation index NDVI, and vegetation condition index VCI, are similar for both sensors, and specific approaches have been developed and implemented for near-real-time parameter retrievals: htt…

biologyMeteorologybusiness.industryGlobal changeAutomatic processingVegetationBroadcastingbiology.organism_classificationNormalized Difference Vegetation IndexGeostationary orbitGeneral Earth and Planetary SciencesEnvironmental scienceModerate-resolution imaging spectroradiometerbusinessValenciaRemote sensingInternational Journal of Remote Sensing
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Nonlinear Time-Series Adaptation for Land Cover Classification

2017

Automatic land cover classification from satellite image time series is of paramount relevance to assess vegetation and crop status, with important implications in agriculture, biofuels, and food. However, due to the high cost and human resources needed to characterize and classify land cover through field campaigns, a recurrent limiting factor is the lack of available labeled data. On top of this, the biophysical–geophysical variables exhibit particular temporal structures that need to be exploited. Land cover classification based on image time series is very complex because of the data manifold distortions through time. We propose the use of the kernel manifold alignment (KEMA) method for…

domain adaptationComputer science0211 other engineering and technologies02 engineering and technologyLand coverNormalized Difference Vegetation IndexVegetation coverkernel methods0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringTime series021101 geological & geomatics engineeringRemote sensingManifold alignment[SHS.STAT]Humanities and Social Sciences/Methods and statisticsbusiness.industryVegetation15. Life on landGeotechnical Engineering and Engineering GeologyKernel methodKernel (image processing)Agriculturemanifold alignment020201 artificial intelligence & image processingSatellite Image Time SeriesLand cover classificationtime seriesScale (map)businessIEEE Geoscience and Remote Sensing Letters
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SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product

2017

© 2017 by the authors. The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product that was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d'Etudes Spatiales de la BIOsphère). One of the main go…

environmental_sciencesL bandVegetation optical depth010504 meteorology & atmospheric sciencesNDVI[SDV]Life Sciences [q-bio]Science0211 other engineering and technologiesWeather forecasting0207 environmental engineeringSoil science02 engineering and technologycomputer.software_genre01 natural sciencesSMOS; L-band; Level 3; ECMWF; SMOS-IC; soil moisture; vegetation optical depth; MODIS; NDVINormalized Difference Vegetation IndexECMWFvegetation optical depthtempératurehumidité du solluminosity14. Life underwater020701 environmental engineeringWater content021101 geological & geomatics engineeringRemote sensing0105 earth and related environmental sciencessalinité des océansQBiosphereluminositéVegetationAlbedoL-bandSpectroradiometerMODIS13. Climate actionBrightness temperatureProduct (mathematics)General Earth and Planetary SciencesEnvironmental sciencesoil moistureSMOS;L-band;level 3;ECMWF;SMOS-IC;soil moisture;vegetation optical depth;MODIS;NDVISMOS-ICcomputerLevel 3SMOSRemote Sensing
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Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian lan…

2011

In past decades, the Iberian Peninsula has been shown to have suffered vegetation changes such as desertification and reforestation. Normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters, estimated from data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard the National Oceanic and Atmospheric Administration (NOAA) satellite series, are particularly adapted to assess these changes. This work presents an application of the yearly land-cover dynamics (YLCD) methodology to analyse the behaviour of the vegetation, which consists of a combined multitemporal study of the NDVI and LST parameters on a yearly basis. Throughout the 1…

geographygeography.geographical_feature_categoryAdvanced very-high-resolution radiometermedia_common.quotation_subjectEnhanced vegetation indexLand coverNormalized Difference Vegetation IndexDesertificationPeninsulaClimatologymedicineGeneral Earth and Planetary SciencesEnvironmental scienceSatellitemedicine.symptomVegetation (pathology)media_commonInternational Journal of Remote Sensing
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