Search results for "Landsat"

showing 10 items of 40 documents

Cálculo de la evapotranspiración real diaria en la zona norte de Finlandia empleando técnicas de teledetección

2005

J. M. Sánchez Tomás (Juan.M.Sanchez@uv.es) Hasta hace poco tiempo el estudio de la evapotranspiración (LE), fundamental en la ecuación de balance de energía, excluía zonas forestales debido a las dificultades experimentales de la toma de medidas en estas regiones. La teledetección acabó con dichas dificultades, facilitando el estudio de la LE real dentro de estas zonas, que suponen en torno a un 30% de toda la superficie terrestre. En este trabajo se presenta un método operativo para determinar la LE real a partir de medidas de temperatura de la superficie realizadas desde satélite. Este estudio se llevó a cabo de abril a junio de 2002 en Sodankylä, una región de bosque boreal en el norte d…

Bosque boreal; Temperatura; Evapotranspiración real; Imagen Landsat-ETM+; TeledetecciónBosque borealTeledetección:CIENCIAS DE LA TIERRA Y DEL ESPACIO [UNESCO]TemperaturaUNESCO::CIENCIAS DE LA TIERRA Y DEL ESPACIOUNESCO::CIENCIAS DE LA TIERRA Y DEL ESPACIO::GeografíaImagen Landsat-ETM+Evapotranspiración real:CIENCIAS DE LA TIERRA Y DEL ESPACIO::Geografía [UNESCO]
researchProduct

A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data

2018

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then a…

0106 biological sciencesFOS: Computer and information sciences010504 meteorology & atmospheric sciencesSpecific leaf areaClimateBos- en LandschapsecologieSoil ScienceFOS: Physical sciencesApplied Physics (physics.app-ph)010603 evolutionary biology01 natural sciencesStatistics - ApplicationsGoodness of fitAbundance (ecology)Machine learningForest and Landscape EcologyApplications (stat.AP)Computers in Earth SciencesPlant ecologyVegetatie0105 earth and related environmental sciencesRemote sensingMathematics2. Zero hungerPlant traitsVegetationData stream miningClimate; Landsat; Machine learning; MODIS; Plant ecology; Plant traits; Random forests; Remote sensing; Soil Science; Geology; Computers in Earth SciencesGlobal MapRegression analysisGeologyPhysics - Applied Physics15. Life on landRandom forestsRemote sensingPE&RCRandom forestMODISTraitVegetatie Bos- en LandschapsecologieVegetation Forest and Landscape EcologyLandsat
researchProduct

Radiometric correction effects in Landsat multi‐date/multi‐sensor change detection studies

2006

Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi‐sensor, multi‐date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (absolute and relative) for the determination of land cover changes, using Landsat TM and Landsat ETM+ images. In addition, we present an improvement made to the relative correction method addressed. Absolute correction includes a cross‐calibration between TM and ETM+ images, and the application of an atmospheric correction protocol. Relative correction normalizes the images using pseudo‐invariant fe…

Oceanografía Hidrología Recursos HídricosRadiometric correctionRadiometric correctionLand cover changeCiencias de la Tierra y relacionadas con el Medio AmbienteMulti sensorGeographyThematic MapperLandsat TMGeneral Earth and Planetary Sciencespseudo‐invariant featuresCIENCIAS NATURALES Y EXACTASChange detectionRemote sensingInternational Journal of Remote Sensing
researchProduct

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
researchProduct

EVASPA (EVapotranspiration Assessment from SPAce) tool: an overview

2013

International audience; Evapotranspiration (ET) is a fundamental variable of the hydrological cycle and its estimation is required for irrigation management, water resources planning and environmental studies. Remote sensing provides spatially distributed cost-effective information for ET maps production at regional scale. We have developed EVASPA too for mapping ET from remote sensing data at spatial and temporal scales relevant to hydrological or agronomica studies. EVASPA includes several algorithms for estimating evapotranspiration and various equations for estimating the required input information (net radiation, ground heat flux, evaporative fraction…), which provides a way to assess …

Crau-Camargue.010504 meteorology & atmospheric sciencesBiodiversité et Ecologietélédétectionévapotranspirationcartographie - évapotranspiration;télédétection;landsat;MODIS02 engineering and technologysatellite landsat01 natural sciencesirrigationremote sensingEvapotranspirationtélédétection spatialeWater cycle020701 environmental engineeringTemporal scalesGeneral Environmental Science6. Clean waterVariable (computer science)Remote sensing (archaeology)francealgorithmebase de données spatio temporellelandsat0207 environmental engineering[SCCO.COMP]Cognitive science/Computer sciencecartographie - évapotranspirationcycle hydrologiquecamargueBiodiversity and Ecologyressource en eauIrrigation management0105 earth and related environmental sciencesRemote sensingEnvironmental and Societyrayonnement netEvapotranspiration mappingflux conductif de chaleur dans le solcrauComputer science[SDE.ES]Environmental Sciences/Environmental and SocietyWater resourcesMODIS13. Climate actionInformatique (Sciences cognitives)cartographieGeneral Earth and Planetary SciencesEnvironmental scienceéchelle spatio temporelleEnvironnement et Société[SDE.BE]Environmental Sciences/Biodiversity and EcologyScale (map)
researchProduct

Effects of climate change and land use intensification on regional biological soil crust cover and composition in southern Africa

2022

Biological soil crusts (biocrusts) form a regular and relevant feature in drylands, as they stabilize the soil, fix nutrients, and influence water cycling. However, biocrust forming organisms have been shown to be dramatically vulnerable to climate and land use change occurring in these regions. In this study, we used Normalized Difference Vegetation Index (NDVI) data of biocrust-dominated pixels (NDVIbiocrust) obtained from hyperspectral and LANDSAT-7 data to analyse biocrust development over time and to forecast future NDVIbiocrust development under different climate change and livestock density scenarios in southern Africa. We validated these results by analysing the occurrence and compo…

010504 meteorology & atmospheric sciencesNDVISoil ScienceLibrary science01 natural sciencesGermanRegional developmentEffects of global warmingPolitical science11. SustainabilityNobel laureateBiocrustmedia_common.cataloged_instanceSpatial distributionEuropean union0105 earth and related environmental sciencesmedia_common2. Zero hungerLand useEuropean researchLivestock density04 agricultural and veterinary sciences15. Life on landRemote sensingEcologíaSpace-for-time studylanguage.human_languageEarth system modelDrylands soils13. Climate action040103 agronomy & agriculturelanguage0401 agriculture forestry and fisheriesChristian ministryMulti-temporal Landsat imageryGeoderma
researchProduct

Land surface temperature retrieval from LANDSAT TM 5

2004

In this paper, three methods to retrieve the land surface temperature (LST) from thermal infrared data supplied by band 6 of the Thematic Mapper (TM) sensor onboard the Landsat 5 satellite are compared. The first of them lies on the estimation of the land surface temperature from the radiative transfer equation using in situ radiosounding data. The others two are the mono-window algorithm developed by Qin et al. [International Journal of Remote Sensing 22 (2001) 3719] and the single-channel algorithm developed by Jime´nez-Mun˜oz and Sobrino [Journal of Geophysical Research 108 (2003)]. The land surface emissivity (LSE) values needed in order to apply these methods have been estimated from a…

Thermal infraredLans surface emissivityLand surface temperatureNear-infrared spectroscopyOtras Ciencias de la Tierra y relacionadas con el Medio AmbienteSoil ScienceGeologyLandsat 5Ciencias de la Tierra y relacionadas con el Medio AmbienteThematic MapperRadiative transferEmissivityEnvironmental scienceSatelliteComputers in Earth SciencesRoot-mean-square deviationLand Surface TemperatureCIENCIAS NATURALES Y EXACTASRemote sensing
researchProduct

Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud

2020

Remote sensing optical sensors onboard operational satellites cannot have high spectral, spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can adversely affect the signal contaminating the land surface observations. We present a HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to combine multispectral images of different sensors to reduce noise and produce monthly gap free high resolution (30 m) observations over land. Our approach uses images from the Landsat (30 m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500 m spatial resolution and daily revisit cycle). We implem…

010504 meteorology & atmospheric sciencesComputer science0208 environmental biotechnologyMultispectral imageSoil Science02 engineering and technology01 natural sciencesArticleComputers in Earth SciencesImage resolution0105 earth and related environmental sciencesRemote sensingPropagation of uncertaintyNoise (signal processing)GeologyKalman filterData fusionSensor fusion020801 environmental engineeringMODIS13. Climate actionScalabilityGap fillingKalman filterLandsatSmoothingSmoothingRemote Sensing of Environment
researchProduct

Coupling SAR X-band and optical data for NDVI retrieval: model calibration and validation on two test areas

2013

Sustainability of modern agro-hydrology requires the knowledge of spatial and temporal variability of vegetation biomass to optimize management of land and water resources. Diversely from optical imaging, temporal resolution of active sensors, such as SAR, is not limited by sky cloudiness; thus, they may be combined with optical imageries to provide a more continuous monitoring of land surfaces. Several new SAR missions (e.g., ALOS-PALSAR, COSMO-SkyMed 1 and 2, TerraSAR-X, TerraSAR-X2, Sentinel 1) acquiring at X-, C- and L-bands and dual polarization capability, are characterized by a short revisit time (from 12 h to ~10 days) and high spatial resolution (<20 m). These satellites could prov…

Synthetic aperture radarL bandMeteorologyBackscatterCloud covermedia_common.quotation_subjectSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaContinuous monitoringRadar backscatteringNormalized Difference Vegetation IndexNDVI cross-polarized backscattering DEIMOS-1 COSMO-SkyMed Landsat 7 SCL-offGeographySkyTemporal resolutionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSettore ICAR/06 - Topografia E Cartografiamedia_commonRemote sensingvegetation index
researchProduct

A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUM…

2018

Leaf area index (LAI) is a key biophysical variable fundamental in natural vegetation and agricultural land monitoring and modelling studies. This paper is aimed at comparing, validating and discussing different LAI satellite products from operational services and customized solution based on innovative Earth Observation (EO) data such as Landsat-7/8 and Sentinel-2A. The comparison was performed to assess overall quality of LAI estimates for rice, as a fundamental input of different scale (regional to local) operational crop monitoring systems such as the ones developed during the "An Earth obseRvation Model based RicE information Service" (ERMES) project. We adopted a multiscale approach f…

Earth observation010504 meteorology & atmospheric sciencesMean squared errorRice crops0211 other engineering and technologies02 engineering and technology01 natural sciencesLandsat-7/8Agricultural landGEOV1ValidationmedicineLeaf Area Index (LAI)Leaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2. Zero hungerSentinel-2AVegetation15. Life on landSeasonalitymedicine.diseaseMODISLeaf Area Index (LAI); rice crops; Sentinel-2A; Landsat-7/8; EUMETSAT Polar System; MODIS; GEOV1; validationEUMETSAT Polar SystemGeneral Earth and Planetary SciencesEnvironmental scienceSatelliteScale (map)Remote Sensing; Volume 10; Issue 5; Pages: 763
researchProduct