Search results for " LANDSAT"

showing 10 items of 20 documents

Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)

2021

Many factors can influence the displacements of a dam, including water level variability and environmental temperatures, in addition to the dam composition. In this work, optical-based classification, thermal diachronic analysis, and a quasi-PS (Persistent Scatter) Interferometric SAR technique have been applied to determine both forcing factors and resulting displacements of the crest of the Castello dam (South Italy) over a one-year time period. The dataset includes Sentinel-1A images acquired in Interferometric Wide swath mode using the Terrain Observation with Progressive Scans SAR (TOPSAR); Landsat 8 Thermal Infrared Sensor (TIRS) thermal images, and Global Navigation Satellite System …

010504 meteorology & atmospheric sciencesLandsat TIRSScience0211 other engineering and technologiesTerrainSatellite system02 engineering and technologyForcing (mathematics)01 natural sciencesPS–InSARInterferometric synthetic aperture radarDam displacements Full graph GNSS Landsat TIRS PS–InSAR Sentinel-1A TOPSARSentinel-1A TOPSAR021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingdam displacementsGNSSQfull graphdam displacements; GNSS; Sentinel-1A TOPSAR; Landsat TIRS; PS–InSAR; full graphWater levelInterferometryGNSS applicationsGeneral Earth and Planetary SciencesSatelliteGeologySettore ICAR/06 - Topografia E CartografiaRemote Sensing
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Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

2016

Land Surface Temperature (LST) as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same obser…

010504 meteorology & atmospheric sciencesMeteorologyLandsat 7Science0211 other engineering and technologiesland surface temperatureTerrain02 engineering and technology01 natural sciencesNet radiometertime-space variabilityTermodinàmicaSuperfícies (Fisica)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingGround truthRadiometerQSubpixel renderingsurface heterogeneitysurface heterogeneity; land surface temperature; MODIS; Landsat 7; time-space variability; ground truthMODISGeneral Earth and Planetary SciencesEnvironmental scienceSpatial variabilityModerate-resolution imaging spectroradiometerScale (map)ground truthRemote Sensing
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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
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Enhancing the retrieval of stream surface temperature from Landsat data

2019

International audience; Thermal images of water bodies often show a radiance gradient perpendicular to the banks. This effect is frequently due to mixed land and water thermal pixels. In the case of the Landsat images, radiance mixing can also affect pure water pixels due the cubic convolution resampling of the native thermal measurements. Some authors recommended a general-purpose margin of two thermal pixels to the banks or a minimum river width of three pixels, to avoid near bank effects in water temperature retrievals. Given the relatively course spatial resolution of satellite thermal sensors, the three pixel margin severely restricts their application to temperature mapping in many ri…

010504 meteorology & atmospheric sciencesPixel0208 environmental biotechnologySoil ScienceGeologyImage processing02 engineering and technology01 natural sciencesSubpixel rendering6. Clean water020801 environmental engineering[SDE]Environmental SciencesThermalRadianceEnvironmental scienceSatelliteSatellite imageryComputers in Earth SciencesRiver surface temperature Landsat 8 thermal band Thermal spatial resolution Cubic convolution resampling Thermal impact Mequinenza reservoir Ebro river Thermal stratificationImage resolution0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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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
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Multitemporal and multiresolution leaf area index retrieval for operational local rice crop monitoring

2016

Abstract This paper presents an operational chain for high-resolution leaf area index (LAI) retrieval from multiresolution satellite data specifically developed for Mediterranean rice areas. The proposed methodology is based on the inversion of the PROSAIL radiative transfer model through the state-of-the-art nonlinear Gaussian process regression (GPR) method. Landsat and SPOT5 data were used for multitemporal LAI retrievals at high-resolution. LAI estimates were validated using time series of in situ LAI measurements collected during the rice season in Spain and Italy. Ground LAI data were collected with smartphones using PocketLAI, a specific phone application for LAI estimation. Temporal…

2. Zero hunger010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesSoil ScienceGeologyInversion (meteorology)02 engineering and technologyCrop monitoring; Rice; Leaf area index (LAI) retrieval; PROSAIL; Smartphone; Gaussian process regression (GPR); Landsat; SPOT5 Take501 natural sciencesAtmospheric radiative transfer codesKrigingSatellite dataGround-penetrating radarEnvironmental scienceComputers in Earth SciencesLeaf area indexRice crop021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote 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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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]
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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)
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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
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