Search results for "Remote Sensing"

showing 10 items of 1262 documents

Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …

2011

International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…

010504 meteorology & atmospheric sciencesComputer scienceGaussian0211 other engineering and technologiesSoil ScienceCANOPY BIOPHYSICAL CHARACTERISTICS02 engineering and technologyNEURAL NETWORK01 natural sciencesTransfer functionsymbols.namesakeAtmospheric radiative transfer codesRadiative transferRange (statistics)Sensitivity (control systems)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingArtificial neural networkGeologySigmoid functionRELATION SOL-PLANTE-ATMOSPHEREMODEL INVERSION[SDE]Environmental SciencessymbolsINDICE FOLIAIRE
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Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture

2013

Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable, Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire pro…

010504 meteorology & atmospheric sciencesComputer scienceScienceta11710211 other engineering and technologiesPoint cloudStereoscopyradiometry02 engineering and technologyphotogrammetry01 natural scienceslaw.inventionspectrometryradiometriamaatalouslawbiomassa (teollisuus)photogrammetry; radiometry; spectrometry; hyperspectral; UAV; DSM; point cloud; biomass; agriculturefotogrammetriaagriculture021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingta1132. Zero hungerbiomassuavQHyperspectral imagingta4111photogrammetriaReflectivityhyperspektridsmInterferometryspektrometriahyperspectralPhotogrammetry13. Climate actionRemote sensing (archaeology)GeoreferenceGeneral Earth and Planetary SciencesRadiometrypistepilviPrecision agriculturepoint cloudRemote Sensing
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Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

2017

Made available in DSpace on 2018-12-11T17:11:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-03-01 Suomen Akatemia Small unmanned aerial vehicle (UAV) based remote sensing is a rapidly evolving technology. Novel sensors and methods are entering the market, offering completely new possibilities to carry out remote sensing tasks. Three-dimensional (3D) hyperspectral remote sensing is a novel and powerful technology that has recently become available to small UAVs. This study investigated the performance of UAV-based photogrammetry and hyperspectral imaging in individual tree detection and tree species classification in boreal forests. Eleven test sites with 4151 reference trees repr…

010504 meteorology & atmospheric sciencesComputer scienceUAV0211 other engineering and technologiesPoint cloudta117102 engineering and technologyradiometryphotogrammetry01 natural sciencesforestComputer visionForestRadiometrylcsh:Science021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingfotogrammetriata113UAV; hyperspectral; photogrammetry; radiometry; point cloud; forest; classificationluokitus (toiminta)ta114business.industryHyperspectral imaging15. Life on landOtaNanoClassificationRandom forestPoint cloudTree (data structure)PhotogrammetryhyperspectralHyperspectralclassification13. Climate actionMultilayer perceptronPhotogrammetryGeneral Earth and Planetary SciencesRadiometryRGB color modellcsh:QArtificial intelligencebusinesspoint cloudRemote Sensing; Volume 9; Issue 3; Pages: 185
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Efficient remote sensing image classification with Gaussian processes and Fourier features

2017

This paper presents an efficient methodology for approximating kernel functions in Gaussian process classification (GPC). Two models are introduced. We first include the standard random Fourier features (RFF) approximation into GPC, which largely improves the computational efficiency and permits large scale remote sensing data classification. In addition, we develop a novel approach which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones using a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery.

010504 meteorology & atmospheric sciencesContextual image classificationComputer scienceMultispectral imageData classification0211 other engineering and technologiesSampling (statistics)02 engineering and technology01 natural sciencessymbols.namesakeBayes' theoremFourier transformKernel (statistics)symbolsGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Comparison of gap-filling techniques applied to the CCI soil moisture database in Southern Europe

2021

Abstract Soil moisture (SM) is a key variable that plays an important role in land-atmosphere interactions. Monitoring SM is crucial for many applications and can help to determine the impact of climate change. Therefore, it is essential to have continuous and long-term databases for this variable. Satellite missions have contributed to this; however, the continuity of the series is compromised due to the data gaps derived by different factors, including revisit time, presence of seasonal ice or Radio Frequency Interference (RFI) contamination. In this work, the applicability of different gap-filling techniques is evaluated on the ESA Climate Change Initiative (CCI) SM combined product, whi…

010504 meteorology & atmospheric sciencesDatabaseCorrelation coefficient0208 environmental biotechnologySoil ScienceGeology02 engineering and technologycomputer.software_genre01 natural sciencesNormalized Difference Vegetation Index020801 environmental engineeringRandom forestSupport vector machineAutoregressive modelPrincipal component analysisPotential evaporationComputers in Earth Sciencescomputer0105 earth and related environmental sciencesMathematicsInterpolationRemote sensingRemote Sensing of Environment
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Contribution of environmental factors to temperature distribution at different resolution levels on the forefield of the Loven Glaciers (Svalbard)

2007

ABSTRACTThe climate and its components (temperature and precipitation) are organised according to different spatial scales that are structured hierarchically. The aim of this paper is to explore the dependence between temperature and deterministic factors at different scales on a 10 km2 study area on the northwestern coast of Svalbard. A GIS was developed which contained three sources of information: temperature, remotely sensed imagery and digital elevation models (DEM), and derived raster data layers. The first layer, temperatures, was acquired at regularly observed temporal intervals from 53 stations. The second layer comprised remotely sensed images (aerial photography and SPOT imagery)…

010504 meteorology & atmospheric sciencesEcology[SHS.GEO] Humanities and Social Sciences/GeographyGeography Planning and Development0207 environmental engineeringElevation02 engineering and technology[SHS.GEO]Humanities and Social Sciences/Geography15. Life on land01 natural sciences[ SHS.GEO ] Humanities and Social Sciences/GeographyRaster dataAerial photography13. Climate actionLinear regressionSpatial ecologyGeneral Earth and Planetary Sciences020701 environmental engineeringDigital elevation modelScale (map)Image resolutionGeology0105 earth and related environmental sciencesRemote sensing
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Linking photosynthesis and sun-induced fluorescence at sub-daily to seasonal scales

2018

Abstract Due to its close link to the photosynthetic process, sun-induced chlorophyll fluorescence (F) opens new possibilities to study dynamics of photosynthetic light reactions and to quantify CO2 assimilation rates. Although recent studies show that F is linearly related to gross primary production (GPP) on coarse spatial and temporal scales, it is argued that this relationship may be mainly driven by seasonal changes in absorbed photochemical active radiation (APAR) and less by the plant light use efficiency (LUE). In this work a high-resolution spectrometer was used to continuously measure red and far-red fluorescence and different reflectance indices within a sugar beet field during t…

010504 meteorology & atmospheric sciencesEconomicsPhotochemical reflectance index0211 other engineering and technologiesEddy covarianceGrowing seasonSoil Science02 engineering and technologyPhotochemical Reflectance IndexPhotosynthesisAtmospheric sciences01 natural sciencesFluorescence yieldSun-induced chlorophyll fluorescencemedicineddc:550Computers in Earth SciencesChlorophyll fluorescenceBiology021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingLight use efficiencyPhysicsDiurnal temperature variationPrimary productionGeologySeasonalitymedicine.diseaseChemistryEngineering sciences. Technology
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Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress

2019

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF – especially from space – is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using high-resolution spectral sensors in …

010504 meteorology & atmospheric sciencesFIS/06 - FISICA PER IL SISTEMA TERRA E PER IL MEZZO CIRCUMTERRESTRE0208 environmental biotechnologySoil ScienceReview02 engineering and technologyPhotochemical Reflectance Index01 natural sciencesArticleGEO/11 - GEOFISICA APPLICATASIF retrieval methodsRadiative transfer modellingRadiative transfer910 Geography & travelComputers in Earth SciencesChlorophyll fluorescence1111 Soil Science1907 GeologyAirborne instruments0105 earth and related environmental sciencesRemote sensingStress detectionGEO/12 - OCEANOGRAFIA E FISICA DELL'ATMOSFERA1903 Computers in Earth SciencesPrimary productionGeologyVegetationPassive optical techniquesField (geography)020801 environmental engineeringGEO/10 - GEOFISICA DELLA TERRA SOLIDA10122 Institute of GeographySun-induced fluorescenceRemote sensing (archaeology)Sun-induced fluorescence Steady-state photosynthesis Stress detection Radiative transfer modelling SIF retrieval methods. Satellite sensors Airborne instruments Applications Terrestrial vegetation Passive optical techniques. ReviewApplicationsTerrestrial vegetationEnvironmental scienceSatelliteSteady-state photosynthesisSatellite sensors
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Using Optical and Thermal Data for Tracking Snowmelt Processes in Alpine Area

2019

Alpine catchments represent a fundamental reservoir of fresh water at midlatitude. Remote sensing offers the opportunity to estimate snow properties in the optical, thermal and microwave domains. In particular, the possibility to estimate snow density from remote sensing is relevant and still represents a great challenge for the remote sensing scientific community. Since changes of snow density and liquid water content occur continuously in the snowpack, spatial and temporal patterns of optical and thermal data can give information about snowmelt processes. The main goal of this study is to evaluate if snow thermal inertia can be an indicator of snowmelt processes and to evaluate its relati…

010504 meteorology & atmospheric sciencesFIS/06 - FISICA PER IL SISTEMA TERRA E PER IL MEZZO CIRCUMTERRESTREGEO/04 - GEOGRAFIA FISICA E GEOMORFOLOGIA0207 environmental engineeringGEO/12 - OCEANOGRAFIA E FISICA DELL'ATMOSFERA02 engineering and technologySnowpackTracking (particle physics)Snow01 natural sciencesGEO/11 - GEOFISICA APPLICATAGEO/10 - GEOFISICA DELLA TERRA SOLIDARemote sensing (archaeology)Liquid water contentMiddle latitudesSnowmeltThermalEnvironmental science020701 environmental engineeringRemote Sensing Snow Thermal Inertia Snowmelt Snow densitySettore ICAR/06 - Topografia E Cartografia0105 earth and related environmental sciencesRemote sensing
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Mapping Vegetation Density in a Heterogeneous River Floodplain Ecosystem Using Pointable CHRIS/PROBA Data

2012

River floodplains in the Netherlands serve as water storage areas, while they also have the function of nature rehabilitation areas. Floodplain vegetation is therefore subject to natural processes of vegetation succession. At the same time, vegetation encroachment obstructs the water flow into the floodplains and increases the flood risk for the hinterland. Spaceborne pointable imaging spectroscopy has the potential to quantify vegetation density on the basis of leaf area index (LAI) from a desired view zenith angle. In this respect, hyperspectral pointable CHRIS data were linked to the ray tracing canopy reflectance model FLIGHT to retrieve vegetation density estimates over a heterogeneous…

010504 meteorology & atmospheric sciencesFloodplainWater flowpointable sensors; CHRIS/PROBA; leaf area index (LAI); inversion; radiative transfer (RT) model; FLIGHT; river floodplain ecosystem; vegetation density; hydraulic roughnessleaf area index (LAI)0211 other engineering and technologiesClimate change02 engineering and technologyCHRIS/PROBA01 natural sciencesforestinversionLaboratory of Geo-information Science and Remote SensingLaboratorium voor Geo-informatiekunde en Remote SensingLeaf area indexcoverlcsh:ScienceZenithriver floodplain ecosystem021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinggeographychris-proba datahyperspectral brdf datageography.geographical_feature_categoryFLIGHTFlood mythrhine basinradiative-transfer modelHyperspectral imagingEnhanced vegetation index15. Life on landpointable sensorsPE&RCradiative transfer (RT) modelsugar-beetclimate-changeGeneral Earth and Planetary SciencesEnvironmental sciencehydraulic roughnesslcsh:Qflow resistanceleaf-area indexvegetation densityRemote Sensing
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