Search results for "radiative transfer model"

showing 10 items of 22 documents

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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Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrie…

2021

In forest landscapes affected by fire, the estimation of fractional vegetation cover (FVC) from remote sensing data using radiative transfer models (RTMs) enables to evaluate the ecological impact of such disturbance across plant communities at different spatio-temporal scales. Even though, when landscapes are highly heterogeneous, the fine-scale ground spatial variation might not be properly captured if FVC products are provided at moderate or coarse spatial scales, as typical of most of operational Earth observing satellite missions. The objective of this study was to evaluate the potential of a RTM inversion approach for estimating FVC from satellite reflectance data at high spatial reso…

010504 meteorology & atmospheric sciencesMean squared error0208 environmental biotechnologySoil Science02 engineering and technology01 natural sciencesArticleWorldView-3Radiative transferComputers in Earth SciencesImage resolution0105 earth and related environmental sciencesRemote sensingFractional vegetation coverForest fireGeologyInversion (meteorology)15. Life on landEcología. Medio ambienteRadiative transfer modeling020801 environmental engineering13. Climate actionGround-penetrating radarEnvironmental scienceSatelliteSpatial variabilitySentinel-2Scale (map)Remote Sensing of Environment
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Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data.

2019

Knowledge of key variables driving the top of the atmosphere (TOA) radiance over a vegetated surface is an important step to derive biophysical variables from TOA radiance data, e.g., as observed by an optical satellite. Coupled leaf-canopy-atmosphere Radiative Transfer Models (RTMs) allow linking vegetation variables directly to the at-sensor TOA radiance measured. Global Sensitivity Analysis (GSA) of RTMs enables the computation of the total contribution of each input variable to the output variance. We determined the impacts of the leaf-canopy-atmosphere variables into TOA radiance using the GSA to gain insights into retrievable variables. The leaf and canopy RTM PROSAIL was coupled with…

010504 meteorology & atmospheric sciencesradiative transfer models0211 other engineering and technologiesemulation02 engineering and technologytop-of-atmosphere radiance data01 natural sciencesEmulation; Global sensitivity analysis; Machine learning; MODTRAN; PROSAIL; Radiative transfer models; Retrieval; Sentinel-2; Top-of-atmosphere radiance dataKrigingRange (statistics)Radiative transferLeaf area indexlcsh:Scienceretrieval021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingMODTRANPROSAILMODTRANAtmospheric correctionradiative transfer models; global sensitivity analysis; emulation; machine learning; top-of-atmosphere radiance data; PROSAIL; MODTRAN; retrieval; Sentinel-2machine learningglobal sensitivity analysisLookup tableRadianceGeneral Earth and Planetary SciencesEnvironmental sciencelcsh:QSentinel-2Remote sensing
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Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery: Lessons Learned From Empirical Relationships and Radiati…

2019

[Purpose of Review] We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images.

0106 biological sciences010504 meteorology & atmospheric sciencesHigh resolutionVegetation healthPhotochemical Reflectance Index01 natural sciencesVegetation indicesPhysiological indicatorsRadiative transfermedicineEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesNature and Landscape ConservationRemote sensingRadiative transfer modelsEcologyWarning systemHyperspectral and thermal dataHyperspectral imagingForestry15. Life on land13. Climate actionRemote sensing (archaeology)Temporal resolutionEnvironmental sciencemedicine.symptomVegetation (pathology)010606 plant biology & botany
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Optimized and automated estimation of vegetation properties: Opportunities for Sentinel-2

2014

La Biosfera es uno de los principales sistemas que conforman la Tierra. Su estudio permite comprender la relación entre la vegetación y el ciclo del carbono y cómo éste puede ser afectado por los cambios en los niveles de CO2 y los usos de suelo. Para el estudio de estas dinámicas a escala global y local, han sido desarrollados diversos modelos que son representaciones de la realidad en una escala y complejidad más simple. Parte de las variables de entrada de estos modelos son obtenidas mediante medidas de teledetección gracias al Global Climate Observing System (GCOS), que ha determinado un conjunto de 50 variables climáticas esenciales que contribuyen a los estudios de cambio climático qu…

:CIENCIAS TECNOLÓGICAS [UNESCO]:CIENCIAS TECNOLÓGICAS::Tecnología del espacio [UNESCO]leaf area indexUNESCO::CIENCIAS TECNOLÓGICAS::Tecnología del espacio:CIENCIAS DE LA TIERRA Y DEL ESPACIO::Otras especialidades de la tierra espacio o entorno [UNESCO]biophysical parameter retrievalradiative transfer models:CIENCIAS DE LA TIERRA Y DEL ESPACIO [UNESCO]leaf chlorophyll contentUNESCO::CIENCIAS TECNOLÓGICASLUT-based inversionempirical regression modelsmachine learningUNESCO::CIENCIAS DE LA TIERRA Y DEL ESPACIO::Otras especialidades de la tierra espacio o entornoSentinel-2UNESCO::CIENCIAS DE LA TIERRA Y DEL ESPACIO
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Reproducing cloud microphysical and irradiance measurements using three 3D cloud generators

2007

Using three cloud generators, three-dimensional (3D) cloud fields are reproduced from microphysical cloud data measured in situ by aircraft. The generated cloud fields are used as input to a 3D radiative transfer model to calculate the corresponding fields of downward and upward irradiance, which are then compared with airborne and ground-based radiation measurements. One overcast stratocumulus scene and one broken cumulus scene were selected from the European INSPECTRO field experiment, which was held in Norwich, UK, in September 2002. With these data, the characteristics of the three different cloud reproduction techniques are assessed. Besides vertical profiles and histograms of measured…

Atmospheric SciencePixelMeteorologybusiness.industryFernerkundung der Atmosphärecloud generatorAutocorrelationIrradianceCloud computingradiationAtmospheric radiative transfer codesOvercastLiquid water contentRadiative transferEnvironmental sciencethree-dimensionalradiative transfer modelbusinessRemote sensing
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Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling

2022

Atmospheric Scienceprecision farmingradiative transfer modelsApplied Mathematicsplant nitrogen uptake estimationComputers in Earth Sciencesmachine learning regression algorithmsGeneral Environmental ScienceEuropean Journal of Remote Sensing
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Multi-fidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models

2023

This repository contains several datasets of spectral atmospheric transfer functions (i.e. path radiance, transmittances, spherical albedo) simulated with MODTRAN6 atmospheric radiative transfer model. The simulations are stored in hdf5 files using the Atmospheric Look-up table Generator (ALG) toolbox (https://doi.org/10.5194/gmd-13-1945-2020). Each dataset has an associated .xml file that includes the configuration of ALG/MODTRAN6 executions. All datasets include the input atmospheric/geometric variables that are summarized in the following table. Each dataset file has a random distribution (based on latin hypercube sampling) these input variables with varying number of points (e.g. train5…

Atmospheric correctionMuti-fidelityHyperspectralGaussian processesEmulationRadiative transfer models
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The scattering and re-absorption of red and near-infrared chlorophyll fluorescence in the models Fluspect and SCOPE

2019

Scattering and re-absorption have been recognized as relevant aspects for the interpretation of solar induced chlorophyll fluorescence (SIF) in vegetation remote sensing. In an earlier study [Yang and Van der Tol, RSE 215, 97–108, 2018] we addressed the problem of scattering and re-absorption of near-infrared fluorescence in the vegetation canopy. In this study we analyse within-leaf re-absorption of both red and near-infrared fluorescence using the radiative transfer model Fluspect. The leaf scattering determines the ratio of backward to total leaf fluorescence emission Fb/(Fb + Ff). Fluspect reproduces this ratio with an RMSE of less than 0.1, and explains the observed dependence of the s…

CanopySpectral shape analysisMaterials science010504 meteorology & atmospheric sciences0208 environmental biotechnologyAnalytical chemistryUT-Hybrid-DSoil ScienceRadiative transfer model02 engineering and technology01 natural sciencesRe absorptionScatteringAtmospheric radiative transfer codesComputers in Earth SciencesChlorophyll fluorescence0105 earth and related environmental sciencesRemote sensingScatteringNear-infrared spectroscopyGeologyFluorescence22/4 OA procedure020801 environmental engineeringITC-ISI-JOURNAL-ARTICLEChlorophyll fluorescenceRemote sensing of environment
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Development of an Earth observation processing chain for crop biophysical parameters at local and global scale

2017

[ES] Reseña de tesis doctoral defendida el 17 de Julio de 2017. Lugar: Facultat de Física, Universitat de València.

Earth observationVegetation010504 meteorology & atmospheric sciencesScale (ratio):CIENCIAS TECNOLÓGICAS::Tecnología del espacio ::Satélites artificiales [UNESCO]Geography Planning and DevelopmentUNESCO::CIENCIAS TECNOLÓGICAS::Tecnología del espacio ::Satélites artificiales0211 other engineering and technologieslcsh:G1-922Earth02 engineering and technologyAgricultural engineeringRemote sensingUNESCO::CIENCIAS DE LA TIERRA Y DEL ESPACIO::Geología::Teledetección (geología)01 natural sciencesRadiative transfer modelingChain (unit)Biophysical parametersMachine learningEarth and Planetary Sciences (miscellaneous)Environmental science:CIENCIAS DE LA TIERRA Y DEL ESPACIO::Geología::Teledetección (geología) [UNESCO]lcsh:Geography (General)021101 geological & geomatics engineering0105 earth and related environmental sciencesRevista de Teledetección
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