Search results for "Leaf chlorophyll content"

showing 5 items of 5 documents

Hyperspectral response of agronomic variables to background optical variability: Results of a numerical experiment

2022

Understanding how biophysical and biochemical variables contribute to the spectral characteristics of vegetation canopies is critical for their monitoring. Quantifying these contributions, however, remains difficult due to extraneous factors such as the spectral variability of canopy background materials, including soil/crop-residue moisture, soil-type, and non-photosynthetic vegetation (NPV). This study focused on exploring the spectral response of two important agronomic variables (1) leaf chlorophyll content (Cab ) and (2) leaf area index (LAI) under various canopy backgrounds through a global sensitivity analysis of wheat-like canopy spectra simulated using the physically-based PROSAIL …

Atmospheric ScienceResilient LivelihoodsLEAF-AREA-INDEXSoil typePHOTOCHEMICAL REFLECTANCE INDEXBIOPHYSICAL PROPERTIESMeteorology & Atmospheric SciencesAdaptationLeaf chlorophyll contentGlobal and Planetary ChangeScience & TechnologyVEGETATION INDEXESSPECTRAL INDEXESGLOBAL SENSITIVITY-ANALYSISAgricultureNon-photosynthetic vegetationForestry22/4 OA procedureAgronomyHyperspectral responseGlobal sensitivity analysisITC-ISI-JOURNAL-ARTICLEPhysical SciencesLeaf area indexCHLOROPHYLL CONTENTGREEN LAILife Sciences & BiomedicineCANOPY REFLECTANCEAgronomy and Crop ScienceRADIATIVE-TRANSFER MODELAgricultural and Forest Meteorology
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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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Retrieving and Validating Leaf and Canopy Chlorophyll Content at Moderate Resolution: A Multiscale Analysis with the Sentinel-3 OLCI Sensor

2021

ESA’s Eighth Earth Explorer mission “FLuorescence EXplorer” (FLEX) will be dedicated to the global monitoring of the chlorophyll fluorescence emitted by vegetation. In order to properly interpret the measured fluorescence signal, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem formation with Sentinel-3 (S3), which conveys the Ocean and Land Color Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In support of FLEX’s preparatory activities, this paper presents a first validation exercise of OLCI vegetation products against in situ data coming from the 2018 FLEXSense cam…

Canopy010504 meteorology & atmospheric sciencesScience0211 other engineering and technologiesleaf chlorophyll content02 engineering and technology01 natural sciencesLeaf area indexpixel heterogeneityChlorophyll fluorescenceImage resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingleaf area indexPixelQcanopy chlorophyll contentVegetation15. Life on landSpatial ecologyGeneral Earth and Planetary SciencesEnvironmental scienceSentinel-3ddc:620Scale (map)moderate spatial resolutionleaf chlorophyll content; canopy chlorophyll content; leaf area index; pixel heterogeneity; moderate spatial resolution; Sentinel-3; OLCI; FLEX; HyPlantRemote Sensing
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Retrieval of Crop Variables from Proximal Multispectral UAV Image Data Using PROSAIL in Maize Canopy

2022

Mapping crop variables at different growth stages is crucial to inform farmers and plant breeders about the crop status. For mapping purposes, inversion of canopy radiative transfer models (RTMs) is a viable alternative to parametric and non-parametric regression models, which often lack transferability in time and space. Due to the physical nature of RTMs, inversion outputs can be delivered in sound physical units that reflect the underlying processes in the canopy. In this study, we explored the capabilities of the coupled leaf–canopy RTM PROSAIL applied to high-spatial-resolution (0.015 m) multispectral unmanned aerial vehicle (UAV) data to retrieve the leaf chlorophyll content (LC…

General Earth and Planetary SciencesUAV; multispectral; radiative transfer model; inversion; PROSAIL; leaf area index; leaf chlorophyll content; canopy chlorophyll contentRemote Sensing
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On the semi-automatic retrieval of biophysical parameters based on spectral index optimization

2014

Abstract: Regression models based on spectral indices are typically empirical formulae enabling the mapping of biophysical parameters derived from Earth Observation (EO) data. Due to its empirical nature, it remains nevertheless uncertain to what extent a selected regression model is the most appropriate one, until all band combinations and curve fitting functions are assessed. This paper describes the application of a Spectral Index (SI) assessment toolbox in the Automated Radiative Transfer Models Operator (ARTMO) package. ARTMO enables semi-automatic retrieval and mapping of biophysical parameters from optical remote sensing observations. The SI toolbox facilitates the assessment of biop…

Polynomialleaf area indexLogarithmbiophysical parameter retrievalEconomicsImaging spectrometerleaf chlorophyll contentempirical regression modelsCalibrationRadiative transferCurve fittingspectral indicesGeneral Earth and Planetary Scienceslcsh:Qlcsh:ScienceShortwaveGUI toolboxHyMapHyMapRemote sensingMathematics
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