Search results for "hyperspectral"

showing 10 items of 271 documents

Image simulation of geostationary sensor dedicated to ocean color

2010

A method of image simulation of geostationary sensor dedicated to ocean color for open water (case1) and coastal water (case2) is presented in this paper. This method uses HYDROLIGHT to model the radiative transfer in order to obtain the water surface radiance. MeRIS level 3 products have been used for input water components to provide a realistic spatial distribution. The atmospheric radiative transfer model and the sensor model finely lead to satellite remote sensing images. This system allows to evaluate the dynamic range of BOA and TOA radiances depending on solar and viewing angles in operational situation and latter their influence on water composition retrieval.

Atmospheric radiative transfer codesMeteorologyOcean colorRadianceGeostationary orbitRadiative transferHyperspectral imagingEnvironmental scienceAtmospheric modelViewing angleRemote sensing2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
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Advancing cyanobacteria biomass estimation from hyperspectral observations: Demonstrations with HICO and PRISMA imagery

2021

Retrieval of the phycocyanin concentration (PC), a characteristic pigment of, and proxy for, cyanobacteria biomass, from hyperspectral satellite remote sensing measurements is challenging due to uncertainties in the remote sensing reflectance (?R) resulting from atmospheric correction and instrument radiometric noise. Although several individual algorithms have been proven to capture local variations in cyanobacteria biomass in specific regions, their performance has not been assessed on hyperspectral images from satellite sensors. Our work leverages a machine-learning model, Mixture Density Networks (MDNs), trained on a large (N = 939) dataset of collocated in situ chlorophyll-a concentrat…

Biomass (ecology)Aquatic remote sensingcyanoHABsHICOMultispectral imageAtmospheric correctionPhycocyaninSoil ScienceHyperspectral imagingGeologyPRISMASpectral bandsCyanobacteriacyanobacteria ; phycocyanin ; machine learning ; mixture density network ; aquatic remote sensing ; cyanoHABs ; HICO ; PRISMAMachine learningMixture density networkEnvironmental scienceRadiometrySatelliteNoise (video)Computers in Earth SciencesRemote sensingRemote Sensing of Environment
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A sensor-data-based denoising framework for hyperspectral images

2015

Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values. The subsequent denoising is based on an extended variational denoising model, which is suited for a Poisson distributed noise. A spatially and spectrally adaptive total variation regularisation term…

Blind deconvolution[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingHyperspectral imagingAnisotropic diffusionComputer scienceNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processing02 engineering and technology01 natural sciences010309 opticsOptics[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciencesdenoising0202 electrical engineering electronic engineering information engineeringbusiness.industryHyperspectral imagingcomputer.file_formatNon-local meansAtomic and Molecular Physics and OpticsLight intensityFull spectral imagingComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingImage file formatsNoise (video)businesscomputer
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Evaluation of the DART 3D model in the thermal domain using satellite/airborne imagery and ground-based measurements

2011

This work provides an evaluation of the discrete anisotropy radiative transfer (DART) three-dimensional (3D) model in assessing the simulation of directional brightness temperatures (Tb) at both sensor and surface levels. Satellite imagery acquired with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), airborne imagery acquired with the Airborne Hyperspectral Scanner (AHS) sensor and ground-based measurements collected over an agricultural area were used to evaluate the DART model at nadir views. Directional radiometric temperatures measured with a goniometric system at ground level were also used to evaluate modelling results at different view angles. The DART mod…

BrightnessDart010504 meteorology & atmospheric sciencesMeteorology[SDE.IE]Environmental Sciences/Environmental Engineering0211 other engineering and technologiesAtmospheric correctionHyperspectral imaging02 engineering and technology01 natural sciencesAdvanced Spaceborne Thermal Emission and Reflection Radiometer[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsEmissivityRadiative transferGeneral Earth and Planetary SciencesEnvironmental scienceSatellite imagerycomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingcomputer.programming_languageInternational Journal of Remote Sensing
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Hyperspectral UAV-Imagery and photogrammetric canopy height model in estimating forest stand variables

2017

Remote sensing using unmanned aerial vehicle (UAV) -borne sensors is currently a highly interesting approach for the estimation of forest characteristics. 3D remote sensing data from airborne laser scanning or digital stereo photogrammetry enable highly accurate estimation of forest variables related to the volume of growing stock and dimension of the trees, whereas recognition of tree species dominance and proportion of different tree species has been a major complication in remote sensing-based estimation of stand variables. In this study the use of UAV-borne hyperspectral imagery was examined in combination with a high-resolution photogrammetric canopy height model in estimating forest v…

Canopy010504 meteorology & atmospheric sciencesCalibration (statistics)hyperspectral imagingvariablesta1172ta11710211 other engineering and technologies02 engineering and technologyUAVsphotogrammetry01 natural sciencesDigital photogrammetryaerial imagerylcsh:Forestryforest inventoryRadiometric calibrationstereo-photogrammetric canopy modelling021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingfotogrammetriata113forestsForest inventoryEcological ModelingHyperspectral imagingmuuttujatForestryradiometric calibrationOtaNanota4112metsätAerial imagerydigital photogrammetryPhotogrammetryEnvironmental sciencelcsh:SD1-669.5Silva Fennica
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Remote Estimation of Canopy Water Content in Different Crop Types with New Hyperspectral Indices

2018

A diverse range of vegetation indices have earlier been developed for the remote estimation of canopy water content (CWC), but most of them are not universally applicable. The aim of this study is to define new indices valid for a wide variety of crop types, that allow to obtain CWC maps at a large spatial scale. These indices were developed based on PROSAIL simulations and then optimized with an experimental dataset (SPARC03; Barrax, Spain), which consists of field data including water content and other biophysical parameters collected for 6 different crops (lucerne, corn, potato, sugar beet, garlic and onion) and associated TOC reflectance spectra acquired by the HyMap airborne sensor. Sp…

CanopyAbsorption of water010504 meteorology & atmospheric sciences0211 other engineering and technologiesHyperspectral imaging02 engineering and technologyVegetation01 natural sciencesEnvironmental scienceSpectral resolutionAbsorption (electromagnetic radiation)Water contentHyMap021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC)

2010

Abstract The Normalized Area Over reflectance Curve (NAOC) is proposed as a new index for remote sensing estimation of the leaf chlorophyll content of heterogeneous areas with different crops, different canopies and different types of bare soil. This index is based on the calculation of the area over the reflectance curve obtained by high spectral resolution reflectance measurements, determined, from the integral of the red–near-infrared interval, divided by the maximum reflectance in that spectral region. For this, use has been made of the experimental data of the SPARC campaigns, where in situ measurements were made of leaf chlorophyll content, LAI and fCOVER of 9 different crops – thus, …

CanopyGlobal and Planetary ChangeRadiometerPixelHyperspectral imagingManagement Monitoring Policy and Lawchemistry.chemical_compoundGeographychemistryChlorophyllComputers in Earth SciencesSpectral resolutionLeaf area indexAbsorption (electromagnetic radiation)Earth-Surface ProcessesRemote sensingInternational Journal of Applied Earth Observation and Geoinformation
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Assessing Canopy PRI for Water Stress detection with Diurnal Airborne Imagery

2008

Soil Moisture Experiments 2004 (SMEX04) Special Issue

CanopyStomatal conductanceWater stressAHSSoil ScienceGeologySpectral bandsVegetationRemote sensingPhotochemical Reflectance IndexNormalized Difference Vegetation IndexHyperspectralThermalTCARI/OSAVISoil waterAirborneEnvironmental scienceBidirectional reflectance distribution functionPRIComputers in Earth SciencesTESRemote sensing
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Comparison of Crop Trait Retrieval Strategies Using UAV-Based VNIR Hyperspectral Imaging.

2021

Hyperspectral cameras onboard unmanned aerial vehicles (UAVs) have recently emerged for monitoring crop traits at the sub-field scale. Different physical, statistical, and hybrid methods for crop trait retrieval have been developed. However, spectra collected from UAVs can be confounded by various issues, including illumination variation throughout the crop growing season, the effect of which on the retrieval performance is not well understood at present. In this study, four retrieval methods are compared, in terms of retrieving the leaf area index (LAI), fractional vegetation cover (fCover), and canopy chlorophyll content (CCC) of potato plants over an agricultural field for six dates duri…

Canopystatistical method010504 meteorology & atmospheric sciencesScience0211 other engineering and technologiesGrowing season02 engineering and technologyLUT-based inversion; hybrid method; statistical method; leaf area index; fractional vegetation cover; canopy chlorophyll content01 natural sciencesLUT-based inversionhybrid methodLeaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingfractional vegetation coverleaf area indexQHyperspectral imagingcanopy chlorophyll contentStatistical modelRandom forestVNIRGeneral Earth and Planetary SciencesScale (map)Remote sensing
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Relating Hyperspectral Airborne Data to Ground Measurements in a Complex and Discontinuous Canopy

2015

The work described in this paper is aimed at validating hyperspectral airborne reflectance data collected during the Regional Experiments For Land-atmosphere EXchanges (REFLEX) campaign. Ground reflectance data measured in a vineyard were compared with airborne reflectance data. A sampling strategy and subsequent ground data processing had to be devised so as to capture a representative spectral sample of this complex crop. A linear model between airborne and ground data was tried and statistically tested. Results reveal a sound correspondence between ground and airborne reflectance data (R2 > 0.97), validating the atmospheric correction of the latter.

CanopyvalidationData processing010504 meteorology & atmospheric sciencesMeteorologyhyperspectral remote sensingAtmospheric correctionAHSreflectance field spectrometryHyperspectral imagingSampling (statistics)15. Life on land010502 geochemistry & geophysics01 natural sciencesReflectivityGeophysicsEnvironmental science0105 earth and related environmental sciencesRemote sensingActa Geophysica
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