Search results for "Hyperspectral"

showing 10 items of 271 documents

Hyperspectral dimensionality reduction for biophysical variable statistical retrieval

2017

Abstract Current and upcoming airborne and spaceborne imaging spectrometers lead to vast hyperspectral data streams. This scenario calls for automated and optimized spectral dimensionality reduction techniques to enable fast and efficient hyperspectral data processing, such as inferring vegetation properties. In preparation of next generation biophysical variable retrieval methods applicable to hyperspectral data, we present the evaluation of 11 dimensionality reduction (DR) methods in combination with advanced machine learning regression algorithms (MLRAs) for statistical variable retrieval. Two unique hyperspectral datasets were analyzed on the predictive power of DR + MLRA methods to ret…

010504 meteorology & atmospheric sciencesMean squared errorComputer science0211 other engineering and technologies02 engineering and technologycomputer.software_genre01 natural sciencessymbols.namesakeLinear regressionComputers in Earth SciencesEngineering (miscellaneous)Gaussian processHyMap021101 geological & geomatics engineering0105 earth and related environmental sciencesData stream miningbusiness.industryDimensionality reductionHyperspectral imagingPattern recognitionAtomic and Molecular Physics and OpticsComputer Science ApplicationsKernel (statistics)symbolsData miningArtificial intelligencebusinesscomputerISPRS Journal of Photogrammetry and Remote Sensing
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Empirical and physical estimation of Canopy Water Content from CHRIS/PROBA data

2013

20 páginas, 4 tablas, 7 figuras.

010504 meteorology & atmospheric sciencesMean squared errorScience0211 other engineering and technologies02 engineering and technologyCHRIS/PROBA01 natural sciencescanopy water content;model inversion;neural networks;look up tables;empirical up-scalingmodel inversionEmpirical up-scalingAtmospheric radiative transfer codeslook up tablesRadiative transferModel inversion021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingArtificial neural networkCanopy water contentQHyperspectral imagingInversion (meteorology)Sigmoid functionSpectral bandsempirical up-scaling15. Life on landneural networks[SDE]Environmental SciencesGeneral Earth and Planetary SciencesLook up tablescanopy water contentNeural networkscanopy water content; model inversion; neural networks; look up tables; empirical up-scaling; CHRIS/PROBA
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Evaluation of the MODIS Albedo product over a heterogeneous agricultural area

2013

In this article, the Moderate Resolution Imaging Spectroradiometer MODIS Bidirectional Reflectance Distribution Function BRDF/Albedo product MCD43 is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction EODIX project campaign, which was developed in Barrax Spain in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal RTLSR which corresponds to the MODIS BRDF algorithm and the RossThick-Maignan-LiSparse-Reciprocal RTLSR-HS, were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner AHS sensor. During the campaign, airborne im…

010504 meteorology & atmospheric sciencesMeteorologyPixel0211 other engineering and technologiesHyperspectral imaging02 engineering and technologyAlbedo01 natural sciencesGeneral Earth and Planetary SciencesEnvironmental scienceSatelliteSatellite imageryModerate-resolution imaging spectroradiometerBidirectional reflectance distribution functionZenith021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingInternational Journal of Remote Sensing
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2019

The HyPlant imaging spectrometer is a high-performance airborne instrument consisting of two sensor modules. The DUAL module records hyperspectral data in the spectral range from 400–2500 nm, which is useful to derive biochemical and structural plant properties. In parallel, the FLUO module acquires data in the red and near infrared range (670–780 nm), with a distinctly higher spectral sampling interval and finer spectral resolution. The technical specifications of HyPlant FLUO allow for the retrieval of sun-induced chlorophyll fluorescence (SIF), a small signal emitted by plants, which is directly linked to their photosynthetic efficiency. The combined use of both HyPlant modules opens up …

010504 meteorology & atmospheric sciencesNear-infrared spectroscopy0211 other engineering and technologiesImaging spectrometerHyperspectral imaging02 engineering and technology01 natural sciencesSignalDual moduleCalibrationRadianceGeneral Earth and Planetary SciencesEnvironmental scienceSpectral resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing
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Eco-Friendly Estimation of Heavy Metal Contents in Grapevine Foliage Using In-Field Hyperspectral Data and Multivariate Analysis

2019

Heavy metal monitoring in food-producing ecosystems can play an important role in human health safety. Since they are able to interfere with plants’ physiochemical characteristics, which influence the optical properties of leaves, they can be measured by in-field spectroscopy. In this study, the predictive power of spectroscopic data is examined. Five treatments of heavy metal stress (Cu, Zn, Pb, Cr, and Cd) were applied to grapevine seedlings and hyperspectral data (350−2500 nm), and heavy metal contents were collected based on in-field and laboratory experiments. The partial least squares (PLS) method was used as a feature selection technique, and multiple linear regressions (…

010504 meteorology & atmospheric sciencesScience010501 environmental sciences01 natural sciencesMetalHuman healthLinear regressionPartial least squares regressionSpectroscopyheavy metals0105 earth and related environmental sciencesChemistrysvmQfungifield spectroscopy; hyperspectral; heavy metals; grapevine; PLS; SVM; MLRHyperspectral imagingfood and beveragesHeavy metalsplsEnvironmentally friendlyfield spectroscopygrapevinemlrhyperspectralvisual_artEnvironmental chemistryvisual_art.visual_art_mediumGeneral Earth and Planetary SciencesRemote Sensing; Volume 11; Issue 23; Pages: 2731
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Predicting year of plantation with hyperspectral and lidar data

2017

This paper introduces a methodology for predicting the year of plantation (YOP) from remote sensing data. The application has important implications in forestry management and inventorying. We exploit hyperspectral and LiDAR data in combination with state-of-the-art machine learning classifiers. In particular, we present a complete processing chain to extract spectral, textural and morphological features from both sensory data. Features are then combined and fed a Gaussian Process Classifier (GPC) trained to predict YOP in a forest area in North Carolina (US). The GPC algorithm provides accurate YOP estimates, reports spatially explicit maps and associated confidence maps, and provides sens…

010504 meteorology & atmospheric sciencesbusiness.industryComputer scienceForest managementFeature extraction0211 other engineering and technologiesHyperspectral imagingPattern recognition02 engineering and technologyVegetation15. Life on land01 natural sciencessymbols.namesakeLidarsymbolsLidar dataArtificial intelligencebusinessClassifier (UML)Gaussian process021101 geological & geomatics engineering0105 earth and related environmental sciences2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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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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In vivo photoprotection mechanisms observed from leaf spectral absorbance changes showing VIS–NIR slow-induced conformational pigment bed changes

2019

Abstract Regulated heat dissipation under excessive light comprises a complexity of mechanisms, whereby the supramolecular light-harvesting pigment–protein complex (LHC) shifts state from light harvesting towards heat dissipation, quenching the excess of photo-induced excitation energy in a non-photochemical way. Based on whole-leaf spectroscopy measuring upward and downward spectral radiance fluxes, we studied spectrally contiguous (hyperspectral) transient time series of absorbance A(λ,t) and passively induced chlorophyll fluorescence F(λ,t) dynamics of intact leaves in the visible and near-infrared wavelengths (VIS–NIR, 400–800 nm) after sudden strong natural-like illumination exposure. …

0106 biological sciences0301 basic medicineChlorophyllMaterials sciencePassive chlorophyll a fluorescencePigment–protein dynamicsLightHyperspectral remote sensingAnalytical chemistryJuglansPlant Science01 natural sciencesBiochemistryEnergy quenchingFluorescenceAbsorbance03 medical and health sciencesTransmittanceFiber Optic TechnologySpectroscopyChlorophyll fluorescencechemistry.chemical_classificationSpectroscopy Near-InfraredAbsorbed photosynthetic active radiation (APAR)Non-photochemical quenching (NPQ)Cell BiologyGeneral MedicineEquipment DesignPigments BiologicalPhotochemical ProcessesCarotenoidsPlant LeavesWavelength030104 developmental biologychemistryXanthophyllRadianceOriginal ArticleAbsorbance shiftMorusControlled heat dissipation010606 plant biology & botanyPhotosynthesis Research
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Discrimination of common defects in loquat fruit cv. ‘Algerie’ using hyperspectral imaging and machine learning techniques

2021

Abstract Loquat (Eriobotrya japonica L.) is an important fruit for the economy of some regions of Spain that is very susceptible to mechanical damage and physiological disorders. These problems depreciate its value and prevent it from being exported. Visible (VIS) and near infrared (NIR) hyperspectral imaging was used to discriminate between external and internal common defects of loquat cv. ‘Algerie’. Two classifiers, random forest (RF) and extreme gradient boost (XGBoost), and different spectral pre-processing techniques were evaluated in terms of their capacity to distinguish between sound and defective features according to three approaches. In the first approach the fruit pixels were c…

0106 biological sciencesN01 Agricultural engineeringEriobotryaHorticulture01 natural sciences040501 horticultureNon-destructiveClassification rateH20 Plant diseasesArtificial visionMathematicsPixelbiologybusiness.industryHyperspectral imagingPattern recognition04 agricultural and veterinary sciencesClassificationbiology.organism_classificationQualityRandom forestEriobotrya japonicaMultivariate analysisN20 Agricultural machinery and equipmentArtificial intelligence0405 other agricultural sciencesbusinessAgronomy and Crop Science010606 plant biology & botanyFood SciencePostharvest Biology and Technology
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Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images

2018

High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the…

0106 biological sciencesSynthetic aperture radargeographygeography.geographical_feature_category010504 meteorology & atmospheric sciencesStrait of GibraltarHICO010604 marine biology & hydrobiologyMultispectral imageHigh amplitude internal wavesHyperspectral imagingAquatic ScienceInternal waveOceanography01 natural sciencesMediterranean seaAlgeciras baySillOutflowSatelliteSentinel-2Geology0105 earth and related environmental sciencesRemote sensingEstuarine, Coastal and Shelf Science
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