Search results for "Vegetation Indices"

showing 10 items of 22 documents

Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA/CHRIS Data Over …

2009

Abstract: In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC) retrieval from Compact High Resolution Imaging Spectrometer (CHRIS) data onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs), in particular the Normalized Difference Vegetation Index (NDVI) and the Variable Atmospherically Resistant Index (VARI). The second methodology is based on the Spectral Mixture Analysis (SMA) technique, in which a Linear Spectral Unmixing model has been considered in order to retrieve the abundance of the different constituent materials within pixe…

Endmember010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologies550 - Earth sciences02 engineering and technologyLand coverlcsh:Chemical technology01 natural sciencesBiochemistryNormalized Difference Vegetation IndexArticleCHRISAnalytical ChemistryRoot mean squareFractional Vegetation Cover; Vegetation Indices; Spectral Mixture Analysis; PROBA; CHRISPROBAlcsh:TP1-1185Electrical and Electronic EngineeringInstrumentation021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingFractional Vegetation CoverPixelVegetation15. Life on landAtomic and Molecular Physics and OpticsStandard errorSpectral Mixture AnalysisVegetation Indices
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Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer

2015

In this study we present a hyperspectral flying goniometer system, based on a rotary-wing unmanned aerial vehicle (UAV) equipped with a spectrometer mounted on an active gimbal. We show that this approach may be used to collect multiangular hyperspectral data over vegetated environments. The pointing and positioning accuracy are assessed using structure from motion and vary from σ = 1° to 8° in pointing and σ = 0.7 to 0.8 m in positioning. We use a wheat dataset to investigate the influence of angular effects on the NDVI, TCARI and REIP vegetation indices. Angular effects caused significant variations on the indices: NDVI = 0.83–0.95; TCARI = 0.04–0.116; REIP = 729–735 nm. Our analysis high…

hyperspectral; unmanned aerial vehicle (UAV); vegetation; bidirectional reflectance distribution function (BRDF); goniometer; vegetation indicesRemote Sensing; Volume 7; Issue 1; Pages: 725-746
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A low-cost multispectral imaging system for the characterisation of soil and small vegetation properties using visible and near-infrared reflectance

2022

Current Proximal Sensing technologies are based on multispectral imaging systems able to capture images in a few spectral bands, usually centred in VIS and NIR regions, to derive vegetation indices. However, most of such systems lack an internal radiometric calibration to estimate the actual reflectance of the observed target, making them sensitive to the local radiative environment and requiring a per-session calibration against a reference target. To overcome such dependence, the instrument described adopts an active illumination of the target surface, allowing the monitoring of soil and low vegetation surfaces by a radiometrically pre-calibrated imaging camera. The system, driven by a mi…

Settore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeMultispectral camera Vegetation Indices NDVI Image analysis Spectral reflectanceSettore AGR/09 - Meccanica AgrariaForestryHorticultureAgronomy and Crop ScienceSettore AGR/02 - Agronomia E Coltivazioni ErbaceeComputer Science ApplicationsComputers and Electronics in Agriculture
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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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Rapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices

2021

Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near…

klorofylligrowthmonitorointilevätympäristön tilaremote sensingstrainvegetationviherlevätmobile spectral camerachlorophyllstate of the environmentbiomassa (ekologia)algaerasitusbiomassmicroalgaespektrikuvausfluoresenssiBotanykasvillisuusmikrolevätgreen algaemonitoringtransmission imagingvegetation indicesQK1-989kaukokartoitusPlants
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Dispositivo per il monitoraggio di superfici vegetali

2017

La presente invenzione si riferisce al settore della diagnostica ambientale poiché fornisce un dispositivo che consente il monitoraggio dello stato fisiologico dei tappeti erbosi e di altre tipologie di coperture naturali che può essere anche impiegato per una accurata caratterizzazione e gestione delle coperture vegetali quali ad esempio campi sportivi, aree verdi naturali o artificiali e il relativo metodo.

Settore AGR/03 - Arboricoltura Generale E Coltivazioni Arboreemultispectral camera Vegetation Indices NDVI image analysis spectral reflectanceSettore AGR/09 - Meccanica AgrariaSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSettore AGR/02 - Agronomia E Coltivazioni Erbacee
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Modeling Fire Danger in Galicia and Asturias (Spain) from MODIS images

2014

Forest fires are one of the most dangerous natural hazards, especially when they are recurrent. In areas such as Galicia (Spain), forest fires are frequent and devastating. The development of fire risk models becomes a very important prevention task for these regions. Vegetation and moisture indices can be used to monitor vegetation status; however, the different indices may perform differently depending on the vegetation species. Eight different spectral indices were selected to determine the most appropriate index in Galicia. This study was extended to the adjacent region of Asturias. Six years of MODIS (Moderate Resolution Imaging Spectroradiometer) images, together with ground fire data…

Index (economics)TeledeteccióMeteorologyCiències de la terraVegetationEnhanced vegetation indexLogistic regressionforest fires; vegetation indices; fire danger; MODIS; remote sensingBoscos i silviculturaremote sensingMODISvegetation indicesNatural hazardLinear regressionIncendisforest firesGeneral Earth and Planetary SciencesEnvironmental sciencelcsh:QPhysical geographyModerate-resolution imaging spectroradiometerlcsh:ScienceFire historyfire danger
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Comparison between SMOS Vegetation Optical Depth products and MODIS vegetation indices over crop zones of the USA

2014

The Soil Moisture and Ocean Salinity (SMOS) mission provides multi-angular, dual-polarised brightness temperatures at 1.4 GHz, from which global soil moisture and vegetation optical depth (tau) products are retrieved. This paper presents a study of SMOS' tau product in 2010 and 2011 for crop zones of the USA. Retrieved tau values for 504 crop nodes were compared to optical/IR vegetation indices from the MODES (Moderate Resolution Imaging Spectroradiometer) satellite sensor, including the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVE), Leaf Area Index (LAI), and a Normalised Difference Water Index (NOW!) product. tau values were observed to increase during the…

2. Zero hunger010504 meteorology & atmospheric sciences0211 other engineering and technologiesSoil ScienceGrowing seasonGeology02 engineering and technologyVegetationEnhanced vegetation index01 natural sciencesNormalized Difference Vegetation Indexvegetation optical depthLinear regressionEnvironmental scienceL-band radiometryModerate-resolution imaging spectroradiometerComputers in Earth SciencesLeaf area indexoptical vegetation indices[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingWater contentSMOS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Metodo per il monitoraggio di superfici vegetali

2019

Si descrive un metodo da impiegare per la caratterizzazione delle coperture vegetali. A method to be used for the monitoring of vegetation surfaces is described, which includes the use of a device for measuring the spectral reflectance of vegetation using images acquired with a lightening system based on visible and infrared monoband LEDs and including devignetting, image cropping, radiometric calibration procedures and calculation of reflectance values and vegetation indices.

Settore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeMultispectral camera Vegetation Indices NDVI Image analysis Spectral reflectanceSettore AGR/09 - Meccanica AgrariaSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSettore AGR/02 - Agronomia E Coltivazioni Erbacee
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Canopy chlorophyll content and LAI estimation from Sentine1-2: Vegetation indices and Sentine1-2 Leve1-2A automatic products comparison

2019

The aim of this work is to analyze different methodologies for the estimation of leaf area index (LAI) and canopy chlorophyll content (CCC), using the Sentine1-2 satellite. LAI and CCC are biophysical parameters indicator of crop health state and fundamental in the productivity prediction. The purpose is to define the most optimal LAI and CCC estimation method for operational use in the monitoring of agricultural areas. Moreover, the CCC and LAI automatic products obtained directly through the Sentinel Application Platform Software (SNAP) biophysical processor and Sentine1-2 images by means of an artificial neural network (ANN) are validated. On the other hand, common vegetation indices use…

CanopyDiscrete mathematicsvalidationChlorophyll contentMean squared errorcanopy chlorophyll contentState (functional analysis)VegetationLAIvegetation indicesSaturation (graph theory)Leaf area indexSentinel-2Mathematics
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