Search results for "Computers in Earth Science"

showing 10 items of 323 documents

Significance of the remotely sensed thermal infrared measurements obtained over a citrus orchard

1990

Abstract In this work we have developed a theoretical model that helps the interpretation of the remotely sensed thermal infrared measurements carried out over citrus orchards. A detailed analysis of the different factors which take part in the definition of the effective emissivity and temperature (observation height, viewing angle, type of soil, dimensions and separation between orange trees) is made. The model was validated under vertical observation in a citrus orchard during seven nights. In this situation we have determined that the model performs to an accuracy of about 1%.

Thermal infraredMeteorologyEmissivityEnvironmental scienceComputers in Earth SciencesViewing angleEngineering (miscellaneous)Atomic and Molecular Physics and OpticsComputer Science ApplicationsRemote sensingCitrus orchardISPRS Journal of Photogrammetry and Remote Sensing
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Thermal infrared radiance model for interpreting the directional radiometric temperature of a vegetative surface

1990

Abstract In this work we have proposed a two-dimensional radiance model that serves for interpreting the directional remotely-sensed thermal infrared data obtained over a vegetative surface when the effects of the shadows are minimal. The model was validated for different view angles from the measurements made with a radiometer placed on board a helicopter in two different citrus regions. And the root-mean-square deviation between the model predictions and the sensor measurements was 0.3°C.

Surface (mathematics)Thermal infraredRadiometerbusiness.industrySoil ScienceGeologyOn boardOpticsRadianceEnvironmental scienceRadiometric temperatureComputers in Earth SciencesbusinessRemote sensingRemote Sensing of Environment
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Batch Methods for Resolution Enhancement of TIR Image Sequences

2015

Thermal infrared (TIR) time series are exploited by many methods based on Earth observation (EO), for such applications as agriculture, forest management, and meteorology. However, due to physical limitations, data acquired by a single sensor are often unsatisfactory in terms of spatial or temporal resolution. This issue can be tackled by using remotely sensed data acquired by multiple sensors with complementary features. When nonreal-time functioning or at least near real-time functioning is admitted, the measurements can be profitably fed to a sequential Bayesian algorithm, which allows to account for the correlation embedded in the successive acquisitions. In this work, we focus on appli…

Earth observationAtmospheric ScienceBayesian smoothing methodComputer scienceBayesian probabilityInterval (mathematics)Thermal imagecomputer.software_genreremote sensingComputers in Earth ScienceSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliComputer visionimage enhancementComputers in Earth SciencesImage resolutionThermal imagesbusiness.industrySettore ING-INF/03 - TelecomunicazioniSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaBayesian smoothing methodsinterpolationTemporal resolutioncloud detectionBatch processingBayesian smoothing methods; cloud detection; image enhancement; interpolation; remote sensing; Thermal images; Computers in Earth Sciences; Atmospheric ScienceData miningArtificial intelligencebusinessFocus (optics)computerSmoothingSettore ICAR/06 - Topografia E Cartografia
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A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data

2018

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then a…

0106 biological sciencesFOS: Computer and information sciences010504 meteorology & atmospheric sciencesSpecific leaf areaClimateBos- en LandschapsecologieSoil ScienceFOS: Physical sciencesApplied Physics (physics.app-ph)010603 evolutionary biology01 natural sciencesStatistics - ApplicationsGoodness of fitAbundance (ecology)Machine learningForest and Landscape EcologyApplications (stat.AP)Computers in Earth SciencesPlant ecologyVegetatie0105 earth and related environmental sciencesRemote sensingMathematics2. Zero hungerPlant traitsVegetationData stream miningClimate; Landsat; Machine learning; MODIS; Plant ecology; Plant traits; Random forests; Remote sensing; Soil Science; Geology; Computers in Earth SciencesGlobal MapRegression analysisGeologyPhysics - Applied Physics15. Life on landRandom forestsRemote sensingPE&RCRandom forestMODISTraitVegetatie Bos- en LandschapsecologieVegetation Forest and Landscape EcologyLandsat
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Atmospheric correction of ENVISAT/MERIS data over inland waters: Validation for European lakes

2010

Traditional methods for aerosol retrieval and atmospheric correction of remote sensing data over water surfaces are based on the assumption of zero water reflectance in the near-infrared. Another type of approach which is becoming very popular in atmospheric correction over water is based on the simultaneous retrieval of atmospheric and water parameters through the inversion of coupled atmospheric and bio-optical water models. Both types of approaches may lead to substantial errors over optically-complex water bodies, such as case II waters, in which a wide range of temporal and spatial variations in the concentration of water constituents is expected. This causes the water reflectance in t…

Inland watersAtmospheric correction1903 Computers in Earth SciencesSoil ScienceGeologyInversion (meteorology)550 - Earth sciencesAerosolMERISAtmospheric correction10122 Institute of GeographyAerosol optical thicknessValidationWater modelEnvironmental scienceSpatial variabilitySatellite imageryWater qualityComputers in Earth Sciences910 Geography & travelSurface water1111 Soil Science1907 GeologyRemote sensing
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A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data

2001

Abstract A comparative study has been carried out on the most recent algorithms for the estimation of land surface emissivity (ϵ) using Advanced Very High Resolution Radiometer (AVHRR) data. Three of the algorithms are based on the Temperature-Independent Spectral Indices (TISI) concept using atmospherically corrected channels 3, 4, and/or 5, namely: (1) TISI BL , (2) TS-RAM, and (3) Δ day. The fourth is a simplified method based on the estimation of ϵ using atmospherically corrected data in the visible and near-infrared channels, called Normalized Difference Vegetation Index (NDVI) Thresholds Method (NDVI THM ). This method integrates a wide spectral data set of bare soil reflectivity meas…

MeteorologyAdvanced very-high-resolution radiometerSoil ScienceGeologyVegetationNormalized Difference Vegetation IndexRoot mean squareData retrievalEmissivityRadiometryEnvironmental scienceComputers in Earth SciencesRoot-mean-square deviationRemote sensingRemote Sensing of Environment
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Brown and green LAI mapping through spectral indices

2015

Abstract When crops senescence, leaves remain until they fall off or are harvested. Hence, leaf area index (LAI) stays high even when chlorophyll content degrades to zero. Current LAI approaches from remote sensing techniques are not optimized for estimating LAI of senescent vegetation. In this paper a two-step approach has been proposed to realize simultaneous LAI mapping over green and senescent croplands. The first step separates green from brown LAI by means of a newly proposed index, ‘Green Brown Vegetation Index (GBVI)’. This index exploits two shortwave infrared (SWIR) spectral bands centred at 2100 and 2000 nm, which fall right in the dry matter absorption regions, thereby providing…

Global and Planetary ChangeHyperspectral imagingEnhanced vegetation indexVegetationSpectral bandsManagement Monitoring Policy and LawGeographyAbsorption bandComputers in Earth SciencesLeaf area indexAbsorption (electromagnetic radiation)HyMapEarth-Surface ProcessesRemote sensingInternational Journal of Applied Earth Observation and Geoinformation
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Assessment of MODIS imagery to track light-use efficiency in a water-limited Mediterranean pine forest

2012

Abstract Daily values of gross primary production ( GPP ) derived from an eddy-covariance flux tower have been used to analyze the information content of the MODIS Photochemical Reflectance Index ( PRI ) on the light-use efficiency ( e ). The study has been conducted in a Mediterranean Pinus pinaster forest showing summer water stress. Advanced processing techniques have been used to analyze the effect of various external factors on e and PRI temporal variations. The intra-annual correlation between these two variables has been found to be mostly attributable to concurrent variations in sun and view zenith angles. The PRI has been normalized from these angular effects ( NPRI ), and its abil…

CanopyMediterranean climatebiologyWater stressSoil SciencePrimary productionGeologyPhotochemical Reflectance Indexbiology.organism_classificationEnvironmental sciencePinus pinasterEcosystemComputers in Earth SciencesZenithRemote sensingRemote Sensing of Environment
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Correcting AVHRR Long Term Data Record V3 estimated LST from orbital drift effects

2012

Abstract NOAA (National Oceanic and Atmospheric Administration) satellite series is known to suffer from what is known as the orbital drift effect. The Long Term Data Record (LTDR [Pedelty et al., 2007]), which provides AVHRR (Advanced Very High Resolution Radiometer) data from these satellites for the 80s and the 90s, is also affected by this orbital drift. To correct this effect on Land Surface Temperature (LST) time series, a novel method is presented here, which consists in adjusting retrieved LST time series on the basis of statistical information extracted from the time series themselves. This method is as simple and straightforward as possible, in order to be implemented easily for s…

Polynomial regression010504 meteorology & atmospheric sciencesBasis (linear algebra)Series (mathematics)PixelAdvanced very-high-resolution radiometer0211 other engineering and technologiesSoil ScienceGeology02 engineering and technologyResidual01 natural sciences13. Climate actionEnvironmental scienceSatelliteComputers in Earth SciencesChange detection021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Vegetation dynamics from NDVI time series analysis using the wavelet transform

2009

A multi-resolution analysis (MRA) based on the wavelet transform (WT) has been implemented to study NDVI time series. These series, which are non-stationary and present short-term, seasonal and long-term variations, can be decomposed using this MRA as a sum of series associated with different temporal scales. The main focus of the paper is to check the potential of this MRA to capture and describe both intra- and inter-annual changes in the data, i.e., to discuss the ability of the proposed procedure to monitor vegetation dynamics at regional scale. Our approach concentrates on what wavelet analysis can tell us about a NDVI time series. On the one hand, the intra-annual series, linked to th…

Advanced very-high-resolution radiometerSoil ScienceWavelet transformGeologyVegetationLand coverSeasonalitymedicine.diseaseNormalized Difference Vegetation IndexWaveletmedicineComputers in Earth SciencesTime seriesRemote sensingMathematicsRemote Sensing of Environment
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