Search results for "Computers in Earth Science"

showing 10 items of 323 documents

Evaluation of the S-NPP VIIRS land surface temperature product using ground data acquired by an autonomous system at a rice paddy

2018

Abstract The S-NPP VIIRS Land Surface Temperature (LST) product attained the stage V1 of validation maturity (provisional validated) at the end of 2014. This paper evaluates the current VIIRS V1 LST product versus concurrent ground data acquired at a rice paddy site from December 2014 to August 2016. The experimental site has three different seasonal and homogeneous land covers through the year, which makes the site interesting for validation activities. An autonomous and multiangular system was used to record continuous ground data at the site. The data acquired at zenith angles similar to the VIIRS viewing angles were used for the validation to avoid possible differences between satellite…

010504 meteorology & atmospheric sciencesPixelMeteorologymedia_common.quotation_subject0211 other engineering and technologies02 engineering and technologyLand cover01 natural sciencesAtomic and Molecular Physics and OpticsComputer Science ApplicationsSkyEmissivityRange (statistics)Environmental scienceSatelliteStage (hydrology)Computers in Earth SciencesEngineering (miscellaneous)Zenith021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingmedia_commonISPRS Journal of Photogrammetry and Remote Sensing
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Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review

2020

Abstract Green fractional vegetation cover ( f c ) is an important phenotypic factor in the fields of agriculture, forestry, and ecology. Spatially explicit monitoring of f c via relative vegetation abundance (RA) algorithms, especially those based on scaled maximum/minimum vegetation index (VI) values, has been widely investigated in remote sensing research. Although many studies have explored the effectiveness of RA algorithms over the past 30 years, a literature review summarizing the corresponding theoretical background, issues, current state-of-the-art techniques, challenges, and prospects has not yet been published. The overall objective of the present study was to accomplish a compre…

010504 meteorology & atmospheric sciencesResilient Livelihoods0211 other engineering and technologies02 engineering and technologyForests01 natural sciencesNormalized Difference Vegetation IndexArticleVegetation coverAbundance (ecology)Computers in Earth SciencesAdaptationEngineering (miscellaneous)Image resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingMathematicsEstimationVegetationBiodiversity15. Life on landAtomic and Molecular Physics and OpticsComputer Science ApplicationsRemote sensing (archaeology)Vegetation IndexAlgorithm
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Comparison of cloud-reconstruction methods for time series of composite NDVI data

2010

Land cover change can be assessed from ground measurements or remotely sensed data. As regards remotely sensed data, such as NDVI (Normalized Difference Vegetation Index) parameter, the presence of atmospherically contaminated data in the time series introduces some noise that may blur the change analysis. Several methods have already been developed to reconstruct NDVI time series, although most methods have been dedicated to reconstruction of acquired time series, while publicly available databases are usually composited over time. This paper presents the IDR (iterative Interpolation for Data Reconstruction) method, a new method designed to approximate the upper envelope of the NDVI time s…

010504 meteorology & atmospheric sciencesSeries (mathematics)0211 other engineering and technologiesSoil ScienceGeology02 engineering and technologyLand cover15. Life on land01 natural sciencesNormalized Difference Vegetation IndexBruit13. Climate actionCompositingmedicineEnvironmental scienceSatellite imageryNoise (video)Computers in Earth Sciencesmedicine.symptom021101 geological & geomatics engineering0105 earth and related environmental sciencesInterpolationRemote sensingRemote Sensing of Environment
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Influence of microporosity distribution on the mechanical behavior of oolithic carbonate rocks.

2015

Abstract The mechanical behavior of oolithic carbonate rocks was investigated for selected rocks with two different microstructural attributes: uniform (UP) and rimmed (RP) distribution of microporosity within ooids. These oolithic carbonate rocks are from the Oolithe Blanche formation, a deep saline aquifer in the Paris Basin, and a possible target for CO2 sequestration and geothermal production. Samples of similar physical properties (porosity, grain diameter, cement content) but different microporosity textures were deformed under triaxial configuration, in water saturated conditions, at 28 MPa of confining pressure, 5 MPa of pore pressure and at a temperature of 55 °C. During the experi…

010504 meteorology & atmospheric sciences[SDU.STU.PE]Sciences of the Universe [physics]/Earth Sciences/PetrographyMineralogy010502 geochemistry & geophysics[ SDU.STU.ST ] Sciences of the Universe [physics]/Earth Sciences/Stratigraphy01 natural sciencesTortuosityPore water pressureBrittlenessRock mechanicsMicroporosityParis BasinComputers in Earth SciencesOolithe Blanche formationSafety Risk Reliability and QualityPorosity0105 earth and related environmental sciences[ SDU.STU.PE ] Sciences of the Universe [physics]/Earth Sciences/PetrographyCarbonate rockGeotechnical Engineering and Engineering GeologyOverburden pressurePermeability (earth sciences)Rock mechanics[SDU.STU.ST]Sciences of the Universe [physics]/Earth Sciences/StratigraphyCarbonate rockGeology
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Monitoring elevation variations in leaf phenology of deciduous broadleaf forests from SPOT/VEGETATION time-series

2011

International audience; In mountain forest ecosystems where elevation gradients are prominent, temperature gradient-based phonological variability can be high. However, there are few studies that assess the capability of remote sensing observations to monitor ecosystem phenology along elevation gradients, despite their relevance under climate change. We investigated the potential of medium resolution remotely sensed data to monitor the elevation variations in the seasonal dynamics of a temperate deciduous broadleaf forested ecosystem. Further, we explored the impact of elevation on the onset of spring leafing. This study was based on the analysis of multi-annual time-series of VEGETATION da…

010504 meteorology & atmospheric sciences[SDV]Life Sciences [q-bio]0211 other engineering and technologiesSoil Science02 engineering and technologyLand coverSPRING PHENOLOGYPhonologyTemperate deciduous forest01 natural sciencesPLANT PHENOLOGYGLOBAL CHANGEComputers in Earth SciencesBeechVEGETATION PHENOLOGY021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingCLIMATE-CHANGEbiologyPhenologyElevationLeaf unfoldingGeologyVegetation15. Life on landbiology.organism_classificationDeciduous forestNOAA-AVHRRDeciduousMODISTemporal unmixingHIGH-LATITUDES13. Climate actionElevation[SDE]Environmental SciencesSATELLITE DATAEnvironmental scienceCommon spatial patternVEGETATIONPerpendicular vegetation indexREMOTE-SENSING DATARemote Sensing of Environment
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Mapping a ‘cryptic kingdom’: Performance of lidar derived environmental variables in modelling the occurrence of forest fungi

2016

Abstract Fungi are crucial to forest ecosystem function and provide important provisioning, regulating, supporting, and cultural ecosystem services. As major contributors to biomass decomposition, fungi are important to forest biogeochemical cycling and maintenance of vertebrate animal diversity. Many forest plant species live in a symbiotic relationship with a fungal partner that helps a host plant to acquire nutrients and water. In addition, edible fungi are recreationally as well as economically valuable. However, most fungi live in very cryptic locations (e.g. in soils and interior plant tissues) and are only visible when their ephemeral fruiting bodies are produced, making fungal occur…

0106 biological sciences010504 meteorology & atmospheric sciencesRange (biology)Soil ScienceBiology010603 evolutionary biology01 natural sciencesEcosystem servicesremote sensingAbundance (ecology)Forest ecologymushroomComputers in Earth Sciences0105 earth and related environmental sciencesNon-timber forest productBiomass (ecology)EcologySpecies diversityGeologydistribution modellingecosystem serviceHabitatta1181fruiting bodynon-timber forest productALSRemote Sensing of Environment
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Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

2018

International audience; Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types.…

0106 biological sciencesCanopyEarth observationPhoton010504 meteorology & atmospheric sciencesF40 - Écologie végétalehttp://aims.fao.org/aos/agrovoc/c_1920Soil Science01 natural sciencesMeasure (mathematics)http://aims.fao.org/aos/agrovoc/c_7701Multi-angle remote sensingProbability theoryhttp://aims.fao.org/aos/agrovoc/c_718Foliage clumping indexRange (statistics)http://aims.fao.org/aos/agrovoc/c_3081[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyComputers in Earth SciencesLeaf area indexhttp://aims.fao.org/aos/agrovoc/c_4039http://aims.fao.org/aos/agrovoc/c_4116Photon recollision probabilityhttp://aims.fao.org/aos/agrovoc/c_10672http://aims.fao.org/aos/agrovoc/c_32450105 earth and related environmental sciencesMathematicsRemote sensinghttp://aims.fao.org/aos/agrovoc/c_8114GeologyVegetationhttp://aims.fao.org/aos/agrovoc/c_5234http://aims.fao.org/aos/agrovoc/c_7558Leaf area indexhttp://aims.fao.org/aos/agrovoc/c_7273http://aims.fao.org/aos/agrovoc/c_1236http://aims.fao.org/aos/agrovoc/c_1556U30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_4026010606 plant biology & botanyhttp://aims.fao.org/aos/agrovoc/c_6124
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Chlorophyll fluorescence as a tool for management of plant resources

1994

Abstract Light-induced chlorophyll fluorescence has become a tool which has ever-increasing potential application to experimental plant physiology. The effects of frost, heat, and drought have been analyzed using the kinetics of individual leaves of two representative types of life form: an evergreen tree (holm oak) dominant in the Mediterranean Basin and an annual cultivated legume (soybean). Various indices were used to quantify their response to environmental stress. Canopy fluorescence for the two types of plants was simulated. For two levels of measurement, leaf or canopy, light-induced fluorescence appears to be helpful for forest or crop management in the Mediterranean area.

0106 biological sciencesCanopy[SPI.OTHER]Engineering Sciences [physics]/Other010504 meteorology & atmospheric scienceshealth care facilities manpower and serviceseducationSoil Science01 natural sciencesMediterranean Basinchemistry.chemical_compoundBotanyComputers in Earth SciencesChlorophyll fluorescencehealth care economics and organizations0105 earth and related environmental sciencesRemote sensingbiology[SPI.OTHER] Engineering Sciences [physics]/Otherfungifood and beveragesPlant physiologyGeology15. Life on landEvergreenbiology.organism_classificationFagaceaechemistryAgronomyChlorophyllFrostEnvironmental science010606 plant biology & botany
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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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Spatio-Temporal model structures with shared components for semi-continuous species distribution modelling

2017

Abstract Understanding the spatio-temporal dynamism and environmental relationships of species is essential for the conservation of natural resources. Many spatio-temporally sampled processes result in continuous positive [ 0 , ∞ ) abundance datasets that have many zero values observed in areas that lie outside their optimum niche. In such cases the most common option is to use two-part or hurdle models, which fit independent models and consequently independent environmental effects to occurrence and conditional-to-presence abundance. This may be correct in some cases, but not as much in others where the detection probability is related to the abundance. The aim of this work is to infer the…

0106 biological sciencesStatistics and ProbabilityProcess (engineering)Computer science010604 marine biology & hydrobiologyNicheManagement Monitoring Policy and Lawcomputer.software_genre01 natural sciencesNatural resourceEnvironmental niche modelling010104 statistics & probabilityAbundance (ecology)Component (UML)Data miningDynamism0101 mathematicsComputers in Earth SciencescomputerBayesian krigingSpatial Statistics
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