Search results for "Soil"

showing 10 items of 3493 documents

Modeling the Effects of Climate Change on the Supply of Phosphate-Phosphorus

2009

The transfer of phosphorus from terrestrial to aquatic ecosystems is a key route through which climate can influence aquatic ecosystems. A number of climatic factors interact in complex ways to regulate the transfer of phosphorus and modulate its ecological effects on downstream lakes and reservoirs. Processes influencing both the amount and timing of phosphorus export from terrestrial watersheds must be quantified before we can assess the direct and indirect effects of the weather on the supply and recycling of phosphorus. Simulation of the export of phosphorus from the terrestrial environment is complicated by the fact that it is difficult to describe seasonal and inter-annual variations …

010504 meteorology & atmospheric sciencesAquatic ecosystemPhosphorus0207 environmental engineeringchemistry.chemical_elementSoil science02 engineering and technology15. Life on landAtmospheric sciences01 natural sciences6. Clean waterExtreme weatherchemistry13. Climate actionEffects of global warmingEvapotranspirationEnvironmental scienceTerrestrial ecosystemPrecipitation020701 environmental engineeringSurface runoff0105 earth and related environmental sciences
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Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

2012

Abstract ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT-5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms may be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from …

010504 meteorology & atmospheric sciencesArtificial neural networkMean squared errorbusiness.industryComputer science0211 other engineering and technologiesSoil ScienceGeology02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesRegressionSupport vector machineTemporal resolutionGround-penetrating radarCurve fittingArtificial intelligenceComputers in Earth SciencesbusinessImage resolutioncomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Coastal precipitation regimes in Kenya.

1997

Kenya is under the influence of the seasonal reversal of the Indian ocean monsoons. However, its coastal belt, up to about 50 km inland, exhibits original climatic features. Hierarchical clustering...

010504 meteorology & atmospheric sciencesAtmospheric circulation[SHS.GEO] Humanities and Social Sciences/GeographyGeography Planning and Development0207 environmental engineeringSoil resilienceGeology02 engineering and technology[SHS.GEO]Humanities and Social Sciences/GeographySeasonality010502 geochemistry & geophysicsMonsoonmedicine.disease01 natural sciences[ SHS.GEO ] Humanities and Social Sciences/GeographyIndian oceanSea breeze13. Climate actionClimatologymedicineEnvironmental sciencePrecipitationSurface runoff020701 environmental engineering0105 earth and related environmental sciences
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Evaluating roughness effects on C-band AMSR-E observations

2014

International audience; The usefulness of microwave remote sensing to retrieve near-surface soil moisture has already been demonstrated in many studies. However, obtaining high quality estimates of soil moisture is influenced by many effects from soil, vegetation and atmosphere; one of the key parameters is surface roughness. This research focusses on a semi-empirical method to evaluate the roughness effects from space borne observations. Global maps of roughness effects are evaluated at C-band from AMSR-E measurements.

010504 meteorology & atmospheric sciencesC band[SDE.MCG]Environmental Sciences/Global Changes0211 other engineering and technologiessoil surface roughnessAMSR-E02 engineering and technologySurface finish01 natural sciences13. Climate actionEnvironmental sciencesoil moisture[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing2014 IEEE Geoscience and Remote Sensing Symposium
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Estimating the macroscopic capillary length from Beerkan infiltration experiments and its impact on saturated soil hydraulic conductivity predictions

2020

International audience; The macroscopic capillary length, λc, is a fundamental soil parameter expressing the relative importance of the capillary over gravity forces during water movement in unsaturated soil. In this investigation, we propose a simple field method for estimating λc using only a single-ring infiltration experiment of the Beerkan type and measurements of initial and saturated soil water contents. We assumed that the intercept of the linear regression fitted to the steady-state portion of the experimental infiltration curve could be used as a reliable predictor of λc. This hypothesis was validated by assessing the proposed calculation approach using both analytical and field d…

010504 meteorology & atmospheric sciencesCapillary actionField dataHydraulic conductivity0207 environmental engineeringSoil science02 engineering and technology[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study01 natural sciencesHydraulic conductivityBeerkan Hydraulic conductivity Infiltration Macroscopic capillary length Ring infiltrometerApproximation errorBeerkanLinear regressionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestali[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology020701 environmental engineeringRing infiltrometer0105 earth and related environmental sciencesWater Science and TechnologyInfiltration6. Clean waterMacroscopic capillary lengthInfiltration (hydrology)Capillary lengthSoil waterEnvironmental science
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Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud

2020

Remote sensing optical sensors onboard operational satellites cannot have high spectral, spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can adversely affect the signal contaminating the land surface observations. We present a HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to combine multispectral images of different sensors to reduce noise and produce monthly gap free high resolution (30 m) observations over land. Our approach uses images from the Landsat (30 m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500 m spatial resolution and daily revisit cycle). We implem…

010504 meteorology & atmospheric sciencesComputer science0208 environmental biotechnologyMultispectral imageSoil Science02 engineering and technology01 natural sciencesArticleComputers in Earth SciencesImage resolution0105 earth and related environmental sciencesRemote sensingPropagation of uncertaintyNoise (signal processing)GeologyKalman filterData fusionSensor fusion020801 environmental engineeringMODIS13. Climate actionScalabilityGap fillingKalman filterLandsatSmoothingSmoothingRemote Sensing of Environment
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Recent Advances in Techniques for Hyperspectral Image Processing

2009

International audience; Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information. Performance of the discussed techniques is evaluated in …

010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesSoil ScienceImage processing02 engineering and technologyMachine learningcomputer.software_genre01 natural sciences[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingComputer visionComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingData processingContextual image classificationbusiness.industryHyperspectral imagingGeologyImaging spectroscopyInformation extractionKernel methodSnapshot (computer storage)Artificial intelligencebusinesscomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …

2011

International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…

010504 meteorology & atmospheric sciencesComputer scienceGaussian0211 other engineering and technologiesSoil ScienceCANOPY BIOPHYSICAL CHARACTERISTICS02 engineering and technologyNEURAL NETWORK01 natural sciencesTransfer functionsymbols.namesakeAtmospheric radiative transfer codesRadiative transferRange (statistics)Sensitivity (control systems)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingArtificial neural networkGeologySigmoid functionRELATION SOL-PLANTE-ATMOSPHEREMODEL INVERSION[SDE]Environmental SciencessymbolsINDICE FOLIAIRE
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Multi-phase classification by a least-squares support vector machine approach in tomography images of geological samples

2016

Abstract. Image processing of X-ray-computed polychromatic cone-beam micro-tomography (μXCT) data of geological samples mainly involves artefact reduction and phase segmentation. For the former, the main beam-hardening (BH) artefact is removed by applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. A Matlab code for this approach is provided in the Appendix. The final BH-corrected image is extracted from the residual data or from the difference between the surface elevation values and the original grey-scale values. For the segmentation, we propose a novel least-squar…

010504 meteorology & atmospheric sciencesComputer scienceStratigraphySoil ScienceImage processing010502 geochemistry & geophysicsResidual01 natural sciences550 Earth scienceslcsh:StratigraphyGeochemistry and PetrologyLeast squares support vector machineSegmentationlcsh:QE640-6990105 earth and related environmental sciencesEarth-Surface ProcessesPixelbusiness.industrylcsh:QE1-996.5PaleontologyGeologyPattern recognition550 Geowissenschaftenlcsh:GeologyData setSupport vector machineGeophysicsData pointArtificial intelligencebusinessSolid Earth
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Soil organic carbon stock on the Majorca Island: temporal change in agricultural soil over the last 10 years

2019

8 Pags.- 5 Tabls.- 3 Figs.

010504 meteorology & atmospheric sciencesConservation agricultureLand managementMediterranean soil organic carbonspatial variationSpatial and temporal variationCarbon sequestration01 natural sciencestemporal changeSoil managementMediterranean soil carbonsoil carbon sequestrationAgricultural landGeostatistics0105 earth and related environmental sciencesEarth-Surface ProcessesAgroforestrySoil organic matter04 agricultural and veterinary sciencesSoil carbonCrop rotationMajorca carbon storage040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceCrop management
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