0000000000061842

AUTHOR

Philippe Richaume

showing 8 related works from this author

Calibrating the effective scattering albedo in the SMOS algorithm: some first results

2016

International audience; This study focuses on the calibration of the effective scattering albedo (ω) of vegetation in the soil moisture (SM) retrieval at L-Band. Currently, in the SMOS Level 2 and 3 algorithms, the value of ω is set to 0 for low vegetation and ∼ 0.06 – 0.08 for forests. Different parameterizations of vegetation (in terms of ω values) were tested in this study. The possibility of combining soil roughness and vegetation contributions as a single parameter (“combined” method) leads to an important simplification in the algorithm and was also evaluated here. Following these assumptions, retrieved values of SMOS SM were compared with SM data measured over many in situ sites worl…

L band010504 meteorology & atmospheric sciencesPixelScattering0211 other engineering and technologies[SDU.STU]Sciences of the Universe [physics]/Earth SciencesSingle parameter02 engineering and technologyVegetationSMAP15. Life on landAlbedo01 natural sciencesscattering albedoCalibrationEnvironmental sciencesoil moistureL-MEB modelAlgorithmWater content[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingSMOS
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Evaluation of the most recent reprocessed SMOS soil moisture products: Comparison between SMOS level 3 V246 and V272

2015

International audience; Soil Moisture and Ocean Salinity (SMOS) satellite has been providing surface soil moisture (SSM) and ocean salinity (OS) retrievals at L-band for five years (2010–2014). During these five years, the SSM retrieval algorithm i.e. the L-MEB (L-Band Microwave Emission of the Biosphere [1] model has been progressively improved and hence results in different versions of the SMOS SSM products. This study aims at evaluating the last improvement in the SSM products of the most recent SMOS level 3 (SMOSL3) reprocessing (SMOSL3_2.72) vs. an earlier version (SMOSL3_246). Correlation, bias, Root Mean Square Difference (RMSD) and unbiased RMSD (unbRMSD) were used as perform…

Meteorologyland surfaceEquatorBiosphereRoot mean square differenceSM-DAS-2hydrologyAridSalinityremote sensingsatellites13. Climate actionClimatologyHigh latitudecorrelationEnvironmental scienceSatellitesoil moisturemicrowave theory and techniquesWater content[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSMOS
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First evaluation of the simultaneous SMOS and ELBARA-II observations in the Mediterranean region

2012

Abstract The SMOS (Soil Moisture and Ocean Salinity) mission was launched on November 2, 2009. Over the land surfaces, simultaneous retrievals of surface soil moisture (SM) and vegetation characteristics made from the multi-angular and dual polarization SMOS observations are now available from Level-2 (L2) products delivered by the European Space Agency (ESA). Therefore, first analyses evaluating the SMOS observations in terms of Brightness Temperatures (TB) and L2 products (SM and vegetation optical depth TAU) can be carried out over several calibration/validation (cal/val) sites selected by ESA over all continents. This study is based on SMOS observations and in situ measurements carried …

Mediterranean climate010504 meteorology & atmospheric sciences[SDV]Life Sciences [q-bio]0211 other engineering and technologiesSoil Science550 - Earth sciences02 engineering and technology01 natural sciencesVineyardNormalized Difference Vegetation Index14. Life underwaterComputers in Earth SciencesWater contentComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometerGeology15. Life on land13. Climate actionBrightness temperatureSoil water[SDE]Environmental SciencesEnvironmental sciencesoil moisture; optical depth; retrievals; mediterranean environment; level 2 algorithm; brightness temperature; vineyards; soil; NDVI; MODIS;Moderate-resolution imaging spectroradiometerSMOS
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Analyzing the impact of using the SRP (Simplified roughness parameterization) method on soil moisture retrieval over different regions of the globe

2015

International audience; This paper focuses on a new approach to account for soil roughness effects in the retrieval of soil moisture (SM) at L-band in the framework of the SMOS (Soil Moisture and Ocean Salinity) mission: the Simplified Roughness Parameterization (SRP). While the classical retrieval approach considers SM and τ nad (vegetation optical depth) as retrieved parameters, this approach is based on the retrieval of SM and the TR parameter combining τ nad and soil roughness (TR τ nad + Hr /2). Different roughness parameterizations were tested to find the best correlation (R), bias and unbiased RMSE (ubRMSE) when comparing homogeneous retrievals of SM and in situ SM measurements carri…

L bandVegetation optical depth010504 meteorology & atmospheric sciencesMean squared errorvegetation mapping0211 other engineering and technologiesSampling (statistics)[SDU.STU]Sciences of the Universe [physics]/Earth SciencesSoil science02 engineering and technologySurface finish01 natural sciencesL-bandHomogeneousEnvironmental sciencesoil measurementsmicrowave radiometrysoil moistureWater contentSoil roughness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingmathematical model021101 geological & geomatics engineering0105 earth and related environmental sciences
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A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm

2017

Abstract This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (H R , and N Rp , p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and H R  = 0.1, whereas values of ω = 0.06 − 0.08 and H R  = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, H R and N Rp , p = H,V) were tested in this study, tre…

biosphèreL band010504 meteorology & atmospheric sciences[SDV]Life Sciences [q-bio]0211 other engineering and technologieseffective scattering albedo02 engineering and technologyLand coverManagement Monitoring Policy and Law01 natural sciencestélédétection microondesCalibrationhumidité du sol14. Life underwaterComputers in Earth SciencesWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesRemote sensingrugosité de surfaceGlobal and Planetary Changesalinité des océansScatteringVegetation15. Life on landAlbedoL-bandGeographysoil roughnessalbédosoil moistureSoil roughnessSMOSrugosité du sol
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Retrievals of soil moisture and optical depth from CAROLS

2011

International audience; We propose in this paper to evaluate a method to retrieve soil moisture (SM) and vegetation optical thickness, in areas of unknown roughness and unknown vegetation water content in view of operational applications, by using airborne Tb measurements acquired in South-West of France. Results are compared to in situ measurements, manual and automatic ones included in SMOSmania network, in the South-West of France.

[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]télédétection[SDE.MCG]Environmental Sciences/Global ChangesSignal and Image processingmicroondetempérature de brillance RADIOMETRE;SATELLITE SMOSvol instrumentemodèle de transfert radiatifTraitement du signal et de l'imagehumidité du solRADIOMETRESATELLITE SMOSMilieux et Changements globaux[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUS
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SMOS-IC : a revised SMOS product based on a new effective scattering albedo and soil roughness parameterization

2017

International audience; This study presents a new SMOS (Soil Moisture and Ocean Salinity) soil moisture (SM) product based on a different scattering albedo and soil roughness parameterization: the SMOS-IC (SMOS INRA-CESBIO) data set. In this study, several parameterizations of the vegetation and soil roughness parameters (co, H-R and N-RP, P = H, V) were tested and the retrieved SM was compared against in situ observations obtained from the International Soil Moisture Network (ISMN). Firstly, values of omega = 0.10, H-R = 0.4 and N-RP = -1 (P = H, V) were found globally. Secondly, a calibration of these parameters was obtained for the different land cover categories of the International Geo…

010504 meteorology & atmospheric sciencesScattering[SDV]Life Sciences [q-bio]0211 other engineering and technologies02 engineering and technologyLand coverVegetation15. Life on landAlbedoAtmospheric sciences01 natural sciences13. Climate actionProduct (mathematics)[SDE]Environmental SciencesCalibrationEnvironmental scienceWater contentSoil roughness021101 geological & geomatics engineering0105 earth and related environmental sciences
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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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