0000000000061843

AUTHOR

Marie Parrens

showing 9 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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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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Analysis of the radar vegetation index and assessment of potential for improvement

2018

The Radar Vegetation Index (RVI) is widely applied to indicate vegetation cover. The index includes the backscattering intensities of co- and cross-polarization that do not only contain information coming from vegetation scattering at longer wavelength (L-band), but also from the soil underneath. A forward modelling approach using active and passive microwave-derived parameters to obtain the scattering contribution of the soil is pursued. The idea of this research study is a subtraction of the attenuated soil scattering contribution from the measured backscattering intensities, to provide a clean vegetation-based solution, called improved RVI (RVII). For latter analysis, the vegetation volu…

010504 meteorology & atmospheric sciencesmicrowave[SDV]Life Sciences [q-bio]0211 other engineering and technologiesSoil science02 engineering and technology01 natural scienceslaw.inventionVegetation coverlawmedicineRange (statistics)RadarComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRadarVegetationScatteringSMAP15. Life on landWavelength[SDE]Environmental SciencesVegetation water contentEnvironmental scienceactive-passive sensingmedicine.symptomVegetation IndexVegetation (pathology)Cartography
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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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Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations

2015

Quantifying roughness effects on ground surface emissivity is an important step in obtaining high-quality soil moisture products from large-scale passive microwave sensors. In this study, we used a semi-empirical method to evaluate roughness effects (parameterized here by the parameter) on a global scale from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) observations. AMSR-E brightness temperatures at 6.9 GHz obtained from January 2009 to September 2011, together with estimations of soil moisture from the SMOS (Soil Moisture and Ocean Salinity) L3 products and of soil temperature from ECMWF’s (European Centre for Medium-range Weather Forecasting) were used as inputs in a retrieval…

010504 meteorology & atmospheric sciencestélédétectionScience0211 other engineering and technologiesWeather forecasting[SDU.STU]Sciences of the Universe [physics]/Earth SciencesElectromagnétismesoil surface roughness02 engineering and technologySurface finishcomputer.software_genredonnée satellite01 natural sciencesSciences de la TerreNormalized Difference Vegetation Indexsoil moisture;soil surface roughness;AMSR-EElectromagnetismEmissivitySurface roughnessTraitement du signal et de l'image14. Life underwaterWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometercapteur smosQSignal and Image processingradiométrie microondesVegetationAMSR-E15. Life on land[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismEarth SciencesGeneral Earth and Planetary SciencesEnvironmental sciencesoil moisturecomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingRemote Sensing
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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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Roughness and vegetation parameterizations at L-band for soil moisture retrievals over a vineyard field

2015

Abstract The capability of L-band radiometry to monitor surface soil moisture (SM) at global scale has been analyzed in numerous studies, mostly in the framework of the ESA SMOS and NASA SMAP missions. To retrieve SM from L-band radiometric observations, two significant effects have to be accounted for, namely soil roughness and vegetation optical depth. In this study, soil roughness effects on retrieved SM values were evaluated using brightness temperatures acquired by the L-band ELBARA-II radiometer, over a vineyard field at the Valencia Anchor Station (VAS) site during the year 2013. Different combinations of the values of the model parameters used to account for soil roughness effects (…

BrightnessL bandRadiometerMean squared error[SDE.MCG]Environmental Sciences/Global ChangesSoil ScienceGeology15. Life on landL-bandAtmospheric radiative transfer codesL-MEBvegetationCalibrationsoil roughnessRadiometryEnvironmental sciencemicrowave radiometryComputers in Earth Sciencessoil moistureWater content[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUSRemote sensingSMOS
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