0000000000311298

AUTHOR

Amen Al-yaari

showing 13 related works from this author

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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Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements

2019

Soil moisture (SM) is a key state variable in understanding the climate system through its control on the land surface energy, water budget partitioning, and the carbon cycle. Monitoring SM at regional scale has become possible thanks to microwave remote sensing. In the past two decades, several satellites were launched carrying on board either radiometer (passive) or radar (active) or both sensors in different frequency bands with various spatial and temporal resolutions. Soil moisture algorithms are in rapid development and their improvements/revisions are ongoing. The latest SM retrieval products and versions of products that have been recently released are not yet, to our knowledge, com…

TechnologyPassive microwave remote sensing010504 meteorology & atmospheric sciences0208 environmental biotechnologyActive microwave remote sensingReview02 engineering and technology01 natural sciences7. Clean energylaw.inventionRemote SensinglawRadarEvaluationComputingMilieux_MISCELLANEOUSevaluationGeologypassive microwave remote sensingDATA SETSLife Sciences & Biomedicineactive microwave remote sensingSMOSLAND SURFACESreviewSoil ScienceClimate changeEnvironmental Sciences & EcologyLand coverVALIDATIONRETRIEVALSInternational soil moisture networkComputers in Earth SciencesImaging Science & Photographic Technology[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment0105 earth and related environmental sciencesRemote sensingScience & TechnologyRadiometerAMSR-ESMAPScatterometerinternational soil moisture network020801 environmental engineeringCLIMATEASCAT13. Climate actionSoil waterEnvironmental scienceSpatial variabilitySatelliteSoil moisturesoil moistureEnvironmental SciencesL-BANDRemote Sensing of Environment
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SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product

2017

© 2017 by the authors. The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product that was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d'Etudes Spatiales de la BIOsphère). One of the main go…

environmental_sciencesL bandVegetation optical depth010504 meteorology & atmospheric sciencesNDVI[SDV]Life Sciences [q-bio]Science0211 other engineering and technologiesWeather forecasting0207 environmental engineeringSoil science02 engineering and technologycomputer.software_genre01 natural sciencesSMOS; L-band; Level 3; ECMWF; SMOS-IC; soil moisture; vegetation optical depth; MODIS; NDVINormalized Difference Vegetation IndexECMWFvegetation optical depthtempératurehumidité du solluminosity14. Life underwater020701 environmental engineeringWater content021101 geological & geomatics engineeringRemote sensing0105 earth and related environmental sciencessalinité des océansQBiosphereluminositéVegetationAlbedoL-bandSpectroradiometerMODIS13. Climate actionBrightness temperatureProduct (mathematics)General Earth and Planetary SciencesEnvironmental sciencesoil moistureSMOS;L-band;level 3;ECMWF;SMOS-IC;soil moisture;vegetation optical depth;MODIS;NDVISMOS-ICcomputerLevel 3SMOSRemote Sensing
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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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Global Long-Term Brightness Temperature Record from L-Band SMOS and Smap Observations

2021

Passive microwave remote sensing observations at L-band provide key and global information on surface soil moisture (SM) and vegetation optical depth (VOD), which are related to the Earth water and carbon cycles. Only two spaceborne L-band sensors are currently operating: SMOS, launched end of 2009 and thus providing now a 11-year global dataset and SMAP, launched beginning of 2015. To ensure SM and L-VOD data continuity in the event of failure of one of the space-borne SMOS or SMAP sensors, we developed a consistent brightness temperature (TB) record by first producing consistent 40° SMOS and SMAP TB estimates based on SMOS-IC and SMAP enhanced data resp., and then fusing them via linear f…

Vegetation optical depthL bandData continuityBrightness temperatureEnvironmental scienceMicrowave remote sensingOptical polarizationSensor fusionTerm (time)Remote sensing2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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Alternate Inrae-Bordeaux VOD Indices from SMOS, AMSR2 and ASCAT: Overview of Recent Developments

2021

International audience; Vegetation optical depth (VOD) is used to parameterize microwave extinction effects within the vegetation layer. Many studies have showed VOD presents interesting features for applications in ecology, water and carbon cycles, and VOD is only marginally impacted by signal disturbances and artefacts from atmospheric, cloud and sun illumination effects. As soil moisture (and not VOD) has generally been the main factor of interest in retrieval studies from microwave observations, there is room for improvement in the retrieved VOD products. In this context, INRAE Bordeaux recently developed alternate VOD products from the SMOS, AMSR2 and ASCAT sensors, by addressing speci…

Spatial correlationVegetation optical depth[SDE.IE]Environmental Sciences/Environmental EngineeringEnvironmental scienceContext (language use)VegetationRemote sensingRadiometryMoistureRemote sensing2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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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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Interannual Variability of Biomass (SMOS Vegetation Optical Depth) Over the Contiguous United States

2021

Interannual variability in biomass represented by SMOS vegetation optical depth (VOD) and precipitation was assessed over the Contiguous United States. The greatest interannual variability in both VOD and precipitation occurred in shrubs and herbaceous (grasslands), with forests the least variable. At a continental scale, VOD was strongly correlated with annual precipitation. Results showed a significant correlation coefficient (∼ 0.93) between interannual variability of precipitation and biomass, indicating that the interannual variability of precipitation could be a good predictor of the interannual variability of biomass.

Biomass (ecology)Vegetation optical depthCorrelation coefficientfood and beveragesEnvironmental sciencePrecipitationVegetationHerbaceous plantAtmospheric sciencescomplex mixtures2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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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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Global Scale IB AMSR2 Vegetation Optical Depth at X-Band

2021

Vegetation Optical Depth (VOD) plays an increasingly important role in studying global carbon, water and energy transformation [1], [2]. This study explores the performance of the X-MEB (X-band microwave emission of the biosphere) model at global scale. Similar to the L-MEB model, the X-MEB model, built by INRAE (Institut national de recherche pour l'agriculture, l'alimentation et l'environnement) Bordeaux, aims to retrieve VOD (referred to as IB X-VOD) at X-band. To avoid the ill-posed problem caused by retrieving two parameters of interest (soil moisture (SM) and VOD) from mono-angular and dual-polarized observations (AMSR2), which are strongly correlated, we used the ERA5 SM product as a…

Biomass (ecology)Scale (ratio)BiosphereEnvironmental scienceVegetationLeaf area indexAlbedoAtmospheric sciencesWater contentNormalized Difference Vegetation Index2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
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