0000000000061841

AUTHOR

Roberto Fernandez-moran

showing 15 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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Towards a long-term dataset of ELBARA-II measurements assisting SMOS level-3 land product and algorithm validation at the Valencia Anchor Station

2015

[EN] The Soil Moisture and Ocean Salinity (SMOS) mission was launched on 2nd November 2009 with the objective of providing global estimations of soil moisture and sea salinity. The main activity of the Valencia Anchor Station (VAS) is currently to assist in a long-term validation of SMOS land products. This study focus on a level 3 SMOS data validation with in situ measurements carried out in the period 2010-2012 over the VAS. ELBARA-II radiometer is placed in the VAS area, observing a vineyard field considered as representative of a major proportion of an area of 50×50 km, enough to cover a SMOS footprint. Brightness temperatures (TB) acquired by ELBARA-II have been compared to those obser…

010504 meteorology & atmospheric sciencesMeteorologyGeography Planning and Development0211 other engineering and technologiesData validationlcsh:G1-92202 engineering and technology01 natural sciencesVineyardSoil roughnessFootprintEarth and Planetary Sciences (miscellaneous)Vegetation optical depth14. Life underwaterPrecipitationWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRadiometerHumedad del suelobrightness temperature ELBARA-II L-MEB SMOS SMOS level 3 data soil moisture soil roughness Valencia Anchor Station vegetation optical depth15. Life on landEspesor óptico de la vegetaciónTerm (time)GeographyL-MEB13. Climate actionBrightness temperatureRugosidad del sueloTemperatura de brilloSoil moistureBrightness temperaturelcsh:Geography (General)
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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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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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First Retrievals of ASCAT-IB VOD (Vegetation Optical Depth) at Global Scale

2021

Global and long-term vegetation optical depth (VOD) dataset are very useful to monitor the dynamics of the vegetation features, climate and environmental changes. In this study, the radar-based global ASCAT (Advanced SCATterometer) IB (INRAE-BORDEAUX) VOD was retrieved using a model which was recently calibrated over Africa. In order to assess the performance of IB VOD, the Saatchi biomass and three other VOD datasets (ASCAT V16, AMSR2 LPRM V5 and VODCA LPRM V6) derived from C-band observations were used in the comparison. The preliminary results show that IB VOD has a promising ability to predict biomass $(\mathrm{R}=0.74,\ \text{RMSE} =44.82\ \text{Mg}\ \text{ha}^{-1})$ , which is better …

Vegetation optical depth010504 meteorology & atmospheric sciencesvegetation mapping0211 other engineering and technologiesScale (descriptive set theory)02 engineering and technology01 natural sciencesCombinatoricsremote sensingvegetationoptical sensorC-bandComputingMilieux_MISCELLANEOUSattenuation021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsprediction algorithmbiomassOrder (ring theory)15. Life on landPrediction algorithmsASCAT13. Climate action[SDE]Environmental SciencesVegetation optical DepthScatterometerBiomedical optical imagingRadar Measurement
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Evaluating the impact of roughness in soil moisture and optical thickness retrievals over the VAS area

2014

International audience

Valencia Anchor Station[SDE.MCG]Environmental Sciences/Global ChangesL - MEB modelSoil scienceSurface finishELBARA - IIsoil roughnessEnvironmental sciencesoil moistureWater content[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUSRemote sensingSMOS
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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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Simultaneous retrieval of global scale Vegetation Optical Depth, surface roughness, and soil moisture using X-band AMSR-E observations

2019

Abstract The radiative transfer scheme implemented for the retrieval of soil moisture from passive microwaves is a function of scattering, polarization mixing and attenuation effects of soil and vegetation. Theses factors are usually represented by Vegetation Optical Depth (VOD), vegetation scattering albedo, and surface roughness parameter, along with soil moisture. The VOD is the degree to which vegetation attenuates the microwave radiation. It has generally the dominant effect from vegetation, whereas scattering is negligible and close to zero. The surface roughness (which varies in space but not much in time) is until recently, often assumed to be a global constant. In this work, we att…

Radiometer010504 meteorology & atmospheric sciencesAttenuation0208 environmental biotechnologySoil ScienceGeology02 engineering and technologyVegetationAlbedo01 natural sciencesCivil Engineering020801 environmental engineeringSurface roughnessRadiative transferEnvironmental sciencePrecipitationComputers in Earth SciencesWater content0105 earth and related environmental sciencesRemote sensingIndraStra Global
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Intercomparison of Soil Moisture Retrieved from GNSS-R and from Passive L-Band Radiometry at the Valencia Anchor Station

2019

In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on the intercomparison of soil moisture monitoring from Global Navigation Satellite System Reflectometry (GNSS-R) signals and passive L-band microwave radiometer observations at the Valencia Anchor Station is introduced. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and a dual-pol down-looking antenna for receiving LHCP (left-hand circular polarization) and RHCP (right-hand circular polarization) reflected signals from the soil surface. Data were collected from the three different antennas through the two channels of Oceanpal GNSS-R receiver and, in addition, calibration …

010504 meteorology & atmospheric sciences0211 other engineering and technologies02 engineering and technologyELBARA-II radiometerlcsh:Chemical technology01 natural sciencesBiochemistryArticleAnalytical Chemistrylcsh:TP1-1185L-band radiometryElectrical and Electronic EngineeringOceanpalReflectometryInstrumentationWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingValencia Anchor StationRadiometerMoistureGNSS-RMicrowave radiometerAtomic and Molecular Physics and OpticsGNSS applicationsSoil waterEnvironmental scienceRadiometrysoil moistureSensors
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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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Flipped evaluation: herramientas online para la evaluación participativa

2021

[EN] The evaluation of a subject is a fundamental part of the teaching-learning process and one of the main concerns of our students. This is a complex task that requires a lot of effort from the teacher. This is a growing effort in line with the increased weight of con-tinuous evaluation in the current educational system. In this work, different methodo-logies focused on maximizing the student’s performance are presented, thus minimizing the extra effort for the teacher in the evaluation process. We provide several examples of activities throught Moodle platform such as the workshop, glossary, databases, ques-tionnaires, etc. Some of them allow self-assessment once configured, whereas others pr…

Innovación educativaMoodle toolsEvaluaciónQuestionnaireEducación superiorEnseñanza superiorHerramientas de MoodleTecnologías y educaciónTallerEvaluationWorkshopCuestionario
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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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