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2. Estimating High-Resolution Soil Moisture Over Mountainous Regions Using Remotely-Sensed Multispectral and Topographic Data

Author

Fan, Lei, primary, Al-Yaari, Amen, additional, Frappart, Frederic, additional, Peng, Jian, additional, Wen, Jianguang, additional, Xiao, Qing, additional, Jin, Rui, additional, Li, Xiaojun, additional, Liu, Xiangzhuo, additional, Wang, Mengjia, additional, Chen, Xiuzhi, additional, Zhao, Lin, additional, Ma, Mingguo, additional, and Wigneron, Jean-Pierre, additional

Published
2022
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3. SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives

Author

Wigneron, Jean-Pierre, Li, Xiaojun, Frappart, Frédéric, Fan, Lei, Al-Yaari, Amen, De Lannoy, Gabrielle, Liu, Xiangzhuo, Wang, Mengjia, Le Masson, Erwan, Moisy, Christophe, Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Nanjing University of Information Science and Technology (NUIST), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), NASA Goddard Space Flight Center (GSFC), Technologie campus Gent - KU Leuven (KU Leuven), Beijing Normal University (BNU), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), École pratique des hautes études (EPHE), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Technology, VEGETATION OPTICAL DEPTH, Science & Technology, L-BAND EMISSION, LAND SURFACES, Vegetation phenology, Environmental Sciences & Ecology, AMSR-E, SMAP, MICROWAVE EMISSION, PRODUCTS, Remote Sensing, RETRIEVAL ALGORITHMS, L-VOD, [SDE]Environmental Sciences, EFFECTIVE SCATTERING ALBEDO, Vegetation optical depth, Soil moisture, Biomass, Imaging Science & Photographic Technology, SMOS-IC, Life Sciences & Biomedicine, Environmental Sciences, SATELLITE, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography
Abstract

Passive microwave remote sensing observations at L-band provide key and global information on surface soil moisture and vegetation water content, which are related to the Earth water and carbon cycles. Only two space-borne L-band sensors are currently operating: SMOS, launched end of 2009 and thus providing now a 10-year global data set and SMAP, launched beginning of 2015. This study provides a state-of-the-art scientific overview of the SMOS-IC retrieval data set based on the SMOS L-band observations. This SMOS product aims at improved performance and independence of auxiliary data, key features for robust applications. The SMOS-IC product includes both a soil moisture (SM) and a L-band vegetation optical depth (L-VOD) data set which are currently at the basis of several studies evaluating the impact of climate and anthropogenic activities on aboveground carbon stocks. Since the release of the first version, the algorithm has been significantly changed in support to key applications, but no document is available to report these changes. This paper fills this gap by analyzing key science questions related to the product development, reviewing application results and presenting an extensive description of the last version of the product (version 2) considering changes in comparison to the previous version (V105). For the future it is planned to merge the SMOS and SMAP L-VOD data sets to ensure L-VOD data continuity in the event of failure of one of the space-borne SMOS or SMAP sensors. ispartof: REMOTE SENSING OF ENVIRONMENT vol:254 status: published

Published
2021

4. Multivariable evaluation of land surface processes in forced and coupled modes reveals new error sources to the simulated water cycle in the IPSL (Institute Pierre Simon Laplace) climate model

Author

Mizuochi, Hiroki, primary, Ducharne, Agnès, additional, Cheruy, Frédérique, additional, Ghattas, Josefine, additional, Al-Yaari, Amen, additional, Wigneron, Jean-Pierre, additional, Bastrikov, Vladislav, additional, Peylin, Philippe, additional, Maignan, Fabienne, additional, and Vuichard, Nicolas, additional

Published
2021
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6. Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review

Author

Frappart, Frédéric, primary, Wigneron, Jean-Pierre, additional, Li, Xiaojun, additional, Liu, Xiangzhuo, additional, Al-Yaari, Amen, additional, Fan, Lei, additional, Wang, Mengjia, additional, Moisy, Christophe, additional, Le Masson, Erwan, additional, Aoulad Lafkih, Zacharie, additional, Vallé, Clément, additional, Ygorra, Bertrand, additional, and Baghdadi, Nicolas, additional

Published
2020
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7. An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets:high sensitivity of L-VOD to above-ground biomass in Africa

Author

Rodríguez-Fernández, Nemesio J., Mialon, Arnaud, Mermoz, Stephane, Bouvet, Alexandre, Richaume, Philippe, Al Bitar, Ahmad, Al-Yaari, Amen, Brandt, Martin Stefan, Kaminski, Thomas, Le Toan, Thuy, Kerr, Yann H., and Wigneron, Jean-Pierre

Abstract

The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (~ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass.

Published
2018

8. Le nouveau produit Smos-IC : humidité du sol et indice de végétation L-VOD

Author

Wigneron, Jean-Pierre, Mialon, Arnaud, Al-Yaari, Amen, Kerr, Yann H., Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
[SDV]Life Sciences [q-bio], ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2018

9. SMOS-IC: an alternative SMOS soil moisture and 3 vegetation optical depth product

Author

Fernandez-Moran, Roberto, Al-Yaari, Amen, Mialon, Arnaud, Mahmoodi, Ali, Al Bitar, Ahmad, De Lannoy, Gabrielle, López-Baeza, Ernesto, Kerr, Yann, and Wigneron, Jean-Pierre

Subjects
SMOS, L-band, Level 3, ECMWF, SMOS-IC, soil moisture, vegetation optical depth, MODIS, NDVI
Abstract

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 which was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). This SMOS-INRA-CESBIO (SMOS-IC) product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated to the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary data sets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A 6 year (2010-2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and of the northern mid-latitudes.

Published
2017

10. Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index (Correction)

Author

Yao, Panpan, Shi, Jiancheng, Zhao, Tianjie, Lu, Hui, Al Yaari, Amen, University of Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences [Changchun Branch] (CAS), The Joint Center for Global Change Studies, Interactions Sol Plante Atmosphère (ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de la Recherche Agronomique (INRA), Interactions Sol Plante Atmosphère (UMR ISPA), and Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)

Subjects
analyse de données, remote sensing, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, data analysis, Signal and Image processing, Traitement du signal et de l'image, indice de végétation, Milieux et Changements globaux, radiometer, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Physics::Geophysics
Abstract

Correction de l'article : "Rebuilding Long Time Series Global Soil Moisture Products Using the Neural Network Adopted the Microwave Vegetation Index" (Remote Sensing, vol 9, pg 35, 2017); Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index (Correction)

Published
2017

11. An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets: high sensitivity of L-VOD to above-ground biomass in Africa

Author

Rodríguez-Fernández, Nemesio J., primary, Mialon, Arnaud, additional, Mermoz, Stephane, additional, Bouvet, Alexandre, additional, Richaume, Philippe, additional, Al Bitar, Ahmad, additional, Al-Yaari, Amen, additional, Brandt, Martin, additional, Kaminski, Thomas, additional, Le Toan, Thuy, additional, Kerr, Yann H., additional, and Wigneron, Jean-Pierre, additional

Published
2018
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12. Satellite‐Observed Major Greening and Biomass Increase in South China Karst During Recent Decade

Author

Brandt, Martin, primary, Yue, Yuemin, additional, Wigneron, Jean Pierre, additional, Tong, Xiaowei, additional, Tian, Feng, additional, Jepsen, Martin Rudbeck, additional, Xiao, Xiangming, additional, Verger, Aleixandre, additional, Mialon, Arnaud, additional, Al‐Yaari, Amen, additional, Wang, Kelin, additional, and Fensholt, Rasmus, additional

Published
2018
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16. The global SMOS Level 3 daily soil moisture and brightness temperature maps

Author

Al Bitar, Ahmad, primary, Mialon, Arnaud, additional, Kerr, Yann H., additional, Cabot, François, additional, Richaume, Philippe, additional, Jacquette, Elsa, additional, Quesney, Arnaud, additional, Mahmoodi, Ali, additional, Tarot, Stéphane, additional, Parrens, Marie, additional, Al-Yaari, Amen, additional, Pellarin, Thierry, additional, Rodriguez-Fernandez, Nemesio, additional, and Wigneron, Jean-Pierre, additional

Published
2017
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19. Eleven-years of an homogeneous soil moisture dataset from AMSR-E and SMOS observations

Author

Rodriguez-Fernandez, Nemesio, Kerr, Yann, Wigneron, Jean-Pierre, Al Yaari, Amen, De Jeu, Richard, Van der Schalie, Robin, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Faculty of Earth and Life Sciences, VU University, ESRIN, European Space Agency (ESA), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Interactions Sol Plante Atmosphère (UMR ISPA), Vrije Universiteit Amsterdam [Amsterdam] (VU), ESA Centre for Earth Observation (ESRIN), Agence Spatiale Européenne = European Space Agency (ESA), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), VU University Amsterdam, and Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU)

Subjects
analyse de données, remote sensing, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, data analysis, Signal and Image processing, Traitement du signal et de l'image, Milieux et Changements globaux, donnée satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

Eleven-years of an homogeneous soil moisture dataset from AMSR-E and SMOS observations. 2015 International Geoscience and Remote Sensing Symposium IGARSS

Published
2015

20. Long time series of soil moisture obtained using neural networks : application to AMSR-E and SMOS

Author

Rodriguez‐Fernandez, Nemesio, Kerr, Yann H., De Jeu, Richard, Van der Schalie, Robin, Wigneron, Jean-Pierre, Al-Yaari, Amen, Dolman, Han, Drusch, Matthias, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Geosciences Union (EGU). DEU., Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Vrije Universiteit Amsterdam [Amsterdam] (VU), Agence Spatiale Européenne = European Space Agency (ESA), and VU University Amsterdam

Subjects
analyse de données, télédétection par satellite, capteur smos, Signal and Image processing, Earth Sciences, Traitement du signal et de l'image, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Sciences de la Terre, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

21. Global SMOS soil moisture retrievals using the land parameter retrieval model

Author

Van der Schalie, Robin, De Jeu, Richard, Kerr, Yann H., Wigneron, Jean-Pierre, Rodriguez‐Fernandez, Nemesio, Al-Yaari, Amen, Drusch, Matthias, Mecklenburg, Susanne, Dolman, Han, VU University Amsterdam, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Geosciences Union (EGU). DEU., Vrije Universiteit Amsterdam [Amsterdam] (VU), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agence Spatiale Européenne = European Space Agency (ESA), and Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU)

Subjects
capteur smos, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, Earth Sciences, Signal and Image processing, Traitement du signal et de l'image, humidité du sol, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Milieux et Changements globaux, donnée satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Sciences de la Terre, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

22. The integration of SMOS soil moisture in a consistent soil moisture climate record

Author

de Jeu, Richard, Wigneron, Jean-Pierre, Rodriguez‐fernandez, Nemesio, Al-Yaari, Amen, van Der Schalie, Robin, Dolman, Han, Drusch, Matthias, Mecklenburg, Susanne, VU University Amsterdam, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), European Geosciences Union (EGU). DEU., Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Vrije Universiteit Amsterdam [Amsterdam] (VU), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Agence Spatiale Européenne = European Space Agency (ESA)

Subjects
[SPI.ELEC]Engineering Sciences [physics]/Electromagnetism, Electromagnetism, [SDE.MCG]Environmental Sciences/Global Changes, capteur smos, télédétection par satellite, Signal and Image processing, Traitement du signal et de l'image, humidité du sol, Electromagnétisme, Milieux et Changements globaux, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, donnée satellite, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2015

23. A radiative transfer based approach to merge SMOS and AMSR‐e soil moisture retrievals into one consistent record

Author

Van der Schalie, Robin, De Jeu, Richard, Kerr, Yann, Wigneron, Jean-Pierre, Rodriguez‐Fernandez, Nemesio, Al Yaari, Amen, Drusch, Matthias, Mecklenburg, Susanne, Dolman, Han, University of Amsterdam [Amsterdam] (UvA), Transmissivity, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), European Space Research Institute (ESRIN). ITA., Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Agence Spatiale Européenne = European Space Agency (ESA)

Subjects
analyse de données, [SDV]Life Sciences [q-bio], télédétection, projet smos, transfert radiatif, humidité du sol, donnée satellite
Abstract

In 2010 Soil moisture was recognized as an Essential Climate Variable (ECV) by the Global Climate Observation System (GCOS) and in the same year ESA started the development of a consistent, long‐term, multi‐sensor time series of satellite derived soil moisture. First as part of the Water Cycle Observation Multi‐mission Strategy (WACMOS) and later as a part of the Climate Change Initiative (CCI) program. In 2014,a one year project was initiated by ESA to provide guidelines for the inclusion of soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) sensor. With this project testing three different fusion methods were be included; one based on a neural network approach (Rodriguez‐Fernandez et al., 2014), one based on a linear regression approach (Wigneron et al., 2004) and one based on the CCI soil moisture baseline algorithm, the Land Parameter Retrieval Model (LPRM, Owe et al., 2008). This study focused on the last method. The LPRM was applied to the SMOS observations by optimizing the single scattering albedo and roughness, against two different modelled soil moisture products (MERRA and ERA‐Land) , comparison against SMOS networks from the international soil moisture network over the period of July 2010 to December 2013 (Van der Schalie et al., 2015). The comparison against SMOS Level 3 soil moisture reached correlations of over 0.9 for the continents that are mostly free of radio frequency interference. Then AMSR‐E and SMOS retrievals were combined by updating the AMSR‐E LPRM and optimizing its parameters to best match the SMOS LPRM retrievals. Other updates included an improved approach to estimate the effective temperature at C‐band. The resulting AMSR‐E LPRM retrievals were evaluated against MERRA and ERA‐Land and validated against available In Situ networks and revealed a lower RMSE as compared to the original AMSR‐E LPRM v5 products while still having high correlations with the mentioned datasets.

Published
2015

24. Global map of soil roughness using L-band SMOS data

Author

Parrens, Marie, Wigneron, Jean-Pierre, Richaume, Philippe, Ahmad, Al Bitar, Mialon, Arnaud, Wang, Shu, Fernandez-Moran, Roberto, Al-Yaari, Amen, Kerr, Yann H., Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Geosciences Union (EGU). DEU., Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
analyse de données, capteur smos, télédétection par satellite, Earth Sciences, Signal and Image processing, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Traitement du signal et de l'image, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS, Sciences de la Terre
Abstract

International audience

Published
2015

25. Long time series of soil moisture retrieved from AMSR‐E and SMOS Observations

Author

Rodriguez‐Fernandez, Nemesio, Kerr, Yann H., Van der Schalie, Robin, De Jeu, Richard, Wigneron, Jean-Pierre, Al Yaari, Amen, Richaume, Philippe, Drusch, Matthias, Mecklenburg, Susanne, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), University of Amsterdam [Amsterdam] (UvA), Interactions Sol Plante Atmosphère (ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), European Space Research and Technology Centre (ESTEC), European Space Agency (ESA), ESA Centre for Earth Observation (ESRIN), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), and European Space Research Institute (ESRIN). ITA.

Subjects
analyse de données, télédétection par satellite, Signal and Image processing, Traitement du signal et de l'image, projet smos, régression non linéaire, variable climatique, radiomètre, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

Introduction: Soil moisture (SM) represents less than 1/10000 of the total water of our planet but it plays an important role as it affects the water and energy exchanges at the land surface/atmosphere interface and it is the reservoir of water for agriculture and vegetation in general. SM has been endorsed by the Global Climate Observing System (GCOS) as an Essential Climate Variable. In order to use SM information for climate modeling, SM datasets spanning long time periods are needed. In the context of the European Space Agency (ESA) Climate Change Initiative (CCI) several strategies have been evaluated to merge SM datasets from different microwave sensors (Owe et al. 2008). These strategies consist typically in merging a posteriori several SM datasets computed with different algorithms applied to data from different sensors. In addition, they do not include data from the Soil Moisture and Ocean Salinity (SMOS) satellite (Kerr et al. 2001), which is the first mission specifically designed to retrieve SM from space. Therefore, in the context of an ESA funded project, several approaches have been studied to add SMOS data to long term SM datasets. In a first phase, three different approaches are tested to merge ESA SMOS and NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR‐E). This paper is devoted to a method using statistical retrieval algorithms to compute a priori a long time dataset that is consistent along time by construction. Methods Rodriguez‐Fernandez et al. (2015) have shown the good performances of a SM retrieval from SMOS observations using neural networks trained with ECMWF numerical weather prediction models (Balsamo et al. 2009). In addition, the same approach but using SMOS L3 SM as reference has proven to be useful to develop a Near‐Real‐Time SM retrieval algorithm (Rodriguez‐Fernandez et al. this conference). This study uses both approaches to obtain larger SM time series adding AMSR‐E as input: i) Using a Land Surface model as reference, two neural networks algorithms have been defined and optimized using AMSR‐E or SMOS as input data in the periods 2003‐Oct 2011 and 2010‐2014, respectively. ii) An alternative approach which is independent of land surface models has also been studied. It consist in using SMOS L3 SM retrievals as reference to train a NN using as input AMSR‐E Tb's. Results The best input data to retrieve SM using ASMR‐E data as input is using the three lower frequency bands and two polarizations. Soil temperature and a vegetation index improve the ability of the NN to capture the SM variability of the ECMWF model simulations and SMOS L3 SM. The NN performances are higher when using Tb's as input instead of the polarization index ( PI =(Tb^V ‐ Tb^H)/(Tb^V + Tb^H) ) used by the LPRM algorithm (Owe et al. 2001) or other NNs algorithms (Santi et al. 2012). As shown in Rodriguez‐Fernandez et al. (2015) for the SMOS case, the performance of the NN using AMSR‐E as input data and trained with ECMWF SM simulations improves when using soil texture maps as input (clay and sand fractions). For instance when using the lowest frequency channel, R increases from 0.79 to 0.83. In contrast, when more Tb's measured at higher frequencies are added as input, the contribution of NDVI decreases. When using all the frequency bands, including the 89 GHz channel, the NDVI contribution is negligible and the correlation of NN SM and ECMWF SM is as high as 0.9 (only using AMSR‐E plus soil texture information as input). For comparison, the global score obtained using SMOS Tb's from 7 angle bins from 25deg to 65deg, soil texture and NDVI is R = 0.88 (NN SM with respect to ECMWF SM). In conclusion, both NNs using AMSR‐E or SMOS data as input exhibit similar performances to capture the SM variability in the ECMWF models. Discussion In order to check the consistency of the two NN SM datasets, the trained NNs have been applied to AMSR‐E and SMOS \Tb's in the period from June to September 2010, which has not been used for the training of the NNs. The two maps are very similar, probing that the produced SM is consistent using SMOS or AMSR‐E as input. In addition, the performances of the NN retrieved SM have been evaluated against more than 1100 measurements from in situ sensors in America, Europe, Africa and Australia in the 2003‐2013 period. Results show that, on average, remote sensing retrievals performances in Europe are below those of ERA‐Interim/Land and MERRA‐Land models. In contrast, the remote sensing retrievals performances with respect to in situ measurements in other locations are, on average, similar or better than those of the land surface models. Therefore, this is a promising method to compute long time series of SM that can be used for hydrological and climate application and it is the first step towards a longer dataset which will include additional sensors.

Published
2015

26. GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring

Author

Motte, Erwan, primary, Zribi, Mehrez, additional, Fanise, Pascal, additional, Egido, Alejandro, additional, Darrozes, José, additional, Al-Yaari, Amen, additional, Baghdadi, Nicolas, additional, Baup, Frédéric, additional, Dayau, Sylvia, additional, Fieuzal, Remy, additional, Frison, Pierre-Louis, additional, Guyon, Dominique, additional, and Wigneron, Jean-Pierre, additional

Published
2016
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27. Evaluation and intercomparison of SMOSL3, AMSR E-LPRM, SM-DAS-2, and ERA-Interim/land soil moisture products

Author

Al Yaari, Amen, Wigneron, Jean-Pierre, Ducharne, Agnès, Govind, Ajit, Moisy, Christophe, De Rosnay, Patricia, De Jeu, Richard, Albergel, Clément, Balsamo, Gianpaolo, Kerr, Yann H., Écologie fonctionnelle et physique de l'environnement (EPHYSE), Institut National de la Recherche Agronomique (INRA), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), European Centre for Medium-Range Weather Forecasts (ECMWF), Vrije Universiteit Amsterdam [Amsterdam] (VU), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), and VU University Amsterdam

Subjects
microonde passive, télédétection par satellite, modèle de transfert radiatif, Earth Sciences, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Sciences de la Terre, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2013

28. Evaluation and intercomparison of SMOSL3, CCI, AMSRE-LPRM, SM-DAS-2, and ERA-Interim/Land soil moisture products

Author

Al Yaari, Amen, Wigneron, Jean-Pierre, Ducharne, Agnès, Govind, Ajit, Moisy, C., De Rosnay, Patricia, De Jeu, Richard, Albergel, Clément, Balsamo, Gianpaolo, Kerr, Yann, Écologie fonctionnelle et physique de l'environnement (EPHYSE), Institut National de la Recherche Agronomique (INRA), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), European Centre for Medium-Range Weather Forecasts (ECMWF), VU University Amsterdam, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Vrije Universiteit Amsterdam [Amsterdam] (VU), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC), and Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU)

Subjects
analyse d'images, analyse de données, télédétection, [SDE.MCG]Environmental Sciences/Global Changes, satellite, Signal and Image processing, Traitement du signal et de l'image, Milieux et Changements globaux, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2013

29. Evaluation and intercomparison of SMOSL3, CCI, AMSR E-LPRM, SM-DAS-2, and ERA-Interim/Land soil moisture products

Author

Al Yaari, Amen, Wigneron, Jean-Pierre, Govind, Ajit, Ducharne, Agnès, Moisy, Christophe, De Rosnay, Patricia, De Jeu, Richard, Albergel, Clément, Balsamo, Gianpaolo, Kerr, Yann H., Écologie fonctionnelle et physique de l'environnement (EPHYSE), Institut National de la Recherche Agronomique (INRA), Université Pierre et Marie Curie - Paris 6 (UPMC), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), European Centre for Medium-Range Weather Forecasts (ECMWF), Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Space Agency (ESA). Frascati, ITA., École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)

Subjects
télédétection, [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, humidité du sol, projet smos, image satellite, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2013

30. The high sensitivity of SMOS L-Band vegetation optical depth to biomass.

Author

Rodríguez-Fernández, Nemesio J., Mialon, Arnaud, Mermoz, Stephane, Bouvet, Alexandre, Richaume, Philippe, Al Bitar, Ahmad, Thuy Le Toan, Kerr, Yann H., Al-Yaari, Amen, Wigneron, Jean-Pierre, Brandt, Martin, and Kaminski, Thomas

Subjects
VEGETATION dynamics, SENSITIVITY analysis, BIOMASS, OPTICAL depth (Astrophysics), SOIL moisture, SEAWATER salinity
Abstract

The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (~ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass. [ABSTRACT FROM AUTHOR]

Published
2018
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33. Rebuilding Long Time Series Global Soil Moisture Products Using the Neural Network Adopting the Microwave Vegetation Index.

Author

Panpan Yao, Jiancheng Shi, Tianjie Zhao, Hui Lu, and Al-Yaari, Amen

Subjects
BACK propagation, ARTIFICIAL neural networks, SOIL moisture, TIME series analysis, VEGETATION mapping
Abstract

This study presents a back propagation neural network (BPNN) method to rebuild a global and long-term soil moisture (SM) series, adopting the microwave vegetation index (MVI). The data used in our study include Soil Moisture and Ocean Salinity (SMOS) Level 3 soil moisture (SMOSL3sm) data, the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) Level 3 brightness temperature (TB) data and L3 SM products. The BPNNs on each grid were trained over July 2010-June 2011, and the entire year of 2013, with SMOSL3sm as a training target, and taking the reflectivities (Rs) of the C/X/Ku/Ka/Q bands, and the MVI from AMSR-E/AMSR2 TB data, as input, in which the MVI is used to correct for vegetation effects. The training accuracy of networks was evaluated by comparing soil moisture products produced using BPNNs (NNsm hereafter) with SMOSL3sm during the BPNN training period, in terms of correlation coefficient (CC), bias (Bias), and the root mean square error (RMSE). Good global results were obtained with CC = 0.67, RMSE = 0.055 m³/m³ and Bias = -0.0005 m³/m³, particularly over Australia, Central USA, and Central Asia. With these trained networks over each pixel, a global and long-term soil moisture time series, i.e., 2003-2015, was built using AMSR-E TB from 2003 to 2011 and AMSR2 TB from 2012 to 2015. Then, NNsm products were evaluated against in situ SM observations from all SCAN (Soil Climate Analysis Network) sites (SCANsm). The results show that NNsm has a good agreement with in situ data, and can capture the temporal dynamics of in situ SM, with CC = 0.52, RMSE = 0.84 m³/m³ and Bias = -0.002 m³/m³. We also evaluate the accuracy of NNsm by comparing with AMSR-E/AMSR2 SM products, with results of a regression method. As a conclusion, this study provides a promising BPNN method adopting MVI to rebuild a long-term SM time series, and this could provide useful insights for the future Water Cycle Observation Mission (WCOM). [ABSTRACT FROM AUTHOR]

Published
2017
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34. Application of the TDR Sensor and the Parameters of Injection Irrigation for the Estimation of Soil Evaporation Intensity.

Author

Walczak, Amadeusz, Lipiński, Mateusz, Janik, Grzegorz, Al-Yaari, Amen, and Adamchuk, Viacheslav

Subjects
TIME-domain reflectometry, IRRIGATION, SOIL horizons, SOILS
Abstract

The objective of the study was to develop a precise method of determination of the evaporation rate in a soil irrigated with the use of a mobile injection irrigation system. Two methods of constructing functions approximating the value of evaporation have been developed. In the first method, the domain comprises the parameters of injection irrigation, i.e., the dose and the depth of injection, and in the second, the volumetric moisture of soil in the layer immediately below the soil surface, which was measured with time-domain reflectometry (TDR) sensors. For that purpose, a laboratory experiment was carried out, based on 12 physical models. The study was conducted on a natural soil material, with particle size distribution of its mineral parts corresponding to that of a loamy sand soil. It was demonstrated that evaporation intensity increases with irrigation and decreases with increase in the depth of water application. Using TDR sensors, it was also shown that evaporation intensity increases proportionally to the weighted arithmetic mean of the volumetric moisture. Comparison of the two methods indicates that the evaporation intensity of injection-irrigated soil can be estimated with higher accuracy when the domain of the approximating function is the injection depth and dose than when the domain of the function is the weighted mean of volumetric moisture of the surface horizon of the soil. However, the method using TDR sensors for the estimation of evaporation intensity of an injection-irrigated soil has a greater potential for the construction of universal approximating models. In addition, the advantage of the method based on the use of TDR sensors is that it uses arguments for the approximating function, f 2 (θ ˜) , in real time. [ABSTRACT FROM AUTHOR]

Published
2021
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