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Challenges in flood modeling over data-scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco / El Mahdi El Khalk in Natural Hazards and Earth System Sciences, vol 20 n° 10 (October 2020)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 20 n° 10 (October 2020) . - pp 2591 - 2607 Titre : Challenges in flood modeling over data-scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco Type de document : Article/Communication Auteurs : El Mahdi El Khalk, Auteur ; Yves Tramblay, Auteur ; Christian Massari, Auteur Année de publication : 2020 Article en page(s) : pp 2591 - 2607 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Advanced scatterometer [Termes IGN] Atlas marocain [Termes IGN] bassin hydrographique [Termes IGN] crue [Termes IGN] humidité du sol [Termes IGN] image SMOS [Termes IGN] inondation [Termes IGN] Maroc [Termes IGN] modèle hydrographique [Termes IGN] modélisation [Termes IGN] variation saisonnière [Termes IGN] zone semi-aride Résumé : (auteur) The Mediterranean region is characterized by intense rainfall events giving rise to devastating floods. In Maghreb countries such as Morocco, there is a strong need for forecasting systems to reduce the impacts of floods. The development of such a system in the case of ungauged catchments is complicated, but remote-sensing products could overcome the lack of in situ measurements. The soil moisture content can strongly modulate the magnitude of flood events and consequently is a crucial parameter to take into account for flood modeling. In this study, different soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI; Soil Moisture and Ocean Salinity, SMOS; Soil Moisture and Ocean Salinity by the Institut National de la Recherche Agronomique and Centre d'Etudes Spatiales de la Biosphère, SMOS-IC; Advanced Scatterometer, ASCAT; and ERA5 reanalysis) are compared to in situ measurements and one continuous soil-moisture-accounting (SMA) model for basins located in the High Atlas Mountains, upstream of the city of Marrakech. The results show that the SMOS-IC satellite product and the ERA5 reanalysis are best correlated with observed soil moisture and with the SMA model outputs. The different soil moisture datasets were also compared to estimate the initial soil moisture condition for an event-based hydrological model based on the Soil Conservation Service curve number (SCS-CN). The ASCAT, SMOS-IC, and ERA5 products performed equally well in validation to simulate floods, outperforming daily in situ soil moisture measurements that may not be representative of the whole catchment soil moisture conditions. The results also indicated that the daily time step may not fully represent the saturation state before a flood event due to the rapid decay of soil moisture after rainfall in these semiarid environments. Indeed, at the hourly time step, ERA5 and in situ measurements were found to better represent the initial soil moisture conditions of the SCS-CN model by comparison with the daily time step. The results of this work could be used to implement efficient flood modeling and forecasting systems in semiarid regions where soil moisture measurements are lacking. Numéro de notice : A2020-610 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-20-2591-2020 date de publication en ligne : 05/10/2020 En ligne : https://doi.org/10.5194/nhess-20-2591-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95974 [article]

Using Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture / Ju Hyoung Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 2 (February 2020) . - pp 91 - 98 Titre : Using Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture Type de document : Article/Communication Auteurs : Ju Hyoung Lee, Auteur Année de publication : 2020 Article en page(s) : pp 91 - 98 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique occidentale [Termes IGN] données multitemporelles [Termes IGN] erreur moyenne quadratique [Termes IGN] erreur systématique [Termes IGN] humidité du sol [Termes IGN] image SMOS [Termes IGN] salinité Résumé : (Auteur) To mitigate instantaneously evolving biases in satellite retrievals, a stochastic approach is applied over West Africa. This stochastic approach independently self-corrects Soil Moisture Ocean Salinity (SMOS) wet biases, unlike the cumulative density function (CDF) matching that rescales satellite retrievals with respect to several years of reference data. Ranked probability skill score (RPSS) is used as nonlocal root-mean-square errors (RMSEs) to assess stochastic retrievals. Stochastic method successfully decreases RMSEs from 0.146 m3/m3 to 0.056 m3/m3 in the Republic of Benin and from 0.080 m3/m3 to 0.038 m3/m3 in Niger, while the CDF matching method exacerbates the original SMOS biases up to 0.141 m3/m3 in Niger, and 0.120 m3/m3 in Benin. Unlike the CDF matching or European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA))–interim soil moisture, only a stochastic retrieval responds to Tropical Rainfall Measuring Mission rainfall. Based on the effects of bias correction, RPSS is suggested as a nonlocal verification without needing local measurements. Numéro de notice : A2020-126 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.2.91 date de publication en ligne : 01/02/2020 En ligne : https://doi.org/10.14358/PERS.86.2.91 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94772 [article]

Improving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data / Ali Khazaal in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 1 (January 2019) . - pp 277 - 290 Titre : Improving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data Type de document : Article/Communication Auteurs : Ali Khazaal, Auteur ; Philippe Richaume, Auteur ; François Cabot, Auteur ; Eric Anterrieu, Auteur ; Arnaud Mialon, Auteur ; Yann H. Kerr, Auteur Année de publication : 2019 Article en page(s) : pp 277 - 290 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] correction d'image [Termes IGN] erreur systématique [Termes IGN] humidité du sol [Termes IGN] image SMOS [Termes IGN] résidu [Termes IGN] télédétection en hyperfréquence [Termes IGN] température de luminance Résumé : (Auteur) SMOS is a space mission led by the European Space Agency and designed to provide global maps of Soil Moisture and Ocean salinity, two important geophysical parameters for understanding the water cycle variations and climate change. The SMOS payload is a 2-D interferometer operating at L-band that consists of 69 elementary antennas located along a Y-shaped structure. Important spatial biases persist in the retrieved brightness temperature (BT) images mainly due to the phenomenon of aliasing inside the field of view of SMOS but also due to the Gibbs oscillations near land/ocean transitions. To minimize these biases, a differential image reconstruction algorithm is used in the operational processor that reduces the contrast of the image to be retrieved. To do that, the contribution of a constant artificial temperature map is removed from the measurements prior to reconstruction and then added back after the reconstruction. In this paper, we show that strong residual biases are still present in the retrieved images. To reduce them, we propose to improve the bias correction algorithm by using a more realistic artificial temperature scene based on separating the land and ocean regions and assigning a constant temperature over land and a Fresnel BT model over the ocean. The artificial scene is also improved by means of representing each pixel by its water fraction percentage to smooth the land/ocean transitions. The improved algorithm is validated over the ocean by comparing the retrieved temperatures to a forward geophysical model but also over land by comparing the retrieved soil moisture to in situ measurements. Numéro de notice : A2019-106 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2853619 date de publication en ligne : 09/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2853619 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92412 [article]

Sea surface salinity remote sensing / Emmanuel P. Dinnat (2019)  

Public Titre : Sea surface salinity remote sensing Type de document : Monographie Auteurs : Emmanuel P. Dinnat, Editeur scientifique ; Xiaobin Yin, Editeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 296 p. Format : 17 x 23 cm ISBN/ISSN/EAN : 978-3-03921-077-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Arctique, océan [Termes IGN] Atlantique (océan) [Termes IGN] bande L [Termes IGN] fusion de données [Termes IGN] HYbrid Coordinate Ocean Model [Termes IGN] image AQUARIUS [Termes IGN] image SMOS [Termes IGN] Indien (océan) [Termes IGN] Méditerranée, mer [Termes IGN] Mexique (golfe du) [Termes IGN] modèle de transfert radiatif [Termes IGN] océanographie [Termes IGN] Pacifique (océan) [Termes IGN] salinité [Termes IGN] Soil Moisture Active Passive [Termes IGN] surface de la mer Résumé : (éditeur) This Special Issue gathers papers reporting research on various aspects of remote sensing of Sea Surface Salinity (SSS) and the use of satellite SSS in oceanography. It includes contributions presenting improvements in empirical or theoretical radiative transfer models; mitigation techniques of external interference such as RFI and land contamination; comparisons and validation of remote sensing products with in situ observations; retrieval techniques for improved coastal SSS monitoring, high latitude SSS and the assessment of ocean interactions with the cryosphere; and data fusion techniques combining SSS with sea surface temperature (SST). New instrument technology for the future of SSS remote sensing is also presented. Note de contenu : 1- Status of Aquarius and salinity continuity 2- The salinity retrieval algorithms for the NASA Aquarius Version 5 and SMAP version3 releases 3- Assessment of Aquarius Sea surface salinity 4- Improving SMOS sea surface salinity in the Western Mediterranean Sea through multivariateand multifractal analysis 5- Seven Years of SMOS sea surface salinity at high latitudes: Variability in Arctic and Sub-Arctic region 6- Inter comparison of in-situ and remote sensing salinity products in the Gulf of Mexico, a river-influenced system 7- Remote sensing of sea surface salinity: Comparison of satellite and in situ observations and impact of retrieval parameters 8- An observational perspective of sea surface salinity in the Southwestern Indian Ocean and its role in the South Asia summer monsoon 9- The potential and challenges of using soil moisture active passive (SMAP) sea surface salinity to monitor Arctic Ocean freshwater changes 10- Assessing coastal SMAP surface salinity accuracy and its application to monitoring Gulf of Maine circulation dynamics 11- SMAP and CalCOFI observe freshening during the 2014–2016 Northeast Pacific warm anomaly 12- Seasonal variability of retroflection structures and transports in the Atlantic Ocean as Inferred from satellite-derived salinity maps 13- Comparison of the retrieval of sea surface salinity using different instrument configurations of MICAP 14- End-to-End simulation of WCOM IMI sea surface salinity retrieval Numéro de notice : 28541 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03921-077-0 En ligne : https://doi.org/10.3390/books978-3-03921-077-0 Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97393

Assimilation of SMOS retrievals in the land information system / Clay B. Blankenship in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 11 (November 2016) . - pp 6320 - 6332 Titre : Assimilation of SMOS retrievals in the land information system Type de document : Article/Communication Auteurs : Clay B. Blankenship, Auteur ; Jonathan L. Case, Auteur ; Bradley T. Zavodsky, Auteur ; William L. Crosson, Auteur Année de publication : 2016 Article en page(s) : pp 6320 - 6332 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] carte de la végétation [Termes IGN] Etats-Unis [Termes IGN] filtre de Kalman [Termes IGN] humidité du sol [Termes IGN] image radar [Termes IGN] image SMOS [Termes IGN] modèle numérique de surface [Termes IGN] radiométrie [Termes IGN] système d'information foncière Résumé : (Auteur) The Soil Moisture and Ocean Salinity (SMOS) satellite provides retrievals of soil moisture in roughly the upper 5 cm with a 30-50-km resolution and a mission accuracy requirement of 0.04 cm3/cm-3. These observations can be used to improve land surface model (LSM) soil moisture states through data assimilation (DA). In this paper, SMOS soil moisture retrievals are assimilated into the Noah LSM via an Ensemble Kalman Filter within the National Aeronautics and Space Administration Land Information System. Bias correction is implemented using cumulative distribution function (cdf) matching, with points aggregated by either land cover or soil type to reduce the sampling error in generating the cdfs. An experiment was run for the warm season of 2011 to test SMOS DA and to compare assimilation methods. Verification of soil moisture analyses in the 0-10-cm upper layer and the 0-1-m root zone was conducted using in situ measurements from several observing networks in central and southeastern United States. This experiment showed that SMOS DA significantly increased the anomaly correlation of Noah soil moisture with station measurements from 0.45 to 0.57 in the 0-10-cm layer. Time series at specific stations demonstrates the ability of SMOS DA to increase the dynamic range of soil moisture in a manner consistent with station measurements. Among the bias correction methods, the correction based on soil type performed best at bias reduction but also reduced correlations. The vegetation-based correction did not produce any significant differences compared with using a simple uniform correction curve. Numéro de notice : A2016-913 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2016.2579604 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83135 [article]

A comparative analysis of low-level radio frequency interference in SMOS and Aquarius microwave radiometer measurements / Mustafa Aksoy in IEEE Transactions on geoscience and remote sensing, vol 51 n° 10 (October 2013)  

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The soil moisture and ocean salinity (SMOS) mission: first results and achievements / Yann H. Kerr in Revue Française de Photogrammétrie et de Télédétection, n° 200 (Novembre 2012)

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Kalideos OSR MiPy : un observatoire pour la recherche et la démonstration des applications de la télédétection à la gestion des territoires / J.F. Dejoux in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)

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ESA's Soil Moisture and Ocean Salinity mission : mission performance and operations / S. Mecklenburg in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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Evaluation of SMOS soil moisture products over continental U.S. using the SCAN/SNOTEL network / A. Al Bitar in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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A first set of techniques to detect radio frequency interferences and mitigate their impact on SMOS data / R. Castro in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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Overview of the first SMOS sea surface salinity products. Part 1: quality assessment for the second half of 2010 / N. Reul in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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Validation of the SMOS L2 soil moisture data in the REMEDHUS network (Spain) / N. Sanchez in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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