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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 descripteurs IGN] Afrique occidentale [Termes descripteurs IGN] données multitemporelles [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image SMOS [Termes descripteurs 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 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 descripteurs IGN] correction d'image [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image SMOS [Termes descripteurs IGN] résidu [Termes descripteurs IGN] télédétection en hyperfréquence [Termes descripteurs 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 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]

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 descripteurs IGN] carte de la végétation [Termes descripteurs IGN] Etats-Unis [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image radar [Termes descripteurs IGN] image SMOS [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] radiométrie [Termes descripteurs 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 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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 10 (October 2013) . - pp 4983 - 4992 Titre : A comparative analysis of low-level radio frequency interference in SMOS and Aquarius microwave radiometer measurements Type de document : Article/Communication Auteurs : Mustafa Aksoy, Auteur ; Joel T. Johnson, Auteur Année de publication : 2013 Article en page(s) : pp 4983 - 4992 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] image AQUARIUS [Termes descripteurs IGN] image SMOS [Termes descripteurs IGN] interférence [Termes descripteurs IGN] polarimétrie radar [Termes descripteurs IGN] télédétection en hyperfréquence [Termes descripteurs IGN] température de luminance Résumé : (Auteur) Measurements of both the Soil Moisture and Ocean Salinity (SMOS) and Aquarius L-band microwave radiometers show a significant presence of radio frequency interference (RFI), although they operate in a protected frequency band where transmission is prohibited. RFI detection and mitigation remain a challenging problem for both missions, especially for low or moderate (i.e., on the order of 10 K or less) amplitude contributions. An algorithm for low-level source detection and mitigation is already included in Aquarius data sets, and both Aquarius and SMOS have distinct attributes that can potentially enable further improvements in detection and mitigation of these sources to some degree. The combination of SMOS and Aquarius data sets may enable further future improvements as well. Initial efforts toward this goal are reported in this paper. Similarities and differences in RFI effects on SMOS and Aquarius are examined, with a particular focus on instrument properties that cause differences in received RFI power in SMOS and Aquarius observations of a specific source. A study is also performed of SMOS observations for regions reported by Aquarius to contain “low-level” RFI. It is shown that the detection of these sources in the SMOS data set is challenging and that the dependence of the SMOS third and fourth Stokes parameters on incidence angle makes the polarimetric features of SMOS difficult to utilize for low-level source detection. However, an angular fitting procedure suggested previously in the literature can, in some cases, detect such sources in horizontal and vertical polarizations. Numéro de notice : A2013-602 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2266278 En ligne : https://doi.org/10.1109/TGRS.2013.2266278 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32738 [article]

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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)

Public [article]  inRevue Française de Photogrammétrie et de Télédétection > n° 200 (Novembre 2012) . - pp 12 - 19 Titre : The soil moisture and ocean salinity (SMOS) mission: first results and achievements Type de document : Article/Communication Auteurs : Yann H. Kerr, Auteur ; P. Waldteufel, Auteur ; J. Wigneron, Auteur ; J. Boutin, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 12 - 19 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Missions spatiales [Termes descripteurs IGN] aérosol [Termes descripteurs IGN] bande L [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] hydrosphère [Termes descripteurs IGN] image SMOS [Termes descripteurs IGN] océanographie spatiale [Termes descripteurs IGN] salinité Résumé : (Auteur) The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to providing soil moisture over continental surface (with an accuracy goal of 0.04 nf/nf) and ocean salinity (with a goal of 0.1 psu). These two geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge is of interest at global scales for climatic and weather research in particular for improving model forecasts. But it also has impact on various domains, ranging from hurricane monitoring to water resource management. The first six months after the launch, the so called commissioning phase, was dedicated to testing the functionalities of the spacecraft, the instrument and the ground segment including data processing. This phase was successfully completed in May 2010, and SMOS has since been in the routine operation phase, providing data products for the scientific community for over two years. The instrument performance and data quality fit the specifications. However, radio frequency interferences have been detected over large parts of Europe, China, Southern Asia, and the Middle East. The generation of Level 2 soil moisture and ocean salinity data is an on-going activity with continuously improved processings. Numéro de notice : A2012-563 Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32009 [article]

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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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