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An RFI-suppressed SMOS L-band multi-angular brightness temperature dataset spanning over a decade (since 2010).
Peng, Zhiqing; Zhao, Tianjie; Shi, Jiancheng; Kerr, Yann H; Rodríguez-Fernández, Nemesio J; Yao, Panpan; Che, Tao.
Afiliação
  • Peng Z; State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China.
  • Zhao T; University of Chinese Academy of Sciences, Beijing, 100049, China.
  • Shi J; State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China. zhaotj@aircas.ac.cn.
  • Kerr YH; National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China. shijiancheng@nssc.ac.cn.
  • Rodríguez-Fernández NJ; Centre d'Etudes Spatiales de la Biosphère (CESBIO), Université de Toulouse, Centre National d'Etudes Spatiales (CNES), Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Dévelopement (IRD), Institut national de recherche pour l'agriculture, l'alimentation et l'environ
  • Yao P; Centre d'Etudes Spatiales de la Biosphère (CESBIO), Université de Toulouse, Centre National d'Etudes Spatiales (CNES), Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Dévelopement (IRD), Institut national de recherche pour l'agriculture, l'alimentation et l'environ
  • Che T; State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100101, China.
Sci Data ; 10(1): 599, 2023 09 08.
Article em En | MEDLINE | ID: mdl-37684228
ABSTRACT
The Soil Moisture Ocean Salinity (SMOS) was the first mission providing L-band multi-angular brightness temperature (TB) at the global scale. However, radio frequency interferences (RFI) and aliasing effects degrade, when present SMOS TBs, and thus affect the retrieval of land parameters. To alleviate this, a refined SMOS multi-angular TB dataset was generated based on a two-step regression approach. This approach smooths the TBs and reconstructs data at the incidence angle with large TB uncertainties. Compared with Centre Aval de Traitement des Données SMOS (CATDS) TB product, this dataset shows a better relationship with the Soil Moisture Active Passive (SMAP) TB and enhanced correlation with in-situ measured soil moisture. This RFI-suppressed SMOS TB dataset, spanning more than a decade (since 2010), is expected to provide opportunities for better retrieval of land parameters and scientific applications.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article