A new SMAP soil moisture and vegetation optical depth product (SMAP-IB): Algorithm, assessment and inter-comparison

Xiaojun Li, Jean Pierre Wigneron, Lei Fan, Frédéric Frappart, Simon H. Yueh, Andreas Colliander, Ardeshir Ebtehaj, Lun Gao, Roberto Fernandez-Moran, Xiangzhuo Liu, Mengjia Wang, Hongliang Ma, Christophe Moisy, Philippe Ciais

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43 Scopus citations

Abstract

Passive microwave remote sensing at L-band (1.4 GHz) provides an unprecedented opportunity to estimate global surface soil moisture (SM) and vegetation water content (via the vegetation optical depth, VOD), which are essential to monitor the Earth water and carbon cycles. Currently, only two space-borne L-band radiometer missions are operating: the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) missions in orbit since 2009 and 2015, respectively. This study presents a new mono-angle retrieval algorithm (called SMAP-INRAE-BORDEAUX, hereafter SMAP-IB) of SM and L-band VOD (L-VOD) from the dual-channel SMAP radiometric observations. The retrievals are based on the L-MEB (L-band Microwave Emission of the Biosphere) model which is the forward model of SMOS-IC and of the official SMOS retrieval algorithms. The SMAP-IB product aims at providing good performances for both SM and L-VOD while remaining independent of auxiliary data: neither modelled SM data nor optical vegetation indices are used as input in the algorithm. Inter-comparison with other SM and L-VOD products (i.e., MT-DCA, SMOS-IC, and the new versions of DCA and SCA-V extracted from SMAP passive Level 3 product) suggested that SMAP-IB performed well for both SM and L-VOD. In particular, SMAP-IB SM retrievals presented the higher scores (R = 0.74) in capturing the temporal trends of in-situ observations from ISMN (International Soil Moisture Network) during April 2015–March 2019, followed by MT-DCA (R = 0.71). While the lowest ubRMSD value was obtained by the new version of SMAP DCA (0.056 m3/m3), SMAP-IB SM retrievals presented best scores for R, ubRMSD (~ 0.058 m3/m3) and bias (0.002 m3/m3) when considering only products independent of optical vegetation indices (e.g., NDVI). L-VOD retrievals from SMAP-IB, MT-DCA, and SMOS-IC were well correlated (spatially) with aboveground biomass and tree height, with spatial R values of ~0.88 and ~ 0.90, respectively. All three L-VOD products exhibited a smooth non-linear density distribution with biomass and a good linear relationship with tree height, especially at high biomass levels, while the L-VOD datasets incorporating optical information in the algorithms (i.e., SCA-V and DCA) showed obvious saturation effects. It is expected that this new algorithm can facilitate the fusion of both SM and L-VOD retrievals from SMOS and SMAP to obtain long-term and continuous L-band earth observation products.

Original languageEnglish (US)
Article number112921
JournalRemote Sensing of Environment
Volume271
DOIs
StatePublished - Mar 15 2022

Bibliographical note

Funding Information:
This study was jointly funded by CNES, France (Centre National d'Etudes Spatiales), the China Scholarship Council (201804910838) and the National Natural Science Foundation of China (Grant No.42171339). A partial contribution to this work was made at Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration. Ardeshir Ebtehaj's effort was supported by an award from the NASA's Remote Sensing Theory Program (80NSSC20K1717).

Funding Information:
This study was jointly funded by CNES , France ( Centre National d'Etudes Spatiales ), the China Scholarship Council ( 201804910838 ) and the National Natural Science Foundation of China (Grant No. 42171339 ). A partial contribution to this work was made at Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration. Ardeshir Ebtehaj's effort was supported by an award from the NASA’s Remote Sensing Theory Program ( 80NSSC20K1717 ).

Publisher Copyright:
© 2022 The Authors

Keywords

  • Biomass
  • Evaluation
  • L-MEB
  • SMAP
  • SMAP-IB
  • Soil moisture
  • Vegetation optical depth

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