Assessment of Surface Fractional Water Impacts on SMAP Soil Moisture Retrieval

Jinyang Du, John S. Kimball, Steven K. Chan, Mario Julian Chaubell, Rajat Bindlish, R. Scott Dunbar, Andreas Colliander

Research output: Contribution to journalArticlepeer-review

Abstract

Fractional water (FW) correction of satellite microwave brightness temperature (Tb) observations is a prerequisite for accurate soil moisture (SM) mapping over mixed land and water areas. Here, we evaluated the FW impacts on NASA Soil Moisture Active Passive (SMAP) L-band (1.4 GHz) SM retrievals using two water masks including (a) the NASA Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Land Water Mask version 6 (MOD44W) multi-year (2015-2019) water record and (b) the Ocean Discipline Processing System (ODPS) water mask previously used for SMAP global operational Tb and SM processing. The MOD44W and ODPS data were first compared with the European Commission's Joint Research Centre (JRC) Landsat-based water record. MOD44W showed major improvements in land/water classifications relative to the ODPS, with producer accuracy increasing from 50.02% to 95.02%, and user accuracy from 53.93% to 91.73% for water pixels. For assessing the FW impacts on SM retrievals, the same single channel V-polarization (SCA-V) algorithm was applied to SMAP Tb datasets corrected using ODPS and MOD44W water masks separately. MOD44W showed overall greater FW values (mean increase of 0.006) relative to the ODPS, leading to relatively drier SM retrievals (mean decrease: -0.012 m3/m3). Additional comparisons with globally distributed SM measurements confirmed consistently lower SM retrieval biases (mean decrease 0.04 m3/m3) and higher correlations (mean increase 0.06) of the MOD44W-based results relative to those based on the ODPS. Our results revealed non-negligible SM retrieval uncertainty introduced from the underlying ancillary FW data for areas with substantial water presence (e.g. FW>0.01).

Original languageEnglish
Pages (from-to)4871-4881
Number of pages11
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume16
DOIs
StatePublished - 2023

Keywords

  • Landsat
  • moderate resolution imaging spectroradiometer (MODIS)
  • soil moisture
  • soil moisture active passive (SMAP)
  • water fraction

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