干旱区研究

Arid Zone Research >

2023 , Vol. 40 >Issue 4: 583 - 593

DOI: https://doi.org/10.13866/j.azr.2023.04.07

Land and Water Resources

Downscaling analysis of SMAP soil moisture products in Gurbantunggut Desert

  • Zhixuan XUE ,
  • Li ZHANG ,
  • Xinjun WANG ,
  • Yongkang LI ,
  • Guanhong ZHANG ,
  • Peiyao LI
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  • 1. College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China
    2. Xinjiang Soil and Plant Ecological Process Laboratory, Urumqi 830052, Xinjiang, China

Received date: 2022-06-29

  Revised date: 2023-01-05

  Online published: 2023-04-28

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Abstract

The low spatial resolution of SMAP products limits its applicability to sparsely vegetated arid regions and deserts with high surface heterogeneity. Considering the special environmental characteristics of sparsely vegetated desert areas in arid regions, traditional downscaling methods such as land surface temperature (LST), normalized difference vegetation index (NDVI), and digital elevation model (DEM) have been used, among others. Based on the scale factor, the enhanced modified soil-adjusted vegetation index (Enhanced Modified Soil-Adjusted Vegetation Index, EMSAVI) and the ratio sand brightness index (RSBI), which are more correlated with the desert surface soil moisture, were added to reflect the study area. For the downscaling factors of vegetation coverage and bare sand distribution, the random forest (RF) algorithm was used to build a soil moisture downscaling model in arid areas. The results showed the following: (1) Correlation analysis showed that EMSAVI (rdry = -0.37, rwet = -0.34) and RSBI (rdry = -0.42, rwet = -0.25) were good indicators of desert soil moisture, being superior to NDVI (rdry = -0.21, rwet = 0.08). (2) The importance of EMSAVI and NDVI was 18.7% and 13.2%, respectively, and EMSAVI contributed more to the construction of the downscaling model. (3) The results obtained from the soil moisture downscaling model in dry and wet season arid regions and R2 of the SMAP product reached 0.916 and 0.910, and the RMSE reached 0.0075 cm3·cm-3 and 0.0063 cm3·cm-3, respectively, which are lower than the RMSE of the traditional model of 0.0013 cm3·cm-3. (4) By calculating the difference (LBPC) of LBP (local binary patterns) to evaluate the spatial consistency, the result of the newly constructed downscaling model (0.0585) was better than that of traditional downscaling (0.0645). This research shows that introduction of the short-wave infrared band into the EMSAVI established by the vegetation index enables its better application to the study of soil moisture downscaling in sparsely vegetated desert areas in arid regions.

Key words： soil moisture; random forest; SMAP; downscaling; Gurbantunggut Desert

Cite this article

Zhixuan XUE , Li ZHANG , Xinjun WANG , Yongkang LI , Guanhong ZHANG , Peiyao LI . Downscaling analysis of SMAP soil moisture products in Gurbantunggut Desert[J]. Arid Zone Research, 2023 , 40(4) : 583 -593 . DOI: 10.13866/j.azr.2023.04.07

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