古尔班通古特沙漠SMAP土壤水分产品降尺度分析

doi:10.13866/j.azr.2023.04.07

Abstract

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 (r_dry = -0.37, r_wet = -0.34) and RSBI (r_dry = -0.42, r_wet = -0.25) were good indicators of desert soil moisture, being superior to NDVI (r_dry = -0.21, r_wet = 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^-3and 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 (LBP_C) 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

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

Figures/Tables 7

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	降尺度因子	湿季	干季
传统降尺度因子	NDVI	0.08	-0.21^**
	DEM	0.07	-0.59^**
新增降尺度因子	LST	-0.31^**	-0.47^**
	RSBI	-0.25^**	-0.42^**
	EMSAVI	-0.34^**	-0.37^**

	湿季	干季
LBP_C-o	0.065	0.067
LBP_C-n	0.057	0.060

Downscaling analysis of SMAP soil moisture products in Gurbantunggut Desert

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