Enhanced Surface Soil Moisture Retrieval at High Spatial Resolution From the Integration of Satellite Observations and Soil Pedotransfer Functions

文献类型： 外文期刊

第一作者： Leng, Pei

作者： Leng, Pei;Li, Zhao-Liang;Geng, Yun-Jing;Yan, Qiu-Yu;Liao, Qian-Yu;Zhang, Xia;Shang, Guo-Fei

作者机构：

关键词： Soil; Remote sensing; Earth; Artificial satellites; Hydraulic systems; Soil measurements; Spatial resolution; Soil hydraulic characteristics; soil pedotransfer functions (PTF); surface soil moisture (SSM); trapezoid method

期刊名称：IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING （ 影响因子：8.125； 五年影响因子：8.137 ）

ISSN： 0196-2892

年卷期： 2022 年 60 卷

页码：

收录情况： SCI

摘要： Trapezoidal configurations constituted by land surface temperature and fractional vegetation cover have been frequently used to estimate surface soil moisture (SSM). Determination of the SSM status over the trapezoidal dry and wet edges is required to decouple the volumetric SSM content from the trapezoid-derived M0 because of the coupling of volumetric SSM content and soil texture (i.e., soil moisture availability, $M_{0}$ ). Currently, soil hydraulic characteristics generated from soil pedotransfer functions (PTFs) provide a preferred solution for describing the SSM status over trapezoidal dry and wet edges; however, most PTFs have been developed from laboratory-based soil measurements that have not been fully integrated into remote sensing models for SSM retrieval. This study investigated a practical calibration approach for PTF-derived soil hydraulic characteristics to enhance SSM retrieval using these trapezoidal configurations. Three years of high-resolution SSM measurements were estimated using trapezoidal configurations with Landsat-8 data over a semiarid network in Spain. For the uncalibrated trapezoid, fair accuracy with a root-mean-square error (RMSE) of 0.062 $\text{m}<^>{3}/\text{m}<^>{3}$ and a bias of 0.040 $\text{m}<^>{3}/\text{m}<^>{3}$ was achieved when compared with in situ measurements. Furthermore, a practical PTF-calibration approach with local measurements was proposed and subsequently integrated into the trapezoid to obtain SSM values. Our results indicated enhanced SSM estimates with an RMSE of 0.050 $\text{m}<^>{3}/\text{m}<^>{3}$ and a bias of 0.012 $\text{m}<^>{3}/\text{m}<^>{3}$ with the calibrated PTF. Finally, we found that the calibrated trapezoid can eliminate overestimation and underestimation when the SSM was lower or higher, respectively, which occurred frequently for optical SSM retrievals.

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