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Article

Evaluation of Satellite-Derived Soil Moisture in Qinghai Province Based on Triple Collocation

1
School of surveying and mapping science and engineering, Shandong University of Science and Technology, Qingdao 266000, China
2
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Water 2020, 12(5), 1292; https://doi.org/10.3390/w12051292
Submission received: 1 April 2020 / Revised: 28 April 2020 / Accepted: 29 April 2020 / Published: 2 May 2020
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology II)

Abstract

Evaluating the reliability of satellite-based and reanalysis soil moisture products is very important in soil moisture research. The traditional methods of evaluating soil moisture products rely on the verification of satellite inversion data and ground observation; however, the ground measurement data is often difficult to obtain. The triple collocation (TC) method can be used to evaluate the accuracy of a product without obtaining the ground measurement data. This study focused on the whole of Qinghai Province, China (31°–40° N, 89°–103° E), and used the TC method to obtain the error variance for satellite-based soil moisture data, the signal-to-noise ratio (SNR) of the same data, and the correlation between the same data and the ground-truth soil moisture, using passive satellite products: Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS), Fengyun-3B Microwave Radiation Imager (FY3B), Fengyun-3C Microwave Radiation Imager (FY3C), and Advanced Microwave Scanning Radiometer 2 (AMSR2); an active satellite product Advanced Scatterometer (ASCAT), and reanalysis data Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system. The TC results for the passive satellite data were then compared with the satellite-derived enhanced vegetation index (EVI) to explore the influence of vegetation coverage on the results. The following conclusions are drawn: (1) for the SMAP, SMOS, FY3B, FY3C, and AMSR2 satellite data, the spatial distributions of the TC-derived error variance, the SNR of the satellite-derived soil moisture, and the correlation coefficient between the satellite-derived and ground-truth soil moisture, were all relatively similar, which indirectly verified the reliability of the TC method; and (2) SMOS data have poor applicability for the estimation of soil moisture in Qinghai Province due to their insufficient detection capability in the Qaidam area, high error variance (median 0.0053), high SNR (median 0.43), and low correlation coefficient with ground-truth soil moisture (median 0.57).
Keywords: soil moisture; EVI; triple collocation; Qinghai region soil moisture; EVI; triple collocation; Qinghai region

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MDPI and ACS Style

Zhu, H.; Zhang, Z.; Lv, A. Evaluation of Satellite-Derived Soil Moisture in Qinghai Province Based on Triple Collocation. Water 2020, 12, 1292. https://doi.org/10.3390/w12051292

AMA Style

Zhu H, Zhang Z, Lv A. Evaluation of Satellite-Derived Soil Moisture in Qinghai Province Based on Triple Collocation. Water. 2020; 12(5):1292. https://doi.org/10.3390/w12051292

Chicago/Turabian Style

Zhu, Hongchun, Zhilin Zhang, and Aifeng Lv. 2020. "Evaluation of Satellite-Derived Soil Moisture in Qinghai Province Based on Triple Collocation" Water 12, no. 5: 1292. https://doi.org/10.3390/w12051292

APA Style

Zhu, H., Zhang, Z., & Lv, A. (2020). Evaluation of Satellite-Derived Soil Moisture in Qinghai Province Based on Triple Collocation. Water, 12(5), 1292. https://doi.org/10.3390/w12051292

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