Evaluation of satellite-derived soil moisture in Qinghai province based on triple collocation

2Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

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).

References Powered by Scopus

The SMOS L: New tool for monitoring key elements ofthe global water cycle

1608Citations
N/AReaders
Get full text

Toward the true near-surface wind speed: Error modeling and calibration using triple collocation

648Citations
N/AReaders
Get full text

The ASCAT soil moisture product: A review of its specifications, validation results, and emerging applications

503Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Statistical validation of modis-based sea surface temperature in shallow semi-enclosed marginal sea: A comparison between direct matchup and triple collocation

8Citations
N/AReaders
Get full text

Identifying Seismic Anomalies via Wavelet Maxima Analysis of Satellite Microwave Brightness Temperature Observations

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Zhu, H., Zhang, Z., & Lv, A. (2020). Evaluation of satellite-derived soil moisture in Qinghai province based on triple collocation. Water (Switzerland), 12(5). https://doi.org/10.3390/W12051292

Readers over time

‘20‘21‘22‘2300.751.52.253

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 5

83%

Lecturer / Post doc 1

17%

Readers' Discipline

Tooltip

Earth and Planetary Sciences 2

40%

Computer Science 1

20%

Agricultural and Biological Sciences 1

20%

Environmental Science 1

20%

Article Metrics

Tooltip
Mentions
Blog Mentions: 1

Save time finding and organizing research with Mendeley

Sign up for free
0