1. Multi-star linear regression retrieval model for monitoring soil moisture using GPS-IR
- Author
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LIANG Yueji, REN Chao, HUANG Yibang, PAN Yalong, and ZHANG Zhigang
- Subjects
signal to noise ratio ,multi-satellite combination ,gps-interferometric reflectometry ,lcsh:Mathematical geography. Cartography ,soil moisture ,lcsh:GA1-1776 ,Physics::Atmospheric and Oceanic Physics ,Physics::Geophysics ,retrieval accuracy - Abstract
Global positioning system interferometric reflectometry (GPS-IR) is a new remote sensing technique that can be used to estimate near-surface soil moisture from signal-to-noise ratio (SNR) data recorded by a measurement receiver. Considering that there are few studies on the inversion of soil moisture by multi-satellite combination, a multi-star linear regression soil moisture inversion model is proposed. The experiment shows that: ①The multi-satellite combination inversion mode can more comprehensively reflect the soil moisture information within the effective monitoring range near the station, and effectively improve the phenomenon that the inversion process is prone to abnormal jump when using single satellite inversion. At the same time, it improves the accuracy of soil moisture inversion during sudden rainfall periods. ②When the number of combined satellites reaches 6 or more, the correlation coefficient between the inversion result and the soil moisture reference value is greater than 0.9, which is at least 20.8% higher than that of a single satellite.
- Published
- 2020