利用GPS-IR监测土壤湿度的多星线性回归反演模型

全球定位系统干涉反射测量(GPS-interferometric reflectometry,GPS-IR)是一种新的遥感技术,利用测量型接收机记录的信噪比(SNR)观测值可实现近地表土壤湿度的监测。考虑到目前利用多星组合反演土壤湿度的研究较少,本文提出一种土壤湿度多星线性回归反演模型。试验表明:①多星组合反演能够更全面地反映测站附近有效监测范围内的土壤湿度信息,有效改善采用单颗卫星反演时反演过程极易出现异常跳变的现象,提高了突发性降雨时段的土壤湿度反演精度。②当组合卫星数达到6颗以上时,其反演结果与土壤湿度参考值之间的相关系数均大于0.9,相对于单颗卫星至少提高了20.8%。

Multi-star linear regression retrieval model for monitoring soil moisture using GPS-IR

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.