基于GPS-IR的地表土壤湿度估算方法

Estimation method for surface soil moisture based on GPS-IR

全球定位系统干涉反射测量(GPS-IR)是一种新型的遥感技术,可用于估算近地表土壤水分含量。本文从多卫星融合角度出发,提出了一种基于多星融合的地表土壤湿度估算方法。首先通过低阶多项式拟合分离出卫星反射信号;然后建立反射信号正弦拟合模型,获取相对延迟相位;最后基于多卫星相对延迟相位建立多元线性回归模型。利用美国板块边界观测计划(PBO)提供的监测数据,对比分析不同建模序列长度的反演效果,从而确定最佳的建模长度。试验结果表明,采用多元线性回归模型可实现多颗卫星的有效融合,运用于土壤湿度估算是可行的。

Global Positioning System Interferometric Reflectance(GPS-IR)is a new remote sensing technique,which can be used to estimate soil moisture content near the surface.From the view of multi-satellite fusion,an estimating method of surface soil water content based on multi-satellite fusion is proposed.Firstly,the direct and reflected signals of multiple satellites are separated by low order polynomial fitting,and then the sinusoidal fitting model of the reflected signals is established to obtain the relative delay phase.Finally,a multiple linear regression model is established based on the relative delay phase of multiple satellites.Based on the monitoring data provided by the plate boundary Observatory(PBO),the inversion effects of different modeling sequence lengths are compared and analyzed to determine the best modeling length.The experimental results show that multiple linear regression model can effectively integrate multiple satellites,and it is feasible to estimate soil moisture.