合成孔径雷达反演裸露地表土壤水分的新方法

A New Method for Soil Moisture Inversion by Synthetic Aperture Radar

提出了一种新的合成孔径雷达(SAR)反演裸露地表土壤水分的经验模型,该模型同时考虑了均方根高度S和相关长度L的影响,并将两个粗糙度参数合二为一,然后利用VV和VH极化的后向散射系数即可反演得到土壤水分。通过实测数据对模型进行了验证,发现在θ0>20°时,模型反演值与模拟值有着良好的相关关系(R2=0.71)。该模型在不需要测量地面粗糙度的情况下可以反演得到比较好的土壤水分精度,尤其适用于地表情况复杂、难以精确测量的地区。

We develop an originally experiential methodology to retrieve bare soil moisture by synthetic aperture radar（SAR）. The model does not require any field measurements to sup- port, and only requires the two different kinds of polarized backscattering coefficient data. Taking into account both of the roughness parameters RMS S and the correlative length L, we combine the two roughness parameters and introduce a new roughness parameter （Rs= S3/L2） into this model. Hence, the unknown parameter in the model reduces to Rs and the volume of soil water content mv. Then, the ground soil moisture can be retrieved by integra- ting the equations of VV and VH polarization. The simulating data was used to validate the accuracy of this model. The result shows that there is a strong linear relationship （R2〉 0.71） when the incidence angle is not very small （θ0-20°）. The inversion model can get a better accuracy of soil moisture without any measurements of surface roughness. This meth- od is especially effective in the area with complex terrain where the surface roughness is diffi- cult to be precisely measured.