雷达影像提取垄行结构土壤含水率方法研究

SAR Images in Retrieving Soil Moisture of Periodic Surfaces with Row Structure

摘要:

目前通过主动微波法建立的土壤含水率反演模型都是针对非周期的随机粗糙地表，而不适用于周期性垄行结构的地表。通过对全极化雷达影像和野外采样数据的分析，证明了同极化（hh和vv）后向散射强度受垄行观测方位角的影响可达4 dB，而交叉极化（vh）对方位角不敏感，据此建立了同极化后向散射强度随方位角变化的响应函数。在hh和vv极化模式下，构造的采样点到响应函数曲线的距离参数与土壤体积含水率的相关系数分别为0.7095和0.8723，分离出了方位角的影响。同时通过3种极化组合方案消除了粗糙度参数的实测误差对反演精度的影响。18个检验点的反演值与实测值之间的相关系数为0.9461，标准差为0.0366 cm3/cm3。证明了该模型对垄行结构土壤含水率的反演是有效并可靠的。

Abstract:

The previous retrieval models of soil moisture based on active microwave remote sensing are applicable for non-periodic random surfaces, not available to periodic surfaces with row structure yet. This study was based on fully polarimetric data and field data. It was found that the like-polarized (hh and vv) backscattering coefficients react obviously to the azimuth angles, up to 4 dB. while the cross-polarized (vh) backscattering reacts insensitively to row-direction changes, then the response functions of hh and vv polarizations were given. A distance parameter that denotes the distance between a sampling point and response function curve was constructed to remove the influence of azimuth angles. The correlation coefficients between the distance parameter and soil moisture were 0.7095 and 0.8723, in hh and vv polarization modes, respectively. Meanwhile the influence of the error of roughness parameters in field measurement was removed by three different polarization combination schemes. The effectiveness of this model was demonstrated by the estimated soil moisture of checkpoints. This study selected 18 sampling points as checkpoints.The correlation coefficient between estimated soil moisture and measured soil moisture was up to 0.9461, the standard deviation was 0.0366 cm3/cm3. The model was reliable and applicable for periodic surfaces.