目标分解技术在植被覆盖条件下土壤水分计算中的应用

Evaluate Usage of Decomposition Technique in Estimation of Soil Moisture with Vegetated Surface by Multi-Temporal Measurements Data

目标分解技术利用协方差矩阵的特征值和特征矢量,将极化雷达后向散射测量值分解为单向散射、双向散射和交叉极化散射三个分量,并建立了植被覆盖地表的一阶物理离散散射模型。通过分解的各分量与该模型的比较,建立重轨极化雷达测量数据估算土壤水分的方法。采用Washita’92实验区多时相全极化L波段JPL/AIRSAR图像雷达测量数据,利用分解的散射测量值,我们评估了在同一入射角,单频（L波段）、多路条件下,分解理论在进行土壤水分估计时减小植被影响的能力。结果表明利用目标分解理论和重轨极化雷达数据可以估算植被覆盖区域土壤水分的变化情况。

During recent years, theoretical modeling and field experiments have established the fundamentals of active microwave remote sensing as an important tool in determining physical properties of soil. But, its application to hydrologi-cal and agricultural sciences has been hampered by natural variability and the complexity of the vegetation canopy and surface roughness that significantly affect the sensitivity of radar backscattering to soil moisture. Vegetation cover will cause an under-estimation of soil moisture and an over-estimation of surface roughness when we apply the algorithm for bare surface soil moisture estimation to vegetation covered regions.A polarimetric SAR backscatter measurements, by using eigenvalues and eigenvectors of the covariance matrix, can be decomposed into three components based on the scattering types:an odd number of reflections,an even number reflections , and a cross-polarized scattering power. This decomposition technique allows us to obtain the estimation of single and double reflection components of backscattering coefficients for VV and HH polarization.In this study,we evaluate the usage of the decomposition theory in application of estimating soil moisture for vegetated surface with the temporal fully polarimetric L-band SAR measurements. Using the decomposed scattering measurements from JPL/AIRSAR image data, we evaluated their usage to reduce the vegetation effect on estimation soil moisture under configurations of a single-frequency (L-band)and multi-pass with a same incidence. The results indicate the decomposition technique can be used to estimate the soil moisture change and their magnitudes for vegetated surface, it provide a powerful tool for monitoring surface soil moisture, especially with the moderate vegetated surface.