微波遥感反演土壤水分中构建粗糙度参数的新方法

发布时间：2018-05-31 10:01

本文选题：土壤水分反演 + 组合粗糙度　；参考：《地理与地理信息科学》2017年06期

【摘要】：地表粗糙度是影响雷达后向散射系数的重要因素。该文在基于SAR影像反演地表土壤水分的过程中,考虑到地表粗糙度的野外测量误差、取值范围和雷达入射角等方面的影响,统计了裸土、农用地和草地等几种典型地表的粗糙度测量数据,以此限定AIEM模型的输入参数范围。首先,利用AIEM模型模拟雷达后向散射系数与粗糙度、土壤水分之间的关系,构建了基于曲面拟合思想的、与入射角相关的组合粗糙度参数,并以此为基础利用Envisat ASAR双极化数据(VV、VH)建立了土壤水分反演模型。经实测数据验证,在不同入射角范围内,基于该文建立的模型得到的土壤水分反演结果与实测值都有良好的相关性。与其他形式的组合粗糙度参数进行对比,该文提出的模型反演精度较高,能够适用于入射角范围在(5°,65°)内的SAR影像的反演。
[Abstract]:Surface roughness is an important factor affecting radar backscattering coefficient. In the process of retrieving surface soil moisture based on SAR image, considering the field measurement error of surface roughness, the range of measurement value and the radar incidence angle, the bare soil is counted. The roughness data of several typical land surfaces, such as agricultural land and grassland, are used to limit the input parameters of AIEM model. Firstly, the AIEM model is used to simulate the relationship between radar backscattering coefficient and roughness and soil moisture, and the combined roughness parameters related to incident angle are constructed based on the theory of curved surface fitting. Based on this, a soil moisture inversion model was established by using Envisat ASAR dual polarization data. It is verified by the measured data that soil moisture inversion results based on the model established in this paper have good correlation with the measured values in the range of different incident angles. Compared with other combined roughness parameters, the model presented in this paper has high inversion accuracy and can be used for inversion of SAR images in the incidence angle range of 5 掳or 65 掳.
【作者单位】：长安大学地质工程与测绘学院;
【基金】：国家重大高分专项军事测绘专业处理与服务系统地理空间信息融合分系统(GFZX04040202-07) 中央高校基本科研业务费专业资金项目(310826175031)
【分类号】：S152.7;TP722.6

【相似文献】