基于多时相SAR数据山地土壤含水量反演研究

Soil moisture in mountainous areas plays an important role in hydrological, climatic and disaster studies. The utilization of Synthetic Aperture Radar (SAR) data to estimate soil moisture is of many advantages, such as low cost, wide observation, and impregnability to weather conditions. Therefore, the retrieval of soil moisture from mountainous areas covered with vegetation using SAR data is of comparative advantages and great significance. SAR measurement in mountainous areas, however, leads to the problems of geometric distortion and polarimetric rotation. Moreover, the difficulty in the measurement of mountainous land cover features limits the applicability of the commonly used soil moisture retrieval methods. To address the abovementioned problems, based on multi-temporal SAR data, the following researches are carried out: (1) the analysis of SAR data features acquired from mountainous areas and its correction; (2) the removal of vegetation effect in terms of SAR data acquired from mountainous areas; (3) and the retrieval of soil moisture from mountainous areas; the method of soil moisture retrieval from mountainous areas covered by vegetation without using auxiliary measurement data is finally attained. This project is expected to provide a theoretical basis and research foundation for the study of soil moisture retrieval from mountainous areas, and to promote the application of SAR data in remote sensing measurement.

山区土壤含水量在水文、气候和灾害研究中扮演着重要角色。利用合成孔径雷达(Synthetic Aperture Radar, SAR)数据估计土壤含水量具有成本低、观测范围广、不受天气影响等优点。因此，基于SAR数据的山区植被区域土壤含水量反演具有相对优势和重要意义。然而山区SAR测量会引起几何形变和极化旋转问题。另外，山区地物特征参数测量困难也限制了常用土壤含水量反演方法的适用性。针对以上问题，本项目基于多时相SAR数据，开展如下研究工作：(1)山地SAR数据特性分析与校正研究；(2)山地SAR数据去植被效应研究；(3)山地土壤含水量反演研究；最后实现无需辅助测量数据的山地植被区域土壤含水量反演方法。该项目的研究将为山地区域土壤含水量反演问题提供理论依据和研究基础，推动SAR数据在遥感测量中的应用。

山地土壤含水量是研究水资源形成与径流的关键参数，同时还可以用于滑坡预测、山火预警、植被监测、水资源管理等相关研究。因此，山地土壤含水量提取研究具有重要意义。利用合成孔径雷达（Synthetic Aperture Radar, SAR）估计山地土壤含水量具有成本低、观测范围广、不受天气影响等优点，是目前最有力的测量手段之一。基于此，本项目开展以雷达成像原理、辐射传输理论、极化分解技术、地表散射模型为主要理论依据的山地植被覆盖区域地表含水量提取研究。首先，针对SAR山地测量图像几何形变问题，提出了一种基于查表法的快速识别阴影、叠掩、透视收缩区域算法；其次，针对SAR山地测量极化旋转问题，提出了一种基于被照射面积和极化散射定义的两阶段数据校正方法。SAR山地数据校正保证了后续应用的正确性。再次，利用极化分解算法分析植被中散射粒子特征，基于此降低密西根散射模型中相位函数和消光矩阵所需的输入植被特征变量，从而更容易求得植被后向散射。最后，利用分解重构法模拟随机粗糙面，基于双尺度地表模型求得地表后向散射系数，以介电常数为中间变量，实现地表含水量的估计。总体上，项目按计划基本顺利完成预期研究目标。依托该项目，项目负责人发表基金标注论文于高水平期刊IEEE T GEOSCI REMOTE 3篇，在高水平会议IGARSS上作小组报告4次，1人晋升副教授职称，培养在读博士生1人，在读硕士生2人。本项目的研究成果为山地植被区域土壤含水量反演研究提供理论依据和研究基础，进一步推动SAR数据在遥感测量中的应用。