星载GNSS-R遥感解译土壤湿度理论及算法研究

土壤湿度是水循环的关键要素，对于气象，农业，生态坏境等人类生产生活相关的领域有着重要的影响。本项目以获取高时空分辨率的土壤湿度为主要研究目标，发展基于星载GNSS-R解译土壤湿度参数的理论和算法。重点研究星载GNSS-R陆地散射模型的优化、土壤湿度理论模型的仿真、有效的经验模型的构建及多源数据融合算法，深入分析星载GNSS-R几何构型、植被对GNSS陆地反射信号的影响和星载GNSS-R解译土壤湿度分辨率等关键问题。本项目研究成果对于我国星载BDS-R技术的研究应用提供参考价值，并且对水资源管理、天气变化监测、农业和生态监测具有重要的理论意义和实际应用价值。

Soil moisture is the important role of water cycle and it has an important impact on the fields related to human production and life, such as meteorology, agriculture, ecological environment etc. The main research goal of this project is to obtain soil moisture with high temporal and spatial resolution by spacebone GNSS-R and develop theories and methods for retrieving soil moisture parameters based on spaceborne GNSS-R. This project focuses on the optimization of spaceborne GNSS-R land scattering model, the simulation of soil moisture theoretical model, the construction of effective empirical model and the method of multi-source data fusion. Deeply analyzes the key issues such as the geometry of spaceborne GNSS-R, the influence of vegetation on GNSS land reflection signal and the resolution of spaceborne GNSS-R retrieve of soil moisture. The research results of this project provide reference value for the application of spaceborne BDS-R technology in China, meanwhile have important theoretical significance and practical application value for water resources management, weather change monitoring, agricultural and ecological monitoring.