土壤湿度遥感产品时空无缝融合方法研究

Soil water is an important part of the global water cycle movement, soil moisture data is widely used in hydrology, meteorology and so on. Satellite remote sensing soil moisture products have obvious advantages in economic and so on, has been widespread concern. However, because of the track characteristics and inversion algorithms, there is often a large area of spatial and temporal discontinuity existing soil moisture products. It brought great interference for subsequent applications. The project addresses the issue of "fusion Reconstruction - precipitation correction" for the research ideas, the development of sound and efficient integration of remote sensing soil moisture products reconstruction. Combined with land surface temperature, vegetation index, remote sensing information, a multi-variable model reconstruction is established. Then based on the satellite precipitation - soil moisture relationship model, the impact of precipitation on soil moisture change is estimated to get the spatiotemporally continuous soil moisture products.

土壤水是全球水循环运动的重要组成部分之一，土壤湿度数据被广泛应用于水文、气象等多个领域。卫星遥感土壤湿度产品具有宏观、经济、动态等优势，受到了广泛关注。但是由于轨道、传感器特性以及反演算法的影响，现有的土壤湿度产品中时常存在大面积的时空不连续现象。为后续应用带来了极大干扰。本项目针对这一问题，以“融合重建—降水校正”为研究思路，发展稳健、高效的遥感土壤湿度产品融合重建方法。结合地表温度、植被指数等遥感信息，建立多变量重建模型。在此基础上建立卫星降水-土壤湿度关系模型，估算降水对土壤湿度变化的影响，修正上一步的土壤湿度重建值，得到高精度的空间无缝土壤湿度产品。