A fine-resolution soil moisture dataset for China in 2002~2018

Soil moisture is one of the key parameters for flood forecast, drought detection, crop yield estimation, weather prediction and hydrological modeling. Passive microwave remote sensing technology can quickly obtain soil moisture over large areas, but the coarse spatial resolution imposes great limitations. In order to improve the temporal and spatial resolution of soil moisture products, we built a spatial weight decomposition model to improve the resolution of soil moisture products. The validation and application analysis indicate that new product can meet application needs. SMC version 3.0 combines the previous two versions, and corrects and optimizes in some areas.土壤湿度是洪水预报、干旱监测、作物产量估算、天气预报及水文模拟的关键参数之一。被动微波遥感技术可快速获取大区域范围内的土壤湿度数据，但空间分辨率偏低的缺陷带来了诸多应用限制。为提升土壤湿度产品的时空分辨率，本研究构建了空间权重分解模型以优化其分辨率。经验证与应用分析表明，该新型土壤湿度产品可满足实际应用需求。土壤湿度产品（SMC）3.0版本整合了此前两代版本的内容，并在部分区域完成了修正与优化。