天然橡胶是国防、工业、医疗卫生等领域重要的生产材料，是重要的战略物资。由于我国植胶区纬度偏高，种植环境较橡胶树原生地差异较大，寒害一直是我国天然橡胶生产面临的主要灾害之一，也是限制中国天然橡胶发展的主要因素。传统的作物寒害监测方法效率低，而基于时空数据融合技术的橡胶林寒害遥感监测方法研究尚属空白。针对上述问题，本项目拟研究基于多源遥感产品融合模型的云南省橡胶林寒害监测方法。包括：（1）建立基于贝叶斯最大熵理论的高时空分辨率遥感地表温度、植被指数的融合模型；（2）结合遥感地表温度与实测橡胶林气温数据实现近实时橡胶林气温估计理论与模型；（3）云南省橡胶林寒害识别及寒害风险等级划分方法。本项目可为我国天然橡胶生产中的寒害监测和天然橡胶宜植区规划提供理论与技术支撑。

Natural rubber is the basic and strategic material for national defense, industrial engineering and medical treatment. Rubbers are planted high beyond the latitude where they were origined, thus chilling injuries are one of the common threats to natural rubber planting in China, and this is also the main obstacle for rubber planting progress in China. The traditional plant chilling injury observation method was inefficient, however, the remote sensing data blending method with far more advantages for rubber chilling injury monitoring is missing. Therefore, this project aims to propose a muli-source remote sensing data fusing technology based method to observe rubber chilling injury in Yunnan province. This method will 1) give a high spatio-temporal resolution land surface temperature and vegetation index blending method based on the bayesian maximum entropy (BME) theory; 2) present an air temperature estimation method fo rubber plantations using land surface temperature and field observation air temperature data; and 3) propose a rubber chilling injury observation method and chilling injury grading method for Yunnan province. This project will provide academic and technological supports in natural rubber chilling injury observation and rubber planting planning to aid the national natural rubber planting.