通用水土流失方程（USLE）及修正通用土壤流失方程（RUSLE）是世界范围内应用最广泛的土壤侵蚀预报模型，模型中的C因子表示植被覆盖和管理措施对土壤侵蚀的作用，是人为控制土壤侵蚀的重要因子。项目研究以实测不同植被类型叶面积指数（LAI），结合同期遥感数据，构建LAI估测模型；综合考虑林冠层、林下草本层和枯落物层的降雨减蚀作用，引入土壤呼吸温度敏感性因子（Q10值）表达林下草本层和枯枝落叶层信息，进而结合LAI，使遥感数据能够完全刻画出C因子，建立遥感数据与C因子的关系式，实现C因子的遥感重构，更准确地估算南方红壤水土流失区的C因子。

Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) are the most widely used soil erosion prediction models around the world. In those models, the C factor, which is one of the important factors in artificial controlling of soil erosion, indicates the role of vegetation cover and management practices on soil erosion. This project intended to build the Leaf Area Index (LAI) estimation model through the actual measurement of different types of vegetation LAI and combining with contemporaneous remote sensing data; Considering the erosion reduction effect of forest canopy, herb layer and litter layer, the soil respiration temperature sensitivity factor (Q10 value) will be introduced to express the information of herb layer and branches and litter layer. Then with help of the combination Q10 value with LAI, the C factor will be depicted completely by the remote sensing data. The C factor estimated model will be reconstructed with the relationships between remote sensing data and the C factor, which will more accurately estimate the C factor of soil and water loss region in southern red soils area.