基于支持向量机理论的滑坡灾害预测——以浙江庆元地区为例

滑坡发生受很多因素影响，揭示因素与发生滑坡事件的关系是当前滑坡研究中的一个重要内容．运用支持向量机理论，利用数字高程和遥感数据，构建了滑坡预测的支持向量机模型，并以浙江庆元县境内滑坡发生集中区为试验区，开展滑坡灾害的预测与评价，取得了与实际滑坡较为一致的结果．认为基于支持向量机理论建立的滑坡预测与评价模型可以快速准确地实现滑坡灾害区域评价与预测．

Prediction of landslide hazard based on support vector machine theory

Many factors influence the occurrence of landsilide, so it is very important for earth scientists to find the relationship between factors and occurrence of landslide. A new model was established for landslide prediction using Digital Elevation Model data and remote sensing data based on support vector machine theory. As a test area for landslide prediction, a prediction map of Qingyuan County in Zhejiang Province was established by this model, and there is a good coherency between the prediction result and the real landslide sites. According to the prediction result, the prediction model based on support vector machine theory is a useful method for landsilde prediction and the landslide hazard map can be obtained quickly and accurately by this model.