基于投影寻踪模型的滑坡危险性等级评价

危险性评价是滑坡灾害预防与减灾工作首要解决的重要内容.在地理信息系统技术支持下, 以山地灾害频发区——小江流域作为研究对象, 选取坡度、土体粘聚力和内摩擦角这3个评价指标构建滑坡危险性分级评价指标体系, 将投影寻踪技术运用到滑坡危险性等级评价中, 对评价样本的各指标因素进行线性投影, 以最优投影方向所对应的投影特征值作为评价依据, 建立了滑坡危险性等级综合评价模型, 绘制了滑坡危险性等级分布图.结果表明: 研究区极高危险区、高危险区、中等危险区、低危险区和极低危险区的面积比例为14.28∶9.41∶69.12∶7.00∶0.19;根据所建立的5级评价指标体系对研究区60个土质滑坡点资料进行了验证, 在占研究区总面积23.69%的高、极高危险区的小范围内, 实际发生土质滑坡数量45个, 占总土质滑坡数量的75.00%;中等危险性级别以上区域拥有的土质滑坡数量占全部土质滑坡的96.67%;不同危险性级别的滑坡体积方量统计结果表明, 滑坡体积方量密度随危险性级别的提高而迅速增加.对比评价结果及实测结果可知, 投影寻踪分级结果符合实际情况, 证实了该方法的正确性, 为滑坡危险性评价提供了一条新思路. 

Application of Projection Pursuit Model to Landslide Risk Classification Assessment

It's a top priority to estimate risk of landslides for landslide disaster prevention and disaster reduction. In this paper, taking Xiaojiang ravine, a frequent debris flow occurring area as the study area, a classification assessment system of landslide risk is built by selecting 3 evaluation indexes including slope, cohesive force and internal friction angle based on the geographic information system support. Moreover, the projection pursuit technique is applied to evaluate landslide risk classification. According to linear projection of index factors of evaluation samples, the projection pursuit model to classification evaluation of landslide risk is built and the classification map of landslide risk zoning is drawn by the optimal projection direction of the projection characteristic value. The results show that the area ratio of extremely high risk zone, high risk zone, medium risk zone, low risk zone, extremely low risk zone in the study area is 14.28∶9.41∶69.12∶7.00∶0.19. A total of 60 landslides were verified in the study area according to the established evaluation index system of level 5. The high and extremly high risk zones cover 23.69% of the study area, but the actual number of soil landslides is 45, and the number of soil landslides in those risk zones is 75.00% of the total. The number of soil landslides in medium risk level and above risk zones is 96.67% of the total. The statistical results of landslide risk point density in the classification map of landslide risk zoning show that the density of landslides' volume increases rapidly with the increase of risk level. The evaluation results are relatively more consistent with actual situation and more reasonable compared with the measured results. The model proves to be a new perspective for landslide risk prediction.