金沙江流域滑坡易发性空间预报分析  

Analysis and prediction of landslide susceptibility in Jinsha River

作　　者：苏美臣 魏晓燕 周峻松 汪祎勤 SU Meichen;WEI Xiaoyan;ZHOU Junsong;WANG Yiqin(Yunnan Normal University,Kunming 650500,China;Yunnan Provincial Archives of Surveying and Mapping,Kunming 650034,China)

机构地区：[1]云南师范大学,云南昆明650500 [2]云南省测绘资料档案馆,云南昆明650034

出　　处：《测绘通报》2021年第4期13-16,共4页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(42061074;41701470)。

摘　　要：灾害易发性预报是提高灾害防控能力的第一步。针对位于云南省内的金沙江流域因地势险峻、生态环境脆弱,加之近年来人为活动增多已成为地质灾害高发区的现状,本文以金沙江德钦至华坪段滑坡灾害为例,运用Maxent和随机森林两种机器学习模型对滑坡空间分布作归因与预测,并对两者之间的差异进行对比分析。试验结果表明,随机森林模型的预测精度高于Maxent模型,AUC值为0.72。Disaster susceptibility mapping is the first step to improve the ability of control and prediction.In view of the problem that Jinsha River located in Yunnan province due to steep terrain and fragile ecological environment,combined with the increase of human activities in recent year,its basin has become the most frequent incident area of geological disaster in china.Taking Jinsha River of Deqin-Huapingas an example,this paper uses two methods(maxent and random forest model)for attribution and prediction of spatial distribution of landslides,and compares their differences.The result show that the prediction accuracy of random forest is higher than Maxent,and the AUC is 0.72.

关 键 词：滑坡预报 随机森林 Maxent模型 金沙江流域 易发性制图 

分 类 号：P208[天文地球—地图制图学与地理信息工程]