Dou Qiang, Qin Shengwu, Zhang Yichen, Ma Zhongjun, Chen Junjun, Qiao Shuangshuang, Hu Xiuyu, Liu Fei
College of Construction Engineering, Jilin University, Changchun 130026, China.
Jilin Institute of Geological Environment Monitoring, Changchun 130021, China.
Entropy (Basel). 2019 Jul 15;21(7):695. doi: 10.3390/e21070695.
Debris flow is one of the most frequently occurring geological disasters in Jilin province, China, and such disasters often result in the loss of human life and property. The objective of this study is to propose and verify an information fusion (IF) method in order to improve the factors controlling debris flow as well as the accuracy of the debris flow susceptibility map. Nine layers of factors controlling debris flow (i.e., topography, elevation, annual precipitation, distance to water system, slope angle, slope aspect, population density, lithology and vegetation coverage) were taken as the predictors. The controlling factors were improved by using the IF method. Based on the original controlling factors and the improved controlling factors, debris flow susceptibility maps were developed while using the statistical index (SI) model, the analytic hierarchy process (AHP) model, the random forest (RF) model, and their four integrated models. The results were compared using receiver operating characteristic (ROC) curve, and the spatial consistency of the debris flow susceptibility maps was analyzed while using Spearman's rank correlation coefficients. The results show that the IF method that was used to improve the controlling factors can effectively enhance the performance of the debris flow susceptibility maps, with the IF-SI-RF model exhibiting the best performance in terms of debris flow susceptibility mapping.
泥石流是中国吉林省最频发的地质灾害之一，此类灾害常导致人员伤亡和财产损失。本研究的目的是提出并验证一种信息融合（IF）方法，以改善控制泥石流的因素，并提高泥石流易发性地图的准确性。选取了九层控制泥石流的因素（即地形、海拔、年降水量、距水系距离、坡度角、坡向、人口密度、岩性和植被覆盖度）作为预测因子。采用IF方法对控制因素进行了改进。基于原始控制因素和改进后的控制因素，利用统计指标（SI）模型、层次分析法（AHP）模型、随机森林（RF）模型及其四个集成模型绘制了泥石流易发性地图。使用受试者工作特征（ROC）曲线对结果进行比较，并利用斯皮尔曼等级相关系数分析了泥石流易发性地图的空间一致性。结果表明，用于改进控制因素的IF方法能够有效提升泥石流易发性地图的性能，其中IF-SI-RF模型在泥石流易发性制图方面表现最佳。
