@article{ref1,
title="A method for improving controlling factors based on information fusion for debris  flow susceptibility mapping: a case study in  Jilin Province, China",
journal="Entropy (Basel, Switzerland)",
year="2019",
author="Dou, Qiang and Qin, Shengwu and Zhang, Yichen and Ma, Zhongjun and Chen, Junjun and Qiao, Shuangshuang and Hu, Xiuyu and Liu, Fei",
volume="21",
number="7",
pages="e21070695-e21070695",
abstract="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.<p /> <p>Language: en</p>",
language="en",
issn="1099-4300",
doi="10.3390/e21070695",
url="http://dx.doi.org/10.3390/e21070695"
}