Application of Machine Learning to Debris Flow Susceptibility Mapping along the China–Pakistan Karakoram Highway

Feng Qing,Tianjun Qi,Yan Zhao,Dongxia Yue,Xiaojun Su,Xingmin Meng

doi:10.3390/rs12182933

Abstract

The China–Pakistan Karakoram Highway is an important land route from China to South Asia and the Middle East via Pakistan. Due to the extremely hazardous geological environment around the highway, landslides, debris flows, collapses, and subsidence are frequent. Among them, debris flows are one of the most serious geological hazards on the Karakoram Highway, and they often cause interruptions to traffic and casualties. Therefore, the development of debris flow susceptibility mapping along the highway can potentially facilitate its safe operation. In this study, we used remote sensing, GIS, and machine learning techniques to map debris flow susceptibility along the Karakoram Highway in areas where observation data are scarce and difficult to obtain by field survey. First, the distribution of 544 catchments which are prone to debris flow were identified through visual interpretation of remote sensing images. The factors influencing debris flow susceptibility were then analyzed, and a total of 17 parameters related to geomorphology, soil materials, and triggering conditions were selected. Model training was based on multiple common machine learning methods, including Ensemble Methods, Gaussian Processes, Generalized Linear models, Navies Bayes, Nearest Neighbors, Support Vector Machines, Trees, Discriminant Analysis, and eXtreme Gradient Boosting. Support Vector Classification (SVC) was chosen as the final model after evaluation; its accuracy (ACC) was 0.91, and the area under the ROC curve (AUC) was 0.96. Among the factors involved in SVC, the Melton Ratio (MR) was the most important, followed by drainage density (DD), Hypsometric Integral (HI), and average slope (AS), indicating that geomorphic conditions play an important role in predicting debris flow susceptibility in the study area. SVC was used to map debris flow susceptibility in the study area, and the results will potentially facilitate the safe operation of the highway.

Highlights

The China–Pakistan Karakoram Highway (KKH) is an important land route from China to South Asia and the Middle East via Pakistan [1,2]
The probability value of debris flow susceptibility was divided into five categories using the natural fracture method [58]: very low, low, moderate, high, and very high
The susceptibility mapping results (Figure 11) show that debris flow susceptibility in large catchments (>100 km2) is generally low, which may be because the fluvial processes take over the debris flow processes in these catchments

Summary

Introduction

The China–Pakistan Karakoram Highway (KKH) is an important land route from China to South Asia and the Middle East via Pakistan [1,2]. A total of 150 debris flows occurred along the KKH from 2008 to 2011 and were investigated by Liao et al [4]. On 2 March 2015, a debris flow occurred in section 1607 of the KKH, on the border between Aktau county and Shufu county in Kashi Prefecture, Xinjiang, trapping more than 300 vehicles and more than 600 people (according to People’s Daily: http://xj.people.com.cn/n/2015/0305/c188514-24068832.html). On 6 July 2016, a debris flow occurred in Yecheng County in Xinjiang, killing 35 people and seriously damaging the road (according to People’s Daily: http://en.people.cn/n3/2016/0708/c90882-9083370.html). On 11 July 2017, a mud rock flow occurred in Bulunkou Township, Aketao County, Xinjiang Autonomous Prefecture, burying several roads and more than 200 vehicles, and trapping more than 1000 persons (according to China Network: http://www.china.com.cn/news/2017-07/12/content_41202196.htm)

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Methods

Results

Conclusion