Predicting spatio-temporal man-made slope failures induced by rainfall in Hong Kong using machine learning techniques

Author:

Xiao Te1,Zhang Li Min2,Cheung Raymond Wai Man3,Lacasse Suzanne4

Affiliation:

1. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, P. R. China (Orcid:0000-0003-4935-892X).

2. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, P. R. China.

3. Geotechnical Engineering Office, Civil Engineering and Development Department, The Government of the Hong Kong Special Administrative Region, Hong Kong, P. R. China.

4. Norwegian Geotechnical Institute, Oslo, Norway.

Abstract

Rain-induced man-made slope failures pose great threats to public safety as most man-made slopes are formed in densely populated areas. A critical step in managing landslide risks is to predict the time, locations and consequences of slope failures in future rainstorms. Based on comprehensive databases of in-service man-made slopes, rainstorms and landslides in Hong Kong during the past 35 years, a spatio-temporal landslide forecasting model for man-made slopes is developed in this study within a unified machine learning framework. With a storm-based data integration strategy and multiclass classification on landslide scales, the framework incorporates landslide time and consequences in landslide susceptibility mapping to successfully achieve spatio-temporal landslide forecasting. The machine learning-based landslide forecasting model is validated against historical landslide incidents both temporally and spatially and through a case study of the June 2008 storm; the model significantly outperforms the prevailing statistical rainfall–landslide correlations in terms of prediction accuracy. The model can predict the real-time evolution of probabilities, scales and spatial distribution of landslides during the progression of a rainstorm, which can never be achieved by statistical methods. It can serve as an essential module for state-of-the-art landslide risk assessment and early warning.

Publisher

Thomas Telford Ltd.

Subject

Earth and Planetary Sciences (miscellaneous),Geotechnical Engineering and Engineering Geology

Cited by 25 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3