Ensemble learning analysis of influencing factors on the distribution of urban flood risk points: a case study of Guangzhou, China

Author:

Zhao Juchao,Wang Jin,Abbas Zaheer,Yang Yao,Zhao Yaolong

Abstract

Urban waterlogging is a major natural disaster in the process of urbanization. It is of great significance to carry out the analysis of influencing factors and susceptibility assessment of urban waterlogging for related prevention and control. However, the relationship between urban waterlogging and different influencing factors is often complicated and nonlinear. Traditional regression analysis methods have shortcomings in dealing with high-dimensional nonlinear issues. Gradient Boosting Decision Tree (GBDT) is an excellent ensemble learning algorithm that is highly flexible and efficient, capable of handling complex non-linear relationships, and has achieved significant results in many fields. This paper proposed a technical framework for quantitative analysis and susceptibility assessment on influencing factors of urban waterlogging based on the GBDT in a case study in Guangzhou city, China. Main factors and indicators affecting urban waterlogging in terrain and topography, impervious surface, vegetation coverage, drainage facilities, rivers, etc., were selected for the GBDT. The results demonstrate that: (1) GBDT performs well, with an overall accuracy of 83.5% and a Kappa coefficient of 0.669. (2) Drainage density, impervious surface, and NDVI are the most important influencing factors resulting in rainstorm waterlogging, with a total contribution of 85.34%. (3) The overall distribution of urban waterlogging susceptibility shows a characteristic of “high in the southwest and low in the northeast”, in which the high-susceptibility areas are mainly distributed in Yuexiu District (34%), followed by Liwan District (22%) and Haizhu District (20%). To mitigate the impact of frequent urban flooding disasters, future measures should focus on strengthening drainage networks, such as optimizing impervious surface spatial patterns, controlling construction activities in high-risk areas, and preventing excessive development of green spaces.

Funder

National Natural Science Foundation of China

Publisher

Frontiers Media SA

Subject

General Earth and Planetary Sciences

Cited by 7 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