Framework for Spatio-Temporal Distribution of Disasters and Influencing Factors: Exploratory Study of Tianjin, China

Weichao Yang, Hu De, Xuelian Jiang (), Xuebo Dun, Bingtao Hou, Chuanxing Zheng, Caixia Chen and Rong Zhuang
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Weichao Yang: Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
Hu De: Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
Xuelian Jiang: Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
Xuebo Dun: Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
Bingtao Hou: Zhonghuan Information College, Tianjin University of Technology, Tianjin 300380, China
Chuanxing Zheng: Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
Caixia Chen: Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
Rong Zhuang: Tianjin Dongfang Tairui Technology Co., Ltd., Tianjin 300110, China

Sustainability, 2022, vol. 14, issue 17, 1-23

Abstract: Facing the increased frequency of disasters and resulting massive damages, many countries have developed their frameworks for disaster risk management (DRM). However, these frameworks are highly regional and few of them suggest corresponding methods for specific analysis content, which makes them less practical and operational. In this paper, we investigate an exploratory framework for spatio-temporal distribution of disasters and analysis of influencing factors, including suggested methods for all the content. Time series analysis, geographical difference analysis, direction distribution analysis, and spatial autocorrelation analysis are selected as the content of spatio-temporal distribution of disasters part. Mann–Kendall test method, Lorentz curve, standard deviation ellipse method, and exploratory spatial data analysis method are introduced to analyze them. The impact analysis part was carried out on individual disaster and multiple disasters, which are suggested as the two aspects of influencing factors analysis, by means of a geographic detector and a novel comprehensive impact evaluation model that was developed. Then, the framework is applied to analyze disasters including flood, storm surge, and earthquake in Tianjin of China. The research results help to understand the spatial and temporal distribution of disasters and the disaster mechanism in Tianjin. Further, the superiority and limitations of the framework are discussed. Finally, the framework developed is expected to be widely applied in other districts for better DRM in the future.

Keywords: disaster risk management; multiple disasters; spatial-temporal distribution; impact analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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