Multi-Dimensional Urban Flooding Impact Assessment Leveraging Social Media Data: A Case Study of the 2020 Guangzhou Rainstorm

被引:4
|
作者
Lu, Shuang [1 ]
Huang, Jianyun [1 ]
Wu, Jing [2 ]
机构
[1] Shanghai Jiao Tong Univ, Design Sch, Shanghai 200240, Peoples R China
[2] Wuhan Univ, Sch Urban Design, Wuhan 430072, Peoples R China
关键词
social media; disaster assessment; spatiotemporal analysis; sentiment analysis; urban flooding; SENTIMENT ANALYSIS; RESILIENCE; MANAGEMENT; SATELLITE; ANALYTICS; RISK;
D O I
10.3390/w15244296
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the contexts of global climate change and the urbanization process, urban flooding poses significant challenges worldwide, necessitating effective rapid assessments to understand its impacts on various aspects of urban systems. This can be achieved through the collection and analysis of big data sources such as social media data. However, existing literature remains limited in terms of conducting a comprehensive disaster impact assessment leveraging social media data. This study employs mixed-methods research, a synergy of statistical analysis, machine learning algorithms, and geographical analysis to examine the impacts of urban flooding using the case of the 2020 Guangzhou rainstorm event. The result show that: (1) analyzing social media content enables monitoring of the development of disaster situations, with varied distributions of impact categories observed across different phases of the urban flood event; (2) a lexicon-based approach allows for tracking specific sentiment categories, revealing differential contributions to negative sentiments from various impact topics; (3) location information derived from social media texts can unveil the geographic distribution of impacted areas, and significant correlations are indicated between the waterlogging hotspots and four predisposing factors, namely precipitation, proportion of built-up surfaces, population density, and road density. Consequently, this study suggests that collecting and analyzing social media data is a reliable and feasible way of conducting rapid impact assessment for disasters.
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页数:20
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