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Articles | Volume XLVIII-3/W1-2022
https://doi.org/10.5194/isprs-archives-XLVIII-3-W1-2022-79-2022
https://doi.org/10.5194/isprs-archives-XLVIII-3-W1-2022-79-2022
27 Oct 2022
 | 27 Oct 2022

MINING METHOD OF TRAFFIC IMPACT AREAS OF RAINSTORM EVENT BASED ON SOCIAL MEDIA IN ZHENGZHOU CITY

Z. Yang and Q. Wang

Keywords: Social Media, Data Mining, Traffic Impact Areas, Extreme Disaster, Spatiotemporal Analysis, 7.20 Heavy Rains in Zhengzhou

Abstract. Due to the influence of typhoon "fireworks" on July 20, 2021, there was a rare heavy rainfall in Zhengzhou, Henan Province, China, which caused severe urban waterlogged disasters and casualties. Take it as an example, using Web Crawler technology to obtain Weibo’s (Chinese Twitter) time and space data involved in the rare heavy rainfall in Zhengzhou. Through statistical analysis and spatiotemporal analysis to filter, classify, analyse and manipulate the crawled Weibo’s data, and then study the influence of the extreme rainstorm weather on the traffic areas from two aspects of address points and road networks. At the same time, to verify the effectiveness of the social media-based method for mining the traffic impact areas of the Zhengzhou extreme rainstorm, this experiment compares Weibo data with official data in various aspects according to four categories of waterlogging severity.