Browse by author
Lookup NU author(s): Chen YuORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© 2023 Wuhan University. All rights reserved.Objectives: In July 2021, Henan Province of China suffered continuous extreme rainfalls, causing widespread flood and serious paralysis of the highway network. The flood caused by the heavy rainfalls brought enormous loss to people's lives and properties in Henan Province. Methods: We collectively used a range of earth observations, namely remote sensing images from Sentinel-1 and Gaofen-3 satellites, rainfall and water vapor data from the European Centre for Medium-Range Weather Forecasts, and geohazard survey data to investigate and analyze the evolving process of the flood caused by the heavy rainfalls in Henan Province, and proposed a new technical framework for rapid assessment of traffic inefficiency under flood scenarios over wide regions. Results: The application of the new framework to the case in Henan Province suggests that: (1) The cumulative rainfall was highly concentrated, reaching a historic high level and affecting a wide region. (2) The total affected area in Zhengzhou City, Henan Province and its surrounding areas reached 3 800 km2. (3) The potential of secondary landslides in mountainous areas such as Sanmenxia City and Dengfeng City was highly increased.(4) About 1 300.46 km of major roads were affected by this flood, and the overall connectivity of major highway networks in Zhengzhou and its surrounding five cities decreased about 21.27%, with 34.22% for expressways, 13.78% for national highways, and 14.86% for provincial highways. Conclusions: This study shows how to integrate remote sensing, secondary landslide analysis, road network analysis, and other multi-field technologies to construct a framework for traffic inefficiency assessment under natural hazards. It is believed that this framework could be applied to other hazardous events and provide valuable information for emergency rescue.
Author(s): Li Z, Wang J, Hu Y, Zhu W, Fu X, Zhang S, Yu C, Wang L, Zhang C, Du J, Huang W, Lu X, Zhang C, Chen B, Liu X, Yue Y
Publication type: Article
Publication status: Published
Journal: Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University
Year: 2023
Volume: 48
Issue: 7
Pages: 1039-1049
Print publication date: 01/07/2023
Acceptance date: 02/04/2023
ISSN (print): 1671-8860
Publisher: Editorial Board of Medical Journal of Wuhan University
URL: http://ch.whu.edu.cn/en/article/doi/10.13203/j.whugis20220512
DOI: 10.13203/j.whugis20220512
Altmetrics provided by Altmetric
