County road identification and preliminary risk assessment of natural disasters: take Changqing District as an example

Yadong Lv; Zhaoying Wang; Chunhui Wang; Huaixiang Liang; Jizhe Sun; Shuai Peng; Fangfang Li

doi:10.1117/12.3007395

30 August 2023 County road identification and preliminary risk assessment of natural disasters: take Changqing District as an example

Yadong Lv, Zhaoying Wang, Chunhui Wang, Huaixiang Liang, Jizhe Sun, Shuai Peng, Fangfang Li

Author Affiliations +

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127970D (2023) https://doi.org/10.1117/12.3007395
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

For a long time, natural disasters have caused trauma to all aspects of our society, and historical disaster information records are incomplete. The coupling relationship between disaster damage and actual loss lacks spatial information. These factors make it necessary to carry out a natural disaster risk survey. Under the background of comprehensive risk survey of natural disasters, based on the NPP VIIRS remote sensing data, OSM data, "Tianditu" data to recognition of county road in Changqing District, intended for preliminary natural disaster assessment. Then finally the convergence results of two layers of 669 records of municipal roads and 121 records of municipal bridges were obtained. Based on the preliminary work of the municipal infrastructure base map, using the indicator system method to assess the risk of natural disasters on county roads. Based on the Five basic evaluation indicators in the Technical Guidelines for Highway Natural Disaster Census, calculate the County Road Risk Index (CRI) to obtain the disaster risk classification of county roads in the study district. Preliminary research suggests that there are currently no natural disaster risk points in this area, and further risk analysis will be conducted in the future.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yadong Lv, Zhaoying Wang, Chunhui Wang, Huaixiang Liang, Jizhe Sun, Shuai Peng, and Fangfang Li "County road identification and preliminary risk assessment of natural disasters: take Changqing District as an example", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127970D (30 August 2023); https://doi.org/10.1117/12.3007395

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KEYWORDS

Roads

Bridges

Natural disasters

Risk assessment

Floods

Remote sensing

Earthquakes

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