Comprehensive Risk Assessment of Urban Waterlogging Disaster Based on MCDA-GIS Integration: The Case Study of Changchun, China

Urban waterlogging will harm economic development and people’s life safety; however, the waterlogging risk zoning map provides the necessary decision support for the management of urban waterlogging, urban development and urban planning. This paper proposes an urban waterlogging risk assessment meth...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-07, Vol.14 (13), p.3101
Main Authors: Duan, Chenyu, Zhang, Jiquan, Chen, Yanan, Lang, Qiuling, Zhang, Yichen, Wu, Chenyang, Zhang, Zhen
Format: Article
Language:English
Subjects:
Altitude
Analytic hierarchy process
analytical hierarchy process
Cities
Climate change
Decision analysis
Decision making
Disaster risk
Disasters
Drainage
Economic development
Emergency preparedness
Emergency response
Floods
GDP
Geographic information systems
Gross Domestic Product
Multiple criterion
Natural disasters
Population
Precipitation
Rain
Recovery
Remote sensing
remote sensing and GIS
Risk assessment
Spatial data
Stormwater management
Urban areas
Urban development
Urban planning
urban waterlogging
Urbanization
Waterlogging
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Summary:Urban waterlogging will harm economic development and people’s life safety; however, the waterlogging risk zoning map provides the necessary decision support for the management of urban waterlogging, urban development and urban planning. This paper proposes an urban waterlogging risk assessment method that combines multi-criteria decision analysis (MCDA) with a geographic information system (GIS). The framework of urban waterlogging risk assessment includes four main elements: hazard, exposure, vulnerability, and emergency response and recovery capability. Therefore, we selected the urban area of Changchun City, Jilin Province as the study area. The Analytic Hierarchy Process (AHP) is a generally accepted MCDA method, it is used to calculate the weight and generate a result map of hazards, exposure, vulnerability, and emergency responses and recovery capability. Based to the principle of natural disaster risk formation, a total of 18 parameters, including spatial data and attribute data, were collected in this study. The model results are compared with the recorded waterlogging points, and the results show that the model is more reliable.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14133101