A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Spatial Distribution and Susceptibility Mapping of Urban Sinkholes in Shenzhen, China
https://orcid.org/http://orcid.org/0000-0002-6098-3139
https://orcid.org/http://orcid.org/0000-0002-1162-6557
https://orcid.org/http://orcid.org/0000-0001-9081-6932
https://orcid.org/http://orcid.org/0000-0001-6237-8947
https://orcid.org/http://orcid.org/0000-0002-3313-8095
Urban sinkholes can cause subsidence damage to transportation infrastructures, demolition of buildings, and even the loss of human lives when they occur in a rapid way. In this study, the spatial distribution and the susceptibility mapping of the urban sinkholes were studied through the utilization of geographical information systems (GIS) with a sinkhole inventory and a spatial database that contains information on the geology, hydrogeology, and land use. Initially, 1155 sinkhole records from 2016 to 2019 were identified in Shenzhen. It reveals that the urban sinkholes mainly occurred in fill soil areas by examining the 3D geological model produced for this study, and it can also be easily triggered by heavy rains. Then, the sinkhole susceptibility map was obtained based on the gray correlation analysis (GRA). The sinkhole density map and the land subsidence Interferometric Synthetic Aperture Radar (InSAR) data in Futian District were finally used to verify the reliability of the sinkhole susceptibility map. The proposed spatial distribution pattern and the susceptibility mapping based on the GRA method demonstrate a promise to mitigating the risk of urban sinkholes.
Spatial Distribution and Susceptibility Mapping of Urban Sinkholes in Shenzhen, China
https://orcid.org/http://orcid.org/0000-0002-6098-3139
https://orcid.org/http://orcid.org/0000-0002-1162-6557
https://orcid.org/http://orcid.org/0000-0001-9081-6932
https://orcid.org/http://orcid.org/0000-0001-6237-8947
https://orcid.org/http://orcid.org/0000-0002-3313-8095
Urban sinkholes can cause subsidence damage to transportation infrastructures, demolition of buildings, and even the loss of human lives when they occur in a rapid way. In this study, the spatial distribution and the susceptibility mapping of the urban sinkholes were studied through the utilization of geographical information systems (GIS) with a sinkhole inventory and a spatial database that contains information on the geology, hydrogeology, and land use. Initially, 1155 sinkhole records from 2016 to 2019 were identified in Shenzhen. It reveals that the urban sinkholes mainly occurred in fill soil areas by examining the 3D geological model produced for this study, and it can also be easily triggered by heavy rains. Then, the sinkhole susceptibility map was obtained based on the gray correlation analysis (GRA). The sinkhole density map and the land subsidence Interferometric Synthetic Aperture Radar (InSAR) data in Futian District were finally used to verify the reliability of the sinkhole susceptibility map. The proposed spatial distribution pattern and the susceptibility mapping based on the GRA method demonstrate a promise to mitigating the risk of urban sinkholes.
Spatial Distribution and Susceptibility Mapping of Urban Sinkholes in Shenzhen, China
https://orcid.org/http://orcid.org/0000-0002-6098-3139
https://orcid.org/http://orcid.org/0000-0002-1162-6557
https://orcid.org/http://orcid.org/0000-0001-9081-6932
https://orcid.org/http://orcid.org/0000-0001-6237-8947
https://orcid.org/http://orcid.org/0000-0002-3313-8095
Urban sinkholes can cause subsidence damage to transportation infrastructures, demolition of buildings, and even the loss of human lives when they occur in a rapid way. In this study, the spatial distribution and the susceptibility mapping of the urban sinkholes were studied through the utilization of geographical information systems (GIS) with a sinkhole inventory and a spatial database that contains information on the geology, hydrogeology, and land use. Initially, 1155 sinkhole records from 2016 to 2019 were identified in Shenzhen. It reveals that the urban sinkholes mainly occurred in fill soil areas by examining the 3D geological model produced for this study, and it can also be easily triggered by heavy rains. Then, the sinkhole susceptibility map was obtained based on the gray correlation analysis (GRA). The sinkhole density map and the land subsidence Interferometric Synthetic Aperture Radar (InSAR) data in Futian District were finally used to verify the reliability of the sinkhole susceptibility map. The proposed spatial distribution pattern and the susceptibility mapping based on the GRA method demonstrate a promise to mitigating the risk of urban sinkholes.
Spatial Distribution and Susceptibility Mapping of Urban Sinkholes in Shenzhen, China
Lecture Notes in Civil Engineering
Wu, Wei (editor) / Leung, Chun Fai (editor) / Zhou, Yingxin (editor) / Li, Xiaozhao (editor) / Zhang, You (author) / Zhang, Qian-Bing (author) / Jiao, Yu-Yong (author) / Tan, Fei (author) / Zhang, Xi (author)
Conference of the Associated research Centers for the Urban Underground Space ; 2023 ; Boulevard, Singapore
2024-07-10
6 pages
Article/Chapter (Book)
Electronic Resource
English
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