TY - JOUR
T1 - Susceptibility mapping and risk assessment of urban sinkholes based on grey system theory
AU - Zhang, You
AU - Jiao, Yu-Yong
AU - He, Ling-Ling
AU - Tan, Fei
AU - Zhu, Hua-Mei
AU - Wei, Hui-Long
AU - Zhang, Qian-Bing
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China (Grant nos. 41920104007, 42227805), and the Industry-University-Research Innovation Fund for Chinese Universities (No. 2020 IT A03010). The project was supported by the Fundamental Research Funds for National Universities, China University of Geosciences (Wuhan).
Publisher Copyright:
© 2024
PY - 2024/10
Y1 - 2024/10
N2 - Urban sinkholes can cause subsidence damage to transportation infrastructures, building demolitions and even casualties when they occur suddenly. It is hence essential to identify their forming factors and analyze their spatial distribution features, so as to pave the way for sinkhole risk assessment and mitigation for urban sustainable development. Investigation of urban sinkholes poses a significant challenge because of the multi-factor's confusion, as well as the spatial uncertainties in susceptibility mapping due to urban renewal frequently. To address these issues, a comprehensive urban sinkhole risk assessment framework was proposed, and Shenzhen city in South China was selected as a case study area, where a lot of sinkholes occurred along with intensive human construction activities in recent years. Initially, the sinkhole susceptibility map was drawn using the grey relation analysis (GRA) method, incorporating the spatial information database of meteorology, geology, metro and pipeline systems, and then both the sinkhole density map and the time-varying land subsidence monitoring database were used to verify the accuracy of the sinkhole susceptibility map. Furthermore, the sinkhole risk assessment map in transportation system was subsequently drawn based on the susceptibility map, where the Interferometric Synthetic Aperture Radar (InSAR) and the advanced geophysical exploration technologies were employed to probe the potential sinkholes in critical risk areas. The conclusions reveal that the sinkhole susceptibility map based on GRA method demonstrates a promise in identifying the likelihood of urban sinkholes, and the risk assessment framework can be employed for the prevention and remediation of urban sinkholes, which contributes to an economical and efficient scheme for sinkhole detection, as well as transportation system resilience assessment at a city-wide scale.
AB - Urban sinkholes can cause subsidence damage to transportation infrastructures, building demolitions and even casualties when they occur suddenly. It is hence essential to identify their forming factors and analyze their spatial distribution features, so as to pave the way for sinkhole risk assessment and mitigation for urban sustainable development. Investigation of urban sinkholes poses a significant challenge because of the multi-factor's confusion, as well as the spatial uncertainties in susceptibility mapping due to urban renewal frequently. To address these issues, a comprehensive urban sinkhole risk assessment framework was proposed, and Shenzhen city in South China was selected as a case study area, where a lot of sinkholes occurred along with intensive human construction activities in recent years. Initially, the sinkhole susceptibility map was drawn using the grey relation analysis (GRA) method, incorporating the spatial information database of meteorology, geology, metro and pipeline systems, and then both the sinkhole density map and the time-varying land subsidence monitoring database were used to verify the accuracy of the sinkhole susceptibility map. Furthermore, the sinkhole risk assessment map in transportation system was subsequently drawn based on the susceptibility map, where the Interferometric Synthetic Aperture Radar (InSAR) and the advanced geophysical exploration technologies were employed to probe the potential sinkholes in critical risk areas. The conclusions reveal that the sinkhole susceptibility map based on GRA method demonstrates a promise in identifying the likelihood of urban sinkholes, and the risk assessment framework can be employed for the prevention and remediation of urban sinkholes, which contributes to an economical and efficient scheme for sinkhole detection, as well as transportation system resilience assessment at a city-wide scale.
KW - Grey relation analysis
KW - Risk assessment
KW - Sinkhole
KW - Spatial distribution
KW - Susceptibility mapping
UR - http://www.scopus.com/inward/record.url?scp=85195540981&partnerID=8YFLogxK
U2 - 10.1016/j.tust.2024.105893
DO - 10.1016/j.tust.2024.105893
M3 - Article
AN - SCOPUS:85195540981
SN - 0886-7798
VL - 152
JO - Tunnelling and Underground Space Technology
JF - Tunnelling and Underground Space Technology
M1 - 105893
ER -