GIS analysis of urban ground collapse susceptibility: a case study of eastern Hangzhou, China

Zhou, Liling; Zhang, Xiaoyi; Shen, Huizhen; Zhang, Dazheng; Bao, Haijun

doi:10.3389/feart.2023.1338877

Cited by 3 publications

(2 citation statements)

References 46 publications

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“…The cities with the highest geo-hazard risk are Wenzhou and Hangzhou, while Wenzhou's UGC risk is relatively low, and Hangzhou occupies a considerable proportion. This significant difference also tells us that, although UGC is closely related to adverse geological conditions, the factors contributing to its occurrence are fundamentally different from those of geo-hazards, and human activities might be a deeper cause [38]. It can also be noticed that, in the years 2018 and 2019, the high-risk cities for UGC and geo-hazards were the same.…”

Section: Comparison With Other Geo-hazards Eventsmentioning

confidence: 86%

“…This is also a significant feature of UGCs, which differs from collapse events in traditional geological hazards. A typical city is Hangzhou, located in the eastern coastal area, which has experienced severe UGC events [2,38]. Mountain tunnelling [39] and metro system construction [40,41] have contributed to the occurrence of UGC events in Zhejiang province.…”

Section: Study Areamentioning

confidence: 99%

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An LLM-Based Inventory Construction Framework of Urban Ground Collapse Events with Spatiotemporal Locations

Hao,

Qi,

et al. 2024

IJGI

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Historical news media reports serve as a vital data source for understanding the risk of urban ground collapse (UGC) events. At present, the application of large language models (LLMs) offers unprecedented opportunities to effectively extract UGC events and their spatiotemporal information from a vast amount of news reports and media data. Therefore, this study proposes an LLM-based inventory construction framework consisting of three steps: news reports crawling, UGC event recognition, and event attribute extraction. Focusing on Zhejiang province, China, as the test region, a total of 27 cases of collapse events from 637 news reports were collected for 11 prefecture-level cities. The method achieved a recall rate of over 60% and a precision below 35%, indicating its potential for effectively and automatically screening collapse events; however, the accuracy needs to be improved to account for confusion with other urban collapse events, such as bridge collapses. The obtained UGC event inventory is the first open access inventory based on internet news reports, event dates and locations, and collapse co-ordinates derived from unstructured contents. Furthermore, this study provides insights into the spatial pattern of UGC frequency in Zhejiang province, effectively supplementing the statistical data provided by the local government.

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Section: Comparison With Other Geo-hazards Eventsmentioning

confidence: 86%

Section: Study Areamentioning

confidence: 99%

An LLM-Based Inventory Construction Framework of Urban Ground Collapse Events with Spatiotemporal Locations

Hao,

Qi,

et al. 2024

IJGI

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Investigating the internal erosion behavior and microscopic mechanisms of chemically stabilized soil: an experimental study

Zhang,

Zhu,

Tao

et al. 2024

Front. Earth Sci.

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IntroductionInternal erosion triggered by water pipeline leaks seriously threatens the stability of the urban ground. Hangzhou, a city in Zhejiang Province, China, is facing critical challenges due to urban ground collapse (UGC) caused by internal erosion. However, there is a lack of research on the prevention of UGC by improving the internal erodibility of underground soil. Addressing this issue is of utmost importance to ensure the city’s stability and safety. This paper proposes to improve the internal erodibility of typical sandy silt soils with chemical stabilisers.MethodsThe effects of three chemical stabilisers, lignosulphonate (LS), lime (LI), and lignin fibre (LF), on the critical shear stress (τc) and erosion coefficient (kd) of sandy silt soils were investigated, which from Hangzhou, Zhejiang, China, by the hole erosion test (HET) at different mixing amounts and at different conservation times.ResultsThe findings indicate that LF mainly improves the erosion resistance of sandy silt by increasing τc, and the maximum increase is 2.38 times; LI mainly improves the erosion resistance by decreasing kd, and the maximum decrease is 2.18 times. After adding LS, τc and kd did not change significantly. The scanning electron microscope (SEM) test revealed that the inclusion of LF led to the formation of larger agglomerates in the sandy silt soil. The microstructure of sandy silt soil remained dispersed even after adding LS. Various chemical stabilisers used to improve sandy silt soils exhibited distinct erosion mechanisms. Sandy silt soils improved with LF exfoliated into agglomerates, displaying high resistance to erosion. On the other hand, the sandy silt treated with LF still lacks a protective layer and shows minimal improvements in its ability to withstand erosion. In contrast, the LS-amended sandy silt remains stripped with individual soil particles with insignificant changes in erosion resistance.DiscussionThis study can provide a conceptual framework for choosing foundation treatment techniques in future urban development projects.

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Urban Infrastructure Vulnerability to Climate-Induced Risks: A Probabilistic Modeling Approach Using Remote Sensing as a Tool in Urban Planning

Rodríguez-Antuñano,

Barros,

Martínez-Sánchez

et al. 2024

Infrastructures

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In our contemporary cities, infrastructures face a diverse range of risks, including those caused by climatic events. The availability of monitoring technologies such as remote sensing has opened up new possibilities to address or mitigate these risks. Satellite images allow the analysis of terrain over time, fostering probabilistic models to support the adoption of data-driven urban planning. This study focuses on the exploration of various satellite data sources, including nighttime land surface temperature (LST) from Landsat-8, as well as ground motion data derived from techniques such as MT-InSAR, Sentinel-1, and the proximity of urban infrastructure to water. Using information from the Local Climate Zones (LCZs) and the current land use of each building in the study area, the economic and climatic implications of any changes in the current features of the soil are evaluated. Through the construction of a Bayesian Network model, synthetic datasets are generated to identify areas and quantify risk in Barcelona. The results of this model were also compared with a Multiple Linear Regression model, concluding that the use of the Bayesian Network model provides crucial information for urban managers. It enables adopting proactive measures to reduce negative impacts on infrastructures by reducing or eliminating possible urban disparities.

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GIS analysis of urban ground collapse susceptibility: a case study of eastern Hangzhou, China

Cited by 3 publications

References 46 publications

An LLM-Based Inventory Construction Framework of Urban Ground Collapse Events with Spatiotemporal Locations

An LLM-Based Inventory Construction Framework of Urban Ground Collapse Events with Spatiotemporal Locations

Investigating the internal erosion behavior and microscopic mechanisms of chemically stabilized soil: an experimental study

Urban Infrastructure Vulnerability to Climate-Induced Risks: A Probabilistic Modeling Approach Using Remote Sensing as a Tool in Urban Planning

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