• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.255-261
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• 2018

In the field of excavation, it is important to recognize and analyze the factors that cause the ground collapse in order to predict and cope with the ground subsidence. However, it is difficult for field engineers to predict ground collapse due to insufficient knowledge of ground subsidence influence factors. Although there are many cases and studies related to the ground subsidence, there is no manual to help practitioners. In this study, we present the criteria for describing and quantifying the influential factors to help the practitioners understand the existing ground collapse cases and classification of the ground subsidence factors revealed through the research. This study aims to improve the understanding of the factors affecting the ground collapse and to provide a GSRp for the ground subsidence risk assessment which can be applied quickly in the field.

• Journal of Korean Society of Disaster and Security
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• v.10 no.1
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• pp.29-34
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• 2017

This Analyzed case study of measuring displacement, implemented laboratory investigation, and in-situ testing in order to interpret ground subsidence risk rating by excavation work. Since geological features of each country are different, it is necessary to objectify or classify quantitatively ground subsidence risk evaluation in accordance with Korean ground character. Induced main factor that could be evaluated and used to predicted ground subsidence risk through literature investigation and analysis study on research trend related to the ground subsidence. Major factors of ground subsidence might be classified by geological features as overburden, boundary surface of ground, soil, rock and water. These factors affect each other differently in accordance with type of ground that's classified soil, rock, or complex. Then rock could be classified including limestone element or not, also in case of the latter it might be classified whether brittle shear zone or not.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.325-328
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• 2005

To estimate presumptive local ground subsidence area near Abandoned Under ground Coal Mine(AUCM) at Samcheok city in Korea, the geological properties of existing ground subsidence area and the geophysical prospecting data were analyzed using GIS. The electrical resistivity survey and seismic reflection survey database were constructed from investigation reports and factors which are related with ground subsidence such as geological map, topological map, land use map, lineament map, groundwater level, RMR (Rock Mass Rating), mining tunnel map and slope database were constructed also to make a comparative study of each parameters. As a result of the spatial analysis of existing ground subsidence area, 9 major factors causing ground subsidence were extracted and a connection between the structure of underground and the ground subsidence was determined from the analysis of geophysical prospecting data. The estimation of presumptive ground subsidence area was performed using the correlation between the result from neural network analysis of 9 factors and the scrutiny of geophysical prospecting data.

• The Journal of Engineering Geology
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• v.27 no.2
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• pp.153-164
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• 2017

The geological factors for causing ground subsidence are very diverse. It can be affected by any geological or extrinsic influences, and even within the same geological factor, the soil depression impact factor can be determined by different physical properties. As a result of reviewing a large number of papers and case histories, it can be seen that there are seven categories of ground subsidence factors. The depth and thickness of the overburden can affect the subsidence depending on the existence of the cavity, whereas the depth and orientation of the boundary between soil and rock are dominant factors in the ground composed of soil and rock. In case of soil layers, more various influencing factors exist such as type of soil, shear strength, relative density and degree of compaction, dry unit weight, water content, and liquid limit. The type of rock, distance from the main fracture and RQD can be influential factors in the bedrock. When approaching from the hydrogeological point of view, the rainfall intensity, the distance and the depth from the main channel, the coefficient of permeability and fluctuation of ground water level can influence to ground subsidence. It is also possible that the ground subsidence can be affected by external factors such as the depth of excavation and distance from the earth retaining wall, groundwater treatment methods at excavation work, and existence of artificial facilities such as sewer pipes. It is estimated that to evaluate the ground subsidence factor during the construction of underground structures in urban areas will be essential. It is expected that ground subsidence factors examined in this study will contribute for the reliable evaluation of the ground subsidence risk.

• Proceedings of the KSRS Conference
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• v.2
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• pp.717-720
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• 2006

In this study, we predicted locations vulnerable to ground subsidence hazard using fuzzy logic and geographic information system (GIS). Test was carried out at an abandoned underground coal mine in Samcheok City, Korea. Estimation of relative ratings of eight major factors influencing subsidence and determination of effective fuzzy operators are presented. Eight major factors causing ground subsidence were extracted and constructed as a spatial database using the spatial analysis and the probability analysis functions. The eight factors include geology, slope, landuse, depth of mined tunnel, distance from mined tunnel, RMR, permeability, and depth of ground water. A frequency ratio model was applied to calculate relative rating of each factor, and the ratings were integrated using fuzzy membership function and five different fuzzy operators to produce a ground subsidence susceptibility map. The ground subsidence susceptibility map was verified by comparing it with the existing ground subsidences. The obtained susceptibility map well agreed with the actual ground subsidence areas. Especially, ${\gamma}-operator$ and algebraic product operator were the most effective among the tested fuzzy operators.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.553-563
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• 2018

The recent increase of ground subsidence in Korea requires the development of technology for predicting the possibility of ground subsidence. Eighteen parameters affecting the ground subsidence for pre-excavation are classified into 6 categories considering ground types, groundwater, and external factors. Eighteen parameters consists of a table which gives ground subsidence risk ratings for pre-excavation(GSRp). Certain scores are given to these parameters after they are divided into several classes considering the importance and the credibility of parameters and the engineering judgements of the authors. Because of the difference of ground subsidence factors depending on the ground and field conditions, weighting factors for the individual factor and for the each category are multiplied. Weighting factors are calculated from citation frequencies of influencing factors. Ground subsidence risk ratings for pre-excavation can be quantified by considering the individual score of each parameter and weighting factors for the individual factor and for the each category. The suggested GSRp tables obtained from this study are expected to be used by engineers for the estimation of ground subsidence risk ratings for pre-excavation sites.

• Journal of Soil and Groundwater Environment
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• v.28 no.6
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• pp.45-57
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• 2023

To assess land subsidence estimation and preparedness in the Geum River basin, this study applied GIS techniques and identified six key areas. The Geum River basin has experienced an increase in heavy rainfall since late 2010, and four study areas have shown an increase in groundwater levels. Land subsidence primarily occurred from June to September, with higher rainfall years in 2020 and 2023. Approximately 83.6% of land subsidence in Chungcheongbuk-do province occurred in Cheongju-si, mainly attributed to aging sewage pipes. The regions experiencing population growth have likely led to the construction of underground infrastructures and sewer pipes. Thus, it is considered that various factors, including sewage pipe leaks, precipitation, slope gradient, low drainage density, and groundwater level fluctuations, have contributed to land subsidence. Improving land subsidence estimation involves incorporating additional natural factors and human activities.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.148-148
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• 2018

Land subsidence caused by excessive groundwater pumping is a serious hydro-geological hazard. The spatial variability in land use, unbalanced groundwater extraction and aquifer characteristics are the key factors which make the problem more difficult to monitor using conventional methods. This study uses the European Space Agency (ESA) Sentinel satellites to investigate and monitor land subsidence varying with different land covers and groundwater use in the arid Quetta valley, Pakistan. The Persistent Scattering Differential Interferometry of Synthetic Aperture Radar (PS-DInSAR) method was used to develop 28 subsidence interferograms of the study area for the period between 16 Oct 2014 and 06 Oct 2016 using ESA's Sentinel-1 SAR data. The uncertainty of DInSAR result is first minimized by removing the dynamic effect caused by atmospheric factors and then filtered using the radar Amplitude Dispersion Index (ADI) to select only the stable pixels. Finally the subsidence maps were generated by spatially interpolating the land subsidence at the stable pixels, the comparison of DInSAR subsidence with GPS readings showed an R 2 of 0.94 and mean absolute error of $5.7{\pm}4.1mm$. The subsidence maps were also analysed for the effect of aquifer type and 4 land covers which were derived from Sentienl-2 multispectral images. The analysis show that during the two year period, the study area experienced highly non-linear land subsidence ranging from 10 to 280 mm. The subsidence at different land covers was significantly different from each other except between the urban and barren land. The barren land and seasonally cultivated area show minor to moderate subsidence while the orchard and urban area with high groundwater extraction rate showed excessive amount of land subsidence. Moreover, the land subsidence and groundwater drawdown was found to be linearly proportional to each other.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.329-341
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• 2021

This study derives the risk-Influence factors for subway structures, the basis for the transition from the current subway disaster recovery-oriented maintenance system to a preemptive disaster management system, to reduce risk factors for existing subway structures. To apply reasonable risk assessment techniques, risk influence factors for subway underground structures using statistical information(spatial information) and risk influence factors according to frequency of accidents were selected to derive the risk factors. The significant risk factors were verified through ground subsidence (SI: Subsidence Impact)-based correlation analysis. This process confirmed that the subsidence of the ground was a risk influence factor for the subway structure. The main result of this study is that derive the risk factors to improve the risk factors of subway structures due to the rapid increase in disaster risk factors. The derived risk factors that were expected to affect the depression around subway stations and track structures did not show a noticeable correlation, but the cause of this may be that there is no physical connection between them, but on the other hand, the accumulated data may not accurately record the surrounding depression. Accordingly, in order to evaluate the risk of depression around the station and track, more intensive observation and data accumulation around the structure are required.

• Economic and Environmental Geology
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• v.40 no.3 s.184
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• pp.295-306
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• 2007

In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.