• International Journal of Advanced Culture Technology
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• 제6권4호
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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.

• 한국방재안전학회논문집
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• 제10권1호
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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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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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.

• 지질공학
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• 제27권2호
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• pp.153-164
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• 2017

지반 함몰 위험성에 대한 지질학적 인자는 매우 다양하다. 어떠한 지질학적 요인 또는 외부적인 영향에 의해 영향을 받을 수 있으며 동일한 지질학적 요인 내에서도 여러 가지 다른 물성값에 의해 지반함몰 영향인자가 결정될 수 있다. 다수의 논문 및 연구사례를 검토 한 결과 크게 7가지 범주의 지반함몰 요인이 있음을 알 수 있었다. 공동의 존재 여부에 따라 상재하중의 심도 및 두께가 지반침하에 영향을 줄 수 있고, 토사와 암반으로 구성된 지반에서는 그 경계면의 심도와 배향이 지배적 요소이다. 이 중 토사지반에서는 좀 더 다양한 영향인자로 구성이 되어있는데 토사의 종류, 전단강도, 상대밀도 및 다짐도, 건조단위중량, 함수비, 액성한계가 그것이다. 암반지반에서는 암석의 종류와 주 단열과의 거리 및 RQD가 영향인자로 구성될 수 있으며 수리지질학적 측면에서 접근했을 경우 강우 강도, 하천과의 거리와 심도, 투수계수 및 지하수위 변동이 영향을 줄 수 있다. 외부적인 요소도 지반함몰에 영향을 줄 수 있는데 굴착심도와 흙막이 벽과의 거리, 굴착공사 시 지하수 처리공법, 하수관로 등 인공시설물 존재 유무 등이 이에 해당된다. 최근 도심지의 지하구조물 건설에서 지반함몰 요소를 평가하는 것은 필수적일 것으로 예상된다. 본 연구에서 분석한 지반함몰 영향인자가 지반함몰위험 평가에 도움이 되기를 기대한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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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.

• 지질공학
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• 제28권4호
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• pp.553-563
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• 2018

최근 국내에서 지반함몰의 발생빈도가 증가하고 있으므로 지반함몰 가능성을 사전에 예측할 수 있는 기술개발이 필요하다. 본 연구에서는 굴착 전에 지반함몰에 영향을 미치는 18개의 인자들을 지반의 종류, 지하수, 외부 인자 등을 고려하여 6가지 카테고리로 분류하였다. 18개 인자들은 지반함몰 예측을 위한 굴착 전 적용 가능한 지반함몰 위험등급 분류(GSRp) 도표를 구성하는데, 이러한 영향인자들의 중요도, 신뢰성, 저자들의 공학적 판단 등을 종합적으로 고려하여 등급을 나눈 후 점수를 부여하였다. 지반조건과 현장 상황에 따라 적용되는 지반함몰 영향인자가 다르므로 영향인자 별 가중치와 카테고리 별 가중치가 곱해지게 되는데 가중치는 영향인자들의 인용 빈도수를 기준으로 결정되었다. 지반함몰 영향인자 별점수, 인자별 가중치, 지반조건에 따라 부여되는 가중치 등을 종합하여 계산하면 굴착 전의 지반함몰 위험등급을 정량화 할 수 있다. 본 연구를 통하여 제안된 GSRp 도표는 굴착 전 현장에서 실무자들이 지반의 지반함몰 위험성을 예측하는데 활용할 수 있을 것으로 기대된다.

• 한국지하수토양환경학회지:지하수토양환경
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• 제28권6호
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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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.

• 한국측량학회지
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• 제39권5호
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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.

• 자원환경지질
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• 제40권3호
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• pp.295-306
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• 2007

본 연구에서는 확률기법인 빈도비 모델 (frequency ratio model) 및 지리정보시스템 (Geographic Information System: GIS)의 공간분석기법을 이용하여 강원도 삼척지역 폐탄광 주변의 지반침하 발생 취약지역을 예측하였다. 지반침하에 영향을 주는 요인들을 추출하기 위해 지형도, 지질도, 갱내도, 토지특성도, 시추공 자료, 기 관측된 침하지 자료 등으로부터 공간자료를 구축하였다. GIS 공간분석과 확률기법을 이용하여 지반침하의 주 요인이 되는 8개의 인자를 추출하였고 관측된 침하지역과 8개 인자와의 연관성을 알아보기 위하여 각각의 결정계수($R^2$)를 계산하였다. 빈도비 모델을 적용하여 각인자의 등급별 가중치를 결정한 후, 이를 중첩 분석하여 지반침하 위험 예측도를 작성하였다. 지반침하 위험 예측도를 기존 침하지 위치와 비교 검증한 결과 96.05%의 높은 예측정확도를 나타냈다. 이를 통해 폐탄광 지역에서 GIS와 빈도비 모델을 이용하여 지반침하 위험지역을 정량적으로 예측하는 것이 가능하다고 판단된다.