• International Journal of Contents
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• 제14권3호
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• pp.53-60
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• 2018

Based on the previous studies on sinkholes and ground subsidence conducted until date, the factors affecting the occurrence of sinkholes can be divided into natural environmental factors and human environmental factors in accordance with the purpose of the study. Furthermore, to be more specific, the human environment can be classified into the artificial type and the social type. In this study, the assessment indices for assessing risks of sinkholes and ground subsidence were developed by performing AHP analysis based on the results of the study by Lee et al. (2016), who selected the risk factors for the occurrence of sinkholes by performing Delphi analysis targeting relevant experts. Analysis showed that the artificial environmental factors were of significance in affecting the occurrence of sinkholes. Explicitly, the underground factors were found to be of importance in the natural environment, and among them, the level of underground water turned out to be an imperative influencing factor. In the artificial environment, the underground and subterranean structures exhibited similar importance, and in the underground structures, the excessive use of the underground space was found to be an important influencing factor. In the subterranean ones, the level of water leakage and the erosion of the water supply and sewage piping system were the influential factors, and in the surface, compaction failure was observed as an imperative factor. In the social environment, the regional development, and above all, the groundwater overuse were found to be important factors. In the managemental and institutional environment, the improper construction management proved to be the most important influencing factor.

• 중소기업융합학회논문지
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• 제6권4호
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• pp.37-43
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• 2016

최근 사회기반시설이 밀집한 도심지에서 싱크홀이 빈번히 발생하고 있다. 무엇보다 대부분의 싱크홀이 시민의 생활영역 주변에서 발생하고 있어, 싱크홀의 주요 발생요인인 도시개발과 지하수관리에 대한 체계적인 대책수립이 요구되고 있다. 따라서 본 연구에서는 싱크홀과 직간접적으로 관련성이 깊은 지형공간정보를 이용하여 연구지역에서 발생한 싱크홀의 위험요인을 분석하고자 하였다. 분석에 사용된 지형공간정보는 싱크홀의 발생원인을 지형학적 관점에서 구축한 정보이며, 정보의 처리와 분석은 GIS를 기초로 한 다양한 공간분석도구를 이용하였다. 연구결과, 지형학적 요인이 싱크홀의 발생원인과 유의미한 관련성이 존재하며, 지하에 설치된 각종 관망과 지하수위의의 이동특성, 기타 지형학적 특성의 관리가 필요함을 파악할 수 있었다. 이와 같은 연구결과는 향후 도시방재분야의 의사결정지원자료로 활용 가능하며, 수문지형학 및 공간모델링분야를 접목한 확장 연구가 필요하다고 사료된다.

• 한국콘텐츠학회논문지
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• 제16권4호
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• pp.65-75
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• 2016

본 연구에서는 잠재적으로 발생 가능한 싱크홀(지반침하)의 위험도 평가를 위한 싱크홀 발생 위험요인을 도출하였다. 위험요인은 자연적 환경, 인위적 환경 그리고 사회적 환경을 구분하고 요인선정을 위하여 전문가를 대상으로 총 2번의 브레인스토밍 과정과 3번의 델파이 분석을 실시하였다. 분석결과 '자연적 환경'은 지상과 지하 환경으로 나누었고, '인위적 환경'은 지하 구조물, 지중 구조물, 지표 특성으로 구분하였다. 그리고 '사회적 환경'은 관리 제도적 환경과 지역개발로 구분하였다. 본 연구결과는 수자원 관리 및 지반관리 등 각 분야 전문가들의 의견이 반영된 결과로써, 싱크홀의 발생 위험도를 산정하기 위한 평가지표를 개발하는데 기초자료로 활용될 수 있을 것으로 기대된다.

• 동굴
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• 제34권35호
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• pp.78-104
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• 1993

Analysis of one sinkhole, the Dodgeville sinkhole, developed in Ordovician dolostones in the Driftless Area of Wisconsin in the Upper Midwest'd Driftless Area reveals homogenous clayey sediment fills reflecting a range of dissolutional processes during the Quaternary or Pre-Quaternary. Granulometric analysis, graphical moments statistics, carbonate minerals, ana sand grain lithology were used to differentiate sinkhole sediment sources and modes of accumulation. Sediments in the dolostone sinkholes developed by dissolution. Sediments contain two major types of sediments : residual redish clay( autogenic sediments) and aeolian silt (allogenic sediments). The massive clay is generated from the weathered dolostone bedrocks as a in situ materials. The loessial silt is mostly derived from transportation of the surrounding surface materials, with some evidences of penetrated deposition. Unlike the collapsed sandstone sinkholes (Oh et al., 1993), dolostone sinkholes reveal homogenous, autogenic clay materials, and a geochemical composition indicative of in situ autogenic karstification. Dolostone sinkhole si1ts (26.9%) and sands (34.9%) are derived from weathered Plattevi1le-Galena dolostones, and contain high carbonate(37.5%), chert (57.2%) and lead ore (3%). Graphical moments statistics for sorting, skewness, and kurtosis indicate that sand grains from dolostones were derived entirely from local bedrock by in situ dissolution. Upper sinkhole sediments are pedagogically very young as carbonate is unleashed. Materials of the sinkhole sediment are definitely inherited from internal dolostones by dissolution and weathering, because not only a granulomatric comparison of dolostone and sandstone sediments demonstrates that they have heterogeneous paticle size distributions, but also 1ithologic analyses displays they differ completely.

• Geomechanics and Engineering
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• 제36권5호
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• pp.441-453
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• 2024

Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

• 한국암반공학회:학술대회논문집
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• 한국암반공학회 2004년도 추계학술발표 논문집
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• pp.171-180
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• 2004

Underground mining causes surface subsidence long after the mining operation had been ceased. Surface subsidence can be in the form of saucer-shaped depression or collapsed chimneys or sinkholes. Sinkhole formations are predominant over shallow-depth room and pillar mines having weak overburden strata. In this study, occurrences of sinkholes due to mining activity are assessed based on local geological conditions and mining parameters using fuzzy reasoning techniques. All input and output parameters are represented with linguistic hedges. Numerous fuzzy rules are developed to relate sinkhole occurrences with input parameters using fuzzy relational matrix. Based on the combined fuzzy rules, possibility of sinkhole occurrences can be ascertained once the geological and mining parameters of any area are known.

• 한국재난정보학회:학술대회논문집
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• 한국재난정보학회 2016년 정기학술대회
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• pp.229-231
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• 2016

제주도에는 170여개의 확인된 동굴이 있으며 그 중에서 천연기념물 동굴이 10개로서 육지의 동굴보다 면적당 천연문화재적 비중이 상대적으로 높은 지역이다. 이러한 특징으로 용암동굴이 세계자연유산으로 등재되는가 하면 세계지질공원으로서 세계적인 랜드 마크로 부각되었다. 그러나 화산분출에 의하여 형성된 용암동굴은 대부분이 지표 가까운 부분에 손등위의 혈맥과 같은 형상으로 한라산을 중심으로 방사형 분포로 형성되어 있어, 장구한 기간 동안 거센 풍화와 지면 응고성 암석의 특성으로 인한 기포와 균열로 수많은 함몰과 붕괴에 직면하고 있다. 이러한 현상을 분석하고 구현하기 위하여 공간정보시스템을 활용하는 방안을 제시한다. 적용결과 땅꺼짐 현상 관련 분석 및 해결방안은 공간정보시스템의 공간정보의 분석기법과 uIT기법에 지질공학적 기법의 융합적 접근이 효과적임을 확인하였다.

• 한국지형학회지
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• 제24권4호
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• pp.75-89
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• 2017

Sinkholes are key karst landforms that primarily evolve through the dissolution of limestone, and it posing a significant threat to roads, buildings, and other man-made structures. This study aims to analyze the area susceptible to sinkhole development using GIS and to identify potential danger area from sinkholes. Eight sinkhole related factors (slope angle, distance to caves, distance to faults, bedrock lithology, soil depth, drainage class, distance to mines, and distance to traffic routes) were constructed as spatial databases with sinkhole inventory. Based on the spatial database, sinkhole susceptibility maps were produced using nearest neighbor distance and frequency ratio models. The maps were verified with prediction rate curve and area under curve. The result indicates that the nearest neighbor distance and frequency ratio models predicted 95.3% and 94.4% of possible sinkhole locations respectively. Furthermore, to identify potential sinkhole danger area, the susceptibility map was compared with population distribution and land use map. It has been found that very highly susceptible areas are along Osipcheon and southeast southwest part of Hajang-myeon and south part of Gagok-myeon of Samcheok-si. Among those areas, it has been identified that potential sinkhole danger areas are Gyo-dong, Seongnae-dong, Jeongna-dong, Namyang-dong and Dogye-eup. These results can be useful in the aspects of land use planning and hazard prevention and management.

• 대한원격탐사학회지
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• 제33권3호
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• pp.267-274
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• 2017

본 연구는 지표면 아래 존재할 수 있는 싱크홀 탐지를 위해 포텐셜 필드법 중 중력학적 방법을 적용하고, 그 가능성을 제시하는데 목적을 둔다. 싱크홀을 대신하여 지표면 아래 1.8 m 깊이에 수조($1.8{\times}0.8{\times}0.8m$)를 매설하였다. 매설된 위치를 중심으로 $12{\times}12m$ 구역에서 1 m 간격으로 Scintrex사의 CG-5 상대중력계(정밀도 0.001 mGal)를 이용하여 중력을 측정하였다. 싱크홀 모형에 대한 이론상 중력효과를 계산하기 위해 3차원 중력모델링을 수행하였다. 그 결과, 중력 측정에 의해 직접 산정된 싱크홀 모형에 대한 중력효과 0.036 mGal은 3차원 중력모델링에 의한 결과 0.024 mGal와 근소한 차이를 보였다. 이것은 본 연구를 위해 사용된 수조 크기와 비슷한 규모의 싱크홀은 상대중력측량에 의해 탐지될 수 있으며, 보다 조밀한 간격으로 중력탐사를 수행한다면 보다 작은 규모의 싱크홀 탐지에도 중력탐사가 충분히 적용 가능할 것으로 판단된다.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2006년도 총회 및 춘계학술발표회
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• pp.97-99
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• 2006

Occurrence of Hwangji pond in Taebaek karst area was investigated in various hydrogeochemical ways and it is found out that there are underground cavern network and sinkholes under the pavement of Taebaek city. It is partially proved by dye tracing method.