• International Journal of Contents
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• v.14 no.3
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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.

• Journal of Convergence Society for SMB
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• v.6 no.4
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• pp.37-43
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• 2016

Sinkholes happen in increasingly higher frequency in downtown areas with a concentration of social infrastructure these days. Most sinkholes occur around the living areas of citizens, which calls for a systematic countermeasure plan for urban development and underground water management, which are parts of the main causes of sinkholes. This study thus set out to analyze the risk factors of sinkholes in the subject area by using geospatial information deeply connected to sinkholes both directly and indirectly. The geospatial information used in analysis was obtained by examining the causes of sinkholes from a topographical perspective. Collected data were treated and analyzed with a range of spatial analysis tools based on GIS. The findings show that topographical factors had significant relations with sinkhole causes and raise a need to manage all kinds of pipe networks underground, the movement characteristics of underground water levels, and other topographical features. The findings may serve as data to support decision-making processes in the field of urban disaster prevention and call for extensive research to incorporate hydro-geomorphology and spatial modeling.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.65-75
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• 2016

This research was started in order to recognize the necessity of systematic and scientific approach to sinkholes, and to imply from an empirical point of view that a detailed evaluation method and measure for technique should be devised. As the result drew the risk factors that cause sinkholes by reflecting the opinions of water resources and ground experts, this research is expected to contribute to the development of a more systematic and pre-preventive evaluation index by preparing a countermeasure against sinkholes. In the future, it is necessary to develop an evaluation index toward the risk factors of sinkholes, in order to establish a scientific basis and objectivity that can determine priority, by subdividing the decision-making process that is required for preparing a countermeasure against sinkholes. In addition, a detailed methodology and related technique to measure each evaluation index should be continued to be discussed, in order to review the applicability of evaluation indices on actual sites.

• Journal of the Speleological Society of Korea
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• v.34 no.35
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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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• v.36 no.5
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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.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2004.10a
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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.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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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.

• Journal of The Geomorphological Association of Korea
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• v.24 no.4
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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.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.267-274
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• 2017

The purpose of this research was to develop and present methods to detect sinkholes which can exist underneath the surface of the ground. First, we buried a water tank with dimensions $1.8{\times}0.8{\times}0.8m$ at a distance of 1.8 m from the surface. This played the role of the sinkhole. Secondly, we created a square zone with sides 12 meters away from the buried water tank. Within this zone, we measured the gravity at 1-meter intervals using a Scintrex CG5 relative gravimeter with a resolution of 0.001 mGal. Additionally, we performed three-dimensional (3-D) gravity modeling to calculate the theoretical values of the relative gravity around our model sinkhole. The resulting values for the relative gravity around the sinkhole depended on the method used. The measured effect of gravity was 0.036 mGal and the effect calculated using 3-D modeling was 0.024 mGal. Our results suggest that sinkholes that are similar in size to the water tank used in this study can be detected using relative gravity surveys. Smaller sinkholes can be detected by reducing the intervals between the relative gravity measurements.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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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.