• 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.

• 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.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.03a
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• pp.399-406
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• 1999

Recently, the construction of the several highway bridges in the karst area have encountered severe problems associated with cavities and sinkholes. To solve this problems, it is important to understand the distribution characteristics of cavities in the construction site on limestone area. This paper briefly describes the different types, the distribution control factors and the infill sediment types of lime-cavities in the study area, bridge site in the karst area and propose the effective method of survey design. Cavity system may be divided into two main groups, 1)'slot and cave system'and 2)'sinkhole and cave system'. And the shape, the size and the distribution pattern of cavity are controlled by three main factors - rock type, geological structure and ground water condition. Additionally, infill sediment may be considered as one of the important design factors for foundation design and divided into four types by sediment properties. There are geophysical thechnics and geologic survey and drilling test, etc. by the survey method to interpretate characteristics of cavity system, and this methods are optimally designed at the site investigation stage.

• Journal of the Speleological Society of Korea
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• v.5 no.6
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• pp.31-39
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• 1980

우리나라에는 캠브로-오오도비스(Cambro-Ordovician)기에 속하는 조선누층군의 대석회암통이 넓게 분포되어 있어 석회암지대 특유의 Karst지형을 이루는 곳이 많다. 본 논문의 연구대상지역은 고생대 캠브로-오오도비스기의 조선계 대석회암통에 속하는 옥천지향사의 북부태백산지구를 중심으로 한 석회암 분포지역 중에서 Sinkhole terrain이 비교적 잘 발달되고 해발고도가 상이한 3개 지역을 선정하였다.(중략)

• Journal of the Korean Geographical Society
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• v.49 no.5
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• pp.639-655
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• 2014

Uvala is one of the geographic features which have been discussed very actively in the field of Karst geomorphology, but most researches in Korea have been staying at the level which uvala were discussed from the viewpoint of the Karst cycle. In this study, the geomorphological characteristics of Kwangduck-ri Uvala will be identified on the basis of the various definitions, and the irrigation systems which have been developed during 250 years will be analysed using a number of data, such as interviews, statistical data, maps, air-photos, especially topographical analysis from GIS. It is concluded that the site of Kwangduck-ri Uvala would have shown the genuine history to adapt and overcome the obstacles of harsh karst environment and to make the stable agricultural and irrigation system in the high plateau karst area.