• 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.

• 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.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 봄 학술발표회 논문집
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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.

• 동굴
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• 제5권6호
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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)

• 대한지리학회지
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• 제49권5호
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• pp.639-655
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• 2014

우발라는 규모, 형성원인, 발달과정, 기하학적 구조, 수문학적 특징, 돌리네와의 관계에서 다른 카르스트 와지와 구분되는 특징을 갖는다. 광덕리 카르스트 와지의 지질, 고도, 곡중분수계, 하천쟁탈의 증거를 분석한 결과는 우발라의 성인적, 과정적, 구조적, 수문학적 특성에 잘 부합한다. 우발라의 지형, 수문적 특성은 와지내부의 가뭄이나 용수부족 문제를 일으키는데, 우발라 내부의 주민들은 지형적 환경적 제약을 극복하기 위한 적극적 대응방식을 보였다. 집중호우에 따른 침수와 산사태를 예방하기 위해 지형을 이용한 배수시설을 설치하고, 우발라 내 외곽에 존재하는 지하수와 용천수에는 우물, 펌프, 관정, 간이상수도와 같은 시설을 설치하여 용수를 취득함으로써 경관을 변화시켰다. 우발라와 같은 카르스트 와지에서의 입지와 토지이용은 지형과 수문특성이라는 환경적 조건과 관련된 것으로 단순히 공간적 규모에 의해 입지가 결정된다는 기존의 관점에 수정이 요구된다.