• Economic and Environmental Geology
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• v.40 no.1 s.182
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• pp.87-101
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• 2007

A variety of informations obtained from satellite image, digital elevation relief map (DEM), borehole logging, televiewer, geophysical prospecting, etc were synthetically analyzed to investigate subsurface geological and structural characteristics and to evaluate geohazard pertinent to fault-damage in the Busan metropolitan city. It is revealed that the geology is composed of the Cretaceous andesitic$\sim$dacitic volcanics, gabbro, and granitoid and that at least three major faults including the Dongrae fault are developed in the study area. Based on characteristics of topography, fault-fractured zone, and isobath maps of the Quaternary sediments and weathered residuals of the basement, the Dongrae fault is decreased in its width and fracturing intensity of damaged zone from south toward north, and the fault is segmented around the area between the Seomyeon and Yangieong junctions. Meanwhile, we drew a geohazard sectional map using the five major parameters that significantly suggest damage intensity of basement by fault, i.e. distance from fault core, TCR, RQD, uniaxial rock strength, and seismic velocity of S wave. The map is evaluated as a suitable method to express the geological and structural characteristics and fault-damaged intensity of basement in the study area. It is, thus, concluded that the proposed method can contribute to complement and amplify the capability of the present evaluation system of rock mass.

• Journal of Korean Society of Disaster and Security
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• v.6 no.1
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• pp.35-45
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• 2013

In recent years, increasing damage due to landslides. So the government is to create a geotechnical hazard map. This study was to evaluate the applicability of the geotechnical hazard map by using 4 years of landslide cases in Seoul and Busan. And the in-situ aseessment has been carried out in test-bad area with specialists. Study has shown dangerous grade in geotechnical hazard map is more dangerous than the actual. Thus we can utilize geotechnical hazrd map in the purpose of the geotechnical hazard preliminary assessment. However, the in-site inspection and evaluation is required for in order to select the hazard area.

• Economic and Environmental Geology
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• v.40 no.3 s.184
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• pp.295-306
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• 2007

In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.

• 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.

• Geomechanics and Engineering
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• v.24 no.5
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• pp.407-418
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• 2021

Due to the complexity of the causes of the sliding mass instabilities, landslide susceptibility and hazard evaluation are difficult, but they can be more carefully considered and regionally evaluated by using new programming technologies to minimize the hazard. This study aims to evaluate the landslide hazard zonation in the Tabriz region, Iran. A fuzzy logic-based multi-criteria decision-making method was proposed for susceptibility analysis and preparing the hazard zonation maps implemented in MATLAB programming language and Geographic Information System (GIS) environment. In this study, five main factors have been identified as triggering including climate (i.e., precipitation, temperature), geomorphology (i.e., slope gradient, slope aspect, land cover), tectonic and seismic parameters (i.e., tectonic lineament congestion, distribution of earthquakes, the unsafe radius of main faults, seismicity), geological and hydrological conditions (i.e., drainage patterns, hydraulic gradient, groundwater table depth, weathered geo-materials), and human activities (i.e., distance to roads, distance to the municipal areas) in the study area. The results of analyses are presented as a landslide hazard map which is classified into 5 different sensitive categories (i.e., insignificant to very high potential). Then, landslide susceptibility maps were prepared for the Tabriz region, which is categorized in a high-sensitive area located in the northern parts of the area. Based on these maps, the Bozgoosh-Sahand mountainous belt, Misho-Miro Mountains and western highlands of Jolfa have been delineated as risk-able zones.