• Journal of the Korean Geographical Society
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• v.40 no.1 s.106
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• pp.126-152
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• 2005

In recent years, there are some confusions related to the definition and existence of mountain ranges, which have been described in current geography text books. We contend that these confusions came from the lack of understanding on the geomorphological processes that form the mountain system in Korea. This research attempts to clarify the definition of mountain ranges and offer geological and geomorphological explanations about the formation of them. Based on the analyses of the social and cultural causes underlying the recent debates on the existence of mountain ranges, we tried to identify the relationships among the definition of mountain ranges, geological structure of Korea, and the forming processes of mountain ranges. The current and past mountain range maps were compared with geological structures, geological maps, surface curvature, and hill shade maps. The latter two maps were derived from a Digital Elevation Model of the Korean Peninsular. The results show that we are able to prove the existence of most mountain ranges, which provides a useful framework to understand the geological evolution of Korean peninsular and formation of mountainous landscape of Korea. In terms of their morphological continuity and genesis, however, we identified five different categories of mountain ranges: 1) Uplift mountain ranges(Hamkyeong Sanmaek, Nangrim Sanmaek, Taebaek Sanmaek), which were formed by the uplift processes of the Korean Peninsular during the Tertiary; 2) Falut mountain ranges(Macheonryeong Sanmaek, Sobaek Sanmaek, Buksubaek Sanmaek), whirh were directly related to the uplift processes of the Korean Peninsular during the Tertiary; 3) Trust mountain ranges(Jekyouryeong Sanmaek, Kwangju Sanmaek, Charyeong Sanmaek, Noryeong Sanmaek), which were formed by the intrusion of granite and consequent orogenic processes during the Mesozoic era; 4) Drainage divide type mountain ranges, which were formed by the erosion processes after the uplift of Korean Peninsular; 5) Cross-drainage basin type mountain ranges (Kangnam Sanmaek, Eunjin Sanmaek, Myelak sanmaek), which were also formed by the erosion processes, but the mountain ranges cross several drainage basins as connecting mountains laterally We believe that the current social confusions related to the existence of mountain ranges has partly been caused by the vague definition of mountain ranges and the diversity of the forming processes. In order to overcome theses confusions, it is necessary to characterize the types of them according the genesis, the purpose of usages and also the scale of maps which will explains the mountain systems. It is also necessary to provide appropriate educational materials to increase the general public's awareness and understanding of geomorphological processes.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.301-312
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• 2013

Landslides are caused by complex interaction among a large number of interrelated factors such as topography, geology, forest and soils. In this study, a comparative study was carried out using fuzzy relationship method and artificial neural network to evaluate landslide susceptibility. For landslide susceptibility mapping, maps of the landslide occurrence locations, slope angle, aspect, curvature, lithology, soil drainage, soil depth, soil texture, forest type, forest age, forest diameter and forest density were constructed from the spatial data sets. In fuzzy relation analysis, the membership values for each category of thematic layers have been determined using the cosine amplitude method. Then the integration of different thematic layers to produce landslide susceptibility map was performed by Cartesian product operation. In artificial neural network analysis, the relative weight values for causative factors were determined by back propagation algorithm. Landslide susceptibility maps prepared by two approaches were validated by ROC(Receiver Operating Characteristic) curve and AUC(Area Under the Curve). Based on the validation results, both approaches show excellent performance to predict the landslide susceptibility but the performance of the artificial neural network was superior in this study area.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.95-105
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• 2003

A novel reference point detection method is proposed by exploiting tile gradient probabilistic model that captures the curvature information of fingerprint. The detection of reference point is accomplished through searching and locating the points of occurrence of the most evenly distributed gradient in a probabilistic sense. The uniformly distributed gradient texture represents either the core point itself or those of similar points that can be used to establish the rigid reference from which to map the features for recognition. Key benefits are reductions in preprocessing and consistency of locating the same points as the reference points even when processing arch type fingerprints. Moreover, the new feature extraction method is proposed by improving the existing feature extraction using filterbank method. Experimental results indicate the superiority of tile proposed scheme in terms of computational time in feature extraction and verification rate in various noisy environments. In particular, the proposed gradient probabilistic model achieved 49% improvement under ambient noise, 39.2% under brightness noise and 15.7% under a salt and pepper noise environment, respectively, in FAR for the arch type fingerprints. Moreover, a reduction of 0.07sec in reference point detection time of the GPM is shown possible compared to using the leading the poincare index method and a reduction of 0.06sec in code extraction time of the new filterbank mettled is shown possible compared to using the leading the existing filterbank method.

• Journal of the Korea Concrete Institute
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• v.19 no.1
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• pp.91-102
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• 2007

Through lessons in recent earthquakes, the bridge engineering community recognizes the need for new seismic design methodologies based on the inelastic structural performance of RC bridge structures. This study represents results of performance-based fragility analysis of reinforced concrete (RC) bridge. Monte carlo simulation is performed to study nonlinear dynamic responses of RC bridge. Two-parameter log-normal distribution function is used to represent the fragility curves. These two-parameters, referred to as fragility parameters, are estimated by the traditional maximum likelihood procedure, which is treated each event of RC bridge pier damage as a realization of Bernoulli experiment. In order to formulate the fragility curves, five different damage states are described by two practical factors: the displacement and curvature ductility, which are mostly influencing on the seismic behavior of RC bridge piers. Five damage states are quantitatively assessed in terms of these seismic ductilities on the basis of numerous experimental results of RC bridge piers. Thereby, the performance-based fragility curves of RC bridge pier are provided in this paper. This approach can be used in constructing the fragility curves of various bridge structures and be applied to construct the seismic hazard map.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.385-394
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• 2001

There are serious damage of people and properties every year due to landslides that are occurred by heavy rain. Because these phenomena repeat and the heavy rain is not an atmospheric anomaly, the counter plan becomes necessary. The study area, Ulsan, is one of the seven metropolitan, and largest cities of Korea and has many large facilities such as petrochemical complex and factories of automobile and shipbuilding. So it is necessary assess the landslide hazard potential. In the study. the three steps of landslide hazard assessment techniques such as susceptibility, possibility, and risk were performed to the study area using GIS. For the analyses, the topographic, geologic, soil, forest, meteorological, and population and facility spatial database were constructed. Landslide susceptibility representing how susceptible to a given area was assessed by overlay of the slope, aspect, curvature of topography from the topographic DB, type, material, drainage and effective thickness of soil from the soil DB, lype age, diameter and density from forest DB and land use. Then landslide possibility representing how possible to landslide was assessed by overlay of the susceptibility and rainfall frequency map, Finally, landslide risk representing how dangerous to people and facility was assessed by overlay of the possibil. ity and the population and facility density maps The assessment results can be used to urban and land use plan for landslide hazard prevention.

• Spatial Information Research
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• v.10 no.2
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• pp.247-261
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• 2002

There are much damage of people and property because of heavy rain every year. Especially, there are problem to major facility such as dam, bridge, road, tunnel, and industrial complex in the ground stability. So the counter plan for landslide or ground failure must be necessary In the study, the technique of regional landslide susceptibility assessment near the Ulsan petrochemical complex and Kumgang railway bridge was developed and applied using GIS. For the assessment, the geological structures such as bedding and fault were surveyed and the geological structure, topographic, soil, forest, and land use spatial database were constructed using CIS. Using the spatial database, the factors that influence landslide occurrence, such as slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil, type, age, diameter and density of forest, and land use were calculated or extracted from the spatial database. For application of geological structure, the geological structure line and fault density were calculated. Landslide susceptibility was analyzed using the landslide-occurrence factors by probability method that is summation of landslide occurrence probability values per each factors range or type. The landslide susceptibility map can be used to assess ground stability to protect major facility.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.3
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• pp.136-146
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• 2013

This study has specified terminology for mountain ridgeline, and organized the present condition of Korean mountain ridgeline and empirical management measures of Beakdudeagan and Jeongmeak. Moreover, based on previously published paper maps, mountain map, and numerical maps, this study has used GIS to reorganize Jeongmaek of Korea, including Hanbukjeongmaek, Hannamjeongmaek, and Gumbukjoengmaek. To ensure accuracy, DEM, Shaded Relief Image, gradient, curvature, and aspect have been analyzed from recent numerical maps. On extraction process, this study analyzes more specifically the results, previous Beakdudaegan is modified and new Jeongmaeks have been extracted. Moreover, for analyzing natural environment of surrounding of major mountain ridgeline, ecological zoning grade of mountain ridgeline is analyzed. With the analyzed result, domestic and foreign mountain ridgeline management policy is suggested, and environmental impact assessment method for major mountain ridgeline development is also suggested. In this study, Baekdudaegan and its Jeongmaek are organized and analyzed. With the results, this study suggested political linkage of mountain ridgelines and guidelines for environmental impact assessment of ridgeline development.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.327-335
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• 2020

The method of selecting an existing flood hazard area via a numerical model requires considerable time and effort. In this regard, this study proposes a method for selecting flood vulnerable areas through topographic analysis based on a surface runoff mechanism to reduce the time and effort required. Flood vulnerable areas based on runoff mechanisms refer to those areas that are advantageous in terms of the flow accumulation characteristics of rainfall-runoff water at the surface, and they generally include lowlands, mild slopes, and rivers. For the analysis, a digital topographic map of the target area (Seoul) was employed. In addition, in the topographic analysis, eight topographic factors were considered, namely, the elevation, slope, profile and plan curvature, topographic wetness index (TWI), stream power index, and the distances from rivers and manholes. Moreover, receiver operating characteristic analysis was conducted between the topographic factors and actual inundation trace data. The results revealed that four topographic factors, namely, elevation, slope, TWI, and distance from manholes, explained the flooded area well. Thus, when a flood vulnerable area is selected, the prioritization method for various factors as proposed in this study can simplify the topographical analytical factors that contribute to flooding.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.61-89
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• 2020

The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.