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Development and Application of Landslide Analysis Technique Using Geological Structure (지질구조자료를 이용한 산사태 취약성 분석 기법 개발 및 적용 연구)

  • 이사로;최위찬;장범수
    • 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.

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Rock Slope Failure Analysis and Landslide Risk Map by Using GIS (GIS를 이용한 암반사면 파괴분석과 산사태 위험도)

  • Kwon, Hye-Jin;Kim, Gyo-Won
    • Journal of the Korean Geotechnical Society
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    • v.30 no.12
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    • pp.15-25
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    • 2014
  • In this study, types of rock slope failure are analyzed by considering both joint characteristics investigated on previous landslide regions located at northern part of Mt. Jiri and geographic features of natural slopes deduced from GIS. The landslide prediction map was produced by superposing the frequency ratio layers for the six geographic features including elevation, slope aspect, slope angle, shaded relief, curvature and stream distance, and then the landslide risk map was deduced by combination of the prediction map and the damage map obtained by taking account of humanity factors such as roads and buildings in the study area. According to analysis on geographic features for previous landslide regions, the landslides occurred as following rate: 88% at 330~710 m in elevation, 77.7% at $90{\sim}270^{\circ}$ in slope aspect, 93.9% at $10{\sim}40^{\circ}$ in slope angle, 82.78% at grade3~7 in shaded relief, 86.28% at -5~+5 in curvature, and 82.92% within 400m in stream distance. Approximately 75% of the landslide regions belongs to the region of 'high' or 'very high' grade in the prediction map, and 13.27% of the study area is exposed to 'high risk' of landslide.

Comparison of Landslide Susceptibility Analysis Considering the Characteristics of Landslide Trigger Points (산사태 발생지점의 특성을 고려한 취약성 분석 비교)

  • Shin, Hyun Woo;Lee, Su Gon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.2
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    • pp.59-66
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    • 2018
  • This study examined the correlation among topography, forest type, soil and geology in Inje area where landslides occurred during heavy rainfall from July 11 to July 18, 2006 to assess the landslide susceptibility. In order to assess the susceptibility of future landslides, landslides occurred in Inje area were classified into slide type and flow type, and slope angle, aspect, curvature, ridge and valley were extracted from the area. The landslide susceptibility was assessed by applying diameter class, age class, density, and forest type to Bayesianbased LR (Logistic Regression) model and WOE (Weight of Evidence) model, and the fitness of modeling was verified by predict rate curve. As the results of susceptibility assessment, using all landslides without no distintion, it was found that 75% of the LR model and 73% of the WOE model were fit in terms of the top 20% of the landslides. According to slide type and flow type in the top 20% of the landslides, it was found that 71% of the LR model and 69% of the WOE model were fit in terms of the slide type. Whereas, it was found that 86% of the LR model and 82% of the WOE model were fit in terms of the flow type. That is, the results of the LR model showed higher fitness than the results of the WOE model, and the fitness of the flow type was higher than that of the slide type. Consequently, it suggests that it is reasonable to assess and verify the landslide susceptibility according to the types of landslides.

Landslide Susceptibility Mapping and Verification Using the GIS and Bayesian Probability Model in Boun (지리정보시스템(GIS) 및 베이지안 확률 기법을 이용한 보은지역의 산사태 취약성도 작성 및 검증)

  • Choi, Jae-Won;Lee, Sa-Ro;Min, Kyung-Duk;Woo, Ik
    • Economic and Environmental Geology
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    • v.37 no.2
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    • pp.207-223
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    • 2004
  • The purpose of this study is to reveal spatial relationships between landslide and geospatial data set, to map the landslide susceptibility using the relationship and to verify the landslide susceptibility using the landslide occurrence data in Boun area in 1998. Landslide locations were detected from aerial photography and field survey, and then topography, soil, forest, and land cover data set were constructed as a spatial database using GIS. Various spatial parameters were used as the landslide occurrence factors. They are slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil. type, age, diameter and density of wood, lithology, distance from lineament and land cover. To calculate the relationship between landslides and geospatial database, Bayesian probability methods, weight of evidence. were applied and the contrast value that is >$W^{+}$->$W^{-}$ were calculated. The landslide susceptibility index was calculated by summation of the contrast value and the landslide susceptibility maps were generated using the index. The landslide susceptibility map can be used to reduce associated hazards, and to plan land cover and construction.

Analysis of the Controlling Factors of an Urban-type Landslide at Hwangryeong Mountain Based on Tree Growth Patterns and Geomorphology (부산 황령산에서의 수목 성장 및 지형 특성을 이용한 도시 산사태의 발생원인 분석)

  • Choi, Jin-Hyuck;Kim, Hyun-Tae;Oh, Jae-Yong;Kim, Young-Seog
    • The Journal of Engineering Geology
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    • v.21 no.4
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    • pp.281-293
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    • 2011
  • We investigated the causes and characteristics of a landslide at Hwangryeong Mountain, Busan, based on aerial photos, annual precipitation data, rock fracture patterns, and geomorphic features using GIS Software, and a statistical analysis of tilted trees. The analyzed slope shows evidence of a previous slope failure event and the possibility of future failures. Although the NW-SE trending slope was relatively stable until 1975, a large-scale slope failure occurred between 1975 and 1985 due to complex factors, including favorably oriented geologic structures, human activity, and heavy rain. This indicates that a detailed study of geologic structures, slope stability, and rainfall characteristics is important for slope cuttings that could be a major factor and cause of urban landsliding events. The statistic analysis of tilted trees shows a slow progressive creeping type of mass wasting with rock falls oblique to the dip of the slope, with the slope having moved towards the west since 1985. A concentration of tree tilting has developed on the northwestern part of the slope, which could reach critical levels in the future. The analysis of deformed trees is a useful tool for understanding landslides and for predicting and preventing future landslide events.

A Comparison on the Identification of Landslide Hazard using Geomorphological Characteristics (지형특성을 활용한 산사태 위험도 판단을 위한 비교)

  • Cha, Areum
    • Journal of the Korean GEO-environmental Society
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    • v.15 no.6
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    • pp.67-73
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    • 2014
  • Landslide disasters including debris flows are the one of the most frequent natural disasters in Korea, and losses of lives and property damages due to these catastrophic events have been increased every year. Various mitigation programs and related policies have been conducted in order to respond and prepare landslide disasters. Most landslide reduction programs are, however, focused on recovery actions after the disasters and lead to unrealistic consequences to the affected people and their properties. The main objective of this study, therefore, is to evaluate the landslide hazard based on the identification of geomorphological features, which is for the preparedness of the landslide disasters. Two methodologies, SINMAP and vector dispersion analyses are used to simulate those characteristics where landslides are actually located. Results showed that both methods well discriminate geomorphic features between stable and unstable domains. This proves that geomorphological characteristics well describe a relationship with the existing landslide hazard. SINMAP analysis which is based on the consecutive model considering external factors like infiltration is well identify the landslide hazard especially for debris flow type landslides rather than vector dispersion focusing on a specific area. Combining with other methods focusing specific characteristics of geomorphological feature, accurate landslide hazard assessments are implemented.

A study of applying soil moisture for improving false alarm rates in monitoring landslides (산사태 모니터링 오탐지율 개선을 위한 토양수분자료 활용에 관한 연구)

  • Oh, Seungcheol;Jeong, Jaehwan;Choi, Minha;Yoon, Hongsik
    • Journal of Korea Water Resources Association
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    • v.54 no.12
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    • pp.1205-1214
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    • 2021
  • Precipitation is one of a major causes of landslides by rising of pore water pressure, which leads to fluctuations of soil strength and stress. For this reason, precipitation is the most frequently used to determine the landslide thresholds. However, using only precipitation has limitations in predicting and estimating slope stability quantitatively for reducing false alarm events. On the other hand, Soil Moisture (SM) has been used for calculating slope stability in many studies since it is directly related to pore water pressure than precipitation. Therefore, this study attempted to evaluate the appropriateness of applying soil moisture in determining the landslide threshold. First, the reactivity of soil saturation level to precipitation was identified through time-series analysis. The precipitation threshold was calculated using daily precipitation (Pdaily) and the Antecedent Precipitation Index (API), and the hydrological threshold was calculated using daily precipitation and soil saturation level. Using a contingency table, these two thresholds were assessed qualitatively. In results, compared to Pdaily only threshold, Goesan showed an improvement of 75% (Pdaily + API) and 42% (Pdaily + SM) and Changsu showed an improvement of 33% (Pdaily + API) and 44% (Pdaily + SM), respectively. Both API and SM effectively enhanced the Critical Success Index (CSI) and reduced the False Alarm Rate (FAR). In the future, studies such as calculating rainfall intensity required to cause/trigger landslides through soil saturation level or estimating rainfall resistance according to the soil saturation level are expected to contribute to improving landslide prediction accuracy.

Detection of Landslide-damaged Areas Using Sentinel-2 Image and ISODATA (Sentinel-2 영상과 자기조직화 분류기법을 활용한 산사태 피해지 탐지 - 2020년 곡성 산사태를 사례로 -)

  • KIM, Dae-Sun;LEE, Yang-Won
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.253-265
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    • 2020
  • As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.

Analysis of the Effect of Soil Depth on Landslide Risk Assessment (산사태 조사를 통한 토층심도가 산사태 발생 위험성에 미치는 영향 분석)

  • Kim, Man-Il;Kim, Namgyun;Kwak, Jaehwan;Lee, Seung-Jae
    • The Journal of Engineering Geology
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    • v.32 no.3
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    • pp.327-338
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    • 2022
  • This study aims to empirically and statistically predict soil depths across areas affected by landslides. Using soil depth measurements from a landslide area in Korea, two sets of soil depths are calculated using a Z-model based on terrain elevation and a probabilistic statistical model. Both sets of calculation results are applied to derive landslide risk using the saturated infiltration depth ratio of the soil layer. This facilitates analysis of the infiltration of rainfall into soil layers for a rainfall event. In comparison with the probabilistic statistical model, the Z-model yields soil depths that are closer to measured values in the study area. Landslide risk assessment in the study area based on soil depth predictions from the two models shows that the percentage of first-grade landslide risk assessed using soil depths from the probabilistic statistical model is 2.5 times that calculated using soil depths from the Z-model. This shows that soil depths directly affect landslide risk assessment; therefore, the acquisition and application of local soil depth data are crucial to landslide risk analysis.

Open-Ended Response Analysis for University Course Evaluations using Topic Modeling (토픽 모델링을 활용한 대학 강의평가 개방형 응답분석)

  • Su-Hyun Ahn;Sang-Jun Lee
    • Journal of Practical Engineering Education
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    • v.15 no.3
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    • pp.539-547
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    • 2023
  • In recent years, university education has emphasized a learner-centered education model with a change in educational paradigm. This study aims to explore students' diverse opinions and improve the quality of education by analyzing the open-ended responses of university lecture evaluations using topic modeling. To this end, a total of 45,001 open-ended responses based on the results of lecture evaluations from 2017 to 2022 in non-metropolitan universities were divided into majors and liberal arts, and a short-form optimized Biterm Topic Modeling (BTM) analysis was conducted. As a result of the analysis, major lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward questions and discussions", "attitude toward attendance and grading", "attitude toward practical activities and presentations", and "attitude toward communication and collaboration", while liberal arts lectures were divided into "attitude toward non-face-to-face classroom experience", "attitude toward grades and evaluations", "attitude toward attendance and syllabus", "attitude toward academic knowledge and interest", and "attitude toward communication and questions". The results of this study, which analyzed various feedback from students, provide insights that can be used to compare the characteristics of majors and liberal arts courses and improve teaching and learning experiences.