• 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 Korean Geotechnical Society
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• v.39 no.6
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• pp.5-12
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• 2023

Proactive assessment of landslide susceptibility is necessary for minimizing casualties. This study proposes a methodology for classifying the landslide safety factor using a classification algorithm based on machine learning techniques. The high-risk area model is adopted to perform the classification and eight geotechnical parameters are adopted as inputs. Four classification algorithms-namely decision tree, k-nearest neighbor, logistic regression, and random forest-are employed for comparing classification accuracy for the safety factors ranging between 1.2 and 2.0. Notably, a high accuracy is demonstrated in the safety factor range of 1.2~1.7, but a relatively low accuracy is obtained in the range of 1.8~2.0. To overcome this issue, the synthetic minority over-sampling technique (SMOTE) is adopted to generate additional data. The application of SMOTE improves the average accuracy by ~250% in the safety factor range of 1.8~2.0. The results demonstrate that SMOTE algorithm improves the accuracy of classification algorithms when applied to geotechnical data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.431-437
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• 2013

Landslides are caused by earthquakes or heavy rains. Recently the incidence of landslides has been increased. However, it is impossible to predict the occurrence of landslide exactly. The purpose of this research is that subdivide the classes of elements in the landslide management system by using spatial analysis technique and AHP method. The existing landslide management system is only comprised of weighted value the slope elements without weighted value about the slop direction elements. For the accuracy improvement in landslide occurrence point, weighted value about the slope direction should be considered. This research is focused on segmentation in slope direction three categories. If the direction of landslide does not affect the structure, I do not think the subject is worth considerating. Based on these results will discuss the improvements in Landslides management systems. Analysis results, segmentation on the slope and the slope direction are needed. Segmented categories about topography elements will be increase the accuracy of landslides management system. Also, since topography of the elements is only considered, segmentation of different elements is needed.

• Journal of the Korean Geosynthetics Society
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• v.8 no.1
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• pp.1-10
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• 2009

Earthquake induced landslides have caused tens of thousands of deaths and billions of dollars of damage during the last century alone. Determining the potential seismic hazard presented by statically stable slopes is essential for the evaluation of substantial landslide movement during an earthquake. Newmark's method for estimating landslide displacement under dynamic loading was presented and applied to two case studies. A simplified energy-based method was then be developed to estimate the Newmark's displacement.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.55-62
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• 2014

In this study, we investigated the landslides area which occurred in Umyeonsan in 2011 and collected landslide location data. Using this field data with aerial photos and LiDAR data which is obtained before and after disaster event, we analyzed the landslide occurrence frequency per unit area about various topographic characteristics. In case of slope, we compared two kind of slopes which are calculated with Neighborhood algorithm and maximum slope algorithm. Also we used aspect, elevation, profile curvature and planform curvature in topographic analysis of landslide occurrence locations. As a result, the region of which maximum slope is $40^{\circ}-45^{\circ}$ is relatively hazardous in landslide. If the perpendicular surface to the direction of the maximum slope is concave, it is more hazardous than other case.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.248-248
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• 2012

산사태나 토석류와 같은 산지재해가 빈발하고 인명과 재산의 피해가 증가함에 따라 적절한 대책이 시급하게 요구되고 있다. 이런 대책 중에서 신뢰도 높은 산지재해 예, 경보시스템을 구축하는 것은 매우 중요하다. 산림청에서는 산사태 예, 경보 발령을 위한 기준을 마련하고 있으나, 좀더 신뢰도 높은 기준을 필요로 한다고 생각된다. 본 연구에서는 강우분석을 통해서 우리나라의 자연사면에서 토석류, 산사태를 일으키는 강우의 특성을 파악하고, 나아가 산지토사재해 예, 경보시스템에 적절하게 활용될 수 있는 기준을 마련하고자 하였다. 이를 위해서 회귀분석, 판별분석을 적용하여 평가하였고, 보다 개선된 기준으로서 토양우량지수를 제시하였다. 토양우량지수는 강우에 의해 지반이 어느 정도 포화되어 있는가를 계산하여, 토사재해발생의 위험성을 나타낸 것이다. 본 연구에서는 2001년에서 2009년 사이에 충북 제천시 일대의 강우자료를 조사하여 탱크모델에 적용하여 각 탱크에서의 저류량을 계산하여 토양우량지수를 결정하였다. 세 개의 탱크 중에서 두 번째 탱크에서의 저류량 (S2)과 전체 탱크에서의 저류량 (TS)을 이용하여 상위에 랭크된 이력순위를 분석한 결과, S2에서는 산사태가 발생한 2009년 이력이 3번째 높은 수준으로 기록되며, 산사태 미발생의 2007년 강우는 5번째로 기록되었다. 그리고 TS의 경우 2009년 강우가 2002년에 이어 3번째 높은 수준으로 기록되었으며, 2007년 강우는 9번째로 기록되었다. 이러한 결과를 볼 때 토양우량지수의 이력순위는 산지토사재해의 발생을 잘 반영하는 것으로 나타났다. 또한 2011년 발생한 우면산 산사태를 대상으로 토양우량지수를 적용하여 예, 경보시스템의 적용가능성을 판단하였다.

• Journal of Korean Society of societal Security
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• v.2 no.1
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• pp.75-80
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• 2009

The objectives of this research are to develop hazard prediction map S/W for mountain river road. This mountain river road disaster happens by debris flow, landslide, debris accumulation and this cause are locally rainfall and heavy rainfall. System is constructed to GIS base. This research app lied to Kangwondo. We developed protocol to analyze calamity danger in mountain district area and examined propriety system. Furthermore examined the DB required and expression plan for hazard map creation SW construction by mountain rivers road.

• 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.

• Journal of Korean Society of Disaster and Security
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• v.15 no.3
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• pp.31-40
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• 2022

Domestic disaster risk maps are mainly produced and studied as a single disaster map by grid unit and disaster type. In particular, it is necessary to present an evaluation method of the disaster risk map that is more suitable for the relevant facility (local road) in order to utilize the work of practitioners who are mainly in charge of facility maintenance. In this study, an evaluation method was presented to evaluate the risk with a focus on local roads by using the landslide risk map and debris flow risk map provided by the Korea Forest Service. In addition, the risk was evaluated and verified for the provinces located in Gangwon-do. As a result of the evaluation, it was possible to evaluate the risk of grades 1 to 5 for 1,513 evaluation sections in the evaluation section with a total length of 234.59 km.

• Journal of Environmental Policy
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• v.12 no.3
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• pp.21-47
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• 2013

The aim is to analysis landslide vulnerability in Inje, Korea, using GCI(Geospatial Correlative Integration) and probability rainfalls based on geographic information system (GIS). In order to achieve this goal, identified indicators influencing landslides based on literature review. We include indicators of exposure to climate(rainfall probability), sensitivity(slope, aspect, curvature, geology, topography, soil drainage, soil material, soil thickness and soil texture) and adaptive capacity(timber diameter, timber type, timber density and timber age). All data were collected, processed, and compiled in a spatial database using GIS. Karisan-ri that had experienced 470 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data, while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 3-day cumulative rainfalls of 449 mm. Results show that number of slope has comparatively strong influence on landslide damage. And inclination of $25{\sim}30^{\circ}C$, the highest correlation landslide. Improved previous landslide vulnerability methodology by adopting GCI. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing landslide mitigation policies.