• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.81-90
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• 2005

Based on the landslide hazard scoring system of Korea Forest Research Institute, a GIS model for predicting landslide hazards was developed. The risk of landslide hazards was analyzed as the function of 7 environmental site factors for the terrain, vegetation, and geological characteristics of the corresponding forest stand sites. Among the environmental factors, slope distance, relative height and shapes of slopes were interpreted using the forestland slope interpretation module developed by Chung et al. (2002). The program consists of three modules for managing spatial data, analyzing landslide hazard and report-writing, A performance test of the model showed that 72% of the total landslides in Youngin-Ansung landslides area took place in the highly vulnerable zones of grade 1 or 2 of the landslide hazard scoring map.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.69-81
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• 2008

Landslide researches are divided to a method of interrelationship for various factors, method of predicting landslide possibility, and method of estimating landslide risk which are occurring landslides in the natural slope. Most of landslides occurred in natural slope are caused by a heavy rainfall in summer season. Weathered soil layer located in upper side of rock mass was occurred. As well as, they are announced to have an influence to geometry, geology, soil characteristics, and precipitation in the natural slope. In order to investigate and interpret the variety of landslides from field investigation to risk analysis, landslide analysis process due to geotechnical and geological opinions are systematically demanded. In this research, the study area is located in Macheon area, Gyeongsangnam-do and performed the landslide investigation. From the results of landslide investigation and analysis, optimized standard model based on natural landslide is proposed to high technical method of landslide investigation and interpretation.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.54-66
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• 2006

Korea Forest Service made the landslide hazard map for all mountainous districts over the country in May 2005. In this study, we selected landslide areas occurred in Jeonbuk from 02 August 2005 to 03 August 2005 as the study area. We extracted landslide areas using images taken by PKNU 3 System, which was developed by PE&RS Laboratory in Dept. of Satellite Information Sciences, Pukyong National University and verified the accuracy of landslide hazard map by overlaying landslide hazard areas extracted by PKNU 3 images. And we analyzed characteristics of an altitude, a gradient, an inclined direction, a flow length, a flow accumulation for landslide areas using mountainous terrain analysis and Stream Network analysis of ArvView 3.3. As a result of this study, it is necessary to adjust the unitage(%) by the class and to modify and improve the score table for prediction of landslide-susceptible area forming the foundation of making the landslide hazard maps.

• The Journal of Engineering Geology
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• v.30 no.3
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• pp.315-325
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• 2020

This study was performed to develop a model to predict landslides and determine the variable importance of landslides susceptibility factors based on the probabilistic prediction of landslides occurring on slopes along the road. Field survey data of 30,615 slopes from 2007 to 2020 in Korea were analyzed to develop a landslide prediction model. Of the total 131 variable factors, 17 topographic factors and 114 geological factors (including 89 bedrocks) were used to predict landslides. Automated machine learning (AutoML) was used to classify landslides and non-landslides. The verification results revealed that the best model, an extremely randomized tree (XRT) with excellent predictive performance, yielded 83.977% of prediction rates on test data. As a result of the analysis to determine the variable importance of the landslide susceptibility factors, it was composed of 10 topographic factors and 9 geological factors, which was presented as a percentage for each factor. This model was evaluated probabilistically and quantitatively for the likelihood of landslide occurrence by deriving the ranking of variable importance using only on-site survey data. It is considered that this model can provide a reliable basis for slope safety assessment through field surveys to decision-makers in the future.

• Defense and Technology
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• no.3 s.169
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• pp.60-67
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• 1993

박격포는 고포물선 탄도 특성 때문에 산악지형이 많은 우리 실정에 매우 적합할 뿐만 아니라 현대전에서 중시되고 있는 시가지 전투에서도 매우 효과적이므로 국내에서도 지속적인 연구개발 투자를 통해서 군의 전투력을 향상시켜야 할 것입니다. 나아가 기동성 향상을 위한 차량탑재 및 자주화와 첨단 탄약개발등에도 많은 관심을 기울여야 할 것입니다

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2018.10a
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• pp.212-212
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• 2018

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.161-161
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• 2011

지진, 산사태, 액상화 등의 지질재해 예측을 위한 지역적 지반특성을 규명하기 위해서 지질도 또는 지형도를 이용하여 간접적인 방법이 사용되기도 한다. DEM에서 추출한 경사도는 지반분류 시 하나의 기준으로 사용되어질 수 있고, 이때 DEM의 해상력에 따라 그 결과가 다르게 산출될 수도 있다. 이번 연구에서는 DEM의 해상력에 따라 우리나라 일부지역의 지반분류 결과에 어떤 영향을 미치는지 살펴보았다. 각기 다른 해상도의 DEM을 적용하여 우리나라 동남부 지형을 경사도 기준으로 지반분류한 후 그 면적차이를 해상도별로 비교한 결과, 지반분류 C 지역의 면적 변화가 가장 뚜렷하였다. $V_s30$ 범위로 분류한 결과에서는 180 m/sec 이하의 지역에서 해상도별로 가장 큰 변화가 있었다. 고해상도에서는 지반분류 B와 E의 지역에서 면적이 저해상도 보다 크게 산출되는 경향이 있었고, 저해상도에서는 지반분류 C와 D 지역의 면적이 고해상도 보다 크게 산출되는 경향이 있었다. 이는 DEM의 해상도가 낮아질수록 각기 다른 지반정보를 함유한 작은 셀이 큰 셀로 만들어지는 과정에서 평균화되는 지반정보가 과대평가 또는 저평가되었기 때문이다. 연구지역 내 시추지역의 지반과 지반분류 결과를 비교하면 해상도별로 78%~52%까지 일치하였고, 고해상도에서 일치율이 더 높았다. 지형의 변화가 심하고 인구나 산업시설이 밀집된 재해 고위험군 지역은 고해상도의 지도를 이용하고, 지형의 변화가 없거나 단단한 지반의 지역은 재해가 상대적으로 작아서 저해상도의 사용으로 자료처리 시간의 효율성을 증대시키는 방안도 생각할 수 있다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.303-311
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• 2002

Recently, the research that analyze topography parameters that need in hydrology analysis using GIS techniques is achieved. DEM that is used in topography analysis can be constructed effectively using contour data of digital map. Therefore, DEM's applicability is increasing gradually in several fields. In this study, DEM of 20∼l00m grid size was applied PYONGCHANG river and JUBANG river basin to analyze what effect DEM grid size causes about slope and drainage watershed at topography parameter extraction. This study drew a regression equation about slope change by DEM grid size. As a result, according as DEM grid size increases, slope decreases, and basin area could know that is not change almost.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.305-305
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• 2020

2019년 10월에 발생한 태풍 미탁은 강원도 삼척시 근덕면 궁촌리 기준 시간당 최대 129mm/hr, 누적강수량 488.5mm를 기록하며 폭우와 강풍, 홍수, 토석류 및 산사태로 사망 13명, 실종 2명, 이재민 910세대 1,442명의 인명피해와 공공시설 1,835건, 사유시설 3,700건 등의 재산 피해가 발생하였다. 한편 Hyper KANAKO 모형은 일본에서 개발된 토석류 수치 모델로 오픈소스인 QGIS와 연동되어 도구의 형태로 사용할 수 있어 사용자에게 편리함을 제공하고 토석류 해석 시 침식 및 퇴적작용의 해석이 가능하다. 1차원의 지형(계류)과 2차원의 지형(퇴적부)의 지반설정과 사방댐의 종류(Closed, Slit, Landslide) 및 개수, 위치, 높이 등을 쉽게 조절할 수 있다는 장점이 있다. 또한, DEM을 기반으로 변환 프로그램을 사용하여 구축한 자료인 LP(Laser Profiler) 데이터를 바탕으로 3차원의 지형을 볼 수 있어 2차원의 지형보다 사용자의 직관적인 해석이 가능하다. 본 연구에서는 QGIS와 Hyper KANAKO를 이용하여 태풍 미탁으로 토석류 피해가 발생한 강원도 삼척시 신남지역을 대상으로 DEM과 LP 데이터를 구축하고 수치모델링을 실시하여 현장조사 결과와 비교분석 하였다.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.827-835
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• 2023

Drone light detection and ranging (LiDAR) is a state-of-the-art surveying technology that enables close investigation of the top of the mountain slope or the inaccessible slope, and is being used for field surveys in mountainous terrain. To build topographic information using Drone LiDAR, a preprocessing process is required to effectively separate ground and non-ground points from the acquired point cloud. Therefore, in this study, the point group data of the mountain topography was acquired using an aerial LiDAR mounted on a commercial drone, and the application and accuracy of the cloth simulation filtering algorithm, one of the ground separation techniques, was verified. As a result of applying the algorithm, the separation accuracy of the ground and the non-ground was 84.3%, and the kappa coefficient was 0.71, and drone LiDAR data could be effectively used for landslide field surveys in mountainous terrain.