• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.2001-2005
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• 2006

우리나라는 매년 집중호우로 인한 산사태로 인해 인적, 물질적 피해를 일으킨다. 반복적인 산사태의 피해를 방지 하기위해서는 산사태 예측 시스템이 필요하다. 본 연구에서는 안성시를 대상으로 GIS와 RS 자료를 활용하여 산사태 위험지를 분석하고자 Logistic 회귀분석 방법과 AHP 기법을 이용하였다. Logistic 회귀분석과 AHP 기법에는 6개의 인자(경사, 경사향, 고도, 토양배수, 토심, 토지이용)를 사용하여, 7등급으로 산사태 위험도를 분류하였다. Logistic 회귀분석 방법과 AHP 기법을 이용한 산사태 위험지도를 표본 자료와 비교하면 산사태가 발생한 표본에서 산사태 위험성이 높은(1-2등급)지역이 Logistic 회귀분석에서는 46.1% AHP 기법은 48.7%로 분류되어 AHP 기법이 분류도가 높다고 분석 되었다. 하지만 Logistic 회귀분석과 AHP 기법은 서로 분석 과정의 차이를 가지고 있기 때문에 Logistic 회귀분석과 AHP기법을 적용한 결과에 동일 가중치를 부여한 후 7개 등급으로 재분류(reclass)하여 산사태 위험지역을 추출 할 수 있는 방법론을 제시하였다. 그 결과 산사태가 발생한 표본에서 1-2등급지역이 58.9%로 분석되어 분류정확도를 높일 수 있었다.

• Journal of Korean Society of Forest Science
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• v.97 no.3
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• pp.332-339
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• 2008

This study was carried out to develop the score table for prediction of landslide hazard in Gyeongsangbuk-Do province. It was studied to 172 places landslided in 23 cities and counties of Gyeongsangbuk-Do province. An analyze of the score table for landslide hazard was carried out through the multiple statistics of quantification method (I) by the computer. Factors effected to landslide occurrence quantity were shown in order of slope position, slope length, bedrock, aspect, forest age, slope form and slope. As results of the development of score table for prediction of landslide hazard in Gyeongsangbuk-Do province, total score range was divided that 107 under is stable area (IV class), 107~176 is area with little susceptibility to landslide (III class), 177~246 is area with moderate susceptibility to landslide (II class), above 247 area with severe susceptibility to landslide (I class).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.861-867
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• 2006

The objective of this study is to analyze the landslide hazard areas by combining LRA (Lgistic Regression Analysis) and AHP (Analytic Hierarchy Program) methods with Remote Sensing and GIS data in Anseong-si. In order to classify landslide hazard areas of seven levels, six topographic factors (slope, aspect, elevation, soil drain, soil depth, and land use) were used as input factors of LRA and AHP methods. As results, high-risk areas for landslide (1 and 2 levels) by LRA and AHP of its own were classified as 46.1% and 48.7%, respectively. A new method by applying weighting factors to the results of LRA and AHP was suggested. High-risk areas for landslide (1 and 2 levels) form the new method was classified as 58.9%.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.239-239
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• 2021

최근 기후변화로 인해 국지성 집중호우와 태풍의 발생빈도가 증가하고 있다. 특히 우리나라 국토는 전체면적 중 산지면적이 63%에 해당하여 산지에서 발생하는 산사태와 토석류에 취약한 실정이다. 이러한 피해를 사전에 예방·대비하기 위해 국내·외에서는 재해지도를 제작하여 관리하고 있지만 대부분의 재해지도는 격자형식으로 제작되어 있어 실무자들이 활용하기에는 다소 어려움이 있다. 따라서 본 연구에서는 산지재해에 취약한 강원도 강릉시 지방도를 대상으로 산림청에서 개발한 산사태위험지도와 토석류 위험지도를 중첩하여 복합재해지도를 제작하였다. 먼저 산사태위험지도에 유역의 개념을 도로에 적용하고서 지방도로를 200m 간격으로 분할하여 도로 중심으로 유역을 제작하였으며, 해당 유역에 산사태위험면적과 토석류위험면적 값을 이용하여 도로의 등급을 1등급(매우 위험) ~ 5등급(매우 안전)으로 분류하였다. 또한 복합재해지도 결과의 검증을 위해 SINMAP모형을 이용하여 오차율을 비교분석한 결과 15% 이내인 것으로로 나타났다. 본 연구는 복합재해에 대비 할 수 있는 유역의 개념을 적용한 재해지도를 제작하며 도로관리자의 숙련도에 상관없이 재해지도를 쉽게 이해하고 활용 할 수 있을 것으로 판단된다.

• 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.

• 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.

• Journal of Korean Society of Forest Science
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• v.103 no.2
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• pp.233-239
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• 2014

This study was carried out to propose the criteria for the prediction of landslide occurrence through analysis the influence of each factor by using the quantification theory. The results obtained from this study are summarized as follows. From a stepwise regression analysis between the landslide area($m^2$) and environmental factors, the factors strongly affecting the landslide sediment($m^2$) were the Parents rock (igneous), cross slope(complex), coniferous forests (forest type) and slope gradient ($21{\sim}30^{\circ}$). According to the range, it was shown in order of Cross slope (0.2922), Parents rock (0.2691), Forest type (0.2631) and Slope gradient (0.2312). The range of prediction score of landslide occurrence has been distributed between score 0 and score 1.0556, the median value was score 0.5278. The prediction for class I was over 0.7818, for class II was 0.5279 to 0.7917, for class III 0.2694 to 0.5278 and for class IV was below 0.2693. The prediction on landslide occurrence appeared relatively high accuracy rate as 72% for class I and II. Therefore, this score table for landslide will be very useful for judgement of dangerous slope.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.291-293
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• 2010

최근 발생하고 있는 국지성 집중호우 및 돌발홍수로 인해 강원도와 경상북도 등을 중심으로 산지하천유역의 산사태 피해가 급증하고 있으며 발생면적은 연평균 402ha에 이르며 연평균 피해면적은 80년대에 비해 2000년대 들어 3배 이상 증가한 것으로 보고 되고 있다. 본 연구에서는 산지하천 유역의 토사유출재해 취약성 분석을 위해 GEOMania GMMap 기반으로 구동되는 산사태 분석모듈(HyGIS-Landslide)을 개발하였다 HyGIS-Landslide는 산림청의 산사태 위험지도 제작에 사용된 위험지역 평가기준을 참조하였으며 DEM을 이용하여 경사인자 및 사면인자를 생성하고 수치지질도, 수치임상도 산림입지도 등과의 연산을 통해 위험등급에 대한 분류결과를 제시한다. 또한, 과거 산사태 발생지역에 대한 맵핑 경과가 존재하는 경우 산사태 위험지역 분류결과를 과거 사상과 중첩하여 분류정확도를 확인할 수 있도록 제작되었다.

• Journal of Korean Society of Forest Science
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• v.97 no.3
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• pp.326-331
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• 2008

This study was carried out to analyze the characteristics of each factors by using the quantification theory(I) for prediction of landslide hazard area. The results obtained from this study were summarized as follows; The stepwise regression analysis between landslide sediment ($m^3$ ) and environmental factors, factors affecting landslide sediment ($m^3$ ) were high in order of mixed (forest type), < 15 cm(soil depth), 801~1,200 m (altitude), $31{\sim}40^{\circ}$ (slope gradient), 46 cm < (soil depth), 1,201 m < (altitude) and s(aspect). According to the range, it was shown in order of soil depth (0.3784), altitude (0.2876), forest type (0.2409), slope gradient (0.1728) and aspect (0.1681). The prediction of landslide hazard area was estimated by score table of each category. The extent of prediction score was 0 to 1.2478, and middle score was 0.6239. Class I was over 1.1720, class II was 0.7543 to 0.1719, class III was 0.4989 to 0.7542 and class IV was below 0.4988.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.17-24
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• 2016

At present, summer cloudburst and local torrential rainfalls have increased in this country, because of climatic change. Therefore, studies on prevention of soil loss have been actively proceeded, and Korea Forest Service has offered landslide hazard map. Landslide hazard map divides risks into 5 classes, by giving weight with 9 kinds of elements. In August 25 2014, soil loss occurred in the whole Oryun Tunnel, Geumjeong-gu, Busan, because of local torrential heavy rain. As a result of comparing with landslide hazard map, the area where soil loss occurred in reality is a safety zone on hazard map. Rainfall, soil map, geological map, forest type map, gradient, drainage network, watershed, basin shape, and efflux of the whole Oryun Tunnel where soil loss occurred were analyzed. As a result of an analysis, it is judged that soil, forest type, much efflux and peak discharge, degree of water network and basin shape of a place where landslide occurred are causes of soil loss. It is judged that efflux, peak discharge, and basin shape by the localized rainfall that is not considered in landslide hazard map of them are the biggest causes of soil loss. It is judged that efflux, peak discharge, degree of water network and basin shape by the rainfall are important through a study on a causual analysis on soil loss in the whole Oryun Tunnel where is one of occurrence area where a lot of propertywere lost by the record local torrential rainfalls. A localized torrential downpour should be prepared by considering these elements on judgement of a landslide hazard area.