• Journal of Environmental Science International
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• v.18 no.11
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• pp.1189-1197
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• 2009

The purpose of this research was develop tailored landslide hazard assessment table (LHAT) in Gyeongsangbuk-do Province and propose building strategies on environmental information system to estimate landslide hazard area according to LHAT. To accomplish this purpose, this research investigated factors occurring landslide at 172 landslide occurred sites in 23 city and county of Gyeongsangbuk-do Province and analyzed what factors effected landslide occurrence quantity using the multiple statistics of quantification method(I). The results of analysis, factors affecting landslide occurrence quantity were shown in order of slope position, slope length, bedrock, aspect, forest age, slope form and slope. And results of the development of LHAT for predict mapping of landslide-susceptible area 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). According to LHAT, this research built landslide attribute database and made 7 digital theme maps at mountainous area located in Goryeong Gun, Seongju-Gun, and Kimcheon-City. The results of prediction on degree of landslide hazard using environmental information system, area with little susceptibility to landslide(III class) occupied 65.56% and severe susceptibility to landslide(I class) occupied 0.51%.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.311-321
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• 2019

This study was carried out to establish basic data for the development of slow-moving landslide hazard classes. Mountain slopes in slow-moving landslide areas ranged from $11.8^{\circ}$ to $37.0^{\circ}$ with a mean slope of $23.8^{\circ}$. However, the slope inclination of microtopography in slow-moving landslide areas was slightly different, with a mean slope of $23.5^{\circ}$ ($10.7^{\circ}{\sim}41.5^{\circ}$) compared with the mountain slope. There was a significant difference (p < 0.05) between the contour intervals of microtopography and the contour intervals of the slow-moving landslide areas. Among all the slow-moving landslide areas examined, 14 plots (approximately 38.0%) were classified into landslide hazard class I, 6 plots (approximately 16.0%) into landslide hazard class II, 5 plots (approximately 14.0%) into landslide hazard class III and IV, and 16 plots (approximately 43.0%) into landslide hazard class V, whereas 9 plots (approximately 24.0%) fit the no landslide hazard class.

• 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).

• 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.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 of Forest Science
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• v.83 no.2
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• pp.175-190
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• 1994

In order to get fundamental information for prediction of landslide hazard, both forest and site factors affecting slope stability were investigated in many areas of active landslides. Twelve descriptors were identified and quantified to develop the prediction model by multivariate statistical analysis. The main results obtained could be summarized as follows : The main factors influencing a large scale of landslide were shown in order of precipitation, age group of forest trees, altitude, soil texture, slope gradient, position of slope, vegetation, stream order, vertical slope, bed rock, soil depth and aspect. According to partial correlation coefficient, it was shown in order of age group of forest trees, precipitation, soil texture, bed rock, slope gradient, position of slope, altitude, vertical slope, stream order, vegetation, soil depth and aspect. The main factors influencing a landslide occurrence were shown in order of age group of forest trees, altitude, soil texture, slope gradient, precipitation, vertical slope, stream order, bed rock and soil depth. Two prediction models were developed by magnitude and frequency of landslide. Particularly, a prediction method by magnitude of landslide was changed the score for the convenience of use. If the total store of the various factors mark over 9.1636, it is evaluated as a very dangerous area. The mean score of landslide and non-landslide group was 0.1977 and -0.1977, and variance was 0.1100 and 0.1250, respectively. The boundary value between the two groups related to slope stability was -0.02, and its predicted rate of discrimination was 73%. In the score range of the degree of landslide hazard based on the boundary value of discrimination, class A was 0.3132 over, class B was 0.3132 to -0.1050, class C was -0.1050 to -0.4196, class D was -0.4195 below. The rank of landslide hazard could be divided into classes A, B, C and D by the boundary value. In the number of slope, class A was 68, class B was 115, class C was 65, and class D was 52. The rate of landslide occurrence in class A and class B was shown at the hige prediction of 83%. Therefore, dangerous areas selected by the prediction method of landslide could be mapped for land-use planning and criterion of disaster district. And also, it could be applied to an administration index for disaster prevention.

• 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.

• 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 Geotechical Society Conference
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• 2010.09a
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• pp.782-789
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• 2010

Landslides cause enormous economic losses and casualties. Korea has mountainous regions and heavy slopes in most parts of the land and has consistently built new roads and large-scale housing complexes according to its industrial and urban growth. As a result, the damage from landslides becomes greater every year. In this study, performed a GIS-based landslide hazard analysis by SINMAP(Stability Index MAPping) model in Gyeonggi Icheon area coupling with geomorphological and geological data. SINMAP model has its theoretical basis in the infinite plane slope stability model with wetness obtained from a topographically based steady state model of hydrology. To Gyeonggi Icheon area landslides hazards evaluated, these SINMAP model were analysed results while simultaneously referring to the stability index map, where lines distinguish the zones categorized into the different stability classes and a table giving summary statistics.

• The Journal of Engineering Geology
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• v.22 no.3
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• pp.353-363
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• 2012

The geology of Ulleung-Do is dominated by volcanic rocks with low strength and trachytic rocks with high strength but containing vertical joints that yield easily. Consequently, rockfalls along roadcuts are a major geological hazard, with the potential to affect the ring road of Ulleung-Do. In this study, we performed three types of rockfall hazard-risk assessment on the 3-km-long section of the ring road expected to have the highest possibility of rockfall. We used a rockfall ranking sheet in a roadside landslide hazard map, the Slope Stability Inspection Manual for National Highways (Japan), and a rockfall hazard rating system for inspection from the Japan Highway Public Corporation. We also employed the evaluation criteria of 'RHRS' developed by the Federal Highway Administration (FHA). An analysis of roadcuts at 27 sites with regard to geographic and geological conditions resulted in the identification of three classes of rockfall hazard (high, medium, and low). Of note, over 74% of slopes were assessed as high- and medium-class. Finally, a rockfall hazard map of the northeast region of Ulleung-Do was produced based on the evaluation results.