• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1047-1060
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• 2017

In recent years, global warming has been continuing and abnormal weather phenomena are occurring frequently. Especially in the 21st century, the intensity and frequency of hydrological disasters are increasing due to the regional trend of water. Since the damage caused by disasters in urban areas is likely to be extreme, it is necessary to prepare a landslide susceptibility maps to predict and prepare the future damage. Therefore, in this study, we analyzed the landslide vulnerability using the logistic model and assessed the management plan after the landslide through the field survey. The landslide area was extracted from aerial photographs and interpretation of the field survey data at the time of the landslides by local government. Landslide-related factors were extracted topographical maps generated from aerial photographs and forest map. Logistic regression (LR) model has been used to identify areas where landslides are likely to occur in geographic information systems (GIS). A landslide susceptibility map was constructed by applying a LR model to a spatial database constructed through a total of 13 factors affecting landslides. The validation accuracy of 77.79% was derived by using the receiver operating characteristic (ROC) curve for the logistic model. In addition, a field investigation was performed to validate how landslides were managed after the landslide. The results of this study can provide a scientific basis for urban governments for policy recommendations on urban landslide management.

• 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.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.385-394
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• 2001

There are serious damage of people and properties every year due to landslides that are occurred by heavy rain. Because these phenomena repeat and the heavy rain is not an atmospheric anomaly, the counter plan becomes necessary. The study area, Ulsan, is one of the seven metropolitan, and largest cities of Korea and has many large facilities such as petrochemical complex and factories of automobile and shipbuilding. So it is necessary assess the landslide hazard potential. In the study. the three steps of landslide hazard assessment techniques such as susceptibility, possibility, and risk were performed to the study area using GIS. For the analyses, the topographic, geologic, soil, forest, meteorological, and population and facility spatial database were constructed. Landslide susceptibility representing how susceptible to a given area was assessed by overlay of the slope, aspect, curvature of topography from the topographic DB, type, material, drainage and effective thickness of soil from the soil DB, lype age, diameter and density from forest DB and land use. Then landslide possibility representing how possible to landslide was assessed by overlay of the susceptibility and rainfall frequency map, Finally, landslide risk representing how dangerous to people and facility was assessed by overlay of the possibil. ity and the population and facility density maps The assessment results can be used to urban and land use plan for landslide hazard prevention.

• Economic and Environmental Geology
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• v.44 no.4
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• pp.289-302
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• 2011

Since the frequency of the earthquake occurrence in Korean peninsular is continuously increasing, the possibility that massive landslides are triggered by earthquake is also growing in Korea. Previously, the landslide is known to be induced by large magnitude earthquake, whose magnitude is larger than 6.0. However, the landslide can be induced by only small magnitude earthquake, especially in the fully saturated soil. Therefore, the susceptibility of landslide caused by small magnitude earthquake in fully saturated soil is analyzed in this study. For that, the topographical and geological characteristics of the site were obtained and managed by GIS software. In the procedure of the study, slope angle, cohesion, friction angle, unit weight of soil were obtained and constructed as a spatial database layer. Combining these data sets in a dynamic model based on Newmark's displacement analysis, the landslide displacements were estimated in each grid cell. In order to check out the possibility of the earthquake induced landslides, the level of the groundwater table is varied from dry to 80% saturated soil. In addition, in order to analyze the effect of the magnitude of earthquake and distance to epicenter, four different earthquakes epicenters were considered in the study area.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.47-57
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• 2010

The aim of this study is to detect landslide using digital aerial photography and apply the landslide to landslide susceptibility mapping by artificial neural network (ANN) and geographic information system (GIS) at Jinbu area where many landslides have occurred in 2006 by typhoon Ewiniar, Bilis and Kaemi. Landslide locations were identified by visual interpretation of aerial photography taken before and after landslide occurrence, and checked in field. For landslide susceptibility mapping, maps of the topography, geology, soil, forest, lineament, and landuse were constructed from the spatial data sets. Using the factors and landslide location and artificial neural network, the relative weight for the each factors was determinated by back-propagation algorithm. As the result, the aspect and slope factor showed higher weight in 1.2-1.5 times than other factors. Then, landslide susceptibility map was drawn using the weights and finally, the map was validated by comparing with landslide locations that were not used directly in the analysis. As the validation result, the prediction accuracy showed 81.44%.

• 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.

• Journal of Cadastre & Land InformatiX
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• v.44 no.2
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• pp.113-124
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• 2014

Recently landslide occurs frequently by heavy rainfall, therefore there area many studies to analyze the vulnerable district of landslide and forecast the occurrence of landslide. This study analyzed soil characteristics in the occurrence district of landslide and the occurrence possibility of landslide ranked high in well draining soil as the result of frequency ratio according to the characteristics of drainage. Also as the result of frequency ratio of slope derived from DEM data, the occurrence possibility of landslide ranked high in slope range of $20{\sim}40^{\circ}$. And Also as the result of frequency ratio of aspect by geospatial analysis, the occurrence possibility of landslide ranked high in north aspect. Also, it is possible to evaluate the vulnerability of landslide by overlapping frequency ratio of the drainage of soil, slope and aspect. And future prediction ratio of landslide occurrence can be evaluated by performing the analysis and validation process respectively on the subject of the occurrence district of landslide.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.39-50
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• 2012

KMA(Korea Meteorological Administration) projected that annual mean temperatures of South Korea will rise $3.8^{\circ}C$ and the annual total precipitation will increase by 17 percent by 2100. Rainfall is concentrated during the summer in South Korea. Thus the risk of landslide by heavy rain is expected to increase. After the landslide of Mt. Umyeon occurred in July 2011, disaster of forest sector is highlighted. Therefore vulnerability assessment of landslide is urgent. However, vulnerability assessment based on local governments was not done yet. In this study, we assess vulnerability of landslide by heavy rain for local governments. We used several scenarios to consider uncertainty of climate change. Through this study, local governments can use the results to establish adaptation plans. Also, the results could be used to decrease vulnerability of landslide.

• Economic and Environmental Geology
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• v.45 no.6
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• pp.697-707
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• 2012

The quantitative landslide susceptibility assessment methods can be divided into statistical approaches and geomechanical approaches based on the consideration of the triggering factors and landslide models. The geomechanical approach is considered as one of the most effective approaches since this approach proposes physical slope model and considers geomorphological and geomechanical properties of slope materials. Therefore, the geomechanical approaches has been used widely in landslide susceptibility analysis using the infinite slope model as physical slope model. However, the previous studies assumed constant groundwater level for broad study area without the consideration of rainfall intensity and hydraulic properties of soil materials. Therefore, in this study, landslide susceptibility assessment was implemented using the coupled infinite slope model with hydrologic model. For the analysis, geomechanical and hydrualic properties of slope materials and rainfall intensity were measured from the soil samples which were obtained from field investigation. For the practical application, the proposed approach was applied to Jinbu area, Gangwon-Do which was experienced large amount of landslides in July 2006. In order to compare to the proposed approach, the previous approach was used to analyze the landslide susceptibility using randomly selected groundwater level. Comparison of the results shows that the accuracy of the proposed method was improved with the consideration of the hydrologic model.

• 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.