• Water for future
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• v.46 no.3
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• pp.42-47
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• 2013

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.61-69
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• 2010

The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.

• Journal of Korea Water Resources Association
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• v.39 no.1 s.162
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• pp.23-33
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• 2006

In this study, application potential of SINMAP, a GIS-based landslide hazard mapping tool, is evaluated through a case study. Through the application to the severe landslide events occurred during a heavy storm in 1991 on the Mt. Dalbong area about 78 kilometers south from Seoul, SINMAP successfully spotted most landslide sites. The effects and proper ranges of three calibration parameters of SINMAP, i.e. the soil internal friction angle, the combined cohesion of tree roots and soil, and T/R, were examined through comparison of predicted landslides with the landslide inventory data. From the findings of this study, it seems that SINMAP could be used as an effective screening tool for landslide hazard mapping especially for mountain areas with fairly steep slopes and relatively thin soil layers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.152-163
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• 2020

The present study introduces a procedure to prepare and manage a high-resolution rainfall and soil moisture (SM) database in the LAMP prediction system, especially for landslide researchers. The procedure also includes converting the data into spatial resolution suitable for their interest regions following proper map projection methods. The LAMP model precipitation and SM data are quantitatively and qualitatively evaluated to identify the model prediction characteristics using the ERA5 reanalysis precipitation and observed 10m depth SM data. A detailed process of converting LAMP Weather Research and Forecasting (WRF) output data for 10m horizontal resolution is described in a step-wise manner, providing technical convenience for users to easily convert NetCDF data from the WRF model into TIF data in ArcGIS. The converted data can be viewed and downloaded via the LAMP website (http://df.ncam.kr/lamp/index.do) of the National Center for AgroMeteorology. The constructed database will contribute to monitoring and prediction of landslide risk prior to landslide response steps and should be data quality controlled by more observation data.

• Journal of Korea Water Resources Association
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• v.45 no.6
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• pp.617-629
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• 2012

The land use map of the Nakdong River watershed was classified by each land use contents and analyzed to rank the risk of soil loss and erosion. Also, the soil loss and erosion was evaluated in the Nakdong River watershed using Revised Universal Soil Loss Equation (RUSLE) and the subbasin with high risk of soil loss was evaluated with the analysis results of land use contents. Finally, the analyzed results were also compared with the landslide risk map, hence the practical application methods using developed and analyzed results were considered in this study. As a result of land use analysis and RUSLE calculation, it was represented that the Naesung Stream watershed had the high risk for soil loss among the subbasins of the Nakdong River watershed. It was also presented that the high risk area identified by computation of RUSLE was corresponding to the landslide risk area. However, the high risk of soil erosion by land use near the river or wetland was confirmed only through the calculation results of RUSLE.

• Journal of the Korean GEO-environmental Society
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• v.18 no.6
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• pp.21-30
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• 2017

This study analyzed the ground characteristics region by designating 3 research areas, Anrim-dong in Chungju City, Busa-dong in Daejeon Metropolitan City and Sinan-dong in Andong City out of the areas subject to concentrated management to prepare for sediment disaster in downtown areas. The correlation between ground characteristics were observed by using characteristics (crown density, root cohesion, rainfall characteristics, soil characteristics) and the risk areas were predicted through sediment disaster prediction modeling. Landslide MAPping (LSMAP), Stability Index MAPping (SINMAP) and Landslide Hazard MAP (LHMAP) were used for the comparative analysis of the hazard prediction model for sediment disaster. As a result of predicting the sediment disaster danger, in case of SINMAP which was generally used, excessive range was predicted as a hazardous area and in case of the Korea Forest Service's landslide hazard map (LHMAP), the smallest prediction area was assessed. LSMAP predicted a medium range of SINMAP and LHMAP as hazardous area. The difference of the prediction results is that the analysis parameters of LSMAP is more diverse and engineering than two comparative models, and it is found that more precise prediction is possible.

• Journal of Korean Society of Disaster and Security
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• v.6 no.1
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• pp.35-45
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• 2013

In recent years, increasing damage due to landslides. So the government is to create a geotechnical hazard map. This study was to evaluate the applicability of the geotechnical hazard map by using 4 years of landslide cases in Seoul and Busan. And the in-situ aseessment has been carried out in test-bad area with specialists. Study has shown dangerous grade in geotechnical hazard map is more dangerous than the actual. Thus we can utilize geotechnical hazrd map in the purpose of the geotechnical hazard preliminary assessment. However, the in-site inspection and evaluation is required for in order to select the hazard area.

• Journal of The Geomorphological Association of Korea
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• v.27 no.2
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• pp.65-80
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• 2020

This paper deals with risk assessment of life in a landslide-prone area by a GIS-based modeling method. Landslide susceptibility maps can provide a probability of landslide prone areas to mitigate or proper control this problems and to take any development plan and disaster management. A landslide inventory map of the study area was prepared based on past historical information and aerial photography analysis. A total of 550 landslides have been counted at the whole study area. The extracted landslides were randomly selected and divided into two different groups, 50% of the landslides were used for model calibration and the other were used for validation purpose. Eleven causative factors (continuous and thematic) such as slope, aspect, curvature, topographic wetness index, elevation, forest type, forest crown density, geology, land-use, soil drainage, and soil texture were used in hazard analysis. The correlation between landslides and these factors, pixels were divided into several classes and frequency ratio was also extracted. Eventually, a landslide susceptibility map was constructed using a logistic regression model based on entire events. Moreover, the landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract a success rate curve. Based on the results, logistic regression produced an 85.18% accuracy, so we believed that the model was reliable and acceptable for the landslide susceptibility analysis on the study area. In addition, for risk assessment, vulnerability scale were added for social thematic data layer. The study area predictive landslide affected pixels 2,000 and 5,000 were also calculated for making a probability table. In final calculation, the 2,000 predictive landslide affected pixels were assumed to run. The total population causalities were estimated as 7.75 person that was relatively close to the actual number published in Korean Annual Disaster Report, 2006.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.371-374
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• 2007

For development of landslide risk assessment techniques using GIS(Geographic Information System), this study classifies the category of socioeconomic factors. The landslide quantitative risk assessment performs first prediction of flow trajectory and runout distance of debris flow over natural terrain. Based on those results, it can be analyzed the factors of socioeconomic which are directly related to the magnitude of risk due to landslide hazards. Those risk assessment results can deliver factual damage situation prediction to policy making for the landslide damage mitigation. Therefore, this study is based on feature classification of the digital map ver. 2.0 provided by the National Geographic Information Institute. The category of factors can be used as useful data in preventing landslide.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.139-149
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• 2012

Flooding caused by torrential rains and landslide causes the deaths of people and property damage as well as traffic congestion and isolation. Driver enters the dangerous area when driver doesn't recognize disaster information on the road and the damage is spread over time. In this paper, we will develop a smart phone application to collect dangerous disaster area information and a system based on C/S to manage the data received from the smart phone application. This system can analyze dangerous disaster areas using the data received from the smart phone application and the spatial database analyzed dangerous disaster areas is displayed in the smart phone application using a map server. We think that the suggested system provides more efficient information to user.