• The Journal of Engineering Geology
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• v.26 no.3
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• pp.413-422
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• 2016

With the rapidly increasing population density and development of infrastructure, the loss of life and property damage caused by landslides has increased gradually in urban area. Especially, Because Busan has high percentage of mountainous terrain among the metropolitan in Korea, it is unavoidable to develop mountainous region excessively. The objective of this evaluation is to study on landslide hazard possibility for Mt. Hwangryeong in Busan Metropolitan City using the infinite slope model considering the groundwater level. All data related to creating the thematic maps was carried out using ArcGIS 10.0. The results show that FS (Factor of Safety) for landslide is inversely proportional to groundwater level change as expected. Most area indicates stable state in dry condition, and unstable area increase due to high pore water pressure when the groundwater level rise. However, several places in high lineament density area where landslide has been previously occurred, are more stable than other places according to the analysis. This inconsistency between real situation and analysis results indicates that additional analytical method would be necessary to solve the problem. Therefore, we suggest that development of new infiltration theory for unsaturated zone would be helpful to evaluate groundwater level distribution as time goes by.

• Journal of The Korea Institute of Healthcare Architecture
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• v.28 no.4
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• pp.31-39
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• 2022

The purpose of this study is to analyse the hazard risk by examining the magnitude and severity of each type of hazard in order to mitigate and prepare for disasters in medical facilities. Methods: The hazard risk analysis for hazard types was surveyed for team leaders of medical facilities. The questionnaire analyzed data from 27 facilities, which were returned from 41 Local Medical Centers. Results: When looking at the 'Risk' by category type of hazard, the influence of health safety and fire/energy safety comes first, followed by natural disaster, facility safety, and crime safety. On the other hand, as for 'Magnitude', facility safety and crime safety come first, followed by health safety, fire/energy safety, and natural disasters. Most of the top types of disaster judged to have high hazard in medical facilities are health types. The top five priorities of hazard in medical facilities, they are affected by the geographical and industrial conditions of the treatment area. In the case of cities, the hazard was found to be high in the order of infectious disease, patient surge, and wind and flood damage. On the other hand, in rural areas, livestock diseases and infectious diseases showed the highest hazard. In the case of forest areas, the hazard was high in the order of wildfire, fire accident, lightning, tide, earthquake, and landslide, whereas in coastal areas of industrial complexes, the hazard was high due to fire, landslide, water pollution, marine pollution, and chemical spill accident. Implications: Through the research, standards will be established for the design of hospitals with disaster preparedness, and will contribute to the preparation of preemptive measures in terms of maintenance.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.376-386
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• 2023

Due to climate changes, landslide hazards in the Republic of Korea (hereafter South Korea) continuously increase. To establish the effective landslide mitigation strategies, such as erosion control works, landslide hazard estimation in the long-term perspective should be proceeded considering the influence of climate changes. In this study, we examined the change in landslide-damaged areas in South Korea responding to climate change scenarios using the multivariate regression method. Data on landslide-damaged areas and rainfall from 1981-2010 were used as a training dataset. Sev en indices were deriv ed from rainfall data as the model's input data, corresponding to rainfall indices provided from two SSP scenarios for South Korea: SSP1-2.6 and SSP5-8.5. Prior to the multivariate regression analysis, we conducted the VIF test and the dimension analysis of regression model using PCA. Based on the result of PCA, we developed a regression model for landslide damaged area estimation with two principal components, which cov ered about 93% of total v ariance. With climate change scenarios, we simulated landslide-damaged areas in 2030-2100 using the regression model. As a result, the landslide-damaged area will be enlarged more than the double of current annual mean landslide damaged area of 1981-2010; It infers that landslide mitigation strategies should be reinforced considering the future climate condition.

• Spatial Information Research
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• v.1 no.1
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• pp.89-94
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• 1993

GIS was appl ied for analysis of the potfnt ial degree of regional geologic hazard, expecially landslide, in the suburb of Seoul city. Potential elements causing a landslide are geology, slope geometry, groundwater, soil property, rainfall and vegetation etc. These factors were incorporated through GIS in order to predict the potential hazards, and to produce a regional geologic hazard map in the study area, For this study, ARC/INFO and ERDAS systems were used in SUN4-390 workstation.

• Journal of The Geomorphological Association of Korea
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• v.15 no.2
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• pp.25-35
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• 2008

Typhoon Ewiniar and Bilis followed by heavy rainfall in July 2006 triggered massive slope failures and debris flows along the Osaek valley within Seoraksan National Park. Since national road 44 is constructed along the fault-line, the susceptibility of hazard in the area is very high. Debris flows in Osaekcheon are mobilized from landslides near the ridgelines and peaks when heavy rainfall elevates pore pressure and adds weight to the hillslopes, causing failure. Stream flows falling onto the existing colluvium or channel-margin deposits also trigger debris flows. Steep slopes constructed along the road and thin regolith in the slope is the main reason for the landslide in the upper stream. In middle reaches of stream, under-fit drainage utilities and narrow bridges cause the overflow, this then triggers debris flow. Overflowing and erosion in the channel margin deposits is main reasons for the debris flow. The intensities and frequencies of heavy rainfall are certain to increase, so early warning and management system for the landslide-related hazard is urgently needed.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.369-372
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• 2008

Recently, landslides have frequently occurred on natural slopes during periods of intense rainfall. With a rapidly increasing population on or near steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is introduced. The system is focused to debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of sensor nodes, gateway, and server system. Sensor nodes comprising a sensing part and a communication part are developed to detect ground movement. Sensing part is designed to measure inclination angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15.1) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of experimental studies was performed at a small-scale earth slope equipped with an artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope starts to move. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.179-193
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• 2019

Landslides are one of the most damaging geological hazards worldwide, threating both humans and property. Hence, there have been many efforts to prevent landslides and mitigate the damage that they cause. Among such efforts, there have been many studies on mapping landslide susceptibility. Geographic information system (GIS)-based techniques have been developed and applied widely, and are now the main tools used to map landslide susceptibility. We reviewed the status of landslide susceptibility mapping using GIS by number of papers, year, study area, number of landslides, cause, and models applied, based on 776 articles over the last 20 years (1999-2018). The number of studies published annually increased rapidly over time. The total study area spanned 65 countries, and 47.7% of study areas were in China, India, South Korea, and Iran, where more than 500 landslides, 27.3% of all landslides, have occurred. Slope (97.6% of total articles) and geology (82.7% of total articles) were most often implicated as causes, and logistic regression (26.9% of total articles) and frequency ratio (24.7% of total article) models were the most widely used models. We analyzed trends in the causes of and models used to simulate landslides. The main causes were similar each year, but machine learning models have increased in popularity over time. In the future, more study areas should be investigated to improve the generalizability and accuracy of the results. Furthermore, more causes, especially those related to topography and soil, should be considered and more machine learning models should be applied. Finally, landslide hazard and risk maps should be studied in addition to landslide susceptibility maps.

• The Journal of Engineering Geology
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• v.4 no.1
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• pp.43-55
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• 1994

Two thematic maps on environmental geology were produced in the Cheong-Ju area, with aids of GIS technique. They are landslide hazards & risk maps and cut-fill maps. The models of environmental geology map and digital database were established for creation of these maps by means of cartographic simulation in GIS. These special maps are very important for understanding the environmental characteristics of the study area, and can be applied in the establishment of the regional land use planning. For instance, the landslide hazard and risk map can play very important role in the road design, and cut- fill map in the construction work in the area. The scoring system for landslide analysis was developed through the evaluation of each environmental geologic factor in relation to the others and reflects the relative imporatance of each factor. The excavation index(easy, intermediate and difficult) was evaluated through cut-fill analysis, and they can be very useftil for assessing the degree of excavation difficulty.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.