• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.314-317
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• 2004

The aim of this study was to evaluate the susceptibility from landslides in the Lai Chau region of Vietnam, using Geographic Information System (GIS) and remote sensing data, focusing on the relationship between tectonic fractures and landslides. Landslide locations were identified from an interpretation of aerial photographs and field surveys. Topographic and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image processing techniques, and a scheme of the tectonic fracturing of the crust in the Lai Chau region was established. In this scheme, Lai Chau was identified as a region with low crustal fractures, with the grade of tectonic fracture having a close relationship with landslide occurrence. The factors found to influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature, distance from drainage, lithology, distance from a tectonic fracture and land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability-likelihood ratio method. The results of the analysis were verified using landslide location data, and these showed a satisfactory agreement between the hazard map and existing landslide location data.

• 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 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.

• The Journal of Engineering Geology
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• v.2 no.2
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• pp.131-140
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• 1992

GIS(Geographic Information System) technology was applied for analysis of the potential degree of regional geologic hazard, especially landslide hazards in the suburb of Seoul City, whereby a regional geologic hazard map was produced. The factors causing a landslide such as slope geometry, geology, groundwater, soil property, rainfall and vegetation were incorporated through GIS in order to predict the potential hazards in this area. Cartographic simulation was finally made with these factors to produce a regional geologic hazard map. For this study, ARC/INFO and ERDAS systems were used in SUN 4-390 workstation.

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.67-75
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• 2004

The landslide is one of the most significant natural disasters, which cause a lot of loss of human lives and properties. The landslides in natural slopes generally occur by complicated problems such as soil properties, topography, and geology. Artificial Neural Network (ANN) model is efficient computing technique that is widely used to solve complicated problems in many research fields. In this paper, the ANN model with application of error back propagation method was proposed for estimation of landslide hazard in natural slope. This model can evaluate the possibility of landslide hazard with two different approaches: one considering only soil properties; the other considering soil properties, topography, and geology. In order to evaluate reasonably the landslide hazard, the SlideEval (Ver, 1.0) program was developed using the ANN model. The evaluation of slope stability using the ANN model shows a high accuracy. Especially, the prediction of landslides using the ANN model gives more stable and accurate results in the case of considering such factors as soil, topographic and geological properties together. As a result of comparison with the statistical analysis(Korea Institute of Geosciences and Mineral Resources, 2003), the analysis using the ANN model is approximately equal to the statistical analysis. Therefore, the SlideEval (Ver. 1.0) program using ANN model can predict landslides hazard and estimate the slope stability.

• 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 the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.1-13
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• 2022

The damages caused by landslides are increasing worldwide due to climate change. In Korea, damages from landslides occur frequently, making it necessary to develop the effective response strategies. In particular, there is a lack of countermeasures against landslides in cultural heritage areas. The purpose of this study was to spatially analyze the relationship between Buyeo-gun's cultural heritage and landslide susceptible areas in Buyeo-gun, Chungcheongnam-do, which has a long history. Nine spatial distribution models were used to evaluate the landslide susceptibility, and the ensemble method was applied to reduce the uncertainty of individual model. There were 17 cultural heritages belonging to the landslide susceptible area. As a result of calculating the area ratio of the landslide susceptible area for cultural heritages, the cultural heritages with 100% of the area included in the landslide susceptible area were "Standing statue of Maae in Hongsan Sangcheon-ri" and "Statue of King Seonjo." More than 35% of "Jeungsanseong", "Garimseong", and "Standing stone statue of Maitreya Bodhisattva in Daejosa Temple" belonged to landslide susceptible areas. In order to effectively prevent landslide damage, the application of landslide prevention measures should be prioritized according to the proportion belonging to the landslide susceptible area. Since it is very difficult to restore cultural properties once destroyed, preventive measures are required before landslide damage occurs. The approach and results of this study provide basic data and guidelines for disaster response plans to prevent landslides in Buyeo-gun.

• Journal of Cadastre & Land InformatiX
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• v.45 no.2
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• pp.161-173
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• 2015

The influence of climate change on rainfall patterns has triggered landslide and debris flow with casualties and property damage. This study constructed DSM and Orthophoto by using UAV surveying technique and evaluated landslide risk area by applying GIS data into the infinite slope stability model. As a result of the estimation of slope stability in a site, the slope instability has $SI{\leq}1.0$ with cover area 46,396m2, and the distribution percentage was 18.2%. The most dangerous section has $SI{\leq}0.0$ with its cover area 7,988m2, and the ratio was 0.8%. The reviews regarding the risk of landslide and debris flow risk by stability index and river channel analysis respectively help being able to designate the hazard zone due to heavy rainfall. Therefore the analysis result of this study will need to reinforce soil slope and plan their safety measures in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.12 no.2
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• pp.147-154
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• 1994

Landslides in the close residential area occur loss of life and properties. Usually soil mechanical methods and multi-statistical methods used to analysis the landslide. The factors of landslide analysis by multi-statistical methods are composite operations of geology, topography, vegetation, and climate etc. In this study, existing landslide areas are cheesed to extract the characteristics of their geographical data for adaption of Multi-statical methods. Authors give a weight to their values and analyze the some area using technique of overlap on GSIS.

• 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.