• Journal of the Korean Geosynthetics Society
• /
• v.12 no.2
• /
• pp.67-74
• /
• 2013

In this study, the prediction of slope hazard probability was performed to the study area located in Hadae-ri, Woochun-myeon, Hoengsung-gun, Gangwon Province around Youngdong express way using the computer program SHAPP ver 1.0 developed by a decision tree model. The soil samples were collected at total 10 points, and soil tests were performed to measure soil properties. The thematic maps of soil properties such as coefficient of permeability and void ratio were made on the basis of soil test results. The slope angle analysis of topography was performed using a digital map. As the prediction result of slope hazard probability, 2,120 cells among total 27,776 cells were predicted to be in the event of slope hazards. Therefore, the predicted area of occurring slope hazards may be $53,000m^2$ because the analyzed cell size was $5m{\times}5m$.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.10 no.6
• /
• pp.73-80
• /
• 2010

Conventional slope stability analysis is focused on calculating minimum factor of safety or maximum probability of failure. To minimize inherent uncertainty of soil properties and analytical model and to reflect various analytical models and its failure shape in slope stability analysis, slope stability analysis method considering simultaneous failure probability for multi failure mode was proposed. Linear programming recently introduced in system reliability analysis was used for calculation of simultaneous failure probability. System reliability analysis for various analytical models could be executed by this method. Optimum design to determine angle of a simple slope is executed for multi failure mode using linear programming. Because of complex consideration for various failure shapes and modes, it is possible to secure advanced safety by using simultaneous failure probability.

• The Journal of Engineering Geology
• /
• v.18 no.3
• /
• pp.303-309
• /
• 2008

A probability of slope hazards was predicted at a natural terrain around the stone relics of Jinjeon-saji area, which is located in Yangyang, Kangwon Province. As the analyzing results of field investigation, laboratory test and geology and geomorphology data, the effect factors of landslides occurrence were evaluated. Also, the landslides prediction map was made up using the prediction model by the effect factors. The landslide susceptibility of stone relics was investigated as the grading classification of occurrence probability. In the landslides prediction map, the high probability area was $3,489m^2$ and it was 10.1% of total prediction area. The high probability area has over 70% of occurrence probability. If landslides are occurred at the predicted area, the three stories stone pagoda of Jinjeon-saji(National treasure No. 122) and the stone lantern of Jinjeon-saji(Treasure No.439) will be collapsed by debris flow.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.129-131
• /
• 2003

The aim of this study is to evaluate the hazard of landslides at Penang, Malaysia, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys. The topographic and geologic data and satellite image were collected, processed and constructed into a spatial database using GIS and image processing. The used factors that influence landslide occurrence are topographic slope, topographic aspect topographic curv ature and distance from drainage from topographic database, geology and distance from lineament from the geologic database, land use from TM satellite image and vegetation index value from SPOT satellite image. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by probability - likelihood ratio - method. The results of the analysis were verified using the landslide location data. The validation results showed satisfactory agreement between the hazard map and the existing data on landslide location.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.04a
• /
• pp.65-70
• /
• 2003

The weight-of-evidence model one of the Bayesian probability model was applied to the task of evaluating landslide susceptibility using GIS. Using the location of the landslides and spatial database such as topography, soil, forest, geology, land use and lineament, the weight-of-evidence model was applied to calculate each factor's rating at Boun area in Korea where suffered substantial landslide damage fellowing heavy rain in 1998, The factors are slope, aspect and curvature from the topographic database, soil texture, soil material, soil drainage, soil effective thickness, and topographic type from the soil database, forest type, timber diameter, timber age and forest density from the forest map, lithology from the geological database, land use from Landsat TM satellite image and lineament from IRS satellite image. Tests of conditional independence were performed for the selection of the factors, allowing the 43 combinations of factors to be analyzed. For the analysis, the contrast value, W$\^$＋/and W$\^$-/, as each factor's rating, were overlaid to map laudslide susceptibility. The results of the analysis were validated using the observed landslide locations, and among the combinations, the combination of slope, curvature, topographic, timber diameter, geology and lineament show the best results. The results can be used for hazard prevention and planning land use and construction

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

• Economic and Environmental Geology
• /
• v.33 no.4
• /
• pp.321-332
• /
• 2000

The purpose of this study is to analyze landslide that occurred in Yongin area in 1991 using spatial database. For this, landslide locations are detected from aerial photographs interpretation and field survey. The locations of landslide, topography, soil, forest and geology were constructed to spatial database using Geographic Information System (GIS). To establish occurrence factors of landslide, slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective thickness of soil were extracted from the soil database, and type, age, diameter and density of wood were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the TM satellite image. Landslide was analyzed using spatial correlation between the landslide and the landslide occurrence factors by bivariate probability methods. GIS was used to analyze vast data efficiently and statistical programs were used to maintain specialty and accuracy. The result can be used to prevention of hazard, land use planning and construction planning as basic data.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.10 no.4
• /
• pp.81-88
• /
• 2010

As there occurs recently and frequently a flash flood due to the climate change, a sudden local flood of great volume and short duration caused by heavy or excessive rainfall in a short period of time over a small area, it is increasing that significant danger and loss of life and property in Korea as well as the whole world. Since a flash flood usually occurs as the result of intense rainfall over small steep slope regions and has rapid runoff and debris flow, a flood rises quite quickly with little or no advance warning to prevent flood damage. The aim of this study is to quantify the severity of flash food by estimation of a flash flood index(FFI) from probability rainfall data in a study basin. FFI-D-F(FFI-Duration-Frequency) curves that present the relative severity of flash flood are developed for a study basin to provide regional basic information for the local flood forecasting and warning system particularly in ungauged catchments. It is also expected that FFI-D-F curves can be utilized for evaluation on flash flood mitigation ability and residual flood risk of both existing and planned flood control facilities.

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

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.717-720
• /
• 2006

In this study, we predicted locations vulnerable to ground subsidence hazard using fuzzy logic and geographic information system (GIS). Test was carried out at an abandoned underground coal mine in Samcheok City, Korea. Estimation of relative ratings of eight major factors influencing subsidence and determination of effective fuzzy operators are presented. Eight major factors causing ground subsidence were extracted and constructed as a spatial database using the spatial analysis and the probability analysis functions. The eight factors include geology, slope, landuse, depth of mined tunnel, distance from mined tunnel, RMR, permeability, and depth of ground water. A frequency ratio model was applied to calculate relative rating of each factor, and the ratings were integrated using fuzzy membership function and five different fuzzy operators to produce a ground subsidence susceptibility map. The ground subsidence susceptibility map was verified by comparing it with the existing ground subsidences. The obtained susceptibility map well agreed with the actual ground subsidence areas. Especially, ${\gamma}-operator$ and algebraic product operator were the most effective among the tested fuzzy operators.