• Journal of The Geomorphological Association of Korea
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• v.25 no.3
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• pp.1-18
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• 2018

In Korea, 64% of the land is known as mountain area, but the definition and classification standard of mountain are not clear. Demand for utilization and development of mountain area is increasing. In this situation, the unclear definition and scope of the mountain area can lead to the destruction of the mountain and the increase of disasters due to indiscreet permission of forestland use conversion. Therefore, this study analyzed the variables and criteria that can extract the mountain boundaries through the questionnaire survey and the terrain analysis. We developed a mountain boundary extraction algorithm that can classify topographic mountain by using selected variables. As a result, 72.1% of the total land was analyzed as mountain area. For the three catchment areas with different mountain area ratio, we compared the results with the existing data such as forestland map and cadastral map. We confirmed the differences in boundary and distribution of mountain. In a catchment area with predominantly mountainous area, the algorithmbased mountain classification results were judged to be wider than the mountain or forest of the two maps. On the other hand, in the basin where the non-mountainous region predominated, algorithm-based results yielded a lower mountain area ratio than the other two maps. In the two maps, we was able to confirm the distribution of fragmented mountains. However, these areas were classified as non-mountain areas in algorithm-based results. We concluded that this result occurred because of the algorithm, so it is necessary to refine and elaborate the algorithm afterward. Nevertheless, this algorithm can analyze the topographic variables and the optimal value by watershed that can distinguish the mountain area. The results of this study are significant in that the mountain boundaries were extracted considering the characteristics of different mountain topography by region. This study will help establish policies for stable mountain management.

• Restorative Dentistry and Endodontics
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• v.38 no.1
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• pp.21-25
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• 2013

Objectives: The aim of this study was to evaluate the shaping ability of newly marketed single-file instruments, Wave One (Dentsply-Maillefer) and Reciproc (VDW GmbH), in terms of maintaining the original root canal configuration and curvature, with or without a glide-path. Materials and Methods: According to the instruments used, the blocks were divided into 4 groups (n = 10): Group 1, no glide-path / Wave One; Group 2, no glide-path / Reciproc; Group 3, #15 K-file / Wave One; Group 4, #15 K-file / Reciproc. Pre- and post-instrumented images were scanned and the canal deviation was assessed. The cyclic fatigue stress was loaded to examine the cross-sectional shape of the fractured surface. The broken fragments were evaluated under the scanning electron microscope (SEM) for topographic features of the cross-section. Statistically analysis of the data was performed using one-way analysis of variance followed by Tukey's test (${\alpha}$ = 0.05). Results: The ability of instruments to remain centered in prepared canals at 1 and 2 mm levels was significantly lower in Group 1 (p < 0.05). The centering ratio at 3, 5, and 7 mm level were not significantly different. Conclusions: The Wave One file should be used following establishment of a glide-path larger than #15.

• The Journal of Engineering Geology
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• v.26 no.1
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• pp.23-32
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• 2016

This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.

• Economic and Environmental Geology
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• v.36 no.2
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• pp.133-139
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• 2003

The purpose of this study is the analyses of the relationship between geology and terrain/satellite image in the southern part of the Bandung, Indonesia to provide basic information fur geological survey. For this, topography, geology and satellite image were constructed to spatial database. Digital elevation, slope, aspect, curvature, hill shade of topography were calculated from the topographic database and lithology was imported from the geologi-cal database. Lineament, lineament density, and NDVI were extracted the Landsat TM satellite image. The results showed the close relationship between geology and terrain and satellited image. Each sedimentary rocks seldom correspond with geology and analyses of topography but as a whole fur sedimentary rocks coincide with them. Tuff and volcanic breccia in the volcanic rocks correspond with the result of terrain analyses. Talus deposit is well matched with the analyses of topography/satellite image.

• Economic and Environmental Geology
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• v.37 no.5
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• pp.521-532
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• 2004

The aim of this study is to evaluate the susceptibility of landslides at Kangneung area, Korea, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified from interpretation of satellite image and field surveys. The topographic, soil, forest, geologic, lineament and land cover data were collected, processed and constructed into a spatial database using GIS and remote sensing data. Using frequency ratio model which is one of the probability model, the relationships between landslides and related factors such as 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 were calculated as frequency ratios. Then, the frequency ratio were summed to calculate a landslide susceptibility indexes and the landslide susceptibility maps were generated using the indexes. The results of the analysis were verified and cross-validated using actual landslide location data. The verification results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

• Journal of Ocean Engineering and Technology
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• v.20 no.3 s.70
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• pp.67-76
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• 2006

Three-dimensional information of submarine topography was acquired by assembling DGPS and Echo Sounder, which is mainly used in the marine survey. However, the features of submarine topography, derived according to mechanical data, were confirmed using human eyes. Because the dredging capacity using a submarine surveying data influences harbor public affairs, analysis and the process method of surveying data is a very special element in construction costs. In this study, information on submarine topography is acquired by assembling DGPS and Echo Sounder. Moreover, the dredging capacity in harbor public affairs has been analyzed by the interpolation method: inverse distance to a power, kriging, minimum curvature, nearest neighbor, and radial basis function. Also, utilization of DGPS and Echo Sounder method in calculation of the dredging capacity have been confirmed by comparing and analyzing the dredging capacity and the actual one, as per each interpolation. According to this comparison result, in the case of applying Radial basis function interpolation and Kriging, 3.94 % and 4.61 % of error rates have been shown, respectively. In the case of the study for application of the proper interpolation, as per characteristics of submarine topography, is preceded in calculation of the dredging capacity relevant to harbor public affairs, it is expected that more speedy and correct calculation for the dredging capacity can be made.

• Economic and Environmental Geology
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• v.38 no.1
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• pp.33-43
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• 2005

The purpose of this study is to make and validate landslide susceptibility map using artificial neural network and GIS in Kangneung area. For this, topography, soil, forest, geology and land cover data sets were constructed as a spatial database in GIS. From the database, slope, aspect, curvature, water system, topographic type, soil texture, soil material, soil drainage, soil effective thickness, wood type, wood age, wood diameter, forest density, lithology, land cover, and lineament were used as the landslide occurrence factors. The weight of the each factor was calculated, and applied to make landslide susceptibility maps using artificial neural network. Then the maps were validated using rate curve method which can predict qualitatively the landslide occurrence. The landslide susceptibility map can be used to reduce associated hazards, and to plan land use and construction as basic data.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.87-103
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• 2020

The purpose of this study is to evaluate the risk of cropland and man-made infrastructures in a landslide-prone area using a GIS-based method. To achieve this goal, a landslide inventory map was prepared based on aerial photograph analysis as well as field observations. A total of 550 landslides have been counted in the entire study area. For model analysis and validation, extracted landslides were randomly selected and divided into two groups. The landslide causative factors 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 the analysis. Moreover, to identify the correlation between landslides and causative factors, pixels were divided into several classes and frequency ratio was also extracted. A landslide susceptibility map was constructed using a bayesian predictive model (BPM) based on the entire events. In the cross validation process, the landslide susceptibility map as well as observation data were plotted with a receiver operating characteristic (ROC) curve then the area under the curve (AUC) was calculated and tried to extract a success rate curve. The results showed that, the BPM produced 85.8% accuracy. We believed that the model was acceptable for the landslide susceptibility analysis of the study area. In addition, for risk assessment, monetary value (local) and vulnerability scale were added for each social thematic data layers, which were then converted into US dollar considering landslide occurrence time. Moreover, the total number of the study area pixels and predictive landslide affected pixels were considered for making a probability table. Matching with the affected number, 5,000 landslide pixels were assumed to run for final calculation. Based on the result, cropland showed the estimated total risk as US $ 35.4 million and man-made infrastructure risk amounted to US $ 39.3 million.

• Journal of The Geomorphological Association of Korea
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• v.26 no.3
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• pp.53-67
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• 2019

The purpose of this study is to identify the quality of landslide susceptibility in a landslide-prone area (Jinbu-myeon, Gangwon-do, South Korea) by spatial prediction modeling approach and compare the results obtained. For this goal, a landslide inventory map was prepared mainly based on past historical information and aerial photographs analysis (Daum Map, 2008), as well as some field observation. Altogether, 550 landslides were counted at the whole study area. Among them, 182 landslides are debris flow and each group of landslides was constructed in the inventory map separately. Then, the landslide inventory was randomly selected through Excel; 50% landslide was used for model analysis and the remaining 50% was used for validation purpose. Total 12 contributing factors, such as slope, aspect, curvature, topographic wetness index (TWI), elevation, forest type, forest timber diameter, forest crown density, geology, landuse, soil depth, and soil drainage were used in the analysis. Moreover, to find out the co-relation between landslide causative factors and incidents landslide, pixels were divided into several classes and frequency ratio for individual class was extracted. Eventually, six landslide susceptibility maps were constructed using the Bayesian Predictive Discriminant (BPD), Empirical Likelihood Ratio (ELR), and Linear Regression Method (LRM) models based on different category dada. Finally, in the cross validation process, landslide susceptibility map was plotted with a receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC) and tried to extract success rate curve. The result showed that Bayesian, likelihood and linear models were of 85.52%, 85.23%, and 83.49% accuracy respectively for total data. Subsequently, in the category of debris flow landslide, results are little better compare with total data and its contained 86.33%, 85.53% and 84.17% accuracy. It means all three models were reasonable methods for landslide susceptibility analysis. The models have proved to produce reliable predictions for regional spatial planning or land-use planning.

• 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.