• 한국지형학회지
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• 제25권3호
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• pp.105-120
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• 2018

This study estimates possibility and limitation on production of DEM using aerial photo by comparison of DEMs using aerial photo and digital map. Mountain and urban areas show higher elevation in DEM using aerial photo than in DEM using digital map, due to height of vegetation cover and buildings, respectively. However, artificial affects due to bridge, embankment and road construction are responsible for areas with higher elevation in DEM using digital map than in DEM using aerial photo. This difference in elevation between DEMs seems to be caused by rapid change in real elevation that is not reflected in digital map. There is little difference in elevation between DEMs in plain and area with little or no vegetation cover. This study suggests that problems associated with vegetation cover and error by GCP should be fixed, although DEM using aerial photo can quantitatively and 3-dimensionally reconstruct topography with a high resolution.

• 한국지형학회지
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• 제19권3호
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• pp.135-142
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• 2012

일제강점기인 1910년에 작성된 1:50,000 지도(이하 근세 한국 오만분지일 지형도)는 전국을 망라한 최초의 근대적 방법에 의해 제작된 지도이다. 본 지도는 주로 인문 지리적 관점에서 이용되어 왔으나 최근 지도의 높은 정확성이 인식됨에 따라 다양한 분야에서 유용하게 되었다. 특히 해안분야에 있어서는 해안 구조물 건설에 따른 장기적인 지형변화를 제공할 것으로 기대된다. 본 연구는 독립된 해안 표사계에 대해 구조물의 건설 전후에 진행된 지형변화의 분석방법에 관한 것이다. 장기적인 해안의 지형변화를 분석하기 위한 기점은 1910년도의 지형도로 하였다.

• 한국지형학회지
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• 제25권3호
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• pp.89-103
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• 2018

This study presents results of analysis on fault-related landforms and the Quaternary fluvial landforms, which are important evidences for active faulting by identifying surface deformation, around the Ulsan Fault Zone. In addition, this study suggests lineament map and inferred active fault-line map based on analyzing linearity and continuity of these landforms and by compiling location information of existing active faults. We convince that quantitative tectonic-geomorphological analysis are an effective method for active faults tracking, in particular, considering the conditions of relatively low seismicity and surface ruptured-events in the Korean Peninsula compared to plate boundary active areas. However, research on active fault in South Korea is just an infant stage since the 1990s and requires accumulation of research achievements on development and application of various fault analysis techniques, analysing and standardizing linear structures.

• 한국지형학회지
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• 제27권1호
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• pp.47-60
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• 2020

This study tried to produce an uplift rate map and reveal the spatial distribution of the rate with topographical characteristics and absolute ages on marine terrace in the East Coast of the Korean Peninsula. Based on a total of 57 ages at 26 sites from previous study and 13 ages at 13 sites from this study, the coast showed the rates ranging from 0.145 m/ka to 0.410m/ka with an average of 0.258 m/ka. The highest and lowest rates were found from the Jeongdongjin area in Gangneung and the Goraebul area in Yeongdeok, respectively. However, some areas in the coast showed large differences in the rate among the sites. In addition, areas with only 1 age were also found, indicative of low reliability. This study suggests that a more reliable and precise interpretation on the rate can be made with more ages identified, especially in Goseong to northern part of Gangneung, middle and southern parts of Samcheok and Yeongdeok, southern part of Pohang to northern part of Gyeongju, and Ulsan.

• 한국지형학회지
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• 제27권2호
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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.

• 한국지형학회지
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• 제27권2호
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• pp.1-17
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• 2020

This study evaluated a debris landform distribution potential area map in the southwest region of the Korean peninsula. A GIS spatial integration technique and logistic regression method were used to produce a distribution potential area map. Seven topographic and environmental factors were considered for analysis and 28 different data set were combined and used to get most effective results. Moreover, in an accuracy assessment, the extracted results of the Distribution Potential area were evaluated by conducting a cross-validation module. Block stream showed the highest accuracy in the combination No. 6, and that DEM (digital elevation model) and TWI (topographic wetness index) have relatively high influences on the production of the Block stream Distribution Potential area map. Talus showed the highest accuracy in the combination No. 13. We also found that slope, TWI and geology have relatively high influences on the production of the Talus Distribution Potential area map. In addition, fieldwork confirmed the accuracy of the input data that were used in this study, and the slope and geology were also similar. It was also determined that these input data were relatively accurate. In the case of angularity, the block stream was composed of sub-rounded and sub-angular systems and Talus showed differences according to the terrain formation. Although the results of the rebound strain measurement using a Schmidt's hammer did not shown any difference in topographic conditions, it is determined that the rebound strain results reflected the underlying geological setting.

• 한국지형학회지
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• 제26권3호
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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.

• 한국지형학회지
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• 제24권4호
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• pp.75-89
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• 2017

Sinkholes are key karst landforms that primarily evolve through the dissolution of limestone, and it posing a significant threat to roads, buildings, and other man-made structures. This study aims to analyze the area susceptible to sinkhole development using GIS and to identify potential danger area from sinkholes. Eight sinkhole related factors (slope angle, distance to caves, distance to faults, bedrock lithology, soil depth, drainage class, distance to mines, and distance to traffic routes) were constructed as spatial databases with sinkhole inventory. Based on the spatial database, sinkhole susceptibility maps were produced using nearest neighbor distance and frequency ratio models. The maps were verified with prediction rate curve and area under curve. The result indicates that the nearest neighbor distance and frequency ratio models predicted 95.3% and 94.4% of possible sinkhole locations respectively. Furthermore, to identify potential sinkhole danger area, the susceptibility map was compared with population distribution and land use map. It has been found that very highly susceptible areas are along Osipcheon and southeast southwest part of Hajang-myeon and south part of Gagok-myeon of Samcheok-si. Among those areas, it has been identified that potential sinkhole danger areas are Gyo-dong, Seongnae-dong, Jeongna-dong, Namyang-dong and Dogye-eup. These results can be useful in the aspects of land use planning and hazard prevention and management.

• 한국지형학회지
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• 제23권2호
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• pp.109-125
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• 2016

This study aims to identify the landslide susceptible zones of Boeun area and provide reliable landslide susceptibility maps by applying different modeling methods. Aerial photographs and field survey on the Boeun area identified landslide inventory map that consists of 388 landslide locations. A total ofseven landslide causative factors (elevation, slope angle, slope aspect, geology, soil, forest and land-use) were extracted from the database and then converted into raster. Landslide causative factors were provided to investigate about the spatial relationship between each factor and landslide occurrence by using fuzzy set and logistic regression model. Fuzzy membership value and logistic regression coefficient were employed to determine each factor's rating for landslide susceptibility mapping. Then, the landslide susceptibility maps were compared and validated by cross validation technique. In the cross validation process, 50% of observed landslides were selected randomly by Excel and two success rate curves (SRC) were generated for each landslide susceptibility map. The result demonstrates the 84.34% and 83.29% accuracy ratio for logistic regression model and fuzzy set model respectively. It means that both models were very reliable and reasonable methods for landslide susceptibility analysis.

• 한국지형학회지
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• 제26권2호
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• pp.1-14
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• 2019

This study analyzed the relativity between block stream and talus distributions by employing a likelihood ratio approach. Possible distribution sites for each debris slope landform were extracted by applying a spatial integration model, in which we combined fuzzy set model, Bayesian predictive model, and logistic regression model. Moreover, to verify model performance, a success rate curve was prepared by cross-validation. The results showed that elevation, slope, curvature, topographic wetness index, geology, soil drainage, and soil depth were closely related to the debris slope landform sites. In addition, all spatial integration models displayed an accuracy of over 90%. The accuracy of the distribution potential area map of the block stream was highest in the logistic regression model (93.79%). Eventually, the accuracy of the distribution potential area map of the talus was also highest in the logistic regression model (97.02%). We expect that the present results will provide essential data and propose methodologies to improve the performance of efficient and systematic micro-landform studies. Moreover, our research will potentially help to enhance field research and topographic resource management.