• Journal of The Geomorphological Association of Korea
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• v.19 no.4
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• pp.139-155
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• 2012

Most of previous landform classification methods using DEM compares the values between the center of the cell and the surrounding cells, which in turn, greatly depends on analysis scale. To overcome the problem of scale-dependency, a new classification scheme is developed, which is called "Geomorphons". Unlike the traditional approaches using DEM, Geomorphons is the way which compares the level with other cells against the criteria cell. As a pilot study, we classify the landforms of Pyeongchang-Gun in Korea. Then, we compare the result with the other methods such as Topographic Position Index. Through the systematic analysis, we obtain the following findings. First, Geomorphons can reduce the time for the classification of landforms because of using unsupervised classification. Second, Geomorphons is little dependent on change in the scale, which can provide a pilot tool for reconnaissance study for covering large area.

• Journal of the Korean Geographical Society
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• v.50 no.5
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• pp.485-503
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• 2015

This study aims at evaluating geomorphological classification systems to predict the occurrence of landslides in mountainous region in Korea. Geomorphological classification systems used in this study are Catena, TPI, and Geomorphons. Study sites are Gapyeong-gun, Hoengseong-gun, Gimcheon-si, Yeoju-si/Yicheon-si in which landslide occurrence data were collected by local governments from 2001-2014. Catena method has objective classification standard to compare among regions objectively and understand the result intuitively. However, its procedure is complicated and hard to be automated for the general public to use it. Both TPI and Geomorphons have simple procedure and GIS-extension, therefore it has high accessibility. However, the results of both systems are highly dependent on the scale, and have low relevance to geomorphological formation process because focusing on shape of terrain. Three systems have low compatibility, therefore unified concept are required for broad use of landform classification. To assess the effectiveness of prediction on landslide by each geomorphological classification system, 50% of geomorphological classes with higher landslide occurrence are selected and the total landslide occurrence in selected classes are calculated and defined as 'predictive ability'. The ratio of terrain categorized by 'predictive ability' to whole region is defined as 'vulnerable area ratio'. An indicator to compare three systems which is predictive ability divided by vulnerable area ratio was developed to make a comprehensive judgment. As a result, Catena ranked the highest in suitability.

• Journal of The Geomorphological Association of Korea
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• v.24 no.1
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• pp.63-76
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• 2017

This research was classified mountain areas with high ecological, environmental and resource value among the macro scaled terrain that can be checked at the space scale of less than 1:1,000,000 and analyzed the topographical characteristics. It has been confirmed that the mountains of the Korean peninsula belong to the groups IV, V, VI(classification by Kapos et al.(2000)) as a result of applying the quantitative standards for designation of mountain areas to the global mountain system. The area of mountains calculated using high resolution DEM is equivalent to 48% of the area of the Korean peninsula, and the result is quite different from the general idea of which 70% is the mountain area of the Korean peninsula. The mountain areas show the distribution of geomorphons, that is different from the plains and the hills and also, it shows the differences between the mountains of the groups IV~ VI classified according to the altitude. As a result of analyzing the relations among type pattern, slope, and relief, specific geomorphons are concentrated at $10^{\circ}$ and $20^{\circ}$ and it shows the possibility to classify the mountainous areas into two groups based on the result that the distribution of landform patterns are bimodal in the relation to the amount of relief.