• Journal of the Korean association of regional geographers
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• v.2 no.1
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• pp.151-164
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• 1996

The regional division by the characteristics of the drainage patterns is important to understand its physical environment comprehensively, because the drainage network develops in reflecting characteristics of geological, geographical and climatical features in the drainage basin keenly. This study is the attempt to divide physical region in China whose drainage pattern is diverse. Chinese drainage basin is mainly divided into the interior drainage basin and the peripheral drainage basin. The interior drainage basin is divided into (1)the deranged pattern and (2)the centripetal pattern. The peripheral drainage basin is divided into (1)the dendritic pattern, (2)the parallel pattern, (3)the radial pattern and (4)the anastomatic pattern. Drainage patterns of the interior drainage basin are formed by affecting geographical features and climatic conditions mainly. In the peripheral drainage basin, drainage patterns are formed by other factors: the parallel pattern is connected with geological structure lineament by tectonic movement, the radial pattern with changes of the river channel resulted from the Yellow River's overflow, the anastomotic pattern with human's activities. The distributional features of the physical region in China are as follows: The deranged pattern appears in Zangbai Plateau, the centripetal pattern does in arid basin of the northwest China. the parallel pattern does in Hengduan mountains affected strongly by tectonic movement between Yangtze paraplatform and Indian Plate, does in the upper stream of Yangtze River and Ganges River in the south of Qinghai-Xizang Plateau, the radial pattern in Huaihe Haihe River drainage basin appearing in the alluvial fan region of Yellow River's downstream and the anastomotic pattern does in the delta of Yangtze River, in the northern coastal plain of the Jiangsu-Province and in the delta of Zhujiang River. Except these areas in the peripheral drainage basin, the dendritic pattern is usually found in the other areas.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.633-642
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• 2004

This study tries to generalize the stream network by constructing rule-based modelling. A study on the map generalization tends to be concentrated on development of algorithms for modification of linear features and evaluations to the limited cartographic elements. Rule-based modelling can help to improve previous algorithms by application of generalization process with the results that analyzing mapping principles and spatial distribution patterns of geographical phenomena. Rule-based modelling can be applied to generalize various cartographic elements, and make an effective on multi-scaling mapping in the digital environments. In this research, nile-based modelling for stream network is composed of generalization rule, algorithm for centerline extraction and linear features. Before generalization, drainage pattern was analyzed by the connectivity with lake to minimize logical errors. As a result, 17 streams with centerline are extracted from 108 double-lined streams. Total length of stream networks is reduced as 17% in 1:25,000 scale, and as 29% in 1:50,000. Simoo algorithm, which is developed to generalize linear features, is compared to Douglas-Peucker(D-P) algorithm. D-P made linear features rough due to the increase of data point distance and widening of external angle. But in Simoo, linear features are smoothed with the decrease of scale.

• 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.