• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.133-142
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• 2010

To monitor composition and change of the national land, intelligent topographical classifier which enables accurate classification of land-cover types from airborne LiDAR data is highly required. We developed a topographical classifier development support system cooperating with da1a mining tool WEKA to help users to construct accurate topographical classification systems. The topographical classifier development support system has the following functions; superposing LiDAR data upon corresponding aerial images, dividing LiDAR data into tiles for efficient processing, 3D visualization of partial LiDAR data, feature from tiles, automatic WEKA input generation, and automatic C++ program generation from the classification rule set. In addition, with dam mining tool WEKA, we can choose highly distinguishable features by attribute selection function and choose the best classification model as the result topographical classifier. Therefore, users can easily develop intelligent topographical classifier which is well fitted to the developing objectives by using the topographical classifier development support system.

• 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 Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.55-59
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• 2008

For effective mobility control of UGV(unmanned ground vehicle), the terrain cover classification is an important component as well as terrain geometry recognition and obstacle detection. The vision based terrain cover classification algorithm consists of pre-processing, feature extraction, classification and post-processing. In this paper, we present a method to classify terrain covers based on the color and texture information. The color space conversion is performed for the pre-processing, the wavelet transform is applied for feature extraction, and the SVM(support vector machine) is applied for the classifier. Experimental results show that the proposed algorithm has a promising classification performance.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.7-18
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• 2005

Currently, design speed selection is chosen by highway function, terrain type and area type. But some standards in classifing highway function let designer decide design speed in an arbitrary manner and too rough a highway function classification system leads to a road function which can not reflect road design, and some ambiguity of terrain type leads to a road which can not reflect land use pattern. Highway design based on traffic volume level without considering area type can result high construction cost. This research paper provides new highway design standards which are based on the refinement of highway design speed selection procedure. The new design speed is summarized to be determined by a more detailed highway function, terrain type, and area type that were made considering South Korean characteristics. The new highway function is established by adopting highway function reclassification and design volumes and rural town center reclassification and new design standards for terrain type selection are developed in this research by analyzing South Korean GIS Data Base obtained over the national government offices.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.84-88
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• 2007

우리나라의 토양조사는 미농무성(USDA)의 분류방법에 따라 개략토양조사($'65{\sim}'67$년), 정밀토양조사($'68{\sim}'79$년), 논토양배양사업 10개년계획($'80{\sim}'90$년), 그리고 밭토양세부정밀토양조사($'95{\sim}'99$년) 등을 실시하였다. 현지에서의 토양조사는 지형, 배수등급, 토성, 자갈함량, 유효토심, 경사 등 현지의 지형지물 및 환경을 통하여 많은 정보를 얻을 수 있으며, 이를 통하여 전국에 대한 토양조사 결과, 토양통 (심토의 특성이 유사한 토양) 390개, 토양구(표토의 토성을 세분) 536개, 토양상(경사도 및 침식등급을 세분) 1,321개로 분류되어 있다. 우리나라 토양형성 발달에 미친 기후인자는 습윤권역(Udic moisture regime)과 토양온도는 mesic과 일부 남해안과 제주지역의 thermic인 토양온도(Soil moisture regime)였으며, 식생인자는 높은 지역의 경우에는 산림이 낮은 저지대 평탄지는 자연초지가 대부분이다. 지형인자는 동고서저지형으로 동부는 산악지, 서부는 경사가 완만한 구릉지며, 한강 등 대부분이 서남방향으로 흐르는 지형이다. 모재는 다양하나 70%이상이 화강암, 화강편마암이 주를 이루고 있었다. 시간인자의 경우에는 기간이 매우 오래되었으나, 지형이 복잡하여 토양발달이 약한 Inceptisol과 층위발달이 없는 Entisol이 대부분이며, 다음으로 Ultisol과 Alfisol이 뒤를 이었다. 일부 Andisol, Mollisol, Histosol이 존재하였다. 우리나라의 토양분류는 Soil Taxonomy에 의해 분류되었는데, 이것은 토양의 단면내에 존재하는 감식층위(Diagnostic Horizon)의 유무 및 종류에 따른 분류이다. 토양분류 결과 최고 상위분류 단위인 목(order)이 7개, 아목(suborder) 14개, 대군(great group) 27개, 아군(sub group) 67개, 속(family) 161개로 분류되었으며, 가장 저차단위인 통(series)이 390개 분류되었다. 또한 작물이용측면에서 실용적 분류를 실시하였는데, 논토양의 경우 보통논, 미숙논, 사질논, 습논, 염해논, 특이산성논으로 분류할 경우 각각의 분포면적이 31.9%, 23.0%, 31.9%, 9.1%, 3.9%, 0.2%이었다. 밭토양의 경우에도 보통밭, 사질밭, 미숙밭, 중점밭, 고원밭, 화산회밭으로 6개 유형으로 분류할 경우 각각의 분포면적은 41.9%, 23.3%, 17.5%, 13.9%, 1.1. 2.2% 이었다. 도시화 및 도로확대 등 다양한 토지이용 및 지형개변으로 과거의 토양정보가 많이 변경되었다. 그래서, 앞으로는 인공위성자료 및 항공사진을 이용하여 빠르고 쉽게 활용할 수 있는 토양조사 방법개발과 기 구축된 토양도의 수정, 보완 작업이 필요한 절실히 요구되고 있는 현실이다.

• Journal of The Geomorphological Association of Korea
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• v.20 no.1
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• pp.1-9
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• 2013

This study aims to provide fundamental data for further shape-factor research on karst by measuring and classifying the shape of surface topography in Hogye, Mungyeong. First, in the research area, there are 35 dolines and uvalas. Second, large uvalas are found in three places, including Gulnomjae in Bugokri, and Teotgol and Denjimigol in Urori. Third, there are 13 round dolines and 22 oval dolines. Next examining the cross section of dolines, there are 27 bowl shaped dolines, 2 plate shaped dolines, and 6 funnel shaped dolines. Fourth, most dolines lay over 200m elevation, which is ridge and top of mountain. Fifth, development direction of dolines resembles the strike direction of limestone in Hogye, suggesting that the development direction of limestone affects doline corrosion. From this situation, we can guess sinkholes of the doline would be linked with limestone caves by the underground water pipe. Three limestone caves, karren and dry valley etc. appear in the research area.

• 한국지형공간정보학회:학술대회논문집
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• 2002.03a
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• pp.48-53
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• 2002

본 연구에서는 각각 1998년 8월 12일(홍수 발생시), 8월 19일(홍수 발생 후) 옥천, 보은 지역을 촬영한 RADARSAT SAR 위성영상을 이용하여 수계지역 및 홍수지역 분류를 수행하고자 하였다. 이를 위해, 먼저 두 장의 위성영상에 대해서 각각 스페클 잡영(speckle noise)을 제거하고, ${\sigma}^0$(sigma naught, dB)을 계산한 후 수계지역에 대한 ${\sigma}^0$값을 분석하였다. 이 값을 기준으로 각각 두 장의 위성영상에서 각각 최대우도법을 이용하여 수계지역을 분류하였다. SAR 영상은 영상취득의 원리에 의해 지형의 기복에 따른 음영효과(shadow effect)가 발생하는데, 음영효과가 발생하는 지역의 ${\sigma}^0$값은 수계지역과 비슷한 반사특성(낮은 dB 값)을 보인다. 따라서 지형의 기복이 심한 지역의 수계지역 분류시 음영효과를 제거해야 효과적적인 분류를 할 수 있으며, 이를 위해 위성의 헤더자료로부터 촬영시 각각의 촬영중심을 계산하고, 촬영중심과 지상좌표와의 기하학적 관계를 고려하여 음영효과를 제거하였다. 마지막으로, 수계지역만이 추출된 영상에 대해 영상의 기하보정을 수행하였으며, 기하 보정된 두장의 위성영상에 대해 차분영상를 생성함으로서 홍수지역을 분류하였다.

• Journal of the Korean Society of Child Welfare
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• no.59
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• pp.183-208
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• 2017

The purpose of this study was to identify groups depending on the change trajectory of child maltreatment in childhood and early adolescence. For this study, the data from waves two through six (2011-2015) of the Korean Children and Youth Panel Survey (KCYPS) were used. Participants included first-grade (n=2,300) and fourth-grade (n=2,325) elementary school students. A latent class growth model (LCGM) using Mplus 7.21 was adopted to classify the types of developmental trajectories of child maltreatment. The main results were as follows: First, in physical abuse, childhood from the second to the sixth grades was classified into four groups: decreased, low maintenance, increased, and no maltreatment type. In addition, early adolescence from the fifth grade of elementary school to the third grade of middle school was also classified into the same types. Second, in emotional abuse, childhood was classified into three groups: decreased, increased, and no maltreatment type. Early adolescence was classified into four groups: decreased, low maintenance, increased, and no maltreatment type. Third, in neglect, childhood was classified into four groups: maintenance, low decreasing, low increasing, and no maltreatment type. Early adolescence was classified into three groups: maintenance, low increasing, and no maltreatment type. According to the change of child maltreatment by developmental period, physical abuse continued from childhood to early adolescence, whereas emotional abuse and neglect increased in early adolescence compared to childhood. This study is meaningful in classifying latent classes depending on maltreatment types. Theoretical and practical implications were suggested based on the study results.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.639-645
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• 2009

The objective of this research was to introduce the TPI approach for interpreting land-forms of mountain forests in South Korea. We develop an objective procedure to decide the scale factor as a basic analytical unit in land-form classification of rugged mountain areas using TPI. In order to determine the scale factor associated with the pattern of slope profiles, the gradient variance curve was derived from a revised hypsometric curve developed using the relief energy of topographic profiles. Using the gradient variance curve, found was the grid size with which the change in relief energy got the peak point. The grid size at the peak point was determined as the scale factor for the study area. In order to investigate the performance of the procedure based on the gradient variance curve, it was applied to determination of the site-specific scale factors of 3 different terrain conditions; highly-rugged, moderately-rugged and relatively less-rugged. The TPI associated with the corresponding scale factors by study site was, then, determined and used in classifying the land-forms. According to the results of this study, the scale factor gets shorter with more rugged terrain conditions. It was also found that the numbers of valleys and ridges estimated with TPI show almost the same trends as those of the observed and the scale factors tends to approach to the mean distance of ridges.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.2
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• pp.200-206
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• 2008

To implement a mobile radio system, wave-propagation models are necessary to determine propagation characteristics accurately, Currently, the empirical/theoretical prediction models for urban environments are fairly well-developed. But there is a lack of a suitable prediction model for mountain region. So in this paper, to develop the prediction model for mountain region, propagation environments are classified based on three basic mechanisms: reflection, diffraction, penetration(absorbtion and scattering), and measurements have been performed for the classified mountain regions including open area, forest and ridge. Using the measurement data, empirical modeling of propagation characteristics are performed, and then a prediction model for mountain region is proposed.