• Journal of Korean Society of Rural Planning
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• v.4 no.2
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• pp.128-137
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• 1998

The objective of this study is to approach on the spatial boundary of rural development protect by areal classification technique with spatial reference to searching of areal homogeneities in two hierachial administrative units, Ri Eup/Myun. In this study, a criterion for judging areal homogeneities is the degree of agriculture and urbanizing. Variables selected by these two criteria are analysed with the method of fator analysis. The results of areal analysis are as follows: first, generally, the importance of agricultural factors in areal analysis is getting less. Second, areal classification by Myun, Ri in Ansong City is revealed variously because of urban factors. Urban factors make areal heterogeneities become greater, Therefore urban factors are important when analyzing areal characteristics. Third, lately, in areas near by Chung- cheong Do and areas with bad road's condition, areal heterogeneities have been also getting greater. The results of analysis about areal characteristics of Myun and Ri are different from each other. In addition, urban factors are more influential on the areal characteristics than agricultural factors. Therefore, the establishment of rural development project for inindle spatial boundary between Myun unit and Ri unit is needed.

• Proceedings of the KSRS Conference
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• v.2
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• pp.647-650
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• 2006

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.115-126
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• 2016

This paper suggests the method of the spherical signature description of 3D point clouds taken from the laser range scanner on the ground vehicle. Based on the spherical signature description of each point, the extractor of significant environmental features is learned by the Deep Belief Nets for the urban structure classification. Arbitrary point among the 3D point cloud can represents its signature in its sky surface by using several neighborhood points. The unit spherical surface centered on that point can be considered to accumulate the evidence of each angular tessellation. According to a kind of point area such as wall, ground, tree, car, and so on, the results of spherical signature description look so different each other. These data can be applied into the Deep Belief Nets, which is one of the Deep Neural Networks, for learning the environmental feature extractor. With this learned feature extractor, 3D points can be classified due to its urban structures well. Experimental results prove that the proposed method based on the spherical signature description and the Deep Belief Nets is suitable for the mobile robots in terms of the classification accuracy.

• Korean Journal of Geomatics
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• v.5 no.1
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• pp.27-34
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• 2005

Unsupervised classification is an important area of research in image processing because supervised classification has the disadvantages such as long task-training time and high cost and low objectivity in training information. This paper focuses on unsupervised classification, which can extract ground object information with the minimum 'Spectral Angle Distance' operation on be behalf of 'Spectral Euclidian Distance' in the clustering process. Unlike previous studies, our algorithm uses the unit vector, not the spectral distance, to compute the cluster mean, and the Single-Pass algorithm automatically determines the seed points. Atmospheric correction for more accurate results was adapted on the Hyperion data and the results were analyzed. We applied the algorithm to the Hyperion and ETM+ data and compared the results with K-Means and the former USAM algorithm. From the result, USAM classified the water and dark forest area well and gave more accurate results than K-Means, so we believe that the 'Spectral Angle' can be one of the most accurate classifiers of not only multispectral images but hyperspectral images. And also the unit vector can be an efficient technique for characterizing the Remote Sensing data.

• Journal of the Korean Institute of Landscape Architecture
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• v.34 no.2 s.115
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• pp.1-17
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• 2006

The purpose of this study was to analyze biotope types of urban land-use patterns. Forest areas were considered according to vegetation type and potential for succession. Urban ecosystem structure was analyzed according to land use, land coverage, vegetation structure (actual vegetation, diameter at breast height, layer structure, and revetment). As a results of the classification, the biotopes were divided into 71 types according to the urban ecosystem structure. In the case of the Hanam province, the biotopes were divided into 51 types: 26 forest types; 5 swampy and grass land types; 3 farm land types; 3 types of planted land, and 8 types of urbanization.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.633-636
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• 2004

Airborne laser scanning thechnology has been studied in many applications, DSM(Digital Surface Model) development, building extraction, 3D virtual city modeling. In this paper, we will evaluate the possibility of airborne laser scanning technology for transportation application, especially for recognizing moving vehicles on road. First, we initially segment the region of roads from all LiDAR DATA using the GIS map and intensity image. Secondly, the segmented region is divided into the roads and vehicles using the height threshold value of local based window. Finally, the vehicles will be classified into the several types of vehicles by MDC(Minimum Distance Classification) method using the vehicle's geometry information, height, length, width, etc

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.343-347
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• 2004

Landuse information is used to plan land use, urban and environmental management as base data. And, demand for landuse information is rising due to ecological consideration in urban area. But existing method to extract landuse information from aerial photographs or satellite images is difficulte to describe sufficient urban landuses. Also landuse information need to be linked with statistical data because statistical data is used to make decision for urban planning and management with landuse. Therefore this study aims to examine the landuse classification method using statistical unit data and 1:1,000 digital topographic data. for the purpose, the method was applied to a part of metropolitan Seoul. The results of study shows that total accuracy is 95%. For the future, the method will be effectively applicable for the city maintenance.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.5
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• pp.101-109
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• 2009

There are increasing needs about creation and sustainable management of urban forest for environmental conservation and recreational service for citizen. However, it is difficult for local governments to create or manage urban forest in recreational or conservational way. The purpose of this study is to classify the urban forest types by considering its geographical feature, biological and sociological characteristics in order to suggest a guide to local governments about effective creation or management of urban forest. In this study, we extracted common characteristics of the selected five indicators. Factors about urban forest are divided into two groups. Factors were named according to the variables as 'Urban Forest Naturalness', and 'High Accessibility and Disturbed by Human.' In addition, we classified urban forests into four types in this study. The type I of urban forest is a large forest and has high naturalness such as Mt. Bukhan and Mt. Gwanak. The type II is fragmented to large forests by developmental projects. The type III is flat and has high accessibility such as forest behind Seonjeongneung. The type IV is located near residential area such as Mt. Ansan, Mt. Inwang and Mt. Bonghwa. It is possible to set up recreational area for citizens and ecological networks for species by the research of the urban forest type. The results of the study, classification of urban forest types and its application, contribute to provide a guide for local governments to create or manage urban forests effectively.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.3
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• pp.38-46
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• 1999

The purpose of the study is to analyze the effect of urbanization, the degree of development in urban scale and the comparative analysis of landuse change in order to construct the important basic data for establishing development direction and characterizing each city. To analyze the urban growth patterns a land cover classification using Landsat TM data was performed : 1987 and 1997 for the change detection of each land cover. The results of this study demonstrates that urban areas increased on while forest areas had decreased all over the Korean cities. Especially, in case of the analysis on landuse conversion rate, we found out that the forest areas was first changed into agricultural areas, then it is consequently developed into urban areas in most rural areas. This study concludes that the insufficiency of the number of knowledged officials in the local administration and a government official in one's charge, tight financial conditions and absence of recognition of cities' characteristics, urban development following unrefined development patterns, inappropriate urban planning and policy of metropolitan cities and the negligence of peculiar development patterns of each city.

• Proceedings of the KSEEG Conference
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• 1999.04a
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• pp.279-281
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• 1999