• Journal of Korean Society of Rural Planning
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• v.17 no.3
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• pp.1-13
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• 2011

This study aims to analyse the landscape ecological characteristics of 39 rural villages in Korea and classify them according to their characteristics. After producing a land-use map of rural villages, this study quantified the landscape ecological characteristics of the subject sites as 18 landscape indexes using Fragstats. By applying the landscape index as a variable, selecting 4 factor through principal component analysis and conducting a cluster analysis, it classified them into 3 groups. Rural villages of Korea have their unique types of land-use due to the influence of physical environment such as geography, climate and ecology as well as the social and cultural influence, and the characteristics of land-use can be analysed and classified using the landscape index, the quantified landscape ecological characteristics.

• Journal of Korean Society of Rural Planning
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• v.1 no.1
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• pp.35-48
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• 1995

The drastic change of spatial structure in rural area and the recent rural development policies(related to settlement reorganization and plot rearrangement) make the rural space planning more important than ever. So this paper tries to evaluate the institutional aspects of rural spatial planning system focused on planning area. land use classification and hierachical order between existing plans. The results of this study can be summarized as follows. First, the rural planning areas are classified into 4-tiers(e.g., Gun, Myon, District, Village). Second, the rural land use planning has 3-tiers(e.g., macro, mediate and micro zoning) from the viewpoint of land use classification system, but it doesn't have mediate-micro zoning system. Third, the spatial plans in rural area, positioned in local planning, were categorized into regional planning system and land use planning system. However there's no linkage between both sides of each hierachial planning order.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.667-672
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• 2007

Land-use in Cheongju region is changing rapidly because of the increased interactions of human activities with the environment as population increases. We used multi-temporal Landsat images (1991 and 2000) and DEM data in a post-classification analysis with GIS to map land-use distribution and to analyse factors influencing the land-use changes for Cheongju City. Land-use statistics revealed that substantial land-use changes have taken place and that the built-up areas have expanded by about $17.57km^2(11.47%)$ over the study period (1991-2000). Agricultural lands and forests have decreased substantially while urban and barren lands have been on the increase. Rapid economic developments together with the increasing population were noted to be the major factors influencing rapid land use changes. Urban expansion has replaced urban and barren lands, thereby affecting habitat quality and leading to serious environmental degradation.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.3
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• pp.61-69
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• 2008

Land-use in northern Cheongju region is changing rapidly because of the increased interactions of human activities with the environment as population increases. Land-use change detection is considered essential for monitoring the growth of an urban complex. The analysis was undertaken mainly on the basis of the multi-temporal Landsat images (1991, 1992 and 2000) and DEM data in a post-classification analysis with GIS to map land-use distribution and to analyse factors influencing the land-use changes for Cheongju city. The area of each land-use category was also calculated for monitoring land-use changes. Land-use statistics revealed that substantial land-use changes have taken place and that the built-up areas have expanded by about $17.57km^2$ (11.47%) over the study period (1991 - 2000). This study illustrated an increasing trend of urban and barren lands areas with a decreasing trend of agricultural and forest areas. Land-use changes from one category to others have been clearly represented by the NDVI composite images, which were found suitable for delineating the development of urban areas and land use changes in northern Cheongju region. Rapid economic developments together with the increasing population were noted to be the major factors influencing rapid land use changes. Urban expansion has replaced urban and barren lands.

• Korean Journal of Agricultural Science
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• v.38 no.1
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• pp.153-162
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• 2011

This study analyzed the spatio-temporal change detection of land-use and urbanization in Yongin and Anseong regions, Kyunggi Province, using three Landsat-5 TM images for 1990, 1996, and 2000. Remote sensing (RS) and geographic information system (GIS) techniques were used for image classification and result analysis. Six land-use types were classified using supervised maximum likelihood classification. In the two study areas, the land-use changed significantly, especially the decrease of arable land and forest and increase of built-up area. Spatially, the urban expansion of Yongin region showed a spreading trend mainly along the national road and expressways. But in Anseong region the expansion showed 'urban sprawl phenomenon' with irregular shape like starfish. Temporally, the urban expansion showed disparity - the growth rates of urbanized area rose from the period 1990-1996 to 1996-2000 in both study areas. The increased built-up areas were converted mainly from paddy, dry vegetation, and forest.

• Journal of Korean Society of Rural Planning
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• v.1 no.1
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• pp.65-74
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• 1995

As a initial methodological approach to rational land use planning in the county-level area, three types of land suitability classification techniques were examined from the viewpoint of their practical applicability through the case study of Seungju-gun area, Chonnam-province, Korea : major factors' criteria(method I ), principal component analysis( I ), and local monitoring( R( ). Each method has its strong and weak points as shown in Tab.-5. Therefore, when its practical application, there seem to be wide-range methodological selectivities from exclusive use of the best one to intermethodological combination of related ones In the beginning stage, intermethodological combination of all three types were tried to formulate the best solution possible. However, because of reliability problem of method R accrued from non- uniformity of evaluators'quality, only two methods( 1 , E ) were combined into a new evaluation method The applied results of the new combined method to case study area are shown in Fig.-2, 3 and 4.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.473-478
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• 1999

The purpose of the study were to detect and evaluate the land use and changes on the Balan Watersheds, located southwest of Suwon, using the Thematic Mapper(TM) data. Three sests of TM taken in 1985 , 1993 and 1996 were used and the changes in the land use analyzed and compared. The suupervised and unsuperivised classification methods were adoppted to classify five land-cover categories ; Paddy , upland , forest , residential , and water. Future ladn use patterns were simulated using a Markow chain method, and the change ratios presented.

• Magazine of the Korean Society of Agricultural Engineers
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• v.8 no.1
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• pp.1048-1054
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• 1966

1. Data of this article come from actual soil survey activity by the UNKUP project personel. 2. Proper national land use must be solved because of the growing population and increasing economic activity. 3. Korea has to be developed for the natural resources of soil and water in the subwate\ulcorner rsheds. 4. This problem. depends On the result of land capability classification which was determind by the soil survey.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.44-55
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• 2018

The importance of establishing a greenhouse gas inventory is emerging for policymaking and its implementation to cope with climate change. Thus, it is needed to establish Approach 3 level Land Use, Land-Use Change and Forestry (LULUCF) matrix that is spatially explicit regarding land use classifications and changes. In this study, four types of spatial information suitable for establishing the LULUCF matrix were analyzed - Cadastral Map, Land Cover Map, Forest Map, and Biotope Map. This research analyzed the classification properties of each type of spatial information and compared the quantitative and qualitative characteristics of the maps in Boryeong city. Drawn from the conclusions of the quantitative comparison, the forest area showed the maximum difference of 50.42% ($303.79km^2$) in the forest map and 46.09%($276.65km^2$) in the cadastral map. The qualitative comparison drew five qualitative characteristics: data construction scope difference, data construction purpose difference, classification standard difference, and classification item difference. As a result of the study, it was evident that the biotope map was the most appropriate spatial information for the establishment of the LULUCF matrix. In addition, if the LULUCF matrix is made by integrating the biotope, the forest map, and the land cover map, the limitations of each spatial information would be improved. The accuracy of the LULUCF matrix is expected to be improved when the map of the level-3 land cover map and the biotope map of 1:5,000 covering the whole country are completed.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.3
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• pp.55-64
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• 2014

While utilizing high resolution satellite image for land use classification has been popularized, object-oriented classification has been adapted as an affordable classification method rather than conventional statistical classification. The aim of this study is to extract the paddy field area using object-oriented classification with time series NDVI from high-resolution satellite images, and the RapidEye satellite images of Jaeryung-gun in North Korea were used. For the implementation of object-oriented classification, creating objects by setting of scale and color factors was conducted, then 3 different land use categories including paddy field, forest and water bodies were extracted from the objects applying the variation of time-series NDVI. The unclassified objects which were not involved into the previous extraction classified into 6 categories using unsupervised classification by clustering analysis. Finally, the unsuitable paddy field area were assorted from the topographic factors such as elevation and slope. As the results, about 33.6 % of the total area (32313.1 ha) were classified to the paddy field (10847.9 ha) and 851.0 ha was classified to the unsuitable paddy field based on the topographic factors. The user accuracy of paddy field classification was calculated to 83.3 %, and among those, about 60.0 % of total paddy fields were classified from the time-series NDVI before the unsupervised classification. Other land covers were classified as to upland(5255.2 ha), forest (10961.0 ha), residential area and bare land (3309.6 ha), and lake and river (1784.4 ha) from this object-oriented classification.