• 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 Soil Science and Fertilizer
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• v.43 no.5
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• pp.696-704
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• 2010

The objective of this study was analysis of two methods of land suitability classification for wild edible green. One method was Maximum limiting factor method (MLFM) and the other was Multi-regression method (MRM) for land suitability classification for wild edible green. The investigation was carried out in Pyeongchang, Hongcheong, Hoeingseong, and Yanggu regions in Korea. The obtained results showed that factors related to the decision classification of the land suitability for wild edible green cultivation were land slope, altitude, soil morphology and gravel contents so on. The classification of the best suitability soil for wild edible greens were fine loamy (silty), valley or fan of soil morphology, well drainage class, B-slope (2~7%), available soil depth deeper than 100cm, and altitude higher than 501m. Contribution of soil that influence to crop yields using Multi-regression method were slope 0.30, altitude 0.22, soil morphology 0.13, drainage classes 0.09, available soil depth 0.07, and soil texture 0.01 orders. Using MLFM, area of best suitable land was 0.2%, suitable soil 15.0%, possible soil 16.7%, and low productive soil 68.0% in Hongcheon region of Gangwon province. But, area of best suitable land was 35.1%, suitable soil 30.7%, possible soil 10.3%, and low productive soil 23.9% by MRM. There was big difference of suitable soil area between two methods (MLFM and MRM). When decision classificatin of the land suitability for wild edible green cultivation should consider enough analysis methods. Furthermore, to establishment of land suitability classification for crop would be better use MRM than MLFM.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.133-144
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• 2018

To suggest the field maintenance plan considering the geographical characteristics of the region, we selected representative regions(plain regione and mountain region) and compared spatial distribution of cultivated land in Muan-gun and Hwasun-gun. Firstly, we examined the distribution characteristics of cultivated land according to the scope of the maintenance object with Fragstats. As a result of that, it was found that the cultivated area except rice paddy had the highest aggregation effect. And then, we developed type classification of maintenance considering geographic characteristics and cultivated crops information. As a result of classification, plain land type Muan region was mostly cultivated land suitable for integrated maintenance. On the other hand, Hwasun, a mountainous terrain, needs small-scale maintenance and road maintenance. Based on these results, it was found that more detailed planning is needed for the upland field infrastructure improvement considering the topographic characteristics.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.4 s.111
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• pp.1-10
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• 2005

Recently, as urban landscape is growing in importance, urban landscape planning is being actively performed. for this purpose, classification of the urban landscape is definitely required. Therefore, this research focuses on classifying urban landscape in Daejeon metropolis by dividing the urban land use pattern. This results are as follows. 1. Urban land use pattern is divided into 20 classes. The residential, commercial and industrial areas, the old market and the bus terminal are evaluated negatively, whereas the areas of school, water reservoir, neighborhood park and train station are appreciated as being positive in landscape characters. 2. As a result of a cluster analysis, urban landscape has five different landscape types. These are: landscapes of medium diversity lacking green area, landscapes of high diversity lacking green area, landscapes rich in green area and with medium diversity, landscapes rich in green area and with high diversity, and landscapes rich in green area and with low diversity. 3. In landscape characters of beauty and harmony, landscapes rich in green area and with medium diversity are more positively evaluated than those rich in green area and with low diversity. This point should be taken into account for planning the urban landscape.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.5
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• pp.535-546
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• 2020

Land cover maps are derived from satellite and aerial images by the Ministry of Environment for the entire Korea since 1998. Even with their wide application in many sectors, their usage in research community is limited. The main reason for this is the map compilation cycle varies too much over the different regions. The situation requires us a new and quicker methodology for generating land cover maps. This study was conducted to automatically generate land cover map using aerial ortho-images and Landsat 8 satellite images. The input aerial and Landsat 8 image data were trained by Residual U-Net, one of the deep learning-based segmentation techniques. Study was carried out by dividing three groups. First and second group include part of level-II (medium) categories and third uses group level-III (large) classification category defined in land cover map. In the first group, the results using all 7 classes showed 86.6 % of classification accuracy The other two groups, which include level-II class, showed 71 % of classification accuracy. Based on the results of the study, the deep learning-based research for generating automatic level-III classification was presented.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.1
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• pp.55-60
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• 1993

Forest occupied a part of natural ecosystem carries out a role of purifying air, preserving water resource, prevention of the breeding and extermination, recreation areas and etc that preserve and for me one's living environment. In this study, the classification for management of this forest is performed with Landsat TM Image. The classes are decided needle-leaf trees, broad-leaf trees, farming land and grass land, and water. When the TM digital images are classified on computer, water is represented in 7∼13 D.N. of 4th band. But the others is appeared similar mostly specific values so that must be done image processing. When the images compounded 2ed band and 3ed band are processed with ratio of enhancement. Needle-leaf treas is represented in l18∼136 D.N. of 1st band, broad-leaf trees in 72∼91 D.N. of 3ed band, farm land and glass land in 96∼120 of 3ed band. Forest Information is classified with M.L.C, an image classification method. The errors of needle-leaf trees, broad-leaf trees, farm land and grass land, and water are appeared each －7.43, ＋1.89,＋7.58 and －2.04 as compared the digital image with investigation on the scene. Finally, these results are useful for classification of forest vegetation with Landsat TM Image.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.544-549
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• 1999

The objective of this study is to identify the applicability of land cover image classified by remotely sensed data ; Landsat TM merged by SPOT for hydrological applications such as SCS runoff estimation . By comparing the calssified land cover image with the statistical data, it was proved that hey are agreed well with little errors. As a simple application , SCS runoff estimation was tested by varying rainfall intensity and AMC with Soilmap classfied by hydrologica soil map.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.231-233
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• 2003

Agricultural land use generally shows specific temporal characteristics of NDVI obtained from satellite data. In terms of winter wheat, a higher value compared with other land use types in May and a considerably low value in June could be discriminative features of temporal change of NDVI. In this study, the author examined methods for estimating winter wheat sown area in sub-pixel level of coarse resolution satellite data using temporal characteristics of NDVI. Application of the methods to the major grain production area in China exhibited properly a spatial distribution pattern of winter wheat sown area.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.535-542
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• 2001

The objective of this study is to develop a spatial analysis modeling technique to evaluate the functional suitability of forest lands for land slide prevention. The functional suitability is classified into 3 categories of high, medium and low according to the potential of land slide on forest lands. The potential of land slide hazards is estimated using the measurements of 7 major site factors : slope, bed rock, soil depth, shape of slope, forest type and D.B.H. class of trees. The analytic hierarchical process is applied to determining the relative weight of site factors in estimating the potential of land slides. The spatial analysis modeling starts building base layers for the 7 major site factors by $25m{\times}25m$ grid analysis or TIN analysis, reclassifies them and produces new layers containing standardized attribute values, needed in estimating land slide potential. To these attributes, applied is the weight for the corresponding site factor to build the suitability classification map by map algebra analysis. Then, finally, cell-grouping operations convert the suitability classification map to the land unit function map. The whole procedures of the spatial analysis modeling are presented in this paper.