• Journal of the Korean Regional Science Association
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• v.8 no.1
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• pp.31-50
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• 1992

The aim of this paper is to define major factors influencing land development of each of major uses (residential, commercial, industrial) in the process of rapid urban expansion. The main hypothesis of this study is that land use changing patterns are directed by supply side of land managed to public policies rather than demand side. The graphic analysis is applied to relationships between urban growth and land development process of each use and between land development project managed to public policies and land development process. Public and land development projects and zonning protection seem to be major roles of land supply and main determinants of urban spatial structure. Location factors for land development of each uses are selected in 23 variables. Factor analysis is applied to test correlation between variables in 1971 and 1981. Factor structure between two years is similar, but progressive processing of functional separation is derived such as intensive land use is grouped, different location between residential and industrial use is deep. Dependent variables are standardized to logarithm of land development of each use per unit vacant land in two periods, between 1971 and 1980 year and between 1981 year. Correlation analysis between 6 dependent variables and 23 location factors in each years are applied. Major factors of each use are selected in criteria such as high correlation with dependent variables, low correlation between independent variables and common application in two periods. As the result, major factors for residential land development are Land Readjustment Project (LRP), percent of total zoned area in residential zone, residential floor space density per available area, percent of total area in industrial use; for commercial development is distance to CBD, percent of total area in commercial use, residential floor space density per available area in each year, and volumn rate of industrial use; for industrial use is percent of total area of industrial use is percent of total area of industrial use, Industrial Estate Project (IES), LRP, and distance from CBD. Land development pattern of each use between two periods are slightly different. So 6 equation is derived from appling backward method of regession. Adjusted multiple R squares of all is more than 0.5 and those equation is statistically significant and valuable to assist urban land use forecasting.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.295-304
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• 2017

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.109-116
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• 2013

By IPCC climate change scenario, the socioeconomic actions such as the land use change are closely associated with the climate change as an up zoning action of urban development to increase green gas emission to atmosphere. Prediction of the land use change with rational quality can provide better data for understanding of the climate change in future. This study aims to predict land use change of Cheongju in future and SLEUTH model is used to anticipate with the status quo condition, in which the pattern of land use change in future follows the chronical tendency of land use change during last 25 years. From 40 years prediction since 2000 year, the area urbanized compared with 2000 year increases up to 87.8% in 2040 year. The ratios of the area urbanized from agricultural area and natural area in 2040 are decreased to 53.1% and 15.3%, respectively.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.345-352
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• 2004

This study analyzes interrelationship with air pollution quality and land use patterns using GIS. The relationship can be obtained via three steps: (1) making out air pollution map from air pollution information of study area, (2) dividing land use patterns into residential area, commercial area, industrial area, traffic concentrated area, and non-polluted area, and (3) spatial overlaying analysis of GIS. Moreover, through analyzing air pollution quality by land use patterns, pollution sources can be identified. The results also coincide with the characteristics of conventional air pollution finding. More detailed analyses using articulated on site air pollution quality measurement databases are needed to correctly identify the pollution sources through finding interrelationship with land use patterns and air pollution Quality using GIS. The developed method can help trace the path of pollution sources and plan urban land use projects.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.51-82
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• 2007

The purpose of this paper is exploring changes in land use pattern when considering environmental carrying capacity. A sustainable development requires a society to define sustainability constraints, environmental carrying capacity. Environmental carrying capacity can be defined as a level of human activity a region can sustain at a desired level of quality of environment. This concept of environmental carrying capacity can be applied to land use to explore sustainable land use pattern. Since land use pattern can affect environment in an important way, exploring sustainable land use pattern within the limit of environmental carrying capacity can suggest useful implications for a sustainable regional management and planning. For this purpose, this paper built the environmental carrying capacity land use model and applied it to the Metropolitan Area, Korea. System dynamics modeling methods was used to build the model. The model developed in this paper consisted of 6sectors; population, housing, industry, land, environment, and traffic sector. The model limits its main focus on the NO2 level as an indicator of quality of environment in Metropolitan Area. Box model was translated into system dynamics model and combined to urban dynamics model to estimate NO2 level, the maximum number of population, industry structure, housing and maximum amount of land use for industrial, housing, and green space that can sustain desirable NO2 level. Metropolitan area was divided into 16 areas and the model was applied to each area. Since NO2 is flowing in and out from each area, model was built to allow this transboundering nature of air pollutants. Based on the model estimation, several policy implications for a sustainable land use pattern was discussed.

• The Journal of Information Technology
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• v.10 no.4
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• pp.1-10
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• 2007

The C.B.D(Central Business District), called the central place of the urban area, is core of the city. It is consists of variety services. This study is aimed at analyzing the land use of the C.B.D. in Daejeon. Deajeon Metropolitan City site $36^{\circ}11'{\sim}36^{\circ}30'N,\;127^{\circ}15'{\sim}127^{\circ}34'E$. The field survey area is JoongAng-ro neighboring area, partial EunHaing-dong. The results are as follows: First, The land use of surveyed area is concentrate on variety services, because of excellent accessibility. Second, The land use of ground floor(Fl) and second floor(F2) has services for the customers convenience to approach. Third, The land use of surveyed area has undergone a lot of changes over the last three years(2004. 11~2007. 11.)

• Journal of the Economic Geographical Society of Korea
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• v.1 no.2
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• pp.5-19
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• 1998

This attempts to study the change of land use pattern and to (md out the factors to impact the change of the pattern in metropolitan area of Seoul. The data are collected from the 9 units of geomorphological map of the study area with the help of Mapinfo techniques. The data are analyzed statistically with aids of SAS programs. Land use patterns are classified into two: rural and urban and population, urbanization, transportation, industrialization and land development programs are selected as independent variables to change the land use patterns from 1960-1990. The results may be summarized as follows : (1) Arable lands consisted of 30% of the total land in 1960 but the ratio of the arable land decreased to less than 25% in 1990 in the study area. (2) Urban land use types are dominant around southern part of Seoul but rural one are dominant around northern and eastern area of Seoul. (3) Rural type are influenced by population factor but urban land use type are related to transportation and population factors. Land development program is not a significant one to impact the land use pattern in the study area.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.417-419
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• 2003

Based on the Chinese resource and environment database, and using the Landsat TM and ETM data acquired in 1990 and 2000 respectively, the spatial-temporal characteristics of land use/cover changes in the Dongting lake area of central China was analyzed. The result showed that cultivated land decreased by 0.57% of total cultivated land. Built -up land and water area expanded, with an increase of 8.97% and 0.43% respectively. 94 percent of the cropland decreased was changed into water (mostly to fishpond) and built-up areas. Land-use changed most quickly in cities, and the slowest in the north and east of the study area.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.702-707
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• 2002

Three periods of land-use maps of the Suomo Basin were drawn from topographic maps (1970a) and Landsat TM/ETM images (1986a and 1999a). The area of each kind of land use was calculated from the three maps. From 1970 to 1999, the area of forestland decreased 17%, the area of sparse forestland increased 8%, and the area of grassland increased 10%. The transferring trend of the land-use is that forestland turned into sparse forestland and brush land, and the brush land degenerated into grassland based on the transferring matrixes from 1970 to 1986, and from 1986 to 1999. According to the local government record and statistical data, forest cover rate had been increasing from 1970 to 1998, but the amount of growing stock had been declining. From 1957 to 1998, the amount of growing stock declined from 423m$^3$/ha to 177m$^3$/ha.

• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.33-49
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• 2015

The objective of this study was to predict land use change based on the land use change scenarios for the Hwangguji river watershed, South Korea. The land use change scenario was derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. The CLUE (conversion of land use and its effects) model was used to simulate the land use change. The CLUE is the modeling framework to simulate land use change considering empirically quantified relations between land use types and socioeconomic and biophysical driving factors through dynamical modeling. The Hwangguji river watershed, South Korea was selected as study area. Future land use changes in 2040, 2070, and 2100 were analyzed relative to baseline (2010) under the RCP4.5 and 8.5 scenarios. Binary logistic regressions were carried out to identify the relation between land uses and its driving factors. CN (Curve number) and impervious area based on the RCP4.5 and 8.5 scenarios were calculated and analyzed using the results of future land use changes. The land use change simulation of the RCP4.5 scenario resulted that the area of urban was forecast to increase by 12% and the area of forest was estimated to decrease by 16% between 2010 and 2100. The land use change simulation of the RCP8.5 scenario resulted that the area of urban was forecast to increase by 16% and the area of forest was estimated to decrease by 18% between 2010 and 2100. The values of Kappa and multiple resolution procedure were calculated as 0.61 and 74.03%. CN (III) and impervious area were increased by 0-1 and 0-8% from 2010 to 2100, respectively. The study findings may provide a useful tool for estimating the future land use change, which is an important factor for the future extreme flood.