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http://dx.doi.org/10.11108/kagis.2016.19.3.075

Prediction of Land-Use Change based on Urban Growth Scenario in South Korea using CLUE-s Model  

LEE, Yong-Gwan (Department of Civil & Environmental System Engineering, Konkuk University)
CHO, Young-Hyun (Hydrometeorological Cooperation Center, K-water)
KIM, Seong-Joon (Department of Civil & Environmental System Engineering, Konkuk University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.19, no.3, 2016 , pp. 75-88 More about this Journal
Abstract
In this study, we used the CLUE-s model to predict the future land-use change based on the urban growth scenario in South Korea. The land-use maps of six classes (water, urban, rice paddy, upland crop, forest, and grass) for the year 2008 were obtained from the Ministry of Environment (MOE), and the land-use data for 5-year intervals between 1980 and 2010 were obtained from the Water Resources Management Information System (WAMIS), South Korea. For predicting the future land-use change, the MOE environmental conservation value assessment map (ECVAM) was considered for identifying the development-restricted areas, and various driving factors as location characteristics were prepared for the model. The predicted results were verified by comparing them with the land-use statistics of urban areas in each province for the year 2008. The prediction error rates were 9.47% in Gyeonggi, 9.96% in Gangwon, 10.63% in Chungbuk, 7.53% in Chungnam, 9.48% in Jeonbuk, 6.92% in Jeonnam, 2.50% in Gyeongbuk, and 8.09% in Gyeongnam. The sources of error might come from the gaps between the development of political decisions in reality with spatio-temporal variation and the mathematical model for urban growth rate in CLUE-s model for future scenarios. Based on the land-use scenario in 2008, the land-use predictions for the year 2100 showed that the urban area increased by 28.24%, and the rice paddy, upland crop, and forest areas decreased by 8.27, 6.72, and 1.66%, respectively, in South Korea.
Keywords
Urban Growth Scenario; Land Use; Land Use Prediction; CLUE-s;
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Times Cited By KSCI : 9  (Citation Analysis)
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