기후변화 시나리오에 따른 미래 토지피복변화 예측 및 군집분석을 이용한 지역 특성 분석
Prediction of Land-cover Change Based on Climate Change Scenarios and Regional Characteristics using Cluster Analysis
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This study was conducted to predict future land-cover changes under climate change scenarios and to cluster analysis of regional land-cover characteristics. To simulate the future land-cover according to climate change scenarios - A1B, A2, and B1 of the Special Report on Emissions Scenarios (SRES), Dyna-CLUE (Conversion of Land Use Change and its Effects) was applied for modeling of competition among land-use types in relation with socioeconomic and biophysical driving factors. Gyeonggi-do were selected as study areas. The simulation results from 2010 to 2040 suggested future land-cover changes under the scenario conditions. All scenarios resulted in a gradual decrease in paddy area, while upland area continuously increased. A1B scenario showed the highest increase in built-up area, but all scenarios showed only slight changes in forest area. As a result of cluster analysis with the land-cover component scores, 31 si/gun in Gyeonggi-do were classified into three clusters. This approach is expected to be useful for evaluating and simulating land-use changes in relation to development constraints and scenarios. The results could be used as fundamental basis for providing policy direction by considering regional land-cover characteristics.
Abstract
This study was conducted to predict future land-cover changes under climate change scenarios and to cluster analysis of regional land-cover characteristics. To simulate the future land-cover according to climate change scenarios - A1B, A2, and B1 of the Special Report on Emissions Scenarios (SRES), Dyna-CLUE (Conversion of Land Use Change and its Effects) was applied for modeling of competition among land-use types in relation with socioeconomic and biophysical driving factors. Gyeonggi-do were selected as study areas. The simulation results from 2010 to 2040 suggested future land-cover changes under the scenario conditions. All scenarios resulted in a gradual decrease in paddy area, while upland area continuously increased. A1B scenario showed the highest increase in built-up area, but all scenarios showed only slight changes in forest area. As a result of cluster analysis with the land-cover component scores, 31 si/gun in Gyeonggi-do were classified into three clusters. This approach is expected to be useful for evaluating and simulating land-use changes in relation to development constraints and scenarios. The results could be used as fundamental basis for providing policy direction by considering regional land-cover characteristics.
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