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Estimation of Future Land Cover Considering Shared Socioeconomic Pathways using Scenario Generators

Scenario Generator를 활용한 사회경제경로 시나리오 반영 미래 토지피복 추정

  • Song, Cholho (Dept. of Environmental Science and Ecological Engineering, Korea University) ;
  • Yoo, Somin (Dept. of Environmental Science and Ecological Engineering, Korea University) ;
  • Kim, Moonil (Environmental GIS/RS Center, Korea University) ;
  • Lim, Chul-Hee (Institute of Life Science and Natural Resources, Korea University) ;
  • Kim, Jiwon (Dept. of Climatic Environment, Korea University) ;
  • Kim, Sea Jin (Dept. of Environmental Science and Ecological Engineering, Korea University) ;
  • Kim, Gang Sun (Korea Environment Institute) ;
  • Lee, Woo-Kyun (Division of Environmental Science and Ecological Engineering, Korea University)
  • 송철호 (고려대학교 환경생태공학과) ;
  • 유소민 (고려대학교 환경생태공학과) ;
  • 김문일 (고려대학교 환경 GIS/RS 센터) ;
  • 임철희 (고려대학교 생명자원연구소) ;
  • 김지원 (고려대학교 기후환경학과) ;
  • 김세진 (고려대학교 환경생태공학과) ;
  • 김강선 (한국환경정책.평가연구원) ;
  • 이우균 (고려대학교 환경생태공학부)
  • Received : 2018.06.28
  • Accepted : 2018.08.29
  • Published : 2018.09.29

Abstract

Estimation of future land cover based on climate change scenarios is an important factor in climate change impact assessment and adaptation policy. This study estimated future land cover considering Shared Socioeconomic Pathways (SSP) using Scenario Generators. Based on the storylines of SSP1-3, future population and estimated urban area were adopted for the transition matrix, which contains land cover change trends of each land cover class. In addition, limits of land cover change and proximity were applied as spatial data. According to the estimated land cover maps from SSP1-3 in 2030, 2050, and 2100, respectively, urban areas near a road were expanded, but agricultural areas and forests were gradually decreased. More drastic urban expansion was seen in SSP3 compared to SSP1 and SSP2. These trends are similar with previous research with regard to storyline, but the spatial results were different. Future land cover can be easily adjusted based on this approach, if econometric forecasts for each land cover class added. However, this requires determination of econometric forecasts for each land cover class.

Keywords

Acknowledgement

Supported by : 환경부, 산림청(한국임업진흥원)