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Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China

Author

Listed:
  • Huiran Han

    (School of Geography, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian district, Beijing 100875, China)

  • Chengfeng Yang

    (School of Geography, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian district, Beijing 100875, China)

  • Jinping Song

    (School of Geography, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian district, Beijing 100875, China)

Abstract

Land use and land cover (LULC) models are essential for analyzing LULC change and predicting land use requirements and are valuable for guiding reasonable land use planning and management. However, each LULC model has its own advantages and constraints. In this paper, we explore the characteristics of LULC change and simulate future land use demand by combining a CLUE-S model with a Markov model to deal with some shortcomings of existing LULC models. Using Beijing as a case study, we describe the related driving factors from land-adaptive variables, regional spatial variables and socio-economic variables and then simulate future land use scenarios from 2010 to 2020, which include a development scenario (natural development and rapid development) and protection scenarios (ecological and cultivated land protection). The results indicate good consistency between predicted results and actual land use situations according to a Kappa statistic. The conversion of cultivated land to urban built-up land will form the primary features of LULC change in the future. The prediction for land use demand shows the differences under different scenarios. At higher elevations, the geographical environment limits the expansion of urban built-up land, but the conversion of cultivated land to built-up land in mountainous areas will be more prevalent by 2020; Beijing, however, still faces the most pressure in terms of ecological and cultivated land protection.

Suggested Citation

  • Huiran Han & Chengfeng Yang & Jinping Song, 2015. "Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China," Sustainability, MDPI, vol. 7(4), pages 1-20, April.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:4:p:4260-4279:d:48102
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    1. Hubacek, Klaus & Sun, Laixiang, 2001. "A scenario analysis of China's land use and land cover change: incorporating biophysical information into input-output modeling," Structural Change and Economic Dynamics, Elsevier, vol. 12(4), pages 367-397, December.
    2. Brueckner, Jan K & Kim, Hyun-A, 2003. "Urban Sprawl and the Property Tax," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 10(1), pages 5-23, January.
    3. Peter Verburg & Bas Eickhout & Hans Meijl, 2008. "A multi-scale, multi-model approach for analyzing the future dynamics of European land use," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 57-77, March.
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