Scenario simulation of land system change in the Beijing-Tianjin-Hebei region

• Yang, Yuanyuan ^[1] ; Bao, Wenkai ^[1] ; Liu, Yansui ^[1]
  1. [1] Institute of Geographic Sciences and Natural Resources Research

     Institute of Geographic Sciences and Natural Resources Research

     China

     
• Localización: Land use policy: The International Journal Covering All Aspects of Land Use, ISSN 0264-8377, ISSN-e 1873-5754, Nº. 96, 2020
• Idioma: inglés
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• Dialnet Métricas: 5 Citas
• Resumen

  • Urbanization-induced land use problems have been haunting China’s urban agglomerations ever since the beginning of this period of unparalleled economic progress. The Beijing-Tianjin-Hebei (BTH) region is no exception, where coordinated development planning has been implemented by the central government to further resolve attributed problems. Land use simulation models can be used to help governments and planners understand how planning and policies affect the future landscape, by developing sustainable land use strategies which may reasonably balance urbanization and eco-environmental protection. In this paper, we explored the characteristics of historical land use dynamics from 2000 to 2015 in the BTH region and simulated its future land use patterns for 2030 by combining the Dyna-CLUE model with a Markov model to deal with some short comings of existing land use models. The main conclusions are as follows: (1) The figure of merits (FoM) based on the method of three-map comparison reached 85.89 %, which indicated that the simulation model has satisfactory accuracy. (2) Land use structures and spatial patterns differed significantly under business as usual (BAU) scenario, cropland protection (CP) scenario and ecological security (ES) scenario, respectively, owing to the variation of the major objectives designed for different scenarios. (3) By scenario analysis and through tradeoffs, the land use mode under the ecological security scenario might be the optimal solution for future coordinated development in the BTH region. These results will provide theoretical basis and meaningful guidance for regional land optimal allocation.