土地利用动态模拟模型的构建及其应用——以北京市海淀区为例

Construction of a Land-use Change Simulation Model and Its Application in Haidian District, Beijing

CLUE-S模型是一个基于经验统计原理的模拟多土地利用类型空间变化的动态模拟模型,它在世界多个国家和地区的区域尺度农业、森林为主的土地利用变化模拟中得到应用.作者对CLUE-S模型进行了改进,改进后的模型(CLUE-SII)引入了动态计算的邻域分析因子,可以对土地利用变化中的自发过程、自组织过程和土地利用类型间的竞争进行模拟,还可以根据研究区域特点构建不同的模拟方案,在这些模拟方案中,局地因子和邻域因子在土地利用变化中的作用方式不同.应用CLUE-SII对北京市海淀区1991～2001年土地利用变化进行了多方案模拟,结果表明邻域因子对城镇用地变化具有重要作用,其中将邻域因子看作自发过程放大因子的模拟方案获得了较好的模拟结果,整图符合比达到77%,其中城镇用地符合比达到82%,Kappa值达到0.754.CLUE-SII在北京市海淀区的应用实例表明,该模型可以对高分辨率和多土地利用类型下的城市扩展进行有效模拟,扩展了CLUE-S的应用领域;通过构建多模拟方案,不但可以探索最佳的模拟结果,还可以研究和分析不同土地利用驱动因子在土地利用变化中的作用模式.

CLUE-s (Conversion of Land Use and its Effects in small extent) is a model for simulating spatial changes in land use. The model was applied for regional agriculture and forest land-use system simulations in many countries. The author extended the CLUE-s model with a dynamic neighborhood analysis. The extended model (CLUE-sII) could simulate the self-organizational processes, spontaneous processes and the competition processes of the land-use changes. CLUE-sII can also implement different simulation schemes according to the characteristics of the study area. The local factors and the neighborhood factors play different roles in each scheme. Therefore, the researchers could find the best scheme for the specific study area. Land use change from 1991 to 2001 is simulated using CLUE-sII for Haidian District, Beijing. The results indicate that neighborhood factor analyse is important to simulate urban land-use changes and the scheme that took the neighborhood factor as a magnifying factor to the spontaneous processes obtained the best results, with which the whole map correspondence proportion gained 77% and the Kappa of urban attained 0.754. The case study in this paper showed that CLUE-sII could simulate urban sprawl with multiple land-use types at a high spatial and temporal resolution. Through constructing multiple simulation schemes, one can not only find the best simulation performance, but also could obtain more information on the importance of different land-use drivers.