地理科学进展

地理科学进展 ›› 2019, Vol. 38 ›› Issue (1): 111-125.doi: 10.18306/dlkxjz.2019.01.010

• 研究综述 • 上一篇    下一篇

城镇化与生态环境耦合动态模拟模型研究进展

崔学刚1,2(), 方创琳1,*(), 李君3, 刘海猛1,2, 张蔷1   

  1. 1. 中国科学院地理科学与资源研究所,北京 100101
    2. 中国科学院大学,北京 100049
    3. 东北大学信息科学与工程学院,沈阳 110004
  • 收稿日期:2018-04-03 修回日期:2018-09-10 出版日期:2019-01-28 发布日期:2019-01-22
  • 通讯作者: 方创琳
  • 作者简介:

    第一作者简介：崔学刚(1990— ),男,山东淄博人,博士生,主要从事城市地理与区域规划研究。E-mail: cuixg.16b@igsnrr.ac.cn

  • 基金资助:
    国家自然科学基金重大项目(41590840,41590842)

Progress in dynamic simulation modeling of urbanization and ecological environment coupling

Xuegang CUI1,2(), Chuanglin FANG1,*(), Jun LI3, Haimeng LIU1,2, Qiang ZHANG1   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2018-04-03 Revised:2018-09-10 Online:2019-01-28 Published:2019-01-22
  • Contact: Chuanglin FANG
  • Supported by:
    Major Program of National Natural Science Foundation of China, No. 41590840 and 41590842.

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摘要：

按照地理学科发展趋势,对城镇化与生态环境耦合的研究将由定量描述转入动态模拟。目前,城镇化与生态环境耦合动态模拟模型呈现多元化。论文系统梳理了其中4类常见的动态模拟模型,包括城镇化与生态环境耦合系统动力学模型、基于人工智能算法的城镇化与生态环境耦合动态模拟模型、基于土地利用变化的城镇化与生态环境耦合动态模拟模型以及基于多模型集成的城镇化与生态环境耦合复合模型。主要结论如下：系统动力学模型被广泛应用于城市复杂系统、城市转型和可持续发展以及城镇化与生态环境单要素耦合的动态模拟之中,但存在空间解释不足以及忽视系统自适应性等问题;人工智能算法(ANN和BN)在自学习、自组织、自适应系统或不确定性系统模拟中具有显著优势,并被应用于城市扩张、环境变化、资源需求以及生态脆弱性的识别之中,但应用面相对狭窄且限制条件偏多;土地利用变化模型(CLUE/CLUE-S、CA和MAS)局限于从土地城镇化视角模拟城镇化与生态环境耦合;基于多模型集成的复合模型实现了各模型之间的优势互补,已成为城镇化与生态环境耦合动态模拟模型的发展趋势。今后,应从技术和理论2个层面实现城镇化与生态环境耦合动态模拟模型的进一步发展,并加强对微观过程的模拟。

关键词: 城镇化与生态环境耦合, 动态模拟, 系统动力学模型, 人工智能算法, 土地利用变化模型, 复合模型

Abstract:

The development trend of geographical science indicates that the research on urbanization and ecological environment coupling will move from quantitative description to dynamic simulation. At present, the dynamic simulation models of urbanization and ecological environment coupling are diverse. This article reviewed and summarized four common types of models, including system dynamics model, artificial intelligence algorithm, land use change model, and composite model. The main conclusions are as follows: 1) System dynamics models are widely used in the dynamic simulation of urban complex nonlinear systems, urban transition and sustainable development, and urbanization and ecological environment elements coupling. However, spatial interpretation is insufficient and system adaptability is ignored. 2) Artificial intelligence algorithm has significant advantages in simulating self-learning, self-organizing, and adaptive systems, as well as uncertain systems. It is applied to identify urban expansion, environmental change, resource demand, and ecological vulnerability, but the application range is narrow. 3) Land use change models are limited to the simulation of urbanization and ecological environment coupling under the condition of land transfer to urban use. 4) To achieve complementarities between the various models, it has become a trend to develop composite models based on multi-model integration. In the future, we should develop dynamic simulation models from both the technical and theoretical aspects, and strengthen the simulation of microscopic processes.

Key words: urbanization and ecological environment coupling, dynamic simulation, system dynamics model, artificial intelligence algorithm, land use change model, composite model