地理科学进展 ›› 2018, Vol. 37 ›› Issue (1): 152-162.doi: 10.18306/dlkxjz.2018.01.016

• 自然地理综合研究 • 上一篇    下一篇

土地变化模型方法综述

戴尔阜1,2,3(), 马良1,2,3   

  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. 中国科学院陆地表层格局与模拟重点实验室,北京 100101
  • 收稿日期:2018-01-15 修回日期:2018-01-23 出版日期:2018-01-28 发布日期:2018-01-28
  • 作者简介:

    作者简介:戴尔阜(1972-),男,甘肃平凉人,研究员,主要从事自然地理综合研究、气候变化及其区域响应、土地变化模拟研究,E-mail: daief@igsnrr.ac.cn

  • 基金资助:
    国家自然科学基金项目(L1624026,41571098,41530749);中国科学院学部学科发展战略研究项目(2016-DX-C-02);国家重点基础研究发展(973)计划项目(2015CB452702)

Review on land change modeling approaches

Erfu DAI1,2,3(), Liang MA1,2,3   

  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. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2018-01-15 Revised:2018-01-23 Online:2018-01-28 Published:2018-01-28
  • Supported by:
    National Natural Science Foundation of China, No.L1624026, No.41571098, No.41530749;Research Project on the Development Strategy of Chinese Academy of Sciences, No.2016-DX-C-02;National Basic Research Program of China (973Program), No.2015CB452702

摘要:

土地系统变化长期以来不仅是地理学研究热点,也是资源环境经济学、生态学、城市规划等多学科领域关注的主题。构建模型模拟土地变化能够促进理解人地相互作用机制,模拟结果可为土地资源优化与资源环境政策制定提供依据。不同研究者基于不同学科理论、应用多种方法构建土地变化模型,模型从早期关注自然覆被类型变化发展到对人类决策行为的刻画,从统计方法发展到更突出空间分布的元胞自动机方法,以及更聚焦土地变化过程的经济学方法和多主体方法。未来土地变化模型发展方向为:在多尺度进行多方法耦合,对土地变化过程进行更为明晰地刻画,将土地变化模型与其他地球系统模型耦合等方面,进一步能够促进解释复杂人地系统,并推进模型在决策支持层面的应用。

关键词: 土地变化科学, 土地利用/覆被变化, 土地变化模型, 多主体模型, 元胞自动机

Abstract:

Land change has long been the research hot-spot of geography, and is also the focus of multiple disciplines including resource and environment economics, ecology, and urban planning. Land change models and simulations are an effective approach for understanding the mechanism of human-environment interactions. The modeling results are also valuable for the government to make resource management and environmental policies. Researchers of different fields have applied various approaches based on their theories to develop land change models. Attention has evolved from modeling land cover types to representation of human decision-making behaviors. The methods have shifted from statistical to cellular automata that can better characterize spatial patterns, and to economic methods and agent-based methods that can better represent the processes and mechanisms of land change. Future land change models should focus coupling multiple methods cross scales. Land change processes should be better represented. The complexity of the human-environment system can be better explained by a combination of land change models and other earth system models. The application of models to support policymaking also needs more attention.

Key words: land change science, land use/land cover change, land change model, agent-based model, cellular automata