PROGRESS IN GEOGRAPHY ›› 2018, Vol. 37 ›› Issue (1): 152-162.doi: 10.18306/dlkxjz.2018.01.016

• Comprehensive Research • Previous Articles     Next Articles

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

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