Agent based model of land system: Theory, application and modelling framework

被引：0
|
作者：
Dai E. [1 ,3 ]
Ma L. [1 ,3 ]
Yang W. [2 ,4 ]
Wang Y. [1 ,3 ]
Yin L. [2 ,3 ]
Tong M. [1 ,3 ]
机构：
[1] Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Beijing
[2] Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
[3] University of Chinese Academy of Sciences, Beijing
[4] School of Geography and Planning, Sun Yat-Sen University, Guangzhou
来源：
Dili Xuebao/Acta Geographica Sinica | 2019年 / 74卷 / 11期
基金：
中国国家自然科学基金; 国家重点研发计划;
关键词：
Agent based model; Land change model; Land change science; Land system; Land use; Modeling framework;
D O I：
10.11821/dlxb201911005
中图分类号：
学科分类号：
摘要：
Land change science has become an interdisciplinary research direction for understanding human-natural coupling systems. As a process-oriented modelling approach, Agent based model (ABM) plays an important role in revealing the driving forces of land change and understanding the process of land change. This paper starts from three aspects: the theory, application and modeling framework of ABM. First, we summarize the theoretical basis of ABM and introduce some related concepts. Then we expound the application and development of ABM in both urban land systems and agricultural land systems, and further introduce the case study of an model on Grain to Green Program in the Hengduan Mountains region, Southwest China. On the basis of combing the ABM modeling protocol, we propose the land system ABM modeling framework and process from the perspective of agents. In terms of urban land use, ABM research initially focused on the study of urban expansion based on landscape, then expanded to issues like urban residential separation, planning and zoning, ecological functions, etc. In terms of agricultural land use, ABM application presents more diverse and individualized features. Research topics include farmers' behavior, farmers' decision-making, planting systems, agricultural policy. Compared to traditional models, ABM is more complex and difficult to generalize beyond specific context since it relies on local knowledge and data. However, due to its unique bottom-up model structure, ABM has an indispensable role in exploring the driving forces of land change as well as the impact of human behavior on the environment. © 2019, Science Press. All right reserved.
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页码：2260 / 2272
页数：12
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