计算机科学
土地覆盖
相互依存
土地利用
领域(数学)
比例(比率)
数据科学
仿真建模
基于Agent的模型
管理科学
程式化事实
计算模型
环境资源管理
风险分析(工程)
人工智能
环境科学
地理
地图学
工程类
土木工程
政治学
医学
数学
纯数学
法学
微观经济学
经济
宏观经济学
作者
Dawn C. Parker,Steven M. Manson,Marco A. Janssen,Matthew J. Hoffmann,Peter Deadman
标识
DOI:10.1111/1467-8306.9302004
摘要
Abstract This article presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decision making, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas. We discuss the potential strengths of MAS/LUCC models and suggest that these strengths guide researchers in assessing the appropriate choice of model for their particular research question. We find that MAS/LUCC models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We discuss a range of possible roles for MAS/LUCC models, from abstract models designed to derive stylized hypotheses to empirically detailed simulation models appropriate for scenario and policy analysis. We also discuss the challenge of validation and verification for MAS/LUCC models. Finally, we outline important challenges and open research questions in this new field. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers whose goal is to create fine-scale models of LUCC phenomena that focus on human-environment interactions.
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