Cellular automata show thoroughly the essence of complexity science that complicated construction comes from the interaction of the simple sub-system, so cellular automata is fit to study geographic system with spatial-temporal feature very much.
元胞自动机(Cellular Automata，简称CA)充分体现了“复杂结构来自于简单子系统的相互作用”这一复杂性科学的精髓，非常适用于具有复杂时空特征的地理系统模拟。
参考来源 - 地理特征元胞自动机及城市土地利用演化研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The conceptual modeling elements and mutual relations between them are discussed and some key technical problems are identified in the development of feature based temporal - spatial data models.
讨论了基于特征的概念模型要素及相互关系；提出了基于特征的时空数据模型所面临的关键技术。
A product correlation algorithm of image registration based on feature and spatial-temporal correlation was presented.
提出了基于特征和时空关联的积相关图像匹配算法。
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