提出了一种基于面向对象知识表达的空间推理决策方法 ,该方法扩展了常规的GIS空间分析功能 ,使其建立在GIS空间分析与领域知识基础上。认为GIS空间分析与领域知识利用的结合需要建立统一的知识表达概念模型 ,通过将常规决策知识设计为决策知识类 ,将决策事实作为事实知识类处理 ,并由知识类的消息机制进行内部通讯 ,实现空间推理决策的智能化。在进行领域知识分析与知识分类的基础上 ,给出了领域知识类的层次结构组织图和知识类定义以及决策知识及事实知识的面向对象表达 ,最后给出了空间知识类的形成及空间推理决策过程。方法的实用性在实践中得到验证。

GIS (or Geographical Information System) works well on spatial data manage but has shortage in spatial analysis. Many spatial decision-making problems are dependent on spatial analysis so it is essential to extend the function of GIS analysis. Spatial decision support system has become an important research area in GIS and the traditional methods rely on analysis models while focus little on the importance of knowledge. Model-based decision support system presumes that the real world is structured and can be well simulated. But the fact is that most of the decision problems are ill-structured and cannot do without domain knowledge. How to acquire sufficient decision-related knowledge and well organize it imposes a great challenge both to spatial information science and AI (artificial intelligence). In this paper, an object-oriented spatial knowledge representation is proposed. The foundation of this method is based on knowledge analysis and knowledge classification. The fact that domain knowledge has layer structure should be considered when knowledge base is designed. The layer structure and organization of domain knowledge class and classification model know are given in this article. The whole knowledge used can be classified into decision area class, decision area sub-class, knowledge class of decision area sub-class, sub-knowledge class and knowledge unit according to the layer structure of knowledge from the top to bottom. Each knowledge class encapsulates attributes, methods and some rules. The detail of spatial reasoning controlled by knowledge unit is illustrated. Based on our method proposed, an application in intelligent spatial decision support system in agriculture is introduced. The function of GIS offers basic spatial data and facts that are the input of spatial decision-making module. In this way GIS and knowledge-based reasoning can be integrated.