中文摘要：

空间数据挖掘的过程与空间概念形成和分析的过程密切相关。本文以空间数据中抽取出各层次、各粒度的概念为主线，以概念形成和分析的形式化理论——概念格和云模型为理论基础，总结了基于概念分析的空间数据挖掘方法及应用，包括概念格的空间关联规则挖掘方法及应用、概念格的概念聚类挖掘方法及应用、云模型的空间关联规则挖掘方法及应用、云模型的空间聚类／分类挖掘方法及应用等。概念格提供了一种形式化的概念描述和概念结构分析的理论和方法，云模型提供了一种综合处理模糊性、随机性以及二者之间关联性的不确定性理论和方法，利用概念格、云模型等形式化的理论和方法分析和描述空间数据挖掘过程中空间概念的形成、空间概念的结构关系、空间概念之间以及空间概念层次之间的不确定性是概念分析的空间数据挖掘研究的进一步的研究方向。

英文摘要：

The process of spatial data mining is closely related to the process of spatial concept formation and analysis. From the view of recognition, centered in the thought to extract the concepts in different hierarchies and granularities, based on the formal theories of concept formation and analysis, i. e. concept lattice and cloud model, this study analyzes and summarizes the methods and their application of spatial data mining based on concept analysis, including the methods and their application of spatial association rule mining based on concept lattice, those of conceptual clustering based on concept lattice, those of spatial association rules mining based on cloud model, those of spatial clustering/classification based on cloud model, etc. Concept lattice provides a kind of theory which can express and analyze spatial concepts and their concept structural relationships by mathematical and formal methods, which is good for the understanding of human, and is convenient to process by computers; Cloud model is a kind of uncertainty theory which can deal with fuzziness, randomness and their association, it is a more powerful and effective uncertainty theory than fuzzy sets and rough sets. The further research directions of spatial data mining based on concept analysis are as follows ： （ 1 ） the formal expression of spatial concepts ; （2） the formal analysis of the process of spatial concepts formation ; （3） the formal expression and analysis of the structural rela- tionships of spatial concepts ; （4） the construction of the spatial concepts hierarchy and their formal expression and analysis; （5） the expression and analysis of spatial concepts and the concept structural relationships with uncertainty.