首先对当前空间数据的复杂性特征进行了分析，提出海量的数据，空间属性之间的非线性关系，空间数据的尺度特征，空间信息的模糊性，空间维数的增高以及空间数据的缺值是当前空间数据复杂性的主要表现特征，并以其为线索将近年来在空间数据知识发现领域的研究进展及其热点进行了较为系统的归纳，在此基础上，对空间数据知识发现与GIS的关系进行了阐述，并对空间数据知识发现的未来发展趋势进行了展望。

In this paper, the authors analyze the increasing trend of spatial data and propose that the large data sets, nonlinear relationship among attributes, scaling characters of spatial data, fuzzy character of spatial information, multidimensional attributes and missing data problems are major characters of the complexity characters of spatial data. The proceedings of spatial data mining researches are systematically summarized in the clue of the complexity characters which mentioned above. In conclusion, the relationship between spatial data mining and GIS is expatiated, and the future of the relative research areas are prospected.