The spatial association rule, which indicates relationship between spatial objects, is an important aspect in spatial data mining. This paper introduced the Apriori algorithm for the data min- ing in spatial association rules. Taking Fuzhou city as an example, the DEM, the slope, the aspect and the landuse of the city in 2009 were extracted to study spatial association rules between terrain fea- tures and landuse. Meanwhile, shortcomings of the Apriori algorithm and extracted spatial association rules were discussed. The results revealed that Fuzhou landuse in 2009 was largely forest lands, with not enough farmlands, residential lands and so on. It was also found that at different levels of support and confidence, extracted results would differ accordingly. Therefore, the improvement of the Apriori algorithm efficiency, the setting of reasonable support and confidence levels and the interpretation of extracted association rules are some keys for the issue.%空间关联规则是空间数据挖掘的重要内容，其结果表明了各种空间对象之间的关联关系．本研究以福州地区作为试验区，以DEM、坡度、坡向等地形特征以及2009年福州地区土地利用现状作为基础数据，利用Apriori算法从中提取出地形特征与土地利用现状之间的关联关系，讨论并分析两者之间关联规则的提取结果及空间关联规则提取方法的优缺点；研究结果表明了2009年福州地区的土地利用现状分布，即林地多，耕地、住宅用地等偏少的情况，林地分布在各种地形上且与坡向之间无强关联性；而且对于不同的最小置信度和支持度，该算法所提取的结果有所不同，如何提高算法效率、合理的设置最小置信度和支持度以及提取结果的评价与解释等将是今后进一步研究的重点．
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