Spatial data mining is a research field and methodological approach concerned with the discovery of interesting, useful, and non-trivial patterns and knowledge from large spatial datasets. It addresses the unique characteristics of spatial data, such as spatial autocorrelation and spatial heterogeneity, to uncover relationships and anomalies that are spatially referenced, proving significant for analyzing geographical, environmental, and urban phenomena.