Spatial analysis is the set of methods used to examine geographic data by considering the locations, geometries, attributes, and spatial relationships of the phenomena being studied ^[1][2]. Its defining characteristic is that the results depend on spatial arrangements or relationships, rather than solely on the non-spatial attributes of the data ^[3]. Spatial analysis includes operations such as spatial queries, buffering, overlay, distance and proximity measurement, terrain analysis, interpolation, network analysis, and statistical examination of spatial patterns ^[1][2][4]. More advanced methods investigate spatial clustering, spatial autocorrelation, geographic variation, and relationships between spatially distributed variables ^[2][4]. The appropriate method depends on the type of spatial data, the research question, the geographic scale, and the assumptions of the analysis ^[1][2]. Spatial analysis is applied in fields such as environmental science, urban and regional planning, public health, transportation, and natural resource management to identify patterns, evaluate spatial relationships, and support decisions ^[2][4].