The collapse of the socialist regime led to significant changes in migration patterns,
garnering considerable attention in geographical research. However, despite the increased
interest, many studies on internal migration lack a detailed analysis of its spatial
aspects. Spatial autocorrelation methods can reveal spatial patterns, but so far they
have not been applied in the detailed research of internal migration in post-socialist
countries. The aim of this study is to explore the spatial patterns of internal migration
with regard to intra-regional and inter-regional migration processes using selected
indicators of spatial autocorrelation (Global Moran’s I, Anselin local Moran’s I and
Getis-Ord Gi* statistic) with Slovakia as a case study. A partial goal is to evaluate
the benefits of applying these methods in the assessment of internal migration. Local
indicators of spatial autocorrelation demonstrated significant differentiation of
both intra-regional and inter-regional migration processes. The dominant intra-regional
process is the decentralization of the population, which is very intensive in the
regions of the largest towns and cities. Inter-regional migration displays spatial
polarisation, emphasizing the importance of the location of key economic centres.
The methodology employed in this study clearly displays the clusters of municipalities
with above-average and below-average values. This approach enables the identification
and cartographic interpretation of specific municipalities where migration contributes
the most to the spatial redistribution of the population. The study serves as a valuable
framework for similar analyses, emphasizing the broader applicability of spatial autocorrelation
methods in studying migration patterns.
