{"title":"Spatial Autocorrelation Methods in Identifying Migration Patterns: Case Study of Slovakia","authors":"Loránt Pregi, Ladislav Novotný","doi":"10.1007/s12061-024-09615-5","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":46392,"journal":{"name":"Applied Spatial Analysis and Policy","volume":"18 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12061-024-09615-5.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Spatial Analysis and Policy","FirstCategoryId":"90","ListUrlMain":"https://link.springer.com/article/10.1007/s12061-024-09615-5","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍：
Description
The journal has an applied focus: it actively promotes the importance of geographical research in real world settings
It is policy-relevant: it seeks both a readership and contributions from practitioners as well as academics
The substantive foundation is spatial analysis: the use of quantitative techniques to identify patterns and processes within geographic environments
The combination of these points, which are fully reflected in the naming of the journal, establishes a unique position in the marketplace.
RationaleA geographical perspective has always been crucial to the understanding of the social and physical organisation of the world around us. The techniques of spatial analysis provide a powerful means for the assembly and interpretation of evidence, and thus to address critical questions about issues such as crime and deprivation, immigration and demographic restructuring, retailing activity and employment change, resource management and environmental improvement. Many of these issues are equally important to academic research as they are to policy makers and Applied Spatial Analysis and Policy aims to close the gap between these two perspectives by providing a forum for discussion of applied research in a range of different contexts
Topical and interdisciplinaryIncreasingly government organisations, administrative agencies and private businesses are requiring research to support their ‘evidence-based’ strategies or policies. Geographical location is critical in much of this work which extends across a wide range of disciplines including demography, actuarial sciences, statistics, public sector planning, business planning, economics, epidemiology, sociology, social policy, health research, environmental management.
FocusApplied Spatial Analysis and Policy will draw on applied research from diverse problem domains, such as transport, policing, education, health, environment and leisure, in different international contexts. The journal will therefore provide insights into the variations in phenomena that exist across space, it will provide evidence for comparative policy analysis between domains and between locations, and stimulate ideas about the translation of spatial analysis methods and techniques across varied policy contexts. It is essential to know how to measure, monitor and understand spatial distributions, many of which have implications for those with responsibility to plan and enhance the society and the environment in which we all exist.
Readership and Editorial BoardAs a journal focused on applications of methods of spatial analysis, Applied Spatial Analysis and Policy will be of interest to scholars and students in a wide range of academic fields, to practitioners in government and administrative agencies and to consultants in private sector organisations. The Editorial Board reflects the international and multidisciplinary nature of the journal.
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