doctoral candidate
United States of America
This review examines I.Yu. Okunev’s monograph “Fundamentals of Spatial Analysis”, in which the author explores the combination of theoretical foundations of spatial analysis with modern methods of geoinformation modeling and statistics. The book covers a wide range of approaches and techniques, (such as mapping and regionalization) using software packages like QGIS, GeoDA, and R, to multifactor models (such as clustering, autocorrelation, and geographically weighted regression), making it particularly valuable for specialists seeking to master the toolkit of spatial analysis in political geography, regional studies, and related disciplines. The author addresses not only technical issues but also the cognitive aspects of spatial perception, emphasizing that spatial factors exert a profound influence on social and political processes. The review highlights the interdisciplinary nature of the monograph, its potential contribution to the development of the Russian school of political geography and spatial analysis and also points to aspects that could be further expanded-particularly issues of methodological rigor, work with big data, and examples from global practices in developing countries. Overall, the publication serves as a deep and comprehensive guide to integrating quantitative and qualitative methods of spatial analysis, reflecting the current trend of reconciling quantitative and qualitative traditions in the social sciences.
spatial analysis, spatial econometrics, causal inference revolution, political geography, GIS, QGIS, GeoDA, spatial autocorrelation, geographically weighted regression, modifiable areal unit problem.
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