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This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading experts in the field. Four main aspects are highlighted, dealing with spatial analysis, pattern analysis, local statistics as well as illustrative empirical applications. Researchers and students will gain an appreciation of Getis' methodological contributions to spatial analysis and the broad impact of the methods he has helped pioneer on an impressively broad array of disciplines including spatial epidemiology, demography, economics, and ecology. The volume is a compilation of high impact original contributions, as evidenced by citations, and the latest thinking on the field by leading scholars. This makes the book ideal for advanced seminars and courses in spatial analysis as well as a key resource for researchers seeking a comprehensive overview of recent advances and future directions in the field.

ABSTRACTThis paper explores the extension of integrated econometric/input‐output models from a single to a multiregional context. A number of methodological issues associated with existing treatments of extraregional relations in both traditional multiregional econometric models and the more recent single region integrated models are discussed. A series of new approaches are introduced that rely on the integration of econometric and input‐output methods to specify extraregional linkages. A comparison of these alternative modeling approaches is undertaken using employment series for 5 regions in Southern California. The forecasting accuracies are evaluated in a series of out‐of‐sample forecasting experiments. The findings suggest that the forecasting performance of the multiregional extensions of the integrated approach is competitive with the performance of single region implementations. The performance of the alternative multiregional approaches is found to be relatively more sensitive to regionalization of the IO component and the level of industrial disaggregation than to the incorporation of distance in the specification of the multiregional linkages.

Front Matter -- Copyright -- Contents -- Contributors -- Acknowledgements -- Introduction: Spatial analysis and the social sciences in a rapidly changing landscape -- PART 1 THEORY, FRAMEWORKS AND FOUNDATIONS -- 1. GIScience through the looking glass -- 2. Locating spatial data in the social sciences -- 3. Analytical environments -- 4. Complexity -- 5. Linking spatial patterns to processes -- PART 2 METHODS -- 6. Spatial econometrics -- 7. Local modeling in a regression framework -- 8. Simulating geographical systems using cellular automata and agent-based models -- 9. Microsimulation -- 10. Multilevel models -- 11. Context-dependent movement analysis -- 12. Spatial interaction modeling -- 13. Spatial optimization -- 14. Cluster identification -- 15. Spatial point patterns -- 16. Spatial dynamics -- 17. GeoAI in social science -- 18. Exploratory spatial data analysis -- 19. Geovisualization and geovisual analysis -- 20. Immersive virtual reality and spatial analysis -- 21. Spatiotemporal data mining -- PART 3 APPLICATIONS -- 22. Neighborhood change -- 23. The spatial analysis of gentrification: Formalizing geography in models of a multidimensional urban process -- 24. Social networks in space -- 25. Analysing the dynamics of inter-regional inequality: The case of Canada -- 26. Spatial approaches to energy poverty -- 27. The shape of bias: Understanding the relationship between compactness and bias in U.S. elections -- 28. Space and New Urbanism -- 29. Space for wellbeing -- 30. Urban analytics: History, trajectory and critique -- PART 4 EMERGING CHALLENGES AND ISSUES -- 31. Reproducibility and replicability in spatial science -- 32. An image library: The potential of imagery in (quantitative) social sciences -- 33. Uncertainty -- Index.

"Diese Studie behandelt die Frage der Konvergenz regionaler Einkommen in den Vereinigten Staaten vom Standpunkt der räumlichen Ökonometrie aus. Kürzlich entwickelte Methoden einer Analyse räumlicher Untersuchungsdaten verschaffen neue Einsichten in die geographische Dynamik der Muster regionalen Wachstums von Einkommen in den Vereinigten Staaten im Zeitraum 1929-94. Für die genannte Untersuchungsperiode werden robuste Muster globaler wie auch örtlicher räumlicher Autokorrelationen festgestellt, wobei der Umfang letzterer sich zudem als in kräftigem zeitlichem Gleichschritt mit der Streuung regionaler Einkommen erweist. Eine räumliche ökonometrische Analyse der bekannten Baumol Spezifierung liefert Beweise fehlerhafter Spezifizierungen infolge unbeachtet gebliebener Abhängigkeit von räumlichen Irrtümern. Dank dieser Abhängigkeit kann der Schock eines Staates in Nachbarstaaten Kreise ziehen, und die Ubergangsdynamik des Konvergenzprozesses verkomplizieren." (Autorenreferat)