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STARS: Space-Time Analysis of Regional Systems

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Handbook of Applied Spatial Analysis

Abstract

One of the active areas in the field of Geographic Information Sciences (GIS) is the development of new methods of exploratory spatial data analysis. A number of impressive efforts have recently appeared to provide researchers with powerful tools for both geospatial statistical analysis, data mining, as well as geovisualization. Well known efforts include the GeoDa environment (Anselin 2003), the GeoVista Studio (Takatsuka and Gahegan 2002), Cartographic Data Visualizer (Dykes 1995), SAGE (Wise et al. 2001) and the ArcView-XGobi project (Symanzik et al. 1998).

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References

  • Anselin L (1995) Local indicators of spatial association-LISA. Geogr Anal 27(2)::93–115

    Google Scholar 

  • Anselin L (2003) An introduction to EDA with GeoDa. Technical report, Spatial Analysis Laboratory, University of Illinois

    Google Scholar 

  • Carlino GA, Mills LO (1993) Are U.S. regional incomes converging? A time series analysis. J Monet Econ 32(2):335–346

    Article  Google Scholar 

  • Christakos G, Bogaert P, Serre M (2001) Temporal GIS. Springer, Berlin, Heidelberg and New York

    Google Scholar 

  • Dykes JA (1995) Pushing maps past their established limits: a unified approach to cartographic visualization. In Innovations in GIS. Taylor and Francis, London, pp. 177–187

    Google Scholar 

  • Egenhofer MJ, Golledge RG (1997) Spatial and temporal reasoning in geographic information systems. Oxford University Press, Oxford and New York

    Google Scholar 

  • Hinsen K (2000) The molecular modeling toolkit: a new approach to molecular simulations. J Comput Chem 21:79–85

    Article  Google Scholar 

  • Langtangen HP (2004) Python scripting for computational science. Springer, Berlin, Heidelberg and New York

    Google Scholar 

  • Peuquet DJ (2002) Representations of space and time. Guilford, New York

    Google Scholar 

  • R Development Core Team (2004) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

    Google Scholar 

  • Rey SJ (2000a) Identifying regional industrial clusters in California, volume II: methods handbook. Technical Report. California Employment Development Department, Sacramento [CA]

    Google Scholar 

  • Rey SJ (2000b) Identifying regional industrial clusters in California, volume III: technical documentation of the state's candidate industry clusters. Technical Report. California Employment Development Department, Sacramento [CA]

    Google Scholar 

  • Rey SJ (2000c) Identifying regional industrial clusters in California, volume IV: the role of industrial clusters in California's economic recent economic expansion. Technical Report. California Employment Development Department, Sacramento [CA]

    Google Scholar 

  • Rey SJ (2000d) A structural economic analysis of the biotechnology cluster in the San Diego Economy. Working Paper, San Diego State University, San Diego [CA]

    Google Scholar 

  • Rey SJ (2000e) A structural economic analysis of the visitors industry cluster in the San Diego Economy. Working Paper, San Diego State University, San Diego [CA]

    Google Scholar 

  • Rey SJ (2001) Spatial empirics for regional economic growth and convergence. Geogr Anal 33(3):195–214

    Google Scholar 

  • Rey SJ (2002) Identifying regional industrial clusters in Imperial County California. Technical Report. California Center for Border and Regional Economic Studies, Diego State University, San Diego [CA]

    Google Scholar 

  • Rey SJ (2004a) Spatial analysis of regional income inequality. In Goodchild M and Janelle D (eds) Spatially integrated social science: examples in best practice. Oxford University Press, Oxford and New York, pp. 280–299

    Google Scholar 

  • Rey SJ (2004b) Spatial dependence in the evolution of regional income distributions. In Getis A, Múr J, Zoeller H (eds) Spatial econometrics and spatial statistics. Palgrave, Hampshire, pp. 194–214

    Google Scholar 

  • Rey SJ, Dev B (2004) σ-convergence in the presence of spatial effects. Paper presented at the Western Regional Science Association Meetings. Maui [HI]

    Google Scholar 

  • Rey SJ, Janikas MV (2005) Regional convergence, inequality, and space. Econ Geogr 5(2):155–176

    Article  Google Scholar 

  • Rey SJ, Mattheis DJ (2000) Identifying regional industrial clusters in California, volume I: conceptual design Technical Report. California Employment Development Department, Sacramento [CA]

    Google Scholar 

  • Rey SJ, Montouri BD (1999) U.S. regional income convergence: a spatial econometric perspective. Reg Stud 33(2):143–156

    Article  Google Scholar 

  • Saenz J, Zubillaga J, Fernandez J (2002) Geophysical data analysis using Python. Comput Geosci 28(4):475–465

    Google Scholar 

  • Schliep A, Hochstättler W, Pattberg T (2001) Rule-based animation of algorithms using animated data structures in gato. Technical report, Zentrum für Angewandte Informatik Köln, Arbeitsgruppe Faigle/Schrader

    Google Scholar 

  • Symanzik J, Kötter T, Schmelzer S, Klinke S, Cook D, Swayne DF (1998) Spatial data analysis in the dynamically linked ArcView/XGobi/Xplore environment. Comput Sc Stat 29:561–569

    Google Scholar 

  • Takatsuka M, Gahegan M (2002) GeoVista Studio: a codeless visual programming environment for geoscientific data analysis and visualization. Comput Geosci 28(10):1131–1144

    Article  Google Scholar 

  • Theil H (1996) Studies in global econometrics. Kluwer, Dordrecht

    Google Scholar 

  • Wise S, Haining R, Ma J (2001) Providing spatial statistical data analysis functionality for the GIS user: the SAGE project. Int J of Geogr Inform Sci 15(3):239–254

    Article  Google Scholar 

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Correspondence to Sergio J. Rey .

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Rey, S.J., Janikas, M.V. (2010). STARS: Space-Time Analysis of Regional Systems. In: Fischer, M., Getis, A. (eds) Handbook of Applied Spatial Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03647-7_6

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  • DOI: https://doi.org/10.1007/978-3-642-03647-7_6

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