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Spatial Autocorrelation and Association Measures

Spatial Autocorrelation and Association Measures
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Author(s): J. Negreiros (Universidade Lusófona, Portugal), M. Painho (Instituto Superior de Estatística e Gestão de Informação - Universidade Nova de Lisboa, Portugal), I. Lopes (Universidade Lusófona, Portugal)and A.C. Costa (Instituto Superior de Estatística e Gestão de Informação - Universidade Nova de Lisboa, Portugal)
Copyright: 2008
Pages: 7
Source title: Encyclopedia of Networked and Virtual Organizations
Source Author(s)/Editor(s): Goran D. Putnik (University of Minho, Portugal)and Maria Manuela Cruz-Cunha (Polytechnic Institute of Cavado and Ave, Portugal)
DOI: 10.4018/978-1-59904-885-7.ch199

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Abstract

Several classical statements relating to the definition of GIS can be found in specialized literature such as the GIS International Journal, expressing the idea that spatial analysis can somehow be useful. GIS is successful not only because it integrates data, but it also enables us to share data in different departments or segments of our organizations. I like this notion of putting the world’s pieces back together again (ArcNews, 2000). “GIS is simultaneously the telescope, the microscope, the computer and the Xerox machine of regional analysis and the synthesis of spatial data” (Abler, 1988). “GIS is a system of hardware, software and liveware implemented with the aim of storing, processing, visualizing and analyzing data of a spatial nature. Other definitions are also possible” (Painho, 1999). “GIS is a tool for revealing what is otherwise invisible in geographical information” (Longley, Goodchild, Maguire, & Rhind, 2001). Certainly, GIS is not a graphic database.

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