Discovery of Spatial Relationships in Spatial Data

  • Yee LeungEmail author
Part of the Advances in Spatial Science book series (ADVSPATIAL)


Study of relationships in space has been the core of geographical research. In the simplest case, we might be interested in their characterization by some simple indicators. Sometimes we might be interested in knowing how things co-vary in space. From the perspective of data mining, it is the discovery of spatial associations in data. Often time, we are interested in relationships in which the variation of one phenomenon can be explained by the variations of the other phenomena. In terms of data mining, we are looking for some kinds of causal relationships that might be expressed in functional forms. Statistics in general and spatial statistics in particular have been commonly employed in such studies (Cliff and Ord 1972; Anselin 1988; Cressie 1993).


Spatial Autocorrelation Null Distribution Spatial Association Geographically Weighted Regression Regional Industrialization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Dept. of Geography & Resource Management ShatinThe Chinese University of Hong KongNew TerritoriesHong Kong SAR

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