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    Geographically weighted principal components analysis


    Harris, Paul and Brunsdon, Chris and Charlton, Martin (2011) Geographically weighted principal components analysis. International Journal of Geographical Information Science, 25 (10). pp. 1717-1736. ISSN 1365-8816

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    Abstract

    Principal components analysis (PCA) is a widely used technique in the social and physical sciences. However in spatial applications, standard PCA is frequently applied without any adaptation that accounts for important spatial effects. Such a naive applica- tion can be problematic as such effects often provide a more complete understanding of a given process. In this respect, standard PCA can be (a) replaced with a geographically weighted PCA (GWPCA), when we want to account for a certain spatial heterogeneity; (b) adapted to account for spatial autocorrelation in the spatial process; or (c) adapted with a specification that represents a mixture of both (a) and (b). In this article, we focus on implementation issues concerning the calibration, testing, interpretation and visual- isation of the location-specific principal components from GWPCA. Here we initially consider the basics of (global) principal components, then consider the development of a locally weighted PCA (for the exploration of local subsets in attribute-space) and finally GWPCA. As an illustration of the use of GWPCA (with respect to the imple- mentation issues we investigate), we apply this technique to a study of social structure in Greater Dublin, Ireland.

    Item Type: Article
    Keywords: PCA; GWPCA; bandwidth selection; visualisation; nonstationarity; GWR;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 5759
    Identification Number: https://doi.org/10.1080/13658816.2011.554838
    Depositing User: Martin Charlton
    Date Deposited: 03 Feb 2015 10:39
    Journal or Publication Title: International Journal of Geographical Information Science
    Publisher: Taylor & Francis
    Refereed: Yes
    URI:

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