Recent Advances in Spatial Data Analysis

    Publication: Working/Discussion PaperWU Working Paper


    This article views spatial analysis as a research paradigm that provides a unique set of
    specialised techniques and models for a wide range of research questions in which the prime
    variables of interest vary significantly over space. The heart of spatial analysis is concerned
    with the analysis and modeling of spatial data. Spatial point patterns and area referenced data
    represent the most appropriate perspectives for applications in the social sciences. The
    researcher analysing and modeling spatial data tends to be confronted with a series of
    problems such as the data quality problem, the ecological fallacy problem, the modifiable
    areal unit problem, boundary and frame effects, and the spatial dependence problem. The
    problem of spatial dependence is at the core of modern spatial analysis and requires the use of
    specialised techniques and models in the data analysis. The discussion focuses on exploratory
    techniques and model-driven [confirmatory] modes of analysing spatial point patterns and
    area data. In closing, prospects are given towards a new style of data-driven spatial analysis
    characterized by computational intelligence techniques such as evolutionary computation and
    neural network modeling to meet the challenges of huge quantities of spatial data
    characteristic in remote sensing, geodemographics and marketing. (author's abstract)
    Original languageEnglish
    Place of PublicationVienna
    PublisherWU Vienna University of Economics and Business
    Publication statusPublished - 2000

    Publication series

    NameDiscussion Papers of the Institute for Economic Geography and GIScience

    WU Working Paper Series

    • Discussion Papers of the Institute for Economic Geography and GIScience

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