Empirically Derived Probability Maps to Downscale Aggregated Land-Use Data

N. Dendoncker, Patrick Bogaert, M. Rounsevell

    Research output: Contribution in Book/Catalog/Report/Conference proceedingChapter


    Land-use simulation results are often provided at spatial resolutions that are too coarse to establish links with local or regional studies that, for example, deal with the physical or ecological impacts of land-use change. This chapter aims to use novel spatial statistical techniques to derive representations of land-use patterns at a resolution of 250 metres based on aggregate land-use change simulations. The proposed statistical downscaling method combines multinomial autologistic regression and an iterative procedure using Bayes’ theorem. Based on these methods, a set of probability maps of land-use presence is developed at two time steps. The method’s low data requirements (only land-use datasets are used) make it easily replicable, allowing application over a wide geographic area. The potential of the method to downscale land-use change scenarios is shown for a small area in Belgium using the CORINE land-cover dataset.

    Original languageEnglish
    Title of host publicationGeoJournal Library
    PublisherSpringer Science and Business Media B.V.
    Number of pages16
    Publication statusPublished - 2007

    Publication series

    NameGeoJournal Library
    ISSN (Print)0924-5499
    ISSN (Electronic)2215-0072


    • Bayes’ theorem
    • Downscaling
    • multinomial logistic regression
    • suitability maps


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