Obtaining population estimates in non-census reporting zones: An evaluation of the 3-class dasymetric method

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    Abstract

    Interpolating population data between incompatible spatial zones is an important task in many GIS applications. This paper investigates whether regional regression models between population and land cover outperform a global approach, and whether the 3-class dasymetric method improves upon the binary dasymetric approach. In the experiments conducted, regional regressions resulted in better areal interpolation, but also highlighted spatial non-stationarity in the relationship between population and land cover. The benefits of a 3-class dasymetric model over a binary model were inconclusive. However, it is suggested that greater flexibility in model calibration to more fully incorporate spatial non-stationarity could improve 3-class dasymetric performance. Accurate urban residential density mapping is also important since the 3-class dasymetric method seems less robust than the binary approach to land cover classification error.
    Original languageEnglish
    Article number30
    Pages (from-to)161-180
    JournalComputers Environment and Urban Systems
    Volume30
    Issue number2
    DOIs
    Publication statusPublished - 1 Mar 2006

    Keywords

    • Interpolation
    • Population
    • Dasymetric
    • Regression

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