Multi-layer multi-class dasymetric mapping to estimate population distribution

The Science of the Total Environment
Ming-Dawa SuChun-Hung Lin

Abstract

The spatial patterns of population distribution are very important information for most regional planning and management decisions. But the socioeconomic data are usually published in areal aggregated format due to privacy concerns. Although choropleth maps are used extensively to display spatial distributions of these areal aggregated data, patterns may be distorted due to assumptions of homogeneous distributions and the modifiable areal unit problem. Most human activity, including population distribution, is spatially heterogeneous due to variations in topography and regional development. A multi-layer multi-class dasymetric (MLMCD) framework was proposed in this study to better redistribute the regionally aggregated population statistics into smaller areal units and reveal more realistic spatial population distribution pattern. The Taipei metropolitan area in Taiwan was used as a case study area to demonstrate the disaggregation ability of the proposed framework and the improvements to the traditional binary or multi-class dasymetric method. Assorted data, including remote sensing images, land use zoning, topography, transportation and accessibility to facilities were introduced in different layers to improve the redistribut...Continue Reading

References

Apr 1, 1989·Environment & Planning a·I Bracken, D Martin

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Citations

Feb 13, 2014·Ageing and Society·Elisabeth Schröder-Butterfill, Tengku Syawila Fithry
Jan 1, 2020·GIScience & Remote Sensing·Hamidreza Zoraghein, Stefan Leyk
Jan 14, 2020·The Science of the Total Environment·R MeloT W J van Asch

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