New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products

In the production of gridded population maps, remotely sensed, human settlement datasets rank among the most important geographical factors to estimate population densities and distributions at regional and global scales. Within this context, the German Aerospace Centre (DLR) has developed a new sui...

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Bibliographic Details
Published inSustainability Vol. 11; no. 21; p. 6056
Main Authors Palacios-Lopez, Daniela, Bachofer, Felix, Esch, Thomas, Heldens, Wieke, Hirner, Andreas, Marconcini, Mattia, Sorichetta, Alessandro, Zeidler, Julian, Kuenzer, Claudia, Dech, Stefan, Tatem, Andrew J., Reinartz, Peter
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2019
Subjects
Accuracy
Census of Population
Datasets
Land settlement
Mapping
Parameterization
Population density
Population distribution
Remote sensing
Rural areas
Spatial discrimination
Spatial resolution
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Summary:In the production of gridded population maps, remotely sensed, human settlement datasets rank among the most important geographical factors to estimate population densities and distributions at regional and global scales. Within this context, the German Aerospace Centre (DLR) has developed a new suite of global layers, which accurately describe the built-up environment and its characteristics at high spatial resolution: (i) the World Settlement Footprint 2015 layer (WSF-2015), a binary settlement mask; and (ii) the experimental World Settlement Footprint Density 2015 layer (WSF-2015-Density), representing the percentage of impervious surface. This research systematically compares the effectiveness of both layers for producing population distribution maps through a dasymetric mapping approach in nine low-, middle-, and highly urbanised countries. Results indicate that the WSF-2015-Density layer can produce population distribution maps with higher qualitative and quantitative accuracies in comparison to the already established binary approach, especially in those countries where a good percentage of building structures have been identified within the rural areas. Moreover, our results suggest that population distribution accuracies could substantially improve through the dynamic preselection of the input layers and the correct parameterisation of the Settlement Size Complexity (SSC) index.
ISSN:2071-1050
2071-1050
DOI:10.3390/su11216056