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

Palacios Lopez, Daniela and Bachofer, Felix and Esch, Thomas and Heldens, Wieke and Hirner, Andreas and Marconcini, Mattia and Sorichetta, Alessandro and Zeidler, Julian and Kuenzer, Claudia and Dech, Stefan and Tatem, Andrew and Reinartz, Peter (2019) New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products. Sustainability, 11 (21), pp. 1-24. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/su11216056 ISSN 2071-1050

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Official URL: https://www.mdpi.com/2071-1050/11/21/6056/pdf


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.

Item URL in elib:https://elib.dlr.de/130168/
Document Type:Article
Title:New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Palacios Lopez, DanielaDaniela.PalaciosLopez (at) dlr.dehttps://orcid.org/0000-0001-6302-2491
Bachofer, FelixFelix.Bachofer (at) dlr.dehttps://orcid.org/0000-0001-6181-0187
Esch, ThomasThomas.Esch (at) dlr.deUNSPECIFIED
Heldens, WiekeWieke.Heldens (at) dlr.dehttps://orcid.org/0000-0001-6209-5664
Hirner, AndreasAndreas.Hirner (at) dlr.deUNSPECIFIED
Marconcini, MattiaMattia.Marconcini (at) dlr.dehttps://orcid.org/0000-0002-5042-5176
Sorichetta, AlessandroUniversity of SouthhamptonUNSPECIFIED
Zeidler, JulianJulian.Zeidler (at) dlr.dehttps://orcid.org/0000-0001-9444-2296
Kuenzer, Claudiaclaudia.kuenzer (at) dlr.deUNSPECIFIED
Dech, StefanStefan.Dech (at) dlr.deUNSPECIFIED
Tatem, AndrewUniversity of SouthhamptonUNSPECIFIED
Reinartz, Peterpeter.reinartz (at) dlr.dehttps://orcid.org/0000-0002-8122-1475
Date:31 October 2019
Journal or Publication Title:Sustainability
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3390/su11216056
Page Range:pp. 1-24
Rosen, Marc ASustainability Editorial Office
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:MPDI
Keywords:global population distribution mapping; World Settlement Footprint; percent impervious surface; dasymetric mapping; Settlement Size Complexity Index
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
German Remote Sensing Data Center > Leitungsbereich DFD
Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Palacios Lopez, Daniela
Deposited On:12 Nov 2019 10:01
Last Modified:20 Dec 2019 10:49

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