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Are the Poor Digitally Left Behind? Indications of Urban Divides Based on Remote Sensing and Twitter Data

Taubenböck, Hannes and Staab, Jeroen and Zhu, Xiao Xiang and Geiß, Christian and Dech, Stefan and Wurm, Michael (2018) Are the Poor Digitally Left Behind? Indications of Urban Divides Based on Remote Sensing and Twitter Data. ISPRS International Journal of Geo-Information, 7 (304), pp. 1-18. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/ijgi7080304 ISSN 2220-9964

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Official URL: http://www.mdpi.com/2220-9964/7/8/304


Every city is—quoting Plato—divided into two, one city of the poor, the other of the rich. In this study we test whether the economic urban divide is reflected in the digital sphere of cities. Because, especially in dynamically growing cities, ready-to-use comprehensive data sets on the urban poor, as well as on the digital divide, are not existent, we use proxies: we spatially delimit the urban poor using settlement characteristics derived from remote sensing data. The digital divide is targeted by geolocated Twitter data. Based on a sample of eight cities across the globe, we spatially test whether areas of the urban poor are more likely to be digital cold spots. Over the course of time, we analyze whether temporal signatures in poor urban areas differ from formal environments. We find that the economic divide influences digital participation in public life. Less residents of morphological slums are found to be digitally oriented (“are digitally left behind”) as compared to residents of formal settlements. However, among the few twitter users in morphological slums, we find their temporal behavior similar to the twitter users in formal settlements. In general, we conclude, this study exemplifies that the combination of both heterogeneous data sets allows for extending the capabilities of individual disciplines for research towards urban poverty.

Item URL in elib:https://elib.dlr.de/121217/
Document Type:Article
Title:Are the Poor Digitally Left Behind? Indications of Urban Divides Based on Remote Sensing and Twitter Data
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Taubenböck, Hanneshannes.taubenboeck (at) dlr.dehttps://orcid.org/0000-0003-4360-9126
Staab, Jeroenjeroen.staab (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Geiß, ChristianChristian.Geiss (at) dlr.deUNSPECIFIED
Dech, Stefanstefan.dech (at) dlr.deUNSPECIFIED
Wurm, Michaelmichael.wurm (at) dlr.dehttps://orcid.org/0000-0001-5967-1894
Date:31 July 2018
Journal or Publication Title:ISPRS International Journal of Geo-Information
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3390/ijgi7080304
Page Range:pp. 1-18
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:MDPI
Keywords:urban society; morphological slum; digital divide; social media; Twitter; remote sensing; geoinformation system; human geography
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, R - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Geo Risks and Civil Security
Remote Sensing Technology Institute > EO Data Science
Deposited By: Taubenböck, Dr. Hannes
Deposited On:31 Jul 2018 11:06
Last Modified:14 Dec 2019 04:22

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