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Crowdsourcing Street View Imagery: A Comparison of Mapillary and OpenStreetCam

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Department of Computational and Data Sciences, George Mason University, Fairfax, VA 22030, USA
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Center for Geoinformatics and Geospatial Intelligence, George Mason University, Fairfax, VA 22030, USA
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Department of Geography and Geoinformation Science, George Mason University Fairfax, VA 22030, USA
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Department of Computer Science, William and Mary, Williamsburg, VA 23187, USA
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(6), 341; https://doi.org/10.3390/ijgi9060341
Received: 8 April 2020 / Revised: 12 May 2020 / Accepted: 24 May 2020 / Published: 26 May 2020
Over the last decade, Volunteered Geographic Information (VGI) has emerged as a viable source of information on cities. During this time, the nature of VGI has been evolving, with new types and sources of data continually being added. In light of this trend, this paper explores one such type of VGI data: Volunteered Street View Imagery (VSVI). Two VSVI sources, Mapillary and OpenStreetCam, were extracted and analyzed to study road coverage and contribution patterns for four US metropolitan areas. Results show that coverage patterns vary across sites, with most contributions occurring along local roads and in populated areas. We also found that a few users contributed most of the data. Moreover, the results suggest that most data are being collected during three distinct times of day (i.e., morning, lunch and late afternoon). The paper concludes with a discussion that while VSVI data is still relatively new, it has the potential to be a rich source of spatial and temporal information for monitoring cities. View Full-Text
Keywords: crowdsourcing; volunteered geographic information; street view imagery; Mapillary; OpenStreetCam crowdsourcing; volunteered geographic information; street view imagery; Mapillary; OpenStreetCam
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Mahabir, R.; Schuchard, R.; Crooks, A.; Croitoru, A.; Stefanidis, A. Crowdsourcing Street View Imagery: A Comparison of Mapillary and OpenStreetCam. ISPRS Int. J. Geo-Inf. 2020, 9, 341.

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