Comparison of spatiotemporal contribution patterns among three crowd-sourcing drone platforms. (2nd October 2021)

• Record Type: Journal Article
• Authors: Mandourah, Ammar; Hochmair, Hartwig
• Is Part Of: Journal of location based services. Volume 15:Number 4(2021)
• Page Start: 280
• Page End: 304
• Publication Date: 2021-10-02
• Subjects: User-generated content -- drone -- Dronestagram -- Travelwithdrone -- Flickr -- social media -- point pattern; Mobile computing -- Periodicals; Multimedia systems -- Periodicals; Local area networks (Computer networks) -- Periodicals; Wireless communication systems -- Periodicals; 004.68
• DOI: 10.1080/17489725.2021.1889057
• Languages: English
• ISSNs: 1748-9725

Abstract

ABSTRACT: Since the introduction of drones to the mass market for private users, drone pilots have started to share geo-tagged aerial photos and videos on a variety of drone platforms. This study compares the spatio-temporal contribution patterns of georeferenced drone-based images and videos between three crowd-sourcing platforms, namely Dronestagram, Travelwithdrone, and Flickr. The comparison addresses aspects of spatial accuracy, geographic coverage, contribution inequality, power-law approximations of different contribution characteristics, and negative binomial multilevel regression models that identify man-made and natural features, socio-economic factors, and land use categories that are associated with image and video contribution numbers. This study provides new insight into the abundance of drone-based image and video contributions around the globe, helps to determine which drone platform is best suited to find drone media for a specific location, and discusses a few potential applications that could benefit from crowd-sourced drone imagery and videos.