Analysing user contribution patterns of drone pictures to the dronestagram photo sharing portal

Drones, also known as unmanned aerial vehicles, are nowadays frequently used to supplement traditional airborne data collection methods such as aerial photography and satellite imagery. Dronestagram, launched in July 2013, is one of the first Web 2.0 projects that share georeferenced drone pictures, providing a valuable source of VGI image data. This paper analyses spatial patterns of contributions to dronestagram world-wide and for two selected regions. Results show that the number of uploaded pictures is associated with the socioeconomic development of a country and the presence of geographical features, and that pictures are clustered in sub-regions.

[1]  Dennis Zielstra,et al.  Positional accuracy analysis of Flickr and Panoramio images for selected world regions , 2013 .

[2]  Ross Purves,et al.  Exploring place through user-generated content: Using Flickr tags to describe city cores , 2010, J. Spatial Inf. Sci..

[3]  J. Hudson.  A DIAMOND ANNIVERSARY , 1979 .

[4]  Tat-Seng Chua,et al.  Mining Travel Patterns from Geotagged Photos , 2012, TIST.

[5]  Christoph Schlieder,et al.  Photographing a City: An Analysis of Place Concepts Based on Spatial Choices , 2009, Spatial Cogn. Comput..

[6]  Pemetaan Jumlah Balita,et al.  Spatial Scan Statistic , 2014, Encyclopedia of Social Network Analysis and Mining.

[7]  Henry A. Kautz,et al.  Towards Understanding Global Spread of Disease from Everyday Interpersonal Interactions , 2013, IJCAI.

[8]  Dennis Zielstra,et al.  Using Free and Proprietary Data to Compare Shortest-Path Lengths for Effective Pedestrian Routing in Street Networks , 2012 .

[9]  Yuji Murayama,et al.  Prioritizing Areas for Rehabilitation by Monitoring Change in Barangay-Based Vegetation Cover , 2012, ISPRS Int. J. Geo Inf..

[10]  Hartwig H. Hochmair,et al.  Spatial Association of Geotagged Photos with Scenic Locations , 2010 .

[11]  Vincent G. Ambrosia,et al.  Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of Use , 2012, Remote. Sens..

[12]  Hannes Isaak Reuter,et al.  An evaluation of void‐filling interpolation methods for SRTM data , 2007, Int. J. Geogr. Inf. Sci..

[13]  Cecilia Mascolo,et al.  A Tale of Many Cities: Universal Patterns in Human Urban Mobility , 2011, PloS one.

[14]  F. López-Granados,et al.  Configuration and Specifications of an Unmanned Aerial Vehicle (UAV) for Early Site Specific Weed Management , 2013, PloS one.

[15]  Michael F. Goodchild,et al.  Citizens as Voluntary Sensors: Spatial Data Infrastructure in the World of Web 2.0 , 2007, Int. J. Spatial Data Infrastructures Res..

[16]  Josep Blat,et al.  Digital Footprinting: Uncovering Tourists with User-Generated Content , 2008, IEEE Pervasive Computing.

[17]  Alfred DeMaris,et al.  Regression With Social Data: Modeling Continuous and Limited Response Variables , 2004 .

[18]  M. Goodchild,et al.  Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr , 2013 .

[19]  Brian Wildsmith,et al.  What a Tale , 1987 .

[20]  Christian Heipke,et al.  Crowdsourcing geospatial data , 2010 .

[21]  Cristina V. Lopes,et al.  User contribution and trust in Wikipedia , 2009, 2009 5th International Conference on Collaborative Computing: Networking, Applications and Worksharing.

[22]  Frederick Mortimer Atkinson.  The Associated Press , 1913 .

[23]  Bernd Resch,et al.  From Social Sensor Data to Collective Human Behaviour Patterns - Analysing and Visualising Spatio-Temporal Dynamics in Urban Environments , 2012 .

[24]  Dennis Zielstra,et al.  Comparative Study of Pedestrian Accessibility to Transit Stations Using Free and Proprietary Network Data , 2011 .

[25]  Fabio Remondino,et al.  UAV PHOTOGRAMMETRY FOR MAPPING AND 3D MODELING - CURRENT STATUS AND FUTURE PERSPECTIVES - , 2012 .

[26]  Pascal Neis,et al.  Analyzing the Contributor Activity of a Volunteered Geographic Information Project - The Case of OpenStreetMap , 2012, ISPRS Int. J. Geo Inf..

[27]  A. F. Adams,et al.  The Survey , 2021, Dyslexia in Higher Education.

[28]  Jeremy Morley,et al.  Web 2.0 geotagged photos: Assessing the spatial dimension of the phenomenon , 2010 .

[29]  M. Goodchild,et al.  Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice , 2012 .

[30]  Slava Kisilevich,et al.  Analysis of community-contributed space- and time-referenced data (example of flickr and panoramio photos) , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[31]  Albert Rango,et al.  Texture and Scale in Object-Based Analysis of Subdecimeter Resolution Unmanned Aerial Vehicle (UAV) Imagery , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Darren Gergle,et al.  On the "localness" of user-generated content , 2010, CSCW '10.

[33]  Carol J. Friedland,et al.  A SURVEY OF UNMANNED AERIAL VEHICLE ( UAV ) USAGE FOR IMAGERY , 2011 .

[34]  Yi Lin,et al.  Mini-UAV-Borne LIDAR for Fine-Scale Mapping , 2011, IEEE Geoscience and Remote Sensing Letters.

[35]  Ling Chen,et al.  Event detection from flickr data through wavelet-based spatial analysis , 2009, CIKM.