The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Sep 2018)

CONSISTENCY AND RELEVANCE OF VGI AVAILABLE FROM SOCIAL NETWORKS FOR EMERGENCY MITIGATION AND MUNICIPAL MANAGEMENT

  • C. C. Fonte,
  • C. C. Fonte,
  • J. Patriarca,
  • J. Estima,
  • J. Estima,
  • J.-P. de Almeida,
  • J.-P. de Almeida,
  • A. Cardoso,
  • A. Cardoso

DOI
https://doi.org/10.5194/isprs-archives-XLII-4-217-2018
Journal volume & issue
Vol. XLII-4
pp. 217 – 224

Abstract

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Volunteered geographical information (VGI) is an increasing source of data for many applications. In order to explore some of these sources of data, an algorithm was conceived and implemented in the ExploringVGI platform enabling the collection of georeferenced data from collaborative projects that provide an Application Programming Interface (API). This paper presents a preliminary study to evaluate the consistency and relevance of VGI extracted from Flickr platform for emergency mitigation and municipal management. The study carried out was based on data extraction and analysis with keywords related to emergency events (“Accident”, “Flood” and “Fire apartment”), and municipal management (“Graffiti” and “Homeless”) in four European cities (Frankfurt, Lisbon, London, and Rome). The proposed approach sets up a region of interest on a map, selects one or more keywords for the search, and carries out a search using the Flickr API. Data detected and extracted were then loaded into a database and further analysed to verify whether they were consistently obtained through consecutive searches at different locations. A statistical analysis performed on data collected for each case provided us with: the total number of data collected for each keyword and location; their relevance in terms of search goal; and the quality of the associate geolocation of the post. Results obtained illustrate the effectiveness of the approach when applied to different scenarios, which contributes to assess the role that VGI available on the Web may have in different events depending on the specific context of a geolocation/keyword(s) combination.