Mapping Information of Fire Events, from VGI Source (Twitter), for Effective Disaster Management (in Greece); The Fire of North-East Attica, August 2017, (Greece) Case Study

  • Stathis G. ArapostathisEmail author
  • Marianthi Karantzia
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)


This article introduced a novel method for mapping information related to fire events, from a source of Volunteered Geographic Information (VGI) and from Twitter, in particular. As a case study, the fire of North East Attica (August 2017, Greece), was used. The fire event resulted in the burn of 15,000 decares of woodland. Moreover, state of emergency was declared in the region and thousands of citizens who were in the middle of summer vacations were incited to leave from the area of Kalamos, even if they were located at the coastal part. Regarding the methodology, as a first step, all the tweets that were published within 168 h of the fire event and contain relevant information, were collected. Next, they were classified into certain groups the most important of which are: (i) to information regarding fire event tracking, (ii) to the tracking of the consequences and (iii) to the simple identification of the fire event. The geo-referencing of the classified information is performed by using a script written in R. The final output consisted of thematic maps that visualize the classified information.


Disaster management Fire events Twitter Tweets Volunteered geographic information VGI 


  1. 1.
    Arapostathis, S.G., Parcharidis, I., Stefanakis, E., Drakatos, G., Kalogeras, I.: A method for creating seismic intensity maps from twitter data. J. Civ. Eng. Archit. (2016). Scholar
  2. 2.
    Arapostathis, S.G.: Automated methods for effective geo-referencing of tweets related to disaster management. In: Proceedings of GeoMapplica International Conference 2k18, 23–29 June, Syros, Mykonos (2018)Google Scholar
  3. 3.
    Arapostathis, S.G., Lekkas, E., Kalabokidis, K., Drakatos, G., Xanthopoulos, G., Spyroy, N., Kalogeras, I.: Developing seismic intensity maps from twitter data; The case study of Lesvos Greece 2017 earthquake: assessments, improvements and enrichments on the methodology. In: Proceedings of the GI4DM 2018 Congress, Istanbul, Mar 2018Google Scholar
  4. 4.
    Connors, J.P., Lei, S., Kelly, M.: Citizen science in the age of neogeography: utilizing volunteered geographic information for environmental monitoring. Ann. Assoc. Am. Geogr. (2011). Scholar
  5. 5.
    Dashti, S., Palen, L., Heris, M.P., Anderson, K.M., Anderson, S., Anderson, T.J.: Supporting disaster reconnaissance with social media data: a design-oriented case study of the 2013 Colorado floods. In: Proceedings of the 11th International ISCRAM Conference, University Park, Pennsylvania, USA (2013)Google Scholar
  6. 6.
    Goodchild M. F.: Citizens as sensors: The world of volunteered geography. GeoJournal 69 (4):211-221 (2007)Google Scholar
  7. 7.
    McDougall, K.: Using volunteered information to map the Queensland floods. In: Proceedings of the Surveying & Spatial Sciences Biennial Conference 2011. 21–25 Nov 2011, Wellington, New Zealand (2011)Google Scholar
  8. 8.
    Yin, J., Lampert, A., Cameron, M., Robinson, B., Power, R.: Using social media to enhance emergency situation awareness. IEEE Comput. Soc. 1541–1672 (2012)Google Scholar
  9. 9.
    Zhong, X., Duckham, M., Chong, D., Tolhurst, K.: Real time estimation of wildfire parameters from curated crowdsourcing. Sci. Rep. (2016). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of GeographyHarokopio UniversityAthensGreece
  2. 2.National Technical University of AthensAthensGreece

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