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Multimedia Tools and Applications

, Volume 78, Issue 22, pp 31267–31302 | Cite as

Natural disasters detection in social media and satellite imagery: a survey

  • Naina Said
  • Kashif AhmadEmail author
  • Michael Riegler
  • Konstantin Pogorelov
  • Laiq Hassan
  • Nasir Ahmad
  • Nicola Conci
Article

Abstract

The analysis of natural disaster-related multimedia content got great attention in recent years. Being one of the most important sources of information, social media have been crawled over the years to collect and analyze disaster-related multimedia content. Satellite imagery has also been widely explored for disasters analysis. In this paper, we survey the existing literature on disaster detection and analysis of the retrieved information from social media and satellites. Literature on disaster detection and analysis of related multimedia content on the basis of the nature of the content can be categorized into three groups, namely (i) disaster detection in text; (ii) analysis of disaster-related visual content from social media; and (iii) disaster detection in satellite imagery. We extensively review different approaches proposed in these three domains. Furthermore, we also review benchmarking datasets available for the evaluation of disaster detection frameworks. Moreover, we provide a detailed discussion on the insights obtained from the literature review, and identify future trends and challenges, which will provide an important starting point for the researchers in the field.

Keywords

Information retrieval Natural disasters Satellite Social media Deep learning CNN 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Naina Said
    • 1
  • Kashif Ahmad
    • 2
    Email author
  • Michael Riegler
    • 3
  • Konstantin Pogorelov
    • 4
  • Laiq Hassan
    • 1
  • Nasir Ahmad
    • 1
  • Nicola Conci
    • 5
  1. 1.DCSEUniversity of Engineering and TechnologyPeshawarPakistan
  2. 2.Information and Computing Technologies (ICT) Division, College of Science and Engineering (CSE)Hamad Bin Khalifa UniversityDohaQatar
  3. 3.Simula MetSimulaNorway
  4. 4.Simula Research LaboratorySimulaNorway
  5. 5.DISIUniversity of TrentoTrentoItaly

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