Conference paper Open Access

Multimodal Data Fusion Of Social Media And Satellite Images For Emergency Response And Decision-making

Ilias Gialampoukidis; Stelios Andreadis; Stefanos Vrochidis; Ioannis Kompatsiaris

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Ilias Gialampoukidis</dc:creator>
  <dc:creator>Stelios Andreadis</dc:creator>
  <dc:creator>Stefanos Vrochidis</dc:creator>
  <dc:creator>Ioannis Kompatsiaris</dc:creator>
  <dc:description>Artificial Intelligence (AI) is already part of our lives and is extensively entering the space sector to offer value-added Earth Observation (EO) products and services. The Copernicus programme provides data on a free, full and open basis, while the recently launched Data and Information Access Service (DIAS) providers index, store and exchange tremendous amounts of data and cloud infrastructure computational resources. Copernicus data and other georeferenced data sources are often highly heterogeneous, distributed and semantically fragmented. One example is the massively generated social media data from citizen observations, including visual, textual and spatiotemporal information. Social media information offers reliable, timely and very prescriptive information about a crisis event. In this work we present the multimodal fusion aspects for combining satellite images and social media for emergency response, such as flood monitoring and extreme weather conditions in polar regions. </dc:description>
  <dc:relation>info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Research and Innovation action/101004152/</dc:relation>
  <dc:subject>Multimodal data fusion</dc:subject>
  <dc:subject>Social Media</dc:subject>
  <dc:subject>Emergency response</dc:subject>
  <dc:subject>Deep Learning</dc:subject>
  <dc:title>Multimodal Data Fusion Of Social Media And Satellite Images For Emergency Response And Decision-making</dc:title>
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