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Publication . Conference object . 2021

Multimodal Data Fusion of Social Media and Satellite Images for Emergency Response and Decision-Making

Ilias Gialampoukidis; Stelios Andreadis; Stefanos Vrochidis; Ioannis Kompatsiaris;
Open Access
Published: 11 Jul 2021
Publisher: IEEE
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.
Subjects by Vocabulary

Microsoft Academic Graph classification: Visualization Information access Space (commercial competition) Computer science Service (systems architecture) Data science Social media Event (computing) Cloud computing business.industry business Earth observation


Multimodal data fusion, Social Media, Emergency response, Decision-making, Deep Learning

Related Organizations
Funded by
EOPEN: opEn interOperable Platform for unified access and analysis of Earth observatioN data
  • Funder: European Commission (EC)
  • Project Code: 776019
  • Funding stream: H2020 | RIA
Copernicus Artificial Intelligence Services and data fusion with other distributed data sources and processing at the edge to support DIAS and HPC infrastructures
  • Funder: European Commission (EC)
  • Project Code: 101004152
  • Funding stream: H2020 | RIA
Validated by funder
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