A Multimodal Approach for Event Detection: Study of UK Lockdowns in the Year 2020.
Type
conference paper
Date Issued
2022-07-19
Author(s)
Research Team
AIML Lab
Abstract
Satellites allow spatially precise monitoring of the Earth, but provide only limited information on events of societal impact. Subjective societal impact, however, may be quantified at a high frequency by monitoring social media data. In this work, we propose a multi-modal data fusion framework to accurately identify periods of COVID-19-related lockdown in the United Kingdom using satellite observations (NO2 measurements from Sentinel-5P) and social media (textual content of tweets from Twitter) data. We show that the data fusion of the two modalities improves the event detection accuracy on a national level and for large cities such as London.
Language
English
HSG Classification
contribution to scientific community
Publisher
IEEE Geoscience and Remote Sensing Society
Pages
4
Event Title
IEEE Geoscience and Remote Sensing Symposium 2022
Event Location
Kuala Lumpur, Malaysia
Event Date
17-22 July 2022
Subject(s)
Division(s)
Contact Email Address
joelle.hanna@unisg.ch
Eprints ID
267271
File(s)![Thumbnail Image]()
Name
IGARSS_2022.pdf
Size
1.43 MB
Format
Adobe PDF
Checksum (MD5)
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