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Earthquakes: From Twitter Detection to EO Data Processing

Authors :
Stelios Andreadis
Ilias Gialampoukidis
Andrea Manconi
David Cordeiro
Vasco Conde
Manuela Sagona
Fabrice Brito
Nick Pantelidis
Thanassis Mavropoulos
Nuno Grosso
Stefanos Vrochidis
Ioannis Kompatsiaris
Source :
IEEE Geoscience and Remote Sensing Letters, 19
Publication Year :
2022
Publisher :
ETH Zurich, 2022.

Abstract

The increase of social media use in recent years has shown potential also for the identification of specific trends in the data that could be used to locate earthquakes. In this work, we implemented a pipeline that uses Twitter data to identify locations of earthquakes and use the information to trigger EO data analysis. We tested the pipeline for almost a year over Japan, an area where earthquake events are frequent, as well as the use of social media in the population. Here, we show the results and discuss the potential development of such procedures. In the future, considering the rapid development and the increase of satellite constellations aimed at global coverage with short revisit times, algorithms of this kind could be used to prioritize satellite acquisitions for the detection of the areas most affected by earthquake damages.<br />IEEE Geoscience and Remote Sensing Letters, 19<br />ISSN:1545-598X<br />ISSN:1558-0571

Details

Language :
English
ISSN :
1545598X and 15580571
Database :
OpenAIRE
Journal :
IEEE Geoscience and Remote Sensing Letters, 19
Accession number :
edsair.doi.dedup.....7a133d36967c683de72d91ced687f4e7
Full Text :
https://doi.org/10.3929/ethz-b-000538275