Search from over 60,000 research works

Advanced Search

EURMARS: use of satellite imagery as an asset for maritime environment rapid mapping and objects detection in large areas

[thumbnail of Open Access]
Preview
digilience_2024_EURMARS.pdf - Published Version (754kB) | Preview
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Kourounioti, O., Kontopoulos, C., Wei, H. orcid id iconORCID: https://orcid.org/0000-0002-9664-5748, Urbas, A., Rodic, T., Frohlich, H., Ferryman, J. and Charalampopoulou, V. (2024) EURMARS: use of satellite imagery as an asset for maritime environment rapid mapping and objects detection in large areas. Information & Security, 55 (2). pp. 149-164. ISSN 1314-2119 doi: 10.11610/isij.5524

Abstract/Summary

The increasing complexity of maritime risks and threats requires accurate and timely identification for environmental and human safety. Satellite observa-tions enable comprehensive surveillance of large maritime areas, which is es-sential for detecting and responding to environmental changes and potential threats. The Horizon Europe project EURMARS aims to develop and validate a multi-purpose observation platform to enhance detection capabilities for various risks and threats. This paper introduces a novel Earth Observation (EO) algorithm based on Object-Based Image Analysis (OBIA), employing a You Only Look Once (YOLO) -v9 model to process data from open-access sat-ellites (Sentinel-1, Sentinel-2, Landsat 8, 9) and video from the microsatellite NEMO-HD. Automatic Identification System (AIS) data are used to ensure comprehensive monitoring and validate the method’s results. Satellite im-agery with AIS data integration is a critical element of the vessel tracking methodology, significantly improving the accuracy and reliability of maritime surveillance. Real-life demonstrations have confirmed the method’s effective-ness in enhancing maritime security and facilitating early detection and re-sponse to threats.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/119983
Item Type Article
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
Publisher Procon Ltd.
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar