Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/21975
Title: | Detecting Migrant Vessels in the Cyprus Region using Sentinel-1 SAR data | Authors: | Melillos, George Themistocleous, Kyriacos Danezis, Chris Michaelides, Silas Hadjimitsis, Diofantos G. Jacobsen, Sven Tings, Björn |
Major Field of Science: | Engineering and Technology | Field Category: | Civil Engineering | Keywords: | Remote Sensing;Sentinel-1 SAR;OSINT;Migrants;Maritime Surveillance;Cyprus coasts | Issue Date: | 20-Sep-2020 | Source: | Proceedings Volume 11542, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV | Volume: | 11542 | Issue: | 115420N | Project: | ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment | Journal: | Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV | Conference: | SPIE Security + Defence | Abstract: | Remote sensing is considered as an increasingly important technology for maritime surveillance. The process of maritime surveillance for safety is critical for every country. The need for information on migrant movements by sea using different sizes and types of vessels is of paramount significance. Such information is essential for the search and rescue (SaR) operations of unauthorised migrants. The aim of this paper is to show how to detect migrant vessels in the Cyprus Region using freely available Sentinel-1 SAR data. The comparison was made using open source available migrant data and Sentinel-1 SAR acquisitions. Sentinel-1 SAR images were used to investigate three Areas of Interest (AoI). The main AoI is located at the Northwest coasts, whilst the second area includes the Southeast coasts of Cyprus. The results indicate that the Sentinel-1 SAR data can provide decision-makers with effective results and spatial information on migration routes. | URI: | https://hdl.handle.net/20.500.14279/21975 | DOI: | 10.1117/12.2573744 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Type: | Conference Papers | Affiliation : | Cyprus University of Technology ERATOSTHENES Centre of Excellence DLR - German Aerospace Center |
Publication Type: | Peer Reviewed |
Appears in Collections: | EXCELSIOR H2020 Teaming Project Publications |
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File | Description | Size | Format | |
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20200920_EXCELSIOR_WP10_DETECTINGMIGRANTVESSELSINCYPRUSUSINGSENTINEL1_V1_PU.pdf | 638.35 kB | Adobe PDF | View/Open |
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