Remote Sensing for Maritime Traffic Understanding
The capability of prompt response in the case of critical circumstances occurring within a maritime scenario depends on the awareness level of the competent authorities. From this perspective, a quick and integrated surveillance service represents a tool of utmost importance. This is even more true...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/3/557 |
| _version_ | 1797318290820825088 |
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| author | Marco Reggiannini Emanuele Salerno Clara Bacciu Andrea D’Errico Angelica Lo Duca Andrea Marchetti Massimo Martinelli Costanzo Mercurio Antonino Mistretta Marco Righi Marco Tampucci Claudio Di Paola |
| author_facet | Marco Reggiannini Emanuele Salerno Clara Bacciu Andrea D’Errico Angelica Lo Duca Andrea Marchetti Massimo Martinelli Costanzo Mercurio Antonino Mistretta Marco Righi Marco Tampucci Claudio Di Paola |
| author_sort | Marco Reggiannini |
| collection | DOAJ |
| description | The capability of prompt response in the case of critical circumstances occurring within a maritime scenario depends on the awareness level of the competent authorities. From this perspective, a quick and integrated surveillance service represents a tool of utmost importance. This is even more true when the main purpose is to tackle illegal activities such as smuggling, waste flooding, or malicious vessel trafficking. This work presents an improved version of the OSIRIS system, a previously developed Information and Communication Technology framework devoted to understanding the maritime vessel traffic through the exploitation of optical and radar data captured by satellite imaging sensors. A number of dedicated processing units are cascaded with the objective of (i) detecting the presence of vessel targets in the input imagery, (ii) estimating the vessel types on the basis of their geometric and scatterometric features, (iii) estimating the vessel kinematics, (iv) classifying the navigation behavior of the vessel and predicting its route, and, eventually, (v) integrating the several outcomes within a webGIS interface to easily assess the traffic status inside the considered area. The entire processing pipeline has been tested on satellite imagery captured within the Mediterranean Sea or extracted from public annotated datasets. |
| first_indexed | 2024-03-08T03:50:18Z |
| format | Article |
| id | doaj.art-ed2df81361d9448d8821d0894e78569c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-08T03:50:18Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ed2df81361d9448d8821d0894e78569c2024-02-09T15:21:28ZengMDPI AGRemote Sensing2072-42922024-01-0116355710.3390/rs16030557Remote Sensing for Maritime Traffic UnderstandingMarco Reggiannini0Emanuele Salerno1Clara Bacciu2Andrea D’Errico3Angelica Lo Duca4Andrea Marchetti5Massimo Martinelli6Costanzo Mercurio7Antonino Mistretta8Marco Righi9Marco Tampucci10Claudio Di Paola11Institute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Informatics and Telematics, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Informatics and Telematics, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Informatics and Telematics, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Informatics and Telematics, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, ItalyMapsat S.R.L., 82100 Benevento, ItalySisTer S.R.L., 56021 Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, ItalyInstitute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, ItalyMapsat S.R.L., 82100 Benevento, ItalyThe capability of prompt response in the case of critical circumstances occurring within a maritime scenario depends on the awareness level of the competent authorities. From this perspective, a quick and integrated surveillance service represents a tool of utmost importance. This is even more true when the main purpose is to tackle illegal activities such as smuggling, waste flooding, or malicious vessel trafficking. This work presents an improved version of the OSIRIS system, a previously developed Information and Communication Technology framework devoted to understanding the maritime vessel traffic through the exploitation of optical and radar data captured by satellite imaging sensors. A number of dedicated processing units are cascaded with the objective of (i) detecting the presence of vessel targets in the input imagery, (ii) estimating the vessel types on the basis of their geometric and scatterometric features, (iii) estimating the vessel kinematics, (iv) classifying the navigation behavior of the vessel and predicting its route, and, eventually, (v) integrating the several outcomes within a webGIS interface to easily assess the traffic status inside the considered area. The entire processing pipeline has been tested on satellite imagery captured within the Mediterranean Sea or extracted from public annotated datasets.https://www.mdpi.com/2072-4292/16/3/557maritime awareness systemsea surveillanceSAR sensingremote sensingship detectionship segmentation |
| spellingShingle | Marco Reggiannini Emanuele Salerno Clara Bacciu Andrea D’Errico Angelica Lo Duca Andrea Marchetti Massimo Martinelli Costanzo Mercurio Antonino Mistretta Marco Righi Marco Tampucci Claudio Di Paola Remote Sensing for Maritime Traffic Understanding Remote Sensing maritime awareness system sea surveillance SAR sensing remote sensing ship detection ship segmentation |
| title | Remote Sensing for Maritime Traffic Understanding |
| title_full | Remote Sensing for Maritime Traffic Understanding |
| title_fullStr | Remote Sensing for Maritime Traffic Understanding |
| title_full_unstemmed | Remote Sensing for Maritime Traffic Understanding |
| title_short | Remote Sensing for Maritime Traffic Understanding |
| title_sort | remote sensing for maritime traffic understanding |
| topic | maritime awareness system sea surveillance SAR sensing remote sensing ship detection ship segmentation |
| url | https://www.mdpi.com/2072-4292/16/3/557 |
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