A Synergic Integration of AIS Data and SAR Imagery to Monitor Fisheries and Detect Suspicious Activities
We are happy to share with you our latest work entitled "A Synergic Integration of AIS Data and SAR Imagery to Monitor Fisheries and Detect Suspicious Activities". You can find the work here: https://doi.org/10.3390/s21082756
This work stems from the work carried out by Prof. Adriano Mancini and Alessandro Galdelli (Postdoc), in collaboration with “Istituto per le Risorse Biologiche e le Biotecnologie Marine” of the CNR (CNR-IRBIM) on the identification of illegal fishing activities. The authors would thank Prof. Ennio Gambi and Adelmo De Sanctis of Università Politecnica delle Marche for making available the AIS data collected by the Comar receiver installed on the roof of the University.
The paper integrates non-cooperative Synthetic Aperture Radar (SAR) Sentinel-1 images and cooperative Automatic Identification System (AIS) data, by proposing two types of associations: (i) point-to-point and (ii) point-to-line. They allow the fusion of ship positions and highlight “suspicious” AIS data gaps in close proximity of managed areas that can be further investigated only once the vessel—and the gear it adopts—is known. This is addressed by a machine-learning approach based on the Fast Fourier Transform that classifies single sea trips. The approach is tested on a case study in the central Adriatic Sea, automatically reporting AIS-SAR associations and seeking ships that are not broadcasting their positions (intentionally or not).
#vrai #cnr #irbim #ais #sar #fishingeffort #machinelearning #iuufishing #mdpi #sensors
