The synergic utilization of data from different sources, either ground-based or spaceborne, can lead to effectively monitor fishing activities in close proximity of managed areas, and help tackle the problem of global overfishing. To this end, the integration of spaceborne Synthetic Aperture Radar (SAR) data and cooperative Automatic Identification System (AIS) information has the appealing potential to provide a better picture of what is happening at sea by detecting vessels that are not reporting their positioning data (intentionally or not) and, on the other side, by validating ships detected in satellite imagery. In this context, this paper deals with the investigation of" suspicious" AIS data gap and the integration of SAR-based ship detection by a point-to-point and a point-to-line types of association. Time-filtered and classified AIS transmissions (according to the gear in use) are used to predict SAR positions, with the next step being to search/match corresponding SAR-based targets. A case study is analyzed, in which the method is tested in proximity of managed areas characterized by significant AIS blackouts, using occasional Sentinel-1 images of the central Adriatic Sea and AIS data.