# Large-Scale Automatic Vessel Monitoring Based on Dual-Polarization Sentinel-1 and AIS Data
## 4 Discussion
In general, the fact of not having an AIS matching position can be due to the following scenarios: (i) the vessel is located in a very dense traffic area where collisions of AIS messages may occur, e.g., English channel case study, (ii) the area where the vessel is located is not covered by AIS terrestrial stations and the reception of SAT-AIS messages is limited, and (iii) it is a dark vessel that did not broadcast its position during the time range centred on SAR acquisition time. Analogous, T3, T5 and T6 present similar SAR signatures with those of T2, which is a small sized sailing vessel. T3 is detected in the \(C_{VV-VH}^{un-norm}\) domain as well as in the \(I_{VH}\) image but not in the \(I_{VV}\) image. The latter, i.e. co-polarization channel, is more sensitive to the sea clutter and therefore, the signatures of small sized targets are impacted by the clutter and become hardly distinguishable. However, even if the VV signature is more hard to be detected, its correlation with the VH channel remains valid as it can be observed from the coherence signature which presents a high \(C_{VV-VH}^{un-norm}\) value. The sea-clutter is rarely represented with such high values of \(C_{VV-VH}^{un-norm}\), e.g., very high sea state. Therefore, in such scenarios \(C_{VV-VH}^{un-norm}\) facilitates the detection of small sized targets. The same aspect is demonstrated for T5 which presents a more important \(C_{VV-VH}^{un-norm}\) signature with respect to the VV and VH intensities. T6 illustrates a target that is visible only in the VH intensity channel, the VV signature being completely similar with the one of sea clutter and therefore not distinguishable in this domain. Based on the assessment of the examples given in Figure 8, which present illustratively a part of our analysis of the SAR vessel signatures, we conclude that for medium and large sized vessels (i.e., >100 m) the \(C_{VV-VH}^{un-norm}\) method and the \(I_{VV}\) and \(I_{VH}\) give similar detection performances. For small size targets, \(I_{VH}\) allows to detect more small size vessels with the drawback of having a high rate of alarms. However, as indicated in Section 3.2, the \(I_{VH}\) domain is also influenced by larger number of SAR over-detections with respect to \(C_{VV-VH}^{un-norm}\). Table 3 gives the total number of detections for each SAR methodology and the result of their intersection. We can notice that the intersection provides the lowest number of SAR detected targets. As indicated in previous example (Figure 8), the targets detected by all three SAR methodologies present a very high reliability of corresponding to vessels, even when AIS data is not available. The total  
number of SAR targets detected by the three methodologies, i.e., SAR intersection set, is superior to the number of AIS matched targets, thereby indicating the utility of SAR imagery for detecting dark vessels. In addition to the SAR over-detections associated to dark vessels and confirmed by the three SAR detectors, in the following we quantify the number of over-detections that are not detected jointly by the three SAR detectors. Table 4 gives percentages of AIS-SAR matched targets, AIS under-detections and SAR over-detections with respect to total of all AIS and SAR matched and unmatched targets, for each SAR methodology. The first two columns concerning the matching of the AIS data, confirm our previous conclusion, i.e., that the CFAR (VH) detector outperforms the other two methods, due to its capability to better detect small size vessels. The third column of the table, gives the percentage of SAR over-detections. We notice that the percentage of \(C_{VV-VH}^{un-norm}\)-based over-detections is lower with respect to the results obtained with the CFAR for both \(I_{VV}\) and \(I_{VH}\). In addition, the total number of AIS-SAR matched and unmatched targets is higher for both \(I_{VV}\) and \(I_{VH}\) than for \(C_{VV-VH}^{un-norm}\).