# Mass Processing of Sentinel-1 Images for
## 4 Results and Discussion
### Density Maps  
Maps were computed applying a smoothing kernel to the points. In the different maps, a point can be a SAR ship detection, an interpolated reported position or a source of recurrence. To compute the density maps in this section, the points are weighted by the inverse of the number of images, excluding RFI-labelled images, at each point's location. Figure 8 shows the density map of all the ship detections with high reliability level. The main shipping lanes are clearly visible in the map, as are the high concentration of ships outside many coastal cities and ports. It has to be remembered that this map has been created aggregating snapshots taken at 6:00 a.m. and 6:00 p.m. local time only; this temporal filtering hides traffic that only occurs outside those times. Note that, in Figures 8-12, the results that extend into the Black Sea are not so statistically robust as they are based on a few images only (see Figure 2). Figure 9 presents the density map of interpolated reported positions. The main difference between Figure 8 (detections) and Figure 9 (reported positions) is the high density of reported positions near the coast of Spain, France and Italy that are not detected in the SAR images. These reported positions likely correspond to small boats. Figure 10 maps the uncorrelated, non-recurrent detections. This map evidences the presence of a large number of ships for which no position reports are available. The map closely reflects the AIS area coverage: many of the detections in areas with good AIS coverage are excluded from the map, but detections in areas with bad coverage remain. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Number** & **Fraction** & **Fraction** & **Fraction** & **Fraction** \\ \hline Ship detections (only reliable) & 608,326 & 100\% & & & \\ Non-recurrent detections & 485,342 & 80\% & 100\% & & \\ Correlated & 320,566 & 53\% & 66\% & & \\ Uncorrelated & 164,776 & 27\% & 34\% & & \\ Recurrent detections & 122,984 & 20\% & & 100\% & \\ Fixed structures & 91,757 & 15\% & & 75\% & \\ Ambiguities & 31,227 & 5\% & & 25\% & \\ Sources of recurrence & 12,300 & & & & 100\% \\ Fixed structures & 9565 & & & & 78\% \\ Ambiguities & 2735 & & & & 22\% \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of the recurrence analysis (excluding off Israel area). Figure 8: Density map of all the reliable detections (608,326). Area off Israel with high concentration of RFI-related detections is indicated as a white polygon. Figure 10: Density map of uncorrelated, non-recurrent ship detections (164,776). Area off Israel with high concentration of RFI-related detections is indicated as a white polygon. Figure 9: Density map of interpolated reported positions (818,493). Area off Israel with high concentration of RFI-related detections is indicated as a white polygon. Figure 11: Weighted maps of: (**a**) sources of recurrence (12,300); (**b**) sources classified as fixed structures (9565); and (**c**) sources classified as ambiguities (2735). In all maps, the sources of recurrence are weighted by the ratio between the number of images in which the source has been detected over the number of images in which the source could have been detected Area off Israel with high concentration of RFI-related detections is indicated as a white polygon. Figure 11 displays the weighted geographic distribution of: (a) all the sources of recurrence; (b) the sources categorised as fixed structures; and (c) the sources categorised as ambiguities. The weight applied to each point in these maps is calculated as the ratio between the number of images in which the source of recurrence has been detected over the number of images in which the source could have been detected, i.e., all the images in the case of the fixed structures, only the images with a given observation geometry in the case of the ambiguities. It is seen that many of the small blobs of SAR ship detections in Figure 8 correspond to recurrent detections.