# MEC: A Mesoscale Events Classifier for Oceanographic Imagery
## 5 Results and Discussion  
Looking at Figure 7, we observe that the results of our analysis are aligned with the ground truth since the majority of the squares have been classified as \"E4\" (the red ones), and they are located within the geographical zone where events of type E4 are usually detected. Notably, the squares classified as E4 have a high reliability value \(n_{i,j}\), i.e., more high-quality data were available with respect to other squares. The features computation depends only on properties that are observable inside or in a neighbourhood of the considered square. Indeed, no a priori knowledge is assumed about the geographic and oceanographic properties of the area of interest. Based only on the requirement that a sufficient amount of captured temperature values is available, the algorithm actually returns the prediction of the mesoscale event that may have occurred within every square inside the area of interest. Of course, this approach is not always acceptable since it also provides a classification prediction for regions where the emergence of these phenomena cannot be observed due to the physical properties of the system. To avoid this issue, it is suitable to introduce constraints deriving from theoretical and empirical knowledge about the analysed phenomena. These considerations allow restricting the analysis to the geographical regions that constitute the most likely domains for the development of mesoscale events. Concerning the ICCS EBUF case, cold-water filaments are observed only within well-defined geographical zones off the Portuguese coast while the upwelling phenomena detection is possible only close to the shore. The introduction of such constraints, graphically represented in Figure 8, enables to filter out the unrealistic classifications, resulting, for the presented case study, in the refined classification depicted in Figure 9, where a single dominant event clearly emerges. In this case, the classifier correctly identifies the event class by returning several suitably labelled squares located in the corresponding geographical domain. It is not unusual to observe SST images series where the classifier response is less univocal. For example, on 16 September 2017 and 7 October 2017 (see, respectively, Figures 10 and 11), two separate clusters differently labelled are observed. In those cases, the output of the classifier apparently conflicts with the ground truth, but this can be explained by the fact that around the end of the observed time window, different types of SST events are detected. On 16 September 2017, two distinct events, E1 and E3, are concurrently detected, while almost the same circumstance occurs on 7 October 2017, where the ground truth label is E4, but traces of E1 are also detected on the previous days. This confirms the correctness of the MEC approach that, employing an analysis based on time series, accordingly identifies multiple typologies of events that develop within the considered time window in the neighbourhood of the main event. Figure 7: Labels given to each square of the grid, depending on their scores. Figure 8: Map of the areas where an event of a certain type may occur. Figure 10: **Left**: event of 16 September 2017, classified as E1 in the ground truth (but images with events classified as E3 are present around that day in the dataset). **Right**: heatmap generated by MEC. The figures are cropped to the area between 36\({}^{\circ}\) and 39\({}^{\circ}\) N and between 11\({}^{\circ}\) and 7\({}^{\circ}\) W for a better visualisation. Figure 9: Same as Figure 7, but for each type of event only the labels fulfilling the geographical constraints are kept. Despite the specific definition of the classification rules, modelled on the characteristic behaviour of the SST in the ICCS, the general applicability of the algorithm is ensured by the formulation of the classifier core. In fact, it can be applied to any marine environment, provided that the classification rules and the geographical constraints identifying the allowed areas are updated accordingly.