# Aveiro Canyon Head (Portugal) Submarine Slope Instability Assessment
## 4 Data Acquisition and Processing
### Predisposing Factors
In general, these values mean that the models predicted approximately 79% (IV) and 83% (LR) of the instability events. Observing the Figure 5, it is possible to verify that at the beginning of the curve, the first 5% of the susceptible area (false positives) corresponds to approximately 21%, for the IV curve, and 33%, for the LR curve, of the inventoried movements (true positives). However, both curves end up converging when 45% of the total area returns about 90% of the instability inventory. Based on the outputs of the IV and LR models, susceptibility maps to the occurrence of slope movements were produced (Figure 6). In order to make the results comparable, the predictive maps correspond to the models integrating all 5 factors. In the case of the LR model, the obtained map presents the best model, while the IV map presents the model with the worst AUC result between all of the method's models (Table 4). The degree of susceptibility was assessed in 5 classes based on the percentage of susceptible area, i.e.,  
Figure 6: Susceptibility maps based on the information value (IV) model with all factors (on the left), and on the logistic regression (LR) model with all factors (on the right). Black polygons correspond to the delimitations of the identified instabilities. the percentage area affected by SMM: very low (\(<\)5%), low (5-20%), moderate (20-35%), high (35-50%) and very high (\(>\)50%). In this study, considering only the forward regression method, with the exception of the curvature, all factors contributed to the increase in the success rates of the models, with AUCs ranging from a minimum 0.79 with one factor, to a maximum 0.83 with 5 factors (Table 4). As for the IV method, the addition of more predisposing factors does not necessarily correspond to an improvement on the susceptibility model output. The best models were obtained with a maximum of 4 factors (bathymetry, superficial sediments, slope and aspect). The increase in more factors resulted in a decrease in the quality of the obtained models, which may be attributed to the poor correlation of some factors with the occurrence of landslides. In fact, in the single model category it appears that the one considering bathymetry presents the highest AUC value. The models that produced the best AUC results (0.7971 and 0.7955, respectively) are those using bathymetry, slope and aspect. The remaining models, although presenting satisfactory results, showed lower AUC scores, ranging from 0.7875 to 0.7936. In spite of the differences between the results, both methods indicate that bathymetry is the most important factor in the prediction of the instabilities in the Aveiro Canyon slopes. In fact, it makes sense because not only dynamic processes, in marine environment, are strongly controlled by depth, but this variable is also expressed in others important factors such as slope, roughness, aspect, the presence/absence of rocky outcrops and the distribution of marine sediments (which are controlled also with the distance to the particle sources). In the predictive models, the mean slope angle and aspect play important roles as well. These two factors, derived from the DBM, represent, not only the bathymetric spatial variation, but also the expression of geologic internal structures. In fact, the morphologic analysis of the Aveiro Canyon [48; 49] revealed three important variations in the slope gradient, explained by the outcrop of intercalated geologic formations, with different resistance to the marine erosion processes. In fact, the existence of alternation of soft layers with more resistant layers of the Cenozoic detrital formations was identified in this sector of the Portuguese margin [20; 21] and explains the different levels of erosion. The existence of bottom currents, specifically upwelling currents [50; 51], is probably one of the erosional agents that carves the canyon slopes and promote the variation of mean slope angle and slope direction, contributing to the instability of sediments located nearby.