## 3 Results
### LISA and Hot-Spot Analysis
\begin{table}
\begin{tabular}{c c c c} \hline \multicolumn{2}{c}{**Bivariate Anselin Local Moran’s I Values**} & \(\boldsymbol{LID}-\boldsymbol{I_{\text{IDS}}}\) & \(\boldsymbol{SA}-\boldsymbol{I_{\text{IDS}}}\) & \(\boldsymbol{ATO}-\boldsymbol{I_{\text{EDS}}}\) \\ \hline Global Moran’s Index & 0.47 & 0.57 & 0.62 \\ z-score & 37.8 & 54.8 & 57.1 \\ \(p\)-value & \textgreater{}0.01 & \textgreater{}0.01 & \textgreater{}0.01 \\ \hline F-statistic & 55.1 & 69.6 & 71.5 \\ R-squared & 0.18 & 0.20 & 0.21 \\ Adjusted R-squared & 0.18 & 0.21 & 0.22 \\ Number of observations & 387 & 1,022 & 730 \\ \hline \end{tabular}
\end{table} 
Table 5: Bivariate Anselin Local Moran’s \(I\) statistics for spatial autocorrelation between the \(I_{\text{EDS}}\) global coastal vulnerability index and the three GIS anthropization indices \(LID\), \(SA\), and \(ATO\). were discretized through a tessellation geoprocess with 100 \(\times\) 100 m cells to facilitate the understanding of the HL large-scale territorial behavior patterns of the phenomenon (the value of a tile is assigned if an HL combination occupies more than 50% of its surface; in case none of the possible combinations exceeds 50%, no value is assigned). If the density of points is observed, it can be verified that the phenomenon of territorial anthropization that generates a greater link with the damages of the DANA is the territorial transformation associated with the alteration of the orography or land use. The one that generates the least association of damages from floods is the transformation derived from  
Figure 11: Hot- and cold-spot LISA analysis for spatial statistical correlation between damage and anthropization indices: (**a**) \(LID-I_{EDS}\) (**b**) \(SA-I_{EDS}\) and (**c**) \(ATO-I_{EDS}\). the creation of transport infrastructures. On the other hand, it can be verified that in the three cases, the areas with a positive correlation (i.e., low level of damage correlating to low level of territorial transformation) mostly coincide, being located in areas such as natural parks or protected areas belonging to the Natura 2000 Network. Regarding the behavior patterns of the geostatistical damage-indicator correlation, we observed three clearly differentiated patterns. In the first case, transport infrastructures in many cases present a certain linear pattern at the spatial level, which overlaps on many occasions with the proximity to some major highways. This denotes the existence of a certain dam effect in some areas. However, what is more complex to understand is the dispersed distribution in other areas, which is possibly a consequence of joint action with other variables from other indicators. In the case of the so-called process of \"artificialization\" of the soil, we see how the highest level of geostatistical correlation between damages and territorial transformations tends to be concentrated in three urban settlements where the urban areas have undergone significant growth in recent decades. This more concentrated behavior pattern is likely related to the phenomenon of soil sealing, making areas vulnerable that were not previously vulnerable to flooding. Finally, the distribution of the correlation of damages associated with the transformations from alterations of uses and the orography of the soil presents a very dispersed character. As indicated above, although it has the highest level of density--which confirms its importance in the global phenomenon--and some clustering points can be found, it is difficult to establish a clear pattern of behavior. Therefore, it is necessary to carry out a more detailed analysis through the use of subindices to better understand the phenomenon.