## 3 Results
### Regression Analysis: Acoustic and Non-Acoustic Factors  
To identify the acoustic and non-acoustic variables that best explain the soundscape pleasantness (SSC-pleasant) and their relative relevance [31], step-by-step regression analysis is used. SSC-pleasant is introduced as the dependent variable. Separately, the variables that best explain soundscape pleasantness are:  
1. For acoustic parameters: LAmin,1s and LAeq,10 min, which account for 7.4% of the variance of soundscape pleasantness. 2. For acoustic event assessment: The balance of acoustic events (positive versus negative), which accounts for just 1%. 3. For sound source assessment: The balance of pleasantness (3.8% of variance explained). 4. For physical characteristics of the surroundings: The percentage of surface covered by water (%BLUE), the presence of traffic and social interactions, and the surface area of the place, which explain 14.1% of the variance. 5. The variable that represents whether or not people would use the place to relax in accounts for 4.7% of the variance in soundscape pleasantness of a place. Considering all of the variables related with the acoustic environment (points a, b and c), it can be said that the acoustic factors that account for a significant percentage of variance in soundscape pleasantness are, firstly, the balance of pleasantness of the main sound sources (\(R^{2}\) adjusted = 0.038); secondly, LAmin,1s (\(R^{2}\) adjusted = 0.055); thirdly LAeq,10 min (\(R^{2}\) adjusted = 0.109); and lastly the number of negative events (\(R^{2}\) adjusted = 0.120). These variables account for 12.0% of the soundscape variance, which means a 62% increase compared with the variance explained by acoustic indicators (7.4%). By including non-acoustic variables (point d) in the analysis as well, the percentage of variance explained in soundscape pleasantness rises even more: (1) by the presence of water (%BLUE); (2) be the presence of traffic (\(R^{2}\) adjusted = 0.121); (4) by the balance of pleasantness among the main sound sources (\(R^{2}\) adjusted = 0.139) and surface area sources (\(R^{2}\) adjusted = 0.149); LAeq,10 min (\(R^{2}\) adjusted = 0.164) and LAmin,1s (\(R^{2}\) adjusted = 0.171); and (5) by LAmax,1s (\(R^{2}\) adjusted = 0.177). The objective and objetifiable variables, both acoustic and non-acoustic, account for 17.7% of soundscape pleasantness variance, 48% in the variance explained by acoustic variables (12%) and 239% in that explained by acoustic indices (7.4%). \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**Parameters** & **LAeq,10 min** & **LAmin,1s** & **LAmax,1s** & **LA10-LA90** & **LA10** & **LA50** & **LA90** & **No.** & **No.** & **No.** & **No.** & **No.** \\  & & & & & & & & & & & & \\  & & & & & & & & & & & & \\ \hline No. total & \(-\)0.27 & \(-\)0.39 & \(-\)0.19 & \(-\)0.16 & \(-\)0.27 & \(-\)0.27 & \(-\)0.26 & & 0.12 & 0.12 & \(-\)0.14 & \\ \hline No. pleasant & & & & & & & & & & & & \\ sound source & - & - & - & - & - & - & - & - & - & - & - \\ \hline No. & & & & & & & & & & & & \\ unpleasant & \(-\)0.11 & \(-\)0.16 & - & - & \(-\)0.11 & \(-\)0.10 & - & - & - & - & - & - \\ sound source & & & & & & & & & & & & \\ balance & 0.12 & 0.15 & - & - & 0.12 & 0.12 & 0.12 & - & - & - & - & - \\ \hline SSC\_Pleasant & & & 0.16 & - & - & - & - & - & - & - & - & 0.11 \\ \hline LSC\_Pleasant & 0.12 & 0.15 & 0.12 & 0.11 & 0.13 & 0.11 & 0.10 & - & - & - & - & - \\ \hline Relaxing use & 0.10 & - & - & - & - & 0.10 & - & - & - & - & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Pearson significant correlation (\(p<0.05\)) between acoustic parameters and pleasantness of sources, landscape and soundscape. If the variable most closely related with soundscape pleasantness, the congruence between soundscape and landscape, is also included in the analysis, the percentage of explained variance is 31.9%. This variable, though subjective, could be made \"objectifiable\", which is one of the challenges we face into the future.