## 3 Results
In the diagram in Figure 9, the relationships between average values of reflectivity (_I_) and rebound (_r_) for different lithotypes are compared. The figure displays data obtained from the six surveys performed on distinct lithotypes. From the overall analysis of the results, it can be concluded that the average values of the measurements obtained with the laser scanner are well correlated with those obtained with the Schmidt hammer. The figure also indicates the types of lasers used. Consequently, the parameters of the correlation curve depend on the wavelength of the beam emitted by the instrument and, essentially, on the model of the instrument used. The data were correlated using linear regression characterized by high values of the correlation coefficient (R\({}^{2}\) = 0.93-0.98). It is necessary to specify that the relationships obtained do not have absolute validity but undergo variations depending on the analyzed lithotype, as reflectivity is closely dependent on the type of  
Figure 8: Palazzo Jung (Palermo). Altered column (on the right) and intact column (on the left). Figure 9: Relationships between reflectivity (I) and rebound (_r_) for the six surveys. material constituting the surface subject to the survey. This is evident from the diagram in Figure 9, where the results obtained for different lithotypes are compared. The correlation between the spectral signatures and the strength of stone materials depends on the degree of alteration, which itself is influenced by various factors including chemical processes, environmental conditions, and humidity. In the context of rock mass characterization, operations are carried out under the same conditions to ensure accurate zoning of the rock mass. Considering the relationship between reflectivity (_I_) and rebound (_r_) values, expressed as \(r\) = _ml_ + \(q\), Table 2 presents the values of \(m\) (angular coefficient) and \(q\) (intercept on the _y_-axis) for each lithotype. Furthermore, the table includes the rebound values corresponding to reflectivity values of 100% (_r_=100). This study, conducted in the laboratory, included controlled weathering processes in samples of tuff and calcarenite to validate the correlation between reflectivity (_I_) and the degree of alteration. Tuff and calcarenite are two rocks that exhibit the typical mechanical behavior of hard soils/soft rocks. Two distinct techniques were employed to induce weathering processes: one based on the effects of thermal stress induced by repeated cycles of freezing (\(-20\)\({}^{\circ}\)C) and thawing (+105 \({}^{\circ}\)C), and a second based on volume variations inanhydrous sodium sulfate during crystal formation. Tuff samples were subjected to freeze-thaw cycles, and both tuff and limestone samples were immersed in a saturated solution of sodium sulfate. In both lithotypes, a reduction in reflectivity was recorded as the material's porosity (_n_) increased (Figure 10). The measurements provided variable values of reflectivity (_I_) within similar ranges for each lithotype, even in the presence of significantly different porosities. Schmidt hammer measurements were taken at the beginning and end of each weathering process. Similar to reflectivity (_I_) the values of rebound (_r_), regardless of the technique and lithotype, decreased with the progression of the weathering process, and the two parameters are correlated with linear regression.