The assignment of normalized intensity curves to specific clusters is reconstructed into an image in Figure . This visualization is overlaid with the initially detected pit regions, which were previously identified through UMAP analysis (marked in orange for one exemplar pit in Figure ). Higher magnification images in Figure reveal that pits preferentially initiate in pixels assigned to the orange cluster, which corresponds to regions with lower average normalized intensities and identified as pitting-susceptible zones (PSZ). For example, Pits 2 and 3 are located entirely within orange pixels. Pits 1, 6, and 7 each include only one blue pixel, with all other pixels belonging to the orange cluster. Pit 5 shares more than 50% of its area with orange pixels. To establish the general trend and ensure statistical significance, we analyzed entire datasets obtained in 5-100 mM NaCl, encompassing a total of 61 pits, to determine the number of pits as a function of the PSZ area fraction within the pit and as a function of pit centroid position (Figure ). The overall conclusion is that pits tend to form within the orange area, identified as the PSZ, with approximately 70% of the initially detected pit area residing completely within the PSZ (Figure , left). Cumulatively, approximately 90% of the pit area is at least half within the PSZ, with only a few examples exhibiting no overlap with the PSZ. A similar trend is observed based on analysis of the centroid position of the pits, with approximately 82% of centroids located within the PSZ (Figure , right). It is important to note that the overall proportion of blue and orange areas is approximately 50%, as visible in Figure . This observation is sufficient to rule out the possibility of random coincidence of orange area dominance within pit areas. Nevertheless, we additionally performed a Chi-Square Test of Independence (SI-7), which further confirmed that the observed trend of pit locations within the PSZ is statistically significant across our datasets.