## 5 Discussion  
Two databases for the selected area in Vigonzano were collected and studied. Geochemical in situ samples were taken directly from the mining wastes, and EO data were indirect data (Sentinel-2 image). At the first statistical analysis, iron showed a high correlation with the major and trace elements (such as Cr, Co, Cu, Ce, La, Rb, and Nb). In addition, since iron is an important element in RS to detect minerals, the iron band ratios were considered as auxiliary database for mapping. To map the selected elements, we needed the co-regionalization modeling to demonstrate the spatial correlations. The co-regionalization modelling of major and trace elements was quite challenging because (1) the limited numbers of geochemical samples and (2) the selectivity and directional sampling that resulted in having more samples in the middle and less samples from the boundaries of the mining wastes, wherein the bedrock crops out. RS data provide a homogenous 10 \(\times\) 10 m data grid that plays a fundamental role in mapping because of the large amount of data. The spatial correlation between RS data and in situ samples helped in the estimation of the unknown areas using the Co-Kriging estimation. The composition maps confirmed the geochemical interpretations of iron (Fe\({}_{2}\)O\({}_{3}\)) and Cu and Cr enrichments in the Vigonzano mining wastes compared to the adjacent agricultural areas. The Fe\({}_{2}\)O\({}_{3}\) and Cu reflected the heterogeneity of the wastes, whereas the Cr distribution was likely related to the bedrock lithological composition, i.e., serpentinized ultramafic rocks. The element distribution showed that about 20% of the mine area (around 1000 m\({}^{2}\)) had Cu > 2500 ppm and Cr > 1500 ppm. Results were obtained from the integration of RS and in situ samples (considering only the surface area) and assuming a bulk density of 1350 kg/m\({}^{3}\)[39]. Therefore, a minimum grade of 0.3% for Cu and 0.2% for Cr was obtained for one meter depth. For comparison with the main source of global copper, the Cu grade in porphyry deposits is 0.2-1.5% [40]. Moreover, Co as a critical element, showing the  
Figure 6: Composition maps of La, Ce, Nb, and Rb within the Vigonzano mining waste obtained by Co-Kriging of samples and the band ratio (4/11). enrichment in the south-east part of the Vigonzano abandoned site, with a similar pattern as Cr. About 10% of the mining wastes area had Co > 130 ppm, with the minimum grade of 0.01%. This very low grade value is instead similar to the Co grade assessed for magmatic Ni-Cu (Co-PGE) sulfide deposits worldwide [41]. The maps (Figure 6) indicate the Ce, La, Rb, and Nb depletion within the Vigonzano mining waste relative to the surrounding areas. The relative enrichment of these elements in the agriculture soils was not investigated, but a working hypothesis is that the enrichment of these elements is related to the use of fertilizers. The main limitation of this practical approach is that it relies on the surface data (surface samples and Sentinel-2 images). In general, the lack of concentration data along vertical profiles in mining waste increases the uncertainties of the grade assessments. Many challenges such as sampling along depth profiles, heterogeneity of materials, and modification of the mineralogy due to weathering remain. To achieve a comprehensive characterization of mining wastes, one requires precise and regular sampling (both for environmental and economic aspects). Our practical approach, however, highlights the suitable subregions inside the dump area where more detailed investigations, especially in 3D, should be performed. The Vigonzano site is a small-scale abandoned mine that can be regarded as an unimportant prospect for secondary recovery of critical and other strategic raw materials. However, according to the most recent Italian catalogue on abandoned mine sites [42], small-scale sites (with mining concessions less than 100,000 m\({}^{2}\)) account for about 19% of the Italian legacy mines inventory.