Abstract
Abandoned mining wastes are both an environmental challenge and a possible secondary raw material source. The characterization and monitoring of these sites are often expensive and cumbersome because of the need of repeated field surveys. Remote sensing data are a cost-effective alternative that helps in producing multiscale maps of mining wastes. These maps can be used to investigate and monitor the spatial patterns of different elements within the mining wastes. In this work, Sentinel-2 images are combined with the geochemical samples in order to map the distribution of iron, copper, chromium, and cobalt. The target area was the Vigonzano mining wastes in Northern Apennines (Italy) where there are a small number of geochemical analyses but a large amount of satellite image data. We used the multivariate geostatistical estimation method (Co-Kriging) that exploit the meaningful spatial correlation between the elements of interest and band ratios (obtained from Sentinel-2 images). The concentration maps highlighted subareas for Cu and Cr with an estimated grade of about 0.3% and 0.2%, respectively. In addition, the critical element Co showed an enrichment in the south-east part of the mining wastes, in a similar pattern as Cr. Instead, the obtained maps show Ce, La, Rb, and Nb depletion compared to the surrounding agricultural areas. The concentration maps were intended as a prefeasibility study to determine enriched areas for further detailed investigation.
Funder
European Institute of Innovation and Technology
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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