Preliminary Assessment of Metal Contamination in Mining Soils Using Sentinel-2 MSI: A Case Study of São Domingos Mine, Portugal

The INCOME project (Instruments for Managing Areas Contaminated by Metals) proposes the development of an environmental management model for mining soils contaminated by metals. This study presents preliminary results obtained using the Multispectral Imager (MSI) aboard the European Space Agency's (ESA) Sentinel-2 satellite to identify contaminated soils in the São Domingos Mine, located in southeastern Portugal.

The MSI instrument offers significant advantages, including high spatial resolution (10, 20, or 60 m depending on the spectral band), open access for rapid image download, and frequent revisitation of the study area. The preliminary analysis focuses on identifying areas with fully exposed soil using spectral indices, which combine spectral measurements at different wavelengths to improve classification accuracy. Additionally, the Random Forest (RF) method, a widely recognised approach to general-purpose classification, was tested. Contaminated soils characteristically exhibit discrepancies in optical properties, such as distinct colouration, which can also be detected in the visible region bands of the MSI instrument. The Shortwave Infrared (SWIR) bands are particularly efficacious for identifying heavy metals.

The designated soil areas will be subject to monitoring for metal contamination utilizing the MSI instrument, with the prospective incorporation of hyperspectral data from satellites such as the Environmental Mapping and Analysis Program (EnMAP).

Funding: The work was supported by the Promove Program of the “la Caixa” Foundation, in partnership with BPI and the Foundation for Science and Technology (FCT), in the scope of the project INCOME – Inputs para uma região mais sustentável: Instrumentos para a gestão de zonas contaminadas por metais (Inputs for a more sustainable region: Instruments for managing metal-contaminated areas), PD23-00013. Acknowledgment: CREATE Project (R&D Unit ID 6107).