Earth Observation (EO) data can become an essential tool in the transformation of a raw materials sector that aims to reconfigure its model of operation. The high demand for the mineral resources necessary for the transition to a carbon neutral and circular economy conflicts with the increasing difficulties of finding new deposits. As the sector heads towards embracing circularity and reducing the environmental impacts, a clear focus has been set on developing appropriate tools to boost the efficiency of mineral resource management, both technologically and economically. In this scenario, the Sentinel satellites of the European Copernicus program come into play. Despite being satellites considered medium resolution, they provide great temporal and spatial coverage in a continuous record, which makes them tools with great potential for the raw materials sector. However, the lack of applications in the raw materials sector suggests that these technological advances have remained underrated by sectoral actors. The RawMatCop program was designed to bridge this gap. This program, co-funded by the European Commission and EIT RawMaterials, aims to develop applications and promote the use of Copernicus data in the raw materials sector to contribute to a safe and sustainable supply of mineral resources. The presented applications can be grouped into three categories covering the whole mining cycle from exploration to exploitation and post-mining. Two of the presented case studies cover the study of primary sources including exploration of Iron Oxide Copper Gold mineralisations to identify high-potential mining areas and mapping of informal gold mining and its environmental impacts. Another project focused on secondary sources tackled data applications for grade mapping and sample optimisation in mining residues. And the forth project focused on monitoring ground stability related to mining activity. The results demonstrate the high cost-effectiveness of Sentinel 1 and 2 in extending ground-based measurements to larger areas, especially when these are hard-to-reach areas. Finally, the presented projects examine the industrial and social impacts of technological innovations, as well as contribute to the achievement of prominent European Union policy objectives and the United Nations Sustainable Development Goals.

The aim of this work is to develop a simple and effective approach for surficial iron mineral potential zone identification and mapping using optical remote sensing data. Thus, an iron mineral potential model (IMPM) was developed by combining multiple band ratios for iron mineral detection. The developed method was applied on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data from Malmberget and nearby area from Gällivare district, Norrbotten county, Sweden. The results from the study area revealed that the developed approach is effective in iron mineral potential zone mapping using ASTER data with more than 90% accuracy.

Nowadays, remote sensing technologies are playing a significant role in mineral potential mapping. To optimize the exploration approach along with a cost-effective way, narrow down the target areas for a more detailed study for mineral exploration using suitable data selection and accurate data processing approaches are crucial. To establish optimum procedures by integrating space-borne remote sensing data with other earth sciences data (e.g., airborne magnetic and electromagnetic) for exploration of Iron Oxide Copper Gold (IOCG) mineralization is the objective of this study. Further, the project focus is to test the effectiveness of Copernicus Sentinel-2 data in mineral potential mapping from the high Arctic region. Thus, Inglefield Land from northwest Greenland has been chosen as a study area to evaluate the developed approach. The altered minerals, including irons and clays, were mapped utilizing Sentinel-2 data through band ratio and principal component analysis (PCA) methods. Lineaments of the study area were extracted from Sentinel-2 data using directional filters. Self-Organizing Maps (SOM) and Support Vector Machines (SVM) were used for classification and analysing the available data. Further, various thematic maps (e.g., geological, geophysical, geochemical) were prepared from the study area. Finally, a mineral prospectively map was generated by integrating the above mentioned information using the Fuzzy Analytic Hierarchy Process (FAHP). The prepared potential map for IOCG mineralization using the above approach of Inglefield Land shows a good agreement with the previous geological field studies.

This paper investigates spaceborne multiple multispectral data-fusion and blending to generate an integrated data with higher spatio-spectral resolution and spectral coverage in order to obtain improved geological mapping. A hybrid approach using Gram-Schmidt pan-sharpening and Inverse Distance Weighting (IDW) based downsampling technique is developed to generate integrated data from multiple multispectral data. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat 8, and Sentinel-2 data have been used to evaluate the developed approach for lithological mapping. Liikavaara to Puoltikasvaara including Nautanen and nearby-mining area, in the Gällivare district of Norrbotten county, Sweden, is chosen as a case study. Lithological map of the study area is produced using Support Vector Machine (SVM) classifier. Bedrock geological map from the Geological Survey of Sweden (SGU) is used for classification accuracy assessment. The results show that integrated data produced better accuracy than original individual spaceborne multispectral data for lithological mapping of the study area.