SOURCE-LINKED INTELLIGENCE

Enabling Global-Scale Mine-Level Indicators from Satellite Observations

CORDIS · observation · Publication date unknown

development efforts. Essential indicators, such as geographical locations, waste generation, and details of extracted minerals and commodities, are surprisingly scant worldwide. Satellite images and artificial intelligence algorithms are prominent technologies to fill this knowledge gap. However, scaling the mapping of mining indicators to the global level remains a challenge due to the small size and low quality of training sets. The MINE-THE-GAP project will lay the foundations of an innovative methodology to scale up the production of mine-level indicators. Methodologically, the project presents a breakthrough by integrating high-precision data products from various satellite sources to substantially enrich training sets that will enable the creation of scalable artificial intelligence models to effectively map mine land use, waste generation, and types of extracted minerals and commodities. This approach will allow the production of mine-level indicators that are timely, locally relevant, and globally reliable, and ensure the continuous improvement of models beyond the project's

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recordType

award

status

SIGNED

region

EU

value

2000000

unit

EUR