Satellites for Batteries Project
Cornish Lithium partnered with a consortium of remote sensing and machine learning specialists in a project funded by the UK Space Agency (UKSA) under the National Space Innovation Programme (NSIP).
This project worked towards understanding how automating processes, specifically the interpretation of satellite imagery, could be utilised to create prospectivity tools for key technology metals in Cornwall. This sustainable approach to exploration will help to expedite the achievement of climate targets outlined by the UK government that state emissions must drop by 78% by 2035 (gov.uk). This smart approach to exploration, utilising machine learning to define targets from remote sensing data, coupled with targeting the elements that are key for the transition to a clean, green future, is crucial to Cornish Lithium’s ethos of employing cutting edge techniques to enable an environmentally conscious exploration programme.
Academic and industry partners made up the consortium which consisted of Cornish Lithium, Satellite Applications Catapult, Camborne School of Mines, Terrabotics, Decision Lab, The British Geological Survey, Pixalytics and CGG.
Multispectral and hyperspectral satellite imagery was processed to produce mineral alteration maps, structural lineaments, vegetation indices and land classification maps. These were, in turn, embedded within a machine learning ensemble that when cross-validated with ground truth data produced prospectivity targets.
Due to the innovative approach undertaken in this project, an element of ground verification was required which sent Cornish Lithium employees out into the field to use more conventional geological mapping methods. Continual validation of targets on the ground was a key element of the iterative approach that the machine learning modelling took. This allowed for a highly accurate prospectivity map to be produced.
This data driven approach to exploration has given Cornish Lithium a key insight into potential future targets for the extraction of metals that are key for the energy transition that the UK is currently undergoing.
To compliment the S4B project drone footage was acquired that enabled further structural analysis and site verification to take place (https://www.cornishlithium.com/360/lithium/#s=pano10119).
Ground Verification and Machine Learning iteration fieldwork campaign