dida successfully completed the ESA project "ASMSpotter". The project investigated the feasibility of automatically identifying artisanal gold mining sites (ASGM)
on satellite images using machine learning.
In the implementation, dida has worked with both PlanetScope and Sentinel-2 satellite images and, together with the Institute of Mineral Resources
Engineering (MRE) from RWTH Aachen University, generated a training data set of more than 10,000 annotated images for model training. For the test area in the
Northeast Surinam a classification accuracy of over 80% was achieved. Furthermore it could be proven that the ML model
can be applied to areas of similar topography.
Due to the positive assessment by ESA, the project will be continued with an ASGM partner in the future. The software will be implemented in a
ASGM project in Ghana to identify illegal mining activities at an early stage.
We would like to thank ESA and the MRE of RWTH Aachen University for the trustful cooperation!