This experiment borrows an artificial neural network architecture originally developed in the field of biomedical imaging and applies it to the processing of orthophotos (orthorectified Earth observation images captured by drones, aircraft or satellites). In geology and in mineral exploration specifically, orthophotos are commonly used to guide the logistic planning of field work. In this post I show that the U-Net architecture can be trained to automatically map waterbodies and detect areas where the bedrock is outcropping using high-resolution orthophotos. This tool is fast and provides new insights in preparation of geological mapping traverses, rock/soil sampling campaigns, and for the…

Charles L. Bérubé

Assistant professor of applied geophysics @ Polytechnique Montréal. Previously R&D lead @ GoldSpot Discoveries.

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