Detecting illegal mines from space
Matthias Werner
Throughout the globe, rain forests and other natural landscapes are endangered by illegal mining, which transforms areas formerly rich in flora and fauna into wasteland. In order for local governments to take countermeasures, they first need to know about the locations of illegal mines. In countries covered by vast areas of impenetrable rain forest, such as Brazil or Congo, obtaining this information is a difficult problem. In this blog post I describe an approach to detect illegal mines based on deep learning and remote sensing, that we have developed to support the conservation efforts of governments and NGOs. In particular, we use a U-Net for semantic segmentation , a branch of computer vision. As part of the project of automatic detection of illegal mines , we were also joined by scientists from the Institute of Mineral Resources Engineering of the RWTH Aachen University, who contributed their mining-specific expertise. The project was funded by the European Space Agency .
