Radar, hyperspectral imaging and deep learning. Mining-monitoring tools for the southern cone of America: a literature review

Abstract

This research examines, through a process of several consecutive phases (identification, selection and critical synthesis), the role of remote sensing and advanced data analysis in mining. It analyzes how hyperspectral sensors, UAV or radar are applied to the detection of mining disturbances, acid drainage and deforestation, integrated with socio-environmental approaches that drive ecological restoration. From the evidence compiled, the relevance of collaborative methodologies and computational tools (big data, deep learning) to optimize decision making is recognized. A key finding is that smart mining can reconcile productivity and conservation of ecosystem services, provided that there is coordination between science, industry and local governance for continuous monitoring and timely mitigation of impacts.