We present global and regional correlations between whole-rock values of Sr/Y and La/Yb and crustal thickness for intermediate rocks from modern subduction-related magmatic arcs formed around the Pacific. These correlations bolster earlier ideas that various geochemical parameters can be used to track changes of crustal thickness through time in ancient subduction systems. Inferred crustal thicknesses using our proposed empirical fits are consistent with independent geologic constraints for the Cenozoic evolution of the central Andes, as well as various Mesozoic magmatic arc segments currently exposed in the Coast Mountains, British Columbia, and the Sierra Nevada and Mojave-Transverse Range regions of California. We propose that these geochemical parameters can be used, when averaged over the typical lifetimes and spatial footprints of composite volcanoes and their intrusive equivalents to infer crustal thickness changes over time in ancient orogens.

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Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geological activities during exploration and mining monitoring. We describe an integrated workflow to produce a geometrically and spectrally accurate combination of a Structure-from-Motion Multi-View Stereo point cloud and hyperspectral data cubes in the visible to near-infrared (VNIR) and short-wave infrared (SWIR), as well as long-wave infrared (LWIR) ranges acquired by terrestrial and drone-borne imaging sensors. Vertical outcrops in a quarry in the Freiberg mining district, Saxony (Germany), featuring sulfide-rich hydrothermal zones in a granitoid host, are used to showcase the versatility of our approach. The image data are processed using spectroscopic and machine learning algorithms to generate meaningful 2.5D (i.e., surface) maps that are available to geologists on the ground just shortly after data acquisition. We validate the remote sensing data with thin section analysis and laboratory X-ray diffraction, as well as point spectroscopic data. The combination of ground- and drone-based photogrammetric and hyperspectral VNIR, SWIR, and LWIR imaging allows for safer and more efficient ground surveys, as well as a better, statistically sound sampling strategy for further structural, geochemical, and petrological investigations.