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.

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.

Magmatic activity in continental arcs is known to vary in a non-steady-state manner, with the mechanisms driving magmatic activity being a matter of ongoing discussion. Of particular importance is the question of what extent episodic magmatism in continental arcs is governed by external factors (e.g., plate motions) and internal factors (e.g., feedback processes in the upper plate). To test existing models for magmatic episodicity, which are mostly based on temporally and spatially limited records, this study uses large data sets of geochronological, geochemical, and plate kinematic data to document the Paleozoic to Mesozoic development of the North and South American Cordilleras in eight transects from British Columbia to Patagonia. The temporal distribution of U/Pb bedrock and detrital zircon ages, used as a proxy for timing of magmatic accretion, shows that some minima and maxima of zircon abundance are nearly synchronous for thousands of kilometers along the arc. Some age patterns are characterized by a periodicity of 50–80 Ma, suggesting a cyclic controlling mechanism. Other magmatic lulls or flare-ups find no equivalents in adjacent sectors, indicating that either discrete events or variable lag times may also be important in governing magmatic activity in continental arcs. Magma composition in Mexico, the Peninsular Ranges, and the Sierra Nevada varies episodically and proportionally with the temporal record of arc activity. During flare-up events, there is an increase in Sm/Yb, indicating deeper melting, and a decrease in εNd_i, suggesting a higher degree of crustal assimilation. Geochemical scatter also increases during the initiation of flare-up events. Plate kinematic data provide a means of evaluating mantle heat input. The correlation between plate convergence rate and magmatic accretion varies for each sector, suggesting that different flare-ups or lulls likely reflect variable combinations of processes.

Recently, ground-based hyperspectral imaging has come to the fore, supporting the arduous task of mapping near-vertical, difficult-to-access geological outcrops. The application of outcrop sensing within a range of one to several hundred metres, including geometric corrections and integration with accurate terrestrial laser scanning models, is already developing rapidly. However, there are few studies dealing with ground-based imaging of distant targets (i.e., in the range of several kilometres) such as mountain ridges, cliffs, and pit walls. In particular, the extreme influence of atmospheric effects and topography-induced illumination differences have remained an unmet challenge on the spectral data. These effects cannot be corrected by means of common correction tools for nadir satellite or airborne data. Thus, this article presents an adapted workflow to overcome the challenges of long-range outcrop sensing, including straightforward atmospheric and topographic corrections. Using two datasets with different characteristics, we demonstrate the application of the workflow and highlight the importance of the presented corrections for a reliable geological interpretation. The achieved spectral mapping products are integrated with 3D photogrammetric data to create large-scale now-called “hyperclouds”, i.e., geometrically correct representations of the hyperspectral datacube. The presented workflow opens up a new range of application possibilities of hyperspectral imagery by significantly enlarging the scale of ground-based measurements.