A stability investigation based on Digital Outcrop Models (DOMs) acquired in emergency conditions by photogrammetric surveys based on Remote Piloted Aerial System (RPAS) was conducted on an unstable rock slope near Gallivaggio (Western Alps, Italy). The predicted mechanism of failure and volume of the unstable portion of the slope were successively verified on the DOMs acquired after the rockfall that effectively collapsed the May 29th, 2018. The comparison of the pre- and post-landslide 3D models shows that the estimated mode of failure was substantially correct. At the same time, the predicted volume of rock involved in the landslide was overestimated by around 10%. To verify if this error was due to the limited accuracy of the models georeferenced in emergency considering only the Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU)-information of RPAS, several Ground Control Points (GCPs) were acquired after the failure. The analyses indicate that the instrumental error in the volume calculation due to the direct-georeferencing method is only of the 1.7%. In contrast, the significant part is due to the geological uncertainty in the reconstruction of the real irregular geometry of the invisible part of the failure surface. The results, however, confirm the satisfying relative accuracy of the direct-georeferenced DOMs, compatible with most geological and geoengineering purposes.

While uncrewed aerial vehicles are routinely used as platforms for hyperspectral sensors, their application is mostly confined to nadir imaging orientations. Oblique hyperspectral imaging has been impeded by the absence of robust registration and correction protocols, which are essential to extract accurate information. These corrections are especially important for detecting the typically small spectral features produced by minerals, and for infrared data acquired using pushbroom sensors. The complex movements of unstable platforms (such as UAVs) require rigorous geometric and radiometric corrections, especially in the rugged terrain often encountered for geological applications. In this contribution we propose a novel correction methodology, and associated toolbox, dedicated to the accurate production of hyperspectral data acquired by UAVs, without any restriction concerning view angles or target geometry. We make these codes freely available to the community, and thus hope to trigger an increasing usage of hyperspectral data in Earth sciences, and demonstrate them with the production of, to our knowledge, the first fully corrected oblique SWIR drone-survey. This covers a vertical cliff in the Dolomites (Italy), and allowed us to distinguish distinct calcitic and dolomitic carbonate units, map the qualitative abundance of clay/mica minerals, and thus characterise seismic scale facies architecture.

Carbon capture and storage (CCS) has the potential to help nations meet their Paris Agreement CO ₂ reduction commitments ^1,2 . The ability to capture CO ₂ within mafic and ultramafic rocks through mineralization of carbon is an example of such a CCS technology ^3,4 , but large-scale deployment has yet to be achieved ^5,6 . Each geologic environment in the Earth’s crust requires a distinct carbon storage solution. Whereas some regions of the subsurface contain saline aquifers and sedimentary traps suitable for traditional carbon storage through the injection of high-pressure, dense CO ₂ below impermeable caprocks, other regions may lack caprocks ^5–9 . In these regions, carbon storage is possible through the mineralization of injected water-dissolved CO ₂ forming stable carbonate minerals through its reactions with reactive silicate rocks and minerals ^6,10,11 . A notable challenge to applying this process at scale is that it can require 20–50 times or more water than the mass of CO ₂ stored ¹² . Here we report on an industrial-scale pilot project designed to find a carbon disposal solution for western Saudi Arabia. This arid region has large point-source CO ₂ emitters, including petroleum refining and desalination facilities, but lacks saline aquifers and sedimentary traps ^13–17 . We find that a CO ₂ injection approach based on the recirculation of subsurface fluids can eliminate the need for external water. Our results demonstrate the feasibility of carbon mineral storage in regions in which access to water resources may be limited.

The Markland test is one of the most diffused and adopted methods of kinematic analysis for the identification of critical intersections of rock discontinuities that could generate rock failures. Traditionally, the kinematic analysis is based on the use of a stereographic approach that is able to identify the critical combination between the orientations of discontinuities and the rock wall. The recent improvements in the use of Digital Outcrop Models (DOMs) created the conditions for the development of a new automatized approach. We present ROck Slope Kinematic Analysis (ROKA) which is an open-source algorithm aimed at performing the Kinematic Analysis using the discontinuity measures collected onto a 3D DOM. The presented algorithm is able to make a local identification of the possible critical combination between the identified discontinuities and the orientation of the slope. Using this approach, the algorithm is able to identify on the slope the presence of critical combinations according to the traditional kinematic analysis of planar failure, flexural toppling, wedge failure, and direct toppling modes of failures and then visualize them on DOMs. In this way, the traditional approach is more effective and can be adopted for a more detailed analysis of large and complex areas.