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Major advances in smartphones and tablets in terms of their built-in sensors (esp. cameras), available computational power and on-board memory are transforming the role of such devices into the key digital platform around which geological fieldwork is redesigning itself. This digital transition is changing how geoscientists collect and share multimodal-multidimensional field datasets, which can now be readily distributed via standardized exchange formats and online data repositories. The increased accessibility of digital field datasets means that such data products are no longer the sole preserve of geospatial/geoscience specialists, but also students, stakeholders and the general public alike, providing great opportunities for knowledge transfer over the entirety of the research value chain. In the wake of this digital transition, the geological community has welcomed with enthusiasm and curiosity the introduction during 2020 of a native LiDAR scanner equipped on both the iPad Pro and the iPhone 12 Pro. This scanner offers a potential paradigm shift in digital geological fieldwork and puts these devices at the forefront of smartphone assisted fieldwork. In this work, we review progress in smartphone/tablet assisted geological fieldwork and test the iPhone 12 Pro's effectiveness as a replacement for conventional geological field tools. Specifically, we evaluate the geo-location accuracy of the iPhone's Global Navigation Satellite System (GNSS) receiver, the effectiveness of its inertial measurement unit (IMU) and magnetometer for orientation data collection, its photo-video imaging capabilities, and the performance of the device's newly equipped LiDAR in the field. We demonstrate that the performance of the iPhone for orientation and raster image data capture is high, being comparable to analog compass-clinometers and reflex/mirrorless cameras. Whilst location error is within the order of a few meters, the level of accuracy and the fast stabilization of the signal means that, beyond survey grade applications, the iPhone's geo-location capabilities are acceptable for most field cases. With regards to the iPhone's built-in LiDAR scanner, it is an excellent tool for depth assisted camera focusing and for casual 3D outcrop sharing, especially for ‘soft’ applications such as geo-heritage documentation and the production of teaching materials (here we also propose a simple mode of uploading outcrops models in Google Maps). However, the generated 3D models in some cases may be considered overly crude for detailed interrogation, particularly where the fidelity of the surface reconstruction is critical to the analysis (e.g. mesh facet orientation estimation). Based on our review of the evolution of digital field acquisition technologies and on our extensive field testing of the sensor suite integrated within the iPhone 12 Pro, it is clear that the digital transition of geological fieldwork is already mature, whereby smartphone devices have become as indispensable in the field as the geologists' traditional hammer and hand lens.

Since the advent of affordable consumer-grade cameras over a century ago, photographic images have been the standard medium for capturing and visualizing outcrop-scale geological features. Despite the ubiquity of raster image data capture in routine fieldwork, the development of close-range 3D remote-sensing techniques has led to a paradigm shift in the representation and analysis of rock exposures from two- to three-dimensional forms. The use of geological 3D surface reconstructions in routine fieldwork has, however, been limited by the portability, associated learning curve, and/ or expense of tools required for data capture, visualization, and analysis. Smartphones are rapidly becoming a viable alternative to conventional 3D close-range remote-sensing data capture and visualization platforms, providing a catalyst for the general uptake of 3D outcrop technologies by the geological community, which were up until relatively recently the purview of a relatively small number of geospatial specialists. Indeed, the continuous improvement of smartphone cameras, coupled with their integration with global navigation satellite system (GNSS) and inertial sensors provides 3D reconstructions with comparable accuracy to survey-grade systems. These developments have already led many field geologists to replace reflex cameras, as well as dedicated handheld GNSS receivers and compass clinometers, with smartphones, which offer the equivalent functionality within a single compact platform. Here we demonstrate that through the use of a smartphone and a portable gimbal stabilizer, we can readily generate and register high-quality 3D scans of outcropping geological structures, with the workflow exemplified using a mirror of a seismically active fault. The scan is conducted with minimal effort over the course of a few minutes with limited equipment, thus being representative of a routine situation for a field geologist.

Geotagged smartphone photos can be employed to build digital terrain models using structure from motion-multiview stereo (SfM-MVS) photogrammetry. Accelerometer, magnetometer, and gyroscope sensors integrated within consumer-grade smartphones can be used to record the orientation of images, which can be combined with location information provided by inbuilt global navigation satellite system (GNSS) sensors to geo-register the SfM-MVS model. The accuracy of these sensors is, however, highly variable. In this work, we use a 200 m-wide natural rocky cliff as a test case to evaluate the impact of consumer-grade smartphone GNSS sensor accuracy on the registration of SfM-MVS models. We built a high-resolution 3D model of the cliff, using an unmanned aerial vehicle (UAV) for image acquisition and ground control points (GCPs) located using a differential GNSS survey for georeferencing. This 3D model provides the benchmark against which terrestrial SfM-MVS photogrammetry models, built using smartphone images and registered using built-in accelerometer/gyroscope and GNSS sensors, are compared. Results show that satisfactory post-processing registrations of the smartphone models can be attained, requiring: (1) wide acquisition areas (scaling with GNSS error) and (2) the progressive removal of misaligned images, via an iterative process of model building and error estimation.

In this work, the application of consumer-grade virtual reality (VR) hardware and software to the analysis of digital outcrop data is explored. Here, we utilize a widely available VR hardware platform (HTC Vive) and VR based freeform 3D visual arts software package (Google Tilt Brush), to digitize fault traces from photo-textured digital outcrop models of exposures of the Penrith Sandstone Formation (Lacy's Caves), in northwest England. Using MATLAB routines provided herein, triangular meshes output from Tilt Brush are used as the basis for 3D fracture trace map extraction, which in turn, are used to generate fracture properties (trace length, orientation, areal fracture intensity). We compare the results of this analysis to two equivalent datasets obtained from the Lacy's Caves model using digital outcrop analysis deployed via a conventional flat panel display: namely (1) a 3D trace map extracted using optical ray tracing from manually interpreted calibrated images and (2) 3D traces fitted directly the Lacy's Caves textured mesh using manual polyline interpretation within an established digital outcrop analysis software platform (OpenPlot). Fault statistics obtained using VR based analysis are broadly equivalent to those acquired from 3D trace maps extracted using the flat panel display deployed analyses presented herein. In this case study, it was found that VR based digital outcrop analysis provided faster data acquisition than the comparative pixel-based approach, which requires linkage and merging of traces mapped from multiple contiguous images. Manual raster analysis and optical ray tracing did however provide 3D trace maps with significantly higher areal fault intensity, with VR analysis incurring censoring of finer fault traces, due to the limited resolution of the outcrop model textured mesh. Whilst data acquisition times and resultant fault intensities proved similar between the VR and OpenPlot workflows, it was noted anecdotally, that the VR analysis holds some advantages for the operator when interpreting models exhibiting complex geometries, such as mine workings and caves systems, with the clip point implemented within the viewport of conventional digital outcrop analysis software tools obstructing the user from obtaining an optimum view of the outcrop surface. VR based digital outcrop analysis techniques, such as those presented here, provide an immersive analytical environment to the operator. This allows users to fuse powerful 3D visualizations of photo-realistic outcrop models with geological interpretation and data collection, fulfilling the early promise of ‘virtual outcrops’ as an analytical medium that can emulate traditional fieldwork. It is hoped that this study and its associated code library will facilitate the evaluation of emerging VR technologies for digital outcrop applications, by provided access to VR analytical tools for non-specialists in virtual reality systems. Finally, prospects for the use of VR technology within the field of digital outcrop geology, as well as within the wider geosciences, are also discussed.

Smartphones can be regarded as cameras, natively equipped with geolocation and orientation sensors, making them powerful, portable, user-friendly and inexpensive tools for terrestrial structure from motion/multiview stereo photogrammetry (SfM-MVS) surveys. Camera extrinsic parameters (i.e. camera position and orientation), required to produce fully georeferenced SfM-MVS 3D models are available for the majority of smartphone images via inbuilt magnetometer, accelerometer/gyroscope, and global navigation satellite system (GNSS) sensors. The precision of these internal sensors is not yet sufficient to directly use them as input to SfM-MVS photogrammetric reconstructions. However, when the reconstructed scene is significantly greater than the positional error, camera extrinsic parameters can be successfully used to register 3D models during post-processing. We present a survey of a 400 m wide vertical cliff to illustrate a workflow that enables the use of smartphone cameras to generate and fully georeference photogrammetric models without employing ground control points. Survey images were acquired at a distance of ~350 m to the mapped scene using a consumer-grade smartphone. This survey image dataset was subsequently used to build an unreferenced 3D model, which was registered during post-processing using orientation and position metadata tagged to each photograph.

Fault roughness constitutes a key element in the understanding of earthquake nucleation, and surficial asperities on the fault plane play a critical role in slip dynamics and frictional behavior during the seismic cycle. Since it is not generally feasible to recover fault roughness profiles or maps directly at the seismogenic sources, faults at the Earth’s surface are typically used as analogues. However, these analogue fault surfaces are often subjected to weathering and erosion, which in turn, reduces their representativeness as seismogenic faults. Rupture along active faults episodically exposes “fresh” fault planes at the Earth’s surface, which represent the best available targets for the evaluation of fault roughness generated at seismogenic depths.Here we present a study conducted on a splay of the Mt. Vettore fault system in the Central Apennines, Italy, along a vertical transect that includes both a weathered and freshly exposed portion of the fault. The latter was exposed after the dramatic Mw 6.5 shock that hit the area on 30 October 2016. We have produced a highly detailed model (i.e., point cloud) of a section of the fault using structure from motion-multiview stereo photogrammetry to assess its roughness parameters (i.e., the Hurst fractal parameter) and to determine the extent to which these parameters are affected by weathering assuming that they had similar fractal characteristics when reaching the surface.Our results show that weathering can modify the value of the fractal parameters. In particular, by independently analyzing different patches of the fault, we have observed that the smoother and recently exposed portions have an average Hurst exponent of 0.52 while the average Hurst exponent of zones with more prolonged exposure times is 0.64. Accordingly, we conclude that by using high-resolution point clouds, it is possible to recognize patches of faults having a similar intensity of deterioration attributable to weathering.

Joint systems in the eastern portion of the Ebro Basin of the eastern Pyrenees enjoy near continuous exposure from the frontal portion of the belt up to the external portion of its associated foredeep. Utilizing orthophoto mosaics of these world-class exposures, we have manually digitized over 30 000 joints within a 16 km×50 km study area. The mapped traces exhibit orientations that are dominantly perpendicular to the trend of the belt (transverse) and, subordinately, parallel to the belt (longitudinal). In particular, joints systematically orient perpendicular to the trend of the belt both in the frontal folds and in the inner and central portion of the foredeep basin. Longitudinal joints occur rarely with a disordered spatial distribution, exhibiting null difference in abundance between the belt and the foredeep. Joint orientations in the external portion of the foredeep become less clustered, with adjacent areas dominated by either transverse or oblique joints. Our data indicate that joints in the studied area formed in the foredeep in response to a foredeep-parallel stretching, which becomes progressively less intense within the external portion of the foredeep. There, the minimum stress direction becomes more variable, providing evidence of the poor contribution of the forebulge-perpendicular stretching on stress organization.

The application of structure from motion–multiview stereo (SfM-MVS) photogrammetry to map metric- to hectometric-scale exposures facilitates the production of three-dimensional (3-D) surface reconstructions with centimeter resolution and range error. In order to be useful for geospatial data interrogation, models must be correctly located, scaled, and oriented, which typically requires the geolocation of manually positioned ground control points with survey-grade accuracy. The cost and operational complexity of portable tools capable of achieving such positional accuracy and precision is a major obstacle in the routine deployment of SfM-MVS photogrammetry in many fields, including geological fieldwork. Here, we propose a procedure to overcome this limitation and to produce satisfactorily oriented models, which involves the use of photo orientation information recorded by smartphones. Photos captured with smartphones are used to: (1) build test models for evaluating the accuracy of the method, and (2) build smartphone-derived models of outcrops, used to reference higher-resolution models reconstructed from image data collected using digital single-lens reflex (DSLR) and mirrorless cameras. Our results are encouraging and indicate that the proposed workflow can produce registrations with high relative accuracies using consumer-grade smartphones. We also find that comparison between measured and estimated photo orientation can be successfully used to detect errors and distortions within the 3-D models.

Along convergent plate boundaries, the negative buoyancy of the lithosphere pulls the slab into subduction. Bending and offscraping of the downgoing plate are processes occurring at subduction zones and acting against plate motions. These localised dissipative processes cause extensional deformation in the bulge-foredeep region and thrusting and folding in the thrust wedge respectively. Within this framework, widespread early subduction-related extensional structures affecting pre-orogenic rocks of the downgoing plate of fossil subduction systems, are commonly interpreted as induced by extension occurring in the forebulge-foredeep zone. Slab pull is to date, rarely considered as a potential causative process when interpreting basin-scale pre-shortening extensional structures. The problem of distinguishing slab-pull and foreland flexuring induced extensional structures relates to the fact that for most belts, slab pull and forebulge-foredeep flexuring are expected to produce extension roughly in the same direction (i.e. parallel to the foredeep-belt system) and, when syn-kinematic strata are not available, discriminating between these two processes is arduous. In this work we present a field investigation of basin-scale extensional faults from the downgoing plate of the Oman Mts. fossil subduction system. Syn-kinematic strata indicate that normal fault development largely predated extension in the bulge-foredeep region. Herein, we argue that such faulting occurred during the transition from induced to self-sustained subduction, when the negative buoyancy of the slab started to exceed the resisting forces and the downgoing plate began to be pulled towards the trench. © 2019 Elsevier Ltd