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El 25 de agosto de 1804 un fuerte terremoto sacudió la región del Campo de Dalías (Almería) llegando a sentirse con una intensidad EMS de IX (Mw ~6,4). En este estudio se muestran evidencias que sugieren una relación entre este episodio sísmico y la falla de Llano del Águila. Se trata de una falla normal sub vertical de dirección NW-SE y paralela a la falla de Loma del Viento, situada a unos 3 km al sur. Para la caracterización de la falla de Llano del Águila se ha llevado a cabo una nueva interpretación geomorfológica de los depósitos aluviales cuaternarios que se ven atravesados por la traza de la falla a lo largo del área de estudio. Se han identificado cuatro generaciones de abanicos aluviales provenientes de la Sierra de Gádor, y dos secciones de falla a escala cartográfica (Cantera Este y Rambla de la Maleza). La interpretación geomorfológica se basa en el análisis de fotografías aéreas históricas. Debido a la intensa antropización de la zona, los modelos digitales del terreno actuales no son útiles. Para solventar esta limitación se procesó un modelo digital de elevaciones mediante fotogrametría usando las fotos aéreas del vuelo interministerial (1977). El análisis de escarpes de falla mediante perfiles topográficos medidos en el nuevo modelo de elevaciones proporciona un salto vertical de 6,3 ± 1,9 m para la sección de la Cantera Este y de 12,1 ± 1,9 m para la sección de la Rambla de la Maleza. Estas interpretaciones han sido verificadas en el campo donde además se adquirieron nuevos datos sobre la cinemática de la falla. Todo ello ha permitido estimar la tasa de deslizamiento neta de cada sección: 0,016 ± 0,002 y 0,10 ± 0,02 mm/año para la sección de la Cantera Este y 0,031 ± 0,002 – 0,19 ± 0,.02 mm/año para la Rambla de la Maleza, respectivamente para los últimos 126 y 781 ka (Pleistoceno Medio). A partir de la longitud total de la traza de la falla se puede estimar mediante relaciones empíricas una magnitud máxima potencial de 6,59 ± 0,19.

The facies distribution in time and space of sedimentary successions is controlled by a complex interplay between physical, chemical and biological processes, which are nowadays difficult to construe from the geological record. Numerical models constitute a valuable tool to identify and quantify such controlling factors permitting a reliable 3D extrapolation and prediction of stratigraphic and facies architectures beyond outcropping rock strata. This study assesses the roles of three controlling parameters being carbonate production rate, relative sea-level changes and terrigenous clastic sediment supply, on the evolution of an Aptian carbonate system. The SIMSAFADIM-CLASTIC, a 3D process-based sedimentary-stratigraphic forward model, was used for this evaluation. The carbonate succession modelled crops out in the western Maestrat Basin (E Iberia), and corresponded to a platform-to-basin transition comprising three depositional environment-related facies assemblages: platform top, slope and basin. Testing of geological parameters in forward modelling results in a wide range of possible 3D geological scenarios. The documented distribution of facies and sequence-stratigraphic framework combined with a virtual outcrop model were used as a reference to perform geometric (quantitative) and architectural and stacking pattern (qualitative) research by model-data comparison. The time interval modelled spans 1450 ky. The best-fit simulation run characterizes and quantifies (1) relative sea-level fluctuations recording five different genetic types of deposit (systems tracts) belonging to two depositional sequences as expected from field-data analysis, (2) a rate of terrigenous clastic sediment input ranging between 0.5 and 2.5 gr/s, and (3) a mean autochthonous carbonate production maximum rate of 0.08 m/ky. Furthermore, the quantitative and qualitative sensitivity tests carried out highlight that the fluctuation of relative sea level exerted the main control on the resulting stratigraphic and facies architectures, whereas the effect of inflowing terrigenous clastic sediment is less pronounced. Facies assemblages show different sensitivities to each parameter, being the slope carbonates more sensitive than the platform top facies to inflowing fine terrigenous sediments. On slope depositional settings, siliciclastic input also controls stratal stacking patterns and the dimensions of the carbonate bodies formed. The final 3D model allows to spot architectural features such as stacking patterns that can be misinterpreted by looking at the resulting record in the outcrop or by using other 2D approaches, and facilitates the comprehension of reservoir connectivity highlighting the occurrence of initial disconnected regressive platforms, which were later connected during a transgressive stage.

Rockfall detection is a crucial procedure in the field ofgeology, which helps to reduce the associated risks.Currently, geologists identify rockfall events almostmanually utilizing point cloud and imagery data ob-tained from different caption devices such as TerrestrialLaser Scanner (TLS) or digital cameras. Multitemporalcomparison of the point clouds obtained with thesetechniques requires a tedious visual inspection to iden-tify rockfall events which implies inaccuracies that de-pend on several factors such as human expertize and thesensibility of the sensors. This paper addresses this issueand provides an intelligent framework for rockfall eventdetection for any individual working in the intersectionof the geology domain and decision support systems.The development of such an analysis framework pre-sents major research challenges and justifies exhaustiveexperimental analysis. In particular, we propose an in-telligent system that utilizes multiple machine learningalgorithms to detect rockfall clusters of point cloud data.Due to the extremely imbalanced nature of the problem,aplethoraofstateoftheart resampling techniques ac-companied by multiple models and feature selectionprocedures are being investigated. Various machine learning pipeline combinations have been examinedand benchmarked applying wellknown metrics to beincorporated into our system. Specifically, we developedmachine learning techniques and applied them to ana-lyze point cloud data extracted from TLS in two distinctcase studies, involving different geological contexts: thebasaltic cliff of Castellfollit de la Roca and the con-glomerate Montserrat Massif, both located in Spain. Ourexperimental results indicate that some of the abovementioned machine learning pipelines can be utilized todetect rockfall incidents on mountain walls, with ex-perimentally validated accuracy.

Tight fractured sandstones of the Devonian Huamampampa Formation are associated with large gas discoveries in the sub-Andean fold-and-thrust belt of southern Bolivia. A LIDAR-based fracture characterization of the Abra del Condor backlimb anticline, a structural-stratigraphic analog, is used as the basis for a fracture stratigraphy determination. Fracture characterization using LIDAR is integrated with outcrop scanlines and is framed by stratigraphy and structural positions within this thrust-related anticline. SEFL software was used to process LIDAR data, dividing the outcrop by orientations. A workflow to extract modeled fracture planes and their associated orientations, lengths, and heights results in five fracture sets, partially validated by fracture outcrop scanlines. Multiple virtual scanlines are used to measure fracture intensity, identify fracture stratigraphic units, and define fracture-associated parameters of abundance and size distribution. Our LIDAR-based fracture characterization indicates a distribution of fracture intensities according to their structural position, decreasing from the hinge to the backlimb. From the five fracture sets identified, one set of orthogonal fractures dominates. Moreover, most of the fractures are contained or bounded within their fracture stratigraphic units and calculated fracture spacing ratio and the fracture space index show a nonexistent relation between fracture spacing and the fracture stratigraphic unit thickness.

Digital elevation models (DEM) were generated from oblique stereo-images acquired with a handheld digital camera. Two model scenarios are considered. Firstly, at local outcrop scale, with easy access, and distances between camera and outcrop varying between c. 40 m and c. 120 m, a very dense and high resolution point cloud was produced. The quality of the point cloud was evaluated against a terrestrial laser scan derived model of the same outcrop. The deviation between the two datasets varies between 0.02 m and 0.09. This is negligible for most geological purposes and illustrates the potential of using terrestrial photogrammetry at local outcrop scale as an alternative to lidar generated elevation data. Secondly, the method is explored at a regional scale, where a set of oblique stereo-images of a remotely located steep inaccessible mountain cliff was collected from a helicopter at a distance of c. 2–5 km under challenging and unfavourable conditions. The quality of the point cloud was evaluated a...

Permeability hosted in andesitic lava flows is dominantly controlled by fracture systems, with geometries that are often poorly constrained. This paper explores the fracture system geometry of an andesitic lava flow formed during its emplacement and cooling over gentle paleo-topography, on the active Ruapehu volcano, New Zealand. The fracture system comprises column-forming and platy fractures within the blocky interior of the lava flow, bounded by autobreccias partially observed at the base and top of the outcrop. We use a terrestrial laser scanner (TLS) dataset to extract column-forming fractures directly from the point-cloud shape over an outcrop area of ∼3090 m2. Fracture processing is validated using manual scanlines and high-resolution panoramic photographs. Column-forming fractures are either steeply or gently dipping with no preferred strike orientation. Geometric analysis of fractures derived from the TLS, in combination with virtual scanlines and trace maps, reveals that: (1) steeply dipping column-forming fracture lengths follow a scale-dependent exponential or log-normal distribution rather than a scale-independent power-law; (2) fracture intensities (combining density and size) vary throughout the blocky zone but have similar mean values up and along the lava flow; and (3) the areal fracture intensity is higher in the autobreccia than in the blocky zone. The inter-connected fracture network has a connected porosity of ∼0.5 % that promote fluid flow vertically and laterally within the blocky zone, and is partially connected to the autobreccias. Autobreccias may act either as lateral permeability connections or barriers in reservoirs, depending on burial and alteration history. A discrete fracture network model generated from these geometrical parameters yields a highly connected fracture network, consistent with outcrop observations. peer-reviewed 2019-06-03

The analysis of the three-dimensional rockfall scar geometry provides clues for the understanding of the failure mechanisms acting on cliffs, of the conditioning factors, and on the frequency of the events. In this paper, a supervised step-by-step methodology is presented for establishing the statistical magnitude–frequency relation of rockfall scar volumes, using a point cloud from Terrestrial Laser Scanner (TLS) data. The methodology includes a procedure for identifying discontinuity surfaces, calculating the areas of those which are exposed, and the height of rockfall scars. In the estimation of the rockfall scar volume a key issue is the consideration of the minimum spacing of the discontinuity sets to differentiate between step-path surfaces and undulated ones. Having obtained the distributions of both the basal area and height of the scar across the slope, the volume of the rockfall scars is calculated stochastically by multiplication of these two parameters by means of a Monte Carlo simulation. Both distributions of the basal area and of the rockfall scar volume are found to be power-law, with the exponent b ranging from 0.9 to 1.2. The relation obtained might be used as a first approach of rockfall magnitude–frequency curves in large cliffs.

This case study deals with a rock face monitoring in urban areas using a Terrestrial Laser Scanner. The pilot study area is an almost vertical, fifty meter high cliff, on top of which the village of Castellfollit de la Roca is located. Rockfall activity is currently causing a retreat of the rock face, which may endanger the houses located at its edge. TLS datasets consist of high density 3-D point clouds acquired from five stations, nine times in a time span of 22 months (from March 2006 to January 2008). The change detection, i.e. rockfalls, was performed through a sequential comparison of datasets. Two types of mass movement were detected in the monitoring period: (a) detachment of single basaltic columns, with magnitudes below 1.5 m3 and (b) detachment of groups of columns, with magnitudes of 1.5 to 150 m3. Furthermore, the historical record revealed (c) the occurrence of slab failures with magnitudes higher than 150 m3. Displacements of a likely slab failure were measured, suggesting an apparent stationary stage. Even failures are clearly episodic, our results, together with the study of the historical record, enabled us to estimate a mean detachment of material from 46 to 91.5 m3 year−1. The application of TLS considerably improved our understanding of rockfall phenomena in the study area.

© 2015, Springer-Verlag Berlin Heidelberg. Erosional processes (natural or anthropogenic) may partly destroy the relatively small-sized volcanic edifices characteristic of monogenetic volcanic zones, leaving their internal structure well exposed. Nevertheless, the study of these outcrops may be extremely challenging due to restricted accessibility or safety issues. Digital representations of the outcrop surface have been lately used to overcome such difficulties. Data acquired with terrestrial laser scanning instruments using Light Detection and Ranging technology enables the construction of such digital outcrops. The obtained high-precision 3-D terrain models are of greater coverage and accuracy than conventional methods and, when taken at different times, allow description of geological processes in time and space. Despite its intrinsic advantages and the proven satisfactory results, this technique has been little applied in volcanology-related studies. Here, we want to introduce it to the volcanological community together with a new and user-friendly digital outcrop analysis methodology for inexperienced users. This tool may be useful, not only for volcano monitoring purposes, but also to describe the internal structure of exposed volcanic edifices or to estimate outcrop erosion rates that may be helpful in terms of hazard assessment or preservation of volcanic landscapes. We apply it to the Croscat volcano, a monogenetic cone in the La Garrotxa Volcanic Field (Catalan Volcanic Zone, NE Spain), quarrying of which leads to a perfect view of its interior but restricts access to its uppermost parts. Croscat is additionally one of the most emblematic symbols of the La Garrotxa Volcanic Field Natural Park, and its preservation is a main target of the park administration., AG is grateful for her Juan de la Cierva post-doctoral grant (JCI-2010-06092) and her Ramón y Cajal contract (RYC-2012-11024). SBC acknowledges the JAE-Doc postdoctoral personal grant program of CSIC (JAEDoc_09_01319). This work was partly financed by projects CGL2010-21968-C02-01, CGL2010-18609 and CGL2013-40828-R of the Spanish Ministry of Science and Innovation.