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Finding new ways to quantify discontinuity persistence values in rock masses in an automatic or semi-automatic manner is a considerable challenge, as an alternative to the use of traditional methods based on measuring patches or traces with tapes. Remote sensing techniques potentially provide new ways of analysing visible data from the rock mass. This work presents a methodology for the automatic mapping of discontinuity persistence on rock masses, using 3D point clouds. The method proposed herein starts by clustering points that belong to patches of a given discontinuity. Coplanar clusters are then merged into a single group of points. Persistence is measured in the directions of the dip and strike for each coplanar set of points, resulting in the extraction of the length of the maximum chord and the area of the convex hull. The proposed approach is implemented in a graphic interface with open source software. Three case studies are utilized to illustrate the methodology: (1) small-scale laboratory setup consisting of a regular distribution of cubes with similar dimensions, (2) more complex geometry consisting of a real rock mass surface in an excavated cavern and (3) slope with persistent sub-vertical discontinuities. Results presented good agreement with field measurements, validating the methodology. Complexities and difficulties related to the method (e.g., natural discontinuity waviness) are reported and discussed. An assessment on the applicability of the method to the 3D point cloud is also presented. Utilization of remote sensing data for a more objective characterization of the persistence of planar discontinuities affecting rock masses is highlighted herein. [ABSTRACT FROM AUTHOR]

Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work. [ABSTRACT FROM AUTHOR]

Rock mass classification systems are widely used tools for assessing the stability of rock slopes. Their calculation requires the prior quantification of several parameters during conventional fieldwork campaigns, such as the orientation of the discontinuity sets, the main properties of the existing discontinuities and the geo-mechanical characterization of the intact rock mass, which can be time-consuming and an often risky task. Conversely, the use of relatively new remote sensing data for modelling the rock mass surface by means of 3D point clouds is changing the current investigation strategies in different rock slope engineering applications. In this paper, the main practical issues affecting the application of Slope Mass Rating (SMR) for the characterization of rock slopes from 3D point clouds are reviewed, using three case studies from an end-user point of view. To this end, the SMR adjustment factors, which were calculated from different sources of information and processes, using the different softwares, are compared with those calculated using conventional fieldwork data. In the presented analysis, special attention is paid to the differences between the SMR indexes derived from the 3D point cloud and conventional field work approaches, the main factors that determine the quality of the data and some recognized practical issues. Finally, the reliability of Slope Mass Rating for the characterization of rocky slopes is highlighted. [ABSTRACT FROM AUTHOR]

The integration of data from different sources can be very helpful in understanding the mechanism, the geometry, the kinematic, and the area affected by complex instabilities, especially when the available geotechnical information is limited. In this work, the suitability of different techniques for the study of a deep-seated landslide affecting a bridge in Alcoy (Spain) is evaluated. This infrastructure presents such severe damage that has rendered the bridge unusable, which prevents normal access to an important industrial area. Differential SAR Interferometry (DInSAR) and terrestrial Light Detection and Ranging (LiDAR) remote sensing techniques have been combined with ground displacement monitoring techniques, such as inclinometers and conventional geological and geotechnical investigation, electrical-seismic tomography, damage, and topographic surveys, to determine the boundaries, mechanism, and kinematics of the landslide. The successful case study that is illustrated in this work highlights the potential and the need for integrating multi-source data for the optimal management of complex landslides and the effective design of remedial measurements. [ABSTRACT FROM AUTHOR]

It is not the aim of this work to include all rocks, as reference books on petrography mention over one thousand types of rocks (Goodman [5]), but to upload some main rocks classified in an accepted classification system. Rock-mechanic subjects aim to analyse the behaviour of rocks and rock masses. MC described part of the rock specimens, wrote and revised the manuscript along with the website and created the behavioural datasheet and collected most of the mechanical values of the rock samples. [Extracted from the article]

Abstract Technological progress in remote sensing has enabled digital representation of terrain through new techniques (e.g. digital photogrammetry) and instruments (e.g. 3D laser scanners). However, the use of old aerial images remains important in geosciences to reconstruct past landforms and detect long-term topographic changes. Administrations have recently expressed growing interest in sharing photogrammetric datasets on public repositories, providing opportunities to exploit these resources and detect natural and anthropogenic topographic changes. The SfM-MVS photogrammetric technique was applied to scanned historical black and white aerial photos of the Serra de Fontcalent (Alicante, Spain), as well as to recent high-quality digital aerial photos. Ground control points (GCPs) extracted from a LiDAR-derived three-dimensional point cloud were used to georeference the results with non-linear deformations. Two point clouds obtained with SfM-MVS were compared with the LiDAR-derived reference point cloud. Based on the result, the quality of the models was analysed through the comparison of the stages on stable areas, i.e., lands where no variations were detected, and active areas, with quarries, new infrastructures, fillings, excavations or new buildings. This study also indicates that errors are higher for old aerial photos (up to 5 m on average) than recent digital photos (up to 0.5 m). The application of SfM-MVS to open access data generated 3D models that enhance the geomorphological analysis, compared to stereophotogrammetry, and effectively detected activities in quarries and building of landfills. Highlights • Existing techniques enable the use of historical and recent aerial photos to reconstruct DEMS • An area of interest is reconstructed using historical printed and digital aerial photos, obtained from readily available resources, through Structure-from-Motion • An airbone LiDAR derived point cloud was used as a benchmark and for the extraction of ground control points • Three different stages of the landform were analysed and compared • The quality of the reconstruction and the capability of monitoring changes were analysed [ABSTRACT FROM AUTHOR]

The Ms 7.0 Jiuzhaigou earthquake that occurred on 8 August 2017 triggered hundreds of landslides in the Jiuzhaigou valley scenic and historic-interest area in Sichuan, China, causing heavy casualties and serious property losses. Quick and accurate mapping of post-disaster landslide distribution is of paramount importance for earthquake emergency rescue and the analysis of post-seismic landslides distribution characteristics. The automatic identification of landslides is mostly based on medium- and low-resolution satellite-borne optical remote-sensing imageries, and the high-accuracy interpretation of earthquake-triggered landslides still relies on time-consuming manual interpretation. This paper describes a methodology based on the use of 1 m high-resolution unmanned aerial vehicle (UAV) imagery acquired after the earthquake, and proposes a support vector machine (SVM) classification method combining the roads and villages mask from pre-seismic remote sensing imagery to accurately and automatically map the landslide inventory. Compared with the results of manual visual interpretation, the automatic recognition accuracy could reach 99.89%, and the Kappa coefficient was higher than 0.9, suggesting that the proposed method and 1 m high-resolution UAV imagery greatly improved the mapping accuracy of the landslide area. We also analyzed the spatial-distribution characteristics of earthquake-triggered landslides with the influenced factors of altitude, slope gradient, slope aspect, and the nearest faults, which provided important support for the further study of post-disaster landslide distribution characteristics, susceptibility prediction, and risk assessment. [ABSTRACT FROM AUTHOR]

The complex landslide of Agnone, located in Molise Region (southern Italy), is a large deep-seated roto-translational slide, involving terrigenous flysch sequences and evolving in the lower portion, in an earth flow. First evidences of landslide activities date back to early 1900s and keep on moving in several time spans up to nowadays. This work illustrates the contribution of multiple optical and radar remote sensing data to landslide investigation approximately across a century as well as to mapping and monitoring ground displacements at the catchment scale.In particular, we firstly revised information from scientific literature and technical reports, compiling monitoring data acquired through inclinometers and geo-morphological surveys in preceding studies to characterize the geological setting of the area. Additionally, we used GPS data acquired from 2010 to 2015 to monitor ground surface motions on some benchmarks of the area. Then, we exploited remotely-sensed data in order to in-depth investigate the spatial and temporal evolution of the landslide-affected catchment.The use of historical air-photos enabled the generation of 3D models by means of the Structure for Motion (SfM) technique to detect, map and monitor unique geomorphological landscapes across several decades. Historical and recent sets of optical photographs from 1945 to 2003 were used in the study area to perform 3D reconstructions and analyze the geomorphological enlargement of the Agnone landslide over 60 years. Radar satellite images acquired by ERS1/2 and ENVISAT constellations at medium spatial resolution, in the spanning time 1992-2010, and by COSMO-SkyMed at high resolution, covering the period 2012-2015, were processed through Persistent Scatterer Interferometry (PSI) techniques. The derived PSI data provided yearly velocities and time series of ground deformation with millimetric accuracy and were exploited for back-monitoring slow surface displacements and for better tracing the boundaries of the mass movement. All data were discussed and used to increase the knowledge about the ground motions affecting the whole Agnone landslide and the surrounding territory. Remotely-sensed data were also compared through in situ field checks to evaluate landslide-induced damage on structures and infrastructures within and close to the landslide body. Outcomes of these analyses demonstrated the operative usefulness of the combination of multi-temporal and multi-technique conventional and remote sensing data for the assessment of spatial and temporal evolution of landslides at basin scale. Moreover, the collected data allowed to plan countermeasures and mitigation actions on the Agnone area according to the distribution and intensity of the detected landslide hazard. [ABSTRACT FROM AUTHOR]