scholarly journals Intact rock bridge breakage and rock mass fragmentation upon failure: quantification using remote sensing techniques

2017 ◽  
Vol 32 (160) ◽  
pp. 513-536 ◽  
Author(s):  
Margherita C. Spreafico ◽  
Francesca Franci ◽  
Gabriele Bitelli ◽  
Lisa Borgatti ◽  
Monica Ghirotti
Keyword(s):  
Remote Sensing ◽  
Rock Mass ◽  
Intact Rock ◽  
Rock Bridge ◽  
Mass Fragmentation ◽  
Remote Sensing Techniques

scholarly journals The Impact of Fracture Persistence and Intact Rock Bridge Failure on the In Situ Block Area Distribution

2021 ◽  
Vol 11 (9) ◽  
pp. 3973
Author(s):  
Thomas Strauhal ◽  
Christian Zangerl
Keyword(s):  
Rock Mass ◽  
Size Distribution ◽  
Block Size ◽  
Intact Rock ◽  
Rock Bridge ◽  
Block Area ◽  
The Mean ◽  
Bridge Failure ◽  
Block Size Distribution

The in situ block size distribution is an essential characteristic of fractured rock masses and impacts the assessment of rockfall hazards and other fields of rock mechanics. The block size distribution can be estimated rather easily for fully persistent fractures, but it is a challenge to determine this parameter when non-persistent fractures in a rock mass should be considered. In many approaches, the block size distribution is estimated by assuming that the fractures are fully persistent, resulting in an underestimation of the block sizes for many fracture geometries. In addition, the block size distribution is influenced by intact rock bridge failure, especially in rock masses with non-persistent fractures, either in a short-term perspective during a slope failure event when the rock mass increasingly disintegrates or in a long-term view when the rock mass progressively weakens. The quantification of intact rock bridge failure in a rock mass is highly complex, comprising fracture coalescence and crack growth driven by time-dependent changes of the in situ stresses due to thermal, freezing-thawing, and pore water pressure fluctuations. This contribution presents stochastic analyses of the two-dimensional in situ block area distribution and the mean block area of non-persistent fracture networks. The applied 2D discrete fracture network approach takes into account the potential failure of intact rock bridges based on a pre-defined threshold length and relies on input parameters that can be easily measured in the field by classical discontinuity mapping methods (e.g., scanline mapping). In addition, on the basis of these discrete fracture network analyses, an empirical relationship was determined between (i) the mean block area for persistent fractures, (ii) the mean block area for non-persistent fractures, and (iii) the mean interconnectivity factor. The further adaptation of this 2D approach to 3D block geometries is discussed on the basis of general considerations. The calculations carried out in this contribution highlight the large impact of non-persistent fractures and intact rock bridge failure for rock mass characterization, e.g., rockfall assessment.

scholarly journals Comparison of Remote Sensing Techniques for Geostructural Analysis and Cliff Monitoring in Coastal Areas of High Tourist Attraction: The Case Study of Polignano a Mare (Southern Italy)

2021 ◽  
Vol 13 (24) ◽  
pp. 5045
Author(s):  
Lidia Loiotine ◽  
Gioacchino Francesco Andriani ◽  
Michel Jaboyedoff ◽  
Mario Parise ◽  
Marc-Henri Derron
Keyword(s):  
Remote Sensing ◽  
Rock Mass ◽  
Urban Areas ◽  
Laser Scanning ◽  
Rock Slope ◽  
Mitigation Measures ◽  
Tourist Attraction ◽  
Field Surveys ◽  
Rock Mass Characterization ◽  
Remote Sensing Techniques

Rock slope failures in urban areas may represent a serious hazard for human life, as well as private and public property, even on the occasion of sporadic episodes. Prevention and mitigation measures indispensably require a proper rock mass characterization, which is often achieved by means of time-consuming, costly and dangerous field surveys. In the last decades, remote sensing devices such as high-resolution digital cameras, laser scanners and drones have been widely used as supplementary techniques for rock slope analysis and monitoring, especially in poorly accessible areas, or in sites of large extension. Although several methods for rock mass characterization by means of remote sensing techniques have been reported in specific studies, there are very few contributions that focused on comparing the different methods in an attempt to establish their advantages and limitations. With this study, we performed digital photogrammetry, Terrestrial Laser Scanning and Unmanned Aerial Vehicle surveys on a cliff located in a popular tourist attraction site, characterized by complex geological and geomorphological settings, as well as by disturbance elements such as vegetation and human activities. For each point cloud, we applied geostructural analysis by means of semi-automatic methods, and then compared multi-temporal acquisitions for cliff monitoring. By quantitative comparison of the results and validation by means of conventional geostructural field surveys, the pros and cons of each method were outlined in attempt to depict the conditions and goals the different techniques seem to be more suitable for.

Geomechanical characterization of rock masses by means of remote sensing techniques

2020 ◽  
Author(s):  
Lidia Loiotine ◽  
Marco La Salandra ◽  
Gioacchino Francesco Andriani ◽  
Giovanni Barracane ◽  
Marc-Henri Derron ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Rock Mass ◽  
Point Cloud ◽  
Laser Scanning ◽  
Mitigation Measures ◽  
Rock Masses ◽  
Testing Procedures ◽  
Remote Sensing Techniques

<p>Improving the methods for the characterization of rock masses by integrating traditional field surveys with remote sensing techniques is fundamental for practical and realistic discontinuous modelling, in order to identify the failures and kinematics, develop landslide susceptibility assessment and plan prevention and mitigation measures.</p><p>A 20 m-high cliff at Polignano a Mare (Southern Italy) was selected as case study for the presence of well-developed discontinuities (bedding and joints) and due to the local morphology, consisting of a valley with opposite slopes at a distance of 150 m, and a pocket beach at their toe. This configuration allowed to perform both traditional and remote sensing surveys. First, photogrammetry methods were carried out on the ground and with the help of a boat. Structure from Motion (SfM) technique was then used to process and combine the pictures, in order to elaborate a raw point cloud of the case study. Secondly, high resolution Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle (UAV) techniques were conducted after positioning Ground Control Points (GCPs) all over the rock mass, with the aim of obtaining a more detailed point cloud. Eventually, a unique and optimized georeferenced point cloud was obtained by combining the previous models, also removing the non-geological objects. Furthermore, Infrared Thermography (IT) was carried out in order to investigate the fracture pattern, the areas of concentrated stress, and the presence of humidity and voids.</p><p>The structural analysis of the rock mass was performed directly on the point cloud, by testing procedures and algorithms for the automatic identification of discontinuity sets and of their orientation, spacing, persistence and roughness.</p><p>The next step of this research will concern the evaluation of the instability mechanisms with the help of kinematic analyses, by means of stereographic projections. Finally, the reliability of the procedure for a complete rock mass characterization, which is expected to be obtained as the final result, will be tested by means of numerical stability solutions, after calibrating the geomechanical model and importing the fracture system in an appropriate software.</p><p> </p>

Bibliography of Remote Sensing Techniques Used in Wetland Research

1993 ◽  
Author(s):  
Janet L. Lampman
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Techniques

scholarly journals Análisis del efecto de variables ambientales en la estimación de la erosionabilidad (Factor K) = Analysis of the Effect of Environmental Variables on the Soil Erodibility Estimation (K Factor)

2018 ◽  
pp. 195
Author(s):  
Pedro Perez Cutillas ◽  
Gonzalo G. Barberá ◽  
Carmelo Conesa García
Keyword(s):  
Remote Sensing ◽  
Environmental Variables ◽  
Input Data ◽  
Vegetation Index ◽  
Mineralogical Composition ◽  
Soil Erodibility ◽  
Estimation Algorithms ◽  
K Factor ◽  
Remote Sensing Techniques

El objetivo principal de este trabajo se centra en la determinación y análisis de las variables ambientales que influyen en las divergencias de las estimaciones de erosionabilidad a partir de dos métodos, aplicando tres algoritmos de estimación del Factor K. La exploración de esta información permite conocer el peso que ejerce el origen de los datos de entrada a los modelos en el cómputo de erosionabilidad y qué importancia tiene en función del algoritmo elegido para la estimación del Factor K. Los resultados muestran que las pendientes, así como los índices de vegetación (NDVI) y de composición mineralógico (IOI) obtenidos mediantes técnicas de teledetección han   mostrado los valores de asociación más elevados entre ambos métodos.The main goal of this work is to determine and analyze the influence of environmental variables on the changes of two erodibility methods, through the application of three estimation algorithms of K Factor. The analysis of this information allows knowing the significance of the input data to the models in the erodibility estimation, and likewise the consequence of the algorithm selected for the estimation of K Factor. The results show that the slopes, as well as the vegetation index (NDVI) and the mineralogical composition index (IOI), generated both by remote sensing techniques, have shown the highest values of association between methods.

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