The use of UAVs in engineering geological surveys : mapping along Scotland's south-west coast

UAVs have been used in engineering for at least two decades. While there is a wide range of recognition algorithms for the automatic identification of structural damage, structural geological features etc. from the acquired images, the parameters affecting the resolution of these images are often overlooked. As a result, the potential of the UAV technology is not maximized and at times, it is even regarded as leading to poor outcomes. We present a case study of the structural geological mapping of a coastal area in Scotland carried out using two types of UAVs: a fixed wing and a hexacopter. We compare the structural geological maps obtained from the orthophotos and conventional techniques and find that although the level of detail is the same, the time spent in producing a map is at least 5 times less when using a UAV. The fixed wing is faster and therefore, can cover large areas while the copter gives better resolution images as it can fly at lower heights. The level of detail achieved in this study was 1 cm which is sufficient for most mapping applications. The time required to produce a structural geological map of the studied area was a fifth of the time required when using conventional mapping techniques. The use of one or the other type of UAVs and the flight height depend on the needs of the project and should be chosen after taking into consideration the required resolution

Automatic detection and classification of microseismic events from Super-Sauze landslide using convolutional neural networks

The application of advanced signal processing techniques in the analysis of signals originating from surface and subsurface processes dates back to late 70s. But, it is within the last 5 years that it has become apparent that the volume of geophysical data being collected is ever increasing, while the time available for their analysis and interpretation has shrunk, especially for applications that require decision making in almost real-time, e.g., well stimulation processes, road traffic management prior to an imminent slope failure, etc. Within the past 2 years, the number of studies on the potential of machine learning in deciphering the information contained within geophysical monitoring recordings has significantly increased. Machine learning algorithms for microseismic analysis have focused so far on classification of microseismic events, supported by various signal processing tools for denoising and detection of events. Most classification approaches have focused on well-known tools such as Support Vector Machine and Random Forests, with emerging approaches based on deep neural networks (DNNs). Our approach builds on the potential of DNNs through the implementation of a convolutional neural network (CNN) architecture that performs both detection and classification, and is trained on multi-channel data recordings to ‘learn’ the best feature representation for each event class of interest. We use the curated Super-Sauze landslide dataset with 8 stations that contains manually extracted 10 classes of events. Specifically, our CNN comprises 5 models, to automatically detect and classify 5 classes - local earthquake, distance slidequake, rock falls, undefined sinusoidal events and calibration events. The table below is a confusion matrix showing how many events of each type were correctly classified (on the diagonal) and how many events from the column labelled event are incorrectly classified as the row labelled event. For example, all 15 local earthquake events were correctly detected and classified, 10 out of 12 distance slidequake events were correctly detected and classified whereas the other two slidequake events were misclassified as multiple rock falls. In summary, all seismic events were detected, and clearly distinguished from the calibration shots

High-accuracy real-time microseismic analysis platform : case study based on the super-sauze mud-based landslide

Understanding the evolution of landslide and other subsurface processes via microseismic monitoring and analysis is of paramount importance in predicting or even avoiding an imminent slope failure (via an early warning system). Microseismic monitoring recordings are often continuous, noisy and consist of signals emitted by various sources. Automated analysis of landslide processes comprises detection, localization and classification of microseismic events (with magnitude <2 richter scale). Previous research has mainly focused on manually tuning signal processing methods for detecting and classifying microseismic signals based on the signal waveform and its spectrum, which is time-consuming especially for long-term monitoring and big datasets. This paper proposes an automatic analysis platform that performs event detection and classification, after suitable feature selection, in near realtime. The platform is evaluated using seismology data from the Super-Sauze mud-based landslide, which islocated in the southwestern French Alps, and features earthquake, slidequake and tremor type events

Scale-dependent influence of pre-existing basement shear zones on rift faulting : a case study from NE Brazil

Rifting of continental crust initiates faults that are commonly influenced by pre-existing structures. We document newly identified faults cutting Precambrian units in the interior of the NE Brazilian margin to assess the effects of structural inheritance on both rift geometry and fault architecture. Stratigraphic and structural data indicate that the faults were active in the main phase of rifting of Gondwana. The influence of pre-existing structures on the Mesozoic rift faulting is scale dependent. Regionally, the faults trend parallel to subvertical, crustal-scale Brasiliano (c. 750–540 Ma) shear zones. Mylonitic foliations and broadly distributed low strain in the lower crust indicated by shear-wave splitting controlled the overall orientation and kinematics of the rift faults. However, outcrop observations of the faults show that at scales up to hundreds of metres, mylonitic foliations have little influence on fault architectures. Faults cross-cut shear zones and do not commonly utilize foliation planes as shear fractures. Instead, slip zones and fractures have a range of orientations that form acute angles to the local foliation orientation. This observation explains the range of focal mechanisms associated with seismicity that coincides with ancient shear zones in intra-continental areas

Graph-based micro-seismic signal classification with an optimised feature space

Classification of seismic events detected from seismic recordings has been gaining popularity in interpretation of subsurface processes, e.g., volcanic systems, earthquake activity, induced seismicity and slope stability, in particular landslides. However, due to the variability of signal representation for different classes in the temporal and spectral space, a large feature space to characterise the uniqueness of a particular type of event is used for classifying seismic signals. The consequence is additional complexity on the classifier and overfitting. So far, there has been little attempt to address dimensionality reduction via feature selection. In this paper, we propose an iterative, alternating graph feature and classifier learning method for micro-seismic signals via graph Laplacian regularization and normalized graph Laplacian regularization. Using recorded micro-seismic events from an active landslide, we demonstrate improved classification accuracy with a relatively small feature space compared to state of the art

Unmanned Aerial Vehicle (UAV) based mapping in engineering geological surveys : considerations for optimum results

UAVs have been used in engineering for at least two decades, mainly focusing on structural health monitoring, geological surveys and site inspections, especially at cases where a rapid assessment is required, for example after a natural disaster. While there is a wide range of recognition algorithms for the automatic identification of structural damage, structural geological features etc. from the acquired images, the parameters affecting the resolution of these images are often overlooked. As a result, the UAV technology is not used at its full potential and at times, it is even regarded as leading to poor outcomes. This paper discusses the main parameters affecting the resolution of the images acquired by a UAV. We present a case study of the structural geological mapping of a coastal area carried out using two types of UAVs: a fixed wing and a hexacopter. A comparison between the structural geological maps based on the orthophotos and one produced using conventional techniques shows that the level of detail is the same and the time spent is at least 5 times less when using a UAV. The fixed wing is faster and therefore, can cover large areas while the copter gives better resolution images as it can fly at lower heights. The latter is cost and time effective only if it is used for surveys limited to small areas. The characterization of some structural geological features has not been possible based solely on the orthophotos. We show that in order to achieve the desired accuracy, a ground sample distance of at least half that value is required. We discuss technical aspects, such as the effect of topography and UAV orientation on the overlap value, the camera calibration, number of control points and lighting conditions, that should be taken into account prior to flying a UAV and provide recommendations on how to obtain optimum results, i.e. orthophotos that suit the needs of the project

Investigation of the relationship between rainfall and long-term settlements of earthfill dams based on geodetic measurements : the case of Pournari I dam (Greece)

Ageing earthfill dams become vulnerable to weather phenomena such as rainfall and flooding, with severe consequences, economic and life threatening, to the communities living downstream. A better understanding of their long-term behaviour and the factors affecting it, is crucial. A unique data set was used, consisting of the crest settlements of an earthfill, central clay core dam, the Pournari I dam in Greece, and the rainfall height values at the dam site between 1981 and 2015. The dam is 107 m high and its construction was completed in 1981. In previous studies the settlements of this dam, including rates, were found to be within limits and compliant with empirical relationships derived for dams of this type. In this work we remove the effect of primary consolidation and creep from the settlements and attempt to study the relationship between the residuals and rainfall. We find that consolidation was completed within 4 years since the end of construction (by 1985) and residuals of all points on the crest appear to follow the same evolution pattern. While no direct relationship could be established between the actual settlement observations and the rainfall, residuals seem to have maximum correlation with the cumulative rainfall height over a period of two months before the settlement measurement epoch. Our findings most likely represent a threshold value of rainfall above which the dam seems to be responding rather than a time duration over which rainfall plays an important role to the settlements of the dam

Archaeological evidence of a destructive earthquake in Patras, Greece

Oriented collapse of columns, large-scale destruction debris and temporary abandonment of the area deduced from an archaeological excavation provide evidence for a major (intensity IX) earthquake in Patras, Greece. This, and possibly a cluster of other earthquakes, can be derived from archaeological data. These earthquakes are not included in the historical seismicity catalogues, but can be used to put constraints to the seismic risk of this city. Patras was affected by a cluster of poorly documented earthquakes between 1714 and 1806. The city seems to be exposed to risks of progressive reactivation of a major strike-slip fault. A magnitude 6.4 earthquake in 2008 has been related to it. This fault has also been associated with a total of four events in the last 20 years, a situation reminiscent of the seismic hazard at the western edge of the North Anatolian Fault

Εκτίμηση συντελεστή ασφαλείας για την ταπείνωση της στέψης χωμάτινων φραγμάτων

The crest settlements of embankment dams with a central clay core are usually described as an exponential function of time. They play a major role in the safety and operational capacity of the dam, especially when taking into account that extreme crest settlements that have been observed for some of these dams have resulted in a significant reduction of the storage capacity of the reservoir and maintenance works at large scales and cost (e.g. Ataturk dam, Turkey). We studied the crest settlements of > 40 embankment dams, 10-41 years old, located at different parts of the world. Our analysis shows that the safety threshold for the crest settlements should not be a constant but increase with the age of the dam and that most of suggested thresholds in the literature are too conservative. A safety threshold of 1% (crest settlement to dam height ratio) appears to be realistic for the whole operational life of the dam. The Kremasta dam, whose age and size places it to a most critical situation, has a crest settlement to dam height ratio value well below the above threshold