A robust surface matching technique for coastal geohazard monitoring

Coastal geohazards, such as landslides, mudflows, and rockfalls, represent a major driver for coastal change in many regions of the world, and often impinge on aspects of the human and natural environment. In such cases, there is a pressing need for the development of more effective monitoring strategies, particularly given the uncertainties associated with the impact of future climate change. Traditional survey approaches tend to suffer from limited spatial resolution, while contemporary techniques are generally unsuitable in isolation, due to the often complex coastal topography. To address these issues, this thesis presents the development and application of a strategy for integrated remote monitoring of coastal geohazards. The monitoring strategy is underpinned by a robust least squares surface matching technique, which has been developed to facilitate change detection through the reliable reconciliation of multi-temporal, multi-sensor datasets in dynamic environments. Specifically, this research has concentrated on integrating the developing techniques of airborne and terrestrial laser-scanning. In addition, archival aerial photography has been incorporated in order to provide a historical context for analysis of geohazard development. Robust surface matching provides a mechanism for reliable registration of DEM surfaces contaminated by regions of difference, which may arise through geohazard activity or vegetation change. The development of this algorithm has been presented, and its potential demonstrated through testing with artificial datasets. The monitoring strategy was applied to the soft-cliff test site of Filey Bay, North Yorkshire. This highlighted the viability of the robust matching algorithm, demonstrating the effectiveness of this technique for absolute orientation of DEMs derived from archival aerial photography. Furthermore, the complementary qualities of airborne and terrestrial laser scanning have been confirmed, particularly in relation to their value for multi-scale terrain monitoring. Issues of transferability were explored through application of the monitoring strategy to the hard rock environment of Whitby East Cliff. Investigations in this challenging environment confirmed the potential of the robust matching algorithm, and highlighted a number of valuable issues in relation to the monitoring techniques. Investigations at both test sites enabled in-depth assessment and quantification of geohazard activity over extended periods of time.EThOS - Electronic Theses Online ServiceEnglish Heritage : British Geological SurveyGBUnited Kingdo

Novel Approaches in Landslide Monitoring and Data Analysis

Significant progress has been made in the last few years that has expanded the knowledge of landslide processes. It is, therefore, necessary to summarize, share and disseminate the latest knowledge and expertise. This Special Issue brings together novel research focused on landslide monitoring, modelling and data analysis

Morphology-based landslide monitoring with an unmanned aerial vehicle

PhD ThesisLandslides represent major natural phenomena with often disastrous consequences. Monitoring landslides with time-series surface observations can help mitigate such hazards. Unmanned aerial vehicles (UAVs) employing compact digital cameras, and in conjunction with Structure-from-Motion (SfM) and modern Multi-View Stereo (MVS) image matching approaches, have become commonplace in the geoscience research community. These methods offer a relatively low-cost and flexible solution for many geomorphological applications. The SfM-MVS pipeline has expedited the generation of digital elevation models at high spatio-temporal resolution. Conventionally ground control points (GCPs) are required for co-registration. This task is often expensive and impracticable considering hazardous terrain. This research has developed a strategy for processing UAV visible wavelength imagery that can provide multi-temporal surface morphological information for landslide monitoring, in an attempt to overcome the reliance on GCPs. This morphological-based strategy applies the attribute of curvature in combination with the scale-invariant feature transform algorithm, to generate pseudo GCPs. Openness is applied to extract relatively stable regions whereby pseudo GCPs are selected. Image cross-correlation functions integrated with openness and slope are employed to track landslide motion with subsequent elevation differences and planimetric surface displacements produced. Accuracy assessment evaluates unresolved biases with the aid of benchmark datasets. This approach was tested in the UK, in two sites, first in Sandford with artificial surface change and then in an active landslide at Hollin Hill. In Sandford, the strategy detected a ±0.120 m 3D surface change from three-epoch SfM-MVS products derived from a consumer-grade UAV. For the Hollin Hill landslide six-epoch datasets spanning an eighteen-month duration period were used, providing a ± 0.221 m minimum change. Annual displacement rates of dm-level were estimated with optimal results over winter periods. Levels of accuracy and spatial resolution comparable to previous studies demonstrated the potential of the morphology-based strategy for a time-efficient and cost-effective monitoring at inaccessible areas

Volume II: Mining Innovation

Contemporary exploitation of natural raw materials by borehole, opencast, underground, seabed, and anthropogenic deposits is closely related to, among others, geomechanics, automation, computer science, and numerical methods. More and more often, individual fields of science coexist and complement each other, contributing to lowering exploitation costs, increasing production, and reduction of the time needed to prepare and exploit the deposit. The continuous development of national economies is related to the increasing demand for energy, metal, rock, and chemical resources. Very often, exploitation is carried out in complex geological and mining conditions, which are accompanied by natural hazards such as rock bursts, methane, coal dust explosion, spontaneous combustion, water, gas, and temperature. In order to conduct a safe and economically justified operation, modern construction materials are being used more and more often in mining to support excavations, both under static and dynamic loads. The individual production stages are supported by specialized computer programs for cutting the deposit as well as for modeling the behavior of the rock mass after excavation in it. Currently, the automation and monitoring of the mining works play a very important role, which will significantly contribute to the improvement of safety conditions. In this Special Issue of Energies, we focus on innovative laboratory, numerical, and industrial research that has a positive impact on the development of safety and exploitation in mining

Remote Sensing Applications in Coastal Environment

Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments