Landslides are instrumental drivers of geomorphological change and can cause costly property damage and threaten community safety. The quantitative impact of slope failure on differing spatial and temporal scales on the landscape remains poorly constrained. Here, we evaluate geomorphological change at one of Vermont's largest documented landslides located in Waterbury, Vermont. The Cotton Brook landslide initially failed in 2019 and mobilized large volumes of sediment downstream toward the Waterbury Reservoir. This study spans from 2014 to 2023 and integrates field-based and remotely sensed data to 1) identify active erosive mechanisms following the 2019 event and 2) develop a workflow that allows us to estimate quantitative topographic change linked to distinct geologic processes. Geomorphological field surveys allowed us to map active landscape change mechanisms and ground truth geospatial data analysis results at Cotton Brook. LiDAR data were processed and analyzed using ArcGIS Pro, Agisoft Metashape Pro and CloudCompare softwares to apply topographic differencing techniques to digital elevation models (DEM) and 3-dimensional point clouds. We develop a workflow and use it to compare the change detection outcomes from each software package to quantify uncertainty. Vertical change measurements derived from models across all techniques ranged from -16.59 m to 16.37 m. Estimates derived from DEMs exceeded point cloud results by up to ~15%. We interpret this discrepancy as an overestimation of change by propagated alignment and interpolation error. Calculated vertical uncertainties are influenced by alignment registration errors and range from ~0 cm to 1.5 m. Elevation change measurements were used to extract sediment volume estimates attributed to landslide features. For instance, our results suggest that up to 123,279.8 m3 of debris material has been deposited at the toe of the landslide. Our approach allowed us to identify how different mechanisms of landscape change contributed to the volumes of erosion and deposition on and around the landslide. An integration of field observations with topographic change modeling results suggest that there are heterogeneous processes influencing mass wasting in our study region including erosional features, which have formed since the 2019 landslide and others that are operating throughout the study region. Notable processes include the collapse of thick units of glacial material bordering the main slip region, gully erosion, and rapid stream bank erosion. The findings of this multi-disciplinary research provide an opportunity to quantify the impact of distinctive geomorphological processes and can help to inform future landslide hazard reduction strategies in the Vermont community.

I apply a forensic, multidisciplinary approach that integrates engineering geology field investigations, engineering geomorphology mapping, long-range terrestrial photogrammetry, and a numerical modelling toolbox to two large rock slope failures to study their causes, initiation, kinematics, and dynamics. I demonstrate the significance of endogenic and exogenic processes, both separately and in concert, in contributing to landscape evolution and conditioning slopes for failure, and use geomorphological and geological observations to validate numerical models. The 1963 Vajont Slide in northeast Italy involved a 270-million-m3 carbonate-dominated mass that slid into the newly created Vajont Reservoir, displacing water that overtopped the Vajont Dam and killed 1910 people. Based on literature, maps and imagery, I propose that the landslide was the last phase of slow, deep-seated slope deformation that began after the valley was deglaciated in the Pleistocene. Field and air photograph observations and stream profiles provide the context of Vajont Slide. The first long-range terrestrial digital photogrammetry models of the landslide aid in characterising the failure scar. Analysis of the failure scar emphasises the complexity of the failure surface due to faults and interference between two tectonic fold generations, influencing failure behaviour. Observations of the pre- and post-failure slope and interpretation of numerical simulations suggest a complex three-dimensional active-passive wedge- sliding mechanism, with two main landslide blocks and five sub-blocks in the west block, separated by secondary shear surfaces. The 1959 Madison Canyon Slide in Montana, USA, was triggered by an M = 7.5 earthquake. A 20-million-m3 rock mass descended from the ridge crest, killing 24 people and blocking Madison River to create Earthquake Lake. Marble at the toe of the slope acted as a buttress for weaker schist and gneiss upslope until the earthquake undermined its integrity and triggered failure. Rock mass characterisation, long-range terrestrial digital photogrammetry, and kinematic analysis indicate that the lateral, rear, and basal release surfaces formed a hexahedral wedge-biplanar failure. Dynamic numerical modelling suggests topographic and damage amplification due to ridge geometry and pre-existing tension cracks. Analysis of the case studies highlights the complexity of large, catastrophic rock slope failures, their causes, and their evolution from incipient failure to disaster.

This interactive book presents comprehensive information on the fundamentals of landslide types and dynamics, while also providing a set of PPT, PDF, and text tools for education and capacity development. It is the second part of a two-volume work created as the core activity of the Sendai Partnerships, the International Consortium of Landslides. The book will be regularly updated and improved over the coming years, based on responses from users and lessons learned during its application.

This book discusses various statistical models and their implications for developing landslide susceptibility and risk zonation maps. It also presents a range of statistical techniques, i.e. bivariate and multivariate statistical models and machine learning models, as well as multi-criteria evaluation, pseudo-quantitative and probabilistic approaches. As such, it provides methods and techniques for RS & GIS-based models in spatial distribution for all those engaged in the preparation and development of projects, research, training courses and postgraduate studies. Further, the book offers a valuable resource for students using RS & GIS techniques in their studies.

This study demonstrates the advantages of combining remote sensing with field data in landslide investigations and provides improved data on the structural geology and its influence on slope movements at Downie Slide, a large landslide located in southeastern British Columbia, Canada. The geomorphology of the Downie Slide was studied using airborne LiDAR in a GIS environment to provide new insights on the landslide displacement mechanism. Surface and underground areas of the slide were compared and contrasted using terrestrial laser scanning and photogrammetry. Six joint sets were identified. Some structures and domain boundaries were found to be pervasive throughout the slide. A correlation between slope deformation, and large-scale structural and damage features was made and 12 structural domains defined within the landslide. Large secondary retrogressive-failures were identified for the head scarp and retrogression of the northern boundary, increasing the overall area of slide material by ~ 1 km2.

Modern Technologies for Landslide Investigation and Prediction presents eleven contributed chapters from Chinese and Italian authors, as a follow-up of a bilateral workshop held in Shanghai on September 2013. Chapters are organized in three main parts: ground-based monitoring techniques (photogrammetry, terrestrial laser scanning, ground-based InSAR, infrared thermography, and GNSS networks), geophysical (passive seismic sensor networks) and geotechnical methods (SPH and SLIDE), and satellite remote-sensing techniques (InSAR and optical images). Authors of these contributes are internationally-recognized experts in their respective research fields. Marco Scaioni works in the college of Surveying and Geo-Informatics at Tongji University, Shanghai (P.R. China). His research fields are mainly Close-range Photogrammetry, Terrestrial Laser Scanning, and other ground-based sensors for metrological and deformation monitoring applications to structural engineering and geosciences. In the period 2012-2016 he is chairman of the Working Group V/3 in the International Society for Photogrammetry and Remote Sensing, focusing on ‘Terrestrial 3D Imaging and Sensors’.