Abstract
Latest advances in topographic data acquisition techniques have greatly enhanced the possibility to analyse landscapes in order to understand the processes that shaped them. High-resolution Digital Elevation Models (DEMs), such as LiDAR-derived ones, provide detailed topographic information. In particular, if multi-temporal DEMs are available, it is possible to carry out a detailed geomorphic change detection analysis. This analysis may provide information about the dynamics of large landslides and may thus, be useful for landslide risk assessments. However, LiDAR-derived DEMs are mostly available only as post-event surveys. The technique is relatively recent, and local or national authorities only started widespread surveys in the last decade. Therefore, it is of a certain interest to analyse the effectiveness of DEMs derived from technical cartography to produce reliable volumetric estimates related to large landslides. This study evaluates the use of a multi-source DEM of Difference (DoD) analysis for the investigation of a large landslide –Le Laste–, which occurred on November 12, 2014 on Mount Antelao (eastern Italian Alps). The landslide initiated as a 365,000 m3 rockslide close to the summit of the mountain and transformed into a debris avalanche during its runout. The comparison of pre- and post-event DEMs allowed for the identification and quantification of erosion and deposition areas, and for the estimation of landslide volume. A sound back-analysis of the landslide with the 3D numerical model DAN3D was based on this comparison and on seismic records of the event. These seismic records proved to be remarkably useful, as they allowed for the calibration of the simulated landslide velocity. This ensured the reliability of the model notwithstanding the topographic datasets, intrinsic uncertainties. We found that using a pre-event DEM derived from technical cartography tends to slightly overestimate the volume with respect to the use of the more accurate LiDAR-derived DEM. In recent years, the landslide risk around Mt. Antelao has been increasing alongside the ever-growing population and human activities in the area. Sediment accumulations produced by the Le Laste landslide significantly amplified the debris flow hazard by providing new sediment sources. Therefore, it is crucial to delineate the distribution of this material to enable an adequate debris flow hazard assessment. The material properties derived from the back-analysis of the Le Laste landslide can be used to simulate the runout of possible future events, and to generate reliable hazard zone maps, which are necessary for effective risk mitigation.
Highlights
Landslides occur over a wide range of spatial and temporal scales in mountainous areas all over the world and pose a substantial threat to people, property, and infrastructure (e.g., Palmquist & Bible, 1980; Corominas, 1996; Hungr, Corominas & Eberhardt, 2005)
A second pre-event Digital Elevation Models (DEMs) with a resolution of 5 m was provided by the Regione Veneto cartographic service and it is based on 2007 technical cartography data
A second DEM of Difference (DoD) analysis was based on the 5 m pre-event DEM derived from technical cartography and the LiDAR-derived post-event DEM (Figs. 7 and 8)
Summary
Landslides occur over a wide range of spatial and temporal scales in mountainous areas all over the world and pose a substantial threat to people, property, and infrastructure (e.g., Palmquist & Bible, 1980; Corominas, 1996; Hungr, Corominas & Eberhardt, 2005). The average death toll rate related to landslides reached 59 victims per year in the last century (Guzzetti, 2000) and the Italian National Research Council, Institute for Geo-Hydrological Protection (CNR-IRPI) estimated that the total cost of direct damage ranges between 1 and 2 billion Euros per year (Canuti et al, 2004). This highlights the importance of landslide risk assessment and management, especially in densely populated regions, in order to prevent people and human activity from being exposed to such hazards (Guzzetti, 2000). The understanding of these processes strongly depends on the availability and the quality of topographic data (Brasington, Rumsby & McVey, 2000)
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