Structure from Motion (SfM) is a powerful tool to provide 3D point clouds from a sequence of images taken from different remote sensing technologies. The use of this approach for processing images captured from both Remotely Piloted Aerial Vehicles (RPAS), historical aerial photograms, and smartphones, constitutes a valuable solution for the identification and characterization of active landslides. We applied SfM to process all the acquired and available images for the study of the Champlas du Col landslide, a complex slope instability reactivated in spring 2018 in the Piemonte Region (north-western Italy). This last reactivation of the slide, principally due to snow melting at the end of the winter season, interrupted the main road used to reach Sestriere, one of the most famous ski resorts in north-western Italy. We tested how SfM can be applied to process high-resolution multisource datasets by processing: (i) historical aerial photograms collected from five diverse regional flights, (ii) RGB and multi-spectral images acquired by two RPAS, taken in different moments, and (iii) terrestrial sequences of the most representative kinematic elements due to the evolution of the landslide. In addition, we obtained an overall framework of the historical development of the area of interest, and distinguished several generations of landslides. Moreover, an in-depth geomorphological characterization of the Champlas du Col landslide reactivation was done, by testing a cost-effective and rapid methodology based on SfM principles, which is easily repeatable to characterize and investigate active landslides.
Active landslide risk assessment and management are primarily based on the availability of dedicated studies and monitoring activities. The establishment of decision support for the efficient management of active landslides threatening urban areas is a worthwhile contribution. Nowadays, consistent information about major landslide hazards is obtained through an interdisciplinary approach, consisting of field survey data and long-time monitoring, with the creation of a high populated dataset. Nevertheless, the large number and variety of acquired data can generate some criticalities in their management. Data fragmentation and a missing standard format of the data should represent a serious hitch in landslide hazard management. A good organization in a standard format can be a good operative solution. Based on standardized approaches such as the ICAO (International Civil Aviation Organization), we developed a standard document called operative monography. This document summarizes all available information by organizing monitoring data and identifying possible lacks. We tested this approach in the Aosta Valley Region (NW Italy) on five different slow moving landslides monitored for twenty years. The critical analysis of the available dataset modifies a simple sequence of information in a more complex document, adoptable by local and national authorities for a more effective management of active landslides.
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