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Topographic change detection is increasingly being used to identify and monitor landslides and other geohazards in support of risk-informed decision-making. Expanding change detection from site specific to regional scales enables increasingly proactive asset management and contributes to improving the resilience of infrastructure to extreme events. It is widely known that change detection precision can be improved by applying three-dimensional algorithms, such as iterative closest point (ICP) and M3C2, directly to raw point clouds. However, this also increases the computational requirements compared to alternatives such as digital elevation model differencing. This study presents a novel graphics processing unit (GPU)-based implementation of the ICP-M3C2 workflow to address this limitation. In the proposed algorithm, point cloud data segments are automatically queued and served to the working GPU, which efficiently performs point cloud processing operations, while the central processing unit (CPU) performs data management operations in parallel. The developed method is estimated to be up to 54 times faster than CPU-based versions of the same algorithm. In this study, we present how the workflow has been applied to six regional-scale landslide identification and monitoring case studies in which landslides are causing the disruption of pipelines, highways, and rail corridors. Overall, in 2021 and 2022, over 17 500 linear km of change detection were processed using the demonstrated method. [ABSTRACT FROM AUTHOR]

Traditional mapping and monitoring of active slope processes in mountainous terrain is challenging, given often difficult site accessibility, obstructed visibility, and high complexity of the terrain. For example, the rockfall hazard evaluation system employed by Canadian railways relies partly on visibility of the rockfall source zone from track level, which is often impossible for large or complex slopes, in the mountains and elsewhere. Recent advancements in remote sensing, data collection, and analysis algorithms have helped resolve some of these issues by allowing the slope processes to be mapped, and thereby understood, with a greater degree of accuracy and confidence than was previously possible. For example, a better understanding of the rate of movement of material around a natural rock slope affecting a transportation corridor would certainly improve any assessment of the hazards caused by those movements. Various remote sensing technologies have the capability to be used to assess these processes; however, the optimal conditions under which the technology should be deployed are not clearly defined. Between December 2012 and December 2013 the efficacy of three remote sensing technologies (terrestrial and aerial LiDAR (light detection and ranging) and terrestrial photogrammetry) were compared for their ability to detect natural and anthropogenic changes at a location along the CN railway, in British Columbia, Canada. The results demonstrate a high degree of interoperability between the different technologies, the ability to map topographical change with all three technologies, and the limitations and (or) weaknesses of each technology with respect to mapping change. The project location and site accessibility represent a real world situation with nonideal facets, which challenge the capabilities of these state-of-the-art technologies. These results will aid decisionmaking with respect to implementation of remote sensing technologies to monitor changes to rock slopes adjacent to transportation corridors, which will lead to better understanding and assessment of hazards. Key words: remote sensing, natural hazards, rockfall, light detection and ranging (LiDAR), photogrammetry, change detection, transportation corridors. Les methodes traditionnelles de cartographie et de suivi des processus dans les pentes actives de regions montagneuses sont difficilement applicables, en raison de l'accessibilite limitee aux sites, de la visibilite obstruee, et de la grande complexite du terrain. Par exemple, le systeme devaluation des risques d'eboulement utilise par les chemins de fer canadiens se base en partie sur la visibilite de la zone a la source d'eboulements a partir du niveau du chemin de fer, ce qui est parfois impossible pour les grandes pentes ou les pentes complexes, dans les montagnes et ailleurs. Les avancees recentes dans le domaine de la teledetection, de la collecte de donnees et des algorithmes d'analyse ont aide a solutionner quelques-uns de ces problemes en permettant de cartographies et ainsi de comprendre, les processus des pentes avec un meilleur degre de justesse et de confiance qu'il en etait possible auparavant. Par exemple, une meilleure comprehension du taux de mouvement de materiel autour d'une pente rocheuse naturelle qui affecte un corridor de transport ameliorerait certainement les evaluations des risques causes par ces mouvements. Plusieurs technologies de teledetection ont la capacite d'etre utilisees pour evaluer ces processus, cependant les conditions optimales dans lesquelles la technologie devrait etre deployee ne sont pas encore clairement definies. De decembre 2012 a decembre 2013, l'efficacite de trois technologies de teledetection (<> (LiDAR) terrestre et aerien, photogrammetrie terrestre) a ete comparee par rapport a leur capacite a detecter des changements naturels et anthropogeniques sur un site situe le long du chemin de fer du CN en Colombie-Britannique, Canada. Les resultats demontrent un haut niveau d'interoperabilite entre les differentes technologies, la capacite a cartographier les changements topographiques avec les trois technologies, et les limites et (ou) faiblesses de chaque technologie par rapport aux changements de cartographie. La localisation du projet et l'accessibilite du site representent une situation reelle avec des aspects non ideaux qui mettent au defi les capacites de ces technologies d'avant-garde. Les resultats vont aider la prise de decision lors de l'implantation de technologies de teledetection pour suivre les changements des pentes rocheuses adjacentes a des corridors de transport, ce qui apportera une meilleure connaissance et evaluation des risques. [Traduit par la Redaction] Mots-cles: teledetection, risques naturels, eboulement, <> (LiDAR), photogrammetrie, detection des changements, corridors de transport., Introduction Transportation corridors in mountainous and other steep, rocky terrain are routinely subject to natural hazards, which threaten physical infrastructure, the safety of workers and travelers, and the delivery of [...]