Alexander L. Handwerger

TL;DR: In this article, the primary means by which lidar has and will continue to transform how geomorphologists study landscape form and evolution are identified: (i) lidar serves as a detailed base map for field mapping and sample collection, (ii) lidars allows for rapid and accurate description of morphologic trends and patterns across broad areas, which facilitates model test- ing through increased accuracy and vastly increased sample sizes, and (iii, lidar enables the identification of unanticipated landforms, including those with unknown origin.

TL;DR: In the most destructive and catastrophic landslide events, rocks, soil and fluids can travel at speeds approaching several tens of metres per second as discussed by the authors, but slow-moving landslides rarely claim lives, they can cause major damage to infrastructure and sometimes fail catastrophically, transitioning into fast moving landslides that can result in thousands of casualties.

TL;DR: In this paper, the authors used satellite radar interferometry (InSAR) time series, precipitation data, and high-resolution topographic data from airborne lidar to quantify the seasonal dynamics of 10 slow-moving landslides.

TL;DR: ALarge increase in pore-fluid pressure occurred during a shift from historic drought to record rainfall that triggered a large increase in velocity and drove slip localization, overcoming the stabilizing mechanisms that had previously inhibited landslide acceleration.

TL;DR: In this paper, the authors presented a deformation detection approach using double difference time series with local and regional spatial filters and pixel clustering methods to identify and monitor slow-moving landslides without making a priori assumptions of the location of landslides.