. Building a decision-making framework for monitoring slope instabilities.

Abstract
With population and infrastructure density increasing in mountainous regions, and climate change very likely increasing landslide frequency (Huggel et al., 2012), accurate landslide detection and measurement becomes increasingly important, both for scientific understanding and hazard monitoring and response. Ground-based InSAR (GBInSAR) can measure sub-millimeter displacements but faces several drawbacks (Monserrat et al., 2014): Data interpretation requires a high level of expertise, coverage depends strongly on topography, the instrument needs to be mounted in a long-term stable location, and the instrument cost is very high (~$250,000). Alternatively, crack meters and total stations can be used to obtain very precise measurements at point locations. This work is aimed at building a decision-making framework for natural hazard professionals to find the slope monitoring technique best suited for different situations. Slumgullion landslide is a perfect outdoor laboratory to compare a variety of techniques aimed at measuring slope displacements. In June and August of 2018 we carried out two field campaigns at Slumgullion during which we acquired terrestrial laser scanner (TLS) data (initial and repeat measurement), flew two structure-from-motion (SfM) campaigns with camera-equipped multi-rotor unmanned aerial vehicles (UAVs), and collected over two months-worth of ground-based synthetic aperture radar data. Additionally, we also tested a second, real aperture ground-based radar interferometer, with which we acquired data during the first field campaign. The SfM images were acquired from a variety of platforms, giving us insight into the various qualities and limitations of cameras and UAVs. Preliminary results from processing the UAV images (manual feature tracking) and the ground-based InSAR data suggest that they are in good agreement, showing displacements on the order of 0.01 m per day. In order to thoroughly compare the radar, TLS and SfM data, we will reproject all of the displacements into the radar line-of-sight (LOS). We will reprocess all of the TLS and UAV data using the open source software CloudCompare and COSI-Corr, rather than rely on manual feature tracking. Furthermore, we will also process the data that colleagues at UNAVCO acquired from a UAV in the summer of 2017, so as to evaluate the usefulness SfM data acquired for a different purpose. In addition to the technical values like instrument accuracy and precision of the instruments will take into account cost, laws and regulations, access to the hazard area, displacement velocities, power requirements, logistics, required, as well as the necessary data analysis and interpretation expertise.