Landslides

Landslides!

A great idea for a student research project: Use moving-window iterative-closest-point differencing (MW-ICP) to map the amount and distribution of movement across the Shurtz Lake earthflow. MW-ICP is a technique that quantitatively determines 3-dimensional motion of a surface using digital models of the surface taken at two different times. Working with Chelsea Scott of ASU, who is a world-expert at the method, we successfully imaged creep on the San Andreas fault with the method. In this project we will pioneer applying the method to landslides using the Shurtz Lake earthflow as a test-bed. We made an excellent digital model of the landslide in Geospatial Field Methods in 2019. For this work, we will make a second map using a small uncrewed aerial system (sUAS or drone) and then difference the two to map the landslide's motion since 2019. This approach has the potential to be a significant advance from traditional low to moderate-cost landslide motion measurement which is done by placing isolated markers on the landslide and measuring the marker positions over time. The traditional technique is at least as time-consuming as making digital models, yet provides results only for a few isolated markers. In contrast, the MW-ICP method has the potential to produce complete maps of motion across the entire landslide. This project is perfect for a student interested in hazards and GIS. If you're a UVU student and this work sounds exciting, send me an email at michael.bunds@uvu.edu

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I have ongoing studies of two local landslides. One is the Mile High Drive landslide in east Provo. It's a slow but virtually continuously moving landslide, and I and students (too many to name!) have been using differential-GPS (very accurate, survey and even geodetic grade methods) to measure the movement of the landslide since 2004. We've also measured water table heights and have a great record that correlates the water table height to the rate the slide moves downhill. Previous results have been presented over the years by a couple students (Jessica Oxford, Robert White, Paul Gardner) and me at meetings. Right now, it's just waiting for someone to pick up the reins, take some measurements and run with it.

The other landslide project is the Shurtz Lake earthflow. It's a newer project that we initiated in Geospatial Field Methods, fall 2019 with the parallel goals of using mapping of the earthflow as a vehicle for the class to learn the methods that are the focus of the class and to show that drone-based imaging is an efficient method to detect and measure landslide creep. The class made a superb digital elevation model (DEM) of the slide. Brigham Whitney then did some nice work differencing our new DEM against LiDAR DEMs made a few years earlier to make preliminary estimates of displacement and showed that repeat drone-based photogrammetry is indeed a viable way to identify landslide movement. The next steps on this project are to make a new DEM and to difference it against the 2019 DEM using iterative-closest-point, which should allow pinpointing and excellent quantification of the motion. Iterative closest point is the method we used to quantify the spatial distribution of creep along the San Andreas Fault when we differenced our DEM against older LiDAR data in a recent publication and this is an opportunity to illustrate the power it has, when combined with drone-based imaging, to relatively cheaply and efficiently quantify landslide creep.