QUANTIFYING THE MAGNITUDE OF CHANGES IN RECENT AND HISTORICAL ENVIRONMENTAL CONDITIONS USING INTEGRATED TIME-LAPSE SPATIAL DIFFERENCING OF 3D SURFACE MODELS FROM DRONE (SUAS) DATA

Utilization of time-lapse spatial differencing—where magnitudes of surface topography changes can be quantified in three dimensions by comparing digital surface models from multiple time periods—is becoming more common. The availability and acquisition of 3D surface topography via LiDAR, drone-based structure-from-motion (SfM), or related techniques has increased exponentially in the previous decade. A prerequisite to time-lapse spatial differencing is having “before” data from a time period prior to an event being studied, such as mass wasting, as well as the more-frequently collected data after an event. As the cost burden of LiDAR and SfM have decreased and the availability of “before” datasets has increased, time-lapse spatial differencing analyses are more readily available. Examples will be presented from two case studies. The first will be time-lapse spatial differencing results from a LiDAR-SfM comparison at the site of the 2014 West Salt Creek Landslide in Western Colorado, USA, highlighting a decade of post-slide movement and slope adjustment. The second case-study will present data from several steep-sided stream drainages impacted during the 2020 Pine Gulch Fire in Western Colorado, USA, and the volume and geometry of resulting fire-related slope movement.