Measuring Snow Depth Using RPAS Photogrammetry in a Subalpine Coastal Region of British Columbia (Extended Abstract)

Mountain snow in British Columbia is primarily monitored using automated remote weather stations, which measure snow depth (SD), snow water equivalent (SWE), and multiple weather parameters, and a manual snow survey program, with records dating back to the 1930’s The network provides excellent information to track change through time and data are effectively used to provide regional forecasts for both flooding and drought, however there is still high uncertainty when scaling these measurements to the watershed level. In addition, there is potential for the current network of stations and snow courses to have more frequent snow free years due to climate change, and gaining a better understanding of how they represent snow that occurs above them is needed. Advances in remote sensing technologies present important opportunities to accurately measure the high degree of spatial variation in SD, and use existing methods (Hill et. al., 2019; Strum et. al., 2010) or develop new approaches to improve estimates of snow density and SWE at finer spatial resolutions. To help address the limitations of relying on discrete, in-situ SD sampling and reduce the uncertainties in overall snowpack measurements, small remotely piloted aircraft systems (RPAS) based structure-from-motion photogrammetry (SFM) has emerged as an effective technology. While they are not capable of measuring areas at the same scale as full-size aircraft or satellites, certain RPAS can be used to capture data across several square kilometres, are much less cost prohibitive and their potential to produce 3D models at high accuracies and very fine spatial resolutions is becoming increasingly well established.