GUIDELINES FOR USING PHOTOGRAMMETRIC TOOLS ON UNMANNED AIRCRAFT SYSTEMS TO SUPPORT THE RAPID MONITORING OF AVALANCHE-PRONE ROADSIDE ENVIRONMENTS

Abstract

Unmanned aircraft systems (UAS) technology paired with photogrammetric capabilities has the potential to rapidly provide feedback on snowpack data that can be used to monitor and forecast avalanche risks. This research tested Structure from Motion (SfM) (photogrammetry) software with data from unmanned aircraft above roadside avalanche test sites in Alaska and Washington state. The SfM data included accurate information about snowpack depth and snowpack volume, which can help department of transportation (DOT) avalanche experts assess risk and determine whether mitigation was necessary. In addition, the digital images collected for the SfM provided additional useful information. The collection of SfM data has limitations, as successful data collection requires proper ground control points for registration of the images, adequate lighting to collect the digital images required for the SfM process, and the ability to fly the unmanned aircraft to collect the data, which may be limited by both weather and regulations. Overall, the effort determined that SfM provides usable data, and it created a decision support tool to assist DOTs in more quickly responding to and mitigating avalanche hazards, opening roads, or avoiding closing them at all and thus improving roadway reliability for both freight and passengers.