Autonomous Environmental UAV Survey System for Wildfire Assessments

Wildfire response planning is limited by the lack of high-resolution data for use in wildfire prediction. Wildfire models depend on many variables, including weather, topography, vegetation type and arrangement, fuel moisture content, and regional fire prevention measures, among others. Some of these variables are static or nearly so, but some of these are highly dynamic. In particular, live fuel moisture content can vary on a timescale of days or weeks, and is highly spatially dynamic as well. We propose to develop a wildfire fuel mapping capability onboard a UAS, with special emphasis on live fuel moisture content estimation. Additional mapped variables will include vegetation type and arrangement among other common wildfire modeling inputs. The technical innovation is in combining this perception module with our UAS subcanopy forest survey capability, which is enabled by our exploration-based autonomous control system. The commercial innovation is in our target application. The product’s primary purpose is to collect a digital forest inventory for commercial forest management, and by simultaneously collecting a high-resolution wildfire fuel map, we enable enhanced rapid response in the event of a wildfire, reducing loss of life, property, and disruption from high-impact events.