Autonomous Environmental UAV Survey System for Wildfire Assessments

Prescribed burns are a critical aspect of land management, but they require vegetation data that is hard to obtain at high resolution and on the timescale required. Our autonomous UAV collects critical fire modeling variables through subcanopy flight, enabling rapid surveys for faster and safer burn planning. In Phase I, we proved the feasibility of mapping live fuel moisture content (LFMC) with subcanopy UAV data, including near and shortwave infrared. To build on this, in Phase II we will enable the UAV to measure the remaining required variables for fire behavior prediction, e.g., canopy base height, stand height, and canopy cover. We additionally propose a method for multi-UAV collaboration to reduce total survey time, since subcanopy flight speeds are limited. This technology will enable burn managers to increase their annual acreage treated with prescribed burns, reducing the risk of catastrophic wildfires at a time when that is critically needed.