Automated classification of douglas-fir beetle infested trees in Unpiloted Aerial Vehicle (UAV) acquired imagery**

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Early detection of Douglas fir beetle (IBD) infestation is increasingly important in southern British Columbia, where the IBD infested area has grown from approximately 7,000 ha in 2013 to almost 80,000 ha in 2017. IBD infestation, generally kills the tree rapidly reducing the value of the timber when it is harvested or if is not harvested, contributing to the fuel available to sustain forest fires. Currently, detection of IBD infestation is carried out by visual inspection of the forest canopy during helicopter overview flights and by visual inspection of individual trees from ground level by field crews. Helicopter overviews can cover large areas but cannot quantify the scale of IBD infestation, because the human eye cannot perceive changes in the canopy during the early stage (green attack) of the infestation, and because the human eye cannot resolve individual trees from elevation of a helicopter overview flight. Thus, helicopter overviews cannot produce an accurate count of dead (grey attack) or dying (red attack) trees. Field visits, on the other hand, can accurately identify IBD infestation in the green, red, and grey attack stages, but field method do not scale well economically to large areas. Thus, current methods for quantifying IBD infestation are insufficient, resulting in an incomplete harvest of IBD infested trees when they are still economically valuable. Through a partnership with researchers at Thompson Rivers University, forestry professionals at Second Pass Forestry Ltd. (SPF) want to develop and validate a semi-automated system for analyzing unpiloted aerial vehicle (UAV) -acquired multispectral imagery to identify trees in all three stages (green, red, and grey) of IBD attack. The knowledge gained from this research will be transferred to SPF along with software implementing the image analysis workflow. Through publication of the outcomes of this research in a peer-reviewed journal, the knowledge gained from this research will be distributed more broadly to the forestry community.******