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

早期发现道格拉斯冷杉甲虫（IBD）侵扰在不列颠哥伦比亚省南部越来越重要，IBD侵扰面积已从2013年的约7，000公顷增加到2017年的近80，000公顷。 IBD的侵扰，通常会迅速杀死树木，降低木材的价值，当它被收获或如果没有收获，有助于燃料可用于维持森林火灾。目前，IBD感染的检测是通过在直升机概览飞行期间对森林树冠进行目视检查和由实地工作人员从地面对个别树木进行目视检查来进行的。 直升机概览可以覆盖大面积，但不能量化IBD侵扰的规模，因为人眼不能感知在侵扰的早期阶段（绿色侵袭）树冠的变化，并且因为人眼不能从直升机概览飞行的高度分辨单个树木。因此，直升机鸟瞰不能产生死亡（灰色攻击）或死亡（红色攻击）树木的准确计数。另一方面，实地考察可以准确地识别绿色、红色和灰色发作阶段的IBD侵染，但实地方法不能经济地扩展到大面积。 因此，目前用于定量IBD侵染的方法是不充分的，导致当IBD侵染的树木仍然具有经济价值时，它们的收获不完全。通过与汤普森河流大学的研究人员合作，Second Pass Forestry Ltd.（SPF）的林业专业人员希望开发和验证一种半自动化系统，用于分析无人机（UAV）获取的多光谱图像，以识别IBD攻击的所有三个阶段（绿色，红色和灰色）的树木。从本研究中获得的知识将与实现图像分析工作流程的软件一起沿着转移到SPF。通过在同行评审的期刊上发表这项研究的成果，这项研究所获得的知识将更广泛地传播给林业界。

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.******