무인항공기 촬영 정사영상을 이용한 재선충 감염목 탐지

Pine wilt disease is a disease in which Conifers, such as pinus densiflora, myriopathes japonica, pinus koraiensis, and Pinus parviflora are infected by pine wilt nematodes, and started in North America and spread to Europe and Asia including Korea, causing enormous damage to forest resources. In particular, due to recent rapid climate change such as global warming and drought, the spread is accelerating. Recently, with the development of unmanned aerial vehicle (UAV) operations, forecasting through early detection of infected trees is being introduced. Especially, the rapid development of artificial neural networks in the imaging fields is increasing the possibility of automatically detecting infected trees by using UAVs and many recent studies are challenging it. In this study, we propose a method for automatically detecting the infected treesorthophotos taken by UAVs by employing image-based artificial neural networks, which has been showing excellent performance in detection. Also, through experiments, we show that the proposed method is effective in forecasting the infected trees.