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무인항공기(UAV) 영상을 이용한 소나무재선충병 의심목 탐지
이슬기 ( Seulki Lee ),박성재 ( Sung-jae Park ),백경민 ( Gyeongmin Baek ),김한별 ( Hanbyeol Kim ),이창욱 ( Chang-wook Lee ) 대한원격탐사학회 2019 大韓遠隔探査學會誌 Vol.35 No.3
Bursaphelenchus xylophilus (Pine wilt disease) is a serious threat to the pine forest in Korea. However, dead wood observation by Pine wilt disease is based on field survey. Therefore, it is difficult to observe large-scale forests due to physical and economic problems. In this paper, high resolution images were obtained using the unmanned aerial vehicle (UAV) in the area where the pine wilt disease recurred. The damaged tree due to pine wilt disease was detected using Artificial Neural Network (ANN), Support Vector Machine (SVM) supervision classification technique. Also, the accuracy of supervised classification results was calculated. After conducting supervised classification on accessible forests, the reliability of the accuracy was verified by comparing the results of field surveys.