Detection of the Pine Wilt Disease Tree Candidates for Drone Remote Sensing Using Artificial Intelligence Techniques. Engineering. 2020 Vol. 6, Issue. 8, pp. 919-926. https://doi.org/10.1016/j.eng.2020.07.001 Click (a) (b) (c) (d) Pine wilt disease (PWD) has recently caused substantial pine tree losses in Republic of Korea. PWD is considered a severe problem due to the importance of pine trees to Korean people, so this problem must be handled appropriately. We used drone remote sensing techniques to detect trees with similar symptoms to trees infected with PWD. To differentiate healthy pine trees from those with PWD, we produced a landcover (LC) map from drone images collected from the villages of (a,b) Anbi and (c,d) Wonchang by classifying them using two classifier methods, artificial neural network (ANN) and support vector machine (SVM). Furthermore, compared the accuracy of two types of Global Positioning System (GPS) data, collected using drone and hand-held devices, for identifying the locations of trees with PWD. We then divided the drone images into six LC classes for each study area and found that the SVM was more accurate than the ANN at classifying trees with PWD. Continue reading...
