Early Detecting Damaged Trees by Pine Wilt Disease Using DI(Detection Index) from Portable Near Infrared Camera
2011
Kim, M.I., Korea University, Seoul, Republic of Korea | Lee, W.K., Korea University, Seoul, Republic of Korea | Kwon, T.H., Korea University, Seoul, Republic of Korea | Kwak, D.A., Korea University, Seoul, Republic of Korea | Kim, Y.S., Sundosoft Inc., Seoul, Republic of Korea | Lee, S.H., Korea Forest Research Institute, Seoul, Republic of Korea
The purpose of this study is to examine the possibility of early detection of Pine Wilt Disease (PWD) using NDVI (Normalized Difference Vegetation Index) from ADC (Agricultural Digital Camera) imageries. The PWD induces the different patterns of reduction of NDVI between healthy trees and infected trees, due to the withered leaves on the infected trees. Based on these phenomena, the DI showing the NDVI variations of trees by time series was employed to detect the infected trees. To find out the differences of DI level between normal and infected trees, DIs of trees from May to August in 2007 were calculated and these were analyzed with GLM (General Linear Models) in SAS 9.2. As a result, the difference of DI between in June and August shows the most significant level (0.0001). The discriminant analysis was performed between normal and infected trees, using the DI of June and August. As the result, hit ratio of trees and the accuracy of grouping with Jack-knife method were shown 71.9% and 73.5%, respectively. These results showed that the DI is effective to detect the trees infected by the PWD and it is useful to prevent the PWD.
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