Automatic counting of Paulownia trees using unmanned aerial vehicle images and template matching technique

Paulownia has gained recognition as one of the swiftest-growing tree species globally and is used for medicinal, ornamental and timber purposes. The current conventional method of Paulownia tree counting is based on the ground manual survey which is timeconsuming. Therefore, the main objective of this study was to develop a suitable model for Paulownia tree counting using template matching and unmanned aerial vehicle imageries. First, the suitable template matching method was identified by comparing the performance of template matching with georeferencing data and template matching with the predetermined size of the template image. It was then followed by the development of an automatic Paulownia tree detection and counting model using the most suitable template matching technique at 4 different growing stages which are 3, 6, 9 and 12 months old. Results have shown that the template matching with georeferencing data performed better compared with the template matching with the predetermined size of the template image. For different growing stage models, the 3 and 6-month-old Paulownia tree models perform better compared to the others with an average F1-score of more than 85%. Results also revealed that younger Paulownia present greater homogeneity in crown morphology thus making it easier for the algorithm to detect Paulownia tree at younger age.