School of Information Engineering;
Zhejiang A&F University;
Hangzhou 311300;
People’s Republic of China;
Key Laboratory of State Forestry and Grassland Administration on Forestry Sensing Technology and Intelligent Equipment;
Hangzhou 311300;
People’s Republic of China;
Zhejiang Provincial Key Laboratory of Forestry Intelligent Monitoring and Information Technology;
Hangzhou 311300;
People’s Republic of China;
Urban forest; Unmanned aerial vehicle(UAV); Convolutional neural network; Tree species classification; RGB optical images;