Objective To obtain canopy information in high canopy density forest by remote sensing images.

Method A single tree crown extraction method of UAV remote sensing image based on instance segmentation model was tested. Seven residual networks were selected for feature extraction of the model, and the single tree crowns of pure Chinese fir forests with different canopy density were extracted one by one.

Result The results showed that the average boundary AP value and mask AP value of seven instance segmentation models for canopy segmentation of low canopy density forest were 55.89% and 57.29%, respectively. The average RMSE of east-west crown width, north-south crown width and crown area parameters was 0.161, 0.179 and 0.341, respectively. The R² was 0.912, 0.918 and 0.957, respectively. The average boundary AP value of canopy segmentation and the average AP value of canopy cover of high canopy density forest were 46.00% and 44.45%, respectively. The average RMSE of east-west crown width, north-south crown width and crown area parameters was 0.479, 0.497 and 1.256, respectively. The average predicted R² was 0.806, 0.762 and 0.936, respectively.

Conclusion The extraction accuracy of each parameter is higher than the traditional survey accuracy, and this method can obtain crown information automatically, rapidly and accurately.