Forest canopy information extraction in Gannan Plateau based on UAV high-resolution images

Yanduo Wu; Hui Han

doi:10.1117/12.2681063

8 June 2023 Forest canopy information extraction in Gannan Plateau based on UAV high-resolution images

Yanduo Wu, Hui Han

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127072I (2023) https://doi.org/10.1117/12.2681063
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

In order to explore the feasibility of applying UAV remote sensing and object-oriented canopy extraction technology to forest areas with different canopy densities, 26 forest plots located in Gannan Plateau were selected and divided into two categories of coniferous forests with medium and high canopy densities. ESP tool was used to screen the optimal segmentation scale for multi-scale segmentation, and the feature space was optimized for object-oriented classification. The east-west and north-south crown amplitudes on quadrat scale were extracted in ArcGIS. The extracted crown amplitude was compared with the field measured data to evaluate the accuracy. The results were as follows: In UAV image extraction, the fitting values R2 and RMSE of east and west canopy width and measured values were 0.865 and 1.025m, respectively, and the fitting values R2 and RMSE of north and south canopy width were 0.867 and 1.235m, respectively. The R2 and RMSE of east and west canopy width with high canopy closure were 0.828 and 1.145m, respectively, and the R2 and RMSE of north and south canopy width were 0.787 and 1.523m, respectively. The extraction effect of the plots with medium canopy closure was better than that of the plots with high canopy closure, and both of the two canopy closure met the accuracy requirements. The results show that the automatic extraction method of canopy parameter information based on UAV remote sensing image is efficient and reliable, and has important practical significance in forest resources investigation.

Citation Download Citation

Yanduo Wu and Hui Han "Forest canopy information extraction in Gannan Plateau based on UAV high-resolution images", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127072I (8 June 2023); https://doi.org/10.1117/12.2681063

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KEYWORDS

Image segmentation

Unmanned aerial vehicles

Remote sensing

Image classification

LIDAR

Clouds

Matrices

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