A method of extracting height and coverage of Tetraena based on UAV images and 3D point cloud

BoMeng Li; XiaoDong Cheng; Xin Tian; ChenJie Su

doi:10.1117/12.2659279

23 November 2022 A method of extracting height and coverage of Tetraena based on UAV images and 3D point cloud

BoMeng Li, XiaoDong Cheng, Xin Tian, ChenJie Su

Proceedings Volume 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022); 1245422 (2022) https://doi.org/10.1117/12.2659279
Event: International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 2022, Hohhot, China

Abstract

The height of Tetraena mongolica Maxim is a marker to measure the growth rate and an important index to analyze its growth condition.In this study, the Tetraena in a 50m×50m size sample plot were used as the research object, and the images taken by the UAV mounted camera and the 3D point cloud data taken by the ground-based radar were used to combine the 2D data from the UAV with the 3D data from the ground-based radar. The unsupervised classification and supervised classification by support vector machine, random forest and maximum likelihood methods are performed, and the height is obtained by kriging interpolation of the point cloud data, and the image data and point cloud data are fused. Using this method, the maximum height of 0.504m and the vegetation coverage is 13.11%, which provides a new research method for the effective protection of the Tetraena.

Citation Download Citation

BoMeng Li, XiaoDong Cheng, Xin Tian, and ChenJie Su "A method of extracting height and coverage of Tetraena based on UAV images and 3D point cloud", Proc. SPIE 12454, International Symposium on Robotics, Artificial Intelligence, and Information Engineering (RAIIE 2022), 1245422 (23 November 2022); https://doi.org/10.1117/12.2659279

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