Tree canopy delineation using UAV multispectral imagery

doi:10.13474/j.cnki.11-2246.2022.0213

Abstract

Abstract: As one of the main components of trees,the canopy is an important parameter for tree growth and tree species identification, which is of great significance to forest resource survey and ecological research. Compared with traditional field surveys, UAV remote sensing technology is more efficient and convenient. This paper is based on UAV multi-spectral image for canopy extraction. We use local maximum algorithm and Mean Shift optimization for tree detection, whose detection accuracy is about 10% higher than the local maximum method. In addition, we design a new tree canopy delineation algorithm,which use dynamic programming algorithm to extract the global optimal boundary. Compared with the watershed segmentation algorithm, the proposed method has better results in sparse or denser forest. The F-score is increased by 12% in the sparse, and the F-score is increased by 28% in the desne.

Key words: UAV, multi-spectral, tree canopy delineation, dynamic programming

CLC Number:

P237

RAN Chongxian, LI Senlei. Tree canopy delineation using UAV multispectral imagery[J]. Bulletin of Surveying and Mapping, 2022, 0(7): 112-117.

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