The individual tree segmentation of desert Haloxylon ammodendron forests based on UAV LiDAR

doi:10.7523/j.ucas.2024.006

Abstract

Abstract: The potential of Light Detection And Ranging (LiDAR) technology in the application of individual tree segmentation and parameter estimation in desert Haloxylon ammodendron forests has not been explored. This study uses UAV LiDAR data to extract canopy height models (CHM) at spatial resolutions of 0.1 m, 0.25 m, 0.5 m, and 1 m on different interpolation methods, and applies the CHM seed point segmentation algorithm to segment individual trees in three types of Haloxylon ammodendron plots with different growth conditions. This study evaluates the impact of spatial resolution and growth conditions on segmentation accuracy, and verifies the extraction accuracy of tree height and crown width with field measurement data. The results show that the inverse distance weighting interpolation has a higher segmentation accuracy in this study. Spatial resolution is a key factor affecting the results of individual tree segmentation, with the best segmentation results obtained at a resolution of 0.25m.Class III plots had the highest segmentation accuracy, which was 27% higher than that of Class II plots and 44% higher than that of Class I sample plots. The overlapping crowns of Haloxylon ammodendron in plot I make it difficult to distinguish the crown boundaries, while the independent crowns in plot III make it easier to achieve accurate segmentation. The R² of the tree height fitting model for all three types of plots is around 0.80, with RMSE less than 0.31 m. The R² of the canopy extraction fit for the Class I and II plots is around 0.70, with a slightly higher RMSE error, and the branches in a half dead state of Haloxylon ammodendron in plot III affect the extraction accuracy of crown width. This study demonstrates that LiDAR data has great potential for individual tree segmentation in desert Haloxylon ammodendron forests, which can provide data support for desert forests carbon sink estimation in Xinjiang.

Key words: Desert shrub, LiDAR, spatial resolution, morphological structure, carbon sink

CLC Number:

S771.8

XIONG Shimei, XU Wenqiang, BAO Anming, WANG Zhengyu, TAO Zefu. The individual tree segmentation of desert Haloxylon ammodendron forests based on UAV LiDAR[J]. Journal of University of Chinese Academy of Sciences, DOI: 10.7523/j.ucas.2024.006.

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