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Estimation of Diameter at Breast Height in Tropical Forests Based on Terrestrial Laser Scanning and Shape Diameter Function

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  • Yang Wu

    (College of Biodiversity Conservation, Southwest Forestry University, Kunming 650224, China)

  • Xingli Gan

    (School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China)

  • Ying Zhou

    (College of Biodiversity Conservation, Southwest Forestry University, Kunming 650224, China)

  • Xiaoyu Yuan

    (School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China)

Abstract

Estimating forest carbon content typically requires the precise measurement of the trees’ diameter at breast height (DBH), which is crucial for maintaining the health and sustainability of natural forests. Currently, Terrestrial Laser Scanning (TLS) systems are commonly used to acquire forest point cloud data for DBH estimation. However, traditional circular fitting methods face challenges such as a reliance on forest elevation normalization and underfitting of large trees. This study explores a novel approach, the Shape Diameter Function (SDF) algorithm model, leveraging the advantages of three-dimensional point cloud information to replace traditional circular fitting methods. This study employed a parallel approach, combining the Digital Elevation Model (DEM) with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to segment tree point clouds at breast height. Additionally, a point cloud SDF algorithm based on an octree structure was proposed to accurately estimate individual tree DBH. The research data were obtained from tropical secondary forests located in Cameroon, Peru, Indonesia, and Guyana, with forest ground point cloud data acquired via TLS. The experimental results demonstrated the superior performance of the SDF algorithm in estimating DBH. Compared with the Random Sample Consensus (RANSAC) and Hough transform methods, the Root Mean Square Error (RMSE) decreased by 28.1% and 47.8%, respectively. Particularly in estimating DBH for large trees, the SDF algorithm exhibited smaller errors, indicating a closer alignment between the estimated individual tree DBH values and those obtained from manual measurements. This study presented a more accurate DBH estimation algorithm, contributing to the exploration of improved forest carbon content estimation methods.

Suggested Citation

  • Yang Wu & Xingli Gan & Ying Zhou & Xiaoyu Yuan, 2024. "Estimation of Diameter at Breast Height in Tropical Forests Based on Terrestrial Laser Scanning and Shape Diameter Function," Sustainability, MDPI, vol. 16(6), pages 1-14, March.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:6:p:2275-:d:1353895
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    References listed on IDEAS

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    1. Shuangmin Chen & Taijun Liu & Zhenyu Shu & Shiqing Xin & Ying He & Changhe Tu, 2018. "Fast and robust shape diameter function," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-18, January.
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