Tai Haoyu, Rao Chuangjiang, Li Xia, Li Hongen, Li Chen
Yunnan Institute of Water and Hydropower Engineering Investigation, Design Co., Ltd, Kunming, Yunnan, China.
Yunnan Institute of Water and Hydropower Engineering Investigation, Design and Research, Kunming, Yunnan, China.
PLoS One. 2025 Aug 22;20(8):e0330768. doi: 10.1371/journal.pone.0330768. eCollection 2025.
Facing the dual challenges of global warming and carbon neutrality, forestry carbon sinks play a vital role in achieving carbon neutrality. Rubber plantations, in particular, offer significant ecological and economic co-benefits. However, the efficient and rapid acquisition of data on rubber plantations and the calculation of carbon stock remain key challenges in forestry carbon sink studies. Airborne LiDAR is a powerful tool for forest surveys, yet its inability to directly measure DBH remains a major limitation. This study seeks to address this issue. High-resolution point cloud data were collected, followed by noise removal and ground point classification. Four individual tree segmentation methods were compared, and a linear regression model based on crown diameter parameters was proposed to estimate DBH. The results indicate that the direct point cloud segmentation method achieved the highest accuracy in tree identification. The proposed linear regression model for DBH estimation effectively predicts DBH, enabling precise biomass estimation. The total biomass estimated in the study area was 592,770.57 kg (aboveground biomass: 550,336.17 kg, belowground biomass: 42,434.39 kg), with the corresponding total carbon stock estimated at 278,602.17 kg.
面对全球变暖和碳中和的双重挑战，林业碳汇在实现碳中和方面发挥着至关重要的作用。特别是橡胶种植园，具有显著的生态和经济协同效益。然而，高效快速地获取橡胶种植园数据并计算碳储量仍然是林业碳汇研究中的关键挑战。机载激光雷达是森林调查的有力工具，但其无法直接测量胸径仍是一个主要限制。本研究旨在解决这一问题。收集了高分辨率点云数据，随后进行了去噪和地面点分类。比较了四种单木分割方法，并提出了一种基于树冠直径参数的线性回归模型来估计胸径。结果表明，直接点云分割方法在树木识别中准确率最高。所提出的用于胸径估计的线性回归模型能够有效预测胸径，从而实现精确的生物量估计。研究区域估计的总生物量为592,770.57千克（地上生物量：550,336.17千克，地下生物量：42,434.39千克），相应的总碳储量估计为278,602.17千克。
