Optimization of airborne lidar parameters for forest carbon stock estimation
森林碳储量估算的机载激光雷达参数优化

摘要

森林碳储量估算对量化生态系统碳汇能力至关重要，机载激光雷达凭借高分辨率三维数据采集优势成为关键技术手段。机载激光雷达参数直接影响森林碳储量估算精度与效率，参数设置不当会导致数据冗余或信息缺失。通过系统分析激光雷达点云密度、扫描角度、飞行高度等核心参数与森林碳储量估算指标的关联，构建参数优化模型。优化后的参数组合显著提升估算准确性，为精准评估森林碳储量、制定林业碳汇政策提供技术支撑。

Abstract

Estimating forest carbon stocks is crucial for quantifying the carbon sequestration capacity of ecosystems. Airborne LiDAR (Light Detection and Ranging), with its advantage of high-resolution 3D data acquisition, has become a key technical means. The parameters of airborne LiDAR directly affect the accuracy and efficiency of forest carbon stock estimation. Improper parameter settings can lead to data redundancy or information loss. This study systematically analyzes the relationships between core parameters of LiDAR, such as point cloud density, scanning angle, and flight altitude, and forest carbon stock estimation indicators, and constructs a parameter optimization model. The optimized parameter combinations significantly improve the estimation accuracy, providing technical support for the precise assessment of forest carbon stocks and the formulation of forestry carbon sink policies.