Evaluation of GEDI for Estimating the Vertical Distribution of PAI in Temperate Forests: A Case Study of the Conterminous United States

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2025-02-17 DOI:10.1109/LGRS.2025.3542874

Duo Jia;Cangjiao Wang;Yanchen Bo

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Abstract

The vertical leaf area index (LAI) is crucial for assessing photosynthetic and carbon sequestration dynamics and atmospheric interaction within terrestrial ecosystems. The global ecosystem dynamics investigation (GEDI), the first full-waveform lidar for monitoring global forest structure, has generated a vertical plant area index (VPAI) product at 5 m intervals. This study conducts a comprehensive assessment of the accuracy of GEDI’s vertical plant area index (PAI) across temperate forests in the conterminous United States and analyzes the impact of sensor parameters on the accuracy of the VPAI to provide insights for the optimal application of GEDI’s capabilities. The results show that GEDI can offer reliable layered PAI for heights exceeding 10 m. Substantial inaccuracies across various forest types were observed in layers of 5–10 m, with the worst accuracy observed in mixed forests. The impact of GEDI sensor parameters varies across different layers of PAI with GEDI’s Power beam being more accurate than its Coverage beam in layered PAI below 20 m; night observations are more accurate but also less available than day observations. A significant negative correlation between the signal-to-noise ratio (SNR) and errors of layered PAI exists below 15 m. Prioritizing the use of the Power beam and weighting the GEDI footprint based on the SNR for layers within 15 m, are recommended ways to improve the accuracy of the subsequent layered PAI mapping.

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垂直叶面积指数（LAI）对于评估陆地生态系统的光合作用和碳封存动态以及大气相互作用至关重要。全球生态系统动态调查（GEDI）是首个用于监测全球森林结构的全波形激光雷达，它生成了一个间隔为 5 米的垂直植物面积指数（VPAI）产品。本研究对美国大陆温带森林中 GEDI 垂直植物面积指数 (PAI) 的准确性进行了全面评估，并分析了传感器参数对 VPAI 准确性的影响，从而为 GEDI 功能的最佳应用提供启示。结果表明，GEDI 可以为超过 10 米的高度提供可靠的分层 PAI。在 5-10 米的层中，各种森林类型都观察到了严重的不准确性，在混交林中观察到的准确性最差。GEDI 传感器参数对不同层 PAI 的影响各不相同，在 20 米以下的层 PAI 中，GEDI 的 "功率 "光束比 "覆盖 "光束更准确；夜间观测比白天观测更准确，但可用性也更差。在 15 米以下，信噪比（SNR）与分层 PAI 的误差之间存在明显的负相关。优先使用功率波束，并根据 15 米以内各层的信噪比对 GEDI 的足迹进行加权，是提高后续分层 PAI 测绘精度的建议方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society

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