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

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.