Performance Evaluation of ICESat-2 Laser Altimetry Data in Topographic and Canopy Height Retrieval Under Complex Terrain and Diverse Vegetation Conditions

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Abstract

Accurate estimation of forest canopy height and understory terrain in mountainous regions is crucial for carbon stock assessment under the Paris Agreement but remains challenging. This study aimed to evaluate ICESat-2's performance in these complex environments. To achieve this, ICESat-2 ATL03 Version 6 photon data were processed using a novel adaptive DBSCAN algorithm (BDT-ADBSCAN) in Pu'er City, China, a biodiversity hotspot, and results were validated against airborne LiDAR. ICESat-2 achieved high terrain retrieval accuracy (R2=1.00, RMSE=0.91 m), primarily affected by slope, while canopy height retrieval was less accurate (R2=0.53, RMSE=6.45 m) with systematic underestimation, mainly influenced by canopy height itself. Nighttime strong beam acquisitions substantially improved accuracies for both products. This research demonstrates ICESat-2's viability for high-resolution digital terrain modeling and provides quality control thresholds for forest structure estimation in challenging regions, addressing validation gaps in Asian biodiversity hotspots and supporting carbon monitoring for UN Sustainable Development Goals.

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