ICESat-2 Performance for Terrain and Canopy Height Retrieval in Complex Mountainous Environments

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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Publication Details

Journal
Remote Sensing
Published
2025-05-30
DOI
https://doi.org/10.3390/rs17111897
Citations
3
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
2.40

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article

ICESat-2 Performance for Terrain and Canopy Height Retrieval in Complex Mountainous Environments

Qingtai Shu, Yiran Zhang, Zeyu Li, Xiao Zhang et al.
3 citations
Remote Sensing
Remote Sensing and LiDAR Applications
2.40
article

ICESat-2 Performance for Terrain and Canopy Height Retrieval in Complex Mountainous Environments

Qingtai Shu, Yiran Zhang, Zeyu Li, Xiao Zhang, Lianjin Fu, Cuifen Xia
article en
3 citations

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.

Remote SensingVol. 17(11)
Southwest Forestry University (CN)
National Aeronautics and Space Administration, National Natural Science Foundation of China
Openalex Percentile: Top 12%
Remote Sensing and LiDAR Applications
2.40
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ICESat-2 Performance for Terrain and Canopy Height Retrieval in Complex Mountainous Environments — Qingtai Shu, Yiran Zhang, et al. · Remote Sensing (2025) | TGRS Research Map | TGRS