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<p>Accurate mapping of vegetation canopy height and biomass distribution is essential for effective forest monitoring, climate change mitigation, and sustainable forestry. Here we present high-resolution remote sensing-based canopy height (10 m resolution) and above ground biomass (AGB, 50 m resolution) maps for the forests of the Iberian Peninsula from 2017 to 2021, using a deep learning framework that integrates Sentinel-1, Sentinel-2, and LiDAR data. Two UNET models were developed: one trained on Airborne Laser Scanning (ALS) data (MAE: 1.22 m), while another using Global Ecosystem Dynamics Investigation (GEDI) footprints (MAE: 3.24 m). External validation with 6,308 Spanish National Forest Inventory (NFI) plots (2017–2019) confirmed canopy height reliability, showing MAEs of 2–3 m in tree-covered areas. AGB estimates were obtained through Random Forest models that linked UNET derived height predictions to NFI AGB data, achieves an MAE of ~29 Mg/ha. The creation of high-resolution maps of canopy height and biomass across various forest landscapes in the Iberian Peninsula provides a valuable new tool for environmental researchers, policy makers, and forest management professionals, offering detailed insights that can inform conservation strategies, carbon sequestration efforts, and sustainable forest management practices.</p>

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Canopy height and biomass distribution across the forests of Iberian Peninsula

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月22日

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  • Yang Su,
  • Martin Schwartz,
  • Ibrahim Fayad,
  • Mariano García,
  • Miguel A. Zavala,
  • Julián Tijerín-Triviño,
  • Julen Astigarraga,
  • Verónica Cruz-Alonso,
  • Siyu Liu,
  • Xianglin Zhang,
  • Songchao Chen,
  • François Ritter,
  • Nikola Besic,
  • Alexandre d’Aspremont,
  • Philippe Ciais

摘要

Accurate mapping of vegetation canopy height and biomass distribution is essential for effective forest monitoring, climate change mitigation, and sustainable forestry. Here we present high-resolution remote sensing-based canopy height (10 m resolution) and above ground biomass (AGB, 50 m resolution) maps for the forests of the Iberian Peninsula from 2017 to 2021, using a deep learning framework that integrates Sentinel-1, Sentinel-2, and LiDAR data. Two UNET models were developed: one trained on Airborne Laser Scanning (ALS) data (MAE: 1.22 m), while another using Global Ecosystem Dynamics Investigation (GEDI) footprints (MAE: 3.24 m). External validation with 6,308 Spanish National Forest Inventory (NFI) plots (2017–2019) confirmed canopy height reliability, showing MAEs of 2–3 m in tree-covered areas. AGB estimates were obtained through Random Forest models that linked UNET derived height predictions to NFI AGB data, achieves an MAE of ~29 Mg/ha. The creation of high-resolution maps of canopy height and biomass across various forest landscapes in the Iberian Peninsula provides a valuable new tool for environmental researchers, policy makers, and forest management professionals, offering detailed insights that can inform conservation strategies, carbon sequestration efforts, and sustainable forest management practices.