Spaceborne Canopy Height Products Should Be Complemented With Airborne Laser Scanning Data: Toward a European Canopy Height Model

Abstract Measuring and mapping vegetation structure is essential for understanding the functioning of terrestrial ecosystems and for informing environmental policies. Recent years have seen a growing demand for high‐resolution data on vegetation structure, driving their prediction at fine resolutions (1–30 m) at state, continental, and global spatial extents by combining satellite data with machine learning. As these initiatives expand, it is crucial to actively discuss the quality and usability of these products. Here, we briefly summarize current efforts to map vegetation structure and show that continental‐to‐global canopy height models (CHMs) exhibit significant errors in canopy heights compared to national airborne laser scanning (ALS) data. We recommend that regions with abundant ALS data, such as Europe, prioritize using ALS‐based canopy height metrics rather than relying on less accurate predictions from satellite products. Despite variations in ALS data characteristics, such as temporal inconsistencies and differences in acquisition characteristics and classification accuracy, the generation of spatially contiguous canopy height products in raster format at fine spatial resolution is necessary and feasible. This requires coordinating efforts for data and survey harmonization, developing standardized processing pipelines and continent‐wide ALS products, and ensuring free access for research and environmental policy. We show that ALS data now cover most of Europe, with newer surveys achieving higher point densities, improving their suitability for vegetation mapping. Beyond numerous applications in forestry, ecology, and conservation, such data sets are crucial for calibrating future Earth Observation missions, making them essential for producing reliable and accurate global, fine‐resolution vegetation structure data.

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Publication Details

Journal
Earth and Space Science
Published
2026-01-01
DOI
https://doi.org/10.1029/2025ea004544
Citations
1
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
21.83

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Spaceborne Canopy Height Products Should Be Complemented With Airborne Laser Scanning Data: Toward a European Canopy Height Model

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1 citations
Earth and Space Science
Remote Sensing and LiDAR Applications
21.83
article

Spaceborne Canopy Height Products Should Be Complemented With Airborne Laser Scanning Data: Toward a European Canopy Height Model

Ruben Remelgado, Mikhail Urbazaev, Anette Eltner, Gaia Vaglio Laurin, Peter Surový, D. Rocchini, F. Fischer, Eliška Šárovcová, Žiga Kokalj, Patrick Kacic, Martin Štroner, Ján Kaňuk, Qian Song, Yousef Erfanifard, Matthias Forkel, Michal Gallay, Zlatica Melichová, Perrone Michela, S. Szabo, Jiří Šmída, Tommaso Jucker, Vítězslav Moudrý, Dominik Seidel, Stephanie Roilo, Vojtěch Barták, Marco Malavasi, Christopher R. Hakkenberg, Juan Alberto Molina‐Valero, Virginia E. Garcia Millan, László Bertalan, Anna F. Cord, Daniel Franke, Krzysztof Stereńczak, W. Daniel Kissling, Jiří Prošek, Roberto Cazzolla Gatti, Benjamin Brede, Rudolf Urban, Kateřina Gdulová, Michele Torresani
article en
1 citations

Abstract

Abstract Measuring and mapping vegetation structure is essential for understanding the functioning of terrestrial ecosystems and for informing environmental policies. Recent years have seen a growing demand for high‐resolution data on vegetation structure, driving their prediction at fine resolutions (1–30 m) at state, continental, and global spatial extents by combining satellite data with machine learning. As these initiatives expand, it is crucial to actively discuss the quality and usability of these products. Here, we briefly summarize current efforts to map vegetation structure and show that continental‐to‐global canopy height models (CHMs) exhibit significant errors in canopy heights compared to national airborne laser scanning (ALS) data. We recommend that regions with abundant ALS data, such as Europe, prioritize using ALS‐based canopy height metrics rather than relying on less accurate predictions from satellite products. Despite variations in ALS data characteristics, such as temporal inconsistencies and differences in acquisition characteristics and classification accuracy, the generation of spatially contiguous canopy height products in raster format at fine spatial resolution is necessary and feasible. This requires coordinating efforts for data and survey harmonization, developing standardized processing pipelines and continent‐wide ALS products, and ensuring free access for research and environmental policy. We show that ALS data now cover most of Europe, with newer surveys achieving higher point densities, improving their suitability for vegetation mapping. Beyond numerous applications in forestry, ecology, and conservation, such data sets are crucial for calibrating future Earth Observation missions, making them essential for producing reliable and accurate global, fine‐resolution vegetation structure data.

Earth and Space ScienceVol. 13(1)
University of Debrecen (HU), University of Bonn (DE), Technical University of Liberec (CZ), University of Sassari (IT), University of California, Los Angeles (US), Free University of Bozen-Bolzano (IT), Slovenian Academy of Sciences and Arts (SI), University of Pavol Jozef Šafárik (SK), Czech University of Life Sciences Prague (CZ), University of Tehran (IR), University of Würzburg (DE), American Society for Photogrammetry and Remote Sensing (US), University of Bristol (GB), Ospedale di Bolzano (IT), Forest Research Institute (HU), Institute of Geography (KZ), Istituto di Studi sul Mediterraneo Antico (IT), Slovak Water Management Enterprise (SK), IDEA of Development Foundation (PL), GFZ Helmholtz Centre for Geosciences (DE), Institute of Geography of the Slovak Academy of Sciences (SK), Research Centre of the Slovenian Academy of Sciences and Arts, Czech Technical University in Prague (CZ), Technical University of Munich (DE), University of Göttingen (DE), Universidad de Málaga (ES), University of Amsterdam (NL), University of Bologna (IT)
European Commission
Life in Land
Openalex Percentile: Top 3%
Remote Sensing and LiDAR Applications
21.83
DOIOpen Access PDFOpenAlex
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