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Title:Spaceborne canopy height products should be complemented with airborne laser scanning data: toward a European canopy height model
Authors:ID Moudrý, Vítězslav (Author)
ID Remelgado, Ruben (Author)
ID Forkel, Matthias (Author)
ID Torresani, Michele (Author)
ID Vaglio Laurin, Gaia (Author)
ID Šárovcová, Eliška (Author)
ID Garcia Millan, Virginia E. (Author)
ID Fischer, Fabian Jörg (Author)
ID Jucker, Tommaso (Author)
ID Gallay, Michal (Author)
ID Kokalj, Žiga (Author)
Files:URL URL - Source URL, visit https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025EA004544
 
.pdf PDF - Presentation file, download (4,04 MB)
MD5: 3FDD640634C17DB584C823738001A91B
 
Language:English
Typology:1.03 - Other scientific articles
Organization:Logo ZRC SAZU - The Research Centre of the Slovenian Academy of Sciences and Arts
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.
Publication status:Published
Publication version:Version of Record
Publication date:07.01.2026
Year of publishing:2026
Number of pages:20 str.
Numbering:Vol. 13, issue 1
PID:20.500.12556/DiRROS-28484 New window
UDC:528.8:630*18
ISSN on article:2333-5084
DOI:10.1029/2025EA004544 New window
COBISS.SI-ID:270841347 New window
Copyright:© 2026. The Author(s)
Note:Nasl. z nasl. zaslona; Opis vira z dne 7. 3. 2026;
Publication date in DiRROS:21.03.2026
Views:46
Downloads:28
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Record is a part of a journal

Title:Earth and space science
Publisher:John Wiley & Sons
ISSN:2333-5084
COBISS.SI-ID:525114905 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0406
Name:Opazovanje Zemlje in geoinformatika

Funder:EC - European Commission
Funding programme:HE
Project number:101079310
Name:Building Bridges between Earth observation and Environmental Sciences
Acronym:EarthBridge

Funder:EC - European Commission
Funding programme:H2020
Project number:101001905
Name:Causes and consequences of forest reorganization: Towards understanding forest change
Acronym:FORWARD

Funder:EC - European Commission
Funding programme:HE
Project number:101081195
Name:Central Bohemia Mobility Programme for Excellence in Research, Innovation and Technology
Acronym:MERIT

Funder:EC - European Commission
Funding programme:HE
Project number:101060639
Name:Modern Approaches to the Monitoring of BiOdiversity
Acronym:MAMBO

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:07.01.2026
Applies to:Version of Record valid from 2026-01-07 Text and Data Mining valid from 2026-01-01

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