Comparison of three global canopy height maps and their applicability to biodiversity modeling: Accuracy issues revealed
Open accessAbstract
Global mapping of forest height is an extremely important task for estimating habitat quality and modeling biodiversity. Recently, three global canopy height maps have been released, the global forest canopy height map (GFCH), the high-resolution canopy height model of the Earth (HRCH), and the global map of tree canopy height (GMTCH). Here, we assessed their accuracy and usability for biodiversity modeling. We examined their accuracy by comparing them with the reference canopy height models derived from airborne laser scanning (ALS). Our results show considerable differences between the evaluated maps. The root mean square error ranged between 10 and 18 m for GFCH, 9–11 m for HRCH, and 10–17 m for GMTCH, respectively. GFCH and GMTCH consistently underestimated the height of all canopies regardless of their height, while HRCH tended to overestimate the height of low canopies and underestimate tall canopies. Biodiversity models using predicted global canopy height maps as input data are sufficient for estimating simple relationships between species occurrence and canopy height, but their use leads to a considerable decrease in the discrimination ability of the models and to mischaracterization of species niches where derived indices (e.g., canopy height heterogeneity) are concerned. We showed that canopy height heterogeneity is considerably underestimated in the evaluated global canopy height maps. We urge that for temperate areas rich in ALS data, activities should concentrate on harmonizing ALS canopy height maps rather than relying on modeled global products.
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- Melin M., 2017, Lidar for Ecology and Conservation
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- Moudrý, V., Gábor, L., Marselis, S., Pracná, P., Barták, V., Prošek, J., Navrátilová, B., Novotný, J., Potůčková, M., Gdulová, K., Crespo‐Peremarch, P., Komárek, J., Malavasi, M., Rocchini, D., Ruiz, L. A., Torralba, J., Torresani, M., Cazzolla Gatti, R., & Wild, J.
- Affiliations
- Czech University of Life Sciences Prague (CZ)
- Leiden University (NL)
- Czech Academy of Sciences, Global Change Research Institute (CZ)
- Charles University (CZ)
- Universitat Politècnica de València (ES)
- University of Sassari (IT)
- Geo‐Environmental Cartography and Remote Sensing Group (CGAT), Department of Cartographic Engineering Universitat Politècnica de València València Spain
- Free University of Bozen-Bolzano (IT)
- BIOME Lab, Department of Biological, Geological and Environmental Sciences Alma Mater Studiorum University of Bologna Bologna Italy
- Corresponding author
- Moudrý, Vítězslav
- ORCID
- Venue
- Ecosphere
- Publisher
- Wiley
- Published
- 2024-10
- Volume
- 15
- Issue
- 10
- ISSN
- 2150-8925 (ISSN-L)
- OpenAlex
- W4403404153
- Semantic Scholar
- 9d3d3541e36667beb39c00f563c4e4b068066543
- Cited by
- 43
- References
- 88
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- 2026: 22 · 2025: 19 · 2024: 2
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- 11.27
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- journal article
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- en
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- gold
- doi.org
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- Locations
- Ecosphere (publishedVersion, cc-by)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UnissResearch (Università degli Studi di Sassari) (submittedVersion)
- Open Research (University of Surrey) (submittedVersion, other-oa)
- Funders
- Akademie Věd České Republiky (RVO 67985939)
- HORIZON EUROPE Framework Programme (101079310)
- European Commission
- Topics
- Physical Sciences › Environmental Science › Environmental Engineering › Remote Sensing and LiDAR Applications
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Forest ecology and management
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Keywords
- forest canopy height, airborne laser scanning, map accuracy assessment, biodiversity modelling, species occurrence records, species niche, habitat quality, temperate forests
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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