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Diameter, height and species of 42 million trees in three European landscapes generated from field data and airborne laser scanning data

Authors

Aussenac,  Raphaël
External Organizations;

Monnet,  Jean-Matthieu
External Organizations;

Matija Klopčič,  Matija
External Organizations;

Hawryło,  Paweł
External Organizations;

Socha,  Jarosław
External Organizations;

/persons/resource/mahnken

Mahnken,  Mats
Potsdam Institute for Climate Impact Research;

/persons/resource/Martin.Gutsch

Gutsch,  Martin
Potsdam Institute for Climate Impact Research;

Cordonnier,  Thomas
External Organizations;

Vallet,  Patrick
External Organizations;

External Ressource

https://doi.org/10.5281/zenodo.7462440
(Supplementary material)

Fulltext (public)

28189oa.pdf
(Publisher version), 5MB

Supplementary Material (public)
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Citation

Aussenac, R., Monnet, J.-M., Matija Klopčič, M., Hawryło, P., Socha, J., Mahnken, M., Gutsch, M., Cordonnier, T., Vallet, P. (2023): Diameter, height and species of 42 million trees in three European landscapes generated from field data and airborne laser scanning data. - Open Research Europe, 3, 32.
https://doi.org/10.12688/openreseurope.15373.2


Cite as: https://publications.pik-potsdam.de/pubman/item/item_28189
Abstract
Ecology and forestry sciences are using an increasing amount of data to address a wide variety of technical and research questions at the local, continental and global scales. However, one type of data remains rare: fine-grain descriptions of large landscapes. Yet, this type of data could help address the scaling issues in ecology and could prove useful for testing forest management strategies and accurately predicting the dynamics of ecosystem services. Here we present three datasets describing three large European landscapes in France, Poland and Slovenia down to the tree level. Tree diameter, height and species data were generated combining field data, vegetation maps and airborne laser scanning (ALS) data. Together, these landscapes cover more than 100~000~ha and consist of more than 42 million trees of 51 different species. Alongside the data, we provide here a simple method to produce high-resolution descriptions of large landscapes using increasingly available data: inventory and ALS data. We evaluated the overall reliability of our workflow by comparing the stands dominant heights measured by ALS to those calculated from the trees we generated. Overall, the landscapes we generated are in good agreement with the landscapes they aim to reproduce.