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

Author:

Aussenac RaphaëlORCID,Monnet Jean-MatthieuORCID,Klopčič Matija,Hawryło PawełORCID,Socha Jarosław,Mahnken MatsORCID,Gutsch Martin,Cordonnier Thomas,Vallet PatrickORCID

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 following an area-based approach. 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 carried out an in-depth evaluation of our workflow including, among other analyses, a leave-one-out cross validation. Overall, the landscapes we generated are in good agreement with the landscapes they aim to reproduce. In the most favourable conditions, the root mean square error (RMSE) of stand basal area (BA) and mean quadratic diameter (Dg) predictions were respectively 5.4 m2.ha-1 and 3.9 cm, and the generated main species corresponded to the observed main species in 76.2% of cases.

Funder

Horizon 2020 Framework Programme

GRAINE program of ADEME

Publisher

F1000 Research Ltd

Subject

Multidisciplinary

Reference16 articles.

1. I-maestro data: 42 million trees from three large european landscapes in france, poland and slovenia.;R Aussenac,2022

2. An analysis of transformations.;G Box;Journal of the Royal Statistical Society: Series B (Methodological).,1964

3. Forest data bank.,2020

4. The number of tree species on earth.;R Cazzolla Gatti;Proc Natl Acad Sci U S A.,2022

5. A cross‐scale assessment of productivity–diversity relationships.;D Craven;Glob Ecol Biogeogr.,2020

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