Raphaël Aussenac (Author), Jean-Matthieu Monnet (Author), Matija Klopčič (Author), Paweł Hawryło (Author), Jarosław Socha (Author), Mats Mahnken (Author), Martin Gutsch (Author), Thomas Cordonnier (Author), Patrick Vallet (Author)

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.

Keywords

gozdna inventura;lasersko snemanje;forest inventory;landscape;tree-level;airborne laser scanning;downscaling;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL BF - Biotechnical Faculty
UDC: 630*58
COBISS: 184847363 Link will open in a new window
ISSN: 2732-5121
Views: 1319
Downloads: 83
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Other data

Secondary language: Slovenian
Secondary keywords: gozdna inventura;lasersko snemanje;
Type (COBISS): Article
Pages: str. 1-32
Volume: ǂVol. ǂ3
Issue: 32
Chronology: 2023
DOI: 10.12688/openreseurope.15373.2)
ID: 19700549