Pan-European forest maps produced with a combination of earth observation data and national forest inventory plots
Year: 2025
Type: data-paper
Abstract: The dataset includes Pan-European maps of timber volume (Vol), above-ground biomass (AGB), and deciduous-coniferous proportion (DCP) with a pixel size of 10×10 m for the reference year 2020. In addition, a measure of prediction uncertainty is provided for each pixel. The maps have been created using a combination of a Sentinel-2 mosaic, Copernicus layers, and National Forest Inventory (NFI) data. The mapping was done with the k-Nearest Neighbour (kNN, k=7) approach with harmonized data of species-specific Vol and AGB from 14 NFIs consisting of approximately 151 000 field plots across Europe. The maps cover 40 European countries, forming a continuous coverage of the western part of the European continent. A sample of 1/3 of NFI plots was left out for validation, whereas 2/3 of the plots were used for mapping. Maps were created independently for 13 multi-country processing areas. Root-mean-squared-errors (RMSEs) for AGB ranged from 53 % in the Nordic processing area to 73 % in the South-Eastern area. The maps are on average nearly unbiased on European level (1.0 % of the mean AGB), but show significant overestimation for small biomass values (53 % bias for forests with AGB less than 150 t/ha) and underestimation for high biomass values (-55 % bias for forests with AGB higher than 500 t/ha). The created maps are the first of their kind as they are utilizing a large number of harmonized NFI plot observations and consistent remote sensing data for high-resolution forest attribute mapping. While the published maps can be useful for visualization and other purposes, they are primarily meant as auxiliary information in model-assisted estimation where model-related biases can be mitigated, and field-based estimates improved. Therefore, additional calibration procedures were not applied, and especially high Vol and AGB values tend to be underestimated. We therefore discourage from summarizing map values (pixel counting) over areas in interest, as this may inadvertently result in biased estimates.
Source: Data in Brief
Authors: Jukka Miettinen, Johannes Breidenbach, Patricia Adame, Radim Adolt, Iciar Alberdi, Oleg Antropov, Ólafur Arnarsson, Rasmus Astrup, Ambros Berger, Jón Bogason, Gherardo Chirici, Piermaria Corona, Giovanni D'Amico, Jiří Fejfar, Christoph Fischer, Florence Gohon, Thomas Gschwantner, Johannes Hertzler, Zsofia Koma, Kari T. Korhonen, Luka Krajnc, Nicolas Latte, Philippe Lejeune, Andrew McCullagh, Marcin Mionskowski, Daniel Moreno-Fernández, Mari Myllymäki, Mats Nilsson, Jérôme Perin, Juho Pitkänen, John Redmond, Thomas Riedel, Johannes Schumacher, Lauri Seitsonen, Laura Sirro, Mitja Skudnik, Arnór Snorrason, Radosław Sroga, Berthold Traub, Björn Traustason, Bertil Westerlund, Stephanie Wurpillot
Institutions: VTT Technical Research Centre of Finland, Norwegian Institute of Bioeconomy Research, Consejo Superior de Investigaciones Científicas, Instituto de Ciencias Forestales, Land and Forest Iceland, Austrian Research Centre for Forests, University of Florence, Forestry Research Centre, Swiss Federal Institute for Forest, Snow and Landscape Research, Institut national de l’information géographique et forestière, Johann Heinrich von Thünen-Institut, Natural Resources Institute Finland, Slovenian Forestry Institute, University of Liège, Gembloux Agro-Bio Tech, Department of Agriculture Food and the Marine, Swedish University of Agricultural Sciences, University of Ljubljana
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $1,220
Award: G7171096698
OpenAlex ID: W4410113828