HorizonEurope PathFinder
Published July 31, 2024 | Version v1
Dataset Open

High-Resolution Pan-European Forest Structure Maps: An Integration of Earth Observation and National Forest Inventory Data

Creators

  • 1. ROR icon VTT Technical Research Centre of Finland
  • 2. ROR icon Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria
  • 3. Forest Management Institute_UHUL
  • 4. Land_and forest Iceland
  • 5. ROR icon Norwegian Institute of Bioeconomy Research
  • 6. ROR icon Austrian Research Centre for Forests
  • 7. ROR icon University of Florence
  • 8. ROR icon Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria
  • 9. ROR icon Swiss Federal Institute for Forest, Snow and Landscape Research
  • 10. National Institute of_Geographic_and_Forest_Information
  • 11. ROR icon Johann Heinrich von Thünen-Institut
  • 12. ROR icon Natural Resources Institute Finland
  • 13. ROR icon Slovenian Forestry Institute
  • 14. ROR icon Gembloux Agro-Bio Tech
  • 15. Department_of_Agriculture,Food_and_the_Marine
  • 16. Bureau for Forest_Management_and_Geodesy
  • 17. ROR icon Swedish University of Agricultural Sciences
  • 18. Irish Department_of_Agriculture,_Food_and_the_Marine
  • 19. ROR icon University of Ljubljana
  • 20. Land and forest_Iceland

Description

We developed Pan-European maps of timber volume (V), above-ground biomass (AGB), and deciduous-coniferous proportion (DCP) with a pixel size of 10 x 10 m2 for the reference year 2020 using a combination of a Sentinel 2 mosaic, Copernicus layers, and National Forest Inventory (NFI) data.

For mapping, we used the k-Nearest Neighbor (kNN, k=7) approach with a harmonized database of species-specific V and AGB from 14 NFIs across Europe. This database encompasses approximately 151,000 sample plots, which were intersected with the above-mentioned Earth observation data. 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 % the South-Eastern area.

The created maps are the first of their kind as they are utilizing a huge amount of harmonized NFI 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 V and AGB values tend to be underestimated. Summarizing map values (pixel counting) over large regions such as countries or whole Europe will consequently result in biased estimates that need to be interpreted with care.

The author list is sorted by last name except for the first and last authors who also serve as corresponding authors.

Corresponding authors: Jukka.Miettinen@vtt.fi, Johannes.Breidenbach@nibio.no

Files

PathFinder maps Zenodo.pdf

Files (197.1 GB)

Name Size Download all
md5:3e359b86b0169a363ab2c5dd084eea29
36.9 GB Preview Download
md5:73620d0775a676d5a6fd72c55cf46401
33.1 GB Preview Download
md5:24ea95defd7374516c5cf44037ec4071
27.7 GB Preview Download
md5:fc4e13ea40bc15a29ad309258797dad3
24.5 GB Preview Download
md5:4b821fa475fa35022890414e54995d14
39.2 GB Preview Download
md5:df4b0acf94ffcbc99f16170b06e61abe
35.8 GB Preview Download
md5:4ae5fc0459421bf5f47ca5a4432e7915
1.8 MB Preview Download

Additional details

Funding

European Commission
PathFinder - Towards an Integrated Consistent European LULUCF Monitoring and Policy Pathway Assessment Framework. 101056907