| Title: | High-resolution Pan-European forest structure maps : an integration of earth observation and national forest inventory data |
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| Authors: | ID Miettinen, Jukka (Author)
ID Breidenbach, Johannes (Author)
ID Adame, Patricia (Author)
ID Adolt, Radim (Author)
ID Alberdi, Iciar (Author)
ID Antropov, Oleg (Author)
ID Arnarsson, Ólafur (Author)
ID Astrup, Rasmus (Author)
ID Berger, Ambros (Author)
ID Bogason, Jón (Author)
ID Krajnc, Luka (Author)
ID Skudnik, Mitja (Author) |
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| Files: |  URL - Source URL, visit https://zenodo.org/records/13143235
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| Language: | English |
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| Typology: | 2.20 - Complete scientific database of research data |
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| Organization: |  SciVie - Slovenian Forestry Institute
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| Abstract: | 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. |
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| Keywords: | European forest monitoring system, remote sensing, in-situ data, forest attribute maps |
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| Publication version: | Version of Record |
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| Place of publishing: | Genève |
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| Place of performance: | Genève |
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| Publisher: | CERN |
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| Year of publishing: | 2024 |
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| Year of performance: | 2024 |
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| Number of pages: | 1 spletni vir |
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| PID: | 20.500.12556/DiRROS-22694  |
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| UDC: | 630*58 |
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| DOI: | 10.5281/zenodo.13143235 |
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| COBISS.SI-ID: | 239681027 |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 17. 6. 2025;
Skupno št. avtorjev: 42. Avtorja iz Slovenije: Luka Krajnc, Mitja Skudnik;
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| Publication date in DiRROS: | 17.06.2025 |
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| Views: | 458 |
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| Downloads: | 141 |
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| Metadata: |    |
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