Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodo
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...
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Elsevier
2025-06-01
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340925003452 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Jukka Miettinen |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9ae5af1e835f4e62a547b28f9ea526eb |
| institution | OA Journals |
| issn | 2352-3409 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj-art-9ae5af1e835f4e62a547b28f9ea526eb2025-08-20T02:05:12ZengElsevierData in Brief2352-34092025-06-016011161310.1016/j.dib.2025.111613Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodoJukka Miettinen0Johannes Breidenbach1Patricia Adame2Radim Adolt3Iciar Alberdi4Oleg Antropov5Ólafur Arnarsson6Rasmus Astrup7Ambros Berger8Jón Bogason9Gherardo Chirici10Piermaria Corona11Giovanni D'Amico12Jiří Fejfar13Christoph Fischer14Florence Gohon15Thomas Gschwantner16Johannes Hertzler17Zsofia Koma18Kari T. Korhonen19Luka Krajnc20Nicolas Latte21Philippe Lejeune22Andrew McCullagh23Marcin Mionskowski24Daniel Moreno-Fernández25Mari Myllymäki26Mats Nilsson27Jérôme Perin28Juho Pitkänen29John Redmond30Thomas Riedel31Johannes Schumacher32Lauri Seitsonen33Laura Sirro34Mitja Skudnik35Arnór Snorrason36Radosław Sroga37Berthold Traub38Björn Traustason39Bertil Westerlund40Stephanie Wurpillot41VTT Technical Research Centre of Finland, VTT, P.O. Box 1000, FI-02044, Finland; Corresponding authors.NIBIO Norwegian Institute of Bioeconomy Research, Division of Forest and Forest Resources, Høgskoleveien 8, 1430 Ås, Norway; Corresponding authors.Institute of Forest Sciences (ICIFOR, INIA-CSIC), Crta. de A Coruña km 7.5, Madrid, E-28040, SpainForest Management Institute (UHUL), Nábřežní 1326, Brandýs nad Labem, 250 01, Czech RepublicInstitute of Forest Sciences (ICIFOR, INIA-CSIC), Crta. de A Coruña km 7.5, Madrid, E-28040, SpainVTT Technical Research Centre of Finland, VTT, P.O. Box 1000, FI-02044, FinlandLand and Forest Iceland, Mógilsá, Reykjavík, 162, IcelandNIBIO Norwegian Institute of Bioeconomy Research, Division of Forest and Forest Resources, Høgskoleveien 8, 1430 Ås, NorwayAustrian Research Centre for Forests (BFW), Seckendorff-Gudent-Weg 8, Vienna, 1131, AustriaLand and Forest Iceland, Mógilsá, Reykjavík, 162, IcelandDipartimento di Scienze e Tecnologie Agrarie, Università degli Studi di Firenze, Alimentari, Ambientali e Forestali. Via San Bonaventura 13, Firenze, 50145, ItalyCREA Research Centre for Forestry and Wood, viale Santa Margherita 80, Arezzo, 52100, ItalyDipartimento di Scienze e Tecnologie Agrarie, Università degli Studi di Firenze, Alimentari, Ambientali e Forestali. Via San Bonaventura 13, Firenze, 50145, ItalyForest Management Institute (UHUL), Nábřežní 1326, Brandýs nad Labem, 250 01, Czech RepublicSwiss Federal Research Institute WSL, Zürcherstrasse 111, Birmensdorf, CH 8903, SwitzerlandInstitut National de l'information Géographique et Forestière (IGN), Service de l'information Statistique Forestière et Environnementale, Chemin du Château des Barres, Nogent-Sur-Vernisson, 45290, FranceAustrian Research Centre for Forests (BFW), Seckendorff-Gudent-Weg 8, Vienna, 1131, AustriaThünen Institute of Forest Ecosystems, Alfred-Möller-Straße 1, Haus 41/42, Eberswalde, 16225, GermanyNIBIO Norwegian Institute of Bioeconomy Research, Division of Forest and Forest Resources, Høgskoleveien 8, 1430 Ås, NorwayNatural Resources Institute Finland (Luke), P.O. Box 2, Helsinki, FI-00791, FinlandSlovenian Forestry Institute, Večna pot 2, Ljubljana, 1000, SloveniaGembloux Agro-Bio Tech (GxABT), Forest Resource Management Unit, University of Liège (ULiège), 2 Passage des Déportés, Gembloux, 5030, BelgiumGembloux Agro-Bio Tech (GxABT), Forest Resource Management Unit, University of Liège (ULiège), 2 Passage des Déportés, Gembloux, 5030, BelgiumForest Service, Department of Agriculture, Food and the Marine, Agriculture House, Kildare Street, Dublin 2, IrelandBureau for Forest Management and Geodesy, Leśników 21, Raszyn, 05-090, PolandInstitute of Forest Sciences (ICIFOR, INIA-CSIC), Crta. de A Coruña km 7.5, Madrid, E-28040, SpainNatural Resources Institute Finland (Luke), P.O. Box 2, Helsinki, FI-00791, FinlandDepartment of Forest Resource Management, Swedish University of Agricultural Sciences (SLU), Skogsmarksgränd, Umeå, SE-901 83, SwedenGembloux Agro-Bio Tech (GxABT), Forest Resource Management Unit, University of Liège (ULiège), 2 Passage des Déportés, Gembloux, 5030, BelgiumNatural Resources Institute Finland (Luke), P.O. Box 2, Helsinki, FI-00791, FinlandForest Service, Department of Agriculture, Food and the Marine, Agriculture House, Kildare Street, Dublin 2, IrelandThünen Institute of Forest Ecosystems, Alfred-Möller-Straße 1, Haus 41/42, Eberswalde, 16225, GermanyNIBIO Norwegian Institute of Bioeconomy Research, Division of Forest and Forest Resources, Høgskoleveien 8, 1430 Ås, NorwayVTT Technical Research Centre of Finland, VTT, P.O. Box 1000, FI-02044, FinlandVTT Technical Research Centre of Finland, VTT, P.O. Box 1000, FI-02044, FinlandSlovenian Forestry Institute, Večna pot 2, Ljubljana, 1000, Slovenia; Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, Ljubljana, 1000, SloveniaLand and Forest Iceland, Mógilsá, Reykjavík, 162, IcelandBureau for Forest Management and Geodesy, Leśników 21, Raszyn, 05-090, PolandSwiss Federal Research Institute WSL, Zürcherstrasse 111, Birmensdorf, CH 8903, SwitzerlandLand and Forest Iceland, Mógilsá, Reykjavík, 162, IcelandDepartment of Forest Resource Management, Swedish University of Agricultural Sciences (SLU), Skogsmarksgränd, Umeå, SE-901 83, SwedenInstitut National de l'information Géographique et Forestière (IGN), Service de l'information Statistique Forestière et Environnementale, Chemin du Château des Barres, Nogent-Sur-Vernisson, 45290, FranceThe 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.http://www.sciencedirect.com/science/article/pii/S2352340925003452European forest monitoring systemRemote sensingIn-situ dataForest attribute maps |
| spellingShingle | 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 Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodo Data in Brief European forest monitoring system Remote sensing In-situ data Forest attribute maps |
| title | Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodo |
| title_full | Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodo |
| title_fullStr | Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodo |
| title_full_unstemmed | Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodo |
| title_short | Pan-European forest maps produced with a combination of earth observation data and national forest inventory plotsZenodo |
| title_sort | pan european forest maps produced with a combination of earth observation data and national forest inventory plotszenodo |
| topic | European forest monitoring system Remote sensing In-situ data Forest attribute maps |
| url | http://www.sciencedirect.com/science/article/pii/S2352340925003452 |
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