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Harmonised statistics and maps of forest biomass and increment in Europe

Avitabile, Valerio; Pilli, Roberto; Migliavacca, Mirco; Duveiller, Gregory; Camia, Andrea; Blujdea, Viorel; Adolt, Radim; Alberdi, Iciar; Barreiro, Susana; Bender, Susann; Borota, Dragan; Bosela, Michal; Bouriaud, Olivier;
GND
13586626X
Breidenbach, Johannes; Cañellas, Isabel; Čavlović, Jura; Colin, Antoine; Di Cosmo, Lucio; Donis, Janis; Fischer, Christoph; Freudenschuss, Alexandra; Fridman, Jonas; Gasparini, Patrizia; Gschwantner, Thomas; Hernández, Laura; Korhonen, Kari; Kulbokas, Gintaras; Kvist, Vivian; Latte, Nicolas; Lazdins, Andis; Lejeune, Philippe; Makovskis, Kristaps; Marin, Gheorghe; Maslo, Jan; Michorczyk, Artur; Mionskowski, Marcin; Morneau, François; Myszkowski, Marcin; Nagy, Kinga; Nilsson, Mats; Nord-Larsen, Thomas; Pantic, Damjan; Perin, Jerôme; Redmond, John; Rizzo, Maria; Šebeň, Vladimír; Skudnik, Mitja; Snorrason, Arnor; Sroga, Radosław; Stoyanov, Todor; Svensson, Arvid; Talarczyk, Andrzej; Teeuwen, Sander; Thürig, Esther; Uva, José; Mubareka, Sarah

Forest biomass is an essential resource in relation to the green transition and its assessment is key for the sustainable management of forest resources. Here, we present a forest biomass dataset for Europe based on the best available inventory and satellite data, with a higher level of harmonisation and spatial resolution than other existing data. This database provides statistics and maps of the forest area, biomass stock and their share available for wood supply in the year 2020, and statistics on gross and net volume increment in 2010–2020, for 38 European countries. The statistics of most countries are available at a sub-national scale and are derived from National Forest Inventory data, harmonised using common reference definitions and estimation methodology, and updated to a common year using a modelling approach. For those counties without harmonised statistics, data were derived from the State of Europe’s Forest 2020 Report at the national scale. The maps are coherent with the statistics and depict the spatial distribution of the forest variables at 100 m resolution.

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