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Harmonised statistics and maps of forest biomass and increment in Europe.

Valerio AvitabileRoberto PilliMirco MigliavaccaGregory DuveillerAndrea CamiaViorel BlujdeaRadim AdoltIciar AlberdiSusana BarreiroSusann BenderDragan BorotaMichal BoselaOlivier BouriaudJohannes BreidenbachIsabel CañellasJura ČavlovićAntoine ColinLucio Di CosmoJanis DonisChristoph FischerAlexandra FreudenschussJonas FridmanPatrizia GaspariniThomas GschwantnerLaura HernándezKari KorhonenGintaras KulbokasVivian Kvist JohannsenNicolas LatteAndis LazdinsPhilippe LejeuneKristaps MakovskisGheorghe MarinJan MasloArtur MichorczykMarcin MionskowskiFrançois MorneauMarcin MyszkowskiKinga NagyMats NilssonThomas Nord-LarsenDamjan PanticJerôme PerinJohn RedmondMaria RizzoVladimír ŠebeňMitja SkudnikArnor SnorrasonRadosław SrogaTodor StoyanovArvid SvenssonAndrzej TalarczykSander TeeuwenEsther ThürigJosé UvaSarah Mubareka
Published in: Scientific data (2024)
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.
Keyphrases
  • climate change
  • electronic health record
  • wastewater treatment
  • quality improvement
  • single molecule
  • machine learning
  • artificial intelligence