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Global forest management data for 2015 at a 100 m resolution.

Myroslava LesivDmitry G SchepaschenkoMarcel BuchhornLinda SeeMartina DürauerIvelina GeorgievaMartin JungFlorian HofhanslKatharina SchulzeAndrii M BilousVolodymyr BlyshchykLiudmila MukhortovaCarlos Luis Muñoz BrenesLeonid KrivobokovStéphan NtieKhongor TsogtStephan Alexander PietschElena TikhonovaMoonil KimFulvio Di FulvioYuan-Fong SuRoman ZadorozhniukFlavius Sorin SirbuKripal PangingSvitlana BilousSergii B KovalevskiiFlorian KraxnerAhmed Harb RabiaRoman VasylyshynRekib AhmedPetro DiachukSerhii S KovalevskyiKhangsembou BungnameiKusumbor BordoloiAndrii ChurilovOlesia VasylyshynDhrubajyoti SahariahAnatolii P TertyshnyiAnup SaikiaŽiga MalekKuleswar SinghaRoman FeshchenkoReinhard PresteleIbrar Ul Hassan AkhtarKiran SharmaGalyna DomashovetsSeth A SpawnOleksii BlyshchykOleksandr SlyvaMariia IlkivOleksandr MelnykVitalii SliusarchukAnatolii KarpukAndrii TerentievValentin BilousKateryna BlyshchykMaxim BilousNataliia BogovykIvan BlyshchykSergey BartalevMikhail YatskovBruno SmetsPiero ViscontiIan MccallumMichael ObersteinerSteffen Fritz
Published in: Scientific data (2022)
Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki ( https://www.geo-wiki.org/ ). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.
Keyphrases
  • climate change
  • stem cells
  • healthcare
  • primary care
  • electronic health record
  • artificial intelligence
  • clinical practice