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Global forest management data for 2015 at a 100 m resolution

Myroslava Lesiv, Dmitry Schepaschenko, Marcel Buchhorn, Linda See, Martina Dürauer, Ivelina Georgieva, Martin Jung, Florian Hofhansl, Katharina Schulze, Andrii Bilous, Volodymyr Blyshchyk, Liudmila Mukhortova, Carlos Luis Muñoz Brenes, Leonid Krivobokov, Stephan Ntie, Khongor Tsogt, Stephan Alexander Pietsch, Elena Tikhonova, Moonil Kim, Fulvio Di Fulvio, Yuan-Fong Su, Roma Zadorozhniuk, Flavius Sorin Sirbu, Kripal Panging, Svitlana Bilous, Sergii B. Kovalevskii, Florian Kraxner, Ahmed Harb Rabia, Roman Vasylyshyn, Rekib Ahmed, Petro Diachuk, Serhii S. Kovalevskyi, Khangsembou Bungnamei, Kusumbor Bordoloi, Andrii Churilov, Olesia Vasylyshyn, Dhrubajyoti Sahariah, Anatolii P. Tertyshnyi, Anup Saikia, Žiga Malek, Kuleswar Singha, Roman Feshchenko, Reinhard Prestele, Ibrar ul Hassan Akhtar, Kiran Sharma, Galyna Domashovets, Seth A. Spawn-Lee, Oleksii Blyshchyk, Oleksandr Slyva, Mariia Ilkiv, Oleksandr Melnyk, Vitalii Sliusarchuk, Anatolii Karpuk, Andrii Terentiev, Valentin Bilous, Kateryna Blyshchyk, Maxim Bilous, Nataliia Bogovyk, Ivan Blyshchyk, Sergey Bartalev, Mikhail Yatskov, Bruno Smets, Piero Visconti, Ian Mccallum, Michael Obersteiner, Steffen Fritz

Scientific Data, 9

May 10, 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 ( 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.

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Lesiv, M., Schepaschenko, D., Buchhorn, M., See, L., Dürauer, M., Georgieva, I., Jung, M., Hofhansl, F., Schulze, K., Bilous, A., Blyshchyk, V., Mukhortova, L., Brenes, C. L. M., Krivobokov, L., Ntie, S., Tsogt, K., Pietsch, S. A., Tikhonova, E., Kim, M., … Fritz, S. (2022). Global forest management data for 2015 at a 100 m resolution. Scientific Data, 9(1).