Dataset Open Access

Global forest management data at a 100m resolution for the year 2015

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 Pangin; 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

We provide four data records:

1.The reference data set as a comma-separated file ("reference_data_set.csv") with the following attributes: 

  • “ID” is a unique location identifier 

  • “Latitude, Longitude” are centroid coordinates of a 100m x 100m pixel. 

  • “Land_use_ID “is a land use class: 

    • 11 - Naturally regenerating forest without any signs of human activities, e.g., primary forests.  
    • 20 - Naturally regenerating forest with signs of human activities, e.g., logging, clear cuts etc.  
    • 31 - Planted forest.  
    • 32 - Short rotation plantations for timber.  
    • 40 - Oil palm plantations.  
    • 53 - Agroforestry. 
  • “Flag” identifies a data origin:  1- the crowdsourced locations, 2- the control data set, 0 – the additional experts' classifications following the opportunistic approach.

2. The 100 m forest management map in a geoTiff format with the classes presented - "FML_v3.2.tif ".

3. The predicted class probability from the Random Forest classification in a geoTiff format - "ProbaV_LC100_epoch2015_global_v2.0.3_forest-management--layer-proba_EPSG-4326.tif"

4. Validation data set as a comma-separated file ("validation_data_set.csv) with the following attributes: 

  • “ID” is a unique location identifier 

  • “pixel_center_x” , “pixel_center_y ” are centroid coordinates of a 100m x 100m pixel  in lat/lon projection 

  • “first_landuse_class “is a land use class, as in (1). 

  • “second_landuse_class “is a second possible land use class, as in (1), identified in case it was difficult to assign one class with high confidence. 

5. Original crowdsourced data set as a .csv table.

6. Compiled FAO FRA forest statistics and mapped classes by countries into one table (.csv format).

 

NatureMap project (https://naturemap.earth/) Funder Norway's International Climate and Forest Initiative (NICFI): https://www.norad.no/en/front/thematic-areas/climate-change-and-environment/norways-international-climate-and-forest-initiative-nicfi/ This is a similar data set on zenodo (Lesiv, M. et al. Global planted trees extent 2015. Zenodo https://doi.org/10.5281/zenodo.3931930, 2020) This is the version that was used in one of the follow up studies, which was needed as a reference. Please ignore it and instead use this zenodo record.
Files (2.8 GB)
Name Size
FAO FRA statistics VS mapped classed.csv
md5:abc4661efccc36999ed30eeb44ad16d7
39.2 kB Download
FML_v3-2_with-colorbar.tif
md5:23e1e0f247e0461b348d8cb9b95c8a6f
1.6 GB Download
legend.xlsx
md5:7206130d1ae5f7f45eeeea67260dbbbc
12.0 kB Download
original_crowdsourced_data.csv
md5:47f16a33dc2760b850e5f43f1af59e56
173.6 MB Download
read_me_faofra_areas.csv
md5:e16fbcbb8fdc72cd67e729009755a5ec
834 Bytes Download
readme_original_crowdsourced_data.txt
md5:d953e174c031f480c732946065e05932
801 Bytes Download
reference_data_set_updated.csv
md5:c8659c6e2787891b9428f9aaeeb32e6a
10.8 MB Download
tiles v3.2.zip
md5:e49d5c303b0db20f1e201e9bb1966c20
968.1 MB Download
validation_data_set.csv
md5:03152c22e3de3de3d9d03ebd7ea58eb5
73.7 kB Download
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