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Geo-Wiki: Earth Observation and Citizen Science
Published February 15, 2021 | Version 3
Dataset Open

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

Creators

  • 1. IIASA, Austria
  • 2. VITO, Belgium
  • 3. Department of Environmental Geography, Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam
  • 4. National University of Life and Environmental Sciences of Ukraine
  • 5. V.N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science
  • 6. Moore Center for Science, Conservation International, USA
  • 7. V.N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Russia
  • 8. Université des Sciences et Techniques de Masuku, Gabon
  • 9. Mongolian Forest Research Association, NGO, Mongolia
  • 10. Center of Forest Ecology and Productivity of the Russian Academy of Sciences, Russia
  • 11. Environmental GIS/RS Center, Korea University, Republic of Korea
  • 12. Department of Harbor and River Engineering, National Taiwan Ocean University, Taiwan
  • 13. National University of Life and Environmental Sciences of Ukraine, Ukraine
  • 14. West University of Timisoara, Romania
  • 15. Department of Geography, Gauhati University,India
  • 16. Natural Resources & Agricultural Engineering Department, Faculty of Agriculture, Damanhour University, Egypt
  • 17. Department of Geography, Gauhati University, Jalukbari, Guwahati, Assam 781014, India
  • 18. Abhayapuri College, Gauhati University, India
  • 19. Institute of Meteorology and Climate Research, Germany
  • 20. Department of Meteorology, COMSATS University Islamabad, Islamabad, 45550 Pakistan.
  • 21. Department of Geography, University of Wisconsin-Madison, USA
  • 22. State Enterprise "Sosnove Forestry", Ukraine
  • 23. Berezne Forestry College of National University of Water and Environmental Engineering, Ukraine
  • 24. Space Research Institute of the Russian Academy of Sciences (IKI), Russia
  • 25. USDA Forest Service, PNW Research Station, Anchorage Forestry Sciences Lab, USA

Description

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).

 

Notes

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

FAO FRA statistics VS mapped classed.csv

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