Lesiv, M. ORCID: https://orcid.org/0000-0001-9846-3342, Shchepashchenko, D.
ORCID: https://orcid.org/0000-0002-7814-4990, Buchhorn, M., See, L.
ORCID: https://orcid.org/0000-0002-2665-7065, Dürauer, M., Georgieva, I., Jung, M., Hofhansl, F.
ORCID: https://orcid.org/0000-0003-0073-0946, et al.
(2021).
Global forest management data at a 100m resolution for the year 2015.
10.5281/zenodo.4541512.
Abstract
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.
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