1. Global forest management data at a 100m resolution for the year 2015
- Author
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Lesiv, M., Shchepashchenko, D., Buchhorn, M., See, L., Dürauer, M., Georgieva, I., Jung, M., Hofhansl, F., Schulze, K., Bilous, A., Blyshchyk, V., Mukhortova, L., Brenes, C., Krivobokov, L., Ntie, S., Tsogt, K., Pietsch, S., Tikhonova, E., Kim, M., Di Fulvio, F., Su, Y.-F., Zadorozhniuk, R., Sirbu, F.S., Pangin, K., Bilous, S., Kovalevskii, S.B., Kraxner, F., Rabia, A., Vasylyshyn, R., Ahmed, R., Diachuk, P., Kovalevskyi, S., Bungnamei, K., Bordoloi, K., Churilov, A., Vasylyshyn, O., Sahariah, D., Tertyshnyi, A., Saikia, A., Malek, Ž., Singha, K., Feshchenko, R., Prestele, R., ul Hassan Akhtar, I., Sharma, K., Domashovets, G., Spawn-Lee, S., Blyshchyk, O., Slyva, O., Ilkiv, M., Melnyk, O., Sliusarchuk, V., Karpuk, A., Terentiev, A., Bilous, V., Blyshchyk, K., Bilous, M., Bogovyk, N., Blyshchyk, I., Bartalev, S., Yatskov, M., Smets, B., Visconti, P., McCallum, I., Obersteiner, M., Fritz, S., Lesiv, M., Shchepashchenko, D., Buchhorn, M., See, L., Dürauer, M., Georgieva, I., Jung, M., Hofhansl, F., Schulze, K., Bilous, A., Blyshchyk, V., Mukhortova, L., Brenes, C., Krivobokov, L., Ntie, S., Tsogt, K., Pietsch, S., Tikhonova, E., Kim, M., Di Fulvio, F., Su, Y.-F., Zadorozhniuk, R., Sirbu, F.S., Pangin, K., Bilous, S., Kovalevskii, S.B., Kraxner, F., Rabia, A., Vasylyshyn, R., Ahmed, R., Diachuk, P., Kovalevskyi, S., Bungnamei, K., Bordoloi, K., Churilov, A., Vasylyshyn, O., Sahariah, D., Tertyshnyi, A., Saikia, A., Malek, Ž., Singha, K., Feshchenko, R., Prestele, R., ul Hassan Akhtar, I., Sharma, K., Domashovets, G., Spawn-Lee, S., Blyshchyk, O., Slyva, O., Ilkiv, M., Melnyk, O., Sliusarchuk, V., Karpuk, A., Terentiev, A., Bilous, V., Blyshchyk, K., Bilous, M., Bogovyk, N., Blyshchyk, I., Bartalev, S., Yatskov, M., Smets, B., Visconti, P., McCallum, I., Obersteiner, M., and Fritz, S.
- 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.
- Published
- 2021