Global Forest Management Type Map at 10m Resolution for 2020 Part 2

This is an experimantal dataset that represents the updated version of the global forest management layer for 2015 developed by Lesiv et al. (2022). It is based on a new training dataset for the year 2020 was collected and expanded with two additional classes: rubber plantations and tree crops. The VITO team trained a hybrid classification framework combining a deep learning and pixel-based classification approaches using Sentinel-1 and Sentinel-2 imagery for the year 2020. The resulting product provides a global wall-to-wall map of forest management types at 10 m spatial resolution. The map is spit into two parts and uploaded as 2 seperate records due to the zenodo size limitations. Part 2 includes Europe, Asia, Africa, Australia and Oceania. Tree cover mask comes from the LCFM annual land cover map 2020. The map distinguishes the following classes: 0 – No tree cover; 11 - Naturally regenerating forests without any signs of management, including primary forests; 20 – Naturally regenerated forests where there are clearly visible indications of human activities, such as selective logging, shifting cultivation, etc.; 31 – Planted forest; 32 – Plantation forest ; 33 – Rubber plantation ; 40 – Oil palm plantations ; 50 – Tree crops (monoculture plantations); 53 - Agroforestry; 100- Other trees(e.g. trees in urban areas). Detailed class definitions are provided in a separate file. The modelling framework follows the methodology developed for global land cover mapping and described in the Copernicus Global Land Cover documentation. The work was funded by WRI.