Global Natural and Planted Forests Mapping at Fine Spatial Resolution of 30 m

The expansion of planted forests often encroaches upon natural forests, leading to numerous environmental and social problems. Mapping natural and planted forests is crucial for the monitoring, management, and conservation of these invaluable forest resources. However, global mapping of natural and planted forests at fine spatial resolution remains an unaddressed need. Here, we generated more than 70 million training samples from dense Landsat images and fed them to a random forest classifier (RF). Our dataset achieved an impressive overall accuracy of 85% when validated against reference data. (Note: 

(1) The data for artificial and natural forests is displayed on a single map as an RGB image, where green pixels represent natural forests, yellow pixels indicate artificial forests, and other pixels correspond to non-forest areas.

(2) There was an error during the upload of some tiles (specifically, tiles 300 to 400) in the first version. This portion of the data has been supplemented on the same data platform: https://doi.org/10.5281/zenodo.13759567.

(3) Our algorithm processes tiles that contain forested areas. Therefore, the nodata areas may correspond to regions with very small forest areas or no forest cover at all in tile.)