This project uses machine learning in combination with radar and optical remote sensing observations to map tree species in Sweden. The microwave radiation emitted by the Sentinel-1 satellite can penetrate through the top of the forest canopy and provide information about the structure of the trees. The sensor aboard the Sentinel-2 satellite can capture sunlight reflected from the Earth across a wide spectrum of wavelengths. This includes wavelengths from the "red edge" portion of the electromagnetic spectrum, which is sensitive to the chlorophyll content in vegetation and thus helps differentiate between different tree species. These two satellites complement each other and help improve tree species identification. By using machine learning in combination with these complementary data sources, this project will break new ground in the large-scale determination of tree species in Sweden. Overall, this will lead to an operational process where satellite data and machine learning alone are sufficient to regularly provide maps of tree species distribution in the country.