Abstract: The forest area of Tibet ranks among the top in China, and the forest resources in Tibet play an important role in water conservation and ecological service. Therefore, it is of great significance to assess the assets of forest natural resources in this region. However, existing products and statistical data related to forest cover fail to meet the demands for the assessment of forest natural resource assets in this region, and it is necessary to explore a fine-scale forest classification method suitable for this region. Based on the cloud computing platform Google Earth Engine (GEE), this study constructed the temporal, spatial, spectral, and auxiliary feature sets of the forest coverage in Motuo County using the Landsat8 remote sensing images of 2015 and 2020, as well as field survey data, and the basic geographic data. Then, it conducted forest classification using the random forest (RF) and classification and regression tree (CART) algorithms. As indicated by the accuracy evaluation of the assessment results obtained using the two algorithms, the forest classification results of 2015 and 2020 obtained using the RF algorithm had relatively high accuracy, with overall classification accuracy of 0.88 and 0.87, respectively and Kappa coefficients of both greater than 0.8. The analyses of the areal and spatio-temporal characteristics of forest classification results show that: ① Motuo County had a total forest area of 34 000 km2 in 2015, with a forest cover rate of up to 84.63%, which was 2% less than that in 2020; ② The forest resources in Motuo County are dominated by broadleaved forests, which are mainly distributed in Yarlung Zangbo Grand Canyon and low-altitude areas and accounted for 72.27% and 75.37% of the total forest area in 2015 and 2020, respectively. Coniferous forests accounted for 25.96% and 23.19% of the total forest area in 2015 and 2020, respectively and are concentrated in high-altitude areas, such as the Namcha Barwa and Gyala Peri peaks. This study determined the spatio-temporal distribution of the forests in Motuo County in 2015 and 2020 by developing a spatio-temporal-spectral classification method. It can provide a reference method for calculating specific forest cover indices SDGs and fill the gap of forest data of small zones. The obtained monitoring data will provide data support for the natural asset assessment and ecological function evaluation in Motuo County.