The Mu Us Sandy Land is a key region of man-made desert control and farmland to forest (grass) return in China. Despite global change and the strong influence of human activities, the vegetation in this region has been significantly improved and restored. In this study, multisource remote sensing data and multiple indicators were used to quantitatively monitor and evaluate the vegetation restoration status in this area. The driving factors were also analysed. The results show that in the past 20 years, nearly the entire Mu Us Sandy Land significantly and substantively recovered. The regional fractional vegetation cover increased, with an average annual growth rate of 0.59% and obvious spatial heterogeneity. The nine most important driving factors could comprehensively account for 58.38% of the spatial distribution of the vegetation coverage. Factors such as land use and land cover, the aridity index, and gross domestic product had the most significant impact, followed by precipitation and temperature. The results confirmed that the vegetation was restored and improved in the Mu Us Sandy Land and determined the main driving factors, which is helpful for vegetation restoration and ecological improvement on sandy land similar to the Mu Us Sandy Land.

The accurate habitat suitability evaluation of forest species is vital for forest resource management and conservation. Therefore, the previously published thresholds of soil organic carbon (SOC) contents for the six main forest species were used to screen sample points in this study; the maximum entropy modeling (MaxEnt) was applied to predict the potential distribution of those species in Lvliang Mountain, Shanxi Province, China. The following results were derived: (1) the area under the curve (AUC) value of the MaxEnt model was 0.905, indicating the model results had high accuracy; (2) the main environmental factors affecting the woodlands were mean diurnal temperature range, solar radiation, population density and slope; (3) the model accurately depicted the most suitable areas for those species, namely Populus davidiana Dode (Malpighiales: Salicaceae), Betula platyphylla Sukaczev (Fagales: Betulaceae), Quercus wutaishanica Mayr (Fagales: Fagaceae), Platycladus orientalis (L.) Franco (Pinales: Cupressaceae), Larix gmelinii (Rupr.) Kuzen. (Pinales: Pinaceae) and Pinus tabuliformis Carrière (Pinales: Pinaceae). This study has improved the representativeness of the samples based on prior knowledge to enhance the biological meaning and accuracy of the prediction results. Its findings provide a theoretical basis for the forest resource protection, management measures alongside the reconstruction of low-yield and low-efficiency forests.