Abstract: Forest resource protection and reconstruction are key tasks in the implementation of ecological engineering in the Yellow River Basin (Gansu section),China.Accurately extracting forest cover is of great significance for the adjustment of ecological policies and sustainable environmental development in the region.Utilizing PALSAR and Landsat data from 2008 to 2018,this study establishes a forest/non-forest classification rules based on the backscatter intensity characteristics of sample data in the HH,HV,HH-HV,and HH/HV bands of PALSAR.Then with NDVImax and B7max of Landsat,the time series forest cover and driving analysis were conducted.The conclusions are as follows:(1)Our method of combining PALSAR and Landsat data to extract forests in the region,the overall accuracy and Kappa coefficient reached 95.40% and 0.87 respectively,which is more reliable than FROM-GLC,GLCF-VCF,GlobeLand30,and JAXA forest data.(2)During study period,the forest cover area has increased from 1.32×10⁴km² up to 1.98×10⁴km²,with an average annual growth rate of 0.05.(3)The stable forest areas mainly are natural forests,while the forest increase areas are close to the natural forests,mainly due to ecological engineering.The forest decrease areas are the main human activity area,and climate and overgrazing are important driving factors.Moreover,land use,soil texture,annual average rainfall and temperature,and altitude have good explanatory power on the spatial distribution of forests in the region.This article combines PALSAR and Landsat to construct classification rules for forest cover information extraction,which has high reliability and can provide basic data for the analysis of forest cover change and driving forces in the region.