As one of the driest and lowest regions in Asia, the vegetation variation in the Aydingkol Lake Basin in Xinjiang, China, reveals the status of its ecological recovery. To more accurately retrieve the fractional vegetation index (FVC) to investigate the vegetation variation in this basin, we proposed an innovative method—the random forest (RF) method—based on multiple remote sensing indices. The retrieval shows a satisfactory accuracy with a mean error, mean square error, mean relative error (RE) percentage, and determination coefficient of 0.01,0.04,14.61% and 0.95, respectively. In the Aydingkol Lake Basin, the average annual FVC peaked in 2015 with a value of 0.08. The annual average value of FVC decreases at a rate of 0.06  *  10^−  2  /  a during these eight years. The reduction of FVC is mainly distributed in the central-western part of the basin. In exploring the influence on FVC, average annual precipitation has the most significant impact on the FVC. Its correlation coefficient with FVC is 0.87. With increasing elevation and slope, most FVC showed a decreasing trend. In recent years, the conversion of cropland to barren land and cropland to grassland had the greatest impact on decreasing of the FVC, and the mean FVC decreases from 0.19 to 0.17 before and after the land-use change. Moreover, human impact had a significant influence on the variation in FVC. Due to the establishment of the Aydingkol Lake Basin Wetland Reserve (the SAIC Volkswagen Test Site), the annual average FVC in the corresponding place increases from 0.06 to 0.13 (decreases from 0.148 to 0.005). This study is helpful to guide ecological protection in similar arid regions.