Based on the fractional vegetation cover (FVC) data of 1982-2000 NOAA/AVHRR (National Oceanic and Atmospheric Administration/ the Advanced Very High Resolution Radiometer) images, the whole arid area of Northwest China was divided into three sub-areas, and then, the vegetation cover in each sub-area was classified by altitude. Furthermore, the Markov process of vegetation cover change was analyzed and tested through calculating the limit probability of any two years and the continuous and interval mean transition matrixes of vegetation cover change with 8 km x 8 km spatial resolution. By this method, the Markov process of vegetation cover change and its indicative significance were approached. The results showed that the vegetation cover change in the study area was controlled by some random processes and affected by long-term stable driving factors, and the transitional change of vegetation cover was a multiple Markov process. Therefore, only using two term image data, no matter they were successive or intervallic, Markov process could not accurately estimate the trend of vegetation cover change. As for the arid area of Northwest China, more than 10 years successive data could basically reflect all the factors affecting regional vegetation cover change, and using long term average transition matrix data could reliably simulate and predict the vegetation cover change. Vegetation cover change was a long term dynamic balance. Once the balance was broken down, it should be a long time process to establish a new balance.