Remote sensing technology has been widely used in ecological environment monitoring in recent years. In this paper, taking the sandy land in northeastern China as an example, the maximum likelihood method and the support vector machine method are used to compare the processing results of remote sensing data. Furthermore, the evolutionary characteristics of the sandy land ecological environment in the region were analyzed. The research results show that the study area mainly consists of three parts: sandy land, grassland and water body. The extraction effect of the support vector machine method on sandy land is better than that of the maximum likelihood method. The ecological environment in the study area is divided into two stages. In recent years, the ecological environment of sandy land has been improved to a certain extent, which is due to the enhancement of human-made ecological protection awareness and the development of ecological protection measures. The important cover types that maintain ecosystem services in this region are grasslands and water bodies, which play a decisive role in improving the ecological environment and enhancing ecosystem functions. The ecological environment index of the main sandy land in the west of the study area is mainly distributed between 30 and 44, and the ecological environment index of the eastern region is mainly distributed between 44 and 80. Among the driving factors of desertification in the study area, total population, livestock carrying capacity, and cultivated land area are the main influencing factors of desertification. and the increase of annual precipitation and the decrease of annual average wind speed can alleviate land desertification to a certain extent. With the development of policies such as returning farmland to grassland, prohibiting grazing, and resting grazing, the ecological environment of sandy land can be significantly improved. This study can provide a scientific basis for the ecological environment protection and comprehensive management of sandy land.