Abstract: As an important energy base in China, understanding the vegetation change trends in the HuainanMinging Area is of great significance for the ecological protection and high-quality development of the mining area. Based on the Landsat 8 SR dataset from the Google Earth Engine platform, methods such as band calculation, coefficient of variation, trend analysis, and spatial autocorrelation were used to analyze the vegetation change trends in the Huainan Mining Area over the past decade. The results indicate that, compared to the traditional NDVI, the kNDVI demonstrates a lower coefficient of variation in monitoring vegetation changes, providing more stable monitoring outcomes.According to the kNDVI monitoring results, from 2013 to 2023, a total of 408.43 km²（approximately 64.08%） of the area in the Huainan Mining Area showed an improving trend in vegetation. Among these, the vegetation growth rates in Gubei Mine, Dingji Mine, Xieqiao Mine, and Pansidong Mine significantly exceeded the overall level of the mining area. Notably, in Xieqiao Mine, 23.61% of the area exhibited significant and highly significant growth trends. Furthermore, spatial autocorrelation analysis of the kNDVI data from 2013 and 2023 revealed that the spatial distribution of vegetation in the mining area displayed significant positive spatial autocorrelation. This clustering effect further strengthened over time. This result indicates that vegetation restoration and growth in the Huainan Mining Area exhibit distinct spatial clustering characteristics, reflecting the gradual improvement of the regional ecological environment.