Rapeseed plays a crucial role in global food trade, and remote sensing technology can quickly, non-destructively, and extensively conduct spatial distribution and area statistics of rapeseed. This study uses the Hehuang Valley as the study area, combining 2020 Sentinel-2 time-series data and field sampling data from the research area to extract rapeseed planting area. The study calculates the NDVI index of field sample data, analyzes the NDVI time series variation characteristics based on the phenological characteristics of rapeseed, and introduces the FROM_GLC10 dataset as prior knowledge of cultivated land distribution. The least squares method and threshold method are used to extract the rapeseed planting distribution in the Hehuang Valley. The results indicate that compared with the 2019 statistical data of rapeseed planting areas in the Hehuang Valley, rapeseed is mainly distributed in the central and parts of the research, with less distribution in other regions, showing a consistent spatial distribution of rapeseed planting. The correlation coefficient between the statistical area and the extracted area is 0.89, with an R2 of 0.79.