Dynamic monitoring of food cultivation status is important for guaranteeing food security and planning rational cultivation. Significant progress has been seen in crop classification using remote sensing data with high temporal resolution over large areas. However, improvement is needed for cultivation monitoring at the scale of small watersheds. This study combined high-temporal resolution moderate resolution imaging spectroradiometer (MODIS) data and high-spatial resolution Sentinel-2 data to identify key phenological stages of winter wheat and summer corn. MODIS data were used to construct indicators for differences in stages. Extraction thresholds for winter wheat and summer corn were determined using indicators for field sample sites. Different thresholds for key phenological stages were employed to determine the spatial distribution of these crops using Sentinel-2. The spatial distribution of winter wheat and summer corn rotation lands was generated using an overlay. User accuracies of the spatial extraction of wheat and corn rotation lands were 95%, 88.89%, and 86.96% for 2017-2018, 2018-2019, and 2019-2020, respectively (kappa coefficients: 74.24%, 54.47%, and 68.21%). The key phenological stage difference indicator method is suitable for crop classification and spatial extraction at the scale of small watersheds and can allow dynamic monitoring of grain crop cultivation in small-scale areas.