The inability of a farmer to plant an insured crop by the due date can pose food security risks to the affected region or country at large. This is generally caused by excess moisture or rainfall such as the catastrophic flooding that occurred in the midwestern region of United States in 2019. The aim of this study is to estimate the number of unplanted acres in eastern South Dakota by mapping the flood extent using Landsat 8 and Sentinel 1 images from 2018 and 2019. Change detection techniques such as simple band math of NDVI and NDWI values along with automatic thresholding methods were applied to these images to accentuate changes caused by flooding. The NDVI change detection map showed vegetation loss in the eastern parts of the study area while NDWI values showed increased water content, both indicating possible flooding events. The VH band of Sentinel 1 was also particularly useful in identifying potential flooded areas as the VH value for 2019 was significantly lower than that of 2018 especially in the northern parts of the image. Flood maps were then generated for both Landsat and Sentinel using Otsu thresholding, then combined to form a comprehensive map over the entire study area. This “new” flood map was finally integrated with “unplanted” pixels extracted from Cropland Data Layer 2019 to estimate or predict prevent plant acres across several counties in South Dakota. The predicted figures were found to have high accuracy, particularly in the central part of the study area where the Landsat and Sentinel flood maps overlap, which correlates strongly with the most affected counties in the State such as Beadle, Hanson, Hand, and others according to figures reported by USDA-FSA