Satellite remote sensing time series have frequently been leveraged to track crop phenology changes throughout the growing season worldwide. These time series, primarily derived from optical sensors, can provide insights on changes that occur throughout the growing season compared to previous years. Additionally, time series can help monitor crop yields and overall production and can provide information about what is planted in a specific field. Optical remote sensors rely upon atmospheric and sky conditions, often causing gaps in the time series when images cannot be used because of cloud cover. The increasing availability of observations from synthetic aperture radar (SAR) allows for worldwide and repeat year-round collections. This study uses acquisitions from several different SAR missions (2018-2022) to map cropland extent using the coefficient of variation (CV) method in agricultural regions around the world, focusing predominantly on major global producers of corn, wheat, and rice.