The dataset represents a globally consistent cropland extent time-series at 30-m spatial resolution. Cropland defined as land used for annual and perennial herbaceous crops for human consumption, forage (including hay), and biofuel. Perennial woody crops, permanent pastures, and shifting cultivation are excluded from the definition. The fallow length is limited to four years for the cropland class. The cropland mapping was done using the consistently processed Landsat satellite data archive from 2000 to 2019. The Landsat time-series data were transformed into multitemporal metrics that described land surface phenology. These metrics were used as independent variables for a machine learning classification to map global croplands extent. The classification models were locally calibrated using extensive training data collected by visual interpretation of freely available high spatial resolution remotely sensed data. The crop mapping was performed in four-year intervals (2000-2003, 2004-2007, 2008-2011, 2012-2015, and 2016-2019). There is one cropland layer per epoch (five layers total), with the file name referred to the last year of the interval (2003, 2007, 2011, 2015, and 2019).