South America has been an epicenter of land cover and land use change (LCLUC) for over five decades due to rapid agricultural expansion along forest frontiers, the establishment of plantations in savannas, and desertification in drylands. Most attention has focused on LCLUC in tropical forests, and so information regarding the magnitude, geography, and rate of LCLUC across sub-tropical and temperate ecosystems in Argentina, Paraguay, and Uruguay (APU) is incomplete. To address this, we used Landsat to map changes in the fractional cover of bare ground, woody cover, and herbaceous vegetation at annual time steps from 1999 to 2019 over APU. Using field observations and Landsat imagery, we created a spectral library representative of these three cover types. We trained a machine learning model to map annual fractional cover at 30 m spatial resolution, and used a Bayesian change point algorithm to characterize spatial and temporal trajectories of LCLUC. Our results reveal that 11.6% of the study domain experienced changes in land cover composition over APU between 1999 and 2019. The most substantial changes were herbaceous cover gain (87,507 ± 2730 km2), woody cover loss (101,528 ± 2843 km2), and bare ground gain (31,354 ± 934 km2). Herbaceous cover in Paraguay increased by 51%, mostly because of deforestation for cattle ranching in the Dry Chaco and commodity crop agriculture in the Atlantic Forest. Uruguay showed a 62% increase in woody cover arising from the emergence and growth of pine and eucalyptus plantations. Argentina, the largest and most heterogeneous of the three countries, experienced a 38% increase in bare ground in the Patagonian Steppe due to climate and anthropogenic drivers, including reduced precipitation. Quantification of these abrupt and gradual LCLUC processes can be used to improve models of the carbon and energy budgets in southern South America, especially in arid and semi-arid ecoregions because they are increasingly understood to be important drivers of the interannual variability of the global carbon cycle.