The Sustainable Land Imaging (SLI) Program is a collaboration between the National Aeronautics and Space Administration (NASA) and the Department of the Interior (DOI)/United States Geological Survey (USGS) to ensure the continuation of no-cost, high-quality, and global land-imaging measurements compatible with the existing Landsat record dating back to 1972. This talk provides an overview of the development of data science methods at USGS to advance the utility of the Landsat data archive needed to explain, model, and ultimately forecast changes to the Earth's land surface in support of decision-making for societal benefit. The availability of Landsat Analysis Ready Data (ARD) released in 2017 by the USGS over the United States facilitated the development of time-series products as demonstrated through the USGS Land Change Monitoring, Assessment, and Projection (LCMAP) initiative. A long-term objective is to develop a strategic framework for leveraging multiple Earth observing space systems collectively via harmonized observations, together with data science methodology as part of an open global land imaging and science capability.