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Geospatial Data Science aims to combine powerful computational and geospatial approaches with domain knowledge to extract information from large amounts of structured and unstructured geospatial data. Here, the focus is data-driven science, where we unlock insights hidden within vast amounts of geospatial data. For example, imagine a farmer of the future looking out at her field, except she knows the number of corn stalks, their height, and their health, and based on local sensors and estimated climate data, the estimated yield of each plant, which is controlling the automated irrigation and fertilization systems, all powered by geospatial data science.