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During this presentation, we will compare and contrast project and production photogrammetry problems and solutions for transforming raw data into useful information. Project photogrammetry workflows typically involve smaller quantities of raw imagery, varied types of data (such as raster, vector, GIS, LiDAR), and further imagery processing such as change detection or image classification. Commercial photogrammetry or production mapping customers require high-throughput capabilities that enable them to rapidly process massive volumes of incoming spatial data for the creation or update of large spatial databases. We will also explore unmanned aerial vehicles' (UAVs) heightened susceptibility to in-flight environmental influences, the smaller footprints of the images they collect, and the software workflow necessary to correct the imagery. Imagery obtained from GheoRhea's UAV platform will be used to demonstrate a complete and accurate workflow for correcting the artifacts inherent in UAV-sourced imagery.