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Urban forest is a dynamic urban ecosystem that provides critical benefits to urban residents and the environment. Accurate mapping of urban forest plays an important role in greenspace management. In this study, we apply a deep learning model, the U-net, to urban tree canopy mapping using high-resolution aerial photographs. We evaluate the feasibility and effectiveness of the U-net in tree canopy mapping through experiments at four spatial scales—16 cm, 32 cm, 50 cm, and 100 cm. The overalldoi:10.3390/rs13091749 doaj:3d6d24a4442b49c0be2603c9defe9d28 fatcat:lmiktgewmnd5jmwm2ik3x32ekm