Many cities are developing ambitious future canopy cover targets in recognition of urban trees' numerous benefits. Selecting fast-growing and climate-adapted tree species is important to help achieve these targets. The assessment of growth performance of tree species is challenging, but essential for selecting species that grow in different environments. Often, remote sensing is used to measure canopy cover change at a landscape or neighbourhood scale in urban forests, but rarely at individual tree or species scales. In this study, we developed a novel spatial analysis method combining remotely sensed canopy cover mapping with georeferenced urban tree inventory data to identify individual tree crowns and measure crown expansion rates. We developed species-specific models of crown expansion rates for 20 most common street tree species growing in two rainfall zones (478–665 mm). Predicted crown areas at 10 years after planting ranged from 6.6 m2 to 43.7 m2. The species showed four different crown expansion responses at 10 years after planting: Fast and consistent growth; Fast but sensitive growth; Slow and consistent growth; Slow and sensitive growth. This study demonstrates a simple, but robust method to delineateindividual tree crowns that can be used to develop species-specific crown expansion models. It also shows the importance of developing species specific crown expansion models in different rainfall zones, as some tree species were clearly sensitive to rainfall differences. Using this spatial analysis method, urban forest managers can make informed decisions regarding tree species selection, considering rainfall zone specific environmental growth conditions, as well as space constraints and water availability.