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Heterogeneous land cover patterns contribute to unique ecological conditions in cities and little is known about the drivers of these patterns among cities. We studied tree cover patterns in relationship to urban morphology (for example, housing density, parcel size), socioeconomic factors (for example, education, income, lifestyle characteristics), and historical legacies in Baltimore, Maryland, and Raleigh, North Carolina. Utilizing a multimodel inference approach and bivariate analyses, we analyzed two primary datasets employed in previous research predicting urban tree cover—one comprising continuous data (US Census), and the other consisting of categorical variables (Claritas PRIZM) that incorporate consumer purchasing data. Continuous data revealed that urban morphological characteristics were better predictors of tree cover patterns than socioeconomic factors in Raleigh and Baltimore at the …