Preferences for urban spaces were studied as a function of spatial category and nine predictor variables: spaciousness, refuge, enclosure, coherence, legibility, complexity, mystery, typicality, and age. A non-metric factor analysis of the preference ratings yielded four categories of urban spaces: Open-Undefined, Well-Structured, Enclosed Settings, and Blocked Views. These categories are similar to the spatial categories proposed for natural environments by S. Kaplan (1979, Assessing Amenity Resource Values. USDA Forest Service General Technical Report RM-68), who stressed openness and spatial definition as bases for categorization. The Well-Structured category was best liked, with the other categories not very well liked and about equal in preference. Regression analyses revealed three variables as consistent predictors of preference. Coherence and complexity were positively related to preference, and age was negatively related. Overall, the results support the Kaplans' proposal that both spatial and non-spatial factors are important in categorizing environments and in explaining environmental preferences.