Analysis and Considerations to Lessen Visual Clutter: Multidimensional Associations Between Streetscape Visual Clutter and Urban Perceptions in Shanghai

Visual clutter can affect attention, cognitive load, and environmental evaluation, yet streetscape studies often treat visual complexity as a broad construct without distinguishing visual richness from competition among visual features. Shanghai was selected because its dense, heterogeneous urban fabric and central–peripheral variation make it well suited to city-scale analysis. Using 69,244 street-view images, this study combined computer vision, deep learning, and modeling to quantify edge, color, semantic, and depth clutter and estimate beauty, wealth, liveliness, safety, boredom, and depressiveness. After controlling for built-environment characteristics, 23 of 24 linear associations were significant, although their directions differed. Edge and color clutter were associated with higher positive perceptions and lower negative perceptions. Semantic clutter was positively associated with wealth, liveliness, and safety but negatively associated with beauty; depth clutter was negatively associated with beauty, wealth, and liveliness and positively associated with boredom and depressiveness. Stable inverted U-shaped patterns occurred in only four relationships. Streetscape management in Shanghai should avoid uniformly increasing or reducing visual information. Planning and design may retain architectural detail, vegetation edges, coordinated color variation, and semantic richness while better coordinating facades, signage, street furniture, vehicles, and foreground elements, improving sightline continuity, and reducing obstruction and abrupt spatial discontinuity.