Beyond canopy expansion: Shrubs offer greater potential for enhancing green view equity in urban streetscapes

Abstract

Urban street greenery is a core component of the urban living environment. Despite growing attention to green-space exposure, detailed studies of urban vegetation communities remain underexplored. In the context of optimizing existing assets, it is essential to identify potential opportunities that have thus far been overlooked. Traditional regression analyses often emphasize the most prevalent significant effects within a sample, which can obscure latent relationships or optimization strategies that have not yet been widely implemented. To address this, we combined active LiDAR scanning with deep learning to analyze 746.04 km of roads and 27,926 street-view images in Zhumadian City. We found that the Green View Index (GVI) contributed by both trees and shrubs declines with increasing urbanization intensity, although the magnitude and spatial distribution of these declines differ. Random forest predictions indicate that, compared to trees, shrubs exhibit markedly greater optimization potential in the urban core. By integrating our results with Baidu heatmap data, we quantified green-space exposure demand across different urbanization gradients. While both trees and shrubs can substantially enhance greenness in various urban areas, high pedestrian flows significantly dampen the actual effectiveness of green space exposure. Notably, highly urbanized zones show a far greater demand for shrubs than for trees, and this requirement remains substantially unmet. We argue that employing multifaceted techniques for urban green-space optimization and demand analysis will be pivotal for sustainable urban management. This requires more than merely expanding tree canopy.