In this study, a fractal dimension-based method has been developed to compute the visual complexity of the heterogeneity in the built environment. The built environment is a very complex combination, structurally consisting of both natural and artificial elements. Its fractal dimension computation is often disturbed by the homogenous visual redundancy, which is textured but needs less attention to process, so that it leads to a pseudo-evaluation of visual complexity in the built environment. Based on human visual perception, the study developed a method: fractal dimension of heterogeneity in the built environment, which includes Potts segmentation and Canny edge detection as image preprocessing procedure and fractal dimension as computation procedure. This proposed method effectively extracts perceptually meaningful edge structures in the visual image and computes its visual complexity which is consistent with human visual characteristics. In addition, an evaluation system combining the proposed method and the traditional method has been established to classify and assess the visual complexity of the scenario more comprehensively. Two different gardens had been computed and analyzed to demonstrate that the proposed method and the evaluation system provide a robust and accurate way to measure the visual complexity in the built environment.

Urban systems exhibit multifractal scaling behaviors arising from their hierarchical and heterogeneous spatial organization. Yet the Green View Index (GVI), a widely used indicator of street-level green visibility, is conventionally measured as a static value, overlooking how green exposure is reorganized across scales, which may bias greening evaluations and planning decisions. This study proposes an “X-minute Greenery” framework to examine GVI as a scale-dependent spatial process. Street view imagery and walking isochrone data from Hong Kong and Shenzhen, China, are integrated to measure GVI across 5, 10, 15, and 20 min walking ranges, while a multifractal-inspired approach is developed to characterize its scale-dependent variation structure. Empirical findings show that (1) GVI variation is not random but associated with urban governance and spatial morphology; (2) a staged pattern of variation is identified, with a GVI level around 0.2 marking an approximate shift in configurations of greening dynamics; (3) even under similar initial GVI conditions, areas can still follow divergent variation patterns across walking scales, exposing latent spatial inequalities aligned with institutional and morphological factors. By framing urban green visibility as a scale-aware complex-systems phenomenon, this study adapts multifractal reasoning to street-level greenery, challenges the “equal green, equal policies” assumption, and supports context-sensitive planning interventions.