Representing the landscape visual quality of residential green spaces in Singapore with 3D spatial metrics

Abstract

Visual quality relates to people’s views, feelings about visiting landscapes, and restorative potential, which is crucial in planning urban spaces. This study has investigated the visual quality, particularly in its connection to restorative potential, of Singapore’s residential green spaces (RGSs) that are easily accessible and frequently visited by residents. We deployed a laser scanner to document 152 RGSs in high-density public housing estates and represented their landscape visual quality (LVQ) with previously developed 3D spatial metrics. The spatial metrics correlated to the Perceived Restorative Scale (PRS) of 1500 participants from an online survey were employed for cluster analysis to identify RGSs’ main features. The results concluded five main RGS clusters in Singapore: “High naturalness and low visual scale”, “Low naturalness and coherence”, “High visual scale and low coherence”, “High coherence and low visual scale”, and “Medium-high visual and low complexity”. A set of practical recommendations based on the weaknesses of each cluster were also provided to support their LVQ improvement. The significance of the study lies in the point cloud-based approach to document and characterise RGSs’ LVQ with 3D spatial metrics and paves a typological way to facilitate RGSs planning.