Shade watch: Mapping citywide shade dynamics through ray tracing and LiDAR data in Hong Kong's complex 3-D built environment

Abstract

<p>The importance of urban shade in city planning has been underscored by its various associations with thermal comfort, living environment quality, human health and well-being. However, existing methods for urban shade mapping are often limited to street-level scopes or singular sampling observational times, leaving citywide shade mapping, its spatiotemporal patterns, and controlling factors largely unexplored. To fill these knowledge gaps, this study proposed a novel protocol that enables seamless mapping of spatiotemporal urban shade patterns over the entire city by fusing look-up-table (LUT)-based ray-tracing approach with Google Earth Engine cloud computing technology, as well as high-resolution digital surface model (DSM) derived from LiDAR data. This protocol was applied to Hong Kong, a city characterized by complex 3-D built environments, and then delved into the spatiotemporal patterns of urban shade and the associated controlling factors. Validation results indicate that the proposed method can accurately quantify urban shade compared to ground-based photo references and high-resolution satellite imagery. The analysis uncovers that: (1) Shade exhibits spatial heterogeneity across different 3-D built environments while maintaining a consistent "U-shape" diurnal shade fraction during the day; (2) Solar geometry, regardless of solar zenith and azimuth angle, is negatively associated with aggregated metrics of shade landscape and positively associated with fragmented metrics. Moreover, solar zenith angles exert stronger controls over the citywide shade landscape patterns; and (3) Persistent shade significantly reduces the sunlight hours (i.e., the accumulated sunshine hours per day) across administrative districts, local climate zones (LCZs), and seasons. Due to shade effects originating from 3-D urban structures, Hong Kong typically experiences an average of 4–8 sunlight hours per day within a one-year cycle, which is substantially lower than the 11–14 h of natural daylength. This study offers a practical protocol for large-scale urban shade mapping, enhancing our understanding of urban shade, its spatiotemporal dynamics, and benefits in a broader spatiotemporal context. The associated datasets and findings from this study can inform urban planners and policymakers in developing effective strategies to create healthier and sustainable urban environments in Hong Kong.</p>