FINE SCALE MEASUREMENT OF URBAN SHADE PATTERNS FOR URBAN HEAT RESILIENCE

Abstract

Urban Heat Island (UHI) intensifies over time, mounting pressure on social, ecological and economic and infrastructural systems. The combined impact of rapid urbanization and climate change is expected to accelerate the UHI severity, causing immense threat to urban dwellers. Among the implemented solutions, shade has been widely recognized as a one of the most effective solutions. However, methodologies for accurately measuring shade in complex urban environments remain underexplored. This study introduces a novel approach of creating realistic 3D digital representation of buildings, trees and ground by utilizing LiDAR data and advanced modeling techniques for shade detection. The generated vertical and horizontal shade are quantified by subarea and analyzed different dimensions along an urban-to-suburban transect. Combined scenario generates highest amount of shade and follows the pattern of dominant factor, but averages when contributions are similar. Building shade predominates the built environments, occurring mostly on facades, while tree shade prevails in relatively rural landscape primarily on ground, exhibiting contrary pattern. Except Urban Core and Suburban, all transect zone have inconsequential roof shade. The sensitivity examination indicates that shade detection is steady till 5m, minor discrepancies (mostly below 10%) emerge at 10m. Beyond 10m, significant deviations is expected, particularly for ground and roof surfaces, with 30m resolution showing substantial inaccuracies. Roof shade in all scenarios and ground shade in building scenario are the most volatile to resolution. These findings provide valuable insights for urban planners, geospatial scientists, scholars and policymakers to optimize street level intervention for enhancing human thermal comfort and UHI mitigation strategies.