Abstract

The LCZs (Local Climate Zones) system and its mapping have been emerging in recent years as an important approach to study the variations of local climates in cities, which are closely linked to human comfort issues and building energy demand. However, most of the current practices of LCZs mapping are based on 2D satellite images that can only provide rough estimations. This study tries to improve the current LCZs mapping methods by proposing a bottom-up method that adopts high-resolution 3D building data, land cover data, land use data, etc. This fine-grained and 3D LCZs mapping method has three advantages: using urban block unit as the basic spatial unit to derive more reasonable LCZs; bridging the real urban form with urban canyon models to provide more appropriate parameters; and adopting the linear interpolation algorithm to improve the current LCZs classification system. The mapping method has been tested in Manhattan, Atlanta and central Tokyo, and the results show distinctive LCZ types and distribution patterns in these three cities. This method can be used to provide more accurate LCZs maps that help to better understand human comfort and simulate urban-scale building energy performance, which could inform urban designers and policy makers on the UHI mitigation strategies and urban redevelopment strategies.

Full Text
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