ScholarWorks@중앙대학교

초록

Highlights: Urban 2-D and 3-D forms affect the built environment’s adaptability to surface heat and cold. Access to vegetation and water bodies helps moderate severe heat and cold across all seasons. Taller buildings are likely to reduce surface temperature in warm seasons due to shading. Older buildings with larger footprints are related to temperature increases across all seasons. Grid- and block-based approaches show comparable results in quadrant and regression analyses. Climate change is expected to result in increased occurrences of extreme weather events such as heat waves and cold spells. Urban planning responses are crucial for improving the capacity of cities and communities to deal with significant temperature variations across seasons. This study aims to investigate the relationship between urban temperature fluctuations and urban morphology throughout the four seasons. Through quadrant and statistical analyses, built-environment factors are identified that moderate or exacerbate seasonal land surface temperatures (LSTs). The focus is on Seoul, South Korea, as a case study, and seasonal LST values are calculated at both the grid (100 m × 100 m) and street block levels, incorporating factors such as vegetation density, land use patterns, albedo, two- and three-dimensional building forms, and gravity indices for large forests and water bodies. The quadrant analysis reveals a spatial segregation between areas demonstrating high LST adaptability (cooler summers and warmer winters) and those displaying LST vulnerability (hotter summers and colder winters), with significant differences in vegetation and building forms. Spatial regression analyses demonstrate that higher vegetation density and proximity to water bodies play key roles in moderating LSTs, leading to cooler summers and warmer winters. Building characteristics have a constant impact on LSTs across all seasons: horizontal expansion increases the LST, while vertical expansion reduces the LST. These findings are consistent for both grid- and block-level analyses. This study emphasizes the flexible role of the natural environment in moderating temperatures. © 2023 by the authors.

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