Impact of 3-D urban landscape patterns on the outdoor thermal environment: A modelling study with SOLWEIG

被引:44
作者
Kong, Fanhua [1 ,7 ]
Chen, Jiayu [2 ]
Middel, Ariane [3 ]
Yin, Haiwei [4 ]
Li, Manchun [1 ,7 ]
Sun, Ting [5 ]
Zhang, Ning [6 ]
Huang, Jing [1 ]
Liu, Hongqing [1 ]
Zhou, Kejing [1 ]
Ma, Jinsong [1 ]
机构
[1] Nanjing Univ, Sch Geog & Ocean Sci, Xianlin Ave 163, Nanjing 210023, Peoples R China
[2] Shanghai Energy Technol Dev Co LTD, Tianlin Ave 8887, Shanhai 200233, Peoples R China
[3] Arizona State Univ, Sch Arts Media & Engn, 950 S Forest Mall,Stauffer B258, Tempe, AZ 85281 USA
[4] Nanjing Univ, Sch Architecture & Urban Planning, 22 Hankou Rd, Nanjing 210093, Peoples R China
[5] Univ Reading, Dept Meteorol, Reading RG6 6ET, England
[6] Nanjing Univ, Sch Atmospher Sci, Xianlin Ave 163, Nanjing 210023, Peoples R China
[7] Nanjing Univ, Jiangsu Prov Key Lab Geog Informat Technol, Xianlin Ave163, Nanjing 210023, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Three-dimensional urban landscape metrics; Urban thermal environment; Mean radiant temperature; LiDAR; UMEP; SKY-VIEW FACTOR; MEAN RADIANT TEMPERATURE; HEAT-ISLAND; BUILDING DENSITY; COMFORT; SIMULATION; HEIGHT; AREAS; CITY; MORPHOLOGY;
D O I
10.1016/j.compenvurbsys.2022.101773
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
With global warming and rapid urban growth, cities get warmer, which poses additional stress on human thermal comfort and health. Complex three-dimensional (3D) urban forms change radiation fluxes and shade patterns in cities, but most studies that link urban form to thermal exposure have traditionally investigated the horizontal, two-dimensional composition and configuration of urban landscapes. Supported by high-precision airborne LiDAR data and IKONOS satellite data, this study calculates 3D urban landscape metrics for central Nanjing, China, including vegetation above ground biomass (AGB), building volume (V-B), standard deviation of building and vegetation heights (HSDB, HSDV), the building normalized compactness radio (nCR), sky view factor (SVF), surface roughness (SR), and shadow patterns (SP). Diurnal hourly mean radiant temperature (T-mrt) is simulated using the UMEP (Urban Multi-scale Environmental Predictor) tool forced with fixed-point observation data for a typical hot summer day. Correlation and multiple regression analyses are conducted to investigate the relationship between the 3D form metrics and T-mrt and to identify key factors that influence the thermal environment. T-mrt varies spatially and diurnally and is strongly related to SP during the day, revealing the importance of solar access for modulating the thermal environment. AGB is negatively, but SVF, SP, and building nCR are positively correlated with daytime T-mrt. At night, T-mrt is more homogeneous across space and mainly impacted by the urban fabric's ability to lose heat. Open areas cool faster than areas with low SVF and complex urban forms with high building nCR. Findings from this study have great scientific and practical significance for optimizing urban landscape patterns from a human-centered heat exposure perspective and will guide planning and design strategies to promote thermally comfortable urban environments.
引用
收藏
页数:13
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