Urban morphology affects the sensible heat flux and net radiation exchange which can alter urban heat mitigation plans. This study first parameterized the geometric effects on the net radiation, and then calculated the net radiation and sensible heat flux in the urban landscape of Hong Kong. Considering that the sensible heat flux is the main heat sink in compact urban areas, this study proposes a Normalized Urban Sensible Heat Mitigation Index (NUSHMI) based on the ratio of the net radiation and sensible heat flux. Overall, there is major difference in the dependence of net radiation and sensible heat flux on geometric parameters. Net radiation Rn, reaches an optimal value, either maximum or minimum depending on the parameters of SVF and a standard deviation of building height σ_h, at intermediate parameter values, which suggests a guideline relevant to urban design targeting the mitigation of urban climate. Contrariwise, sensible heat flux decreases or increases, again depending on SVF and σ_h, is being considered, with increasing values of the same parameters. For example, R_n, reaches a minimum value for a Sky View Factor (SVF) between 0.5 and 0.6, while it reaches a maximum value for a standard deviation of building height σ_h between 20 and 30 m. These two results suggest that radiative forcing, i.e. R_n, can be minimized by urban space with SVF around 0.55 and σ_h around 25 m. The relationships between sensible heat flux and SVF or σ_h do not show multiple minima or maxima (as with R_n), with the exception of building density, which could also be applied as a guideline in urban design. The results based on the proposed NUSHMI indicated the NUSHMI reaches the highest values when building density is about 0.7 and building height is about 80 m and when the building height standard deviation within an area is about 10 m to 20 m. These findings revealed how the urban morphology affects the surface heat flux exchange between urban canopy and atmosphere boundary layer, and can help to design an efficient urban landscape towards urban heat mitigation for highly compacted cities, e.g. controlling the building density, height, and the height deviation. This combination of urban geometric parameters identifies an urban configuration maximizing the dissipation of absorbed radiant energy as sensible heat. It should be noted, however, that heat load upon buildings would be reduced at the price of maximizing heat dissipation within the built-up space.

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The urban heat island effect poses a growing threat to human society, especially in densely populated and developed megacities. With the introduction of the Local Climate Zones (LCZ) framework, new perspectives and findings have been brought to urban heat island studies. This study investigated the cooling effect of vegetation and albedo on the surface urban heat island (SUHI) in the classification system of LCZ during different seasons, using three Chinese megacities as case study areas. Single-factor linear regression and Pearson’s correlation coefficient were applied to analyze the seasonal cooling effect of both albedo and the NDVI on the SUHI within different LCZs. The results show that (1) the variability of the SUHI is reflected in its dominance and intensity within certain LCZs in different cities and in the efficiency of cooling factors; (2) the cooling effect of vegetation is dominant in each season, and the cooling effect produced by albedo within specific seasons can be differentiated by LCZs. This study provides valuable information for the mitigation of the SUHI magnitude in specific regions and at specific times of the year.@en

Vegetation is important for urban heat mitigation. The cooling intensity of vegetation is affected by background climate and urban design. How to evaluate vegetation cooling efficiency under different climate conditions is still an issue open to discussion. In this study, a normalized indicator of urban vegetation cooling efficiency (NVCE) is proposed as a metric of urban vegetation cooling efficiency applicable and comparable under different climate and urban conditions. When surfaces are only covered by vegetation, the cooling effects should be highest than other pixels at the local climate scale. The difference of surface temperature between the pure vegetation surfaces and surfaces without vegetations (T_{r, b} − T_{r, v}) is the range of the vegetation cooling intensity at the same local climate conditions. Difference between radiometric surface temperature of a mixed pixel and the vegetation temperature within the mixed pixel (T_{i, r} − T_{i, v}) is excess temperature of pixel i. The ratio of (T_{i, r} − T_{i, v}) to (T_{r, b} − T_{r, v}) can indicate how much percent of existed excess temperature after vegetation cooling effects for pixel i under such local climate condition. Thus, the NVCE is defined as (T_{i, r} − T_{i, v})/(T_{r, b} − T_{r, v}). Based on the high spatial resolution data, the T_{i, v} and T_{i, r}within each 30 m × 30 m grid are derived to calculate the NVCE and the relationships between NVCE and fractional vegetation cover were studied under different conditions. Results showed that NVCE can reduce the differences caused by background climate in the assessment of vegetation cooling efficiency, i.e. making vegetation cooling efficiency under different climate conditions comparable. The NVCE is also sensitive to the vegetation fraction. When vegetation fraction is smaller than 0.2, the mean value of NVCE is about 0.5 and no obvious change. This means that the vegetation has no obvious cooling effects when vegetation fraction is smaller than 0.2. When the vegetation fraction is higher than 0.2, NVCE decreases linearly with increasing vegetation fraction. When the vegetation fraction is higher than 0.9, NVCE tends to 0. This indicates that 0.2 for vegetation fraction is the threshold of vegetation cooling effects. This study can provide information for evaluating the vegetation cooling efficiency under different climate and geometric conditions. This study also can provide useful information for urban green infrastructure design and planning, e.g. the vegetation fraction should be higher than 0.2 for urban cooling and the vegetation cooling efficiency can reach maximum when SVF is about 0.5 to 0.6.

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Urban surface temperature is a very important variable in the observation and understanding of energy exchange. A comprehensive understanding of the urban thermal environment is of great significance towards the adaptability of urban areas to climate hazards. The heterogeneity of urban space increases the complexity of the urban surface temperature observations and the analyses of the energy exchange. To understand how the urban geometry affects the distribution of surface temperature, we used airborne thermal infrared remotely sensed images at very high spatial resolution (original spatial resolution is 0.2 m × 0.2 m after registration). We did this study in Hong Kong to analyze the effects of various geometric parameters on different facet surface temperatures (roof, road, wall and vegetation) in daytime and nighttime and in different seasons. Results show that the urban geometry has greater impacts on the road temperature than on building temperature, and the impact of the geometric parameters on road surface temperature changes with the time of the day and the season. The building height is a more effective driver of heat dissipation in daytime than nighttime for roof facets. A lower building density improves ground heat dissipation, while a higher building density improves heat dissipation by roof facets. Furthermore, the vegetation only limitedly affects the surface temperatures of facets that are lower than vegetation, but to an extent useful to mitigate urban temperature, which might be a feature relevant in urban design. This research can provide insights useful to city planners and policy makers to better understand the urban thermal environment and help design more livable and healthy cities in the near future.

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The surface urban heat island intensity (SUHII) when using nadir-viewing radiometric and complete surface temperature (T_r and T_c) was evaluated. The urban areas of the Kowloon peninsula and Hong Kong Island were selected and four daytime Landsat TM images and two nighttime ASTER images were collected to retrieve T_r and then model T_c based on a semi-empirical model. SUHIIs were estimated using both the retrieved T_r and modelled T_c. High spatial resolution (HR) airborne thermal images (0.2 m) observed at 12:10 noon on Oct 24, 2017 were used to retrieve T_c directly. Results based on HR data and satellite data were consistent and indicated that the geometry of the built-up space had a larger impact on SUHII when using T_c (SUHIIc) than T_r (SUHIIr). During daytime SUHIIc decreased while SUHIIr showed a very slight increase with building density. Both SUHIIc and SUHIIr decreased with higher building height but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr decreased with increasing building height variance and increased with increasing sky view factor (SVF). The rate of decrease with building height variance for SUHIIc was larger than SUHIIr. The rate of increase of SUHIIc with SVF was higher than SUHIIr. During nighttime, geometry effects on SUHIIc and SUHIIr were different from daytime. Both SUHIIc and SUHIIr increased with building density, while the rate of increase of SUHIIc with building density, as well as with building height, was much higher than SUHIIr. Both SUHIIc and SUHIIr decreased with SVF, but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr initially increased with building height variance and then remained approximately constant. We also evaluated the UHI intensity: SUHIIc was much closer to UHII than SUHIIr. Overall, building geometry had larger impact on SUHIIc than on SUHIIr, that is, SUHIIc is more representative of urban climate than SUHIIr.

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