Effects of landscape on thermal livability at the community scale based on fine-grained geographic information: A case study of Shenzhen.

In the current research, the question of how to modify the microclimate through landscape planning to create a livable thermal environment within a residential community area has not been clarified. Therefore, this study investigated the effects of landscape on thermal livability in 2980 communities in Shenzhen, and obtained the following findings: (1) the proportion of trees and the average building height were key indicators to determine the average land surface temperature (LST) of a community, while the two-dimensional building characteristics, particularly shape, similarity, and patch dominance, were mainly responsible for regulating the spatial distribution of LST within a community; (2) at the community scale, the cooling intensity of buildings was strongest when their average height was around 40-60 m, and cooling effect of trees was most pronounced when their proportion achieved 20 %; and (3) the LST threshold for thermal livability in Shenzhen was around 35 °C. In summer, a higher proportion of trees and grass, as well as buildings with higher average heights, larger volume ratios, and more complex three-dimensional structures were favorable to maintain a livable community thermal environment, while in winter, a lower proportion of trees was more encouraged. In addition, a smaller average sky view factor can achieve a community thermal environment that warm in winter and cool in summer. These results are expected to facilitate urban planners to develop community renewal from the perspective of thermal livability.

Irrigation cooling effect on land surface temperature across China based on satellite observations.

The effect of irrigation on temperature has attracted much attention because its cooling effect may mask the warming due to other factors, such as greenhouse gas forcing. Although many studies have examined the irrigation cooling effect (ICE) based on near-surface air temperature from meteorological observations or climate model simulations, few studies have directly addressed the effect of irrigation on land surface temperature (LST), which is closely linked to the surface energy balance and near-surface air temperature. In this paper, an ICE detection (ICED) method is proposed to assess the effect of irrigation on LST using the Moderate Resolution Imaging Spectroradiometer (MODIS) products across China. The magnitude of the ICE is calculated as the LST difference between irrigated area and adjacent non-irrigated area in the self-adaptive moving window determined by the ICED method. The results show that irrigation cools daytime LST by 1.15 K, and cools nighttime LST by 0.13 K, on average, across irrigated areas in China. The effect of irrigation on LST differs greatly among the climate zones and seasons, characterized by the enhanced ICE in arid regions and the growing season. In the arid climate zone, nearly all the irrigated areas show a lower daytime LST than the adjacent non-irrigated areas, leading to a strong ICE magnitude of >6 K in the growing season. In the humid climate zone, the impact of irrigation on LST is generally negligible, with a magnitude around zero throughout the year. This study provides observational evidence and a comprehensive assessment of the effect of irrigation on LST. The proposed ICED method has the potential to be used to study the spatiotemporal variation of the effect of irrigation on LST over other regions with intensive irrigation.

The footprint of urban heat island effect in 302 Chinese cities: Temporal trends and associated factors.

The urban heat island (UHI) effect has been a concern for decades due its adverse influence on energy consumption, air and water quality, and, most importantly, the health of urban dwellers. Researchers have paid much attention to the magnitude of the UHI effect, but ignored its spatial extent (i.e. footprint) which is another important aspect of the UHI effect. In this study, we systematically analyzed the footprint of surface UHI (SUHI) effect in 302 Chinese cities, especially temporal trends of the footprint, by using multi-source remote sensing data. The footprint of SUHI effect (FP) was estimated by the Gaussian surface, and its temporal trend was examined by the Mann-Kendal and the Sen's slope estimator non-parametric tests. We found the FP showed evident diurnal (daytime > nighttime), seasonal (summer > winter) and inter-city (big cities > small and medium-sized cities) differences. During the period 2003-2016, over 80% of the 302 cities exhibited increasing trends of the FP in annual days and summer days, and the increasing trends were statistically significant (p < 0.05) in about half of these cities. In the nights, the FP increased in more than 70% of the cities, and about one-third of the 302 cities experienced significantly increasing trends of the FP. On average, the annual daytime and annual nighttime FPs increased at a rate of 5.0% per year and 3.8% per year, respectively. More importantly, the correlation analysis indicated that the increase of anthropogenic heat emissions and the decrease of vegetation activities and surface albedos should take lead responsibility for the expansion of the FP in the urbanization process. These results reveal that the spatial extent of heat island effect has expanded significantly in numerous Chinese cities, and this increasing trend will be sustained in the coming years if no more effective measures are carried out.

Assessing the relationship between surface urban heat islands and landscape patterns across climatic zones in China.

The urban heat island (UHI) effect exerts a great influence on the Earth's environment and human health and has been the subject of considerable attention. Landscape patterns are among the most important factors relevant to surface UHIs (SUHIs); however, the relationship between SUHIs and landscape patterns is poorly understood over large areas. In this study, the surface UHI intensity (SUHII) is defined as the temperature difference between urban and suburban areas, and the landscape patterns are quantified by the urban-suburban differences in several typical landscape metrics (ΔLMs). Temperature and land-cover classification datasets based on satellite observations were applied to analyze the relationship between SUHII and ΔLMs in 332 cities/city agglomerations distributed in different climatic zones of China. The results indicate that SUHII and its correlations with ΔLMs are profoundly influenced by seasonal, diurnal, and climatic factors. The impacts of different land-cover types on SUHIs are different, and the landscape patterns of the built-up and vegetation (including forest, grassland, and cultivated land) classes have the most significant effects on SUHIs. The results of this study will help us to gain a deeper understanding of the relationship between the SUHI effect and landscape patterns.