| Urban development is often accompanied by increased human activities,changes in ground cover,and increased energy consumption,causing changes in the urban thermal environment,resulting in the well-known Urban Heat Island(UHI)effect.The UHI effect can have important effects on biological phenology,soil properties,hydrological cycle,air quality,and even threaten the health and lives of the inhabitants.With the development of global population and economy,the urbanization process is expected to further accelerate,especially in the less developed areas and countries along the Belt and Road Routes,which will usher in the peak of urban development and construction.Therefore,an in-depth understanding of the spatiotemporal characteristics of the urban thermal environment and its influencing factors,and the development of mitigation measures for the UHI effect are of great significance for the sustainable development of global cities.Traditional studies of the urban thermal environment rely heavily on air temperature observed by in-situ stations,and the research contents and conclusions of these studies are often limited by the number and distribution of stations.With the development of thermal infrared remote sensing technology,the spatially continuous Land Surface Temperature(LST)acquired through satellite images provides a new perspective for understanding the urban thermal environment.The remotely sensed LST reflects the distribution of urban surface thermal environment,and the corresponding UHI effect is called Surface UHI(SUHI)effect.Numerous studies have analyzed the urban surface thermal environment using remotely sensed LST data,however,there are still limitations in the existing studies.First,in terms of the spatial distribution characteristics of the urban surface thermal environment,current studies have carried out a more detailed portrayal,but still lack systematic multi-city and largescale(e.g.,global or national scale)studies of its influencing factors(e.g.,impervious surface fraction,tree cover fraction,and landscape pattern).Second,regarding the temporal trends of urban surface thermal environment,most of the existing studies focus on the changes of SUHI Intensity(SUHII,i.e.,the LST difference between urban and rural areas),but lack a comprehensive analysis of the trends of SUHI Footprint(abbreviated as FP,i.e.,the spatial extent of SUHI).Therefore,this paper presents a more comprehensive analysis of the spatiotemporal variation of the urban surface thermal environment and its influencing factors at the global and national scales based on multi-source remote sensing data and using various analytical methods.The main points and conclusions of this paper are as follows:(1)Relationship between urban LST and Impervious Surface Fraction(ISF).ISF is a comprehensive reflection of the degree of urbanization,and understanding the relationship between LST and ISF is one of the keys in the field of urban surface thermal environment.This paper systematically analyzed the LST-ISF relation using remote sensing data in 682 global cities.The results show that LST tends to increase along the ISF gradient in the vast majority of global cities(more than 90%).On average,each 1%increase in ISF is accompanied by an increase in the annual average daytime and nighttime LST of about 0.0219 °C and 0.0168 °C,respectively,in global cities.More importantly,the LST-ISF relation is strongly linked to the climatic conditions.For example,daytime LST in cities located in tropical and temperate climate zones increases rapidly with increasing ISF,but in cities located in arid climate zones,daytime LST increases at a smaller rate or even decreases along the ISF gradient.In terms of seasonal variation,the change rate of LST with ISF is higher in the warm season than in the cold season,especially for cities in temperate and boreal climate zones.In addition.The correlation analysis results show that vegetation and albedo are the main factors affecting the daytime and nighttime LST-ISF relation,respectively,which implies that measures mainly to improve vegetation conditions in cities are beneficial to mitigate the daytime SUHI effect,while means mainly to enhance surface albedo are more effective to ameliorate the nighttime SUHI effect.(2)Global assessment of urban trees' cooling efficiency.Trees are one of the important features affecting the spatial distribution of urban surface thermal environment.The enhancement of Tree Cover Fraction(TCF)has been always considered as an effective measure to mitigate the SUHI effect,but there is a lack of global-scale quantitative analysis of the Cooling Efficiency(CE,i.e.,the LST reduction by per 1% TCF increase)of urban trees based on satellite observations.Therefore,this paper presents a comprehensive analysis of the spatiotemporal distribution of trees' cooling efficiency in 510 global cities using remote sensing data.The results show that the daytime LST in cities decreases rapidly with the increase of TCF,and the global average daytime CE is 0.063 ? %-1;however,at night,the cooling efficiency of urban trees is negligible and even turns to a weak warming effect,and the global average nighttime CE is only 0.007 ? %-1.Besides,CE shows obvious spatial variation and is generally higher in hot and arid cities located in regions such as northwestern China,southwestern United States,and the Middle East and Africa,indicating that higher cooling gains can be achieved by increasing TCF in these cities.More importantly,the spatial distribution of CE is closely related to urban meteorological factors(e.g.temperature and humidity),and that an increase in temperature and a decrease in humidity will enhance the vapor pressure deficit in tree leaves and further promote transpiration,which in turn causes an increase in cooling efficiency of urban trees.In terms of seasonal variation,CE shows a pattern of highest in summer and weakest in winter,which fits well with the seasonal change pattern of trees' own state.(3)The relationship between SUHII and landscape patterns.The spatial distribution of the urban surface thermal environment can be influenced not only by urban compositions(e.g.,fraction of impervious surfaces or trees),but also by urban configurations(e.g.,shape,density,and aggregation).The composition and configuration are two major aspects of urban landscape patterns,and an in-depth understanding of their effects on the UHI effect can provide scientific guidance for improving the thermal environment from the perspective of urban planning.This paper systematically analyzed the relationship between SUHII and the urban-rural difference in landscape patterns along 332 Chinese cities,based on multi-source remote sensing observation data and using typical landscape metrics.The results show that SUHII is significantly(p < 0.05)and positively correlated with the urban-rural difference in the Area Percentage(i.e.PLAND)of built-up,and mostly negatively correlated with the urban-rural differences in the Patch Density(PD),Clumpiness Index(CI)and Mean Shape Index(MSI)of built-up.In addition to built-up,urban-rural difference in landscape patterns of vegetation,including woodland,grassland and cropland,can also have important effects on SUHII,but their relations are closely related to vegetation type,climatic conditions,and diurnal and seasonal factors.More importantly,SUHI mostly shows a significant and negative correlation with the urban-rural difference in the Shannon's Diversity Index(SHDI),while generally has a positive correlation with the urban-rural difference in the Contagion Index(CONTAG).This suggests that more diverse land-use types and more homogeneous mixing of them in the urban area could help to relieve the SUHI effect.(4)Temporal trend of the SUHI footprint(FP)and its influencing factors.The dynamic urbanization process has affected urban surface thermal environment,resulting in not only changes in SUHII,but also variations of FP.However,current studies mostly focused on the temporal pattern of SUHII and paid little attention to the temporal trend of FP.Therefore,this paper conducted a comprehensive study on the temporal trend of FP and its influencing factors in 302 Chinese cities based on multitimeseries(2003-2016)remotely sensed LST data.The results show that FP has an increasing trend in daytime and nighttime annual average FP in more than 85% and 75%of Chinese cities,respectively,and that this increasing trend is statistically significant(p < 0.05)in about half of the 302 cities.Besides,the number of cities showing a significant upward trend in FP is much higher in summer than in winter.Besides,the national average annual daytime and nighttime FP increased at 4.4% and 2.5% per year,respectively,during the period of 2003-2016,leading to a significant increase in the number of heat island-affected populations.More importantly,the inter-annual variation of FP is generally positively correlated with night light intensity,while mostly negatively correlated with vegetation index and albedo.This indicates that the increase of anthropogenic heat releases,the loss of vegetation and the reduction of surface albedo,in the process of urbanization,can cause the expansion of the spatial extent of SUHI effect. |
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