A Study Of The Scale Effect Of The Relationship Between Urban Sky View Factor On Surface Temperature

Urbanization is the inevitable development.While the urban infrastructure is improving,the inner urban space is suffered from the environmental deterioration problem of gradually increasing local temperature.The emergence of high-floor and high-density buildings has led to changes in the type and structure of urban ground cover,resulting in complex and variable processes of radiation transmission between solar radiation and urban ground surface.Therefore,the characteristics of the internal urban space climate zone change,and the urban thermal environment problem becomes increasingly significant.This situation affects the sustainable development of cities.Besides,the high temperatures reduce the thermal comfort of urban residents.Most of the existing studies focus on urban scale or neighborhood scale to analyze the influence of building morphology and layout on urban thermal environment.However,research on the relationship between urban building structures and the urban thermal environment at both scales is relatively limited.With the increasing research on the influencing factors of urban thermal environment,combining the advantages of urban scale to obtain a larger spatial scope and neighborhood scale to obtain continuous time data,the scale effect of building morphology and thermal environment relationship between urban and neighborhood scales can effectively increase the source of data and study the spatial and temporal distribution characteristics of urban thermal environment of highly heterogeneous urban structures in detail.In addition,the sky view factor(SVF)is a key parameter to describe the three-dimensional building morphology and quantify the short-wave radiation absorption and long-wave radiation release.Therefore,the focus of this paper is the relationship between building SVF and the urban thermal environment about the spatial and temporal characteristics.This paper uses a combination of remote sensing images,field measurements and statistical analysis.Firstly,at the urban scale,we analyzed the relationship between SVF and LST the temporal distribution characteristics of the four seasons and day and night surface temperatures.Otherwise,we analyzed the spatial characteristics of these relationship in the area within the fifth ring road of Beijing city.At the same time,the correlation analysis between SVF and land surface temperature(LST)between different ring roads was carried out according to the characteristics of the ring roads within the study area.In addition,we selected the different heights of buildings to analyze the synergistic effects of SVF and building shading ratio(BSR)on LST.Secondly,at the neighborhood scale,we constructed 10 types of residential and commercial district building scenarios.Then we analyzed the relationship between SVF and LST and the relationship between BSR and building surface temperature(BST)at different moments of each scenario.Besides we analyzed the building scenarios with different building layouts to analyze the synergistic relationship between SVF and BSR on LST.Finally,we selected the same moments to compare the similarities and differences of SVF and LST relationships between city and neighborhood scales.At the same time,the differences in the influence of SVF on BSR and the differences in the degree of common influence of SVF and BSR degree LST are analyzed according to different building scenes at two scales.The main research results are as follows:(1)At the urban scale,the relationship between SVF and LST is consistent in spring and winter,and consistent in summer and autumn,with large differences between day and night.The effect of SVF and BSR on LST varies from scene to scene for building scenes with different average heights.In this paper,the distribution of building SVF within the fifth ring of Beijing is obtained using building vector data and hemispheric model.The LST data of different seasons and days and nights were also obtained using Landsat8 and ASTER data.The mathematical and statistical analysis reveals that LST increases with SVF in spring and winter;LST in summer and autumn is not singularly positively correlated with SVF,and the lowest value appears when the building SVF is between 0.3 and 0.5 in summer when the average temperature is higher,which can effectively mitigate the urban thermal environment.There is a non-linear relationship between SVF and LST during the daytime,with LST increasing with SVF in the interval of 0-0.6,and decreasing with SVF in the interval of 0.6-1;SVF and LST are significantly negatively correlated at night.The average BSR of winter is the largest,and when SVF is 0.6,the average BSR of multi-story and mid-rise buildings is the largest.The larger the shaded area is,the lower the LST is,and the cooling effect of shading has some influence on the relationship between SVF and LST.(2)At the neighborhood scale,there are two relationships between the SVF and hourby-hour LST for the 10 types of building scene models.There is a temporal difference in the effect of BSR on LST,and the SVF has a stronger effect on LST than the BSR.According to the building patterns of residential and commercial areas in Beijing,10 types of building scenarios are constructed,and the parameters of SVF and BST are calculated by using ENVI-met microclimate model,and the correlation analysis shows that LST increases as SVF increases from 10:00 to 17:00,and LST decreases as SVF increases from 18:00 to 9:00because the nighttime is mainly the heat dissipation process.At 10:00 and 18:00,the relationship between SVF and LST is excessive.Secondly,at sunrise,BSR is the maximum moment in a day,but the cooling effect of BSR on temperature is not obvious because of the weak solar radiation,and the arrangement of building direction has a greater influence on the relationship between BSR and BWT.The synergy between daytime SVF and BSR on temperature at 7:00,the relationship between BSR and LST is not obvious,mainly SVF has an effect on temperature;at 14:00,the temperature of the daytime SVF is lower in the smaller area in addition to absorbing less solar radiation,but also due to the presence of building shadows makes the temperature lower.From the relationship between BSR and BST,we found that the internal walls can produce more shadows than the external walls.And the temperature cooling is more obvious of the shadow in the east and west walls.(3)The relationship between SVF and LST at urban and neighborhood scales is smaller at night than the difference at daytime,and the hour-by-hour temperature data at neighborhood scales can compensate for the limitation of longer period of remote sensing data.The relationship between BSR and temperature and SVF combined with BSR on temperature is more obvious at neighborhood scales.Comparative analysis using the statistical results of(1)and(2)revealed that the relationship between SVF and temperature was the same at nighttime for both urban and neighborhood scales,with negative correlations.In daytime,the relationship between SVF and temperature is roughly positive for both scales,and the positive correlation is more obvious as the resolution increases.Second,the BSR decreased with increasing SVF in the four building scenes at the neighborhood scale;the BSR was smaller than that at the neighborhood scale and the relationship with SVF was not clear in the three experimental areas at the city scale.The statistical results for the neighborhood scale were higher for larger SVF and smaller BSR,while the statistical relationship was less obvious for the urban scale.