Spatial-temporal Heterogeneity Of Urban Agglomeration Heat Island Effect Based On Improved Urban-rural Dichotomy And Its Influencing Mechanism

Urban heat island(UHIs)was defined as the phenomenon of higher temperature of urban areas high than that in surrounding rural areas.Urban-rural dichotomy was often used to assess the intensity of urban heat islands,that is,the difference between real-time or cumulative surface temperature between the city and the suburbs and surrounding villages.Urban agglomeration as a new urban form,which has the characteristics of close spatial organization structure and close economic connection.The urban-rural dichotomy was difficult to apply to urban integration or the study of urban heat islands with shorter or less distance between cities.How to understand the urban agglomeration heat island effect and its influence is an urgent problem to be solved.It is an important task to understand the difference of heat island in different time scale and space scale and to clarify the regularity of the influence of heat island intensity with the change of space scale.By introducing the concept of regional heat island(RHIs),this paper constructs a method suitable for the intensity evaluate of regional heat island,which breaks through the boundary of the city and improves the dichotomy between urban and rural areas,takes pixel as the evaluation unit,extracts the peripheral background that least affected by urbanization.Taking the Yangtze River Delta urban agglomeration(YRDUA)as a case study,thermal infrared remote sensing data from 2003-2017 were selected.The spatial and temporal patterns and characteristics of the regional heat island intensity in YRDUA was studied from the perspective of urban agglomeration.The commonalities and differences of RHIs intensity between each cities were analysis.The effects of biophysical factors,socioeconomic factors and climatic factors on regional heat islands intensity in YRDUA were studied.Then,the relative importance of different influencing factors were analyzed by stepwise linear regression method,and the dominant factors of regional heat island intensity in different seasons was identified.We test whether the interpretation of different influence factors will be significantly improved due pixel scale to urban scale.It will help to formulate targeted and focused intervention measures for heat island that understand the causes of spatial heterogeneity of urban heat island intensity in YRDUA.The main findings are as follows.(1)Beyond the boundaries of a single city,surface regional heat island intensity(SRHII)was calculated as the actual surface temperature difference of each pixel(1 km ×1 km)relative to that of the background with the lowest effect of urbanization.The background was selected based on elevation,land cover,annual maximum NDVI and NL.The method was used to evaluate the RHIs intensity in YRDUA.It is found that the RHIs intensity in YRDUA was 5.97? in the summer of 2017,which is twice than that using the traditional UHIs(2.44?)evaluation method.This shows that the traditional UHIs assessment method underestimates the heat island intensity in YRDUA.It mainly because the urban heat island has a certain impact on the surrounding villages.Traditional UHIs intensity ignores the aggregation effect beyond the each cities.(2)From 2003 to 2017,the proportion of the heat island zone in summer increased from 21.74% to 31.03% in YRDUA.A gradual decreasing trend is observed for the three grades of the SRHII(2 ?-4 ?,4 ?-6 ?,> 6 ?),which was 1.28%,4.18% and 5.74%,respectively.The annual average of RHIs at night(SRHII ? 2 ?)increased from 7510 km2 in 2003 to 20097 km2 in 2017.The RHIs intensity among each city in YRDUA were analyzed,which showed that the RHIs intensity of cities was 2-3 ?,4-5 ?,1-2 ? and <0 ? in spring(urban number N=28),summer(N=24),autumn(N=24)and winter(N=22),respectively.The annual intensity of RHIs at night was lower than that in daytime.The strong heat island zone in Suzhou,Wuxi,Changzhou and Nantong show a tranfer trend to Shanghai,while the strong heat island zone of Shaoxing,Yuyao and Cixi show a transfer trend to Hangzhou.(3)There was seasonal variation in the dominant factors of RHIs intensity in YRDUA.The dominant factors of RHIs intensity in daytime in spring,summer,autumn and winter was enhanced vegetation index(interpretation is 33.3%),normalized difference build-up density(NDBI)(37.3%),NDBI(26.8%)and precipitation(26.2%),respectively.At night,Modify normalized difference water body index(MNDWI)had a dominant effect on SRHII in spring(54.12%),autumn(52.62%)and winter(24.19%).The dominant factor of nighttime SRHII in summer was EVI(42%).Moreover,water bodies have a negative effect on RHIs during the day while have positive effect at night.In addition,with the increase of RHIs intensity,the warming effect of NDBI,surface albedo and anthropogenic heat emission becomes more obvious,while the cooling effect of vegetation and water body.(4)The effect of biophysical factors,socio-economic factors and climatic factors on the RHIs intensity in the YRDUA depends on the spatial scale.The correlation between RHIs intensity and per capita GDP,anthropogenic heat emissions and population density on the urban scale was higher than 0.18,0.24 and 0.34 than that in pixel scale,respectively.The correlation between RHIs intensity and temperature and precipitation in urban scale was higher than 0.067 and 0.34 than that in pixel scale.This indicates that human activity and climate background was more impact on RHIs intensity in coarse spatial scale.The concentration effect of RHIs and the influence of human activities will increase the pressure of regional environment,and controlling anthropogencia heat emission was an effective measure to alleviate the RHIs intensity on large scale.(5)The spatial relationship between the RHIs intensity and influencing factors in YRDUA indicates that it has significant spatial heterogeneity.The local R2 of RHIs intensity in YRDUA in summer was 0.79 using the ordinary least square regression(OLS)model.However,the local R2 was 0.91 using geographical weighted regression model(GWR),which indicates that GWR model can better identify spatial heterogeneity than OLS.The coefficients of NDBI and RHIs intensity increase from the value of NDBI,indicating that the degree of urbanization has important influence on RHIs intensity.The spatial heterogeneity of the coefficient between RHIs intensity and temperature and precipitation shows that the southeast decreases to the northwest of YRDUA.Based on this,it is necessary to focused RHIs mitigation measures and eco-environmental control programs.