上海城市热岛效应形成机制及空间格局

城市热岛效应的产生及演变与城市地表覆被变化、人类社会经济活动密切相关,是城市生态环境状况的综合概括与体现,目前对城市热岛形成、演变的驱动机制、热岛效应与地表覆被变化的定量关系研究大多还是从对某些影响因子的测定入手,缺乏对区域热环境系统全面、综合的评价与分析.近年来,在城市化过程中,人类社会、经济活动的加剧使城市地表热力景观呈现出高度的空间异质性,在利用Landsat 7 ETM+热波段数据反演上海地区地表温度的基础上,应用地统计学方法揭示了不同尺度下上海城市地表温度场空间变异特征及其不同的驱动因子.进而,采用决策树方法构造城市热环境系统的分类和预测模型,建立中心城区地表温度场空间分布及其驱动因素之间的定量关系,挖掘上海城市热岛效应的形成机制,揭示出多种影响因素综合作用下中心城区热环境空间格局差异.研究结果表明,城市热环境形成的驱动因子在空间上呈现出明显的分异性特征,各种影响因素在空间上不同的组合方式将决定城市热岛效应的时空演变趋势.运用决策树方法可以有效地确定在城市内部不同区域影响热环境形成的主导因素,揭示城市热岛形成与演变的成因机制及其空间差异,并可以进一步用来预测分析未来城市地表温度场动态变化的空间分布格局.

Mechanism of formation of urban heat island effect and its spatial pattern in Shanghai

The formation and evolution of urban heat island (UHI) effect, which are closely related to changes of land cover and socioeconomic activities of human being in urban area, can generalize and embody urban ecological environment condition. Existing research efforts on the driving mechanism of UHI formation and evolution have been mostly focused on the measurement of a single or several indicators representing land cover changes, socioeconomic conditions, etc. There is still lack of a comprehensive analysis with respect to surface thermal environment system from a regional perspective. The course of urbanization has witnessed a serious spatial heterogeneity of urban land surface thermal landscape due to intensive human socioeconomic activities. In this paper, first, spatial variation patterns of Shanghai urban surface temperature field and their distinct driving factors are presented at different scales with geostatistical methods based on the land surface temperature (LST) retrieved from Landsat 7 ETM+ thermal channel data in Shanghai, China. Second, classification and prediction models of urban thermal environmental system are constructed by means of decision tree. These models facilitate quantitatively establishing the relationship between the spatial distribution of LST field and its influencing factors, discovering the mechanism of forming UHI effect in Shanghai, and exhibiting the different spatial patterns of thermal environment under synthetic effect of various influencing factors. Results indicate that spatial differentiation is inherent in the driving factors influencing the formation of urban thermal environment, and the evolution trends of UHI effect rely on spatial combinations of various influencing factors. The decision tree method can be effectively used to determine the key factors influencing the formation of thermal environment in different regions inside the city, reveal the causation of formation and evolution of UHI and its spatial difference, and further predict and analyze the spatial distribution pattern of dynamic change of urban surface temperature field in the future.