城市热岛
比例(比率)
航程(航空)
土地利用
空间生态学
回归分析
建筑面积比
城市形态
环境科学
归一化差异植被指数
自然地理学
市区
人口
城市规划
空间分布
地理
城市密度
兴趣点
空间变异性
气象学
地图学
统计
生态学
遥感
数学
气候变化
材料科学
人口学
社会学
复合材料
生物
作者
Suiping Zeng,Jiahao Zhang,Jian Tian
出处
期刊:Sustainability
[MDPI AG]
日期:2023-04-03
卷期号:15 (7): 6172-6172
被引量:1
摘要
High-density urban areas have spatial characteristics, such as complex functions, population gathering, and complex forms, that lead to more severe urban heat island effects. Systematically evaluating the thermal environmental benefits of urban spatial forms to optimize the urban physical environment is important. In this study, Tianjin’s central urban area, which is a typical representative of high-density urban areas, was selected to invert the multi-period land surface temperature by relying on the existing two- and three-dimensional morphological data set of communities. The multi-scale geographically weighted regression model was used to fit the regression relationship between the urban land surface temperature and spatial morphological parameters. From this, the influencing factors of different types of existing community spaces and their spatial stabilities were explored. The results show the following: (1) The summer surface temperature varies greatly in the central urban area, and the high-temperature areas are mainly distributed in the industrial, residential, and commercial districts. (2) The MGWR model has the better model-fitting ability. The positive influence coefficients of temperature include ISP and BD, while the negative influence coefficients are BSD, BH, NDVI, and SVF. (3) There is significant spatial heterogeneity in the impact coefficients among the blocks that can be targeted to mitigate the heat island effect. This study provides ideas for optimizing the spatial morphological parameters of surface temperature in urban centers. Future challenges include increasing the spatial morphological parameter selection range, dissecting the interactive relationships between spatial morphological parameters and their effectiveness on the surface temperature, and refining the study’s spatial and temporal granularity.
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