西部人居环境学刊2023，Vol.38Issue(6)：22-29,8.DOI:10.13791/j.cnki.hsfwest.20230604
城市滨水蓝绿空间冷岛效应的影响因素与分布特征
Influencing Factors and Distribution Characteristics of Cold Island Effect in Urban Waterfront Blue-Green Spaces:The Case Studies of Wuhan,Nanjing and Hangzhou
摘要
Abstract
The process of urbanization has led to the replacement of natural landscapes,such as vegetation and water bodies,by man-made structures,triggering the absorption of more solar radiation by impermeable surfaces,the rise of temperatures in urban areas and the exacerbation of the urban heat island effect,which has had a variety of negative impacts on human societies.Blue-green space has the"cold island effect",which is opposite to the heat island effect,and can play an ecological role in regulating urban microclimate and enhancing urban biodiversity.However,there is a lack of in-depth quantitative analysis and research on the cold island effect of waterfront blue-green spaces in large cities in China. In this study,it takes Wuhan,Nanjing and Hangzhou as cases of three cities with developed water systems,and analyzes the cold island effect of blue-green space in three cities with developed water systems(Wuhan,Nanjing and Hangzhou)with the help of multi-source remote sensing and GIS spatial data,and analyzes the cold island effect of blue-green space in the three cities(Wuhan,Nanjing and Hangzhou)with the help of a machine-learning regression decision-tree model to reveal the relationship between blue-green space factors and heat island effect in different waterfront spaces.Factors interact with the heat island effect.In this study,the typical urban center with rich water system is taken as the study area of the cold island effect,and the neighborhood unit is taken as the smallest unit,which highlights the concentrated investigation of the cold island effect of the blue-green space along the waterfront of the city,meanwhile,the decision tree regression is used to solve the problem of the large scope of the study,the number of data is very large,and there is the problem of the linear influence between the respective variables.The results show that the strong cold island effect areas in the waterfront blue-green space in Wuhan are located around large lakes such as Donghu Lake and Tangxun Lake,while the south bank of the Qinhuai River is in Nanjing,and the south side of the middle part of the Qiantang River and the south side of the West Lake are in Hangzhou.Decision tree regression results show that there are also differences in the landscape morphology factors that play a dominant role in different cities,and that the watershed morphology of different cities plays an obvious role in influencing the urban heat island.In Hangzhou and Nanjing,water surface rate and green space rate are the dominant factors,and Hangzhou is jointly affected by them in 72.9%,while Nanjing is 61.8%.In Wuhan,water surface rate and water shape index are the dominant factors,which are jointly influenced by 63.5%. In view of the different waterfront blue-green spatial characteristics of the three large cities with abundant water systems,different cities should put forward targeted optimization strategies.Wuhan can continue to improve the connectivity of large water bodies to further form an overall blue-green space system.Hangzhou should appropriately increase the number of artificial lakes and connect scattered water bodies in the city,and further enrich the shape of waters and improve the overall network of blue-green space in the process of development and construction of new districts and improvement of the water network.Nanjing should continue to give full play to the existing advantages of green space,improve the diversity of green space form boundaries,and at the same time need to set up a combination of waterfront green space system,break the continuous urban heat island,and improve the overall cooling capacity.With the development of the economy,in recent years,urban development has become more concerned about ecological livability,harmonious coexistence of man and nature.For big cities that have been built,it is difficult to adjust the blue-green space pattern by blindly altering and rebuilding on a large scale,but it is possible to start from the more microscopic waterfront blue-green space and carry out small-scale renovation,so as to achieve the ecological planning of blue-green space without large-scale demolition and alteration,and to achieve the purpose of mitigating the urban heat island effect. Based on multi-source remote sensing data,GEE,machine learning-based decision tree regression has a greater potential in the analysis of cold island effect in blue-green space of different water network cities,and the high-precision spatial dataset generated by the study enriches the refined quantitative analysis of the cold island effect of blue-green space of the city,and at the same time provides scientific references for the planning and regulation of blue-green space of the waterfront and the management and control of the thermal health risk of other similar cities.The results of this study can provide useful references for the scientific planning and design of waterfront blue-green spaces in large cities in China.关键词
城市冷岛强度/蓝绿空间/城市水网形态/决策树回归Key words
Urban Cold Island Intensity/Blue-Green Space/Urban Water Network Shape/Decision Tree Regression分类
建筑与水利引用本文复制引用
王伟武,梁爽,杨涵淄..城市滨水蓝绿空间冷岛效应的影响因素与分布特征[J].西部人居环境学刊,2023,38(6):22-29,8.基金项目
国家自然科学基金项目(51578482) （51578482）
中国气象局气候资源经济转化重点开放实验室开放研究课题(2023-15) （2023-15）
