多源数据支持下城市滨水区空间品质测度及影响因素研究

Measurement and influencing factors study of spatial quality in urban waterfront areas along the Suzhou River in Shanghai supported by multi-source data

城市滨水区的空间品质是城市发展建设水平的重要标志,传统的空间品质研究存在空间尺度较小、主观性较强、研究角度单一等问题。基于Open Street Map路网数据、百度地图街景数据与百度地图POI数据,结合机器学习技术对上海苏州河沿岸地区空间品质进行测度,使用MGWR2.2.1软件建立空间品质影响因素的多尺度地理加权回归模型。结果表明:研究区内普陀区西部、长宁区西部和静安区苏河北岸空间品质较低,应作为未来重点提升的区域;休闲业态在研究区内分布不均衡,空间配置应调整优化;研究区东部适合通过植树、修建步道、开辟步行街等方式提升空间品质,西部应着重发展餐饮、购物、娱乐等休闲消费业态。研究结果可为苏州河沿岸地区空间品质优化提供参考。

The spatial quality of urban waterfront areas is an important indicator of the level of urban development and construction.Traditional research on spatial quality has problems such as limited spatial scale,strong subjectivity,and single research perspective.Based on Open Street Map road data,Baidu Map street views,and Baidu Map point-of-interest(POI)data,combing with machine learning technology,the spatial quality of waterfront area along the Suzhou River in Shanghai was measured.MGWR2.2.1 software was used to establish a multi-scale geographically weighted regression model for influencing factors of spatial quality.The result shows that the western Putuo District,western Changning District,and the north bank of Suzhou River in Jingan District have low spatial quality in the study area,which should be prioritized during optimization.The eastern part of the study area is suitable for improving spatial quality through measures such as planting trees,building pedestrian paths,and opening pedestrian streets,while the western part should focus on developing leisure and consumer industries such as catering,shopping,and entertainment,as well as conjunct them with existing park green space resources,more trees should be planted,pocket parks are also necessary.The study results can provide a reference for optimizing the spatial quality of the Suzhou River waterfront area.