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

ZHAN Jiajie

doi:10.12299/jsues.23-0193

Volume 38 Issue 3

Sep. 2024

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Article Navigation > Journal of Shanghai University of Engineering Science > 2024 > 38(3): 304-312, 327

ZHAN Jiajie. Measurement and influencing factors study of spatial quality in urban waterfront areas along the Suzhou River in Shanghai supported by multi-source data[J]. Journal of Shanghai University of Engineering Science, 2024, 38(3): 304-312, 327. doi: 10.12299/jsues.23-0193

Citation:

ZHAN Jiajie. Measurement and influencing factors study of spatial quality in urban waterfront areas along the Suzhou River in Shanghai supported by multi-source data[J]. Journal of Shanghai University of Engineering Science, 2024, 38(3): 304-312, 327. doi: 10.12299/jsues.23-0193

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

doi: 10.12299/jsues.23-0193

ZHAN Jiajie

School of Environmental and Geographical Science, Shanghai Normal University, Shanghai 200233, China

Received Date: 2023-12-22
Available Online: 2024-11-14
Publish Date: 2024-09-30

Abstract

Abstract

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 lowspatial 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.
- urban waterfront,
- Suzhou River,
- street view,
- multi-source data,
- machine learning

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References(20)

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