| id |
caadria2021_354 |
| authors |
Huang, Chenyu, Gong, Pixin, Ding, Rui, Qu, Shuyu and Yang, Xin |
| year |
2021 |
| title |
Comprehensive analysis of the vitality of urban central activities zone based on multi-source data - Case studies of Lujiazui and other sub-districts in Shanghai CAZ |
| source |
A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 549-558 |
| doi |
https://doi.org/10.52842/conf.caadria.2021.2.549
|
| summary |
With the use of the concept Central Activities Zone in the Shanghai City Master Plan (2017-2035) to replace the traditional concept of Central Business District, core areas such as Shanghai Lujiazui will be given more connotations in the future construction and development. In the context of todays continuous urbanization and high-speed capital flow, how to identify the development status and vitality characteristics is a prerequisite for creating a high-quality Central Activities Zone. Taking Shanghai Lujiazui sub-district etc. as an example, the vitality value of weekday and weekend as well as 19 indexes including density of functional facilities and building morphology is quantified by obtaining multi-source big data. Meanwhile, the correlation between various indexes and the vitality characteristics of the Central Activities Zone are tried to summarize in this paper. Finally, a neural network regression model is built to bridge the design scheme and vitality values to realize the prediction of the vitality of the Central Activities Zone. The data analysis method proposed in this paper is versatile and efficient, and can be well integrated into the urban big data platform and the City Information Modeling, and provides reliable reference suggestions for the real-time evaluation of future urban construction. |
| keywords |
multi-source big data; Central Activities Zone; Vitality; Lujiazui |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (16,966,685 bytes) |
| references |
Content-type: text/plain
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 The Recognition of CAZ in Shanghai Based on Evaluated POI
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| last changed |
2022/06/07 07:50 |
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