| id |
caadria2023_84 |
| authors |
Chen, Bowen, Lao, Pui Kuan, Dou, Zhiyi, Qiu, Wai-Shan and Luo, Dan |
| year |
2023 |
| title |
Analyst Patterns of Influence Between a Commercial Distribution and Neighbourhood Dynamic in a Residential Neighbourhood |
| doi |
https://doi.org/10.52842/conf.caadria.2023.1.525
|
| source |
Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 525–534 |
| summary |
The spatial distribution of urban commercial spaces significantly impacts the overall efficiency and vibrancy of adjacent neighbourhoods. As such, it is an important factor to consider during urban development. This study aims to examine the patterns of impact between commercial distributions and neighbourhood dynamics in a residential neighbourhood, based on the case study of a highly populated, thriving commercial, and culturally rich area situated in Mong Kok, Hong Kong. In this research, a series of numeric evaluations and statistical analyses of liveability and vibrancy metrics are presented, uncovering the tension created by existing commercial forms and local living patterns. This research started with multi-dimensional data mining, such as accessing planning data using Geographic Information Systems (GIS), perception data using Street View Images (SVI), and business performance data from Google; secondly, analysing the data via machine learning (ML) algorithm and statistical correlation to identify correlations overlaid with a mapping of spaces of measurable characteristics. The goal is to establish a measurable evaluation of the relationship between commercial vibrance and urban features that can further inform the impact of urban design strategies on fostering the vitality of community commercial centres. |
| keywords |
Mong Kok, Model Learning Machine (ML), SVM, PSPnet, MaskRCNN, POI, Commercial vibrance, Heatmap correlation, Visualization, QGIS, Google Maps Information |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (3,266,932 bytes) |
| references |
Content-type: text/plain
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| last changed |
2023/06/15 23:14 |
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