| id |
caadria2021_310 |
| authors |
Papasotiriou, Tania and Chalup, Stephan |
| year |
2021 |
| title |
Global urban cityscape - Unsupervised clustering exploration of human activity and mobility infrastructure |
| doi |
https://doi.org/10.52842/conf.caadria.2021.2.539
|
| 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. 539-548 |
| summary |
It is widely accepted that cities cultivate innovation and are the engines of productivity. The identification of strengths and weaknesses will enchant social mobility providing equal opportunities for all. The study at hand investigates the relationship between social mobility and transportation planning in 1,860 central urban areas across the globe. Datamining processes combining open-sourced, automated, and crowdsourced information from four major pillars of social mobility (demographics, human activity, transport infrastructure, and environmental quality) are used to describe each location. Next, unsupervised clustering algorithms are used to analyse the extracted information, in order to identify similar characteristics and patterns among urban areas. The process, which comprises an objective framework for the analysis of urban environments, resulted in four major types of central areas, that represent similar patterns of human activity and transport infrastructure. |
| keywords |
Information retrieval; similarity measures; computer methodologies; unsupervised clustering; urban performance |
| series |
CAADRIA |
| email |
Soultana.papasotiriou@uon.edu.au |
| full text |
 file.pdf (2,966,353 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 08:00 |
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