id |
caadria2018_332 |
authors |
van Ameijde, Jeroen and Song, Yutao |
year |
2018 |
title |
Data-Driven Urban Porosity - Incorporating Parameters of Public Space into a Generative Urban Design Process |
source |
T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 173-182 |
doi |
https://doi.org/10.52842/conf.caadria.2018.1.173
|
summary |
This paper presents an urban design project for a new city district, using generative design processes in architecture and urbanism developed over several years within academic research and practice work. The paper discusses the opportunities and challenges found when using a data-driven urban design methodology in relation to the complex logistical, social and economical networks of new urban centers. |
keywords |
Design Methods and Information Processing; Generative System; Simulation & Optimization; Urban Planning and Design; Public Space Design |
series |
CAADRIA |
email |
|
full text |
file.pdf (11,031,206 bytes) |
references |
Content-type: text/plain
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last changed |
2022/06/07 07:58 |
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