TY - GEN
T1 - An algorithmic methodology to predict urban form
T2 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting, CAADRIA 2018
AU - Chowdhury, Shuva
AU - Schnabel, Marc Aurel
N1 - Publisher Copyright:
© 2018 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) in Hong Kong.
PY - 2018/5/17
Y1 - 2018/5/17
N2 - We question the recent practices of conventional and participatory urban design approaches and offer a middle approach by exploring computational design tools in the design system. On the one hand, the top-down urban planning approaches investigate urban form as a holistic matter which only can be calibrated by urban professionals. These approaches are not able to offer enough information to the end users to predict the urban form. On the other hand, the bottom-up urban design approaches cannot visualise predicted urban scenarios, and most often the design decisions stay as general assumptions. We developed and tested a parametric design platform combines both approaches where all the stakeholders can participate and visualise multiple urban scenarios in real-time feedback. Parametric design along with CIM modelling system has influenced urban designers for a new endeavour in urban design. This paper presents a methodology to generate and visualise urban form. We present a novel decision-making platform that combines city level and local neighbourhood data to aid participatory urban design decisions. The platform allows for stakeholder collaboration and engagement in complex urban design processes.
AB - We question the recent practices of conventional and participatory urban design approaches and offer a middle approach by exploring computational design tools in the design system. On the one hand, the top-down urban planning approaches investigate urban form as a holistic matter which only can be calibrated by urban professionals. These approaches are not able to offer enough information to the end users to predict the urban form. On the other hand, the bottom-up urban design approaches cannot visualise predicted urban scenarios, and most often the design decisions stay as general assumptions. We developed and tested a parametric design platform combines both approaches where all the stakeholders can participate and visualise multiple urban scenarios in real-time feedback. Parametric design along with CIM modelling system has influenced urban designers for a new endeavour in urban design. This paper presents a methodology to generate and visualise urban form. We present a novel decision-making platform that combines city level and local neighbourhood data to aid participatory urban design decisions. The platform allows for stakeholder collaboration and engagement in complex urban design processes.
KW - Algorithmic methodology
KW - Design decision tool
KW - Knowledge-based system
KW - Urban form
UR - http://www.scopus.com/inward/record.url?scp=85056129167&partnerID=8YFLogxK
U2 - 10.52842/conf.caadria.2018.2.401
DO - 10.52842/conf.caadria.2018.2.401
M3 - Conference Proceeding
AN - SCOPUS:85056129167
T3 - CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting
SP - 401
EP - 410
BT - Learning, Prototyping and Adapting
A2 - Alhadidi, Suleiman
A2 - Fukuda, Tomohiro
A2 - Huang, Weixin
A2 - Janssen, Patrick
A2 - Crolla, Kristof
PB - The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)
Y2 - 17 May 2018 through 19 May 2018
ER -