id |
caadria2020_046 |
authors |
Alva, Pradeep, Lee, Han Jie, Lin, Zhuoli, Mehta, Palak, Chen, Jielin and Janssen, Patrick |
year |
2020 |
title |
Geo-computation for District Planning - An Agile Automated Modelling Approach |
source |
D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 793-802 |
doi |
https://doi.org/10.52842/conf.caadria.2020.1.793
|
summary |
This paper focuses on developing a novel geo-computational methodology for automating the generation of design options for district planning. The knowledge contribution focuses on the ability of the planners and designers to interact with and override the automated process. This approach is referred to as "agile automated modelling". The approach is demonstrated through a case study in which three adjacent districts are generated with a total area of approximately 1300 hectares. An automated modelling process is implemented based on a set of core planning principles established by the planners. The automated process generates street networks, land parcels, and 3-dimensional urban models. The process is broken down into three steps and users are then able to intervene at the end of every step to override and modify the outputs. This aims to help planners and designers to iteratively generate and assess various planning outcomes. |
keywords |
Geo-computation; procedural modelling; GIS; planning automation; neural network |
series |
CAADRIA |
email |
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full text |
file.pdf (15,875,347 bytes) |
references |
Content-type: text/plain
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last changed |
2022/06/07 07:54 |
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