(by MetaCityGenerator)
MetaCityGenerator is an urban scale application to inform more sustainable urban design-related decisions based on urban computation(space syntax, traffic simulation)
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Based on the design logic, MetaCityGenerator could generate urban design automatically in a very short period of time and evaluate from the view of sustainability with the help of algorithms. While gradually bridging the gap between urban design and sustainable systems, the toolbox could improve design efficiency. The theories behind this tool included space syntax, shape grammar, pattern language, distribution optimization and operation. Thus, this tool has the potential to could be regarded as a key to complexity, which addresses the complexity arising from the synergy among multi-disciplines.

1. Main Functions

Autogeneration of spatial models: by integrating urban planning logics and computer algorithms, MetaCityGenerator can rapidly generate rudimentary spatial models for urban design projects. The spatial model will be complied with superior plans and regulations.

Assessment of urban design projects: MetaCityGenerator can provide instant assessment of urban design projects based on multi-disciplinary features and sustainable development goals.

Construction of a feedback loop: by using parametric design methods, we aim to construct a mechanism for regulatory plans and urban design projects to get instant assessments, feedbacks and modifications. With this mechanism, the efficiency and quality of urban design could be enhanced

2. Objectives

High quality

Sustainable urban development

3. Developers

Tao Yang, Weizhen Luo, Xuhui Lin, Chengru Deng, Hejin Wang

4. Notifications

Rhino version 7.15 and above are recommended.

Model unit MUST BE METER, and models cannot be generated if your model unit is a millimeter (mm)

Please put your geometric objects, such as roads and land parcels, near the origin of coordinates (0, 0, 0). Confined by computation accuracy of geometric objects in RhinoCommon, the geometric Boolean operation might go wrong if you put your model too faraway from the origin point.

If you encounter any other problems or have any demands and suggestions, please let us know via Github Issues. We'll try our best to help.

Github Link:

Source Code:

Official Site:

License Cost:
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