CivicMorph: Generative Modeling for Public Space Form Development

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Abstract

Public spaces play a crucial role in urban environments, and their design must consider various factors to optimize functionality and user experience. CivicMorph, a generative modeling framework, stands at the forefront of this challenge, utilizing computational design and generative algorithms to craft responsive urban spaces. It emphasizes inclusivity by incorporating user-centric data alongside environmental parameters to create diverse spatial configurations. The framework fosters collaboration among stakeholders through design patterns and spatial analytics, ensuring that the planning process is participatory. Case studies illustrate CivicMorph's capability to produce public space designs that adapt to social dynamics and environmental considerations. The findings highlight notable enhancements in user satisfaction and functional efficiency, positioning CivicMorph as an innovative solution for urban design challenges.

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