A new study from the Livable City Lab uses AI to analyze zoning documents, and explores how form-based codes may support greater sustainability in American cities.

The Yale Livable City Lab, in collaboration with the University of Chicago, recently published a study examining the adoption and impact of form-based codes (FBCs) as a tool for creating more sustainable cities. FBCs offer an alternative to traditional zoning approaches, which often have segregated land usage and have led to issues like urban sprawl and vehicular dependence, instead prioritizing the physical form and character of development.  

The researchers used natural language processing techniques to analyze thousands of municipal zoning codes across the United States and identify linguistic patterns that indicate FBC usage. They found that the text of zoning codes is unstructured and highly variable, and municipalities might adopt FBC elements – such as mixed use and narrower setback requirements – in ways that are not explicitly labeled as FBC in their codes. Their research, published in Nature Cities, reveals that cities using FBC-style zoning had improved walkability, shorter commutes, and more multifamily housing. They also find that zoning reform has expanded beyond large cities, with smaller municipalities adopting similar practices.

This study highlights the growing importance of artificial intelligence in analyzing complex zoning codes, and offers new evidence that zoning reform, especially with FBCs, has the potential to create more sustainable cities by addressing sprawl, reducing car dependance, and supporting human-centered urban design.

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Link to article: https://www.nature.com/articles/s44284-025-00214-0