Large Language Models in Urban Analytics

This editorial project reflects on how large language models are opening new possibilities for information extraction in urban analytics. Rather than treating LLMs only as writing tools, the piece considers how they may help lower the barrier for researchers working with urban text, imagery, and other messy sources of information.

The work sits at the intersection of generative AI, geospatial data science, and urban research, asking how these tools might support new ways of reading, structuring, and interpreting urban information while still requiring careful validation and domain knowledge.

Links: Project page · Publication page · https://doi.org/10.1177/23998083241235495