Across the UK, archives of planning documents contain decades of valuable information about land use, development decisions, and policy change. Yet much of this information remains locked in scanned documents, static PDFs, and legacy formats—difficult to access, analyse, or visualise at scale.

This talk explores the potential of open source and AI-driven geospatial workflows to unlock and structure historic planning data. It will present an approach for extracting text, identifying meaningful spatial and semantic information, and linking that to modern geospatial frameworks for exploration and analysis.

Focusing on reproducibility and accessibility, the session outlines a conceptual pipeline that can be adapted by organisations involved in land and property management—such as land registries, planning authorities, and geospatial consultancies—who seek to make better use of archival planning records. Attendees will learn how geospatial AI can support land and property management by bridging the gap between analogue history and modern digital systems.