2026-10-12 –, Create 1
For more than four decades, the geospatial community has been building the digital foundations of our world. Open source projects such as GDAL, PostGIS, QGIS, PDAL and OpenStreetMap have transformed how we capture, process, share and understand geographic information. They are the foundations on which an entire industry has been built.
But we have reached a new frontier.
We have become exceptionally good at representing the world. We can map it, model it, render it and query it. Yet representation is not understanding. A coordinate is not a place. A building footprint is not a building. A point cloud is not a physical environment.
A place has context, history, relationships, purpose and meaning.
As AI systems move from answering questions to taking actions in the physical world, the next generation of geospatial technology faces a fundamental challenge: how do we give machines a sense of place?
Foundation models have demonstrated remarkable capabilities, but intelligence about the physical world requires more than language. It requires spatial memory, continuous observation, simulation, context and reasoning. The future will not be defined only by larger models, geometries or attributes, but by better representations of the world: representations that capture context, relationships, change, history and meaning of its existence.
In this keynote, I will explore the transition from geospatial data to spatial intelligence. Drawing from lessons building a multi-million-pound geospatial technology company on the shoulders of open source, I will challenge this awesome community:
What is the equivalent of GDAL, PostGIS or OpenStreetMap for spatial reasoning?
How do we move from mapping the world to understanding it?
What role should the open geospatial community play when the next generation of GIS users may not be human?
The next era of geospatial is not about creating more maps or more AI. It is about creating systems that understand places.
The question is: who will build the open foundations for machines to understand our world?
Fakhar Khalid is a data scientist, technologist and Chief Scientist, CTO and Head of Sensat Labs at Sensat. He works at the intersection of geospatial data, AI, machine learning and digital twins.