Sector · Urban planning
Track growth, site with evidence, show the impact.
Planning decisions depend on layers that are out of date the day they are published. GeoAI keeps the picture of the city current and makes trade-offs visible.
Problems we solve
Where GeoAI helps in urban planning
Land-use change is spotted late
New construction and land conversion show up in cadastral updates months after the fact. Change detection on imagery flags them between survey cycles.
Siting relies on static layers
Suitability work often stops at overlaying zoning and distance rules. We add terrain, hazard, access and observed land cover, and make the weighting explicit.
Impact is hard to show stakeholders
Council members and communities do not read GIS projects. Focused maps and scenario views make the case without a briefing on the data model.
Consulting
Imagery AI for change and land-cover layers, dashboards to put them in front of decision makers.
Academy
GIS and GeoAI training
Give planning staff the GIS foundations and the GeoAI literacy to commission and check this kind of work.
See the trainingInsights
GIS in urban planning, updated with a GeoAI angle
How classic GIS planning workflows change once imagery and machine learning are added.
Read the articleWorking in urban planning? Tell us the problem.
A short call is enough to tell whether GeoAI can help, and what a pilot would look like.