Authors
Alexis Litvine
Senior Researcher at The Cambridge Group for the History of Population and Social Structure (CAMPOP)
MAPLE: Map Automation for Planning and Local Efficiency
Principal Investigator: Alexis Litvine, University of Cambridge
Council Partner: Greater Cambridge Shared Planning Service
Every year high numbers of planning documents need to be processed by Cambridge City Council and South Cambridgeshire District Council. These can include a range of images, like hand drawn, scanned or photographed maps. Currently, each map image has to be processed, digitised and uploaded manually, which is time consuming, repetitive and contributes to backlogs.
MAPLE is an AI-assisted map processing system, which can detect and isolate the map areas within submitted documents; match and align map extracts to official maps; extract and classify features added by applicants, like boundaries or access routes, and analyse text such as “proposed extension”. These functions can all be reviewed by staff, which is essential given the legal importance of these documents. Data can then be shared across planning teams in dashboards and interactive maps.
Potential benefits include a significant reduction in manual processing time to speed up application turnaround and improve service delivery; specialist staff freed up for tasks which require human judgement and decision-making, and the ability to generalise methods and models across UK councils.