A Dynamic Framework for a GeoAI-Driven Updatable Planning System

Author:  Dr. Hossny Azizalrahman Traditional urban master plans are static documents that struggle to keep pace with rapid urban transformat...





Author: Dr. Hossny Azizalrahman

Traditional urban master plans are static documents that struggle to keep pace with rapid urban transformations. By the time a decadal plan is reviewed, ground realities have already shifted. To bridge this gap, our latest research introduces a dynamic framework that transitions urban governance from periodic, manual reviews into a continuous, data-driven ecosystem.

At the core of this framework is an updatable City Engine” powered by Geospatial Artificial Intelligence (GeoAI). By integrating deep learning models and automated change detection, the system continuously monitors urban metabolism. Rather than relying on intermittent manual data collection, it leverages real-time spatial data to capture physical, environmental, and infrastructural changes automatically.

Crucially, the framework incorporates a simulation layer governed by heuristic logic and GIS-based rules. When real-world changes deviate from strategic goals, the system triggers automated plan amendments, ensuring that planning policies remain dynamically aligned with actual development. This allows municipalities to maintain statutory compliance and swiftly implement climate-resilient strategies, such as Nature-Based Solutions.

By establishing a live body of knowledge, this GeoAI-driven framework empowers city leaders with actionable, real-time insights, transforming master planning into an adaptive, predictive tool. 

Building on this framework, our future research focuses on scaling this City Engine to integrate live carbon-footprint tracking and predictive land-value capture metrics.


About the Author

Dr. Hossny Azizalrahman is a university professor and strategic advisor with a PhD in planning and decades of expertise in urban and regional development. His areas of specialisation include GIS-driven digital twins, land-use legislation, sustainability, and strategic urban planning. He is also a member of prestigious international organisations.

Respectfully,
Dr. Hossny Azizalrahman
Department of Urban Planning
Faculty of Architecture
King Abdulaziz University



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London Journals Press: A Dynamic Framework for a GeoAI-Driven Updatable Planning System
A Dynamic Framework for a GeoAI-Driven Updatable Planning System
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London Journals Press
https://blog.journalspress.com/2026/06/a-dynamic-framework-for-geoai-driven.html
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https://blog.journalspress.com/2026/06/a-dynamic-framework-for-geoai-driven.html
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