Leveraging Urban AI For High-Resolution Urban Heat Mapping: Towards Climate Resilient Cities

Our Tagar#EnvirnomentAndPlanningB article developed and implemented an advanced Urban AI tool—a U-Net convolutional neural network—for high-resolution mapping of Tagar#UrbanHeatIslands in metropolitan Tagar#Adelaide. By leveraging high-resolution satellite imagery and deep learning, this tool significantly improves spatial accuracy and computational efficiency compared to traditional methods, enabling near real-time, precise mapping of urban thermal environments.

Our tool achieved remarkable accuracy and rapid processing times, demonstrating its practical value for urban planners and policymakers to identify Tagar#HeatVulnerableZones and optimise targeted Tagar#MitigationStrategies like Tagar#GreenInfrastructure.

This study underscores the transformative potential of Urban AI to enhance Tagar#ClimateResilience, improve Tagar#PublicHealth outcomes, and support Tagar#SustainableUrbanPlanning.

Kudos to my talented PhD researchers Abdulrazzaq Shaamala and Niklas Tilly for their invaluable contribution to our ongoing effort to bridge Tagar#UrbanAnalytics and actionable Tagar#UrbanDesign.

Read the full text open access article from the link below and a copy is attached for convenience:

https://lnkd.in/eRJX87n6

Source:

https://www.linkedin.com/posts/yigitcanlar_leveraging-urban-ai-for-high-resolution-urban-ugcPost-7321316616388952065-cq_w/?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAtGGkQBsxwMBmX3lEJO8btihnfBCaHqTz4