Artificial intelligence for green infrastructure optimisation to enhance climate change adaptation 

Supervisors

Tan Yigitcanlar (QUT)

The project

This project tackles the rising challenge of urban heat stress in neighbourhoods, where limited vegetation and dense development increase exposure to extreme temperatures. By developing an AI-powered optimisation framework, the research helps urban planners and councils strategically and effectively deploy green infrastructure, such as trees and vegetation.

Unlike traditional greening methods, this model prioritises thermal performance, land suitability, and social equity to determine where and what type of vegetation should be planted. This approach enables high-impact cooling interventions that improve outdoor comfort, support climate adaptation, and reduce reliance on energy-intensive cooling systems.

The project offers a scalable and transferable solution for creating cooler, healthier, and more climate-resilient urban environments, aligned with national goals for sustainability and innovation in city planning.