Study level

  • PhD
  • Master of Philosophy
  • Honours
  • Vacation research experience scheme

Faculty/School

Faculty of Engineering

School of Architecture and Built Environment

Topic status

We're looking for students to study this topic.

Research centre

Supervisors

Professor Tan Yigitcanlar
Position
Professor
Division / Faculty
Faculty of Engineering

External supervisors

  • Abdulrazzaq Shaamala

Overview

Green infrastructure refers to public and private green spaces in cities that provide water cycle benefits. These green spaces range in the range from single trees on city streets to urban parks, and waterway walkways. Some are natural, such as the remains of native plants, while others are more geometric, for example green roofs and green walls. Green infrastructure can increase the sustainability and vitality of cities through benefits such as greening and cooling, water quality, and managing hotter weather. Green infrastructure can play an important role in improving living.

Reference

Teimouri, R., & Yigitcanlar, T., (2018). An approach towards effective ecological planning: quantitative analysis of urban green space characteristics. Global Journal of Environmental Science and Management, 4(2), 195-206.

Research activities

This project will aim to investigate methods to optimise green infrastructure for climate change adaption such as (urban flood resilience, and carbon emission reduction) particularly using machine learning approach. As part of the research project, you will undertake the following tasks (through desktop research):

  • investigate modelling approaches including machine learning models that are used for green infrastructure optimisation
  • analyse the goals and objectives that used for green infrastructure optimisation to adapt and mitigate climate change from the literature
  • present the findings in a concise report and poster

Outcomes

The outcomes of this work will include:

  • a concise project report on optimisation models and their objectives
  • a digital poster presenting methodology and key study findings

Skills and experience

  • data collection skills
  • analytical ability
  • problem solving skills
  • adequate methodological background
  • broad understanding on smart homes
  • excellent written and verbal communication skills
  • ambition to complete a research project within a given timeframe

Keywords

Contact

Contact the supervisor for more information.