PhD Study : Cities conformity to the United Nations Paris Agreement: Climate-resilient development pathways through spatio-temporal assessment of urbanisation, urban heat islands, and local climate zones

Summary

Cities cover just 3 per cent of Earth’s land surface, yet accommodate more than half the world’s population. Climate change is one of the biggest challenges and its projections predict substantial impacts on cities and human development in future. According to a United Nations (UN) estimate, 70 per cent of the world’s population will be living in urban settlements by 2050. The sustainable development goal (SDG) 11 of the UN highlights the importance of sustainable cities and communities.

The Paris Agreement approved and adopted by 197 countries in December 2015 at the Conference of Parties to the UN Framework Convention on Climate Change (UNFCCC), also known as COP 21, aims to mitigate the impacts of climate change by controlling the global temperature rise through reducing carbon emissions. The heat produced as a by-product of higher energy consumption combined with the impervious surfaces in cities form Urban Heat Islands (UHIs) where the urban settlements are significantly warmer than its surrounding areas. A Local Climate Zone (LCZ) classification scheme categorises an area into various zones based on the properties of surface structure and surface cover, and offers a standardised method to observe UHIs.

A long-term analysis of UHIs and LCZs can therefore help evaluate: (1) the effects of urbanisation on UHIs and LCZs; and (2) the effectiveness of measures taken by various cities/regions in controlling heat waste over the past years.

Objectives of the Research:

This project aims to evaluate how effectively various cities from countries signing up to the Paris Agreement are performing to reduce their emissions, which will be assessed through spatio-temporal analysis of urbanisation, UHIs and LCZs.

The objectives of this research are to employ remote sensing (satellite, airborne, ground-based, or a combination of any of these) and other spatial data in order to:

(1)develop a robust model for spatio-temporal assessment of urbanisation, UHIs and LCZs at city and/or regional scales;

(2)assess the spatio-temporal trends of urbanisation, UHIs and LCZs in selected cities/regions to gauge their success in reducing urban heat footprint; and

(3)propose measures to help achieve the targets of SDG11 in light of the research findings.

Methods to be used:

Satellite remote sensing (satellite, airborne, ground-based, or a combination of any of these) and other spatial data will be processed and analysed in this study to examine spatio-temporal variations in land use / landcover, UHIs and LCZs in at least two cities/regions using methods similar to, for example, de Faria Peres et al. (2018); Mills et al. (2015) and Liu & Shi (2020).

The candidate is expected to review the UN’s SDGs relevant to the project, and to gauge the success of selected cities/regions in reducing their urban heat footprint using the spatio-temporal assessments of UHIs and LCZs. Suitable measures would be proposed to help achieve the targets of SDG11 in light of the research findings.

Desirable Criteria:

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

*Demonstrated experience in processing and analysing spatial data (including remote sensing datasets) using software packages such as Erdas Imagine, ArcGIS, QGIS, or others.

*Experience in carrying out independent research demonstrated by, for example, research publication(s) or research project(s) on a subject similar to this research topic.

*Experience in using statistical software packages such as R.

Skills required of applicant:

*A theoretical and practical background in Geosciences or related field.
*An understanding of optical and thermal remote sensing concepts (in relation to terrestrial remote sensing).
*Ability to acquire, process and analyse remote sensing and other spatial data.
*An interest in remote sensing, GIS, climate change, or some combination.
*Ability to work independently.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

Funding and eligibility