Satellite image analysis for monitoring climate change effects on land cover

Eligibility: UK/EU/International graduates with the required entry requirements

PhD funding award: No award (self-funding)

Duration: Full-Time – between three and three and a half years fixed term

Application deadline: 1st November 2019

Interview dates: Will be confirmed to shortlisted candidates

Start date:  January 2020

To find out more please contact Dr Sara Sharifzadeh


Coventry University (CU) is inviting applications from suitably-qualified self-funded graduates for a PhD studentship in satellite image analysis domain.

Coventry University has been voted ‘Modern University of the Year’ three times running by The Times/Sunday Times Good University Guide. Ranked in the UK’s top 15 (Guardian University Guide), we have a global reputation for high quality teaching and research with impact. Almost two-thirds (61%) of our research was judged ‘world leading’ or ‘internationally excellent’ in the Research Excellence Framework (REF) 2014.

The Institute for Future Transport and Cities brings together world class expertise in disciplines across art and design, human factors, engineering, manufacturing, computer systems and business studies to deliver safe and sustainable transport solutions fit for the cities of the future. The institute works across three core themes of;

  • Training and skills development,
  • Research to demonstrate new technologies,
  • Commercialisation of this new technology to deliver impact and business growth.

The Project

Climate change is one of the major global challenges that has significant economic and social consequences. One of the main sources of data for analysis of climate change and understanding of the influencing factors is satellite image. Satellite images provide information about Earth’s surface, subsurface and atmosphere. One of the Essential Climate Variables (ECVs) that significantly dependent on satellite observations include Terrestrial observations such as land cover. Change detection in land cover and vegetation indexes over time, urban area monitoring, deforestation assessment, agriculture and natural hazards mitigation are examples of remote sensing applications in climate change studies. While detection of changes addresses part of the required information in such studies, the detection of type of changes is an active research area.

In this project, image analysis and machine learning techniques are employed to analyse the satellite images in order to investigate the influence of the ECVs on climate change. The focus is specifically on the interaction of the climate change ECVs and land cover. For this aim, object detection, classification and time series analysis techniques will be employed.

Funding details

For the academic year 2019/20, English-resident UK and EU students, or EU students moving to England for a PhD, who are not in receipt of Research Council funding or other direct government funding can apply to borrow up to £25,000 to help cover the cost of their PhD tuition fees. Further details can be found here. 


Considering the climate change as a global challenge and the trend toward developing prevention, mitigation or adaptation policies, this project utilises satellite image analysis in order to develop predictive models for climate change ECVs such as emission maps using land cover maps and their changes. This allows developing climate change prediction models using the land cover maps and estimated ECVs.

As a result, further improvement in understanding of the global climate system dynamics will be achieved that helps the stakeholders on analysis of the climate change impacts on digital economy e.g. water resources, deforestation and alleviation of the rapid and unprecedented consequences of climate changes by taking policies, for example by removing CO2 from the atmosphere, through e.g. reforestation and improved land management.

On the other hand, employing and developing image analysis and AI techniques, strengthens the candidate skills in one of the important branches of computer science as a support for future career.

Coventry University will benefit from this cutting-edge research project by generating three journal publications in high-impact journals, e.g. Elsevier and IEEE Transactions. This will helps the University to meet its target in the UK Research Excellence Framework (REF) also improve its position globally.

  • Our research strategy is underpinned by a £250m investment in research and facilities
  • Dedicated Doctoral College and Centre for Research Capability Development deliver high quality professional support for researchers, from PhD to Professor
  • Free training: research career planning, managing your doctorate, research communication skills, research ethics, research impact, research integrity, research methods and research supervision
  • Coventry is a member of the Doctoral Training Alliance (DTA), the largest multi-partner and only nationwide doctoral training initiative of its kind.

Training and development

The successful candidate will receive comprehensive research training including technical, personal and professional skills. All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.

Entry requirements

  • A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the Project element or equivalent with  a minimum 60% overall module average.

In the event of a first degree classification of less than 2:1, a Masters Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at minimum merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at minimum merit level (60%).


  • a taught Masters degree in a relevant discipline, involving a dissertation of standard length written in English in the relevant subject area with a minimum of a merit profile: 60% overall module average and a minimum of a 60% dissertation mark


  • the potential to engage in innovative research and to complete the PhD within a three-year period of study
  • a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)

Candidate specification

  • A good knowledge of linear algebra, machine learning and AI concepts, linear/non-linear systems, and willingness to quickly learn further in this area
  • Experimental, modelling or analytical experience related to signals and multivariate data preferably spectral images
  • Good programming skills in MATLAB/Python
  • Good writing and interpersonal/communication skills

How to apply

Apply online by submitting full supporting documentation, and covering letter only.

Apply to Coventry University