Royal Society Funded PhD Studentship: Remote Sensing to Assess and Monitor Funding Conditions

Royal Society Funded PhD Studentship: Remote Sensing to Assess and Monitor Funding Conditions

swansea universitySwansea University is a research-led university that has been making a difference since 1920. The University community thrives on exploration and discovery, and offers the right balance of excellent teaching and research, matched by an enviable quality of life.

The University has enjoyed a period of tremendous growth, and we have achieved our ambition to be a top thirty research University, soaring up the 2014 Research Excellence Framework league table to 26th in the UK from 52nd in 2008.

Additionally, an ambitious Campus Development Programme is well underway – one of the largest knowledge economy projects in the UK and within the top five in Europe.

Applications are invited for a Royal Society funded Ph.D. studentship in Geography.

Project Description:

This project will explore the use of remote sensing from satellite images, aircraft and Unmanned Autonomous Vehicles (UAVs) to improve monitoring of forests. The candidate may have skills in one of a number of related areas (e.g. Geography, Forestry, Physics, Computer Science, Engineering or Biology), and will join a leading interdisciplinary team based in the Department of Geography, Swansea University.

Forests play a significant role in the global carbon cycle, through uptake by photosynthesis and long-term storage in biomass. As a result, countries are required to carry out an inventory of forest resources under the UN Framework Convention on Climate Change. However, forests are dynamic, responding to environmental conditions and are subject to disturbance, both natural (e.g. wind damage or impacts from pests and diseases) and through management or deforestation.

In recent years, there has been widespread concern about the spread of pests and diseases in Britain’s forests, and the damage that these cause.  Changes in productive forest area and forest growth can impact the accuracy of information maintained about our forest resources. These factors can lead to loss of wildlife habitats, reduced carbon uptake from the atmosphere, economic impacts on forest industries and destruction of recreational areas enjoyed by the public. Early detection of key indicators of vegetation condition and change will inform effective management and help to limit and contain the problem.

The Forestry Commission currently relies on field inspections to determine the location and nature of threats. For effective management, mapping of spatial extent, progression and damage severity is imperative. Remote sensing offers a means both to monitor vegetation condition indicators and to estimate key forest parameters over large areas and at frequent intervals.

The project is expected to combine remote sensing from UAV, airborne and satellite sensors, field data collection and modelling techniques to facilitate the early detection of vegetation condition and processes of decline and recovery. The research is carried out in close collaboration with the Forestry Commission agency Forest Research, ensuring the operational relevance of the results and their benefits for UK forestry needs.

Please note: this is a full-time position. The University’s regulations regarding Ph.D. degrees can be found here:

The successful candidate is expected to start their studentship on either 1st July 2016 or 1st October 2016.


Candidates must hold an upper second class honours undergraduate degree or a Master’s degree (with Merit), in a relevant discipline, such as Geography, Forestry, Physics, Computer Science, Engineering or Biology.

Non-native English speakers will be required to demonstrate an English language competency of 6.5 in the IELTS (with 5.5 in each component) or equivalent.

This scholarship is open to UK, EU and international applicants.


The studentship covers the full cost of UK/EU tuition fees, plus a tax free stipend of £13,863 p.a for three years.

UK/EU and international students are welcome to apply, though only UK/EU tuition fees are covered by this studentship. International students will be required to pay the difference between UK/EU and international tuition fees.

How to Apply

Deadline: 10 June 2016

Applicants must complete and submit the following documentation by the stated deadline.

  • To apply for this studentship, please download the research scholarship application form and return it to the College of Science with the following:
  • Academic References – all scholarship applications require two supporting references to be submitted. Please ensure that your chosen referees are aware of the funding deadline, as their references form a vital part of the evaluation process. Please either include these with your scholarship application or ask your referees to send them directly to
  • Academic Transcripts and Degree Certificates – academic transcripts and degree certificates must be submitted along with the scholarship application by the funding deadline. We will be using these to verify your academic qualifications.
  • A recent CV

Applicants should use the ‘Supplementary Personal Statement’ section of the application form to explain why the award they are applying for particularly matches their skills and experience and how they would choose to develop the project. Please email the documents to or post them to:

Recruitment and Marketing Team
College of Science
Wallace Building
Swansea University
Singleton Park
Swansea SA2 8PP

Read more at:

Categories: Courses, Remote Sensing

About Author

GIS Resources

GIS Resources is an initiative of Spatial Media and Services Enterprises with the purpose that everyone can enrich their knowledge and develop competitiveness. GIS Resources is a global platform, for latest and high-quality information source for the geospatial industry, brings you the latest insights into the developments in geospatial science and technology.

Write a Comment

Your e-mail address will not be published.
Required fields are marked*

This site uses Akismet to reduce spam. Learn how your comment data is processed.