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We have 26 Remote Sensing PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships
Remote Sensing PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships
We have 26 Remote Sensing PhD Projects, Programmes & Scholarships PhD Projects, Programmes & Scholarships
PhD in Remote Sensing
Remote Sensing is the practice of observing geographical phenomena from afar. It is revolutionising the field of Geography by reducing the need for manual fieldwork and allowing geographers to gather data about dangerous or inaccessible regions.
As a PhD candidate in Remote Sensing, you might focus on collecting and analysing data about a particular region, type of terrain or geographical phenomenon. You could also work on developing or improving remote sensing technologies.
What’s it like to study a PhD in Remote Sensing?
You’ll be assigned a supervisory team that will guide you through the completion of an extended dissertation. Your final thesis should make a significant original contribution to the field.
Possible research areas include:
- Automated crater detection and classification
- Monitoring wildfire emissions
- Carbon capture
- Identifying geohazards
- Semi-autonomous planetary exploration
- Arctic surveillance
- Weather forecasting
Your research might involve using sensors carried by planes, UAVs, satellites or drones. These sensors may have technological capabilities such as Light Detection and Ranging (LIDAR) or Sound Navigation Ranging (Sonar).
Alongside your research, you may be required to attend additional training in fundamental areas such as satellite data and machine learning. You may also have the chance to present at academic conferences and publish your work in journals.
There are a number of advertised projects available in Remote Sensing, but many candidates will design their own project.
PhD in Remote Sensing Systems entry requirements
To apply for a PhD in Remote Sensing, you’ll usually need a good upper-second class Bachelors degree in a relevant subject area. A Masters degree may sometimes be required. It’s worth noting that applications are considered on a case-by-case basis and a postgraduate qualification will often be an advantage even if is not compulsory.
PhD in Remote Sensing funding options
Depending on your specific focus, PhD projects in Remote Sensing might be funded by the Engineering and Physical Sciences Council (EPRSC) or the Natural Environment Research Council (NERC). Research Councils provide studentships that cover your tuition fees and living expenses.
Full studentships are very competitive, so many students will need to self-fund their PhD. There are numerous options for candidates taking this route, including the UK government’s doctoral loan, support from charities or trusts, and part-time employment.
PhD in Remote Sensing careers
Many PhD graduates in Remote Sensing will go on to pursue a career in research. You may also wish to seek work as a professional remote sensing or geospatial intelligence analyst. Remote sensing has applications in many sectors such as resource management, environmental conservation, urban planning and security.
SCENARIO: The impact of high resolution modelling on mineral dust forecasts over West Africa using the ECMWF integrated forecast system (SC2023_02)
SCENARIO: New space-borne perspectives on the global carbon cycle: untangling role of complex vegetation canopies in novel satellite observations (SC2023_15)
A combined remote sensing and machine learning approach to monitoring crop stress and predicting crop yield
Developing a Wildfire Digital Twin: Attributing causes of extreme fire events
Improved monitoring of water resource and hazard using low earth orbit small satellites (RDFC23/EE/ROLLASON)
QUADRAT DTP: A sustainable future for Arctic marine shipping using Artificial Intelligence
Assimilating satellite land surface temperature data to improve numerical weather prediction skill
Follow the Water: Using remote sensing to move towards basin-wide assessments of changes in the deglaciating Peruvian Andes - SENSE CDT
A new, automated, high-resolution global wetland change map - SENSE CDT
Aerosol radiative effects on the global land carbon sink - SENSE CDT
Measuring the climate-smart practices using crop modelling, machine learning and remote sensing - SENSE CDT
Explainable Population Estimation Using Deep Learning from Satellite Imagery - SENSE CDT
Evolution of sub-surface damage and snow properties on Antarctic ice shelves- SENSE CDT
Remote sensing and machine learning techniques for improved nearshore wave prediction - SENSE CDT
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