Climate warming is causing dramatic changes to Earth’s cryosphere. One clear manifestation of this warming is the thaw of frozen slopes, which reduces their stability and increases their geohazard. Due to their view perspective, most satellite-based earth observation sensors are limited in their utility when it comes to detecting mass movements (e.g. rockfall) from both large and small slopes. However, emergent ground-based remote sensing technologies such as gigapixel photogrammetry have exciting potential for advancing our understanding of climate-driven controls on slope evolution and geohazard, their role in wider landscape evolution, and for a fraction of the cost of other methods (e.g. terrestrial laser scanning).
The aim of this studentship is to develop and apply a new low-cost, high resolution, ground-based optical and thermal remote sensing solution for monitoring mass movement activity on slopes affected by permafrost thaw.
The studentship will develop and apply a new ultra-high-resolution solution for near real-time permafrost slope monitoring by:
- Adapting low-cost optical and thermal sensors and peripherals to construct a rugged imaging rig that can be installed in extreme environments for photogrammetric monitoring of slope instability;
- Developing and integrating an edge processing-based workflow for performing on-site surface change detection and transmitting key outputs (e.g. the location and geometry of instabilities) via cellular data or WiFi to the cloud for retrieval and further analysis;
- Provide real-world proof-of-concept by deploying the system to monitor slope evolution at either: i) a section of rapidly eroding permafrost coast in Arctic Canada, where coastal infrastructure and heritage are at risk, or ii) the Zugspitze, Germany, where permafrost thaw presents a geohazard to high-mountain cable-car infrastructure.
The successful applicant will be supported to produce high-quality peer-reviewed outputs at key project milestones and encouraged to disseminate their findings at scientific and industry conferences and via other channels as appropriate. The student will be based in the Department of Geography and Environmental Sciences, and will be co-supervised by staff in the Department of Computer and Information Sciences and the Department of Mechanical and Construction Engineering. They will be aligned to the University’s Extreme Environments Multi-Disciplinary Research Theme and will join a vibrant postgraduate community.
The Principal Supervisor for this project is Dr. Matt Westoby.
Eligibility and How to Apply:
Please note eligibility requirement:
- Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
- Appropriate IELTS score, if required.
- Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere or if they have previously been awarded a PhD.
We seek applicants with a background in one or more of the following: computer science, geosciences (geology, physical geography), civil engineering, electrical and electronic engineering, image analysis and machine learning. Crucially, applicants will have an interest in computer vision / photogrammetry and machine learning-enabled image analysis and will possess a drive to apply novel technologies to address real-world geoscience problems. Experience of using high-level programming languages is desirable.
For further details of how to apply, entry requirements and the application form, see
Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. MRDF22/…) will not be considered.
Deadline for applications: 18 February 2022
Start Date: 1 October 2022
Northumbria University takes pride in, and values, the quality and diversity of our staff and students. We welcome applications from all members of the community.