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Cambridge NERC Doctoral Training Partnerships

Graduate Research Opportunities

Supervisors: Iris Möller (Geography), G Smith (Specto Natura Ltd.) and Tom Spencer (Geography)

Importance of the area of research:

The world's coasts, their residents, habitats, and resources, have come under enormous pressure over recent decades. Human development and exploitation of resources (population at the coast growing at three times the global average), rising sea levels, altering wind/wave climates and modification of sediment transport (river damming, coastal erosion protection) all create unprecedented challenges. To address these challenges, the intertidal zone dynamics must be better understood. Information on his zone and its dynamics, however, has been difficult to obtain regularly and over large areas, due to inaccessibility by land (soft sediments) and sea (very shallow water). Earth Observation has seen large advances over the past decades in terms of improvements to spatial, temporal, and spectral resolution of sensors and ease of access to satellite images. This project exploits this new technology to deliver much needed improvements in our understanding of intertidal coastal processes and modelling capabilities, particularly on coasts where the (re)creation of intertidal wetland is increasingly being considered as a climate change adaptation and natural capital maintenance strategy.

Project summary:

The possibility of using high frequency monitoring of intertidal coastal areas through the new satellite systems now available offers unprecedented opportunities to gain insights into both the complexity of existing and potential future (managed realignment) intertidal coastal surfaces and their change over a range of time scales. The project aims to develop a remote-sensing based ‘INtertidal REsponse Model' (INREM) to understand/simulate coastal dynamics in response to human/climate drivers. This will be achieved by using remote sensing products at high spatial and temporal resolution alongside existing field data to inform the science of biological and physical processes and their interaction within intertidal zones. Results will provide a better understanding of the dynamics of such environments, how they deliver ecosystem services and reduce coastal flood and erosion risk.

What the student will do:

This project will exploit the multi-temporal (up to daily acquisitions, resulting in multiple cloud-free images per month) capability from recently launched optical satellite constellations (such as the EU's Copernicus ‘Sentinel-2' satellites and others). The student will conduct image processing and integrate data for intertidal zones in the UK and particularly those on which managed realignment of sea defences has taken place (or is due to take place), to map temporal change and ecosystem service-related parameters of intertidal surface characteristics and to derive a prototype ‘Intertidal Response Model' (INREM) that aims to predict the response of the intertidal shore to climate drivers and realignment of coastal protection structures. Ground based UAV surveys will be used to capture images of much higher spatial resolution that can then be ‘down-scaled' in spatial resolution to investigate the effects of aggregation of surface features into larger pixel units. The reduction in accuracy of the model (or indeed the potential for an increase in accuracy of certain features) resulting from such ‘coarsening' of image spatial resolution will be quantified and analysed statisticall

Please contact the lead supervisor directly for further information relating to what the successful applicant will be expected to do, training to be provided, and any specific educational background requirements.


Friess, D. a., Spencer, T., Smith, G. M., Möller, I., Brooks, S. M., &
Thomson, a. G. (2012). Remote sensing of geomorphological and ecological
change in response to saltmarsh managed realignment, The Wash, UK.
International Journal of Applied Earth Observation and Geoinformation, 18,

Medeiros, S., Hagen, S., Weishampel, J., & Angelo, J. (2015). Adjusting lidar-derived digital terrain models in coastal marshes based on estimated aboveground biomass density. Remote Sensing, 7(4), 3507-3525.

Forster, R. M., & Jesus, B. (2006). Field spectroscopy of estuarine intertidal habitats. International Journal of Remote Sensing, 27(17), 3657-3669.

Follow this link to find out about applying for this project.

Other projects available from the Lead Supervisor can be viewed here.

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