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Validation of satellite derived bathymetry data in dynamic seabed settings (part of the SENSE Centre for Doctoral Training)

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  • Full or part time
    Prof David Hodgson
    Dr A Hogg
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (UK Students Only)
    Competition Funded PhD Project (UK Students Only)

Project Description

The shallow seabed is a highly dynamic setting, with mobile erosional and depositional bedforms, and rapid deformation and remobilisation events, constantly changing the bathymetry. Accurate data from nearshore environments (less than 15 m depth) is critical to support maritime transport, coastal zone management, environmental protection, maritime boundary delimitation, defence and tourism globally. For example, forecasting the patterns of marine inundation with projected accelerated sea-level rise along many coastlines is complicated by patterns of erosion and deposition in the nearshore environments. Shipborne acoustic surveys often achieve centimetre-level accuracy, but are time-consuming, expensive, and rarely conducted in nearshore areas, meaning that the coastal zone remains a data gap. However, Satellite Derived Bathymetry (SDB) is being adopted as a spatially and temporally higher resolution and cheaper method for bathymetric mapping than traditional shipborne surveys. Remote sensing of coastal zone bathymetry can benefit from satellite imagery with high spatial resolution and acquisition repeat frequency, high radiometric resolution, sufficient image quality, and suitable blue and green bands.

SDB methods can be categorised into three types: i) an empirical approach, where a regression between in-situ calibration data (e.g. known depths and various colour indexes) is developed; ii) a physics-based Radiative Transfer Model (RTM) approach, where light interactions with the water surface, water column and seafloor are simulated; and iii) photogrammetric techniques, where feature extraction and image geometry is used to estimate bathymetry, rather than spectral radiance. Empirical approach relies on existing in-situ depth data, and struggles with heterogeneous seabed settings, and the physics-based approach requires precise atmospheric correction, which is not always available. Photogrammetric approaches are a geometric operation that do not rely on accurate spectral information, therefore no spectral atmospheric correction is necessary, making it useful in difficult atmospheric conditions.

Although SBD is being widely adopted as a relatively cheap and spatially extensive technique to provide support to traditional surveys by filling gaps, and monitor change in areas of dynamic seabed features, there remains a need to validate the best (combination of) approaches to assess a given seabed system. Repeat bathymetric survey datasets available to this PhD studentship include: i) several windfarm arrays that document bedform migration, which pose a risk to renewable energy infrastructure, ii) new repeat surveys after Anak Krakatau collapse, which is building and represents an eruption risk, and iii) the dynamic fjord-head deltas of British Columbia, which are a natural laboratory for understanding the initiation of sediment gravity flows, and investigating the completeness of the stratigraphic record.

The studentship will benefit from the broad spectrum of training workshops facilitated by the NERC Earth Observation CDT, with opportunities for additional relevant training (e.g. in process sedimentology, bathymetric mapping). This research project will build upon collaboration between the University of Leeds and the National Oceanographic Centre, Southampton (co-supervisors Mike Clare and Izzy Yeo), and will involve spending time at the CASE partner (TBC).

This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See

Funding Notes

This 3 year 9 month long NERC SENSE CDT award will provide tuition fees (£4,500 for 2019/20), tax-free stipend at the UK research council rate (£15,009 for 2019/20), and a research training and support grant to support national and international conference travel.


Clare, M.A., Vardy, M.E., Cartigny, M.J., Talling, P.J., Himsworth, M.D., Dix, J.K., Harris, J.M., Whitehouse, R.J. and Belal, M., 2017. Direct monitoring of active geohazards: emerging geophysical tools for deep-water assessments. Near Surface Geophysics, 15(4), pp.427-444.
Vendettuoli, D., Clare, M.A., Clarke, J.H., Vellinga, A., Hizzet, J., Hage, S., Cartigny, M.J.B., Talling, P.J., Waltham, D., Hubbard, S.M. and Stacey, C., 2019. Daily bathymetric surveys document how stratigraphy is built and its extreme incompleteness in submarine channels. Earth and Planetary Science Letters, 515, pp.231-247.

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FTE Category A staff submitted: 79.20

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