About the Project
The growing body of high-resolution earth observation data provides an opportunity to study the oceanic conditions associated with whale strandings. Stranded whales tend to be the most visible indicator of contamination events , so high-resolution observations of the local marine environment  associated with stranding events (e.g. sea-surface salinity and temperature, ocean colour and chlorophyll ) could point to local variations in ocean health and provide new tools for future monitoring of strandings and their causes.
Aim and objectives: The aim of this project is to automate the identification of stranded whales on satellite imagery, and to identify ocean health-related parameters associated with whale stranding events. The objectives are:
Develop an automated identification technique for stranded whales from satellite imagery;
Find relationships between local marine environmental variables and whale strandings;
Assess impact of local ecosystem health on stranding patterns and identify predictors of future strandings.
Methodology: In this project, we will develop analytical tools for identifying and classifying stranded whales on satellite imagery, using machine learning approaches (e.g. convolutional neural networks, among others), applied to existing archival images of stranded whales (including down-sampled images from aerial and drone surveys). We will then collate high-resolution remotely-sensed earth observation data from the vicinity of stranding hotspots (such as WorldView or Pleiades), to assess which environmental parameters are associated with stranding periods. The project will focus in particular on sites in Chile  and New Zealand , where strandings regularly occur. During the PhD, the student will benefit from an excellent supervisory team with expertise in whale population biology (Dr Jen Jackson); remote sensing of coastal systems (Dr Encarni Medina-Lopez); use of satellite imagery to study animals (Dr Peter Fretwell); whale strandings and New Zealand marine ecology (Dr Karen Stockin); Chilean whale populations and marine ecology (Dr Carlos Olavarría); earth observation with satellites (Dr Gwawr Jones, JNCC CASE Partner).
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 http://www.eo-cdt.org
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Fretwell PT, Jackson JA, Ulloa Encina MJ, Haussermann V, Perez Alvarez MJ, Olavarria C, et al. Using remote sensing to detect whale strandings in remote areas: The case of sei whales mass mortality in Chilean Patagonia. PLoS One. 2019;14(10):e0222498.
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Betty EL, Breen BA, Murphy S, Ogle M, Hendriks H, Orams MB, Stockin KA. Using emerging hot spot analysis of stranding records to inform conservation management of a data-poor cetacean species. Biodivers Conserv. 2019;29:643-65.
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