科克大学学院招收农业地理博士
About the Project
Background
The current paradigm in the monitoring of agriculture activity is moving towards one of continuous assessment, rather than annual checks. This project looks to develop this approach for the assessment of farm habitat quality and extent, building on existing projects, with the overall goal being to create a method to automatically score the biodiversity elements of a farm on a continuous basis using Earth Observation (EO) data.
The PhD student will explore the use of EO data sources (Copernicus Sentinel), along with terrestrial photography (smartphone) and drones within a Machine Learning (ML) environment to move beyond mapping of habitats on farms toward assessing and scoring habitat quality. The student will work with farms taking part in the Teagasc Signpost scheme, using manual inspection scoring provided from farm visits by advisors (using Department of Agriculture score cards) as ground truth. The model approach will be tested on a subset of Signpost farms to automatically generate an annual score to help achieve habitat goals. The assessment will be validated using terrestrial photography captured on the Agri-Snap app, using automatic machine learning identification of key habitats from the imagery. A significant work package will examine in detail the scoring of hedgerow condition from satellite data - with farm captured hedgerow score sheets linked to the satellite imagery through drone photogrammetry – linking the overhead footprint of the hedgerow with condition data captured horizontally in the field.
The PhD student will create a new method for directly creating an automatic Biodiversity Score for any farm, including hedgerow specific metrics. Additional metrics will be created to allow for identification of the direction of travel of habitat based advice (going beyond overall area, to also consider value, quality and landscape level linkages) over a 5 year period.
The Structured PhD at University College Cork (UCC) normally lasts for three to four years and students are required to complete a minimum of 15 credits, and a maximum of 30 credits, of taught postgraduate training modules during that time. Training will also be given through the Teagasc Walsh Scholarship programme, and in-house (including drone training).
Requirements
Applicants should have a good primary degree (First or Upper Second Class Honours), and preferably an M.Sc. in an appropriate discipline (Remote Sensing, Agricultural Science, Computer Science, etc.). The successful candidate should be highly self-motivated and a good communicator in both oral and written format. Experience of computer programming and working with drones would be an advantage. The successful applicant will be required to demonstrate English Language Competency to UCC guidelines.
Award
The PhD Fellowship is a joint research project between Teagasc, Ashtown, and the Department of Geography, UCC, with the student registered for a four year PhD degree programme at UCC. The student will be based, either at UCC working under the supervision of Dr. Fiona Cawkwell, or at Ashtown, Dublin under Teagasc supervisor Dr. Stuart Green. The Fellowship will start as soon as possible after 1st of October 2023 when the most suitable candidate is appointed.
The fellowship provides a stipend of €19,000 per annum, with university fees up to a maximum of €6,000 per annum paid in addition to the stipend, for up to 4 years.
To apply
Submit an electronic copy of Curriculum Vitae and a letter of interest simultaneously to: Dr Fiona Cawkwell (f.cawkwell@ucc.ie) and Dr. Stuart Green (stuart.green@teagasc.ie) with the email subject: Walsh Fellowship
For more information please contact:
Dr Fiona Cawkwell email: f.cawkwell@ucc.ie
Dr. Stuart Green, email: stuart.green@teagasc.ie
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