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  HyReS Wetlands: Hyperspectral Remote Sensing for Irish Wetland Ecosystem Mapping and Monitoring(Ref: CW_2023_17_WSCH_3)

   Research Centre

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  Dr Owen Naughton, Dr Lizy Abraham, Dr Shane Regan  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Project Key Words: (enter 3 to help advertise on online platforms) image processing, machine learning, hyperspectral remote sensing

Post summary

An outstanding PhD student is sought for a 4-year fully funded project with the objective of developing and testing hyperspectral image classification techniques for mapping and monitoring of wetland ecosystems.

Wetlands are amongst the most valuable ecosystems on earth. They provide a broad range of ecosystem services such as carbon sequestration, water supply and purification, as well as providing habitats to a diverse array of flora and fauna. However, climate change, biodiversity loss and eutrophication threaten many of the world’s wetland ecosystems. The sustainable management of wetlands requires us to have the ability to accurately map and monitor these ecosystems. In this context, airborne hyperspectral imaging represents an opportunity to revolutionise wetland ecosystem research by collecting imagery at an unprecedented spectral and spatial resolution at relatively low cost. However, a lack of proven and standardised mapping methodologies and similarity (visual and spectral) of complex vegetation in wetland ecosystems all represent significant barriers to the operational use of UAV-hyperspectral data.

The objective of this research is to develop and test a suite of reproducible airborne hyperspectral remote sensing image processing techniques for quantitative mapping and monitoring of ecologically significant wetland ecosystems. Whilst a range of Machine Learning (ML) and Deep Learning (DL) techniques have been applied in the literature for UAV image segmentation, it remains unclear which approach is optimal for the identification of wetland communities. Therefore, relevant spectral indices and classification approaches will be developed to acquired hyperspectral imagery and compared for classifying wetland distribution and composition, tracking restoration, and correlating with ecosystem carbon fluxes.

The position is fully funded for four years and brings with it a stipend of €18,500/year plus fees together with provision for fieldwork, conferences and external course attendance. The successful candidate will join a growing Environmental Engineering research group at South East Technological University (SETU) and will work closely with existing PhD researchers developing UAV-multi- and hyperspectral remote sensing methods for mapping and monitoring intertidal and coastal ecosystems. The candidate will also get to work in collaboration with external project partners the National Parks and Wildlife Service, the Marine Institute and the Abbeyleix Bog Project community group. Person specification

We are looking for an enthusiastic, self-motivated researcher with interests in image processing, machine learning, remote sensing and/or environmental engineering. The PhD candidate should have the following qualifications, experience and competencies:



·       Honours Degree (minimum 2:1) in a relevant discipline (computer science, engineering, electronic engineering, civil and environmental engineering) from an internationally recognised institution.


·       A Masters level qualification in remote sensing/image processing would also be desirable.

Knowledge & Experience


·       Knowledge of image processing, image classification and machine learning.

·       A strong motivation for research and be able to demonstrate ability in data analysis, programming and remote sensing or demonstrate the capacity to develop such skills.

·       Demonstrated organisational skills, time management and ability to work to priorities.

·       Ability to write research reports or other publications to a publishable standard.


·       Experience in the use of fixed wing or rotor commercial drones would be an advantage.

 Skills & Competencies


·       Strong proficiency in spoken and written English is required, together with excellent written and oral communication skills.

·       Applicants whose first language is not English must demonstrate on application that they meet SETU’s English language requirements and provide all necessary documentation. See Page 7 of the Code of Practice

·       In order to be shortlisted for interview, you must meet the SETU English speaking requirements so please provide evidence in your application. 


·       A full EU Drivers Licence is desirable.


Computer Science (8) Engineering (12)

Funding Notes

Department /School/Faculty

Built Environment/Faculty of Engineering


4 Years(48 Months )

Status: Full-time / part-time

Full Time

Funding information

SETU PhD Scholarship Programme 2023

Value of the scholarship per year for four years

Stipend: €18,500 per annum

Fees, up to a maximum of €5,750 per annum

Research costs: €2,000 per annum


Further information
For any informal queries, please contact Dr Owen Naughton on email
For queries relating to the application and admission process, please contact the Postgraduate Admissions Office or telephone +353 (0)51 302883.
For queries relating to the funding programme, please email
University Website
Application procedure
Download the Research Postgraduate Application Form and return the completed application to quoting advert reference code CW_2023_17_WSCH_3 from the above table in the email subject line.
Please note that paper submissions will not be accepted.
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