Research

L. Gilet, W. Habib, E. Aitova, K.A. Byrne, C.A. Farrell, O. Fenton, R. Flynn, D. O'Leary, T.R. Morley, P. Tuohy, S. Regan, F. Renou-Wilson,  D. Wilson, J. Connolly. Peatland use and peat soil land cover types in Ireland: Implications for the calculation of GHG emissions in the context of climate action. Land Use Policy, Volume 159, 2025. Article Link  

H. Pierce, O. Fenton, E. Daly, A. Shnel, D O'Leary, M. G. Healy, P. Tuohy. Assessing localised rainfall and water table depth relationships in agricultural grassland peat soils. Science of The Total Environment, Volume 994, 2025. Article Link 

(Preprint): D O'Leary, P. Tuohy, O. Fenton, M. G. Healy, H. Pierce, A. Shnel, E. Daly. Assessing the impact of rewetting agricultural fen peat soil via open drain damming: an agrogeophysical approach. SOIL Special Issue: Agrogeophysics: illuminating soil's hidden dimensions. Article Link

S. Dogar, C. Brogi, D O'Leary, I. Hernández-Ochoa, M.Donat, H.Vereecken, J.A. Huisman. Combining electromagnetic induction and remote sensing data for improved determination of management zones for sustainable crop production. SOIL Special Issue: Agrogeophysics: illuminating soil's hidden dimensions. Article Link

D. O'Leary, C. Brown, J. Hodgson, J. Connolly, L. Gilet, P. Tuohy, O. Fenton, E. Daly, Airborne radiometric data for digital soil mapping of peat at broad and local scales, Geoderma, Volume 453, 2025. Article Link

A. Romero-Ruiz, D. O'Leary, E. Daly, P. Tuohy, A. Milne, K. Coleman, A. Whitmore. An agrogeophysical modelling framework for the detection of soil compaction spatial variability due to grazing using field-scale electromagnetic induction data. Soil Use and Management. 2024. Article Link

D. O'Leary, C. Brogi, C. Brown, P. Tuohy, E. Daly, Linking electromagnetic induction data to soil properties at field scales aided by neural network clustering, Frontiers in Soil Science, Volume 4 Special Issue: Digital soil mapping using electromagnetic sensors, 2024. Article Link

D. O'Leary, C. Brown, M. G. Healy, S. Regan, E. Daly, Observations of intra-peatland variability using multiple spatially coincident remotely sensed data sources and machine learning, Geoderma, Volume 430, 2023. Article Link.

M.G. Healy, A. Siggins, K. Molloy, A.P. Potito, D. O'Leary, E. Daly, O. Callery, The impact of alternating drainage and inundation cycles on geochemistry and microbiology of intact peat cores, Science of The Total Environment, Volume 858, Part 1, 2023, Article Link.

D. O'Leary, C. Brown, E. Daly, Digital soil mapping of peatland using airborne radiometric data and supervised machine learning – Implication for the assessment of carbon stock, Geoderma, Volume 428, 2022. Article Link.

S. Monteverde, M.G. Healy, D. O'Leary, E. Daly, O. Callery, Management and rehabilitation of peatlands: The role of water chemistry, hydrology, policy, and emerging monitoring methods to ensure informed decision making, Ecological Informatics, Volume 69, 2022,. Article Link.

D. O’Leary. Mapping peat using radiometrics. Nat Rev Earth Environ 2, 523 (2021). Article Link.

M.J. Dolan, B.A. McCabe, K. Molloy, J. Murray, T. Henry, E. Daly, D. O'Leary. A Pleistocene deposit preserved in deep karst at Coolough, County Galway, western Ireland. Geological Journal. 2021. Article Link.

2025 -  Present: Project Title: GRADE. Project Organisations: EPA, SETU, UCD and University of Galway. Project site.

2023 - 2025: Project Title: ReWET. Project Organisations: Teagasc and University of Galway. Position: PostDoctoral Researcher. Project Site.

2018 - 2022: Project Title: Water_PEAT. Project Organisations: University of Galway and EPA. Position: Project Collaborator. Project Site.

EGU2025 - Electromagnetic Induction as a means to assess the hydrological impact of rewetting agricultural fen peat sites. Link to Abstract. 

IGC24 -Identifying the Transition Zone between Peat and Mineral Soils Using Airborne Radiometric Data. Link to Abstract. 

AgroGeo24 - Linking electromagnetic induction data to soil properties at field scales aided by neural network clustering. Link to Abstract.

EGU2023 - Using environmental radioactivity to create a national scale peatlands map: a case study from Ireland. Link to Abstract.

Soil Mapping for a Sustainable Future 2023 - Regional Mapping of Peatland Boundaries using Airborne Radiometric Data and Supervised Machine Learning. Link to Event.

AGU2022 - Data Driven Method for Selection of Optimum Number of Clusters in Earth Science Data using Centroid based Self-Organising Maps Clustering. Link to Abstract.

EGU2022 - Digital Soil Mapping of Peatlands using Airborne Radiometric Data and Supervised Machine Learning. Link to Abstract.

AgriGeo2022 - Large Scale EMI Survey linking Electrical Conductivity to Soil Type Properties using Machine Learning Classification Methods. Link to Abstract.

EGU2021 - Method to obtain optimum number of clusters in geo-spatial data using stability analysis of cluster centres. Link to Abstract.

IGRM 2024 - Identifying the Transition Zone between Peat and Non-Peat Soils Using Airborne Radiometric Data. Link to Conference page.

IQUA 2023 Autumn Symposium -  Identifying the Transition Zone between Peat and Non-Peat Soils Using Airborne Radiometric Data.

ENVIRON23 - Using Tellus Airborne Radiometric data to update the national peatland map in Ireland - Link to Conference Brouchure

IGRM2023 - Using Tellus Airborne Radiometric data to update the national peatland map in Ireland.

IQUA 2023 Spring Symposium - Using Tellus Airborne Radiometric data to update the national peatland map in Ireland. Link to Abstract.

IQUA 2022 - Digital Soil Mapping of Peatlands using Airborne Radiometric Data and Supervised Machine Learning. Link to Abstract.

IGA 2021 - Mapping Peatland Boundaries and Intra-Peat variation using Radiometric Data and Machine Learning. Link to Presentation.

IAH 2021 - Mapping Peatland Boundaries and Intra-Peat variation using Radiometric Data and Machine Learning

IGRM 2021 - The potential of Self-Organising maps clustering to characterise a harvested peatland using airborne radiometric data and a digital elevation model.

IQUA 2020 - Defining peatland zones using self-organising map clustering on airborne radiometric data and OS digital elevation model. Link to Abstract.

IGRM 2020 - Potential of machine learning in linking national airborne radiometric data to soil class mapping.