Staff profile

I began my university studies with bachelors degrees in both physics (Université de Sherbrooke, Sherbrooke, Canada) and engineering (Université Laval, Québec, Canada). These degrees gave me the technical skills and the mathematical background that have done much to shape my contributions to physical geography. I eventually came to fluvial geomorphology through the study of turbulence and sediment transport during my master’s degree (INRS-ETE, Québec, Canada). The study of a complex problem such as turbulence prompted an interest in complex phenomena in rivers and thus I undertook a Ph.D. (INRS-ETE, Québec, Canada) on the intergranular voidspaces that constitute the habitat of juvenile atlantic salmon. In addition to gaining an understanding of salmonid habitat, the requirements of my Ph.D. brought me to develop an expertise in the field of remote sensing applied to fluvial environments. Namely, during a Ph.D. internship as a visiting scholar in Fitzwilliam College, Cambridge, I developed skills in digital photogrammetry which were completed with a second internship at the School of geography of the University of Leeds. My post-doctoral work, carried out jointly at the INRS-ETE in Quebec, the School of Geography at the University of Leeds and the department of geography of Durham university, built on my knowledge of remote sensing and salmonid habitat to develop pioneering methods for the catchment-scale characterization of salmonid habitat with high resolution airborne remote sensing methods.

This interest in high resolution imagery has led me to research topographic mapping from Unmanned Aerial Vehicles (UAV or drones) and since 2008 I have conducted sucessfull UAV field campaigns in the UK, the Swiss Alps, the Atacama Desert and Svalbard. Further, recent work has built upon knowledge of fluvial remote sensing, drone imagery and ecology and moved to a larger scale problem: the health and condition of the Ganges. My objectve over the next decade is to make a data-driven contribution to restoration and rehabilitation efforts in this, the most heavily populated river basin on Earth.

• Digital Photogrammetry
• Digital Image Processing
• Fluvial Remote Sensing
• Fluvial Geomorphology and Ecology
• UAV/drone topography generation and mapping

• Catchments and Rivers

• 2012: Sustainable management of the Ganga river basin through scientific innovation(£20060.25 from UKIERI)
• 2008: KTP - APEM LTD(£124346.00 from APEM Ltd)

Chapter in book

• Carbonneau, P.E. & Piégay, H. (Forthcoming). The Growing Use of Imagery in Fundamental and Applied River Sciences. In Fluvial Remote Sensing for River Science and Management. In Fluvial Remote Sensing for River Science and Management. Carbonneau, P.E. & Piégay, H. Wiley.
• Bergeron, N.E. & Carbonneau, P.E. (Forthcoming). Geosalar: Innovative Remote Sensing Methods for Spatially Continuous Mapping of Fluvial Habitat at Riverscape Scale. In Fluvial Remote Sensing for River Science and Management. Carbonneau, P.E. & Piégay, H. Wiley.
• Carbonneau, P.E., Piégay, H., Lejôt, J., Dunford, R. & Michel, K. (Forthcoming). Hyperspatial Imagery in Riverine Environments. In Fluvial Remote Sensing for River Science and Management. Carbonneau, P.E. & Piégay, H. Wiley.
• Carbonneau, P.E. & Piégay, H. (Forthcoming). Future Prospects and challenges for River Scientists and Managers. In Fluvial Remote Sensing for River Science and Management. Carbonneau, P.E. & Piégay, H. Wiley.

Edited book

• Carbonneau, P.E. & Piégay, H. (Forthcoming). Fluvial Remote Sensing for River Science and Management. Wiley.

Journal Article

• Marchetti, Giulia, Bizzi, Simone, Belletti, Barbara, Lastoria, Barbara, Comiti, Francesco & Carbonneau, Patrice Enrique (2022). Mapping riverbed sediment size from Sentinel‐2 satellite data. Earth Surface Processes and Landforms 47(10): 2544-2559.
• Marochov, M., Stokes, C.R. & Carbonneau, P.E. (2021). Image classification of marine-terminating outlet glaciers in Greenland using deep learning methods. The Cryosphere 15: 5041-5059.
• Carbonneau, P.E., Dugdale, S.J., Breckon, T.P., Dietrich, J.T., Fonstad, M.A., Miyamoto, H. & Woodget, A.S. (2020). Adopting deep learning methods for airborne RGB fluvial scene classification. Remote Sensing of Environment 251: 112107.
• Carbonneau, P.E., Belletti, B., Micotti, M., Lastoria, B., Casaioli, M., Mariani, S., Marchetti, G. & Bizzi, S. (2020). UAV-based training for fully fuzzy classification of Sentinel-2 fluvial scenes. Earth Surface Processes and Landforms 45(13): 3120-3140.
• Piégay, H., Arnaud, F., Belletti, B., Bertrand, M., Bizzi, S., Carbonneau, P., Dufour, S., Liebault, F., Ruiz‐Villanueva, V. & Slater, L. (2020). Remotely Sensed Rivers in the Anthropocene: State of the Art and Prospects. Earth Surface Processes and Landforms 45(1): 157-188.
• Kissick, Lucy E. & Carbonneau, Patrice E. (2019). The Case Against Vast Glaciation in Valles Marineris, Mars. Icarus 321: 803-823.
• Carbonneau, P., Bizzi, S. & Marchetti, G. (2018). Robotic photosieving from low-cost multirotor sUAS: A proof-of-concept. Earth Surface Processes and Landforms 43(5): 1160-1166.
• Woodget, A.S., Fyffe, C. & Carbonneau, P.E. (2018). From manned to unmanned aircraft: Adapting airborne particle size mapping methodologies to the characteristics of sUAS and SfM. Earth Surface Processes and Landforms 43(4): 857-870.
• Milledge, D.G., Gurjar, S.K., Bunce, J.T., Tare, V., Sinha, R. & Carbonneau, P.E. (2018). Population density controls on microbial pollution across the Ganga catchment. Water Research 128: 82-91.
• Carbonneau, P. & Dietrich, J.T. (2017). Cost-effective non-metric photogrammetry from consumer-grade sUAS: implications for direct georeferencing of structure from motion photogrammetry. Earth Surface Processes and Landforms 42(3): 473-486.
• Woodget, A.S., Visser, F., Maddock, I.P. & Carbonneau, P.E. (2016). The accuracy and reliability of traditional surface flow type mapping: is it time for a new method of characterizing physical river habitat? River Research and Applications 32(9): 1902-1914.
• Oliver, D.M., Porter, K.D.H., Pachepsky, Y.A., Muirhead, R.W., Reaney, S.M., Coffey, R., Kay, D., Milledge, D.M., Hong, E., Anthony, S.G., Page, T., Bloodworth, J.W., Mellander, P-E., Carbonneau, P., McGrane, S.J. & Quilliam, R.S. (2016). Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments. Science of The Total Environment 544: 39-47.
• de Haas, T., Kleinhans, M.G., Carbonneau, P., Rubensdotter, L. & Hauber, E. (2015). Surface morphology of fans in the high-Arctic periglacial environment of Svalbard: Controls and processes. Earth Science Reviews 146: 163-182.
• Woodget, A.S., Carbonneau, P.E., Visser, F. & Maddock, I.P. (2015). Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry. Earth Surface Processes and Landforms 40(1): 47-64.
• Sanyal, J., Carbonneau, P. & Densmore, A.L. (2014). Low-cost inundation modelling at the reach scale with sparse data in the Lower Damodar River basin, India. Hydrological Sciences Journal 59(12): 2086-2102.
• de Haas, T., Ventra, D., Carbonneau, P.E. & Kleinhans, M.G. (2014). Debris-flow dominance of alluvial fans masked by runoff reworking and weathering. Geomorphology 217: 165-181.
• Black, M., Carbonneau, P., Church, M. & Warburton, J. (2014). Mapping sub-pixel fluvial grain sizes with hyperspatial imagery. Sedimentology 61(3): 691-711.
• Sanyal, J., Densmore, A.L. & Carbonneau, P. (2014). 2D finite element inundation modelling in anabranching channels with sparse data: examination of uncertainties. Water Resources Management 28(8): 2351-2366.
• Sanyal, J., Densmore, A.L. & Carbonneau, P. (2014). Analysing the effect of land use/cover changes at sub-catchment levels on downstream flood peaks: a semi-distributed modelling approach with sparse data. Catena 118: 28-40.
• Hauber, E., Platz, Thomas, Reiss, Dennis, Le Deit, Laetitia, Kleinhans, M.G., Marra, W.A., De Haas, T. & Carbonneau, P. (2013). Asynchronous formation of Hesperian and Amazonian-aged deltas on Mars and implications for climate. Journal of Geophysical Research: Planets 118(7): 1529-1544.
• Fonstad, M.A., Dietrich, J.T., Courville, B.C., Jensen, J.L. & Carbonneau, P.E. (2013). Topographic structure from motion: a new development in photogrammetric measurement. Earth Surface Processes and Landforms 38(4): 421-430.
• Sanyal, J., Carbonneau, P. & Densmore, A.L. (2013). Hydraulic routing of extreme floods in a large ungauged river and the estimation of associated uncertainties: a case study of the Damodar River, India. Natural Hazards 66(2): 1153-1177.
• Carbonneau, P.E., Fonstad, M.A., Marcus, W.A. & Dugdale, S.J. (2012). Making riverscapes real. Geomorphology 137(1): 74-86.
• Dugdale, S.J., Carbonneau, P.E. & Campbell, D. (2010). Aerial photosieving of exposed gravel bars for the rapid calibration of airborne grain size maps. Earth Surface Processes and Landforms 35(6): 627-639.
• Hardy, R.J., Best, J.L., Lane, S.N. & Carbonneau, P. (2010). Coherent flow structures in a depth-limited flow over a gravel surface: The influence of surface roughness. Journal of Geophysical Research: Earth Surface 115(F3): F03006.
• Carbonneau, P.E., Dugdale, S.J. & Clough, S. (2009). An Automated Georeferencing Tool for Watershed Scale Fluvial Remote Sensing. River Research and Applications 26(5): 650-658.
• Hardy, R.J., Best, J.L., Lane, S.N. & Carbonneau, P.E. (2009). Coherent flow structures in a depth-limited flow over a gravel surface the role of near-bed turbulance and influence of Reynolds number. Journal of Geophysical Research – Earth Surface 114: F01003.
• James, T.D., Carbonneau, P.E. & Lane, S.N. (2007). Investigating the effects of DEM error in scaling analysis. Photogrammetric Engineering and Remote Sensing 73: 67-78.
• Carbonneau, P.E., Lane, S.N. & Bergeron, N.E. (2006). Feature based image processing methods applied to bathymetric measurements from airborne remote sensing in fluvial environments. Earth Surface Processes and Landforms 31(11): 1413-1423.
• Carbonneau, P., Bergeron, N.E. & Lane, S.N. (2005). Texture-based image segmentation applied to the quantification of superficial sand in salmonid river gravels. Earth Surface Processes and Landforms 30(1): 121-127.
• Carbonneau, P.E. (2005). The threshold effect of image resolution on image-based automated grain size mapping in fluvial environments. Earth Surface, Processes and Landforms 30: 1687-1693.
• Carbonneau, P.E., Bergeron, N.E. & Lane, S.N. (2005). Automated grain size measurements from airborne remote sensing for long profile measurements of fluvial grain sizes. Water Resources Research 41(11): W11426.
• Carbonneau, P.E., Lane, S.N. & Bergeron, N.E. (2004). Catchment-scale mapping of surface grain size in gravel bed rivers using airborne digital imagery. Water Resources Research 40(7): W07202.
• Carbonneau, P.E., Lane, S.N. & Bergeron, N.E. (2003). Cost-effective non-metric close-range digital photogrammetry and its application to a study of coarse gravel river beds. International Journal of Remote Sensing 24(14): 2837 – 2854.
• Carbonneau, P.E. & Bergeron, N.E. (2000). The effect of bedload transport on mean and turbulent flow properties. Geomorphology 35(3-4): 267-278.