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

Chapter in book

• Carbonneau, P., & Piégay, H. (2012). The Growing Use of Imagery in Fundamental and Applied River Sciences. In P. Carbonneau, & H. Piégay (Eds.), Fluvial Remote Sensing for Science and Management (1-18). Wiley. https://doi.org/10.1002/9781119940791
• Carbonneau, P., & Piégay, H. (2012). Future Prospects and challenges for River Scientists and Managers. In P. Carbonneau, & H. Piégay (Eds.), Fluvial Remote Sensing for Science and Management (431-434). Wiley. https://doi.org/10.1002/9781119940791
• Bergeron, N., & Carbonneau, P. (2012). Geosalar: Innovative Remote Sensing Methods for Spatially Continuous Mapping of Fluvial Habitat at Riverscape Scale. In P. Carbonneau, & H. Piégay (Eds.), Fluvial Remote Sensing for River Science and Management (193-213). Wiley
• Carbonneau, P., Piégay, H., Lejôt, J., Dunford, R., & Michel, K. (2012). Hyperspatial Imagery in Riverine Environments. In P. Carbonneau, & H. Piégay (Eds.), Fluvial Remote Sensing for River Science and Management (163-191). Wiley

Conference Paper

• Maciel-Pearson, B., Carbonneau, P., & Breckon, T. (2018, July). Extending Deep Neural Network Trail Navigation for Unmanned Aerial Vehicle Operation within the Forest Canopy. Presented at 19th Towards Autonomous Robotic Systems (TAROS) Conference., Bristol, England

Edited book

• Carbonneau, P., & Piégay, H. (Eds.). (2012). Fluvial Remote Sensing for Science and Management. Wiley

Journal Article

• Vanzani, F., Carbonneau, P., & Fontana, A. (2025). Automated Mapping of Braided Palaeochannels From Optical Images With Deep Learning Methods. Journal of Geophysical Research: Earth Surface, 130(2), Article e2024JF008051. https://doi.org/10.1029/2024jf008051
• Carbonneau, P. E. (2024). Global Semantic Classification of Fluvial Landscapes with Attention-Based Deep Learning. Remote Sensing, 16(24), Article 4747. https://doi.org/10.3390/rs16244747
• Valman, S. J., Boyd, D. S., Carbonneau, P. E., Johnson, M. F., & Dugdale, S. J. (2024). An AI approach to operationalise global daily PlanetScope satellite imagery for river water masking. Remote Sensing of Environment, 301, Article 113932. https://doi.org/10.1016/j.rse.2023.113932
• Carbonneau, P. E., & Bizzi, S. (2024). Global mapping of river sediment bars. Earth Surface Processes and Landforms, 49(1), 15-23. https://doi.org/10.1002/esp.5739
• Bozzolan, E., Brenna, A., Surian, N., Carbonneau, P., & Bizzi, S. (2023). Quantifying the Impact of Spatiotemporal Resolution on the Interpretation of Fluvial Geomorphic Feature Dynamics From Sentinel 2 Imagery: An Application on a Braided River Reach in Northern Italy. Water Resources Research, 59(12), Article e2023WR034699. https://doi.org/10.1029/2023wr034699
• Marchetti, G., Bizzi, S., Belletti, B., Lastoria, B., Comiti, F., & Carbonneau, P. E. (2022). Mapping riverbed sediment size from Sentinel‐2 satellite data. Earth Surface Processes and Landforms, 47(10), 2544-2559. https://doi.org/10.1002/esp.5394
• Marochov, M., Stokes, C., & Carbonneau, P. (2021). Image classification of marine-terminating outlet glaciers in Greenland using deep learning methods. The Cryosphere, 15, 5041-5059. https://doi.org/10.5194/tc-15-5041-2021
• Carbonneau, P., Dugdale, S., Breckon, T., Dietrich, J., Fonstad, M., Miyamoto, H., & Woodget, A. (2020). Adopting deep learning methods for airborne RGB fluvial scene classification. Remote Sensing of Environment, 251, Article 112107. https://doi.org/10.1016/j.rse.2020.112107
• Carbonneau, P., 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. https://doi.org/10.1002/esp.4955
• 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. https://doi.org/10.1002/esp.4787
• Kissick, L. E., & Carbonneau, P. E. (2019). The Case Against Vast Glaciation in Valles Marineris, Mars. Icarus, 321, 803-823. https://doi.org/10.1016/j.icarus.2018.12.021
• 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. https://doi.org/10.1002/esp.4298
• Woodget, A., Fyffe, C., & Carbonneau, P. (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. https://doi.org/10.1002/esp.4285
• Milledge, D., Gurjar, S., Bunce, J., Tare, V., Sinha, R., & Carbonneau, P. (2018). Population density controls on microbial pollution across the Ganga catchment. Water Research, 128, 82-91. https://doi.org/10.1016/j.watres.2017.10.033
• Carbonneau, P., & Dietrich, J. (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. https://doi.org/10.1002/esp.4012
• Woodget, A., Visser, F., Maddock, I., & Carbonneau, P. (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. https://doi.org/10.1002/rra.3047
• Oliver, D., Porter, K., Pachepsky, Y., Muirhead, R., Reaney, S., Coffey, R., Kay, D., Milledge, D., Hong, E., Anthony, S., Page, T., Bloodworth, J., Mellander, P.-E., Carbonneau, P., McGrane, S., & Quilliam, R. (2016). Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments. Science of the Total Environment, 544, 39-47. https://doi.org/10.1016/j.scitotenv.2015.11.086
• de Haas, T., Kleinhans, M., 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. https://doi.org/10.1016/j.earscirev.2015.04.004
• Sanyal, J., Carbonneau, P., & Densmore, A. (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. https://doi.org/10.1080/02626667.2014.884718
• Woodget, A., Carbonneau, P., Visser, F., & Maddock, I. (2014). Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry. Earth Surface Processes and Landforms, 40(1), 47-64. https://doi.org/10.1002/esp.3613
• de Haas, T., Ventra, D., Carbonneau, P., & Kleinhans, M. (2014). Debris-flow dominance of alluvial fans masked by runoff reworking and weathering. Geomorphology, 217, 165-181. https://doi.org/10.1016/j.geomorph.2014.04.028
• Sanyal, J., Densmore, A., & 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. https://doi.org/10.1016/j.catena.2014.01.015
• Sanyal, J., Densmore, A., & Carbonneau, P. (2014). 2D finite element inundation modelling in anabranching channels with sparse data: examination of uncertainties. Water Resources Management, 28(8), 2351-2366. https://doi.org/10.1007/s11269-014-0619-x
• Black, M., Carbonneau, P., Church, M., & Warburton, J. (2014). Mapping sub-pixel fluvial grain sizes with hyperspatial imagery. Sedimentology, 61(3), 691-711. https://doi.org/10.1111/sed.12072
• Hauber, E., Platz, T., Reiss, D., Le Deit, L., Kleinhans, M., Marra, W., 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. https://doi.org/10.1002/jgre.20107
• Sanyal, J., Carbonneau, P., & Densmore, A. (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. https://doi.org/10.1007/s11069-012-0540-7
• Fonstad, M., Dietrich, J., Courville, B., Jensen, J., & Carbonneau, P. (2013). Topographic structure from motion: a new development in photogrammetric measurement. Earth Surface Processes and Landforms, 38(4), 421-430. https://doi.org/10.1002/esp.3366
• Carbonneau, P., Fonstad, M., Marcus, W., & Dugdale, S. (2012). Making riverscapes real. Geomorphology, 137(1), 74-86. https://doi.org/10.1016/j.geomorph.2010.09.030
• Hardy, R., Best, J., Lane, S., & 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), Article F03006. https://doi.org/10.1029/2009jf001416
• Dugdale, S., Carbonneau, P., & 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. https://doi.org/10.1002/esp.1936
• Hardy, R., Best, J., Lane, S., & Carbonneau, P. (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, 114, Article F01003. https://doi.org/10.1029/2007jf000970
• Carbonneau, P., Dugdale, S., & Clough, S. (2009). An Automated Georeferencing Tool for Watershed Scale Fluvial Remote Sensing. River Research and Applications, 26(5), 650-658. https://doi.org/10.1002/rra.1263
• James, T., Carbonneau, P., & Lane, S. (2007). Investigating the effects of DEM error in scaling analysis. Photogrammetric engineering and remote sensing, 73(1), 67-78. https://doi.org/10.14358/pers.73.1.67
• Carbonneau, P., Lane, S., & Bergeron, N. (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. https://doi.org/10.1002/esp.1341
• Carbonneau, P., Bergeron, N., & Lane, S. (2005). Automated grain size measurements from airborne remote sensing for long profile measurements of fluvial grain sizes. Water Resources Research, 41(11), Article W11426. https://doi.org/10.1029/2005wr003994
• Carbonneau, P. (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. https://doi.org/10.1002/esp.1288
• Carbonneau, P., Bergeron, N., & Lane, S. (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. https://doi.org/10.1002/esp.1140
• Carbonneau, P., Lane, S., & Bergeron, N. (2004). Catchment-scale mapping of surface grain size in gravel bed rivers using airborne digital imagery. Water Resources Research, 40(7), Article W07202. https://doi.org/10.1029/2003wr002759
• Carbonneau, P., Lane, S., & Bergeron, N. (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. https://doi.org/10.1080/01431160110108364
• Carbonneau, P., & Bergeron, N. (2000). The effect of bedload transport on mean and turbulent flow properties. Geomorphology, 35(3-4), 267-278