Mangilli, A., C. Duguay, J. Murfitt, T. Moreau, S. Amraoui, J.S. Mugunthan, P. Thibaut, and C. Donlon, 2024. Improving the estimation of lake ice thickness with high resolution radar altimetry data. Remote Sensing, 16(14), 2510,  https://doi.org/10.3390/rs16142510.

Murfitt, J., C.R. Duguay, G. Picard, and J. Lemmetyinen, 2024. Forward modelling of SAR backscatter during lake ice melt conditions using the Snow Microwave Radiative Transfer (SMRT) model. The Cryosphere, 18: 869-888, https://doi.org/10.5194/tc-18-869-2024.

Ghiasi, Y., C.R. Duguay, J. Murfitt, M. Asgarimehr, and Y. Wu, 2023. Potential of GNSS-R for the monitoring of lake ice phenology. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17: 660 – 673, doi: 10.1109/JSTARS.2023.3330745.

Mugunthan, J.S., C.R. Duguay, and E. Zakharova, 2023. Machine learning based classification of lake ice and open water from Sentinel-3 SAR altimetry waveforms. Remote Sensing of Environment, 299, 113891, https://doi.org/10.1016/j.rse.2023.113891.

Chegoonian, A.M., N. Pahlevan, K. Zolfaghari, P.R. Leavitt, J.-M. Davies, H.M. Baulch, and C.R. Duguay, 2023. Comparative analysis of empirical and machine learning models for Chla extraction using Sentinel-2 and Landsat OLI data: Opportunities, limitations and challenges. Canadian Journal of Remote Sensing, 49:1, doi: 10.1080/07038992.2023.2215333.

Nandan, V., Willatt, R., Mallett, R., Stroeve, J., Geldsetzer, T., Scharien, R., Tonboe, R., Yackel, J., Landy, J., Clemens-Sewall, D., Jutila, A., Wagner, D. N., Krampe, D., Huntemann, M., Mahmud, M., Jensen, D., Newman, T., Hendricks, S., Spreen, G., Macfarlane, A., Schneebeli, M., Mead, J., Ricker, R., Gallagher, M., Duguay, C., Raphael, I., Polashenski, C., Tsamados, M., Matero, I., and Hoppmann, M., 2023. Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice. The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023.

Shaposhnikova, M., C.R. Duguay, and P. Roy-Léveillée, 2023. Bedfast and floating ice dynamics of thermokarst lakes using a temporal deep learning mapping approach: Case study of the Old Crow Flats, Yukon, Canada. The Cryosphere, 17, 1697-1721, https://doi.org/10.5194/tc-17-1697-2023. 

Carrea, L., J.-F. Crétaux, X. Liu, Y. Wu, M. Berge-Nguyen, B. Calmettes, C.R. Duguay, C.J. Merchant, N. Selmes, S.G. H. Simis, M. Warren, H. Yesou, D. Müller, D. Jiang, and C. Albergel, 2023. Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies. Scientific Data, 10: 30, https://doi.org/10.1038/s41597-022-01889-z.

Murfitt, J., C. Duguay, G. Picard, and G. Gunn, 2023. Forward modelling of synthetic aperture radar backscatter from lake ice over Canadian subarctic lakes. Remote Sensing of Environment, 286, 113424, 1-18,  https://doi.org/10.1016/j.rse.2022.113424.

Zolfaghari, K., N. Pahlevan, S.G.H. Simis, R.E. O'Shea, and C.R. Duguay, 2022. Sensitivity of remotely sensed pigment concentration via mixture density networks (MDNs) to uncertainties from atmospheric correction. Journal of Great Lakes Research, https://doi.org/10.1016/j.jglr.2022.12.010.

Brown, L.C. and C.R. Duguay, 2022. Lake Ice. Arctic Report Card 2022, M. L. Druckenmiller, R. L. Thoman, and T. A. Moon, Eds., https://doi.org/10.25923/1v84-vt30, https://arctic.noaa.gov/Report-Card/Report-Card-2022/ArtMID/8054/ArticleID/1002/Lake-Ice. 

Murfitt, J., C. Duguay, G. Picard, and G. Gunn, 2022. Investigating the effect of lake ice properties on multifrequency backscatter using the Snow Microwave Radiative Transfer (SMRT) model. IEEE Transactions on Geoscience and Remote Sensing, 60: 1-23, https://doi.org/10.1109/TGRS.2022.3197109.

Mangilli, A., P. Thibaut, C.R. Duguay, and J. Murfitt, 2022. A new approach for the estimation of lake ice thickness from conventional radar altimetry. IEEE Transactions on Geoscience and Remote Sensing, 60: 1-15, https://doi.org/10.1109/TGRS.2022.3186253.

Cai, Y., C.R. Duguay, and C.-Q. Ke, 2022. A 41-year (1979-2019) passive microwave derived lake ice phenology data record of the Northern Hemisphere. Earth System Science Data, 14: 3329-3347, https://doi.org/10.5194/essd-14-3329-2022.

Chegoonian, A.M., K. Zolfaghari, P.R. Leavitt, H.M. Baulch, and C.R. Duguay, 2022. Improvement of field fluorometry estimates of chlorophyll-a concentration in a cyanobacteria-rich eutrophic lake. Limnology and Oceanography: Methods, 1-17, https://doi.org/10.1002/lom3.10480.

Saberi, N., K.A. Scott, and C.R. Duguay, 2022. Incorporating aleatoric uncertainties in lake ice mapping in SAR imagery using CNNs. Remote Sensing, 14(3), 644; https://doi.org/10.3390/rs14030644.

Zolfaghari, K., N. Pahlevan, C. Binding, D. Gurlin, S.G.H. Simis, A. Ruiz Verdú, L. Li, C.J. Crawford, A. VanderWoude, R. Errera, A. Zastepa, and C.R. Duguay, 2022. Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment. IEEE Transactions on Geoscience and Remote Sensing, 60: 1-20, https://doi.org/10.1109/TGRS.2021.3114635.

Ma, Z., Z. Liu, J. Pu, L. Xu, K. Li, L. Wangqu, R. Wu, Y. Ma, Y. Chen, and C. Duguay, 2021. Deep convolutional neural network with random field model for lake ice mapping from Sentinel-1 imagery. International Journal of Remote Sensing, 42(24): 9343-9367, doi: 10.1080/01431161.2021.1995074.

Murfitt, J. and C.R. Duguay, 2021. 50 years of lake ice research from active microwave remote sensing: Progress and prospects. Remote Sensing of Environment, 264, 112616, https://doi.org/10.1016/j.rse.2021.112616.

Chegoonian, A.M., K. Zolfaghari, H.M. Baulch, and C.R. Duguay, 2021. Support vector regression for chlorophyll-a estimation using Sentinel-2 images in small waterbodies. Proceedings of 2021 IEEE International Geoscience & Remote Sensing Symposium, Brussels, Belgium, 11-16 July, pp. 7449-7452, doi: 10.1109/IGARSS47720.2021.9554110.

Ghiasi, Y., S. Farzaneh, K. Parvazi, and C.R. Duguay, 2021. Amplitude estimation of dominant tidal constituents using GNSS interferometric reflectometry technique. Proceedings of 2021 IEEE International Geoscience & Remote Sensing Symposium, Brussels, Belgium, 11-16 July, pp. 8546-8549, doi: 10.1109/IGARSS47720.2021.9554876.

Zakharova, E., S. Agafonova, C. Duguay, N. Frolova, and A. Kouraev, 2021. River ice phenology and thickness from satellite altimetry. Potential for climate studies and ice bridge road operation. The Cryosphere, 15, 5387–5407, https://doi.org/10.5194/tc-15-5387-2021.

Wu, Y., C.R. Duguay, and L. Xu, 2021. Assessment of machine learning classifiers for global lake ice cover mapping from MODIS TOA reflectance data. Remote Sensing of Environment, 253, 112206, https://doi.org/10.1016/j.rse.2020.112206.​

​Nitze, I., S. Cooley, C. Duguay, B.M. Jones, and G. Grosse, 2020. The catastrophic thermokarst lake drainage events of 2018 in northwestern Alaska: Fast-forward into the future. The Cryosphere, 14, 4279-4297, https://doi.org/10.5194/tc-14-4279-2020.

​Ghiasi, Y., C.R. Duguay, J. Murfitt, A. Thompson, J. van der Sanden, H. Drouin, and C. Prévost, 2020. Application of GNSS interferometric reflectometry for the estimation of lake ice thickness. Remote Sensing, 12, 2721; doi:10.3390/rs12172721. 

Glass, B.K., D.L., Rudolph, C.R. Duguay, and A. Wicke, 2020. Identifying groundwater discharge zones in Northern Canada using remotely sensed optical and thermal imagery. Canadian Journal of Earth Sciences, doi: 10.1139/cjes-2019-0169, https://doi.org/10.1139/cjes-2019-0169.

Bergstedt, H., A. Bartsch, C. Duguay, and B.M. Jones, 2020. Influence of surface water on coarse resolution C-band backscatter: Implications for freeze/thaw retrieval from scatterometer data. Remote Sensing of Environment, 247, 15 September 2020, 111911, https://doi.org/10.1016/j.rse.2020.111911.

Hoekstra, M., M. Jiang, D. Clausi, and C. Duguay, 2020. Lake ice-water classification of RADARSAT-2 images by integrating IRGS segmentation with pixel-based random forest labeling. Remote Sensing, 12, 1425; doi:10.3390/rs12091425, https://www.mdpi.com/2072-4292/12/9/1425.

Murfitt, J. and C.R. Duguay, 2020. Assessing the performance of methods for monitoring ice phenology of the world’s largest high arctic lake using high density time series analysis of Sentinel-1 data. Remote Sensing, 12, 382; doi:10.3390/rs12030382, https://www.mdpi.com/2072-4292/12/3/382.

Baijnath-Rodino, J.A. and C.R. Duguay, 2019. Assessment of coupled CRCM5-FLake on the reproduction of wintertime lake-induced precipitation in the Great Lakes Basin. Theoretical and Applied Climatology, https://doi.org/10.1007/s00704-019-02799-8.

Derksen, C., D. Burgess, C. Duguay, S. Howell, L. Mudryk, S. Smith, C. Thackeray, and M. Kirchmeier-Young, 2019. Changes in snow, ice, and permafrost across Canada; Chapter 5 in Canada’s Changing Climate Report, (ed.) E. Bush and D.S. Lemmen; Government of Canada, Ottawa, Ontario, p. 194-260.

Du, J., J.D. Watts, L. Jiang, H. Lu, X. Cheng, C. Duguay, M. Farina, Y. Qiu, Y. Kim, J.S. Kimball, and P. Tarolli, 2019. Remote sensing of environmental changes in cold regions: methods, achievements and challenges. Remote Sensing, 11, 1952; doi:10.3390/rs11161952.

Duguay, C.R. and J. Wang, 2019. Advancement in bedfast lake ice mapping from Sentinel-1 SAR data. Proceedings of 2019 IEEE International Geoscience & Remote Sensing Symposium, Yokohama, Japan, 28 July-2 August, pp. 6922-6925, doi: https://doi.org/10.1109/IGARSS.2019.8900650.

Foroutan, M., G. Steinmetz, J. Zimbelman, and C. Duguay, 2019. Megaripples at Wau-an-Namus, Libya: A new analog for similar features on Mars. Icarus, 319: 840-851, https://doi.org/10.1016/j.icarus.2018.10.021.

Kang, K.-K., M. Hoekstra, M. Foroutan, A.M. Chegoonian, K. Zolfaghari, and C.R. Duguay, 2019. Operating procedures and calibration of a hyperspectral sensor onboard a remotely piloted aircraft system for water and agriculture monitoring. Proceedings of 2019 IEEE International Geoscience & Remote Sensing Symposium, Yokohama, Japan, 28 July-2 August, pp. 9200-9203, doi: https://doi.org/10.1109/IGARSS.2019.8900128.

Zolfaghari, K., M. Hoekstra, C. Duguay, D. Rudolph, and I. D'Souza, 2019. Canadian water microsatellite mission - concept design. Proceedings of 2019 IEEE International Geoscience & Remote Sensing Symposium, Yokohama, Japan, 28 July-2 August, pp. 6926-6928, doi: https://doi.org/10.1109/IGARSS.2019.8897898.

Baijnath-Rodino, J.A. and C.R. Duguay, 2018. Historical spatiotemporal trends in snowfall extremes over the Canadian domain of the Great Lakes Basin. Advances in Meteorology, vol. 2018, Article ID 5404123, 20 pages, 2018. https://doi.org/10.1155/2018/5404123.

Baijnath-Rodino, J.A., C.R. Duguay, and E.F. LeDrew, 2018. Climatological trends of snowfall over the Laurentian Great Lakes Basin. International Journal of Climatology, 38: 3942–3962, https://doi.org/10.1002/joc.5546.

Duguay, C. and L. Brown, 2018: Lake Ice [in Arctic Report Card 2018], https://www.arctic.noaa.gov/Report-Card.

Gunn, G., C. Duguay, D. Atwood, J. King, and P. Toose, 2018. Observing scattering mechanisms of bubbled freshwater lake ice using polarimetric RADARSAT-2 (C-band) and UWScat (X-, Ku-band). IEEE Transactions on Geoscience and Remote Sensing, 56(5): 2887-2903, doi: 10.1109/TGRS.2017.2786158.

Wang, J., C.R. Duguay, and D.A. Clausi, V. Pinard, and S.E.L. Howell, 2018. Semi-automated classification of lake ice cover using dual polarization RADARSAT-2 imagery. Remote Sensing, 10(11), 1727; https://doi.org/10.3390/rs10111727.

Du, J., J. S. Kimball, C.R. Duguay, Y. Kim, and J. Watts, 2017. Satellite microwave assessment of Northern Hemisphere lake ice phenology from 2002 to 2015. The Cryosphere, 11: 47–63, doi:10.5194/tc-11-47-2017.

Gunn, G., C. Duguay, C. Derksen, D. Clausi, and P. Toose, 2017. Investigating the influence of variable freshwater ice types on passive and active microwave observations. Remote Sensing, 9, 1242, doi:10.3390/rs9121242.

Kheyrollah Pour, H., C.R. Duguay, A. Scott, and K.-K. Kang, 2017. Improvement of lake ice thickness retrieval from MODIS satellite data using a thermodynamic model. IEEE Transactions on Geoscience and Remote Sensing, 55(10): 5956-5965, doi: 10.1109/TGRS.2017.2718533

Kheyrollah Pour, H., E. Kourzeneva, K. Eerola, L. Rontu, F. Pan, and C.R. Duguay, 2017. Preliminary assessment of lake surface water temperature statistical properties for objective analysis in a NWP model using satellite observations. Tellus Series A: Dynamic Meteorology and Oceanography, 69(1), 1313025, doi:10.1080/16000870.2017.1313025.

Nandan.V., R. Scharien, T. Geldsetzer, M. Mahmud, J. Yackel, T. Islam, J.P.S. Gill, M.C. Fuller, G. Gunn, and C. Duguay, 2017. Geophysical and atmospheric controls on Ku-, X- and C-band backscatter evolution from a saline snow cover on first-year sea ice from late-winter to pre-early melt. Remote Sensing of Environment, 198: 425-441, https://doi.org/10.1016/j.rse.2017.06.029.

Zolfaghari, K., C.R. Duguay, and H. Kheyrollah Pour, 2017. Satellite-derived light extinction coefficient and its impact on thermal structure simulations in a 1-D lake model. Hydrology and Earth System Sciences, 21: 377-391, doi:10.5194/hess-21-377-2017.

Antonova, S., C.R. Duguay, A. Kääb, B. Heim, M. Langer, S. Westermann, and J. Boike, 2016. Monitoring ice phenology and bedfast ice in lakes of the Lena River Delta using TerraSAR-X backscatter and coherence time series. Remote Sensing, 8(11), 903, doi:10.3390/rs8110903.

Muhammad, P., C.R. Duguay, and K.-K. Kang, 2016. Monitoring ice break-up on the Mackenzie River using remote sensing. The Cryosphere, 10: 569-584, doi:10.5194/tc-10-569-2016.

Nandan.V., T. Geldsetzer, T. Islam, J.P.S. Gill, J. Yackel, G. Gunn, and C. Duguay, 2016. Ku-, X- and C-band modeled and measured microwave backscatter from a highly saline snow cover on first-year sea ice. Remote Sensing of Environment, 187: 62-75, https://www.sciencedirect.com/science/article/abs/pii/S0034425716303765.

Surdu, C.M., C.R. Duguay, and D. Fernández Prieto, 2016. Evidence of recent changes in the ice regime of high arctic lakes from spaceborne satellite observations. The Cryosphere, 10: 941-960, doi:10.5194/tc-10-941-2016.

Zolfaghari, K. and C.R. Duguay, 2016. Estimation of water quality parameters in Lake Erie from MERIS using linear mixed effect models. Remote Sensing, 8(6), 473, doi:10.3390/rs8060473.