Select Publications
Book Chapters
2020, 'Machine learning and coastal processes', in Sandy Beach Morphodynamics, pp. 689 - 710, http://dx.doi.org/10.1016/B978-0-08-102927-5.00028-X
,2020, '28 Machine learning and coastal processes', in Sandy Beach Morphodynamics, Elsevier, pp. 689 - 710, http://dx.doi.org/10.1016/b978-0-08-102927-5.00028-x
,2020, 'Machine learning and coastal processes', in Jackson D; Short A (ed.), Sandy Beach Morphodynamics, Elsevier, pp. 689 - 710, http://dx.doi.org/10.1016/C2018-0-02420-2
,Journal articles
2025, 'Do LSTM memory states reflect the relationships in reduced-complexity sandy shoreline models', Environmental Modelling and Software, 183, http://dx.doi.org/10.1016/j.envsoft.2024.106236
,2024, 'Coastal shoreline change assessments at global scales', Nature Communications, 15, http://dx.doi.org/10.1038/s41467-024-46608-x
,2024, 'Observations on the role of internal sand moisture dynamics in wave-driven dune face erosion', Geomorphology, 462, http://dx.doi.org/10.1016/j.geomorph.2024.109331
,2024, 'A framework for national-scale coastal storm hazards early warning', Coastal Engineering, 192, http://dx.doi.org/10.1016/j.coastaleng.2024.104571
,2024, 'High-resolution topographic surveying and change detection with the iPhone LiDAR', Nature Protocols, http://dx.doi.org/10.1038/s41596-024-01024-9
,2023, 'Benchmarking satellite-derived shoreline mapping algorithms', Communications Earth and Environment, 4, http://dx.doi.org/10.1038/s43247-023-01001-2
,2023, 'CAN APPLE LIDAR CAMERAS BE RELIABLY USED FOR COASTAL MONITORING?', Proceedings of the Coastal Engineering Conference
,2023, 'NON-LINEAR DISPERSION EFFECTS IN NEARSHORE WAVES: PERSPECTIVES FOR DEPTH-INVERSION APPLICATIONS', Proceedings of the Coastal Engineering Conference
,2023, 'OBSERVATIONS FROM A CONTROLLED DUNE EROSION EXPERIMENT UNDER VARIABLE WATER LEVELS, WAVES, AND INTERNAL DUNE MOISTURE CONTENT', Proceedings of the Coastal Engineering Conference
,2023, 'SPATIAL VARIABILITY IN BEACH-FACE SLOPES FROM SATELLITE REMOTE SENSING', Proceedings of the Coastal Engineering Conference
,2023, 'Interannual variability in dominant shoreline behaviour at an embayed beach', Geomorphology, 433, http://dx.doi.org/10.1016/j.geomorph.2023.108706
,2023, 'A Model Integrating Satellite-Derived Shoreline Observations for Predicting Fine-Scale Shoreline Response to Waves and Sea-Level Rise Across Large Coastal Regions', Journal of Geophysical Research: Earth Surface, 128, http://dx.doi.org/10.1029/2022JF006936
,2023, 'Pacific shoreline erosion and accretion patterns controlled by El Niño/Southern Oscillation', Nature Geoscience, 16, pp. 140 - 146, http://dx.doi.org/10.1038/s41561-022-01117-8
,2023, 'New Perspectives for Nonlinear Depth-Inversion of the Nearshore Using Boussinesq Theory', Geophysical Research Letters, 50, http://dx.doi.org/10.1029/2022GL100498
,2023, 'Coastal futures: New framings, many questions, some ways forward', Cambridge Prisms: Coastal Futures, 1, http://dx.doi.org/10.1017/cft.2023.22
,2023, 'Drivers of change in Arctic fjord socio-ecological systems: Examples from the European Arctic', Cambridge Prisms: Coastal Futures, 1, http://dx.doi.org/10.1017/cft.2023.1
,2023, 'Introducing Cambridge Prisms: Coastal Futures', Cambridge Prisms: Coastal Futures, 1, http://dx.doi.org/10.1017/cft.2022.12
,2022, 'Improving multi-decadal coastal shoreline change predictions by including model parameter non-stationarity', Frontiers in Marine Science, 9, http://dx.doi.org/10.3389/fmars.2022.1012041
,2022, 'A Python toolkit to monitor sandy shoreline change using high-resolution PlanetScope cubesats', Environmental Modelling and Software, 157, http://dx.doi.org/10.1016/j.envsoft.2022.105512
,2022, 'Dynamic Motions of Piled Floating Pontoons Due to Boat Wake and Their Impact on Postural Stability and Safety', Journal of Marine Science and Engineering, 10, http://dx.doi.org/10.3390/jmse10111633
,2022, 'Creating communities and communicating science during COVID-19: From Coast2Coast to Coast2Cast', Continental Shelf Research, 245, http://dx.doi.org/10.1016/j.csr.2022.104794
,2022, '‘Coastal Management Guide - Managing Coastal Erosion’: A STEM education resource for secondary school teachers', Continental Shelf Research, 244, http://dx.doi.org/10.1016/j.csr.2022.104783
,2022, 'A multi-model ensemble approach to coastal storm erosion prediction', Environmental Modelling and Software, 150, http://dx.doi.org/10.1016/j.envsoft.2022.105356
,2022, 'Beach-face slope dataset for Australia', Earth System Science Data, 14, pp. 1345 - 1357, http://dx.doi.org/10.5194/essd-14-1345-2022
,2022, 'Sensitivity of a one-line longshore shoreline change model to the mean wave direction', Coastal Engineering, 172, http://dx.doi.org/10.1016/j.coastaleng.2021.104025
,2021, 'Challenges and Opportunities in Coastal Shoreline Prediction', Frontiers in Marine Science, 8, http://dx.doi.org/10.3389/fmars.2021.788657
,2021, 'A storm hazard matrix combining coastal flooding and beach erosion', Coastal Engineering, 170, http://dx.doi.org/10.1016/j.coastaleng.2021.104001
,2021, 'Bathymetric data requirements for operational coastal erosion forecasting using xbeach', Journal of Marine Science and Engineering, 9, http://dx.doi.org/10.3390/jmse9101053
,2021, 'LIDAR scanning as an advanced technology in physical hydraulic modelling: The stilling basin example', Remote Sensing, 13, http://dx.doi.org/10.3390/rs13183599
,2021, 'Aligning free surface properties in time-varying hydraulic jumps', Experimental Thermal and Fluid Science, 126, http://dx.doi.org/10.1016/j.expthermflusci.2021.110392
,2021, 'Modelling cross‐shore shoreline change on multiple timescales and their interactions', Journal of Marine Science and Engineering, 9, http://dx.doi.org/10.3390/jmse9060582
,2020, 'Do we need pre-storm surveyed bathymetry for operational erosion forecasting? Evaluation of representative and synthetic bathymetry alternatives', Proceedings of the Coastal Engineering Conference, 36
,2020, 'Machine learning classification of beach state from argus imagery', Proceedings of the Coastal Engineering Conference, 36
,2020, 'Beach state recognition using argus imagery and convolutional neural networks', Remote Sensing, 12, pp. 1 - 20, http://dx.doi.org/10.3390/rs12233953
,2020, 'Blind testing of shoreline evolution models', Scientific Reports, 10, http://dx.doi.org/10.1038/s41598-020-59018-y
,2020, 'Enhanced Coastal Shoreline Modeling Using an Ensemble Kalman Filter to Include Nonstationarity in Future Wave Climates', Geophysical Research Letters, 47, http://dx.doi.org/10.1029/2020GL090724
,2020, 'Enhanced coastal shoreline modelling using an Ensemble Kalman Filter to include non-stationarity in future wave climates', , http://dx.doi.org/10.1002/essoar.10503626.2
,2020, 'Beach Slopes From Satellite-Derived Shorelines', Geophysical Research Letters, 47, http://dx.doi.org/10.1029/2020GL088365
,2020, 'Priorities for wind-waves research', Bulletin of the American Meteorological Society, 101, pp. 505 - 507, http://dx.doi.org/10.1175/BAMS-D-18-0262.A
,2020, 'Coastal Engineering: Processes, Theory, and Design Practice, 3rd edition', Journal of Coastal Research, 36, pp. 676 - 676, http://dx.doi.org/10.2112/jcoastres-d-19a-00014.1
,2020, 'Controls of local geology and cross-shore/longshore processes on embayed beach shoreline variability', Marine Geology, 422, http://dx.doi.org/10.1016/j.margeo.2020.106118
,2019, 'CoastSat: A Google Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite imagery', Environmental Modelling and Software, 122, http://dx.doi.org/10.1016/j.envsoft.2019.104528
,2019, 'Controls of Variability in Berm and Dune Storm Erosion', Journal of Geophysical Research, http://dx.doi.org/10.1029/2019JF005184
,2019, 'Calibration data requirements for modelling subaerial beach storm erosion', Coastal Engineering, 152, http://dx.doi.org/10.1016/j.coastaleng.2019.103507
,2019, 'Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery', Coastal Engineering, 150, pp. 160 - 174, http://dx.doi.org/10.1016/j.coastaleng.2019.04.004
,2019, '15 priorities for wind-waves research: An Australian perspective', Bulletin of the American Meteorological Society, 101, pp. E446 - E461, http://dx.doi.org/10.1175/bams-d-18-0262.1
,2019, 'Ensemble models from machine learning: an example of wave runup and coastal dune erosion', , http://dx.doi.org/10.5194/nhess-2019-81
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