Select Publications
Book Chapters
, 2026, 'ShoreShop2.0: Blind Testing of Shoreline Models', in Coastal Research Library, pp. 718 - 723, http://dx.doi.org/10.1007/978-3-032-15477-4_107
Journal articles
, 2027, 'A review on the use of Synthetic Aperture Radar (SAR) for monitoring shorelines and intertidal areas', Coastal Engineering, 213, http://dx.doi.org/10.1016/j.coastaleng.2026.105145
, 2026, 'A Forty-year regional-scale dataset of shoreline change and nearshore wave conditions in Southeast Australia', Scientific Data, 13, http://dx.doi.org/10.1038/s41597-026-06859-3
, 2026, 'NZ-BeachTopo30: a national-scale and full-coverage 30 m beach topography dataset for New Zealand reconstructed by fusing ICESat-2 and Sentinel-2', Earth System Science Data, 18, pp. 4563 - 4591, http://dx.doi.org/10.5194/essd-18-4563-2026
, 2026, 'Shorelines as graphs: A spatio-temporal data-driven model for predicting shoreline dynamics', Coastal Engineering, 208, http://dx.doi.org/10.1016/j.coastaleng.2026.105017
, 2026, 'Selecting Suitable Nitrogen Offset Strategies In Tropical And Subtropical Regions Globally With Implications To The Great Barrier Reef, Australia', Environmental Management, 76, http://dx.doi.org/10.1007/s00267-026-02466-5
, 2025, 'Benchmarking shoreline prediction models over multi-decadal timescales', Communications Earth and Environment, 6, http://dx.doi.org/10.1038/s43247-025-02550-4
, 2025, 'CAN WE RELIABLY EXTRACT SHORELINES FROM CLOUD-CONTAMINATED SATELLITE IMAGES: THE APPLICATION OF SAR-OPTICAL FUSION METHOD', Coastal Engineering Proceedings, pp. 30, http://dx.doi.org/10.9753/icce.v38.management.30
, 2025, 'Application of SAR-Optical fusion to extract shoreline position from Cloud-Contaminated satellite images', ISPRS Journal of Photogrammetry and Remote Sensing, 220, pp. 563 - 579, http://dx.doi.org/10.1016/j.isprsjprs.2025.01.013
, 2024, 'Predicting Ground Cover with Deep Learning Models—An Application of Spatio-Temporal Prediction Methods to Satellite-Derived Ground Cover Maps in the Great Barrier Reef Catchments', Remote Sensing, 16, http://dx.doi.org/10.3390/rs16173193
, 2024, 'Offset integrity reduces environmental risk: Using lessons from biodiversity and carbon offsetting to inform water quality offsetting in the catchments of the Great Barrier Reef', The Science of The Total Environment, 951, pp. 175786, http://dx.doi.org/10.1016/j.scitotenv.2024.175786
, 2023, 'Benchmarking satellite-derived shoreline mapping algorithms', Communications Earth and Environment, 4, http://dx.doi.org/10.1038/s43247-023-01001-2
, 2023, 'Reconstructing cloud-contaminated NDVI images with SAR-Optical fusion using spatio-temporal partitioning and multiple linear regression', ISPRS Journal of Photogrammetry and Remote Sensing, 198, pp. 115 - 139, http://dx.doi.org/10.1016/j.isprsjprs.2023.03.003
, 2022, 'Global coastal geomorphology – integrating earth observation and geospatial data', Remote Sensing of Environment, 278, http://dx.doi.org/10.1016/j.rse.2022.113082
, 2021, 'Efficient measurement of large-scale decadal shoreline change with increased accuracy in tide-dominated coastal environments with Google Earth Engine', ISPRS Journal of Photogrammetry and Remote Sensing, 181, pp. 385 - 399, http://dx.doi.org/10.1016/j.isprsjprs.2021.09.021
, 2021, 'Determining the Shoreline Retreat Rate of Australia Using Discrete and Hybrid Bayesian Networks', Journal of Geophysical Research Earth Surface, 126, http://dx.doi.org/10.1029/2021JF006112
, 2019, 'Mapping the sandy beach evolution around seaports at the scale of the African continent', Journal of Marine Science and Engineering, 7, http://dx.doi.org/10.3390/jmse7050151
Theses / Dissertations
, Predicting long-term shoreline response to sea-level rise on continental and global scales with data-driven models, http://dx.doi.org/10.14264/d566c79
Preprints
, NZ-BeachTopo30: A national-scale and full-coverage 30 m beach topography dataset for New Zealand reconstructed by fusing ICESat-2 and Sentinel-2, http://dx.doi.org/10.5194/essd-2025-826
, Satellite-derived shorelines for monitoring of sandy beaches: a benchmark study, http://dx.doi.org/10.31223/x58w98