Description: Statewide marine lidar data was collected along the NSW coast in 2018, with elevation data collected down to an average of 35 m depth. This dataset represents aclassification of seabed landforms derived from this marine lidar data, which delineates the prominent seabed features observed. This classification defines areas of reefs, peaks (uppermost part of the reef surface), plains, depressions and channels (within the reef surface), and scarps (areas greater than 10 degrees slope). The statewide dataset is provided as ArcGIS shapefiles divided into 9 segments along the coast, covering 4060 km2 of NSW coastal waters. Features were classified using the Seabed Landforms Classification Toolset (ArcGIS), developed by DPE (Linklater & Morris, 2022) which applies the methodological framework presented in Linklater et al. (2019). In this classification approach, ruggedness (VRM, Walbridge et al. 2018), slope, finescale and broadscale Bathymetric Position Index (Slope Position, Evans et al. 2014) variables were derived from the marine lidar bathymetric dataset and used to characterise prominent features within the seascape. Procedures were implemented to reduce potential noise witin the dataset and identify the full extent of reef outcrops. Manual editing was performed to separate inferred reef outcrops from soft sediment bedforms,with the resulting classification focused on identifying the presence, extent and character of submerged reef outcrops within the marine lidar dataset. The classification output was reviewed and edited by the data creator to capture observed and interpreted seabed features. The resulting layer was externally reviewed to ensure scientific rigour and data integrity.Please cite this dataset as: Linklater, M., Morris, B., Kinsela, M., Ingleton, T. and Hanslow, D. (2022), Exploring patterns of reef distribution along the southeast Australian coast using marine lidar data. Manuscript in preparation.NSW statewide marine lidar data – available for download on SEED:https://datasets.seed.nsw.gov.au/dataset/marine-lidar-topo-bathy-2018Linklater, M. and Morris, B. (2022), Classification of seabed landforms on continental and island shelves. Manuscript in preparation.Linklater, M., Ingleton, T. C., Kinsela, M. A., Morris, B. D., Allen, K. M., Sutherland, M. D.,& Hanslow, D. J. 2019. Techniques for classifying seabed morphology and composition on a subtropical-temperate continental shelf. Geosciences, 9(3), 141.Walbridge, S., Slocum, N., Pobuda, M., Wright, D.J., 2018. Unified geomorphological analysis workflows with Benthic Terrain Modeler. Geosciences, 8(3), 94.Evans, J., Oakleaf, J., Cushman, S., 2014. An ArcGIS Toolbox for Surface Gradient and Geomorphometric Modeling, Version 2.0-0. Available online:https://github.com/jeffreyevans/GradientMetrics.
Description: Multibeam echosounder data was collected offshore of Wollongong, NSW in 2016-17, covering an area of 102 km2 in 4 to 62 m water depth. This dataset represents a classification of seabed landforms derived from this MBES data, which delineates the prominent seabed features observed. This classification defines areas of reefs, peaks (uppermost part of the reef surface), plains, depressions and channels (within the reef surface), and scarps (areas greater than 10 degrees slope). The dataset is provided as an ArcGIS shapefile. Features were classified using the Seabed Landforms Classification Toolset (ArcGIS), developed by DPE (Linklater & Morris, 2022) which applies the methodological framework presented in Linklater et al. (2019). In this classification approach, ruggedness (VRM, Walbridge et al. 2018), slope, finescale and broadscale Bathymetric Position Index (Slope Position, Evans et al. 2014) variables were derived from the MBES dataset and used to characterise prominent features within the seascape. Procedures were implemented to reduce potential noise within the dataset and identify the full extent of reef outcrops. Manual editing was performed to separate inferred reef outcrops from soft sediment bedforms, with the resulting classification focussed on identifying the presence, extent and character of submerged reef outcrops within the MBES dataset. The classification output was reviewed and edited by the data creator to capture observed and interpreted seabed features. The resulting layer was externally reviewed to ensure scientific rigour and data integrity.Wollongong multibeam echosounder data is available for download on AODN: https://portal.aodn.org.auLinklater, M. and Morris, B. (2022), Classification of seabed landforms on continental and island shelves. Manuscript in preparation. Linklater, M., Ingleton, T. C., Kinsela, M. A., Morris, B. D., Allen, K. M., Sutherland, M. D., & Hanslow, D. J. 2019. Techniques for classifying seabed morphology and composition on a subtropical-temperate continental shelf. Geosciences, 9(3), 141.Walbridge, S., Slocum, N., Pobuda, M., Wright, D.J., 2018. Unified geomorphological analysis workflows with Benthic Terrain Modeler. Geosciences, 8(3), 94.Evans, J., Oakleaf, J., Cushman, S., 2014. An ArcGIS Toolbox for Surface Gradient and Geomorphometric Modeling, Version 2.0-0. Available online: https://github.com/jeffreyevans/GradientMetrics.
Copyright Text: This dataset was created by the Coastal and Marine Unit, New South Wales Department of Planning and Environment.
Description: Multibeam echosounder data was collected offshore of Shellharbour, NSW in 2017, covering an area of 45 km2 in 10 to 64 m water depth. This dataset represents a classification of seabed landforms derived from this MBES data, which delineates the prominent seabed features observed. This classification defines areas of reefs, peaks (uppermost part of the reef surface), plains, depressions and channels (within the reef surface), and scarps (areas greater than 10 degrees slope). The dataset is provided as an ArcGIS shapefile. Features were classified using the Seabed Landforms Classification Toolset (ArcGIS), developed by DPE (Linklater & Morris, 2022) which applies the methodological framework presented in Linklater et al. (2019). In this classification approach, ruggedness (VRM, Walbridge et al. 2018), slope, finescale and broadscale Bathymetric Position Index (Slope Position, Evans et al. 2014) variables were derived from the MBES dataset and used to characterise prominent features within the seascape. Procedures were implemented to reduce potential noise within the dataset and identify the full extent of reef outcrops. Manual editing was performed to separate inferred reef outcrops from soft sediment bedforms, with the resulting classification focussed on identifying the presence, extent and character of submerged reef outcrops within the MBES dataset. The classification output was reviewed and edited by the data creator to capture observed and interpreted seabed features. The resulting layer was externally reviewed to ensure scientific rigour and data integrity.Shellharbour multibeam echosounder data will be made available for download on AODN: https://portal.aodn.org.auLinklater, M. and Morris, B., 2022, Classification of seabed landforms on continental and island shelves. Manuscript in preparation. Kinsela, M.A., Hanslow, D.J., Carvalho, R.C., Linklater, M., Ingleton, T.C., Morris, B.D., Allen, K.M., Sutherland, M.D. Woodroffe, C.D., 2020. Mapping the shoreface of coastal sediment compartments to improve shoreline change forecasts in New South Wales, Australia. Estuaries and Coasts, pp.1-27.Linklater, M., Ingleton, T. C., Kinsela, M. A., Morris, B. D., Allen, K. M., Sutherland, M. D., Hanslow, D. J., 2019. Techniques for classifying seabed morphology and composition on a subtropical-temperate continental shelf. Geosciences, 9(3), 141.Walbridge, S., Slocum, N., Pobuda, M., Wright, D.J., 2018., Unified geomorphological analysis workflows with Benthic Terrain Modeler. Geosciences, 8(3), 94.Evans, J., Oakleaf, J., Cushman, S., 2014., An ArcGIS Toolbox for Surface Gradient and Geomorphometric Modeling, Version 2.0-0. Available online: https://github.com/jeffreyevans/GradientMetrics.
Copyright Text: This dataset was created by the Coastal and Marine Unit, New South Wales Department of Planning and Environment.