DEA Intertidal Elevation (Landsat) ================================== National Intertidal Digital Elevation Model 25m 1.0.0 ------------------------------------------------------ **Authored on**: 2018-03 **Updated on**: 2021-07 **Author/s**: Robbi Bishop-Taylor, Stephen Sagar, Leo Lymburner **License**: CC BY Attribution 4.0 International License View the [original metadata page](https://cmi.ga.gov.au/data-products/dea/325/dea-intertidal-elevation-landsat) for the most up-to-date information on this product. Abstract -------- Intertidal environments support important ecological habitats (e.g. sandy beaches and shores, tidal flats and rocky shores and reefs), and provide many valuable benefits such as storm surge protection, carbon storage and natural resources for recreational and commercial use. Intertidal zones are faced with increasing threats from coastal erosion, land reclamation (e.g. port construction), and sea level rise. Accurate elevation data describing the height and shape of the coastline is needed to help predict when and where these threats will have the greatest impact. However, this data is expensive and challenging to map across the entire intertidal zone of a continent the size of Australia. What this product offers ------------------------ The National Intertidal Digital Elevation Model (NIDEM) is a continental-scale elevation dataset for Australia's exposed intertidal zone. This product provides the first three-dimensional representation of Australia's intertidal sandy beaches and shores, tidal flats and rocky shores and reefs at 25 m spatial resolution, addressing a key gap between the availability of sub-tidal bathymetry and terrestrial elevation data. Applications ------------ - Integrating with existing topographic and bathymetric data to seamlessly map the elevation of the coastal zone - Providing baseline elevation data for predicting the impact of coastal hazards such as storm surges, tsunami inundation or future sea-level rise - Investigating coastal erosion and sediment transport processes - Supporting habitat mapping and modelling for coastal ecosystems extending across the terrestrial to marine boundary Accuracy and limitations ------------------------ #### Accuracy To assess the accuracy of NIDEM, we compared modelled elevations against three independent elevation and bathymetry validation datasets: the DEM of Australia derived from LiDAR 5 Metre Grid (Geoscience Australia, 2015), elevation data collected from Real Time Kinematic (RTK) GPS surveys (Danaher & Collett, 2006; HydroSurvey Australia, 2009), and 1.0 m resolution multibeam bathymetry surveys (Solihuddin et al., 2016). We assessed overall accuracy across three distinct intertidal environments: sandy beaches and shores, tidal flats, and rocky shores and reefs: - Sandy beaches and shores, 5 sites: Pearson's correlation = 0.92, Spearman's correlation = 0.93, RMSE +/- 0.41 m - Tidal flats, 9 sites: Pearson's correlation = 0.78, Spearman's correlation = 0.81, RMSE +/- 0.39 m - Rocky shores and reefs, 7 sites: Pearson's correlation = 0.46, Spearman's correlation = 0.79, RMSE +/- 2.98 m #### Limitations NIDEM covers the exposed intertidal zone which includes sandy beaches and shores, tidal flats and rocky shores and reefs. The model excludes intertidal vegetation communities such as mangroves. Areas with comparatively steep coastlines and small tidal ranges are poorly captured in the 25 m spatial resolution input Landsat data and resulting NIDEM model. This includes much of the south eastern and southern Australian coast (e.g. New South Wales, Victoria, Tasmania). Poor validation results for rocky shore and reef sites within the southern Kimberly region highlighted limitations in the NIDEM model that occur when the global OTPS TPX08 Atlas Tidal Model was unable to predict complex and asynchronous local tidal patterns. This is likely to also reduce model accuracy in complex estuaries and coastal wetlands where river flow or vegetative resistance causes hydrodynamic attenuation in tidal flow. The complex temporal behaviour of tides mean that a sun synchronous sensor like Landsat does not observe the full range of the tidal cycle at all locations. This causes spatial bias in the proportion of the tidal range observed in different regions, which can prevent NIDEM from providing elevation data for areas of the intertidal zone exposed or inundated at the extremes of the tidal range. Accordingly, NIDEM provides elevation data for the portion of the tidal range observed by Landsat, rather than the full tidal range. While image compositing and masking methods have been applied to remove the majority of noise and non-tidal artefacts from NIDEM, issues remain in several locations. It is recommended that the data be used with caution in the following areas: - The Recherche Archipelago in southern Western Australia - Port Phillip Bay in Victoria - The eastern coast of Tasmania and King Island - Saunders Reef and surrounds in the northern Coral Sea Publications ------------ Bishop-Taylor, R., Sagar, S., Lymburner, L., & Beaman, R. J. (2019). Between the tides: Modelling the elevation of Australia’s exposed intertidal zone at continental scale. *Estuarine, Coastal and Shelf Science*, *223*, 115–128. References ---------- Bishop-Taylor, R., Sagar, S., Lymburner, L., & Beaman, R. J. (2019). Between the tides: Modelling the elevation of Australia’s exposed intertidal zone at continental scale. *Estuarine, Coastal and Shelf Science*, *223*, 115–128. Chen, L. C. (1998). Detection of shoreline changes for tideland areas using multi-temporal satellite images. *International Journal of Remote Sensing*, *19*(17), 3383–3397. Chen, Y., Dong, J., Xiao, X., Zhang, M., Tian, B., Zhou, Y., Li, B., & Ma, Z. (2016). Land claim and loss of tidal flats in the Yangtze Estuary. *Scientific Reports*, *6*(1), 24018. Liu, Y., Li, M., Zhou, M., Yang, K., & Mao, L. (2013). Quantitative analysis of the waterline method for topographical mapping of tidal flats: A case study in the dongsha sandbank, china. *Remote Sensing*, *5*(11), 6138–6158. Sagar, S., Phillips, C., Bala, B., Roberts, D., & Lymburner, L. (2018). Generating continental scale pixel-based surface reflectance composites in coastal regions with the use of a multi-resolution tidal model. *Remote Sensing*, *10*(3), 480. Sagar, S., Roberts, D., Bala, B., & Lymburner, L. (2017). Extracting the intertidal extent and topography of the Australian coastline from a 28 year time series of Landsat observations. *Remote Sensing of Environment*, *195*, 153–169. Solihuddin, T., O’Leary, M. J., Blakeway, D., Parnum, I., Kordi, M., & Collins, L. B. (2016). Holocene reef evolution in a macrotidal setting: Buccaneer Archipelago, Kimberley Bioregion, Northwest Australia. *Coral Reefs*, *35*(3), 783–794. Zhao, B., Guo, H., Yan, Y., Wang, Q., & Li, B. (2008). A simple waterline approach for tidelands using multi-temporal satellite images: A case study in the Yangtze Delta. *Estuarine, Coastal and Shelf Science*, *77*(1), 134–142. Contacts -------- For questions or more information about this product, email [DEA Support](mailto:dea@ga.gov.au?subject=Data%20Products%20support%20for%20DEA%20Intertidal%20Elevation%20%28Landsat%29&cc=Robbi.BishopTaylor@ga.gov.au,stephen.sagar@ga.gov.au).