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Many atmospheric correction schemes of radiance-based optical satellite data require the selection of normalized solar spectral irradiance models at the top of atmosphere (TOA). However, there is no scientific consensus in literature as to which available model is most suitable. This article examines five commonly used models applied to Landsat 8 Operational Land Imager (OLI) TOA radiance and reflectance products to assess the accuracy and stability between models used to derive surface reflectance products. It is assumed that the calibration of the United States Geological Survey (USGS) Landsat 8 OLI TOA reflectance and radiance products are accurate to currently claimed levels. The results show that the retrieved surface reflectance can exhibit significant variations when different solar irradiance models are used, especially in the OLI coastal blue band at 443 nm. From the five solar irradiance models, the Kurucz 2005 model showed the least bias compared with OLI TOA reflectance product and least variance in surface reflectance. Furthermore, improvement was obtained by adjusting the total solar irradiance (TSI) normalization, and additional validation was provided using observed in situ water leaving reflectance data. The results from this article are particularly relevant to aquatic applications and to satellite sensors that provide TOA radiance such as previous Landsat and other current and historical missions.

The intertidal zone represents a critical transition between marine and terrestrial ecosystems, supporting a complex mosaic of highly productive and biologically diverse habitats. However, our understanding of these important coastal environments is limited by a lack of spatially consistent topographic data, which can be extremely challenging and costly to obtain at continental-scale. Satellite remote sensing represents an important resource for monitoring extensive coastal zones. Previous approaches to modelling the elevation of the intertidal zone using earth observation (EO) data have been restricted to small study regions or have relied on manual image interpretation, thus limiting their ability to be applied consistently over large geographic extents. In this study, we present an automated open-source approach to generate satellite-derived elevation data for over 15,387 km2 of intertidal terrain across the entire Australian coastline. Our approach combines global tidal modelling with a 30-year time series archive of spatially and spectrally calibrated Landsat satellite data managed within the Digital Earth Australia (DEA) platform. The resulting National Intertidal Digital Elevation Model (NIDEM) dataset provides an unprecedented three-dimensional representation of Australia's vast exposed intertidal zone at 25 m spatial resolution. We validate our model against LiDAR, RTK GPS and multibeam bathymetry datasets, finding that modelled elevations are highly accurate across sandy beach (±0.41 m RMSE) and tidal flat environments (±0.39 m RMSE). Model performance was least accurate (±2.98 m RMSE) within rocky shores and reefs and other complex coastal environments with extreme and variable tidal regimes. We discuss key challenges associated with modelling intertidal elevation including tidal model performance and biased observations from sun-synchronous satellites, and suggest future directions to improve the accuracy and utility of continental-scale intertidal elevation modelling. Our model can be applied to tidally-influenced coastal environments globally, addressing a key gap between the availability of sub-tidal bathymetry and terrestrial elevation data.

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

Baseline determination and operational continental scale monitoring of water quality are required for reporting on marine and inland water progress to Sustainable Development Goals (SDG). This study aims to improve our knowledge of the optical complexity of Australian waters. A workflow was developed to cluster the modelled spectral response of a range of in situ bio-optical observations collected in Australian coastal and continental waters into distinct optical water types (OWTs). Following clustering and merging, most of the modelled spectra and modelled specific inherent optical properties (SIOP) sets were clustered in 11 OWTs, ranging from clear blue coastal waters to very turbid inland lakes. The resulting OWTs were used to classify Sentinel-2 MSI surface reflectance observations extracted over relatively permanent water bodies in three drainage regions in Eastern Australia. The satellite data classification demonstrated clear limnological and seasonal differences in water types within and between the drainage divisions congruent with general limnological, topographical, and climatological factors. Locations of unclassified observations can be used to inform where in situ bio-optical data acquisition may be targeted to capture a more comprehensive characterization of all Australian waters. This can contribute to global initiatives like the SDGs and increases the diversity of natural water in global databases.

Accurate, robust and consistent coastline mapping is critical for characterising and managing coastal change. Satellite earth observation provides an unparalleled source of freely available data for studying dynamic coastlines through time and across large spatial extents. However, previous satellite-derived shoreline mapping approaches have been challenged by two key limitations: the medium spatial resolution of freely available satellite data, and the confounding influence of tides that can obscure longer term patterns of coastal change. In this study we present Digital Earth Australia Coastlines, a new continental dataset documenting three decades of coastal change across Australia. We combine sub-pixel waterline extraction with a new pixel-based tidal modelling method to seamlessly map almost 2 million km of tide-datum shorelines along the entire Australian coast from 1988 to 2019. Our tidally-constrained median composite approach maps the dominant annual position of the shoreline at 0 m Above Mean Sea Level each year, suppressing the short-term influence of tides and sub-annual shoreline variability. Using this robust mid-term shoreline proxy, long-term coastal change rates spanning the last three decades were accurately quantified and mapped at the continental scale. We find that 22% of Australia's non-rocky coastline has retreated or grown significantly since 1988, with 16% changing at greater than 0.5 m per year. Although trends of retreat and growth were closely balanced across the Australian continent, our results highlight significant regional variability and extreme local hotspots of coastal change. Our findings provide new insights into patterns and trends of coastal change across Australia, and highlight advantages and limitations of tide modelling and composite-based methods for extracting consistent shoreline data and long-term coastal trends from earth observation data at continental scale. Digital Earth Australia Coastlines is made available to the public as free and open interactive tools and code to support future coastal research and management across Australia, and any coastal region globally with access to free and open medium resolution satellite data.

The physical environment of the intertidal zone presents a number of challenges which make traditional surveying methods difficult to implement; whilst the acquisition cost of airborne elevation data can be prohibitive beyond localised applications. Remote sensing data from earth observation satellites has been well established as a method for mapping the extent and elevation profile of the intertidal zone; however the majority of these applications are local in nature, and based on analysis of a limited number of individual image observations. In this paper we outline an automated methodology to model the intertidal extent and topography of the Australian coastline, that leverages a full time series of Landsat observations from 1987 to 2015 managed in the Australian Geoscience Data Cube (AGDC). Our approach reframes the analysis from time of acquisition into the tidal domain through the use of a continental scale tidal model, combined with a median pixel compositing of Normalised Difference Water Index (NDWI) stacks, to robustly estimate the tidal extent and elevation profile across the observed tidal range. We demonstrate the ability of a median-based compositing approach to deal effectively with data quality, modelling outliers and other issues that commonly affect single scene methodologies. Our new framework enables us to produce a continental-scale intertidal model, detailing intertidal zone topography at a 25 m spatial scale. We then demonstrate the potential of the modelling framework to derive digital elevation data based on tidal model attribution, validating our models against in-situ GPS observations, before discussing issues that must be addressed to move this capability to a continental scale. The ability of the model to examine coastal stability is introduced, in the context of the conceptual reframing of the data into the tidal domain, with a view to furthering this application in future versions of the model.

Accurately mapping the boundary between land and water (the ‘waterline’) is critical for tracking change in vulnerable coastal zones, and managing increasingly threatened water resources. Previous studies have largely relied on mapping waterlines at the pixel scale, or employed computationally intensive sub-pixel waterline extraction methods that are impractical to implement at scale. There is a pressing need for operational methods for extracting information from freely available medium resolution satellite imagery at spatial scales relevant to coastal and environmental management. In this study, we present a comprehensive evaluation of a promising method for mapping waterlines at sub-pixel accuracy from satellite remote sensing data. By combining a synthetic landscape approach with high resolution WorldView-2 satellite imagery, it was possible to rapidly assess the performance of the method across multiple coastal environments with contrasting spectral characteristics (sandy beaches, artificial shorelines, rocky shorelines, wetland vegetation and tidal mudflats), and under a range of water indices (Normalised Difference Water Index, Modified Normalised Difference Water Index, and the Automated Water Extraction Index) and thresholding approaches (optimal, zero and automated Otsu’s method). The sub-pixel extraction method shows a strong ability to reproduce both absolute waterline positions and relative shape at a resolution that far exceeds that of traditional whole-pixel methods, particularly in environments without extreme contrast between the water and land (e.g., accuracies of up to 1.50–3.28 m at 30 m Landsat resolution using optimal water index thresholds). We discuss key challenges and limitations associated with selecting appropriate water indices and thresholds for sub-pixel waterline extraction, and suggest future directions for improving the accuracy and reliability of extracted waterlines. The sub-pixel waterline extraction method has a low computational overhead and is made available as an open-source tool, making it suitable for operational continental-scale or full time-depth analyses aimed at accurately mapping and monitoring dynamic waterlines through time and space.

Generating continental-scale pixel composites in dynamic coastal and estuarine environments presents a unique challenge, as the application of a temporal or seasonal approach to composite generation is confounded by tidal influences. We demonstrate how this can be resolved using an approach to compositing that provides robust composites of multi-type environments. In addition to the visual aesthetics of the images created, we demonstrate the utility of these composites for further interpretation and analysis. This is enabled by the manner in which our approach captures the spatial variation in tidal dynamics through the use of a Voronoi mesh, and preserves the band relationships within the modelled spectra at each pixel. Case studies are presented which include continental-scale mosaics of the Australian coastline at high and low tide, and tailored examples demonstrating the potential of the tidally constrained composites to address a range of coastal change detection and monitoring applications. We conclude with a discussion on the potential applications of the composite products and method in the coastal and marine environment, as well as further development directions for our tidal modelling framework.

This paper outlines a methodology for the estimation of the environmental noise equivalent reflectance in aquatic remote sensing imagery using an object-based segmentation approach. Noise characteristics of remote sensing imagery directly influence the accuracy of estimated environmental variables and provide a framework for a range of sensitivity, sensor specification, and algorithm design studies. The proposed method enables estimation of the noise equivalent reflectance covariance of remote sensing imagery through homogeneity characterization using image segmentation. The method is first tested on a synthetic data set with known noise characteristics and is successful in estimating the noise equivalent reflectance under a range of segmentation structures. Testing on a Portable Hyperspectral Imager for Low-Light Spectroscopy (PHILLS) hyperspectral image in a coral reef environment shows the method to produce comparable noise equivalent reflectance estimates in an optically shallow water environment to those previously derived in optically deep water. This method is of benefit in aquatic studies where homogenous regions of optically deep water were previously required for image noise estimation. The ability of the method to characterize the covariance of an image is of significant benefit when developing probabilistic inversion techniques for remote sensing.

Publisher Summary Lord Howe Island (31°33"S, 159°04"E) sits approximately 580 km east of Australia in the southwest Pacific Ocean. This remote island is the subaerial remnant of a hot-spot volcano that erupted between 6.6 and 7.2 Ma and comprises a mid-ocean basaltic sequence. Erosion of these basalts has dominated island evolution since the cessation of volcanism, creating a rhomboidal-shaped shelf around Lord Howe Island, 24 km wide and 36 km from north to south. As part of a large collaborative program of marine biodiversity research, the shelf around Lord Howe Island was selected as an area representative of a shallow (20–120 m) mid-ocean carbonate shelf environment. The relict reef comprises sand sheet, macroalgae, and hardground habitats. Inshore of the relict reef a sandy basin (mean depth 45 m) has thick sand deposits. Offshore of the relict reef is a relatively flat outer shelf (mean depth 60 m) with bedrock exposures and sandy habitat. Infauna species abundance and richness were similar for sediment samples collected on the outer shelf and relict reef, while samples from the basin had significantly lower infauna abundance and richness. The irregular shelf morphology appears to determine the distribution and character of sandy substrates and local oceanographic conditions, which in turn influence the distribution of different types of infauna communities.

Mapping the shallow water bathymetry of aquatic environments such as the Great Barrier Reef presents a number of challenges, due to both the large area which it occupies and the widely dispersed and variable shallow water reef areas which characterize it.

Integrative oncology combines the discipline of modern science with the wisdom of traditional healing [...]