ALBERT

Description: The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.

Description: Here we demonstrate the applicability of using altimetry data and Landsat imagery to provide the most accurate digital elevation model (DEM) of Australia's largest playa lake – Lake Eyre. We demonstrate through the use of geospatial techniques a robust assessment of lake area and volume of recent lake-filling episodes whilst also providing the most accurate estimates of area and volume for larger lake filling episodes that occurred throughout the last glacial cycle. We highlight that at a depth of 25 m Lake Mega-Eyre would merge with the adjacent Lake Mega-Frome to form an immense waterbody with a combined area of almost 35,000 km**2 and a combined volume of ~520 km**3. This would represent a vast water body in what is now the arid interior of the Australian continent. The improved DEM is more reliable from a geomorphological and hydrological perspective and allows a more accurate assessment of water balance under the modern hydrological regime. The results presented using GLAS/ICESat data suggest that earlier historical soundings were correct and the actual lowest topographic point in Australia is -15.6 m below sea level. The results also contrast nicely the different basin characteristics of two adjacent lake systems; Lake Eyre and Lake Frome.

Description: Hydrographers have traditionally referred to the nearshore area as the "white ribbon" area due to the challenges associated with the collection of elevation data in this highly dynamic transitional zone between terrestrial and marine environments. Accordingly, available information in this zone is typically characterised by a range of datasets from disparate sources. In this paper we propose a framework to 'fill' the white ribbon area of a coral reef system by integrating multiple elevation and bathymetric datasets acquired by a suite of remote-sensing technologies into a seamless digital elevation model (DEM). A range of datasets are integrated, including field-collected GPS elevation points, terrestrial and bathymetric LiDAR, single and multibeam bathymetry, nautical chart depths and empirically derived bathymetry estimations from optical remote sensing imagery. The proposed framework ranks data reliability internally, thereby avoiding the requirements to quantify absolute error and results in a high resolution, seamless product. Nested within this approach is an effective spatially explicit technique for improving the accuracy of bathymetry estimates derived empirically from optical satellite imagery through modelling the spatial structure of residuals. The approach was applied to data collected on and around Lizard Island in northern Australia. Collectively, the framework holds promise for filling the white ribbon zone in coastal areas characterised by similar data availability scenarios. The seamless DEM is referenced to the horizontal coordinate system MGA Zone 55 - GDA 1994, mean sea level (MSL) vertical datum and has a spatial resolution of 20 m.

Description: Orthomosaics for this project were created using Structure-from-Motion (SfM) algorithms from drone-derived imagery. The resultant orthomosaics have 2 cm resolution and are georeferenced to the GDA94 MGA zone 54 coordinate system. Positional accuracy is subject to errors from the on-board GPS and estimated between 5-10 m. GeoTiff data is available and can be requested. Please email the author (jleon@usc.edu.au) and provide a brief paragraph as to the intended use of the data. Images were acquired with a DJI Mavic Pro drone (〈 2 kg) at 50 m altitude using DJI Ground Station Pro mission planner. The drone was operated as part of a GBRMPA accredit institution (University of Queenland). The following were considered to improve image quality over water: - The camera was tilted 10 degrees off nadir - 90% forward / 60% side overlap was used - Flights were undertaken only when wind was 〈 15 knots - Sun azimuth was kept away from the flight direction to reduce glint - Flights were mostly undertaken before midday to reduce glint, although this was not always possible. Similarly, timing low tide levels was not always possible. Images were processed using Agisoft Photoscan 1.4.3 software using the following steps/parameters: - Alignment: Highest accuracy - Resultant sparse point cloud was cleaned selectively and manually. - Build Dense cloud: High quality, Aggressive depth filtering - Calibrate colours: source data - model, no white balance correction - Build Texture: Generic mapping mode - Build DEM: source dense cloud, resolution - 0.02 m/pix, projection - GDA94 MGA zone 54 - Build Orthomosaic: Surface - DEM, resolution - 0.02 m, projection - GDA94 MGA zone 54

Description: Underwater georeferenced photo-transect surveys were conducted on December 10-15, 2011 at various sections of the reef at Lizard Island, Great Barrier Reef. For this survey a snorkeler or diver swam over the bottom while taking photos of the benthos at a set height using a standard digital camera and towing a GPS in a surface float which logged the track every five seconds. A standard digital compact camera was placed in an underwater housing and fitted with a 16 mm lens which provided a 1.0 m x 1.0 m footprint, at 0.5 m height above the benthos. Horizontal distance between photos was estimated by three fin kicks of the survey diver/snorkeler, which corresponded to a surface distance of approximately 2.0 - 4.0 m. The GPS was placed in a dry-bag and logged the position as it floated at the surface while being towed by the photographer. A total of 5,735 benthic photos were taken. A floating GPS setup connected to the swimmer/diver by a line enabled recording of coordinates of each benthic photo (Roelfsema 2009). Approximation of coordinates of each benthic photo was conducted based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the GPS coordinates that were logged at a set time before and after the photo was captured. Benthic or substrate cover data was derived from each photo by randomly placing 24 points over each image using the Coral Point Count for Microsoft Excel program (Kohler and Gill, 2006). Each point was then assigned to 1 of 78 cover types, which represented the benthic feature beneath it. Benthic cover composition summary of each photo scores was generated automatically using CPCE program. The resulting benthic cover data of each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 55 South.

Description: Coral reefs represent major accumulations of calcium carbonate (CaCO3). The particularly labyrinthine network of reefs in Torres Strait, north of the Great Barrier Reef (GBR), has been examined in order to estimate their gross CaCO3 productivity. The approach involved a two-step procedure, first characterising and classifying the morphology of reefs based on a classification scheme widely employed on the GBR and then estimating gross CaCO3 productivity rates across the region using a regional census-based approach. This was undertaken by independently verifying published rates of coral reef community gross production for use in Torres Strait, based on site-specific ecological and morphological data. A total of 606 reef platforms were mapped and classified using classification trees. Despite the complexity of the maze of reefs in Torres Strait, there are broad morphological similarities with reefs in the GBR. The spatial distribution and dimensions of reef types across both regions are underpinned by similar geological processes, sea-level history in the Holocene and exposure to the same wind/wave energetic regime, resulting in comparable geomorphic zonation. However, the presence of strong tidal currents flowing through Torres Strait and the relatively shallow and narrow dimensions of the shelf exert a control on local morphology and spatial distribution of the reef platforms. A total amount of 8.7 million tonnes of CaCO3 per year, at an average rate of 3.7 kg CaCO3 m-2 yr-1 (G), were estimated for the studied area. Extrapolated production rates based on detailed and regional census-based approaches for geomorphic zones across Torres Strait were comparable to those reported elsewhere, particularly values for the GBR based on alkalinity-reduction methods. However, differences in mapping methodologies and the impact of reduced calcification due to global trends in coral reef ecological decline and changing oceanic physical conditions warrant further research. The novel method proposed in this study to characterise the geomorphology of reef types based on classification trees provides an objective and repeatable data-driven approach that combined with regional census-based approaches has the potential to be adapted and transferred to different coral reef regions, depicting a more accurate picture of interactions between reef ecology and geomorphology.