In 2014, UniDive (The University of Queensland Underwater Club) conducted an ecological assessment of the Point Lookout Dive sites for comparison with similar surveys conducted in 2001 - the PLEA project. Involvement in the project was voluntary. Members of UniDive who were marine experts conducted training for other club members who had no, or limited, experience in identifying marine organisms and mapping habitats. Since the 2001 detailed baseline study, no similar seasonal survey has been conducted. The 2014 data is particularly important given that numerous changes have taken place in relation to the management of, and potential impacts on, these reef sites. In 2009, Moreton Bay Marine Park was re-zoned, and Flat Rock was converted to a marine national park zone (Green zone) with no fishing or anchoring. In 2012, four permanent moorings were installed at Flat Rock. Additionally, the entire area was exposed to the potential effects of the 2011 and 2013 Queensland floods, including flood plumes which carried large quantities of sediment into Moreton Bay and surrounding waters. The population of South East Queensland has increased from 2.49 million in 2001 to 3.18 million in 2011 (BITRE, 2013). This rapidly expanding coastal population has increased the frequency and intensity of both commercial and recreational activities around Point Lookout dive sites (EPA 2008). Habitats were mapped using a combination of towed GPS photo transects, aerial photography and expert knowledge. This data provides georeferenced information regarding the major features of each of the Point Lookout Dive Sites.

An object based image analysis approach (OBIA) was used to create a habitat map of Lizard Island reef, Queensland. Georeferenced dive and snorkel photo-transect surveys were conducted at different locations surrounding Lizard Island. Dominant benthic or substrate cover type was assigned to each photo by placing 24 points random over each image. Each point was then assigned a dominant cover type using a benthic cover type classification scheme containing nine first-level categories - seagrass high (>=70%), seagrass moderate (40-70%), seagrass low (<= 30%), coral, reef matrix, algae, rubble, rock and sand. The OBIA class assignment followed a hierarchical assignment based on membership rules with levels for "reef", "geomorphic zone" and "benthic community" (above). This record contains a snapshot of the data taken for use in Seamap Australia (a national benthic habitat map; https://seamapaustralia.org). View the original record at: https://doi.pangaea.de/10.1594/PANGAEA.864209

The MOU74 Box, off the northwest Australian coastline, is an area of approximately 50,000 sq. km within the Australian Fishing Zone. It contains five large, shallow reef systems (less than 15 m deep) ranging in size from 227 sq. km (Ashmore Reef) to 4.5 sq. km (Browse Island). They total approximately 560 sq. km in area. Immediately north of the MOU74 Box within the Australian Fishing Zone (Little Area A) is another shallow reef, Hibernia Reef. In addition to the shallow reefs, there is approximately 925 sq. km of shoal areas (15 to 50 m deep) within the MOU74 Box and 301 sq. km of shoal areas in Little Area A. The reefs and shoals support populations of sedentary reef resources including several species of holothurians (beche-de-mer, sea cucumbers) and trochus, as well as reef-associated fin-fish and sharks. These resources have been fished for many years by Indonesian fishers. Ashmore Reef was declared a Marine Nature Reserve in 1983, banning the removal of fauna and flora to a depth of 50 m. The remaining reefs in the area are under continued, and probably increasing, fishing pressure. The marine resources of the MOU74 Box are managed by the Australian Government. Under the terms of a memorandum of understanding (MOU) between the Australian and Indonesian governments, continued traditional fishing by Indonesian fishing vessels is allowed, principally for sedentary resources such as beche-de-mer (trepang) and trochus, but also fin-fish and reef shark. Apart from limited catch data collected by surveillance and regulatory authorities, little is known about the catch of the Indonesian fishers and the effects of fishing on the target species. There are concerns that the current level of fishing may be unsustainable. In September and October 1998, CSIRO Division of Marine Resources surveyed the shallow reefs (0-15 m deep) and shoal areas (15-50 m deep) of the MOU74 Box area and Little Area A to the north. Its purpose was to assess the status of the reef resources in the area, and the environment that supports them. Fieldwork for the survey was completed on 10 October 1998. Overall, the sedentary marine living resources on the shallow reefs were heavily depleted with the high-value species over-exploited and the lower value species probably either fully or over-exploited. Despite the low density, there appears to be a sustained fishing effort by Indonesian fishers in the area. A drastic reduction in effort would be required to allow for a recovery of the higher value species, and to protect other species from severe depletion. The exception is Ashmore Reef, where there were significant populations of most target species. However, there is most likely some illegal fishing occurring on Ashmore Reef and there is clear evidence of exploitation of at least the high-value resources. The nature of these fisheries and the depleted state of the other reefs in the MOU74 Box suggests that the remaining resources on Ashmore Reef could be quickly depleted if the protection currently given to the reef is not maintained and possibly enhanced. For many reasons, including the potential for recruitment of larvae to depleted reefs, it is important that these populations are protected. Year round protection of the resources on Ashmore Reef should be considered. This record describes the following survey data for the Timor MOU74 Box: • Classified satellite habitat map for Scott and Seringapatam Reefs. • Classified satellite habitat map for Ashmore, Hibernia and Cartier Reefs.

The aim of this study was to create a seagrass presence/absence map for the optically complex waters of Moreton Bay. The capability to map seagrass meadows in waters of varying clarity using a consistent and repeatable method is an invaluable resource for conservation and management of seagrass regionally and globally. The map was created using an adaptation of a Google Earth Engine (GEE) cloud processing and machine learning algorithm which for seagrass, utilized citizen science spot check field data, Landsat 8 OLI imagery pulled directly from GEE, a bathymetry layer (30 m), slope derived from depth and a coral mask. This dataset consists of a shapefile that shows seagrass presence (≥ 25 % cover) and substrate mapped simultaneously for the turbid waters of the Western Bay coastline and the optically clear waters of the Eastern Banks, Moreton Bay, Queensland, Australia. This record contains a snapshot of the data taken for use in Seamap Australia (a national benthic habitat map; https://seamapaustralia.org). View the original record at: https://doi.pangaea.de/10.1594/PANGAEA.937501

Coastal features within and adjacent to the Great Barrier Reef World Heritage area (such as the Queensland Mainland and Islands, Indicative Reef boundaries and Rocks.). Major coral cay features,major and other coral reef structures (as defined by the reef shoal edge) and tidal, drying or emergent reef areas within the Great Barrier Reef World Heritage Area.

This record describes data collected for the 2013 report "Synthesis of seagrass mapping studies conducted by the Water Science Branch of the Department of Water", and collected more recently by the Department of Water and Environmental Regulation ongoing monitoring. This project record provides linkage to each of metadata records describing seagrass data collected from the 11 study areas: Beaufort Inlet (2009), Hardy Inlet (2008, 2018, 2020), Irwin Inlet (2009), Leschenault Estuary (2009, 2015, 2016, 2017, 2018 2019. 2020), Oyster Harbour (1988, 1996, 2006, 2019), Princess Royal Harbour (1996, 2006) Stokes Inlet (2009), Swan Canning (2011), Walpole Nornalup Inlets (2009), Wellstead Estuary (2009), Wilson Inlet (2007, 2008). To access the source datasets from each study site/sampling occasion in their original (unaggregated) form, see child records linked to this parent record.

An environmental classification developed in conjunction with the NSW Marine Parks Authority Research Committee. For more information see: Breen D.A. and R.P. Avery. (2002). Broad-scale biodiversity assessment of the Manning Shelf marine bioregion. Draft final report for the NSW Marine Parks Authority. Copies of the report may be borrowed from the library: Environment Australia, GPO Box 787, Canberra ACT 2601 Australia. This coverage is intended for used in regional level marine conservation assessment. It was prepared using very low cost techniques (ie. unrectified API) and should not be relied upon for navigation purposes. This represents an historic dataset providing transparency on the 2002 marine park systematic planning process. This product is one of three related datasets used in the assessment process: "NSW Ocean Ecosystems 2002", "NSW Estuarine Ecosystems 2002" & "NSW Marine Habitats 2002" ----------------------------------- This record describes classes for each of the five major estuary ecosystems. The full study also describes the environmental classification of the four ocean ocean ecosystems classified by depth, and nine habitat surrogates.

A supervised classification was applied to a Landsat TM5 image. This image was acquired on the 8th August 2004, 15 minutes after low tide. The image classification was applied on areas of clear waters up to three metres depth and for exposed regions of Moreton Bay. Field validation data was collected at 2800 survey sites by UQ, 18 Seagrass-Watch sites and 60 Port of Brisbane Corporation survey sites. GPS referenced field data were used as training areas for the image classification process. For this training the substrate DN signatures were extracted from the Landsat 5 TM image for field survey locations of known substrate cover, enabling a characteristic "spectral reflectance signature" to be defined for each target. The Landsat TM image, containing only those pixels in water < 3.0m deep, was then subject to minimum distance to means algorithm to group pixels with similar DN signatures (assumed to correspond to the different substrata). This process enabled each pixel to be assigned a label of either seagrass cover (0, 1-25 %, 25-50 %, 50-75 % and 75-100 %). The resulting raster data was then converted into a vector polygon file. Species information was added based on the field data and expert knowledge. Both polygon files were joined by overlaying features of remote sensing files with the EHMP field data to produce an output theme that contains the attributes and full extent of both themes. If polygons of remote sensing were within polygons of field data the assumption was made that the remote sensing polygon was showing more detail and the underlying field polygon was deleted.

A supervised classification was applied to a Landsat TM5 image. This image was acquired 9:40 am, on the 27th July 2011 (5.14 am low tide at Brisbane Bar). The image classification was applied on areas of clear waters up to three metres depth and for exposed regions of Moreton Bay. Field validation data was collected at 4797 survey sites by UQ. GPS referenced field data were used as training areas for the image classification process. For this training the substrate DN signatures were extracted from the Landsat 5 TM image for field survey locations of known substrate cover, enabling a characteristic "spectral reflectance signature" to be defined for each target. The Landsat TM image, containing only those pixels in water < 3.0m deep, was then subject to minimum distance to means algorithm to group pixels with similar DN signatures (assumed to correspond to the different substrata). This process enabled each pixel to be assigned a label of either seagrass cover (0, 1-25 %, 25-50 %, 50-75 % and 75-100 %). The resulting raster data was then converted into a vector polygon file. Species information was added based on the field data and expert knowledge. Both polygon files were joined by overlaying features of remote sensing files with the EHMP field data to produce an output theme that contains the attributes and full extent of both themes. If polygons of remote sensing were within polygons of field data the assumption was made that the remote sensing polygon was showing more detail and the underlying field polygon was deleted.