benthic habitat
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In 2016-2017, UniDive (The University of Queensland Underwater Club) conducted an ecological assessment of the Flinders Reef Dive sites - the FREA 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. Habitats were mapped using a combination of towed GPS photo transects, WorldView-2 satellite imagery and expert knowledge. This data provides georeferenced information regarding the major features of each of the Flinders Reef Dive Sites.
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The study involved the collection of field data and acquisitioning of satellite imagery to create a map that presents a benthic inventory of reefal habitat areas within Moreton Bay. Mapping was guided by the most recent reef map (Queensland Environmental Protection Agency, 2004), the new field data, local knowledge and/or visual interpretation of high spatial resolution satellite imagery. The inventories for each reefal area were based on georeferenced spot check field data collected by volunteer teams in 2015 and 2016 (n=610). This field data was overlayed on high spatial resolution ZY-3 satellite imagery (5 m x 5 m pixels) captured in June 2014. Polygons were manually digitised around reefal areas by an expert from the Remote Sensing Research Centre using visual interpretation of the texture and colour of the pixels in the satellite imagery, as related to water depth, field data and local field knowledge. Polygons were subsequently assigned one of three categories (Coral on reef matrix, Soft Coral on Sand/Rubble, and, Algae on sand/rubble). The project was a collaborative citizen science project between Reef Check Australia, The University of Queensland Remote Sensing Research Centre and Healthy Waterways to collect benthic inventories for eight key subtropical reefal areas in Central Moreton Bay - Mud, Saint Helena, Green, King, Macleay, Goat, and Peel Islands, and, Myora Reef.
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Surveying habitats critical to the survival of grey nurse sharks in South-East Queensland has mapped critical habitats, gathered species inventories and developed protocols for ecological monitoring of critical habitats in southern Queensland. This information has assisted stakeholders with habitat definition and effective management. In 2002 members of UniDive applied successfully for World Wide Fund for Nature, Threatened Species Network funds to map the critical Grey Nurse Shark Habitats in south east Queensland. UniDive members used the funding to survey, from the boats of local dive operators, Wolf Rock at Double Island Point, Gotham, Cherub's Cave, Henderson's Rock and China Wall at North Moreton and Flat Rock at Point Look Out during 2002 and 2003. These sites are situated along the south east Queensland coast and are known to be key Grey Nurse Shark aggregation sites. During the project UniDive members were trained in mapping and survey techniques that include identification of fish, invertebrates and substrate types. Training was conducted by experts from the University of Queensland (Centre of Marine Studies, Biophysical Remote Sensing) and the Queensland Parks and Wildlife Service who are also UniDive members. The monitoring methods (see methods) are based upon results of the UniDive Coastcare project from 2002, the international established Reef Check program and research conducted by Biophysical Remote Sensing and the Centre of Marine Studies. This record describes the digitised habitat features for Wolf Rock. View the original metadata record at https://doi.pangaea.de/10.1594/PANGAEA.864211 for the full data collection.
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Seagrass meadow extent and meadow-scape was mapped using two alternative approaches at Green Island, a reef clear water habitat, in the Cairns section of the Great Barrier Reef, in November 2020. Approach 1 included mapping seagrass meadow-scape using imagery captured during low spring tides with a DJI Mavic 2 Pro UAV at an altitude of 100 m, with a resolution of 2.45cm/pixel. Approach 2 used PlanetScope Dove imagery captured on 05 November 2020 coinciding as close as possible to the field-surveys from 25 to 27 November 2020, with 3.7 m x 3.7 m pixels (nadir viewing) acquired from the PlanetScope archive. This record describes meadow extent data collected using Approach 2 (PlanetScope imagery). View the original metadata record at https://doi.pangaea.de/10.1594/PANGAEA.946605 for the full data collection.
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The Seamap Australia National Benthic Habitat Layer (NBHL) is a nationally synthesised database of seafloor habitat data, classified according to the Seamap Australia National Benthic Habitat Classification Scheme (https://vocabs.ardc.edu.au/viewById/129). In generating the Seamap Australia NBHL, datasets from data providers around Australia are collated and centrally hosted by IMAS (UTAS). Through time, some datasets become superseded by newer, more accurate data for the same region (improved data collection or processing methodology). This record aggregates all habitat datasets that have been collated as part of the Seamap Australia project, but are no longer considered the most accurate/up to date habitat for a particular region and have been superseded by another product. The parent record for the Seamap Australia NBHL provides an aggregation point for all "current" habitat datasets: https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/4739e4b0-4dba-4ec5-b658-02c09f27ab9a
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Mangroves are a globally important ecosystem subject to significant anthropogenic and climate impacts. Tidally submerged forests and those that occur in arid and semi-arid regions are particularly susceptible to sea level rise or are growing at the margins of their their ecophysiological limits. The spatial extent of these types of mangroves over broad scales are typically poorly documented as their structural and environmental characteristics make them difficult to detect using remote sensing models. This study utilised the entire Landsat 8 satellite collection between January 2014 and June 2021. A new cloud-based time-series method was used that accounts for tidal variance in detecting mangrove areas that are periodically inundated and have historically been difficult to detect with traditional remote sensing methods. A habitat area model was derived for remote North-western Australia and detected an additional 32% (76,048 hectares) of mangroves that were previously undocumented. The accuracy of the model was assessed within the distinct geomorphic zones of the region through visual validation from high-resolution imagery. See accompanying report for full methodology: Hickey, S.M.; Radford, B. Turning the Tide on Mapping Marginal Mangroves with Multi-Dimensional Space–Time Remote Sensing. Remote Sens. 2022, 14, x. https://doi.org/10.3390/rs14143365