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  • This record provides an overview of the scope and research output of NESP Marine Biodiversity Hub Project C3 - "Change detection and monitoring of key marine and coastal environments – application of the Australian Geoscience Data Cube". For specific data outputs from this project, please see child records associated with this metadata. -------------------- This project aims at leveraging the extensive time-series of earth observation image data in the Australian Geoscience Data Cube (AGDC) by developing change detection algorithms to analyse key environmental parameters in the coastal and marine zone. Spatial information produced by this project can inform management decisions, and assist in evaluating management action outcomes, by providing a quantifiable measure of historical change and ongoing monitoring and change detection capabilities. In Phase 1 of this project we aim to demonstrate the capability of using the AGDC through the development of an inter-tidal zone change detection algorithm and data set, with a view to developing and implementing an expanded range of stakeholder targeted algorithms to inform decision making processes in Phase 2. Planned Outputs • Progress Report • Demonstrator summary Report • Data Products (GIS maps and data, delivered from the GA website as a web service) • Marine Biodiversity Hub article • Pesentation at the Australian Marine Science Association Conference.

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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.