The ability to detect, measure and monitor change in coastal and marine environments can assist in both informing management decision processes and evaluating the results of management interventions. Change detection utilising satellite data requires robust time-series data at temporal and spatial scales that can provide context for meaningful interpretations of coastal and marine ecosystem processes. Previously, this analysis has employed time consuming methods that hampered the efficient extraction of key information on environmental change and trends.

The recently developed Australian Geoscience Data Cube (AGDC) provides a quantum step forward in our ability to utilise satellite data for environmental monitoring. The AGDC provides a platform for efficient processing and analysis of these data, enabling quantitative information to be extracted from the full 28-year time series of the Landsat data archive. Also, this approach can be applied to a wide range of current and future satellite data streams (e.g. Sentinel series of satellites) to provide rapid, robust environmental monitoring.
We have developed a flexible diagnostic change detection tool, able to extract change events from classified variables derived from 28 years of Landsat data in the AGDC. In this report we describe how we apply the algorithm to a water detection problem, and show the broadscale application using examples of coastal change and estuarine drying events in Moreton Bay and the Murray Mouth and Lower Lakes. We also introduce tools which can then be used for further analysis of the detected change events.

The algorithm is flexible enough to be applied to a range of variables in the coastal zone, and we discuss further applications and potential future linkages to extend this work for the examination of important ecological communities.

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