How a Large-scale Satellite-derived Dataset Can be Used to Investigate Statistically Robust Trends?

A new paper is just published in the Journal of Estuarine, Coastal and Shelf Science. The paper is entitled: "Mapping spatial variability in shoreline change hotspots from satellite data; a case study in southeast Australia".

Konlechner et al. (2020)


This study demonstrates how a large-scale satellite-derived dataset can be used to investigate statistically robust trends in shoreline position over a 31-year period from 1987 to 2017, at a regional scale.


Regional patterns of shoreline behavior are important for resolving consistent or, alternatively, dissimilar patterns of past shoreline change. Such patterns are best explored using temporally frequent and spatially extensive datasets. Here we analyze satellite-derived shorelines to identify spatial patterns of hotspots of coastline change on the wave-exposed coast of Victoria in south-east Australia.


Coasts located at the entrances to large tidal inlets have shown the greatest change. The association of hotspots with embayed sandy beaches and adjacent to headlands points to the importance of geological control on shoreline behavior. Consistent with other regional scale studies of shoreline change, this study found little regional coherence in shoreline behavior. Instead change is predominately attributed to local factors such as the geological framework of the coast, localized hydrodynamic conditions and anthropogenic influences.


This project is funded through The Earth Systems and Climate Change Hub of the Australian Government's National Environmental Science Program, The Victorian Coastal Monitoring Program, and the Victorian Government's Department of Environment, Water, Land and Planning.


This study was led by Teresa M. Konlechner (from the University of Melbourne), and the DU Marine Mapping Group members Rafael C. Carvalho and Daniel Ierodiaconou contributed to the publication.

Congrats to all the authors!


To read the full publication, click here.

Last edited on the April 1st, 2021.

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