Deriving Beach Grain Size from Satellite Imagery
A multimethod approach for deriving intertidal beach slopes and sediment grain sizes for different coastal environments
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Abstract
The world's coasts are at risk: an estimated 24% of the world's beaches are eroding. Extreme events such as storms continuously threaten the coastal region and pose a serious risk of coastal flooding. Under the influence of climate change, the seaward pressures are only expected to increase. Sea level rise is accelerating, storm intensities and frequencies will increase, and precipitation will become more extreme. At the same time human pressures such as coastal tourism and rapid urbanisation impose stresses to the coastal system. An estimated 23% of the world's population lives in the coastal zone where natural hazards cause a direct flood risk. Protection of the coastal region becomes more and more relevant. Coastal management strategies need to take the local circumstances into account. Therefore, a good understanding of the coastal zone is needed, but especially in data-poor regions there is a lack of geomorphological information such as slope and grain size. This thesis presents an alternative approach for acquiring this data with the ability to run on a global scale using remote sensing technologies. Remote sensing, satellite imagery in particular, has proven to be a promising new technology to monitor coastal regions at large temporal and spatial scales and is applied here to determine coastal slopes and sediment sizes. The approach has shown promising results and paves the way for an estimate of the grain size at beaches around the world. Some hurdles remain to be taken but the ability to do measurements of coasts around the globe using satellite imagery will change the way we study our coasts forever. This research is a major step forwards in the global monitoring of the world's coast, but only shows the beginning of the endless possibilities.