Engineers and scientists apply numerical models to understand coastal systems, predict coastal morphological changes and improve management plans. However, bathymetry data, which are required by model validations, are limited in time and spatial scales due to the high cost of ground surveys. Nevertheless, the development of remote sensing, especially the launch of Google Earth Engine (GEE), provides an opportunity to fill the gaps of data. The objective of this PhD work is to derive large-scale and frequent bathymetry data from satellite imagery with the help of GEE. These data will then be applied to illustrate historical coastal evolution trends, validate numerical models and improve the model performance.

Funding: UQ Research Training Program

Advisors: Dr Daniel Harris, Professor Stuart Phinn

Project members

Yongjing MAO

PhD Candidate