Machine learning for AquaWatch WQ parameter mapping: Dynamic Machine Learning Model to Estimate Water Quality Parameters in Complex Coastal Waters using Satellite Ocean Colour Observations

This project aims to demonstrate the potential of machine learning (ML)-based algorithms and models in decoupling the complex optical signature in coastal waters and deriving water quality parameters in coastal waters from satellite observations. Through collaborating with CSIRO researchers and our industry partners, this project will investigate the potential of new machine learning approaches in predicting water quality parameters through fusing data from insitu water quality sensors and satellite observational data. We will develop a machine learning model to invert the remote sensing reflectance signal and to derive WQ parameters.

The result will be a machine learning-based modelling tool to improve the water quality products and thus enable better coastal ecosystem management. New ML-based remote sensing products from this project will help end users in the Cockburn Sound and Moreton Bay regions improve their coastal monitoring and management practices.


Project Leader:
Professor Wei Xiang, La Trobe University