The project seeks to assess water quality through a combination of multispectral imagery and cloud data processing. With global temperature increase, sea-level rise and water quality degradation, the marine environment has been impacted severely over the last few decades.

Remote sensing applications have been proven successful in the past to map aquatic environments. However, the number of those studies are limited due to lack of expertise on how to link spatial and spectral information to the field data. The process also comes with challenges due to the harsh environment and related cost to manually survey each study area. Analysing and understanding the physical and chemical characteristics of the water column through aerial platforms will be one of the main focuses of the research.

The project will involve collecting in-situ data using smart buoys to analyse the trend throughout the study period and link those to assessments of chlorophyll from high resolution unmanned aerial vehicle (multispectral drone) and satellite imagery. Calculating phytoplankton abundance will also provide insights towards the food resources for oyster farms. The overall outcome is to design a methodology and deliver a cost-effective approach to collect continuous data to achieve a real-time analysis of water quality monitoring using big data for aquaculture operations.