Poster Presentation 2024 Australian Marine Sciences Association Annual Meeting combined with NZMSS

Enhancing Aquaculture Water Quality Monitoring: A Multi-satellite Approach for Mapping Near-coastal Chlorophyll-a Concentration in Tasmania, Australia (#657)

Avik Nandy 1 2 , Stuart Phinn 2 , Alistair Grinham 1 , Simon Albert 1
  1. School of Civil Engineering , The University of Queensland, Brisbane, Queensland, Australia
  2. School of the Environment , The University of Queensland, Brisbane, Queensland, Australia

Aquaculture is crucial for global food security and economic prosperity. Monitoring water quality, particularly with Chlorophyll-a levels serving as a crucial indicator, is essential for maintaining sustainable and low-impact operations. Conventional in-situ monitoring methods, utilizing manual deployments and automated instruments, are constrained in coverage, time, and variables, especially in remote areas. Integrating remote sensing technologies with in-situ measurements offers potential solutions for accurate, efficient, and continuous mapping of surface water characteristics on local, regional, and global scales. Although existing ocean-color satellite sensors can map Chlorophyll-a concentration, their spatial resolution is limiting, particularly in near-coastal aquaculture zones. This study employs medium to high-spatial resolution sensors, demonstrating their potential for future monitoring applications. By correlating in-situ survey data with multi-spectral satellite sensor data, the study refines satellite estimates of Chlorophyll-a concentration, aiding evidence-based decision-making for sustainable aquaculture practices. Using Sentinel-2 and Landsat-8/9, the study maps surface Chlorophyll-a concentration in various sites across Tasmania, revealing strong correlations between in-situ and satellite-derived data. Initial results suggest that this approach could enable proactive management strategies, early detection of harmful algal blooms, and monitoring beyond individual farm boundaries. The proposed methodology addresses spatial resolution limitations and underscores the effectiveness of remote sensing in enhancing aquaculture operations.