School of Geography, Planning and Environmental Managementii Seagrass is ecologically important submerged aquatic vegetation that serves as one of the major sources of primary production in shallow waters. Despite their high productivity, seagrass habitats are under threat from anthropogenic and global climate change influences and therefore understanding their dynamics and environmental controls is essential. It is fortunate that seagrasses have distinct optical signatures observable from space by satellite sensors, allowing mapping and monitoring of seagrass habitats in spatially continuous and multi-temporal modes. Light availability, along with seagrass leaf area index (LAI), biomass and productivity are important parameters for characterising the condition of seagrass habitat. The aim of this research was to investigate these parameters by integrating field measurement, laboratory analysis and remote sensing to estimate seagrass light climate, LAI, biomass and gross primary productivity. The research addressed the following three objectives with investigations based in a section of subtropical seagrass in Moreton Bay, Australia: (a) to investigate light quality and quantity in the seagrass environment using in situ optical measurements and remote sensing, (b) to map seagrass LAI and biomass using WorldView-2 satellite data, and (c) to estimate seagrass gross primary productivity using a combination of models and remote sensing data.
AbstractTo address research objective one, light quality was assessed using daily water optical measurements at two sites in Moreton Bay. Light quantity was investigated by estimating the seagrass surface area from satellite image-based photosynthetically active radiation (PAR), photosynthetically utilised radiation (PUR) and percentage of light relative to surface light (% SI) parameters. The result showed green light dominated the light climate at the seagrass meadows of the measurement site. A blue light limitation of seagrass in Wanga Wallen bank was indicated, as there was a rapid decrease in blue light contributions relative to green and red light, moving from the more dense inshore seagrass site to the less-dense offshore seagrass site. The majority of the seagrass surface area in the areas assessed was successfully mapped based on satellite image-based light quantity parameters of PAR, PUR and % SI, providing insights into the interaction between light parameters and the spatial distribution of seagrass.The second objective developed a method to estimate seagrass LAI and biomass from image data by first examining the relationship between seagrass LAI and biomass, and reflectance using in situ data. Regression models were then developed and the most accurate one was applied to two highspatial resolution multi-spectral WorldView-2 image data to estimate seagrass LAI and biomass from satellite image reflectance. Analysis using in situ data revealed strong correlation between the green band and LAI but weak correlation between reflectance and biomass. Significant iii relatio...