Mayya Podsosonnaya1, Maria J. Schreider2
1Central Coast Council, Wyong, NSW, Australia, 2258, 2School of Environmental and Life Sciences, University of Newcastle, NSW, Australia, 2258
Correspondence: Maria J. Schreider, Maria.Schreider@newcastle.edu.au
The excessive growth of macroalgae, or blooms, is a world-wide phenomenon in estuarine habitats and may significantly impact the entire ecosystem by inducing hypoxia, smothering seagrasses, and ultimately leading to the loss of biodiversity. Understanding conditions under which blooms occur requires observations of their temporal and spatial dynamics. One of the challenges of effective monitoring is developing reliable and non-expensive techniques of measuring algal biomass and/or the area of the blooms. The use of satellite images is an effective non-invasive method of observation allowing monitoring at large spatial scales.
In this study, we describe a newly constructed Floating Macro Algae Index for detection of algal blooms using satellite images and compare its accuracy with previously developed algorithms for detecting aquatic vegetation via remote sensing. The detection of algal blooms by the indices using the red-edge effect of the chlorophyll (SAI, FLH, SABI, VB-FAH) result in the most accurate results as verified by algal sampling using drones during the algal bloom at Tuggerah Lakes in South-East Australia.
All studied indices can be divided into two groups. Rough estimation algorithms (TVI, NDVI) determine the presence or absence of algal mats whereas the fine gradation ones (FAI, NDAI, MCI, ABDI) provide a measure of relative quantity of the chlorophyll present. For smaller water bodies such as estuaries the resolution of the sensor is a limiting factor. With further improvements of satellite sensors, FMAI can potentially use a wider range of reflected spectra and allow large scale observations of algal blooms in multiple estuaries.