Remote sensing of coastal algal blooms using unmanned aerial vehicles (UAVs)

Abstract

The explosive growth of phytoplankton under favorable conditions in subtropical coastal waters can lead to water discolouration and massive fish kills. Traditional water quality monitoring relies on manual field sampling and laboratory analysis of chlorophyll-a (Chl-a) concentration, which is resources intensive and time consuming. The cloudy weather of Hong Kong also precludes using satellite images for algal blooms monitoring. This study for the first time demonstrates the use of an Unmanned Aerial Vehicle (UAVs) to quantitatively map surface water Chl-a distribution in coastal waters from a low altitude. An estimation model for Chl-a concentration from visible images taken by a digital camera on a UAV has been developed and validated against one-year field data. The cost-effective and robust technology is able to map the spatial and temporal variations of Chl-a concentration during an algal bloom. The proposed method offers a useful complement to traditional field monitoring for fisheries management.