Algal blooms resulted from the explosive growth of phytoplankton under favorable conditions can lead to water discoloration, beach closure and even fish kill. Traditional algal blooms monitoring in Hong Kong relies on field sampling and laboratory analysis of chlorophyll-a (Chl-a) concentration, which is resources intensive and time consuming. The cloudy weather of Hong Kong throughout the year also hampers the use of satellite images for remote sensing of water quality and monitoring of algal blooms.

Unmanned Aerial Vehicle (UAVs) technology is a novel method for algal bloom monitoring in small scale waters from lower altitudes unaffected by cloud coverage. This study for the first time demonstrates the feasibility of using an Unmanned Aerial Vehicle (UAVs) to quantitatively...[ Read more ]

Algal blooms resulted from the explosive growth of phytoplankton under favorable conditions can lead to water discoloration, beach closure and even fish kill. Traditional algal blooms monitoring in Hong Kong relies on field sampling and laboratory analysis of chlorophyll-a (Chl-a) concentration, which is resources intensive and time consuming. The cloudy weather of Hong Kong throughout the year also hampers the use of satellite images for remote sensing of water quality and monitoring of algal blooms.

Unmanned Aerial Vehicle (UAVs) technology is a novel method for algal bloom monitoring in small scale waters from lower altitudes unaffected by cloud coverage. This study for the first time demonstrates the feasibility of using an Unmanned Aerial Vehicle (UAVs) to quantitatively map surface water chlorophyll-a concentration distribution in coastal waters and an estimation model for chlorophyll-a concentration from visible images captured by a low cost UAV has been successfully developed and validated against one-year field data covering different seasons and weather conditions. The cost-effective and robust UAV-based technology is able to map the spatial and temporal variation of chlorophyll-a concentration in coastal waters during an algal bloom. The proposed method is also a promising tool to complement the traditional field sampling and algal bloom monitoring for fisheries management.