Using a UAV-Mounted Multispectral Camera for the Monitoring of Marine Macrophytes

Marine macrophytes constitute one of the most productive ecosystems on the planet, as well as one of the most threatened by anthropogenic activities and climate change. Their monitoring is therefore essential, which has experienced a fast methodological evolution in recent years, from traditional in situ sampling to the use of satellite remote sensing, and subsequently by sensors mounted on unmanned aerial vehicles (UAV). This study aims to advance the monitoring of these ecosystems through the use of a UAV equipped with a 10-band multispectral camera, using different algorithms [i.e., maximum likelihood classifier (MLC), minimum distance classifier (MDC), and spectral angle classifier (SAC)], and using the Bay of Cadiz Natural Park (southern Spain) as a case of study. The results obtained with MLC confirm the suitability of this technique for detecting and differentiating seagrass meadows in a range of 0-2 m depth and the efficiency of this tool for studying and monitoring marine macrophytes in coastal areas. We inferred the existence of a cover of 25452 m(2) of Cymodocea nodosa, and macroalgae species such as Caulerpa prolifera, covering 22172 m(2) of Santibanez (inner Bay of Cadiz).

Automated summary

This study utilized a UAV equipped with a 10-band multispectral camera and different algorithms to monitor marine macrophytes in the Bay of Cadiz Natural Park. The results confirmed the efficiency of the MLC technique in detecting seagrass meadows and studying marine macrophytes in coastal areas. The study inferred the presence of specific marine plant species within the study area.