Rugulopteryx okamurae is a species of brown macroalgae belonging to the Dictyotaceae family and native to the north-western Pacific. As an Invasive Alien Species (IAS), it was first detected in the Strait of Gibraltar in 2015. Since then, R. okamurae has been spreading rapidly through the submerged euphotic zone, colonizing from 0 to 50 m depth and generating substantial economic and environmental impacts on the Andalusian coasts (southern Spain). More than 40% of marine IAS in the European Union (EU) are macroalgae, representing one of the main threats to biodiversity and ecosystem functioning in coastal habitats. This study presents a monitoring pilot of beached R. okamurae and fresh R. okamurae down to 5 m depth in Tarifa (Cadiz, Spain), combining multispectral remote sensing data collected by sensors on-board Unmanned Aerial Vehicles (UAVs) and satellites, and how this information can be used to support decision-making and policy. We used an UAV flight carried out at Bolonia beach (Tarifa, Spain) on 1(st) July 2021 and Sentinel-2 (S2) and Landsat-8 (L8) image acquisitions close to the drone flight date. In situ data were also measured on the same date of the flight, and they were used to train the supervised classification Super Vector Machine (SVM) method based on the spectral information obtained for each substrate cover. The results obtained show how multispectral images allow the detection of beached R. okamurae, and the classification accuracy for water, land vegetation, sand and R. okamurae depending on the image resolution (8.3 cm/pixel for UAV flight, 10 m/pixel for S2 and 30 m/pixel for L8). While the UAV imagery precisely delimited the area occupied by this macroalgae, satellite data were capable of detecting its presence, and able to generate early warnings. This study demonstrates the usefulness of multispectral remote sensing techniques to be incorporated in continuous monitoring programmes of the marine IAS R. okamurae in coastal areas. This information is also key to supporting regional, national and European policies in order to adapt strategic management of invasive marine macrophytes.

Monitoring the marine invasive alien species Rugulopteryx okamurae using unmanned aerial vehicles and satellites

Zoffoli Maria Laura;
2022

Abstract

Rugulopteryx okamurae is a species of brown macroalgae belonging to the Dictyotaceae family and native to the north-western Pacific. As an Invasive Alien Species (IAS), it was first detected in the Strait of Gibraltar in 2015. Since then, R. okamurae has been spreading rapidly through the submerged euphotic zone, colonizing from 0 to 50 m depth and generating substantial economic and environmental impacts on the Andalusian coasts (southern Spain). More than 40% of marine IAS in the European Union (EU) are macroalgae, representing one of the main threats to biodiversity and ecosystem functioning in coastal habitats. This study presents a monitoring pilot of beached R. okamurae and fresh R. okamurae down to 5 m depth in Tarifa (Cadiz, Spain), combining multispectral remote sensing data collected by sensors on-board Unmanned Aerial Vehicles (UAVs) and satellites, and how this information can be used to support decision-making and policy. We used an UAV flight carried out at Bolonia beach (Tarifa, Spain) on 1(st) July 2021 and Sentinel-2 (S2) and Landsat-8 (L8) image acquisitions close to the drone flight date. In situ data were also measured on the same date of the flight, and they were used to train the supervised classification Super Vector Machine (SVM) method based on the spectral information obtained for each substrate cover. The results obtained show how multispectral images allow the detection of beached R. okamurae, and the classification accuracy for water, land vegetation, sand and R. okamurae depending on the image resolution (8.3 cm/pixel for UAV flight, 10 m/pixel for S2 and 30 m/pixel for L8). While the UAV imagery precisely delimited the area occupied by this macroalgae, satellite data were capable of detecting its presence, and able to generate early warnings. This study demonstrates the usefulness of multispectral remote sensing techniques to be incorporated in continuous monitoring programmes of the marine IAS R. okamurae in coastal areas. This information is also key to supporting regional, national and European policies in order to adapt strategic management of invasive marine macrophytes.
2022
invasive macroalgae
algae monitoring
multispectral sensor
hyperspectral sensor
UAV
Sentinel-2
Landsat-8
machine learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/459584
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