Evaluating UAV‐based multispectral imagery for mapping an intertidal seagrass environment

Eylem Elma*, Rachel Gaulton, Thomas R. Chudley, Catherine L. Scott, Holly K. East, Hannah Westoby, Clare Fitzsimmons

*Corresponding author for this work

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Abstract

Worldwide seagrass habitats are under severe anthropogenic threat. In the United Kingdom (UK), the health of habitats of the widely distributed Zostera species is particularly threatened by eutrophication that can lead to detrimental macroalgae overgrowth. To manage and conserve seagrass habitats, effective monitoring tools are required.

We use an off‐the‐shelf consumer‐grade multispectral (RGB, red edge, and near‐infrared) camera mounted on an unoccupied aerial vehicle (UAV) to map an intertidal multispecies seagrass environment in Lindisfarne National Nature Reserve, Northumberland, UK.

Field surveys were undertaken of three seagrass areas, including those dominated by Zostera noltii , Zostera marina and macroalgae. Using the Maximum Likelihood Classifier (MLC), results indicated an overall accuracy (OA) between 84% and 91% across classified habitat maps. As expected, the red edge and near‐infrared bands offered an advantage beyond RGB imagery to discriminate between the vegetation types for accurate habitat mapping.

Our research provides a foundation for accurately mapping a complex intertidal seagrass environment through the utilisation of an off‐the‐shelf multispectral UAV. The study may aid the implementation and development of effective monitoring programmes for the management of Zostera spp. decline and macroalgae proliferation to prevent seagrass degradation and conserve these valuable yet fragile ecosystems.
Original languageEnglish
Article numbere4230
Number of pages14
JournalAquatic Conservation: Marine and Freshwater Ecosystems
Volume34
Issue number8
Early online date27 Aug 2024
DOIs
Publication statusPublished - Aug 2024

Keywords

  • seagrass
  • macroalgae
  • remote sensing
  • habitat classification
  • intertidal mapping
  • multispectral UAV

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