eprintid: 10080845 rev_number: 21 eprint_status: archive userid: 608 dir: disk0/10/08/08/45 datestamp: 2019-09-03 16:46:51 lastmod: 2021-09-26 23:12:02 status_changed: 2019-09-03 16:46:51 type: article metadata_visibility: show creators_name: Kellaris, A creators_name: Gil, A creators_name: Faria, J creators_name: Amaral, R creators_name: Moreu-Badia, I creators_name: Neto, A creators_name: Yesson, C title: Using low-cost drones to monitor heterogeneous submerged seaweed habitats: A case study in the Azores ispublished: pub divisions: UCL divisions: B02 divisions: C08 divisions: D09 keywords: algae, alien species, aquaculture, archipelago, coastal monitoring, remote sensing note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: 1. Remote sensing is a powerful monitoring tool for seaweeds, providing large‐scale insights into their ecosystem benefits and invasive impacts. Satellites and manned aircraft have been widely used for this purpose, but their spatial resolution is generally insufficient to map heterogeneous seaweed habitats. / 2. In this study, the potential of low‐cost and high‐resolution drone imagery to map heterogeneous seaweed habitats was assessed on Azorean coasts, where an invasive and commercial species, Asparagopsis armata, is present. A Phantom Pro 3 drone equipped with a visible‐light sensor was used to create photomosaics in three sites on São Miguel island, and ground‐truth data for various seaweed groups were collected with exploratory kayak sampling. Support‐vector machine, random forest, and artificial neural network algorithms were used to construct predictive models of seaweed coverage. / 3. Wind, clouds, and sun glint were the most significant factors affecting drone surveys and images. Exploratory sampling helped locate relatively homogeneous seaweed patches; however, the data were limited and spatially autocorrelated, contributing to overoptimistic model evaluation metrics. Moreover, the models struggled to distinguish seaweeds deeper than 3–4 m. / 4. In conclusion, using drones to monitor heterogeneous seaweed habitats is challenging, especially in oceanic islands where waters are deep and weather is unpredictable. However, this study highlights the potential use of photo‐interpretation to collect modelling data from drone imagery, instead of time‐consuming exploratory ground‐truth sampling. Future studies could assess drones to map seaweeds in less challenging conditions and use photo‐interpretation to improve collection of modelling data. date: 2019-11 date_type: published publisher: WILEY official_url: https://doi.org/10.1002/aqc.3189 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1682952 doi: 10.1002/aqc.3189 lyricists_name: Yesson, Christopher lyricists_id: CYESS52 actors_name: Yesson, Christopher actors_id: CYESS52 actors_role: owner full_text_status: public publication: Aquatic Conservation: Marine and Freshwater Ecosystems volume: 29 number: 11 pagerange: 1909-1922 pages: 14 issn: 1099-0755 citation: Kellaris, A; Gil, A; Faria, J; Amaral, R; Moreu-Badia, I; Neto, A; Yesson, C; (2019) Using low-cost drones to monitor heterogeneous submerged seaweed habitats: A case study in the Azores. Aquatic Conservation: Marine and Freshwater Ecosystems , 29 (11) pp. 1909-1922. 10.1002/aqc.3189 <https://doi.org/10.1002/aqc.3189>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10080845/1/KellarisEtAl_AqCons_2019-Accepted.pdf