Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data
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| Název: | Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data |
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| Autoři: | Niels Svane, Troels Lange, Sara Egemose, Oliver Dalby, Aris Thomasberger, Mogens R Flindt |
| Zdroj: | Svane, N, Lange, T, Egemose, S, Dalby, O, Thomasberger, A & Flindt, M R 2022, ' Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data ', Progress in Physical Geography, vol. 46, no. 2, pp. 2332-249 . https://doi.org/10.1177/03091333211052005 Svane, N, Lange, T, Egemose, S, Dalby, O, Thomasberger, A & Flindt, M 2022, ' Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data ', Progress in Physical Geography, vol. 46, no. 2, pp. 232-249 . https://doi.org/10.1177/03091333211052005 |
| Informace o vydavateli: | SAGE Publications, 2021. |
| Rok vydání: | 2021 |
| Témata: | macroalgae, Marine biology, 0106 biological sciences, coastal monitoring, seagrass, UAV, name=SDG 14 - Life Below Water, Coastal mining, marine biology, Remote sensing, 15. Life on land, 01 natural sciences, remote sensing, Macroalgae, 13. Climate action, 14. Life underwater, Seagrass |
| Popis: | Traditional monitoring (e.g., in-water based surveys) of eelgrass meadows and perennial macroalgae in coastal areas is time and labor intensive, requires extensive equipment, and the collected data has a low temporal resolution. Further, divers and Remotely Operated Vehicles (ROVs) have a low spatial extent that cover small fractions of full systems. The inherent heterogeneity of eelgrass meadows and macroalgae assemblages in these coastal systems makes interpolation and extrapolation of observations complicated and, as such, methods to collect data on larger spatial scales whilst retaining high spatial resolution is required to guide management. Recently, the utilization of Unoccupied Aerial Vehicles (UAVs) has gained popularity in ecological sciences due to their ability to rapidly collect large amounts of area-based and georeferenced data, making it possible to monitor the spatial extent and status of SAV communities with limited equipment requirements compared to ROVs or diver surveys. This paper is focused on the increased value provided by UAV-based, data collection (visual/Red Green Blue imagery) and Object Based Image Analysis for gaining an improved understanding of eelgrass recovery. It is demonstrated that delineation and classification of two species of SAV ( Fucus vesiculosus and Zostera marina) is possible; with an error matrix indicating 86–92% accuracy. Classified maps also highlighted the increasing biomass and areal coverage of F. vesiculosus as a potential stressor to eelgrass meadows. Further, authors derive a statistically significant conversion of percentage cover to biomass ( R2 = 0.96 for Fucus vesiculosus, R2 = 0.89 for Zostera marina total biomass, and R2 = 0.94 for AGB alone, p < 0.001). Results here provide an example of mapping cover and biomass of SAV and provide a tool to undertake spatio-temporal analyses to enhance the understanding of eelgrass ecosystem dynamics. |
| Druh dokumentu: | Article |
| Popis souboru: | application/pdf |
| Jazyk: | English |
| ISSN: | 1477-0296 0309-1333 |
| DOI: | 10.1177/03091333211052005 |
| Přístupová URL adresa: | https://orbit.dtu.dk/en/publications/88c8bcde-7e21-4e03-af87-76e21d473023 https://findresearcher.sdu.dk:8443/ws/files/196929136/MS_Upload.pdf |
| Rights: | CC BY ND URL: https://journals.sagepub.com/page/policies/text-and-data-mining-license |
| Přístupové číslo: | edsair.doi.dedup.....253bbf75045f697937a5397381482912 |
| Databáze: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | Traditional monitoring (e.g., in-water based surveys) of eelgrass meadows and perennial macroalgae in coastal areas is time and labor intensive, requires extensive equipment, and the collected data has a low temporal resolution. Further, divers and Remotely Operated Vehicles (ROVs) have a low spatial extent that cover small fractions of full systems. The inherent heterogeneity of eelgrass meadows and macroalgae assemblages in these coastal systems makes interpolation and extrapolation of observations complicated and, as such, methods to collect data on larger spatial scales whilst retaining high spatial resolution is required to guide management. Recently, the utilization of Unoccupied Aerial Vehicles (UAVs) has gained popularity in ecological sciences due to their ability to rapidly collect large amounts of area-based and georeferenced data, making it possible to monitor the spatial extent and status of SAV communities with limited equipment requirements compared to ROVs or diver surveys. This paper is focused on the increased value provided by UAV-based, data collection (visual/Red Green Blue imagery) and Object Based Image Analysis for gaining an improved understanding of eelgrass recovery. It is demonstrated that delineation and classification of two species of SAV ( Fucus vesiculosus and Zostera marina) is possible; with an error matrix indicating 86–92% accuracy. Classified maps also highlighted the increasing biomass and areal coverage of F. vesiculosus as a potential stressor to eelgrass meadows. Further, authors derive a statistically significant conversion of percentage cover to biomass ( R2 = 0.96 for Fucus vesiculosus, R2 = 0.89 for Zostera marina total biomass, and R2 = 0.94 for AGB alone, p < 0.001). Results here provide an example of mapping cover and biomass of SAV and provide a tool to undertake spatio-temporal analyses to enhance the understanding of eelgrass ecosystem dynamics. |
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| ISSN: | 14770296 03091333 |
| DOI: | 10.1177/03091333211052005 |