Mapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS)

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dc.contributor.authorNahirnik, Natasha K.
dc.contributor.authorReshitnyk, Luba
dc.contributor.authorCampbell, Marcus
dc.contributor.authorHessing-Lewis, Margot
dc.contributor.authorCosta, Maycira
dc.contributor.authorYakimishyn, Jennifer
dc.contributor.authorLee, Lynn
dc.date.accessioned2020-08-10T18:05:12Z
dc.date.available2020-08-10T18:05:12Z
dc.date.copyright2018en_US
dc.date.issued2018
dc.description.abstractThere is growing interest in the use of Unoccupied Aerial Systems (UAS ) for mapping and monitoring of seagrass habitats. UAS provide flexibility with timing of imagery capture, are relatively inexpensive, and obtain very high spatial resolution imagery compared to imagery acquired from sensors mounted on satellite or piloted aircraft. However, research to date has focused on UAS applications for exposed intertidal areas or clear tropical waters. In contrast, submerged seagrass meadows in temperate regions are subject to high cloud cover and water column turbidity, which may limit the application of UAS imagery for coastal habitat mapping. To test the constraints on UAS seagrass mapping, we examined the effects of five environmental conditions at the time of UAS image acquisition (sun angle, tidal height, cloud cover, Secchi depth and wind speed) and five site characteristics (eelgrass patchiness and density, presence and density of non‐eelgrass submerged aquatic vegetation, sediment tone, eelgrass deep edge and site exposure) at 26 eelgrass (Zostera marina ) monitoring sites in British Columbia, Canada. Eelgrass was delineated in UAS orthomosaics using object‐based image analysis, combining image segmentation with manual classification. Each site was ranked according to the analysts’ confidence in the delineated eelgrass. Robust Linear Regression revealed sun angle and ‘theoretical visibility’ (an aggregate of tidal height, Secchi depth, and eelgrass deep edge conditions) to be the most important variables affecting mapping confidence. In general, ideal environmental conditions to obtain high confidence eelgrass mapping included: (1) sun angles below 40°; (2) positive theoretical visibility with Secchi depths >5 m; (3) cloud cover conditions of <10% or >90%; and (4) wind speeds less than 5 km h−1. Additionally, high mapping confidence was achieved for sites with dense, continuous, and homogeneous eelgrass meadows. The results of this analysis will guide implementation of UAS mapping technologies in coastal temperate regions.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipThis research was jointly supported by the Tula Foundation (Hakai Institute), Parks Canada, University of Victoria and Mitacs (Grant #IT07414). Field work and imagery acquisition was conducted in partnership with the Hakai Institute, Parks Canada and local First Nations communities. The authors acknowledge the multiple First Nation territories in which the data were collected. Many thanks to colleagues and field assistants at all participating organizations in the collection of the field data: Will Hall, Derek Heathfield, Keith Holmes, Will McInnes, Tara Sharma, Mike Vegh, Rebecca Holte, Christine Bentley, Niisii Guujaaw, Clint Johnson Kendrick, Cameron Sanjivi, Caron Olive, Dan Grinnell, Mike Wald, Sarah Brittain and Teagan O'Shaughnessy.en_US
dc.identifier.citationNahirnick, N. K., Reshitnyk, L., Campbell, M., Hessing-Lewis, M., Costa, M., Yakimishyn, J., Lee, L. (2018). Mapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS). Remote Sensing in Ecology and Conservation, 5(2), 121-135. https://doi.org/10.1002/rse2.98.en_US
dc.identifier.urihttps://doi.org/10.1002/rse2.98
dc.identifier.urihttp://hdl.handle.net/1828/11981
dc.language.isoenen_US
dc.publisherRemote Sensing in Ecology and Conservationen_US
dc.subjectBritish Columbia
dc.subjectdrone
dc.subjectmarine habitat mapping
dc.subjectnearshore
dc.subjectseagrass
dc.subjectUAS
dc.subjectUAV
dc.subjectZostera marina
dc.subject.departmentDepartment of Geography
dc.titleMapping with confidence; delineating seagrass habitats using Unoccupied Aerial Systems (UAS)en_US
dc.typeArticleen_US

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