A multi-satellite mapping framework for floating kelp forests

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dc.contributor.authorGendall, Lianna
dc.contributor.authorSchroeder, Sarah B.
dc.contributor.authorWills, Peter
dc.contributor.authorHessing-Lewis, Margot
dc.contributor.authorCosta, Maycira
dc.date.accessioned2024-02-06T18:16:17Z
dc.date.available2024-02-06T18:16:17Z
dc.date.copyright2023en_US
dc.date.issued2023
dc.description.abstractKelp forests provide key habitat on the Pacific Coast of Canada; however, the long-term changes in their distribution and abundance remain poorly understood. With advances in satellite technology, floating kelp forests can now be monitored across large-scale areas. We present a methodological framework using an object-based image analysis approach that enables the combination of imagery from multiple satellites at different spatial resolutions and temporal coverage, to map kelp forests with floating canopy through time. The framework comprises four steps: (1) compilation and quality assessment; (2) preprocessing; (3) an object-oriented classification; and (4) an accuracy assessment. Additionally, the impact of spatial resolution on the detectability of floating kelp forests is described. Overall, this workflow was successful in producing accurate maps of floating kelp forests, with global accuracy scores of between 88% and 94%. When comparing the impact of resolution on detectability, lower resolutions were less reliable at detecting small kelp forests in high slope areas. Based on the analysis, we suggest removing high slope areas (11.4%) from time series analyses using high- to medium-resolution satellite imagery and that error, in this case up to 7%, be considered when comparing imagery at different resolutions in low–mid slope areas through time.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipDuring this research L.G. was supported through a MITACS Accelerate internship with the Hakai Institute, as well as M.C.’s NSERC-DG.en_US
dc.identifier.citationGendall, L., Schroeder, S. B., Wills, P., Hessing-Lewis, M., & Costa, M. (2023). A multi-satellite mapping framework for floating kelp forests. Remote Sensing, 15(5), 1276. https://doi.org/10.3390/rs15051276en_US
dc.identifier.urihttps://doi.org/10.3390/rs15051276
dc.identifier.urihttp://hdl.handle.net/1828/15945
dc.language.isoenen_US
dc.publisherRemote Sensingen_US
dc.subjectkelp forests
dc.subjectmultispectral
dc.subjectsatellite
dc.subjecttime series
dc.subjectspatial resolution
dc.subjectobject-based image analysis
dc.subjectremote sensing
dc.subject.departmentDepartment of Geography
dc.titleA multi-satellite mapping framework for floating kelp forestsen_US
dc.typeArticleen_US

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