{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T21:17:43Z","timestamp":1775078263273,"version":"3.50.1"},"reference-count":137,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,25]],"date-time":"2023-02-25T00:00:00Z","timestamp":1677283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hakai Institute"},{"name":"NSERC-DG"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Kelp 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\u2013mid slope areas through time.<\/jats:p>","DOI":"10.3390\/rs15051276","type":"journal-article","created":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T01:59:10Z","timestamp":1677463150000},"page":"1276","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A Multi-Satellite Mapping Framework for Floating Kelp Forests"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1275-518X","authenticated-orcid":false,"given":"Lianna","family":"Gendall","sequence":"first","affiliation":[{"name":"SPECTRAL Remote Sensing Laboratory, University of Victoria, 3800 Finnerty Road, Victoria, BC V8P 5C2, Canada"}]},{"given":"Sarah B.","family":"Schroeder","sequence":"additional","affiliation":[{"name":"SPECTRAL Remote Sensing Laboratory, University of Victoria, 3800 Finnerty Road, Victoria, BC V8P 5C2, Canada"}]},{"given":"Peter","family":"Wills","sequence":"additional","affiliation":[{"name":"Canadian Hydrographic Service, Institute of Ocean Sciences, 9860 West Saanich Rd, Sidney, BC V8L 4B2, Canada"}]},{"given":"Margot","family":"Hessing-Lewis","sequence":"additional","affiliation":[{"name":"Canadian Hydrographic Service, Institute of Ocean Sciences, 9860 West Saanich Rd, Sidney, BC V8L 4B2, Canada"},{"name":"Hakai Institute, Campbell River, BC V0P 1H0, Canada"}]},{"given":"Maycira","family":"Costa","sequence":"additional","affiliation":[{"name":"SPECTRAL Remote Sensing Laboratory, University of Victoria, 3800 Finnerty Road, Victoria, BC V8P 5C2, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sheppard, C. 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