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dc.contributor.authorMurashkin, Dmitrii
dc.contributor.authorSpreen, Gunnar
dc.contributor.authorHuntemann, Marcus
dc.contributor.authorDierking, Wolfgang Fritz Otto
dc.date.accessioned2019-03-19T12:56:58Z
dc.date.available2019-03-19T12:56:58Z
dc.date.issued2018-03-05
dc.description.abstractThe presence of leads with open water or thin ice is an important feature of the Arctic sea ice cover. Leads regulate the heat, gas and moisture fluxes between the ocean and atmosphere and are areas of high ice growth rates during periods of freezing conditions. Here, an algorithm providing an automatic lead detection based on synthetic aperture radar images is described that can be applied to a wide range of Sentinel-1 scenes. By using both the HH and the HV channels instead of single co-polarised observations the algorithm is able to classify more leads correctly. The lead classification algorithm is based on polarimetric features and textural features derived from the grey-level co-occurrence matrix. The Random Forest classifier is used to investigate the importance of the individual features for lead detection. The precision–recall curve representing the quality of the classification is used to define threshold for a binary lead/sea ice classification. The algorithm is able to produce a lead classification with more that 90% precision with 60% of all leads classified. The precision can be increased by the cost of the amount of leads detected. Results are evaluated based on comparisons with Sentinel-2 optical satellite data.en_US
dc.description.sponsorshipThe University of Bremen The German Excellence Initiative Deutsche Forschungsgemeinschaft (DFG)en_US
dc.descriptionSource at <a href=https://doi.org/10.1017/aog.2018.6> https://doi.org/10.1017/aog.2018.6</a>.en_US
dc.identifier.citationMurashkin, D., Spreen, G., Huntemann, M. & Dierking, W.F.O. (2018). Method for detection of leads from Sentinel-1 SAR images. <i>Annals of Glaciology, 59</i>(76), 124-136. https://doi.org/10.1017/aog.2018.6en_US
dc.identifier.cristinIDFRIDAID 1627536
dc.identifier.doi10.1017/aog.2018.6
dc.identifier.issn0260-3055
dc.identifier.issn1727-5644
dc.identifier.urihttps://hdl.handle.net/10037/15023
dc.language.isoengen_US
dc.publisherCambridge University Press (CUP)en_US
dc.relation.journalAnnals of Glaciology
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Mathematics and natural science: 400::Geosciences: 450::Quaternary geology, glaciology: 465en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi, glasiologi: 465en_US
dc.subjectice/atmosphere interactionsen_US
dc.subjectice/ocean interactionsen_US
dc.subjectremote sensingen_US
dc.subjectsea iceen_US
dc.subjectsea-ice dynamicsen_US
dc.titleMethod for detection of leads from Sentinel-1 SAR imagesen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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