Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29328
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dc.contributor.authorSoldal, Ingri Hallanden_UK
dc.contributor.authorDierking, Wolfgangen_UK
dc.contributor.authorKorosov, Antonen_UK
dc.contributor.authorMarino, Armandoen_UK
dc.date.accessioned2019-04-17T00:00:09Z-
dc.date.available2019-04-17T00:00:09Z-
dc.date.issued2019-04-03en_UK
dc.identifier.other806en_UK
dc.identifier.urihttp://hdl.handle.net/1893/29328-
dc.description.abstractAutomatic detection of icebergs in satellite images is regarded a useful tool to provide information necessary for safety in Arctic shipping or operations over large ocean areas in near-real time. In this work, we investigated the feasibility of automatic iceberg detection in Sentinel-1 Extra Wide Swath (EWS) SAR images which follow the preferred image mode in operational ice charting. As test region, we selected the Barents Sea where the size of many icebergs is on the order of the spatial resolution of the EWS-mode. We tested a new approach for a detection scheme. It is based on a combination of a filter for enhancing the contrast between icebergs and background, subsequent blob detection, and final application of a Constant False Alarm Rate (CFAR) algorithm. The filter relies mainly on the HV-polarized intensity which often reveals a larger difference between icebergs and sea ice or open water. The blob detector identifies locations of potential icebergs and thus shortens computation time. The final detection is performed on the identified blobs using the CFAR algorithm. About 2000 icebergs captured in fast ice were visually identified in Sentinel-2 Multi Spectral Imager (MSI) data and exploited for an assessment of the detection scheme performance using confusion matrices. For our performance tests, we used four Sentinel-1 EWS images. For judging the effect of spatial resolution, we carried out an additional test with one Sentinel-1 Interferometric Wide Swath (IWS) mode image. Our results show that only 8–22 percent of the icebergs could be detected in the EWS images, and over 90 percent of all detections were false alarms. In IWS mode, the number of correctly identified icebergs increased to 38 percent. However, we obtained a larger number of false alarms in the IWS image than in the corresponding EWS image. We identified two problems for iceberg detection: 1) with the given frequency–polarization combination, not all icebergs are strong scatterers at HV-polarization, and (2) icebergs and deformation structures present on fast ice can often not be distinguished since both may reveal equally strong responses at HV-polarization.en_UK
dc.language.isoenen_UK
dc.publisherMDPI AGen_UK
dc.relationSoldal IH, Dierking W, Korosov A & Marino A (2019) Automatic Detection of Small Icebergs in Fast Ice Using Satellite Wide-Swath SAR Images. Remote Sensing, 11 (7), Art. No.: 806. https://doi.org/10.3390/rs11070806en_UK
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjecticeberg detectionen_UK
dc.subjectCFARen_UK
dc.subjectiDPolRADen_UK
dc.subjectSARen_UK
dc.subjectoptical imagesen_UK
dc.titleAutomatic Detection of Small Icebergs in Fast Ice Using Satellite Wide-Swath SAR Imagesen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.3390/rs11070806en_UK
dc.citation.jtitleRemote Sensingen_UK
dc.citation.issn2072-4292en_UK
dc.citation.volume11en_UK
dc.citation.issue7en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderThe Research Council of Norwayen_UK
dc.citation.date03/04/2019en_UK
dc.contributor.affiliationThe Arctic University of Norwayen_UK
dc.contributor.affiliationThe Arctic University of Norwayen_UK
dc.contributor.affiliationNansen Environmental Research Centre (India) Ltden_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.identifier.isiWOS:000465549300071en_UK
dc.identifier.scopusid2-s2.0-85063990860en_UK
dc.identifier.wtid1268789en_UK
dc.contributor.orcid0000-0002-3601-1161en_UK
dc.contributor.orcid0000-0002-4531-3102en_UK
dc.date.accepted2019-03-31en_UK
dcterms.dateAccepted2019-03-31en_UK
dc.date.filedepositdate2019-04-16en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorSoldal, Ingri Halland|en_UK
local.rioxx.authorDierking, Wolfgang|en_UK
local.rioxx.authorKorosov, Anton|0000-0002-3601-1161en_UK
local.rioxx.authorMarino, Armando|0000-0002-4531-3102en_UK
local.rioxx.projectProject ID unknown|The Research Council of Norway|en_UK
local.rioxx.freetoreaddate2019-04-16en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by/4.0/|2019-04-16|en_UK
local.rioxx.filenameremotesensing-11-00806-v2.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source2072-4292en_UK
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