{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T04:38:32Z","timestamp":1769229512243,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,4,3]],"date-time":"2019-04-03T00:00:00Z","timestamp":1554249600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005416","name":"Norges Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["237906"],"award-info":[{"award-number":["237906"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Automatic 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\u201322 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\u2013polarization 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.<\/jats:p>","DOI":"10.3390\/rs11070806","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T03:13:42Z","timestamp":1554347622000},"page":"806","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Automatic Detection of Small Icebergs in Fast Ice Using Satellite Wide-Swath SAR Images"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3272-9624","authenticated-orcid":false,"given":"Ingri Halland","family":"Soldal","sequence":"first","affiliation":[{"name":"Nansen Environmental and Remote Sensing Center, Thorm\u00f8hlens Gate 47, N-5006 Bergen, Norway"},{"name":"Center for Integrated Remote Sensing and Forecasting for Arctic Operations, Department of Physics and Technology, UiT\u2014The Arctic University of Norway, 9019 Troms\u00f8, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5031-648X","authenticated-orcid":false,"given":"Wolfgang","family":"Dierking","sequence":"additional","affiliation":[{"name":"Center for Integrated Remote Sensing and Forecasting for Arctic Operations, Department of Physics and Technology, UiT\u2014The Arctic University of Norway, 9019 Troms\u00f8, Norway"},{"name":"Alfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bussestr. 24, 27570 Bremerhaven, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3601-1161","authenticated-orcid":false,"given":"Anton","family":"Korosov","sequence":"additional","affiliation":[{"name":"Nansen Environmental and Remote Sensing Center, Thorm\u00f8hlens Gate 47, N-5006 Bergen, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4531-3102","authenticated-orcid":false,"given":"Armando","family":"Marino","sequence":"additional","affiliation":[{"name":"Department of Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA, UK"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,3]]},"reference":[{"key":"ref_1","unstructured":"Jackson, C.R., and Apel, J.R. 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