<?xml version='1.0' encoding='UTF-8'?><codeBook xmlns="ddi:codebook:2_5" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="ddi:codebook:2_5 https://ddialliance.org/Specification/DDI-Codebook/2.5/XMLSchema/codebook.xsd" version="2.5"><docDscr><citation><titlStmt><titl>Synthetic-Aperture Radar (SAR) based Ice types/Ice edge dataset for deep learning analysis</titl><IDNo agency="DOI">doi:10.18710/QAYI4O</IDNo></titlStmt><distStmt><distrbtr source="archive">DataverseNO</distrbtr><distDate>2020-07-23</distDate></distStmt><verStmt source="archive"><version date="2023-11-01" type="RELEASED">1</version></verStmt><biblCit>Khaleghian, Salman; Lohse, Johannes Philipp; Kræmer, Thomas, 2020, "Synthetic-Aperture Radar (SAR) based Ice types/Ice edge dataset for deep learning analysis", https://doi.org/10.18710/QAYI4O, DataverseNO, V1</biblCit></citation></docDscr><stdyDscr><citation><titlStmt><titl>Synthetic-Aperture Radar (SAR) based Ice types/Ice edge dataset for deep learning analysis</titl><IDNo agency="DOI">doi:10.18710/QAYI4O</IDNo></titlStmt><rspStmt><AuthEnty affiliation="UiT The Arctic University of Norway">Khaleghian, Salman</AuthEnty><AuthEnty affiliation="UiT The Arctic University of Norway">Lohse, Johannes Philipp</AuthEnty><AuthEnty affiliation="UiT The Arctic University of Norway">Kræmer, Thomas</AuthEnty></rspStmt><prodStmt><producer abbr="UiT">UiT The Arctic University of Norway</producer></prodStmt><distStmt><distrbtr source="archive">DataverseNO</distrbtr><distrbtr affiliation="UiT The Arctic University of Norway" URI="https://dataverse.no/dataverse/uit">UiT The Arctic University of Norway</distrbtr><contact affiliation="UiT The Arctic University of Norway" email="salman.khaleghian@uit.no">Khaleghian, Salman</contact><depositr>Khaleghian, Salman</depositr><depDate>2019-12-18</depDate></distStmt><holdings URI="https://doi.org/10.18710/QAYI4O"/></citation><stdyInfo><subject><keyword xml:lang="en">Computer and Information Science</keyword><keyword xml:lang="en">Earth and Environmental Sciences</keyword><keyword xml:lang="en">Engineering</keyword><keyword xml:lang="en">Physics</keyword><keyword>Deep Learning</keyword><keyword>Remote Sensing</keyword><keyword>Ice types</keyword><keyword>Ice Edge</keyword><keyword>Synthetic-aperture radar</keyword></subject><abstract date="2019-12-18">This dataset has been prepared for Ice types/Ice edge analysis based on deep neural networks. The dataset has been created based on 31 scenes in north of Svalbard based on labeled polygons. The dataset contains six classes including OpenWater, Leads with water, Brash/Pancake Ice, Thin Ice, Thick Ice-Flat and Thick Ice-Ridged. The data records, called patches, extracted all from inside of each polygon with stride 10 in different sizes, 10x10, 20x20, 32x32, 36x36, 46x46 pixels for each class</abstract><sumDscr><collDate cycle="P1" event="start" date="2018-01-01">2018-01-01</collDate><collDate cycle="P1" event="end" date="2018-12-31">2018-12-31</collDate><dataKind>SAR Image</dataKind><dataKind>Satellite image</dataKind></sumDscr></stdyInfo><method><dataColl><sources/></dataColl><anlyInfo/></method><dataAccs><setAvail/><useStmt/><notes type="DVN:TOA" level="dv">The file not available now, you should contact the author to get access.</notes><notes type="DVN:TOU" level="dv">&lt;a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0&lt;/a></notes></dataAccs><othrStdyMat><relPubl><citation><titlStmt><titl>Khaleghian, S.; Ullah, H.; Kræmer, T.; Hughes, N.; Eltoft, T.; Marinoni, A. Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks. Remote Sens. 2021, 13, 1734. https://doi.org/10.3390/rs13091734</titl><IDNo agency="doi">10.3390/rs13091734</IDNo></titlStmt><biblCit>Khaleghian, S.; Ullah, H.; Kræmer, T.; Hughes, N.; Eltoft, T.; Marinoni, A. Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks. Remote Sens. 2021, 13, 1734. https://doi.org/10.3390/rs13091734</biblCit></citation><ExtLink URI="https://doi.org/10.3390/rs13091734"/></relPubl></othrStdyMat></stdyDscr><otherMat ID="f79805" URI="https://dataverse.no/api/access/datafile/79805" level="datafile"><labl>00_Readme.txt</labl><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">text/plain</notes></otherMat><otherMat ID="f19448" URI="https://dataverse.no/api/access/datafile/19448" level="datafile"><labl>Patches10x10.zip</labl><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/zip</notes></otherMat><otherMat ID="f19450" URI="https://dataverse.no/api/access/datafile/19450" level="datafile"><labl>Patches20x20.zip</labl><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/zip</notes></otherMat><otherMat ID="f19449" URI="https://dataverse.no/api/access/datafile/19449" level="datafile"><labl>Patches32x32.zip</labl><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/zip</notes></otherMat><otherMat ID="f19451" URI="https://dataverse.no/api/access/datafile/19451" level="datafile"><labl>patches36x36.zip</labl><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/zip</notes></otherMat><otherMat ID="f19447" URI="https://dataverse.no/api/access/datafile/19447" level="datafile"><labl>Patches46x46.zip</labl><notes level="file" type="DATAVERSE:CONTENTTYPE" subject="Content/MIME Type">application/zip</notes></otherMat></codeBook>