Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance
Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framewo...
Saved in:
Published in: | Remote sensing (Basel, Switzerland) Vol. 11; no. 4; p. 417 |
---|---|
Main Authors: | , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Basel
MDPI AG
01-02-2019
|
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Abstract | Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness. |
---|---|
AbstractList | Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness. If such trends and increased variability persist then it is possible that we could expect enhanced variability or pronounced increases/decreases in wintertime snow accumulation in certain sectors of the Arctic Ocean [12,13,14], thereby influencing atmosphere-sea ice-ocean exchanges and sea ice growth and decay rates. [...]model-based projections of summer sea ice loss in these regions may be problematic due to unrepresentative parameterizations. High-resolution (5–100 m) synthetic aperture radar (SAR) data are available for developing such a methodology, however the temporal resolution and spatial coverage of SAR is typically inconsistent and incidence angle effects on σ° is an additional uncontrolled variable. [...]we employ spaceborne scatterometer data to determine σ° variance based on daily data, albeit at a lower, yet still improved, spatial resolution (as high as ~4.5 km). [...]the dielectric properties will also manifest a correspondingly larger (smaller) change and directly affect the amount of surface and/or volume scattering from the snow/ice system. [...]each of the case study sites has different absolute (i.e., baseline) wintertime σ°, as a function of surface roughness, scatterometer frequency and incidence angle. |
Author | Nandan, Vishnu Geldsetzer, Torsten Howell, Stephen Lam, Hoi Yackel, John Mahmud, Mallik Scharien, Randall |
Author_xml | – sequence: 1 givenname: John surname: Yackel fullname: Yackel, John – sequence: 2 givenname: Torsten surname: Geldsetzer fullname: Geldsetzer, Torsten – sequence: 3 givenname: Mallik surname: Mahmud fullname: Mahmud, Mallik – sequence: 4 givenname: Vishnu surname: Nandan fullname: Nandan, Vishnu – sequence: 5 givenname: Stephen surname: Howell fullname: Howell, Stephen – sequence: 6 givenname: Randall orcidid: 0000-0002-2761-4809 surname: Scharien fullname: Scharien, Randall – sequence: 7 givenname: Hoi surname: Lam fullname: Lam, Hoi |
BookMark | eNpNUU1rGzEQFSWBpG4u-QWC3gqb6Gvl1bE1cWIw5OAkpScxK82269iSK8mU_vvIcWg6DCPx3uhppPeRnIQYkJBLzq6kNOw6Zc6ZYopPP5BzwaaiUcKIk__2Z-Qi5zWrISU3TJ2TsArxD334NbrngDnTm1zGLZQxBlpzPqZcmh8Iia4Q6MIhHVLc0iUUpN_HULASO3DYxxSQrhyUCsUtHohv4J7zEaFPkEYIDj-R0wE2GS_e1gl5nN88zO6a5f3tYvZ12TipeWkcCNkx1Rk2IOu0xl5org32niuvWwDAQbv2UKVmwL0EJUAor7xoXc_khCyOuj7C2u5SfVP6ayOM9hWI6aeFVEa3QdtJM0wZapxyXz_Pm77zAxjhDGsHodqq9fmotUvx9x5zseu4T6GOb4WUsmWqHqtdX45dLsWcEw7_buXMHuyx7_bIF7k0g8Y |
CitedBy_id | crossref_primary_10_3390_rs12091378 crossref_primary_10_1016_j_rse_2020_112049 crossref_primary_10_3390_rs12244032 crossref_primary_10_3390_rs13224570 crossref_primary_10_1080_19479832_2022_2144955 crossref_primary_10_1016_j_rse_2020_111835 crossref_primary_10_1080_07055900_2022_2060178 crossref_primary_10_1109_JSTARS_2022_3141980 crossref_primary_10_1017_aog_2020_48 crossref_primary_10_3390_rs12040606 crossref_primary_10_3390_rs13040768 |
Cites_doi | 10.1002/2014GL060993 10.1109/TGRS.2007.907043 10.1002/2015GL063775 10.1002/2014JC010284 10.5194/tc-11-2571-2017 10.1016/j.rse.2015.06.005 10.1177/0309133307087082 10.1080/07038992.2001.10854885 10.1109/TGRS.2007.903711 10.1088/1748-9326/7/1/014007 10.1175/JCLI-D-18-0125.1 10.1002/2015GL064823 10.1029/1999JC900181 10.1016/j.rse.2017.06.029 10.1016/j.rse.2016.10.004 10.1109/TGRS.1987.289816 10.1029/2012GL052868 10.1109/36.718643 10.5194/tc-12-2789-2018 10.1002/2015GL066855 10.1109/TGRS.2002.808317 10.1002/2015GL064081 10.1109/TGRS.2006.882139 10.1029/2000JC000409 10.1029/2018WR023559 10.1002/joc.3723 10.1016/j.rse.2017.06.038 10.1002/2014JC009985 10.1017/S0022143000007012 10.1109/TGRS.2005.860208 10.1109/TGRS.1984.350604 10.1109/TGRS.1989.35933 10.1002/2016GL069330 10.5194/tc-7-1971-2013 10.3189/2015AoG69A715 10.1029/94JC02201 10.1109/36.673679 10.1029/2011JC007654 10.1002/2017JC012865 10.1109/TGRS.2016.2638323 10.1029/2018JC014028 10.1002/2016JC012398 10.1016/j.asr.2017.09.007 10.3390/rs9070757 10.1002/2017JC013364 10.1029/2007JC004281 10.1109/36.655316 10.5194/tc-8-1607-2014 10.1002/2017GL075494 10.1002/jgrc.20228 10.1002/hyp.6240 10.1002/hyp.7526 10.1002/hyp.10255 10.1080/07055900.2001.9649676 10.1016/j.rse.2016.07.013 10.1016/j.coldregions.2009.03.009 10.1029/2011GL049216 10.5194/tc-12-3551-2018 10.1109/TGRS.2018.2841343 10.1073/pnas.1114910109 10.1029/2012GL052794 10.1109/36.905237 10.1016/j.rse.2016.03.003 10.1029/2011JC007371 10.1029/94JC02200 10.1109/TGRS.2017.2682859 10.1109/TGRS.2006.890418 10.1109/TGRS.2011.2170843 |
ContentType | Journal Article |
Copyright | 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
Copyright_xml | – notice: 2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
DBID | AAYXX CITATION 7QF 7QO 7QQ 7QR 7SC 7SE 7SN 7SP 7SR 7TA 7TB 7U5 8BQ 8FD 8FE 8FG ABJCF ABUWG AFKRA ARAPS AZQEC BENPR BGLVJ BHPHI BKSAR C1K CCPQU DWQXO F28 FR3 H8D H8G HCIFZ JG9 JQ2 KR7 L6V L7M L~C L~D M7S P5Z P62 P64 PCBAR PIMPY PQEST PQQKQ PQUKI PTHSS DOA |
DOI | 10.3390/rs11040417 |
DatabaseName | CrossRef Aluminium Industry Abstracts Biotechnology Research Abstracts Ceramic Abstracts Chemoreception Abstracts Computer and Information Systems Abstracts Corrosion Abstracts Ecology Abstracts Electronics & Communications Abstracts Engineered Materials Abstracts Materials Business File Mechanical & Transportation Engineering Abstracts Solid State and Superconductivity Abstracts METADEX Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest Central Advanced Technologies & Aerospace Database (1962 - current) ProQuest Central Essentials ProQuest Central Technology Collection ProQuest Natural Science Collection Earth, Atmospheric & Aquatic Science Collection Environmental Sciences and Pollution Management ProQuest One Community College ProQuest Central Korea ANTE: Abstracts in New Technology & Engineering Engineering Research Database Aerospace Database Copper Technical Reference Library SciTech Premium Collection (Proquest) (PQ_SDU_P3) Materials Research Database ProQuest Computer Science Collection Civil Engineering Abstracts ProQuest Engineering Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Earth, Atmospheric & Aquatic Science Database Publicly Available Content Database (Proquest) (PQ_SDU_P3) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition Engineering Collection Directory of Open Access Journals |
DatabaseTitle | CrossRef Publicly Available Content Database Materials Research Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts SciTech Premium Collection Materials Business File Environmental Sciences and Pollution Management Engineered Materials Abstracts Natural Science Collection Chemoreception Abstracts Engineering Collection ANTE: Abstracts in New Technology & Engineering Advanced Technologies & Aerospace Collection Engineering Database Aluminium Industry Abstracts ProQuest One Academic Eastern Edition Electronics & Communications Abstracts Earth, Atmospheric & Aquatic Science Database ProQuest Technology Collection Ceramic Abstracts Ecology Abstracts Biotechnology and BioEngineering Abstracts ProQuest One Academic UKI Edition Solid State and Superconductivity Abstracts Engineering Research Database ProQuest One Academic Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts ProQuest Central (Alumni Edition) ProQuest One Community College Earth, Atmospheric & Aquatic Science Collection ProQuest Central Aerospace Database Copper Technical Reference Library ProQuest Engineering Collection Biotechnology Research Abstracts ProQuest Central Korea Advanced Technologies Database with Aerospace Civil Engineering Abstracts ProQuest SciTech Collection METADEX Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database Materials Science & Engineering Collection Corrosion Abstracts |
DatabaseTitleList | CrossRef Publicly Available Content Database |
Database_xml | – sequence: 1 dbid: DOA name: Directory of Open Access Journals url: http://www.doaj.org/ sourceTypes: Open Website |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Geography |
EISSN | 2072-4292 |
ExternalDocumentID | oai_doaj_org_article_839f70e6e71d404d9b8dfa92c905f245 10_3390_rs11040417 |
GeographicLocations | Arctic Ocean Arctic region |
GeographicLocations_xml | – name: Arctic region – name: Arctic Ocean |
GroupedDBID | 29P 2WC 5VS 8FE 8FG 8FH AADQD AAHBH AAYXX ABDBF ABJCF ADBBV AENEX AFKRA AFZYC ALMA_UNASSIGNED_HOLDINGS ARAPS BCNDV BENPR BGLVJ BHPHI BKSAR CCPQU CITATION E3Z ESX FRP GROUPED_DOAJ HCIFZ I-F KQ8 L6V LK5 M7R M7S MODMG M~E OK1 P62 PCBAR PIMPY PROAC PTHSS RIG TR2 TUS 7QF 7QO 7QQ 7QR 7SC 7SE 7SN 7SP 7SR 7TA 7TB 7U5 8BQ 8FD ABUWG AZQEC C1K DWQXO F28 FR3 H8D H8G JG9 JQ2 KR7 L7M L~C L~D P64 PQEST PQQKQ PQUKI |
ID | FETCH-LOGICAL-c361t-ca23804890fe0866eb26169ebd14d65aaaef6c5aef6360a1d3a42a24d4d25cb03 |
IEDL.DBID | DOA |
ISSN | 2072-4292 |
IngestDate | Tue Oct 22 15:13:07 EDT 2024 Sat Nov 09 11:40:44 EST 2024 Thu Nov 21 20:55:02 EST 2024 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 4 |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c361t-ca23804890fe0866eb26169ebd14d65aaaef6c5aef6360a1d3a42a24d4d25cb03 |
ORCID | 0000-0002-2761-4809 |
OpenAccessLink | https://doaj.org/article/839f70e6e71d404d9b8dfa92c905f245 |
PQID | 2333504404 |
PQPubID | 2032338 |
ParticipantIDs | doaj_primary_oai_doaj_org_article_839f70e6e71d404d9b8dfa92c905f245 proquest_journals_2333504404 crossref_primary_10_3390_rs11040417 |
PublicationCentury | 2000 |
PublicationDate | 2019-02-01 |
PublicationDateYYYYMMDD | 2019-02-01 |
PublicationDate_xml | – month: 02 year: 2019 text: 2019-02-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | Basel |
PublicationPlace_xml | – name: Basel |
PublicationTitle | Remote sensing (Basel, Switzerland) |
PublicationYear | 2019 |
Publisher | MDPI AG |
Publisher_xml | – name: MDPI AG |
References | ref13 ref57 ref12 ref56 ref15 ref59 ref14 ref58 ref53 ref52 ref11 ref55 ref10 ref54 ref17 ref16 ref19 ref18 ref51 ref50 ref46 ref45 ref48 ref47 ref42 ref41 ref44 ref43 ref49 ref8 ref7 ref9 ref4 ref3 ref6 ref5 ref40 ref35 ref34 ref37 ref36 ref31 ref30 ref33 ref32 ref2 ref1 ref39 ref38 ref24 ref68 ref23 ref67 ref26 ref25 ref69 ref20 ref64 ref63 ref66 ref21 ref65 ref28 Drobot (ref22) 1998; 64 ref27 ref29 ref60 ref62 ref61 |
References_xml | – ident: ref28 doi: 10.1002/2014GL060993 – ident: ref47 doi: 10.1109/TGRS.2007.907043 – ident: ref12 doi: 10.1002/2015GL063775 – ident: ref29 doi: 10.1002/2014JC010284 – ident: ref30 doi: 10.5194/tc-11-2571-2017 – volume: 64 start-page: 415 year: 1998 ident: ref22 article-title: Towards Development of a Snow Water Equivalence (SWE) Algorithm Using Microwave Radiometry over Snow Covered First-Year Sea Ice publication-title: Photogramm. Eng. Remote Sens. contributor: fullname: Drobot – ident: ref38 doi: 10.1016/j.rse.2015.06.005 – ident: ref23 doi: 10.1177/0309133307087082 – ident: ref54 doi: 10.1080/07038992.2001.10854885 – ident: ref68 doi: 10.1109/TGRS.2007.903711 – ident: ref8 doi: 10.1088/1748-9326/7/1/014007 – ident: ref13 doi: 10.1175/JCLI-D-18-0125.1 – ident: ref36 doi: 10.1002/2015GL064823 – ident: ref44 doi: 10.1029/1999JC900181 – ident: ref49 doi: 10.1016/j.rse.2017.06.029 – ident: ref39 doi: 10.1016/j.rse.2016.10.004 – ident: ref62 doi: 10.1109/TGRS.1987.289816 – ident: ref1 doi: 10.1029/2012GL052868 – ident: ref43 doi: 10.1109/36.718643 – ident: ref31 doi: 10.5194/tc-12-2789-2018 – ident: ref2 doi: 10.1002/2015GL066855 – ident: ref16 doi: 10.1109/TGRS.2002.808317 – ident: ref33 doi: 10.1002/2015GL064081 – ident: ref17 doi: 10.1109/TGRS.2006.882139 – ident: ref15 doi: 10.1029/2000JC000409 – ident: ref56 doi: 10.1029/2018WR023559 – ident: ref9 doi: 10.1002/joc.3723 – ident: ref59 doi: 10.1016/j.rse.2017.06.038 – ident: ref11 doi: 10.1002/2014JC009985 – ident: ref46 doi: 10.1017/S0022143000007012 – ident: ref18 doi: 10.1109/TGRS.2005.860208 – ident: ref65 doi: 10.1109/TGRS.1984.350604 – ident: ref66 doi: 10.1109/TGRS.1989.35933 – ident: ref3 doi: 10.1002/2016GL069330 – ident: ref20 doi: 10.5194/tc-7-1971-2013 – ident: ref69 doi: 10.3189/2015AoG69A715 – ident: ref63 doi: 10.1029/94JC02201 – ident: ref67 doi: 10.1109/36.673679 – ident: ref26 doi: 10.1029/2011JC007654 – ident: ref6 doi: 10.1002/2017JC012865 – ident: ref50 doi: 10.1109/TGRS.2016.2638323 – ident: ref21 doi: 10.1029/2018JC014028 – ident: ref4 doi: 10.1002/2016JC012398 – ident: ref37 doi: 10.1016/j.asr.2017.09.007 – ident: ref40 doi: 10.3390/rs9070757 – ident: ref14 doi: 10.1002/2017JC013364 – ident: ref57 doi: 10.1029/2007JC004281 – ident: ref42 doi: 10.1109/36.655316 – ident: ref32 doi: 10.5194/tc-8-1607-2014 – ident: ref5 doi: 10.1002/2017GL075494 – ident: ref19 doi: 10.1002/jgrc.20228 – ident: ref53 doi: 10.1002/hyp.6240 – ident: ref55 doi: 10.1002/hyp.7526 – ident: ref45 doi: 10.1002/hyp.10255 – ident: ref64 doi: 10.1080/07055900.2001.9649676 – ident: ref35 doi: 10.1016/j.rse.2016.07.013 – ident: ref48 doi: 10.1016/j.coldregions.2009.03.009 – ident: ref24 doi: 10.1029/2011GL049216 – ident: ref34 doi: 10.5194/tc-12-3551-2018 – ident: ref60 doi: 10.1109/TGRS.2018.2841343 – ident: ref7 doi: 10.1073/pnas.1114910109 – ident: ref10 doi: 10.1029/2012GL052794 – ident: ref58 doi: 10.1109/36.905237 – ident: ref61 doi: 10.1016/j.rse.2016.03.003 – ident: ref25 doi: 10.1029/2011JC007371 – ident: ref51 doi: 10.1029/94JC02200 – ident: ref52 doi: 10.1109/TGRS.2017.2682859 – ident: ref41 doi: 10.1109/TGRS.2006.890418 – ident: ref27 doi: 10.1109/TGRS.2011.2170843 |
SSID | ssj0000331904 |
Score | 2.314986 |
Snippet | Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are... If such trends and increased variability persist then it is possible that we could expect enhanced variability or pronounced increases/decreases in wintertime... |
SourceID | doaj proquest crossref |
SourceType | Open Website Aggregation Database |
StartPage | 417 |
SubjectTerms | ASCAT backscatter (σ°) variance Backscattering Decay rate Dielectric properties Electrical properties first-year sea ice Ice Incidence angle QuikSCAT Remote sensing Salinity scatterometer Sea ice Seasons Snow Snow accumulation snow thickness Spatial discrimination Spatial resolution Summer Surface roughness Synthetic aperture radar Temporal resolution Variability Variance Winter |
Title | Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance |
URI | https://www.proquest.com/docview/2333504404 https://doaj.org/article/839f70e6e71d404d9b8dfa92c905f245 |
Volume | 11 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://sdu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1JSwMxFA7ai17EFatVAnodmsnW5mi1RUG8TN1OQ7ahRZxKF8R_78tk2goevAjDHDIhE97-4L3vIXSpjKHEeNBvlfKEO2kSrR0NZX-ikIVlQoZG4dus8_DSvekHmJzVqK9QExbhgSPh2uDAiw7x0ndSxwl3ynRdoRW1Cg6jPKKXEvkjmapsMAPRIjzikTLI69vTGTg6OKCaTLb2QBVQ_y87XDmXwS7aqaNCfBVvs4c2fLmPtuoB5aOvA1Rm5eQTD0dj-xZsE-6DZsamQwzPYAwxXPIKQoszr_Gd9Ti0jeB7CCTxc0CEgA-QHAfbUnqc2QpUc_IeSmFwL3TZxxX8BJlzEIND9DjoD69vk3pUQmKZTOeJ1eB6QRkVKTwkKRLyZZlK5Y1Lgf5Ca-0LaUV4M0l06pjmVFPuuKPCGsKOUKOclP4YYckgBGHG-UIwrqxRnDjvSGoZY7BdNNHFknz5R0TEyCGTCETO10Ruol6g7GpHQLGuFoC3ec3b_C_eNlFryZe8Vq1ZTuEeIgzK5if_8Y9TtA0xkIqF2C3UmE8X_gxtztzivBKpb_rh0R4 |
link.rule.ids | 315,782,786,866,2106,27933,27934 |
linkProvider | Directory of Open Access Journals |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Snow+Thickness+Estimation+on+First-Year+Sea+Ice+from+Late+Winter+Spaceborne+Scatterometer+Backscatter+Variance&rft.jtitle=Remote+sensing+%28Basel%2C+Switzerland%29&rft.au=Yackel%2C+John&rft.au=Geldsetzer%2C+Torsten&rft.au=Mallik+Mahmud&rft.au=Nandan%2C+Vishnu&rft.date=2019-02-01&rft.pub=MDPI+AG&rft.eissn=2072-4292&rft.volume=11&rft.issue=4&rft_id=info:doi/10.3390%2Frs11040417&rft.externalDBID=HAS_PDF_LINK |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2072-4292&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2072-4292&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2072-4292&client=summon |