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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3NNBSMH
Repositorysid.inpe.br/mtc-m21b/2017/04.17.19.37   (restricted access)
Last Update2017:04.17.19.37.04 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21b/2017/04.17.19.37.04
Metadata Last Update2018:06.04.02.27.23 (UTC) administrator
DOI10.1109/JSTARS.2016.2628325
ISSN1939-1404
2151-1535
Citation KeyGenovezFreSanBenLor:2017:OiSlDe
TitleOil Slicks Detection From Polarimetric data using stochastic distances between complex wishart distributions
Year2017
MonthFeb.
Access Date2024, May 10
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size6245 KiB
2. Context
Author1 Genovez, Patrícia Carneiro
2 Freitas, Corina da Costa
3 Sant'Anna, Sidnei João Siqueira
4 Bentz, Cristina Maria
5 Lorenzzetti, João Antônio
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JJ8N
4
5 8JMKD3MGP5W/3C9JHEF
Group1 SER-SRE-SESPG-INPE-MCTIC-GOV-BR
2 DIDPI-CGOBT-INPE-MCTIC-GOV-BR
3 DIDPI-CGOBT-INPE-MCTIC-GOV-BR
4
5 DIDSR-CGOBT-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Centro de Pesquisa da Petrobrás (CENPES)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 genovez.oilspill@gmail.com
2 corina@dpi.inpe.br
3 sidnei.santanna@inpe.br
4 cris@petrobras.com.br
5 joao.lorenzzetti@inpe.br
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume10
Number2
Pages463-477
History (UTC)2017-04-17 19:37:04 :: simone -> administrator ::
2017-04-17 19:37:04 :: administrator -> simone :: 2017
2017-04-17 19:37:58 :: simone -> administrator :: 2017
2017-06-30 23:50:07 :: administrator -> simone :: 2017
2017-12-14 17:01:16 :: simone -> administrator :: 2017
2018-06-04 02:27:23 :: administrator -> simone :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsInformation theory
oil slicks detection
polarimetry
region-based classification
stochastic distances
synthetic aperture radar (SAR)
uncertainty maps
AbstractPolarimetric synthetic aperture radars (PolSAR) have been used to detect oil slicks at the sea surface. Different techniques to extract information from polarimetric data, using an adequate statistical distribution are currently available. A region-based classifier for PolSAR data - named PolClass - uses a supervised approach to compare stochastic distances between scaled complex Wishart distributions and hypothesis tests to associate confidence levels into the classification results. In this paper, the integrated use of these distances together with the uncertainty maps is applied for the first time to detect oil slicks. A quad-pol Radarsat-2 data, acquired during one open-water controlled exercise, was used to perform this test. The PolClass achieved similar overall accuracies for four stochastic distances, reaching 96.54% of global accuracy, the best result obtained by the Hellinger distance. A comparison between the full-and dual-pol matrices indicated that the results obtained with the VV-HH-HV, HH-HV, and VV-HV polarizations are statistically equivalent, but different from that obtained using the HH-VV. Therefore, the exclusion of the HV channel affected the detection of only mineral oils. The classifier demonstrated the potential to detect the three types of oils released, being more effective in detecting biogenic oils rather than mineral oils. The uncertainty levels increase from the center to the border of the mineral oil slicks, indicating the presence of transition regions, possibly related to different weathering mechanisms. The proposed approach will contribute to the understanding of where different physical and chemical processes may be acting, associating confidence levels to the classification results.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Oil Slicks Detection...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Oil Slicks Detection...
Arrangement 3urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Oil Slicks Detection...
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4. Conditions of access and use
Languageen
Target Filegenovez_oil.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policydenypublisher allowfinaldraft
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ER446E
8JMKD3MGPCW/3F3NU5S
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.15.00.20 2
sid.inpe.br/bibdigital/2013/10.18.22.34 1
sid.inpe.br/bibdigital/2013/09.09.15.05 1
DisseminationWEBSCI; IEEEXplore.
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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