| 1. Identity statement | ||||
| Reference Type | Journal Article | |||
| Site | mtc-m21c.sid.inpe.br | |||
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S | |||
| Identifier | 8JMKD3MGP3W34R/3SPH8FE | |||
| Repository | sid.inpe.br/mtc-m21c/2019/02.18.11.35 (restricted access) | |||
| Last Update | 2019:02.18.11.35.54 (UTC) administrator | |||
| Metadata Repository | sid.inpe.br/mtc-m21c/2019/02.18.11.35.54 | |||
| Metadata Last Update | 2020:01.06.11.42.10 (UTC) administrator | |||
| DOI | 10.3390/jmse7020036 | |||
| ISSN | 2077-1312 | |||
| Citation Key | GenovezJoneSantFrei:2019:OiSlCh | |||
| Title | Oil slick characterization using a statistical region-based classifier applied to UAVSAR data  | |||
| Year | 2019 | |||
| Month | Feb. | |||
| Access Date | 2025, Apr. 26 | |||
| Type of Work | journal article | |||
| Secondary Type | PRE PI | |||
| Number of Files | 1 | |||
| Size | 8023 KiB | |||
| 2. Context | ||||
| Author | 1 Genovez, Patrícia Carneiro 2 Jones, Cathleen E. 3 Sant'Anna, Sidnei João Siqueira 4 Freitas, Corina da Costa | |||
| Resume Identifier | 1 2 3 8JMKD3MGP5W/3C9JJ8N | |||
| Group | 1 DIDPI-CGOBT-INPE-MCTIC-GOV-BR 2 3 DIDPI-CGOBT-INPE-MCTIC-GOV-BR 4 DIDPI-CGOBT-INPE-MCTIC-GOV-BR | |||
| Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Jet Propulsion Laboratory (JPL), California Institute of Technology 3 Instituto Nacional de Pesquisas Espaciais (INPE) 4 Instituto Nacional de Pesquisas Espaciais (INPE) | |||
| Author e-Mail Address | 1 genovez.oilspill@gmail.com 2 cathleen.e.jones@jpl.nasa.gov 3 sidnei.santanna@inpe.br 4 corina.freitas@gmail.com | |||
| Journal | Journal of Marine Science and Engineering | |||
| Volume | 7 | |||
| Number | 2 | |||
| Pages | e36 | |||
| History (UTC) | 2019-02-18 11:36:17 :: simone -> administrator :: 2019 2020-01-06 11:42:10 :: administrator -> simone :: 2019 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Content Type | External Contribution | |||
| Version Type | publisher | |||
| Keywords | oil slicks characterization oil thickness polarized SAR data polarimetric SAR data (PolSAR) statistical region-based classification uncertainty maps UAVSAR | |||
| Abstract | During emergency responses to oil spills on the sea surface, quick detection and characterization of an oil slick is essential. The use of Synthetic Aperture Radar (SAR) in general and polarimetric SAR (PolSAR) in particular to detect and discriminate mineral oils from look-alikes is known. However, research exploring its potential to detect oil slick characteristics, e.g., thickness variations, is relatively new. Here a Multi-Source Image Processing System capable of processing optical, SAR and PolSAR data with proper statistical models was tested for the first time for oil slick characterization. An oil seep detected by NASAs Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) in the Gulf of Mexico was used as a study case. This classifier uses a supervised approach to compare stochastic distances between different statistical distributions (fx) and hypothesis tests to associate confidence levels to the classification results. The classifier was able to detect zoning regions within the slick with high global accuracies and low uncertainties. Two different classes, likely associated with the thicker and thinner oil layers, were recognized. The best results, statistically equivalent, were obtained using different data formats: polarimetric, intensity pair and intensity single-channel. The presence of oceanic features in the form of oceanic fronts and internal waves created convergence zones that defined the shape, spreading and concentration of the thickest layers of oil. The statistical classifier was able to detect the thicker oil layers accumulated along these features. Identification of the relative thickness of spilled oils can increase the oil recovery efficiency, allowing better positioning of barriers and skimmers over the thickest layers. Decision makers can use this information to guide aerial surveillance, in situ oil samples collection and clean-up operations in order to minimize environmental impacts. | |||
| Area | SRE | |||
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Oil slick characterization... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
| |||
| 4. Conditions of access and use | ||||
| Language | en | |||
| Target File | genovez_oil.pdf | |||
| User Group | simone | |||
| Visibility | shown | |||
| Read Permission | deny from all and allow from 150.163 | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Next Higher Units | 8JMKD3MGPCW/3EQCCU5 | |||
| Dissemination | WEBSCI; PORTALCAPES; SCOPUS. | |||
| Host Collection | urlib.net/www/2017/11.22.19.04 | |||
| 6. Notes | ||||
| Empty Fields | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url | |||
| 7. Description control | ||||
| e-Mail (login) | simone | |||
| update | ||||