Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/9710
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dc.contributor.authorallPicchiani, M.; University of Rome Tor Vergataen
dc.contributor.authorallChini, M.; Luxembourg Institute of Science and Technologyen
dc.contributor.authorallCorradini, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italiaen
dc.contributor.authorallMerucci, L.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italiaen
dc.contributor.authorallPiscini, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italiaen
dc.contributor.authorallDel Frate, F.; University of Rome Tor Vergataen
dc.date.accessioned2015-06-03T07:26:43Zen
dc.date.available2015-06-03T07:26:43Zen
dc.date.issued2014en
dc.identifier.urihttp://hdl.handle.net/2122/9710en
dc.description.abstractThis work shows the potential use of neural networks in the characterization of eruptive events monitored by satellite, through fast and automatic classification of multispectral images. The algorithm has been developed for the MODIS instrument and can easily be extended to other similar sensors. Six classes have been defined paying particular attention to image regions that represent the different surfaces that could possibly be found under volcanic ash clouds. Complex cloudy scenarios composed by images collected during the Icelandic eruptions of the Eyjafjallajökull (2010) and Grimsvötn (2011) volcanoes have been considered as test cases. A sensitivity analysis on the MODIS TIR and VIS channels has been performed to optimize the algorithm. The neural network has been trained with the first image of the dataset, while the remaining data have been considered as independent validation sets. Finally, the neural network classifier’s results have been compared with maps classified with several interactive procedures performed in a consolidated operational framework. This comparison shows that the automatic methodology proposed achieves a very promising performance, showing an overall accuracy greater than 84%, for the Eyjafjallajökull event, and equal to 74% for the Grimsvötn event.en
dc.language.isoEnglishen
dc.relation.ispartofAnnals of Geophysicsen
dc.relation.ispartofseriesfast track 2/57(2014)en
dc.subjectremote sensing; ash detection; neural networks; MODISen
dc.titleNeural network multispectral satellite images classification of volcanic ash plumes in a cloudy scenarioen
dc.typearticleen
dc.description.statusPublisheden
dc.type.QualityControlPeer-revieweden
dc.subject.INGV04. Solid Earth::04.08. Volcanology::04.08.06. Volcano monitoringen
dc.subject.INGV04. Solid Earth::04.08. Volcanology::04.08.07. Instruments and techniquesen
dc.subject.INGV05. General::05.02. Data dissemination::05.02.03. Volcanic eruptionsen
dc.identifier.doi10.4401/ag-6638en
dc.description.obiettivoSpecifico5V. Sorveglianza vulcanica ed emergenzeen
dc.description.obiettivoSpecifico5IT. Osservazioni satellitarien
dc.description.journalTypeJCR Journalen
dc.description.fulltextopenen
dc.contributor.authorPicchiani, M.en
dc.contributor.authorChini, M.en
dc.contributor.authorCorradini, S.en
dc.contributor.authorMerucci, L.en
dc.contributor.authorPiscini, A.en
dc.contributor.authorDel Frate, F.en
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italiaen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italiaen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italiaen
dc.contributor.departmentUniversity of Rome Tor Vergataen
item.openairetypearticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
crisitem.author.deptLuxembourg Institute of Science and Technology (LIST)-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italia-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italia-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italia-
crisitem.author.orcid0000-0002-4120-200X-
crisitem.author.orcid0000-0001-9432-3246-
crisitem.author.orcid0000-0001-6910-8800-
crisitem.author.orcid0000-0001-5545-3611-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent05. General-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
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