Identificador persistente para citar o vincular este elemento: https://accedacris.ulpgc.es/handle/10553/69802
DC FieldValueLanguage
dc.contributor.authorIbarrola-Ulzurrun, Edurneen_US
dc.contributor.authorMarcello, Javieren_US
dc.contributor.authorGonzalo Martin,Consueloen_US
dc.contributor.authorChanussot, Jocelynen_US
dc.date.accessioned2020-02-05T12:50:09Z-
dc.date.accessioned2020-05-07T08:42:26Z-
dc.date.available2020-02-05T12:50:09Z-
dc.date.available2020-05-07T08:42:26Z-
dc.date.issued2018en_US
dc.identifier.isbn9781538671504en_US
dc.identifier.issn2153-6996en_US
dc.identifier.otherScopus-
dc.identifier.otherWoS-
dc.identifier.urihttps://accedacris.ulpgc.es/handle/10553/69802-
dc.description.abstractEcosystem management and monitoring are essential to preserve natural resources. Hyperspectral imagery (HSI) is a useful tool to obtain accurate classification maps, providing significant level of detail. Thus, traditional and novel methodologies based on pixel and object classification approaches are compared and evaluated in a homogeneous and mixed vulnerable ecosystem. Considering the challenging ecosystem, all classifications successfully resulted in high OA (higher than 82%), showing that HSI is very useful providing accurate vegetation maps to evaluate and monitor the ecosystems in a faster and economic way.en_US
dc.languageengen_US
dc.relationProcesado Avanzado de Datos de Teledetección Para la Monitorización y Gestión Sostenible de Recursos Marinos y Terrestres en Ecosistemas Vulnerables.en_US
dc.relation.ispartofIEEE International Geoscience and Remote Sensing Symposium proceedingsen_US
dc.sourceIEEE International Geoscience and Remote Sensing Symposium proceedings [2153-6996],v. 2018-July, p. 5764-5767en_US
dc.subject220990 Tratamiento digital. Imágenesen_US
dc.subject.otherBinary Partition Treeen_US
dc.subject.otherCasi Sensoren_US
dc.subject.otherEcosystem Managementen_US
dc.subject.otherHyperspectral Imageryen_US
dc.subject.otherSupport Vector Machineen_US
dc.titleEvaluation of hyperspectral classification maps in heterogeneous ecosystemen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conferenceIEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018)en_US
dc.identifier.doi10.1109/IGARSS.2018.8518308en_US
dc.identifier.scopus85060683651-
dc.identifier.isi000451039805149-
dc.contributor.authorscopusid57193098496-
dc.contributor.authorscopusid6602158797-
dc.contributor.authorscopusid36561411500-
dc.contributor.authorscopusid6602159365-
dc.description.lastpage5767en_US
dc.description.firstpage5764en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid5530081-
dc.contributor.daisngid702897-
dc.contributor.daisngid1398100-
dc.contributor.daisngid43565-
dc.description.numberofpages4en_US
dc.identifier.eisbn978-1-5386-7150-4-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Ibarrola-Ulzurrun, E-
dc.contributor.wosstandardWOS:Marcello, J-
dc.contributor.wosstandardWOS:Gonzalo-Martin, C-
dc.contributor.wosstandardWOS:Chanussot, J-
dc.identifier.conferenceidevents121124-
dc.identifier.ulpgces
dc.contributor.buulpgcBU-TELen_US
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.project.principalinvestigatorMarcello Ruiz, Francisco Javier-
crisitem.author.deptGIR IOCAG: Procesado de Imágenes y Teledetección-
crisitem.author.deptIU de Oceanografía y Cambio Global-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0001-5062-7491-
crisitem.author.orcid0000-0002-9646-1017-
crisitem.author.parentorgIU de Oceanografía y Cambio Global-
crisitem.author.fullNameIbarrola Ulzurrun, Edurne-
crisitem.author.fullNameMarcello Ruiz, Francisco Javier-
crisitem.author.fullNameGonzalo Martin,Consuelo-
crisitem.event.eventsstartdate22-07-2018-
crisitem.event.eventsenddate27-07-2018-
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