Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/47789
Campo DC Valoridioma
dc.contributor.authorIbarrola-Ulzurrun, Edurneen_US
dc.contributor.authorMarcello, Javieren_US
dc.contributor.authorGonzalo Martin,Consueloen_US
dc.date.accessioned2018-11-23T16:25:32Z-
dc.date.available2018-11-23T16:25:32Z-
dc.date.issued2018en_US
dc.identifier.issn1860-949Xen_US
dc.identifier.urihttp://hdl.handle.net/10553/47789-
dc.description.abstractIn the last decades, there has been a decline in ecosystems natural resources. The objective of the study is to develop advanced image processing techniques applied to high resolution remote sensing imagery for the ecosystem conservation. The study area is focused in three ecosystems from The Canary Islands, Teide National Park, Maspalomas Natural Reserve and Corralejo and Islote de Lobos Natural Park. Different pre-processing steps have been applied in order to acquire high quality imagery. After an extensive analysis and evaluation of pansharpening techniques, Weighted Wavelet 'à trous’ through Fractal Dimension Maps, in Teide and Maspalomas scenes, and Fast Intensity Hue Saturation, in Corralejo scene, are used, then, a RPC (Rational Polymodal Coefficients) model performs the orthorectification and finally, the atmospheric correction is carried out by the 6S algorithm. The final step is to generate marine and terrestrial thematic products using advanced classification techniques for the management of natural resources. Accurate thematic maps have already been obtained in Teide National Park. A comparative study of both pixel-based and object-based (OBIA) approaches was carried out, obtaining the most accurate thematic maps in both of them using Support Vector Machine classifier.en_US
dc.languageengen_US
dc.publisher1860-949X-
dc.relation.ispartofStudies in Computational Intelligenceen_US
dc.sourceStudies in Computational Intelligence[ISSN 1860-949X],v. 718, p. 1-13en_US
dc.subject220990 Tratamiento digital. Imágenesen_US
dc.subject.otherRemote sensingen_US
dc.subject.otherHigh resolution imageen_US
dc.subject.otherPansharpeningen_US
dc.subject.otherOrthorectificationen_US
dc.subject.otherOBIAen_US
dc.titleAdvanced classification of remote sensing high resolution imagery. An application for the management of natural resourcesen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/978-3-319-58965-7_1en_US
dc.identifier.scopus85026303764-
dc.contributor.authorscopusid57193098496-
dc.contributor.authorscopusid6602158797-
dc.contributor.authorscopusid36561411500-
dc.description.lastpage13en_US
dc.description.firstpage1en_US
dc.relation.volume718en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.utils.revisionen_US
dc.date.coverdateEnero 2018en_US
dc.identifier.ulpgces
dc.description.sjr0,183
dc.description.sjrqQ4
item.grantfulltextnone-
item.fulltextSin texto completo-
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-
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