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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73817
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dc.contributor.authorRotta, Luiz Henrique Da Silva-
dc.contributor.authorImai, Nilton Nobuhiro-
dc.date.accessioned2014-05-27T11:27:17Z-
dc.date.accessioned2016-10-25T18:40:02Z-
dc.date.available2014-05-27T11:27:17Z-
dc.date.available2016-10-25T18:40:02Z-
dc.date.issued2012-12-01-
dc.identifierhttp://dx.doi.org/10.1109/IGARSS.2012.6351439-
dc.identifier.citationInternational Geoscience and Remote Sensing Symposium (IGARSS), p. 808-811.-
dc.identifier.issn2153-6996-
dc.identifier.urihttp://hdl.handle.net/11449/73817-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73817-
dc.description.abstractTraditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques. © 2012 IEEE.en
dc.format.extent808-811-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectGeographic Information Systems-
dc.subjectInterpolation-
dc.subjectRivers-
dc.subjectSubmerged aquatic vegetation-
dc.subjectUnderwater acoustics-
dc.subjectAquatic environments-
dc.subjectData sample-
dc.subjectEcho sounders-
dc.subjectGeo-statistics-
dc.subjectHeight estimation-
dc.subjectHigh costs-
dc.subjectInterpolation method-
dc.subjectKriging interpolation-
dc.subjectNearest neighbors-
dc.subjectOptical remote sensing-
dc.subjectOrdinary kriging-
dc.subjectSample data-
dc.subjectStudy case-
dc.subjectSubmerged aquatic vegetations-
dc.subjectSubmerged macrophytes-
dc.subjectSubmerged targets-
dc.subjectTriangular Irregular Networks-
dc.subjectWeighted averages-
dc.subjectGeographic information systems-
dc.subjectGeology-
dc.subjectRemote sensing-
dc.subjectSurveys-
dc.subjectVegetation-
dc.titleSubmerged macrophytes height estimation by echosounder data sampleen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationSão Paulo State University Postgraduate Course in Cartographic Sciences, Presidente Prudente - SP-
dc.description.affiliationUnespSão Paulo State University Postgraduate Course in Cartographic Sciences, Presidente Prudente - SP-
dc.identifier.doi10.1109/IGARSS.2012.6351439-
dc.identifier.wosWOS:000313189401008-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofInternational Geoscience and Remote Sensing Symposium (IGARSS)-
dc.identifier.scopus2-s2.0-84873163079-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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