dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:27:17Z
dc.date.available2014-05-27T11:27:17Z
dc.date.created2014-05-27T11:27:17Z
dc.date.issued2012-12-01
dc.identifierInternational Geoscience and Remote Sensing Symposium (IGARSS), p. 808-811.
dc.identifier2153-6996
dc.identifierhttp://hdl.handle.net/11449/73817
dc.identifier10.1109/IGARSS.2012.6351439
dc.identifierWOS:000313189401008
dc.identifier2-s2.0-84873163079
dc.identifier2985771102505330
dc.identifier0000-0003-0516-0567
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.
dc.languageeng
dc.relationInternational Geoscience and Remote Sensing Symposium (IGARSS)
dc.rightsAcesso aberto
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 sample
dc.typeActas de congresos


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