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dc.contributor.authorAguilar Torres, Manuel
dc.contributor.authorBianconi Pettirossi, Francesco
dc.contributor.authorAguilar Torres, Fernando José
dc.contributor.authorFernández Luque, Ismael
dc.date.accessioned2020-01-16T11:03:46Z
dc.date.available2020-01-16T11:03:46Z
dc.date.issued2014-04-25
dc.identifier.issn2072-4292
dc.identifier.urihttp://hdl.handle.net/10835/7370
dc.description.abstractRemote sensing technologies have been commonly used to perform greenhouse detection and mapping. In this research, stereo pairs acquired by very high-resolution optical satellites GeoEye-1 (GE1) and WorldView-2 (WV2) have been utilized to carry out the land cover classification of an agricultural area through an object-based image analysis approach, paying special attention to greenhouses extraction. The main novelty of this work lies in the joint use of single-source stereo-photogrammetrically derived heights and multispectral information from both panchromatic and pan-sharpened orthoimages. The main features tested in this research can be grouped into different categories, such as basic spectral information, elevation data (normalized digital surface model; nDSM), band indexes and ratios, texture and shape geometry. Furthermore, spectral information was based on both single orthoimages and multiangle orthoimages. The overall accuracy attained by applying nearest neighbor and support vector machine classifiers to the four multispectral bands of GE1 were very similar to those computed from WV2, for either four or eight multispectral bands. Height data, in the form of nDSM, were the most important feature for greenhouse classification. The best overall accuracy values were close to 90%, and they were not improved by using multiangle orthoimages.es_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectobject-based classificationes_ES
dc.subjectgreenhouseses_ES
dc.subjectGeoEye-1es_ES
dc.subjectWorldView-2es_ES
dc.subjectnormalized digital surface modeles_ES
dc.subjectmultiangle imagees_ES
dc.titleObject-Based Greenhouse Classification from GeoEye-1 and WorldView-2 Stereo Imageryes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://www.mdpi.com/2072-4292/6/5/3554es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional