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dc.contributor.authorCastillejo-González, I.L.
dc.date.accessioned2019-02-25T07:38:13Z
dc.date.available2019-02-25T07:38:13Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/10396/17924
dc.description.abstractThis study sought to verify whether remote sensing offers the ability to efficiently delineate olive tree canopies using QuickBird (QB) satellite imagery. This paper compares four classification algorithms performed in pixel- and object-based analyses. To increase the spectral and spatial resolution of the standard QB image, three different pansharpened images were obtained based on variations in the weight of the red and near infrared bands. The results showed slight differences between classifiers. Maximum Likelihood algorithm yielded the highest results in pixel-based classifications with an average overall accuracy (OA) of 94.2%. In object-based analyses, Maximum Likelihood and Decision Tree classifiers offered the highest precisions with average OA of 95.3% and 96.6%, respectively. Between pixel- and object-based analyses no clear difference was observed, showing an increase of average OA values of approximately 1% for all classifiers except Decision Tree, which improved up to 4.5%. The alteration of the weight of different bands in the pansharpen process exhibited satisfactory results with a general performance improvement of up to 9% and 11% in pixel- and object-based analyses, respectively. Thus, object-based analyses with the DT algorithm and the pansharpened imagery with the near-infrared band altered would be highly recommended to obtain accurate maps for site-specific management.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.sourceAgronomy 8(12), 288 (2018)es_ES
dc.subjectÁ Trous algorithmes_ES
dc.subjectConservation agriculturees_ES
dc.subjectCrop inventoryes_ES
dc.subjectRemote sensinges_ES
dc.subjectSpectralweight variations in fused imageses_ES
dc.titleMapping of Olive Trees Using Pansharpened QuickBird Images: An Evaluation of Pixel- and Object-Based Analyseses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttp://dx.doi.org/10.3390/agronomy8120288es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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