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dc.contributor.authorCuartero Sáez, Aurora-
dc.contributor.authorPaoletti Ávila, Mercedes Eugenia-
dc.contributor.authorRey Presas, Andrea-
dc.contributor.authorHaut Hurtado, Juan Mario-
dc.date.accessioned2024-02-02T08:59:37Z-
dc.date.available2024-02-02T08:59:37Z-
dc.date.issued2022-
dc.identifier.isbn978-1-6654-2792-0-
dc.identifier.urihttp://hdl.handle.net/10662/19713-
dc.descriptionPonencia presentada en IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.Kuala Lumpur, Malaysia, 17-22 July 2022-
dc.description.abstractAnalyzing directional data, in particular circular data, requires methods that are being available in libraries with a well-known prestige as Python including SciPy, NumPy or SciKit-Learn libs. An open-source library has been implemented to be executed by the Python interpreter, called PyCircularStats. Source code: https://github.com/mhaut/pycircularstats The potential of PyCircularStats is shown with an example of analyzing two-dimensional data using circular statistics. The practical case chosen is the positional accuracy analysis of a satellite image of LandSat-8 in Cáceres, Spain, with 99 control points taken with GNSS systems. In this work, the possibilities of two-dimensional data analysis using circular statistics using the PyCircularStats tool with the results of this case of use is presented.es_ES
dc.description.sponsorshipThe authors wish to acknowledge the funding received from the Consejería de Economía, Ciencia y Agenda Digital of the Junta de Extremadura, the European Regional Development Fund (ERDF) of the European Union through grant reference GR21040 and the Programa Estatal de I+D+i Orientada a los Retos de la Sociedad, Ministerio de Economía y Competitividad (PID2019-105221RB-C42) AEI /10.13039/501100011033. We also wish to thank Cáceres city Council for transfer of the IGCPs data for putting available so many free data of great positional accuracy.es_ES
dc.format.extent4 p.es_ES
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.subjectAnalysis dataes_ES
dc.subjectCircular graphical statisticses_ES
dc.subjectGeospatial big dataes_ES
dc.subjectRemote sensinges_ES
dc.subjectAnálisis de datoses_ES
dc.subjectEstadísticas de gráficos circulareses_ES
dc.subjectMacrodatos geoespaciales-
dc.subjectTeledetección-
dc.titleBi-dimensional vector data analysis of positional accuracy of landsat-8 image with pycircularstatses_ES
dc.typeConferenceObjectes_ES
dc.description.versionpeerReviewedes_ES
europeana.typeTEXTen_US
dc.rights.accessRightsclosedAccesses_ES
dc.subject.unesco2506.16 Teledetección (Geología)es_ES
dc.subject.unesco2504.04 Fotogrametría Geodésica-
europeana.dataProviderUniversidad de Extremadura. Españaes_ES
dc.identifier.bibliographicCitationA. Cuartero, M. E. Paoletti, A. R. Presas and J. M. Haut, "Bi-Dimensional Vector Data Analysis of Positional Accuracy of Landsat-8 Image with Pycircularstats," IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022, pp. 2442-2445, doi: 10.1109/IGARSS46834.2022.9883588.es_ES
dc.type.versionpublishedVersiones_ES
dc.contributor.affiliationN/Aes_ES
dc.contributor.affiliationUniversidad de Extremadura. Departamento de Expresión Gráficaes_ES
dc.contributor.affiliationDepartamento de Tecnología de los Computadores y de las Comunicaciones-
dc.contributor.affiliationUniversidad Complutense de Madrid-
dc.contributor.affiliationUniversidad de Santiago de Compostela-
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9883588es_ES
dc.identifier.doi10.1109/IGARSS46834.2022.9883588.-
dc.identifier.publicationtitleIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium-
dc.identifier.publicationfirstpage2442es_ES
dc.identifier.publicationlastpage2445es_ES
dc.identifier.orcid0000-0002-0219-9696es_ES
dc.identifier.orcid0000-0003-1030-3729es_ES
dc.identifier.orcid0000-0001-6701-961Xes_ES
Colección:DEXGR - Artículos

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