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dc.contributor.authorSaura, José Ramón
dc.contributor.authorReyes-Menéndez, Ana
dc.contributor.authorPalos-Sánchez, Pedro R
dc.date2019-02
dc.date.accessioned2019-04-22T07:43:15Z
dc.date.available2019-04-22T07:43:15Z
dc.identifier.issn2405-8440
dc.identifier.urihttps://reunir.unir.net/handle/123456789/8213
dc.description.abstractDue to technology development related to agricultural production, aircrafts such as the Unmanned Aerial Vehicle (UAV) and technologies such as Multispectral photogrammetry and Remote Sensing, have great potential in supporting some of the pressing problems faced by agricultural production in terms of analysis and testing of variables. This paper reports an experience related to the analysis of a vineyard with multispectral photogrammetry technology and UAVs and it demonstrates its great potential to analyze the Normalized Difference Vegetation Index (NDVI), the Near-Infrared Spectroscopy (NIRS) and the Digital Elevation Model (DEM) applied in the agriculture framework to collect information on the vegetative state of the crop, soil and plant moisture, and biomass density maps of. In addition, the collected information is analyzed with the PIX4D Cloud Computing technology software and its advantages over software that work with other data processing are highlighted. This research shows, therefore, the possibility that efficient plantations can be developed with the use of multispectral photogrammetry and the analysis of digital images from this process.es_ES
dc.language.isoenges_ES
dc.publisherHeliyones_ES
dc.relation.ispartofseries;vol. 5, nº 2
dc.relation.urihttps://www.sciencedirect.com/science/article/pii/S2405844018328184?via%3Dihubes_ES
dc.rightsopenAccesses_ES
dc.subjectcomputer sciencees_ES
dc.subjectenvironmental sciencees_ES
dc.subjectgeosciencees_ES
dc.subjectEmerginges_ES
dc.subjectScopuses_ES
dc.titleMapping multispectral Digital Images using a Cloud Computing software: applications from UAV imageses_ES
dc.typeArticulo Revista Indexadaes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttp://dx.doi.org/10.1016/j.heliyon.2019.e01277


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