Expedited generation of terrain digital classes in flat areas from UAV images for precision agriculture purposes

Simple item page
dc.contributor.authorPineda, María Corina
dc.contributor.authorPerdomo, C.
dc.contributor.authorCaballero, R.
dc.contributor.authorValera, A.
dc.contributor.authorMartínez Casasnovas, José Antonio
dc.contributor.authorViloria, J.
dc.date.accessioned2017-09-21T07:49:13Z
dc.date.available2018-03-21T23:32:05Z
dc.date.issued2017-07-16
dc.date.updated2017-09-21T07:49:15Z
dc.descriptionProceedings of the 11th European Conference on Precision Agriculture
dc.description.abstractPrecision agriculture (PA) requires reasonably homogeneous areas for site-specific management. This work explores the applicability of digital terrain classes obtained from a digital elevation model derived from UAV-acquired images, to define management units in in a relative flat area of about 6 ha. Elevation, together with other terrain variables such as: slope degree, profile curvature, plan curvature, topographic wetness index, sediment transport index, were clustered using the Fuzzy Kohonen Clustering Network (FKCN). Four terrain classes were obtained. The result was compared with a map produced by a classification of soil properties previously interpolated by ordinary kriging. The results suggest that areas for site-specific management can be defined from terrain classes based on environmental covariates, saving time and cost in comparison with interpolation of soil variables.
dc.description.sponsorshipThis research was funded by the Venezuelan Organic Law for Science and Technology (LOCTI) and the Consejo de Desarrollo Cientí fi co y Humanístico (Council of Scienti fi c and Humanistic Development) of the Universidad Central de Venezuela (CDCH-UCV). We are also grateful to the International Centre for Theoretical Physics (Trieste, Italy) for the financial support and fellowships
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1017/S2040470017000322
dc.identifier.idgrec025828
dc.identifier.issn2040-4700
dc.identifier.urihttp://hdl.handle.net/10459.1/60244
dc.language.isoeng
dc.publisherThe Animal Consortium
dc.relation.isformatofVersió postprint del document publicat a: https://doi.org/10.1017/S2040470017000322
dc.relation.ispartofAdvances in Animal Biosciences, 2017, vol. 8, núm. 2, p. 828-832
dc.rights(c) The Animal Consortium, 2017
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.subjectUAV
dc.subjectKriging
dc.subjectsoil properties
dc.subjectTerrain variables
dc.titleExpedited generation of terrain digital classes in flat areas from UAV images for precision agriculture purposes
dc.typeinfo:eu-repo/semantics/article
dc.type.versionacceptedVersion
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
025828.pdf
Size:
679.26 KB
Format:
Adobe Portable Document Format
Description:
Postprint
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Articles publicats (Química, Física i Ciències Ambientals i del Sòl)
Articles publicats (Agrotecnio Center)
Articles publicats (Grup de Recerca en AgròTICa i Agricultura de Precisió)