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dc.contributor.author
de la Casa, Antonio Carlos

dc.contributor.author
Ovando, Gustavo

dc.contributor.author
Ravelo, Andres Carlos

dc.contributor.author
Abril, Ernesto Guillermo

dc.contributor.author
Bergamaschi, H.
dc.date.available
2018-01-24T17:39:03Z
dc.date.issued
2014-02
dc.identifier.citation
de la Casa, Antonio Carlos; Ovando, Gustavo; Ravelo, Andres Carlos; Abril, Ernesto Guillermo; Bergamaschi, H.; Estimating maize ground cover using spectral data from Aqua-MODIS in Córdoba, Argentina; Taylor & Francis; International Journal of Remote Sensing; 35; 4; 2-2014; 1295-1308
dc.identifier.issn
0143-1161
dc.identifier.uri
http://hdl.handle.net/11336/34414
dc.description.abstract
Ground cover by foliage is a biophysical property of vegetation linked both to the interception of photosynthetically active radiation and to the crop transpiration rate. The spectral information provided by the Moderate Resolution Imaging Spectroradiometer on board the Aqua (Aqua-MODIS) satellite, which has a spatial resolution of 250 m, is an observation and monitoring resource that may be appropriate for estimating the ground cover of maize when plots exceed 40 ha. In this research, 10 maize plots were monitored in the central region of the province of Córdoba, Argentina, during the 2005–2006 growing season, obtaining photographic records of ground cover and soil moisture data. The normalized difference vegetation index (NDVI) of the Aqua-MODIS images showed a significant linear relationship with maize ground cover which, when the complete cycle is taken into account, is sufficient to explain 87% of the variability of ground cover, with an RMSE of 9%, a level of accuracy that increases when the crop is in the vegetative stage and the moisture conditions of the soil are less limiting. Other vegetation indices and linear mixed models were assessed. In addition to using data from the red and near-infrared channels, they incorporate information about soil conditions, but they showed no predictive advantages compared to the NDVI, resulting in simple models that explained between 77% and 87% of the variability of ground cover, with RMSE values of between 9% and 14%.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Taylor & Francis

dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Suelo
dc.subject
Cordoba
dc.subject
Modis
dc.subject
Maize
dc.subject.classification
Agricultura

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Agricultura, Silvicultura y Pesca

dc.subject.classification
CIENCIAS AGRÍCOLAS

dc.title
Estimating maize ground cover using spectral data from Aqua-MODIS in Córdoba, Argentina
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-01-24T14:45:38Z
dc.journal.volume
35
dc.journal.number
4
dc.journal.pagination
1295-1308
dc.journal.pais
Reino Unido

dc.journal.ciudad
Londres
dc.description.fil
Fil: de la Casa, Antonio Carlos. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina
dc.description.fil
Fil: Ovando, Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Ravelo, Andres Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Abril, Ernesto Guillermo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.fil
Fil: Bergamaschi, H.. Universidade Federal do Rio Grande do Sul; Brasil
dc.journal.title
International Journal of Remote Sensing

dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1080/01431161.2013.876119
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.tandfonline.com/doi/abs/10.1080/01431161.2013.876119
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