Relationship between coffee crop productivity and vegetation indexes derived from oli / landsat-8 sensor data with and without topographic correction

dc.contributor.authorNogueira, Sulimar M. C.
dc.contributor.authorMoreira, Maurício A.
dc.contributor.authorVolpato, Margarete M. L.
dc.date.accessioned2018-12-20T10:44:11Z
dc.date.available2018-12-20T10:44:11Z
dc.date.issued2018-05
dc.description.abstractThe reflectance values of a coffee crop are influenced by several factors such as planting direction, crop spacing, time of the year, plant age and topography which reduces the accuracy of the estimates derived from remote sensing data. In this context were evaluated the relationships between coffee productivity and values of NDVI, SAVI and NDWI vegetation indexes with and without topographic reflectance correction for different coffee phenological phases for the crop years 2013/2014 (low productivity) and 2014/2015 (high productivity). The evaluations were made through the standard deviation of vegetation indices (VIs), linear relationship between the cosine factor and the VIs and between VIs and coffee productivity. The best phenological phases of coffee to determine productivity from spectral indexes were the stages of dormancy and flowering. The results indicated that the NDVI was the best index to estimate the productivity of coffee trees with coefficient of determination (R2) that ranged from 0.58 to 0.90. There was an increase in R2 between productivity and NDVI with topographic correction in the dormancy phase in the year of low productivity; between productivity and NDVI with topographic correction in the flowering phase in the year of high productivity; and between productivity and SAVI and NDWI with topographic corrections in the flowering phase in the year of high productivity.pt_BR
dc.formatpdfpt_BR
dc.identifier.citationNOGUEIRA, S. M. C.; MOREIRA, M. A.; VOLPATO, Margarete M. L. Relationship between coffee crop productivity and vegetation indexes derived from oli / landsat-8 sensor data with and without topographic correction. Engenharia Agrícola, Jaboticabal, v.38, n.3, p.387-394, mai./jun. 2018.pt_BR
dc.identifier.issn1809-4430
dc.identifier.urihttp://dx.doi.org/10.1590/1809-4430-Eng.Agric.v38n3p387-394/2018pt_BR
dc.identifier.urihttp://www.sbicafe.ufv.br/handle/123456789/10712
dc.language.isoenpt_BR
dc.publisherAssociação Brasileira de Engenharia Agrícolapt_BR
dc.relation.ispartofseriesEngenharia Agrícola;v.38, n.3, p.387-394, 2018;
dc.rightsOpen Accesspt_BR
dc.subjectCoffeept_BR
dc.subjectNDVIpt_BR
dc.subjectNDWIpt_BR
dc.subjectYieldpt_BR
dc.subjectSAVIpt_BR
dc.subjectRemote sensingpt_BR
dc.subject.classificationCafeicultura::Implantação e manejo da lavourapt_BR
dc.titleRelationship between coffee crop productivity and vegetation indexes derived from oli / landsat-8 sensor data with and without topographic correctionpt_BR
dc.typeArtigopt_BR

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