dc.creatorBrunsell, NA
dc.creatorPontes, PPB
dc.creatorLamparelli, RAC
dc.date2009
dc.dateJUL-SEP
dc.date2014-07-30T18:23:08Z
dc.date2015-11-26T17:47:11Z
dc.date2014-07-30T18:23:08Z
dc.date2015-11-26T17:47:11Z
dc.date.accessioned2018-03-29T00:29:48Z
dc.date.available2018-03-29T00:29:48Z
dc.identifierGiscience & Remote Sensing. Bellwether Publ Ltd, v. 46, n. 3, n. 289, n. 304, 2009.
dc.identifier1548-1603
dc.identifierWOS:000269625700003
dc.identifier10.2747/1548-1603.46.3.289
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/70882
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/70882
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1288708
dc.descriptionDue to complex microclimatic interactions, a biannual phenological cycle, and the generally small scale of coffee plantations, there have been few applications of satellite observations to examine coffee yield. Using 2001-2006 data, surface precipitation and air temperature are related to MODIS surface temperature and fractional vegetation. Using lagged correlation analysis and deviations from the annual cycle, yield is related to accumulated deviations in fractional vegetation. Results imply that the coarse spatial resolution of MODIS data is compensated for by high temporal coverage, which allows for determination of coffee phenology.
dc.description46
dc.description3
dc.description289
dc.description304
dc.descriptionCooxupe Ltda.
dc.descriptionDepartment of Geography
dc.descriptionCollege of Liberal Arts and Sciences
dc.languageen
dc.publisherBellwether Publ Ltd
dc.publisherColumbia
dc.publisherEUA
dc.relationGiscience & Remote Sensing
dc.relationGISci. Remote Sens.
dc.rightsfechado
dc.sourceWeb of Science
dc.subjectTranspiration
dc.subjectEnvironment
dc.subjectManagement
dc.subjectRipeness
dc.subjectImagery
dc.subjectRegion
dc.subjectCover
dc.subjectLeaf
dc.titleRemotely Sensed Phenology of Coffee and Its Relationship to Yield
dc.typeArtículos de revistas


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