Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes

ABSTRACT In the framework of a continuous search for technological innovations that allow fruit growers to practice a more competitive and sustainable fruit production, satellite-derived vegetation indexes could be used as tools to support the decision-making processes of technicians and territory p...

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Autores principales:	von Bennewitz Alvarez,Eduardo, Cazanga-Solar,Rodrigo, Carrasco-Benavides,Marcos
Lenguaje:	English
Publicado:	Universidad de Tarapacá. Facultad de Ciencias Agronómicas 2018
Materias:	Fruit trees Landsat 7 (ETM+) NDVI phenology SAVI
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-34292018000100065
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spelling	oai:scielo:S0718-342920180001000652019-04-04Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexesvon Bennewitz Alvarez,EduardoCazanga-Solar,RodrigoCarrasco-Benavides,Marcos Fruit trees Landsat 7 (ETM+) NDVI phenology SAVI ABSTRACT In the framework of a continuous search for technological innovations that allow fruit growers to practice a more competitive and sustainable fruit production, satellite-derived vegetation indexes could be used as tools to support the decision-making processes of technicians and territory planners. The objectives of the present study were to characterize phenological stages of cherry trees (Prunus avium L.) in the Maule region of Chile using field observations and to evaluate the capacity of multispectral satellite imagery (Landsat ETM+) and the derived vegetative indexes (NDVI, SAVI), as tools for remotely identifying these phenological stages in cherry trees. Phenological transition stages in cherry trees, estimated from Landsat 7 (ETM+) data did not agree with in situ measurements of phenology made at the different sites. Landsat 7 (ETM+) derived vegetation indices (NDVI, SAVI) could discriminate only gross changes associated with an increase and then a decrease of canopy greenness in cherry trees, but could not discriminate between successive phenological states in which the proportion of foliage is only slightly different. The number of days after the first of July (Southern Hemisphere) tended to be a less variable indicator than growing degree-days (GDD) for predicting the occurrence of different phenological stages in cherry trees.info:eu-repo/semantics/openAccessUniversidad de Tarapacá. Facultad de Ciencias AgronómicasIdesia (Arica) v.36 n.1 20182018-03-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-34292018000100065en10.4067/S0718-34292018000100065
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Fruit trees Landsat 7 (ETM+) NDVI phenology SAVI
spellingShingle	Fruit trees Landsat 7 (ETM+) NDVI phenology SAVI von Bennewitz Alvarez,Eduardo Cazanga-Solar,Rodrigo Carrasco-Benavides,Marcos Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes
description	ABSTRACT In the framework of a continuous search for technological innovations that allow fruit growers to practice a more competitive and sustainable fruit production, satellite-derived vegetation indexes could be used as tools to support the decision-making processes of technicians and territory planners. The objectives of the present study were to characterize phenological stages of cherry trees (Prunus avium L.) in the Maule region of Chile using field observations and to evaluate the capacity of multispectral satellite imagery (Landsat ETM+) and the derived vegetative indexes (NDVI, SAVI), as tools for remotely identifying these phenological stages in cherry trees. Phenological transition stages in cherry trees, estimated from Landsat 7 (ETM+) data did not agree with in situ measurements of phenology made at the different sites. Landsat 7 (ETM+) derived vegetation indices (NDVI, SAVI) could discriminate only gross changes associated with an increase and then a decrease of canopy greenness in cherry trees, but could not discriminate between successive phenological states in which the proportion of foliage is only slightly different. The number of days after the first of July (Southern Hemisphere) tended to be a less variable indicator than growing degree-days (GDD) for predicting the occurrence of different phenological stages in cherry trees.
author	von Bennewitz Alvarez,Eduardo Cazanga-Solar,Rodrigo Carrasco-Benavides,Marcos
author_facet	von Bennewitz Alvarez,Eduardo Cazanga-Solar,Rodrigo Carrasco-Benavides,Marcos
author_sort	von Bennewitz Alvarez,Eduardo
title	Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes
title_short	Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes
title_full	Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes
title_fullStr	Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes
title_full_unstemmed	Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes
title_sort	studying phenological stages of cherry (prunus avium l.) using field observations and satellite-derived vegetation indexes
publisher	Universidad de Tarapacá. Facultad de Ciencias Agronómicas
publishDate	2018
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-34292018000100065
work_keys_str_mv	AT vonbennewitzalvarezeduardo studyingphenologicalstagesofcherryprunusaviumlusingfieldobservationsandsatellitederivedvegetationindexes AT cazangasolarrodrigo studyingphenologicalstagesofcherryprunusaviumlusingfieldobservationsandsatellitederivedvegetationindexes AT carrascobenavidesmarcos studyingphenologicalstagesofcherryprunusaviumlusingfieldobservationsandsatellitederivedvegetationindexes
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Studying phenological stages of cherry (Prunus avium L.) using field observations and satellite-derived vegetation indexes

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