@InProceedings{ChavesAlveRodrTrin:2017:PeTeEV,
author = "Chaves, Michel Eust{\'a}quio Dantas and Alves, Marcelo de
Carvalho and Rodrigues, Julia Dal Poggetto and Trindade, Filipe
Silveira",
title = "Perfis temporais EVI/MODIS e sua rela{\c{c}}{\~a}o com a
produtividade de cultivares de soja no Estado de Mato Grosso",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "5968--5975",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Information derived from remote sensing can be extremely useful
for crop monitoring during the phenological cycle, and is relevant
for strategic planning of large-scale agriculture. Among the
outstanding sensors used with this purpose, the Moderate
Resolution Imaging Spectroradiometer (MODIS), which is aboard the
TERRA and AQUA satellites, is the most used because of its spatial
and temporal characteristics that are consistent with both crop
size and dynamics. The MODIS sensor provides daily data on
vegetation in the form of indexes, which includes, for example,
the Enhanced Vegetation Index (EVI) that is sensitive to
variations of biomass vigor elapsed during the phenological cycle.
In this context, the main purpose of this work was to evaluate the
relationship between the EVI vegetation index and the soybean
yield using the experimental field as representative of high and
low soybean yields obtained in partnership with Bom Futuro SA
Group. A total of three agglomerates of farms were evaluated in
the State of Mato Grosso, in which the two most cultivated soybean
cultivars of the 2010/2011 harvests (TMG 123 RR e TMG 132 RR) were
planted. To interpret the results, we used field information
regarding the phenological cycle. The results demonstrated the
close relationship between EVI and soybean yield, indicating the
potential of this index to monitor cultivation in Mato Grosso and
to assist in the elaboration of crop forecasting models.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "59694",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PSMC3H",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMC3H",
targetfile = "59694.pdf",
type = "Agricultura e pecu{\'a}ria",
urlaccessdate = "27 abr. 2024"
}