@InProceedings{OliveiraFrei:2015:AnCoO,
author = "Oliveira, Gabriel Cury Martins de and Freitas, Marcos Aur{\'e}lio
Vasconcelos de",
title = "An{\'a}lise de correla{\c{c}}{\~o}es entre o {\'{\i}}ndice de
vegeta{\c{c}}{\~a}o por diferen{\c{c}}a normalizada (NDVI) e
dados hidrometeorol{\'o}gicos do entorno do reservat{\'o}rio da
usina hidrel{\'e}trica de Tucuru{\'{\i}}-PA utilizando imagens
Landsat-5 TM",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "771--776",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
abstract = "Different vegetation indices can be estimated from the remote
sensing image data held in the red and near infrared bands, easily
obtained from Landsat series imagery. In this paper the normalized
difference vegetation index (NDVI) was used to evaluate the
vegetation distribution on nine scenes obtained from the TM sensor
on board of Landsat 5 satellite, that compose the mosaic of the
Tucuru{\'{\i}} Hydropower Plant surroundings, in Par{\'a}
state. In order to compare the changes in the land use and land
cover was assessed in three different periods, viz. 1986, 1997 and
2010. After the NDVI was calculated and classified, the total
areas concerning each class (in terms of amount of pixels) were
correlated with physical parameters measured in
hydrometeorological stations. High correlation values were
encountered, which indicates that the presence and distribution of
the canopy influence the state of the parameters, such as
temperature, nebulosity and precipitation, amongst others.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "144",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM474H",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM474H",
targetfile = "p0144.pdf",
type = "Floresta e vegeta{\c{c}}{\~a}o",
urlaccessdate = "07 maio 2024"
}