@InProceedings{SantosBaptMour:2017:SaÍnVe,
author = "Santos, Cloves Vilas Boas dos and Baptista, Gustavo Macedo de
Mello and Moura, Magna Soelma Beserra de",
title = "Sazonalidade do {\'{\I}}ndice de Vegeta{\c{c}}{\~a}o por
Diferen{\c{c}}a Normalizada (NDVI) a partir de dados do sensor
OLI em {\'a}rea de Caatinga e Pastagem",
booktitle = "Anais...",
year = "2017",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "6679--6685",
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 = "Remote Sensing has been used in surveys with greater frequency to
allow the analysis of the surface without the contact with the
targets, allowing to identify biophysical conditions of the
vegetation and understanding its photosynthetic dynamics. This
study aimed to analyze the seasonal behavior of the Normalized
Difference Vegetation Index (NDVI) in the Caatinga area. The study
was carried out in an area with predominance of Caatinga and
Pasture, in Petrolina-PE. We used 14 multispectral images of the
OLI sensor representing rainy and dry periods between 2013 and
2015. NDVI was determined using the red and infrared bands.
Precipitation (P) was recorded through a micrometeorological
station in order to understand the relationship between NDVI and
the occurrence of rainfall in the region. The results showed
seasonal variations throughout the studied period, with higher
NDVI values in January / 2014 for the Caatinga area reaching
0.628, and in June / 2014 for Pasture reaching 0.333. The lowest
indexes occurred before the rainy season, with 0.313 in September
/ 2014 in the Caatinga and 0.128 in October / 2013 in the Pasture.
The NDVI and P ratio in the studied areas showed similarity
between May / 2013 and June / 2014, and January / 2015, differing
in September / 2014 and between August and November / 2015, when
the lowest precipitation values . This is justified by the
reduction of the photosynthetic activity of the plants in this
period, with the absence of water in the soil. Therefore, with the
use of multispectral data it was possible to analyze the
photosynthetic dynamics of the vegetation, identifying that this
dynamics is related to the rainfall.",
conference-location = "Santos",
conference-year = "28-31 maio 2017",
isbn = "978-85-17-00088-1",
label = "59508",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3PSMDC7",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMDC7",
targetfile = "59508.pdf",
type = "Landsat OLI",
urlaccessdate = "27 abr. 2024"
}