@InProceedings{MoreiraTeixGalv:2015:UtÍnVe,
author = "Moreira, Luis Clenio J{\'a}rio and Teixeira, Adunias dos Santos
and Galv{\~a}o, L{\^e}nio Soares",
affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Utiliza{\c{c}}{\~a}o de {\'{\i}}ndices de
vegeta{\c{c}}{\~a}o obtidos de dados multiespectrais e
hiperespectrais para detectar estresse salino na cultura do
arroz",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "2387--2394",
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 = "The purpose of this study was to evaluate multispectral and
hyperspectral vegetation indices aimed at characterizing soil
salinization from spectral information of rice canopies. The work
was performed using plots of rice in the same phenological stage
in the second semester of 2013. With a GPS rover, sampling points
were marked in the field and then the electrical conductivity (EC)
of the soil was measured. Four multispectral vegetation indices
(OLI sensor/Landsat-8) and 10 hyperspectral indices
(Hyperion/EO-1) were computed. Linear regression was used to
describe the relationship between the indices and EC. Spectral
information from the Red (R) vs near infrared (NIR) was plotted
against EC soil above and below 3.00 dS/m. Spectra of the
extracted images indicated an increasing reflectance in red and
reducing in NIR and mid infrared (SWIR) with increasing soil EC.
In the NIR region, the separation of pixels under stress (EC> 3.00
dS/m) from pixels under normal conditions (EC <3.00dS/m) presented
good performance. In the evaluation of multispectral indices, the
Normalized Difference Vegetation Index (NDVI) and Enhanced
Vegetation Index (EVI) showed the best results with R2 of 0.68 and
0.70, respectively. The most promising hyperspectral index is the
Salinity and Water Stress Index (SWSI1) with R2 = 0.70. Therefore,
from both (OLI and Hyperion) sensors, changes in the canopy
reflectance of rice under stress.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "481",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM49UB",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM49UB",
targetfile = "p0481.pdf",
type = "Sensoriamento remoto hiperespectral",
urlaccessdate = "27 abr. 2024"
}