@InProceedings{RamírezAndeForm:2015:NoRaAu,
author = "Ram{\'{\i}}rez, F{\'a}tima Lorena Ben{\'{\i}}tez and
Anderson, Liana Oighenstein and Formaggio, Ant{\^o}nio Roberto",
affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Normaliza{\c{c}}{\~a}o radiom{\'e}trica automatizada para
gera{\c{c}}{\~a}o de mosaicos de imagens RapidEye sobre
paisagens amaz{\^o}nicas, atrav{\'e}s da
transforma{\c{c}}{\~a}o IR-MAD",
booktitle = "Anais...",
year = "2015",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
pages = "1292--1299",
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 = "Radiometric normalization for satellite images mosaics is very
important for monitoring and quantifying large scale land cover
changes. Thus, this paper aims to apply an automatic method for
radiometric normalization of imagery based on the iterative
re-weighted Multivariate Alternation Detection (IR-MAD)
transformation. The procedure was applied in two study areas, each
with different Amazonian landscape. With the purpose of using the
image mosaic in future studies in the Ecuadorian Amazon, the high
resolution images RapidEye were selected. The RapidEye satellites
are distinguished from most other multispectral satellites by the
presence of a RedEdge band, which is relevant for vegetation
characterization. The results of this procedure for mosaicking
RapidEye images over the Amazon showed that the 500 meters overlap
between the adjacent images tiles were not large enough for the
IR-MAD algorithm to detect an adequate amount of invariant pixels
to perform a robust radiometric normalization. Moreover, the
quantity and behavior of the surface features in the scene are
important aspects that limit the identification of invariant
pixels. Finally, to have a successful result, this procedure can
be applied in RapidEye images subsets with a relatively small
array dimensions, due to very large spatial subsets limit this
procedure and does not allow to determinate a satisfactory
regression for radiometric normalization.",
conference-location = "Jo{\~a}o Pessoa",
conference-year = "25-29 abr. 2015",
isbn = "978-85-17-0076-8",
label = "236",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3JM47UB",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM47UB",
targetfile = "p0236.pdf",
type = "Processamento de imagens",
urlaccessdate = "27 abr. 2024"
}