@MastersThesis{Pegolo:2024:AvMéLi,
author = "Pegolo, Fellipe Lousada",
title = "Avalia{\c{c}}{\~a}o de m{\'e}todos de limiariza{\c{c}}{\~a}o
de imagens Sentinel-1 para o mapeamento de superf{\'{\i}}cies de
{\'a}guas abertas de lagos de v{\'a}rzea do baixo Rio Amazonas",
school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
year = "2024",
address = "S{\~a}o Jos{\'e} dos Campos",
month = "2023-12-15",
keywords = "Sentinel-1, Amaz{\^o}nia, {\'a}guas abertas, Sentinel-1, Amazon,
open water.",
abstract = "O conhecimento sobre a variabilidade espacial e temporal de
{\'a}guas abertas (AA), ou seja, aquelas sem a presen{\c{c}}a de
vegeta{\c{c}}{\~a}o, {\'e} crucial para diversos campos de
pesquisa, como a hidrologia, a biogeoqu{\'{\i}}mica, a
geomorfologia, a ecologia, entre outros. No entanto, adquirir
esses dados de AA {\'e} um desafio em vastas regi{\~o}es,
especialmente na Amaz{\^o}nia brasileira. Desde 1980, os dados de
sensoriamento remoto orbital v{\^e}m sendo explorados como
alternativa, apesar das limita{\c{c}}{\~o}es relativas {\`a}
cobertura de nuvem constante que impacta os dados {\'o}pticos em
miss{\~o}es devido {\`a} baixa frequ{\^e}ncia de
aquisi{\c{c}}{\~a}o e {\`a} baixa resolu{\c{c}}{\~a}o
espacial dos dados passivos de micro-ondas, ent{\~a}o
dispon{\'{\i}}veis. As poucas miss{\~o}es SAR, com livre acesso
aos dados e alta frequ{\^e}ncia de aquisi{\c{c}}{\~a}o,
tamb{\'e}m dificultaram a obten{\c{c}}{\~a}o de s{\'e}ries
temporais AA at{\'e} o lan{\c{c}}amento dos sat{\'e}lites
Sentinel-1A e 1B (S1) em 2014 e 2016, respectivamente. Portanto,
este estudo tem como objetivo avaliar o potencial de diferentes
m{\'e}todos de limiariza{\c{c}}{\~a}o (Emp{\'{\i}}rico:
supervisionado e Otsu: n{\~a}o supervisionado) de imagens
polarim{\'e}tricas SAR S1 (VV e VH) para gerar s{\'e}ries
temporais com uma frequ{\^e}ncia de 12 dias ({\'o}rbita
descendente) das AA do Lago Grande de Curuai (LGC), situado no
Baixo Rio Amazonas, Estado do Par{\'a}. Utilizando a plataforma
Google Earth Engine (GEE) e dados SAR S1 dispon{\'{\i}}veis em
seu cat{\'a}logo, foram criadas m{\'a}scaras de AA a partir dos
m{\'e}todos analisados. Essas m{\'a}scaras foram validadas
estatisticamente com m{\'e}tricas como acur{\'a}cia global (AG),
sensibilidade (S) e especificidade (E), e comparadas com imagens
Sentinel-2 quase simult{\^a}neas. Al{\'e}m disso, foram
analisados fatores que podem afetar a precis{\~a}o dessas
m{\'a}scaras (n{\'{\i}}vel de {\'a}gua,
precipita{\c{c}}{\~a}o, cobertura de nuvens e eventos ENSO) para
auxiliar na determina{\c{c}}{\~a}o do m{\'e}todo mais adequado
para extrair s{\'e}ries temporais VV e VH de AA (STAAVV e
STAAVH). Os m{\'e}todos Emp{\'{\i}}ricos de
limiariza{\c{c}}{\~a}o para as polariza{\c{c}}{\~o}es VV e VH
se destacaram em termos de m{\'e}tricas de acur{\'a}cia e
avalia{\c{c}}{\~o}es visuais quando comparados ao m{\'e}todo
Otsu. Embora o m{\'e}todo Emp{\'{\i}}rico com limiar de -17 dB
para VV tenha apresentado maior acur{\'a}cia (OA, S e E),
verificou-se que em algumas condi{\c{c}}{\~o}es, as
m{\'a}scaras geradas por esse m{\'e}todo e
polariza{\c{c}}{\~a}o apresentaram lacunas ({\'a}reas que
n{\~a}o s{\~a}o {\'a}guas abertas (NAA)), devido principalmente
{\`a} influ{\^e}ncia de nuvens carregadas, c{\'e}lulas de chuva
e {\'a}guas agitadas, causadas por for{\c{c}}as hidr{\'a}ulicas
e e{\'o}licas que afetam a velocidade e dire{\c{c}}{\~a}o dos
fluxos entre o Rio Amazonas e o LGC. As lacunas das m{\'a}scaras
de {\'a}gua ocasionaram em uma STAAVV ruidosa. Em contrapartida o
m{\'e}todo Emp{\'{\i}}rico com limiar de -23 dB para VH por ser
menos sens{\'{\i}}vel a esses fatores resultou na STAAVH mais
est{\'a}vel e coerente com os eventos clim{\'a}ticos de
estiagens relacionadas ao El Niño e de inunda{\c{c}}{\~o}es
associadas ao La Niña. ABSTRACT: The knowledge about the spatial
and temporal variability of open waters, i.e., those without the
presence of vegetation, is crucial for various research fields
such as hydrology, biogeochemistry, geomorphology, ecology, among
others. However, acquiring open waters data is challenging in vast
regions, especially in the Brazilian Amazon. Since the 1980s,
orbital remote sensing data have been explored as an alternative,
despite limitations regarding constant cloud cover impacting
optical data in missions due to low acquisition frequency and low
spatial resolution of passive microwave data then available. The
few SAR missions, with free access to data and high acquisition
frequency, also hindered obtaining open waters time series until
the launch of Sentinel-1A and 1B (S1) satellites in 2014 and 2016,
respectively. Therefore, this study aims to evaluate the potential
of different thresholding methods (Empirical: supervised and Otsu:
unsupervised) of S1 SAR polarimetric images (VV and VH) to
generate time series with a frequency of 12 days (descending
orbit) of open waters of Lake Grande de Curuai (LGC), located in
the Lower Amazon River, State of Par{\'a}. Using the Google Earth
Engine (GEE) platform and S1 SAR data available in its catalog,
open waters masks were created from the analyzed methods. These
masks were statistically validated with metrics such as overall
accuracy, sensitivity, and specificity, and compared with
quasi-simultaneous Sentinel-2 images. Furthermore, factors that
may affect the accuracy of these masks (water level,
precipitation, cloud cover, and ENSO events) were analyzed to
assist in determining the most suitable method for extracting VV
and VH OW time series (STAAVV and STAAVH). Empirical thresholding
methods for VV and VH polarizations stood out in terms of accuracy
metrics and visual evaluations when compared to the Otsu method.
Although the Empirical method with a threshold of -17 dB for VV
presented higher accuracy, it was found that under some
conditions, masks generated by this method and polarization showed
gaps (areas that are not open waters), mainly due to the influence
of heavy clouds, rain cells, and agitated waters caused by
hydraulic and wind forces affecting the speed and direction of
flow between the Amazon River and LGC. The gaps in water masks
resulted in noisy STAAVV. In contrast, the Empirical method with a
threshold of -23 dB for VH, being less sensitive to these factors,
resulted in a more stable and coherent STAAVH with drought-related
climatic events associated with El Niño and flooding associated
with La Niña.",
committee = "Barbosa, Cl{\'a}udio Clemente Faria (presidente) and Novo, Evlyn
M{\'a}rcia Le{\~a}o de Moraes (orientadora) and Maciel, Daniel
Andrade (orientador) and Mura, Jose Claudio and Andrade, Alice
C{\'e}sar Fassoni de",
englishtitle = "Assessment of Sentinel-1 image thresholding methods for mapping
open water in flooded lakes of the lower Amazon River",
language = "pt",
pages = "93",
ibi = "8JMKD3MGP3W34T/4AK8DNE",
url = "http://urlib.net/ibi/8JMKD3MGP3W34T/4AK8DNE",
targetfile = "publicacao.pdf",
urlaccessdate = "2024, May 18"
}