@Article{PahlevanBBOAMHOG:2024:ReAnRe,
author = "Pahlevan, Nima and Balasubramanian, Sundarabalan and Begeman,
Christopher C. and O'Shea, Ryan E. and Ashapure, Akash and Maciel,
Daniel Andrade and Hall, Dorothy K. and Odermatt, Daniel and
Giardino, Claudia",
affiliation = "{The Nasa Goddard Space Flight Center} and {University of Maryland
Baltimore County} and {The Nasa Goddard Space Flight Center} and
{The Nasa Goddard Space Flight Center} and {The Nasa Goddard Space
Flight Center} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {University of Maryland} and {Swiss Federal Institute
of Aquatic Science and Technology} and {National Research Council
of Italy}",
title = "A Retrospective Analysis of Remote-Sensing Reflectance Products in
Coastal and Inland Waters",
journal = "IEEE Geoscience and Remote Sensing Letters",
year = "2024",
volume = "21",
pages = "e1501205",
keywords = "Coastal and inland waters, freshwater ecosystems, medium
resolution imaging spectrometer (MERIS), moderate resolution
imaging spectroradiometer (MODIS), ocean color (OC), remote
sensing reflectance, validation, visible infrared imaging
radiometer suite (VIIRS).",
abstract = "Constructing a robust ocean color (OC) record (e.g., water
transparency, phytoplankton absorption) for long-term assessments
of coastal and inland water ecosystems from past, present, and
future missions requires high-quality spectral remote sensing
reflectance (Rrs) products. Using the GLORIA dataset (Lehmann et
al., 2023), we evaluated the quality of Rrs products from the
moderate resolution imaging spectroradiometer (MODIS on Terra and
Aqua), medium resolution imaging spectrometer (MERIS), and visible
infrared imaging radiometer suite (VIIRS) processed via the
two-band heritage atmospheric correction method (a combination of
near-infrared and shortwave infrared bands) available in the
SeaWiFS Analysis Data Analysis System (SeaDAS). Overall, retrieval
residuals are consistent within a few percentages among the four
missions. Median residuals ranged from ~ 20% in the ~ 550-nm band
to > 60% in the ~ 412-nm bands. Spectrally averaged root mean
squared differences for all the missions were ~ 0.0024 sr-1 with
one standard deviation of ~ 0.001 sr-1. The corresponding (median)
biases in the visible bands varied from -60% to -3%, with the
largest biases identified in MERIS and VIIRS products. Despite the
lower sensitivity of band-ratio algorithms to residuals in
specific spectral regions [e.g., OC3 chlorophyll-a algorithm is
less prone to residuals in Rrs (\λ >600 nm)], other
algorithms or downstream products that leverage all the visible
bands are highly compromised. We underscore the need to improve
the quality of Rrs products, thereby enabling the reconstruction
of baseline OC products of high caliber in global coastal and
inland waters that are often near human activity.",
doi = "10.1109/LGRS.2024.3351328",
url = "http://dx.doi.org/10.1109/LGRS.2024.3351328",
issn = "1545-598X",
language = "en",
targetfile = "
A_Retrospective_Analysis_of_Remote-Sensing_Reflectance_Products_in_Coastal_and_Inland_Waters.pdf",
urlaccessdate = "12 maio 2024"
}