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Using Augmented and Virtual Reality (AR/VR) to Support Safe Navigation on Inland and Coastal Water Zones

Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images

Earth Observation and Geoinformatics Division, National Institute for Space Research, São José dos Campos 12227-010, SP, Brazil
Instrumentation Laboratory for Aquatic Systems (LabISA), Earth Observation Coordination of National Institute for Space Research (INPE), São José dos Campos 12227-010, SP, Brazil
Department of Agricultural & Biological Engineering, Mississippi State University, Starkville, MS 39762, USA
Departamento de Meteorologia, Universidade do Rio de Janeiro (UFRJ), Rio de Janeiro 21941-916, RJ, Brazil
Author to whom correspondence should be addressed.
Academic Editors: Marta Wlodarczyk-Sielicka, Katarzyna Bradtke, Paweł Terefenko and Jacek Lubczonek
Remote Sens. 2022, 14(8), 1829;
Received: 24 February 2022 / Revised: 2 April 2022 / Accepted: 4 April 2022 / Published: 11 April 2022
(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)
Satellite remote sensing data have been used for water quality mapping, but accurate water reflectance retrieval is dependent on multiple procedures, such as atmospheric and adjacency corrections. For the latter, physical-based methods are used to minimize the adjacency effects caused by neighboring land targets close to water pixels, and implementation requires atmospheric and environmental parameters, such as aerosol optical depth and horizontal range (i.e., distance in meters) of the adjacency effect (HAdj). Generally, the HAdj is empirically defined by users and can lead to substantial errors in water reflectance when incorrectly used. In this research, a physical-based approach with three empirical methods to determine the HAdj (fixed, SIMilarity Environment Correction—SIMEC, and Adaptative Window by Proportion—AWP-Inland Water) were used to correct and characterize the adjacency effects in Sentinel-2 images over Brazilian inland waters. An interactive inversion method of the deep blue waveband estimated the aerosol loading for the atmospheric correction procedure. The results of atmospheric and adjacency corrections were validated against in-situ reflectance data. The inverted aerosol loading achieved a good agreement with in-situ measurements, especially at visible wavelengths (Mean Absolute Percentage Error—MAPE for eutrophic (~56%), bright (~80%), and dark (~288%) waters). The adjacency correction performance was near similar between the SIMEC and AWP-Inland Water methods in eutrophic and bright waters (MAPE difference < 3%). However, only the AWP-Inland Water method provided a smaller error (MAPE ~53%) for dark waters compared to the fixed (~108%) and SIMEC (~289%) methods, which shows how critical HAdj parametrization is for low water reflectance values. Simulations of different atmospheric and adjacency effects were performed, and they highlighted the importance of adjacency correction under aerosol loading higher 0.1, which is a typical aerosol loading in a dry climate season, and over extremely dark, low-reflectance waters. This paper contributes to further understanding adjacency effects in medium spatial resolution imagery of inland waters using a physical-based approach including the uncertainties in HAdj determination. View Full-Text
Keywords: adjacency effects; surface reflectance; atmospheric correction; aerosol; 6SV; radiative transfer adjacency effects; surface reflectance; atmospheric correction; aerosol; 6SV; radiative transfer
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MDPI and ACS Style

Paulino, R.S.; Martins, V.S.; Novo, E.M.L.M.; Barbosa, C.C.F.; de Carvalho, L.A.S.; Begliomini, F.N. Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images. Remote Sens. 2022, 14, 1829.

AMA Style

Paulino RS, Martins VS, Novo EMLM, Barbosa CCF, de Carvalho LAS, Begliomini FN. Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images. Remote Sensing. 2022; 14(8):1829.

Chicago/Turabian Style

Paulino, Rejane S., Vitor S. Martins, Evlyn M.L.M. Novo, Claudio C.F. Barbosa, Lino A.S. de Carvalho, and Felipe N. Begliomini. 2022. "Assessment of Adjacency Correction over Inland Waters Using Sentinel-2 MSI Images" Remote Sensing 14, no. 8: 1829.

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