Work

Sensitivity Assessment of Atmospheric Corrections for Clear and Moderately Turbid Optical Waters

Year: 2024

Type: article

Abstract: Atmospheric Correction (AC) aims to restore surface reflectance from the top of the atmosphere (TOA) reflectance. In this study, seven highly established state-of-the-art AC (OC-SMART, ACOLITE, Polymer, Sen2Cor, iCOR, C2RCC, and L2gen from SeaDAS) approaches were employed on Sentinel-2 MSI high-resolution imageries. The performance of the AC algorithms was validated by comparing the satellite-derived remote sensing reflectance ($R_{rs}(\lambda)$) at four visible wavelengths (443, 460, 590, and 665 nm) with the co-located in-situ hyperspectral measurements acquired within a temporal window of$\pm $3 hours across various water zones located in the Atlantic Ocean. 75 optimal match-up pairs were obtained from six sites between December 2018 and August 2020. An unsupervised learning technique was used to classify the in-situ hyperspectral$R_{rs}(\lambda)$measurements into three optical water types encompassing nearly clear to moderately turbid coastal and deep water zones. Upon general analysis, OC-SMART produced the most precise$R_{rs}(\lambda)$with and$S_{tot}$score and$\bar{\chi }^{2}$value of 20.54/24, and 0.11, respectively. L2gen AC produced$R_{rs}(\lambda)$that show the highest resemblance with the spectral shape in terms of Spectral Angle and Quality Assurance score with the in-situ$R_{rs}(\lambda)$that are 10.4 and 0.84, respectively. The performance of ACs varies across the water types and wavelengths. Using existing bio-optical algorithms, the validation is further extended by obtaining downstream water-quality parameters, such as$Chl_{a}$, TSS, and$a_{cdom}(440)$, from the in-situ measured and atmospherically corrected$R_{rs}(\lambda)$. The expected reasons that affect the performance of ACs across designated water types were discussed.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

DOI: 10.1109/jstars.2024.3492322

Authors: Shahira Abdul Lathif, Maryam R. Al Shehhi

Institution: Khalifa University of Science and Technology

Language: English

Topic: Marine and coastal ecosystems

Subfield: Oceanography

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: gold

Estimated APC paid: $1,496