Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing

Ocean colour (OC) remote sensing is important for monitoring marine ecosystems. However, inverting the OC signal from the top-of-atmosphere (TOA) radiance measured by satellite sensors remains a challenge as the retrieval accuracy is highly dependent on the performance of the atmospheric correction...

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Published in:Remote Sensing
Main Authors: Christopher O. Ilori, Nima Pahlevan, Anders Knudby
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2019
Subjects:
Q
Online Access:https://doi.org/10.3390/rs11040469
https://doaj.org/article/a606ac62982b4867a9e7905024cb6c96
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spelling ftdoajarticles:oai:doaj.org/article:a606ac62982b4867a9e7905024cb6c96 2023-05-15T13:06:49+02:00 Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing Christopher O. Ilori Nima Pahlevan Anders Knudby 2019-02-01T00:00:00Z https://doi.org/10.3390/rs11040469 https://doaj.org/article/a606ac62982b4867a9e7905024cb6c96 EN eng MDPI AG https://www.mdpi.com/2072-4292/11/4/469 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11040469 https://doaj.org/article/a606ac62982b4867a9e7905024cb6c96 Remote Sensing, Vol 11, Iss 4, p 469 (2019) atmospheric correction remote sensing reflectance Landsat 8 band adjustment validation AERONET-OC Science Q article 2019 ftdoajarticles https://doi.org/10.3390/rs11040469 2022-12-31T16:17:37Z Ocean colour (OC) remote sensing is important for monitoring marine ecosystems. However, inverting the OC signal from the top-of-atmosphere (TOA) radiance measured by satellite sensors remains a challenge as the retrieval accuracy is highly dependent on the performance of the atmospheric correction as well as sensor calibration. In this study, the performances of four atmospheric correction (AC) algorithms, the Atmospheric and Radiometric Correction of Satellite Imagery (ARCSI), Atmospheric Correction for OLI ‘lite’ (ACOLITE), Landsat 8 Surface Reflectance (LSR) Climate Data Record (Landsat CDR), herein referred to as LaSRC (Landsat 8 Surface Reflectance Code), and the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), implemented for Landsat 8 Operational Land Imager (OLI) data, were evaluated. The OLI-derived remote sensing reflectance ( R rs ) products (also known as Level-2 products) were tested against near-simultaneous in-situ data acquired from the OC component of the Aerosol Robotic Network (AERONET-OC). Analyses of the match-ups revealed that generic atmospheric correction methods (i.e., ARCSI and LaSRC), which perform reasonably well over land, provide inaccurate Level-2 products over coastal waters, in particular, in the blue bands. Between water-specific AC methods (i.e., SeaDAS and ACOLITE), SeaDAS was found to perform better over complex waters with root-mean-square error (RMSE) varying from 0.0013 to 0.0005 sr −1 for the 443 and 655 nm channels, respectively. An assessment of the effects of dominant environmental variables revealed AC retrieval errors were influenced by the solar zenith angle and wind speed for ACOLITE and SeaDAS in the 443 and 482 nm channels. Recognizing that the AERONET-OC sites are not representative of inland waters, extensive research and analyses are required to further evaluate the performance of various AC methods for high-resolution imagers like Landsat 8 and Sentinel-2 under a broad range of aquatic/atmospheric conditions. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 11 4 469
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic atmospheric correction
remote sensing reflectance
Landsat 8
band adjustment
validation
AERONET-OC
Science
Q
spellingShingle atmospheric correction
remote sensing reflectance
Landsat 8
band adjustment
validation
AERONET-OC
Science
Q
Christopher O. Ilori
Nima Pahlevan
Anders Knudby
Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing
topic_facet atmospheric correction
remote sensing reflectance
Landsat 8
band adjustment
validation
AERONET-OC
Science
Q
description Ocean colour (OC) remote sensing is important for monitoring marine ecosystems. However, inverting the OC signal from the top-of-atmosphere (TOA) radiance measured by satellite sensors remains a challenge as the retrieval accuracy is highly dependent on the performance of the atmospheric correction as well as sensor calibration. In this study, the performances of four atmospheric correction (AC) algorithms, the Atmospheric and Radiometric Correction of Satellite Imagery (ARCSI), Atmospheric Correction for OLI ‘lite’ (ACOLITE), Landsat 8 Surface Reflectance (LSR) Climate Data Record (Landsat CDR), herein referred to as LaSRC (Landsat 8 Surface Reflectance Code), and the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), implemented for Landsat 8 Operational Land Imager (OLI) data, were evaluated. The OLI-derived remote sensing reflectance ( R rs ) products (also known as Level-2 products) were tested against near-simultaneous in-situ data acquired from the OC component of the Aerosol Robotic Network (AERONET-OC). Analyses of the match-ups revealed that generic atmospheric correction methods (i.e., ARCSI and LaSRC), which perform reasonably well over land, provide inaccurate Level-2 products over coastal waters, in particular, in the blue bands. Between water-specific AC methods (i.e., SeaDAS and ACOLITE), SeaDAS was found to perform better over complex waters with root-mean-square error (RMSE) varying from 0.0013 to 0.0005 sr −1 for the 443 and 655 nm channels, respectively. An assessment of the effects of dominant environmental variables revealed AC retrieval errors were influenced by the solar zenith angle and wind speed for ACOLITE and SeaDAS in the 443 and 482 nm channels. Recognizing that the AERONET-OC sites are not representative of inland waters, extensive research and analyses are required to further evaluate the performance of various AC methods for high-resolution imagers like Landsat 8 and Sentinel-2 under a broad range of aquatic/atmospheric conditions.
format Article in Journal/Newspaper
author Christopher O. Ilori
Nima Pahlevan
Anders Knudby
author_facet Christopher O. Ilori
Nima Pahlevan
Anders Knudby
author_sort Christopher O. Ilori
title Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing
title_short Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing
title_full Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing
title_fullStr Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing
title_full_unstemmed Analyzing Performances of Different Atmospheric Correction Techniques for Landsat 8: Application for Coastal Remote Sensing
title_sort analyzing performances of different atmospheric correction techniques for landsat 8: application for coastal remote sensing
publisher MDPI AG
publishDate 2019
url https://doi.org/10.3390/rs11040469
https://doaj.org/article/a606ac62982b4867a9e7905024cb6c96
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Remote Sensing, Vol 11, Iss 4, p 469 (2019)
op_relation https://www.mdpi.com/2072-4292/11/4/469
https://doaj.org/toc/2072-4292
2072-4292
doi:10.3390/rs11040469
https://doaj.org/article/a606ac62982b4867a9e7905024cb6c96
op_doi https://doi.org/10.3390/rs11040469
container_title Remote Sensing
container_volume 11
container_issue 4
container_start_page 469
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