Toward Long-Term Aquatic Science Products from Heritage Landsat Missions
This paper aims at generating a long-term consistent record of Landsat-derived remote sensing reflectance (Rrs) products, which are central for producing downstream aquatic science products (e.g., concentrations of total suspended solids). The products are derived from Landsat-5 and Landsat-7 observ...
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ftmdpi:oai:mdpi.com:/2072-4292/10/9/1337/ 2023-08-20T03:59:12+02:00 Toward Long-Term Aquatic Science Products from Heritage Landsat Missions Nima Pahlevan Sundarabalan V. Balasubramanian Sudipta Sarkar Bryan A. Franz agris 2018-08-22 application/pdf https://doi.org/10.3390/rs10091337 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs10091337 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 9; Pages: 1337 Landsat coastal/inland waters atmospheric correction vicarious calibration validation water quality time-series applications Text 2018 ftmdpi https://doi.org/10.3390/rs10091337 2023-07-31T21:41:23Z This paper aims at generating a long-term consistent record of Landsat-derived remote sensing reflectance (Rrs) products, which are central for producing downstream aquatic science products (e.g., concentrations of total suspended solids). The products are derived from Landsat-5 and Landsat-7 observations leading to Landsat-8 era to enable retrospective analyses of inland and nearshore coastal waters. In doing so, the data processing was built into the SeaWiFS Data Analysis System (SeaDAS) followed by vicariously calibrating Landsat-7 and -5 data using reference in situ measurements and near-concurrent ocean color products, respectively. The derived Rrs products are then validated using (a) matchups using the Aerosol Robotic Network (AERONET) data measured by in situ radiometers, i.e., AERONET-OC, and (b) ocean color products at select sites in North America. Following the vicarious calibration adjustments, it is found that the overall biases in Rrs products are significantly reduced. The root-mean-square errors (RMSE), however, indicate noticeable uncertainties due to random and systematic noise. Long-term (since 1984) seasonal Rrs composites over 12 coastal and inland systems are further evaluated to explore the utility of Landsat archive processed via SeaDAS. With all the qualitative and quantitative assessments, it is concluded that with careful algorithm developments, it is possible to discern natural variability in historic water quality conditions using heritage Landsat missions. This requires the changes in Rrs exceed maximum expected uncertainties, i.e., 0.0015 [1/sr], estimated from mean RMSEs associated with the matchups and intercomparison analyses. It is also anticipated that Landsat-5 products will be less susceptible to uncertainties in turbid waters with Rrs(660) > 0.004 [1/sr], which is equivalent of ~1.2% reflectance. Overall, end-users may utilize heritage Rrs products with “fitness-for-purpose” concept in mind, i.e., products could be valuable for one application but may not be viable for ... Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 10 9 1337 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
Landsat coastal/inland waters atmospheric correction vicarious calibration validation water quality time-series applications |
spellingShingle |
Landsat coastal/inland waters atmospheric correction vicarious calibration validation water quality time-series applications Nima Pahlevan Sundarabalan V. Balasubramanian Sudipta Sarkar Bryan A. Franz Toward Long-Term Aquatic Science Products from Heritage Landsat Missions |
topic_facet |
Landsat coastal/inland waters atmospheric correction vicarious calibration validation water quality time-series applications |
description |
This paper aims at generating a long-term consistent record of Landsat-derived remote sensing reflectance (Rrs) products, which are central for producing downstream aquatic science products (e.g., concentrations of total suspended solids). The products are derived from Landsat-5 and Landsat-7 observations leading to Landsat-8 era to enable retrospective analyses of inland and nearshore coastal waters. In doing so, the data processing was built into the SeaWiFS Data Analysis System (SeaDAS) followed by vicariously calibrating Landsat-7 and -5 data using reference in situ measurements and near-concurrent ocean color products, respectively. The derived Rrs products are then validated using (a) matchups using the Aerosol Robotic Network (AERONET) data measured by in situ radiometers, i.e., AERONET-OC, and (b) ocean color products at select sites in North America. Following the vicarious calibration adjustments, it is found that the overall biases in Rrs products are significantly reduced. The root-mean-square errors (RMSE), however, indicate noticeable uncertainties due to random and systematic noise. Long-term (since 1984) seasonal Rrs composites over 12 coastal and inland systems are further evaluated to explore the utility of Landsat archive processed via SeaDAS. With all the qualitative and quantitative assessments, it is concluded that with careful algorithm developments, it is possible to discern natural variability in historic water quality conditions using heritage Landsat missions. This requires the changes in Rrs exceed maximum expected uncertainties, i.e., 0.0015 [1/sr], estimated from mean RMSEs associated with the matchups and intercomparison analyses. It is also anticipated that Landsat-5 products will be less susceptible to uncertainties in turbid waters with Rrs(660) > 0.004 [1/sr], which is equivalent of ~1.2% reflectance. Overall, end-users may utilize heritage Rrs products with “fitness-for-purpose” concept in mind, i.e., products could be valuable for one application but may not be viable for ... |
format |
Text |
author |
Nima Pahlevan Sundarabalan V. Balasubramanian Sudipta Sarkar Bryan A. Franz |
author_facet |
Nima Pahlevan Sundarabalan V. Balasubramanian Sudipta Sarkar Bryan A. Franz |
author_sort |
Nima Pahlevan |
title |
Toward Long-Term Aquatic Science Products from Heritage Landsat Missions |
title_short |
Toward Long-Term Aquatic Science Products from Heritage Landsat Missions |
title_full |
Toward Long-Term Aquatic Science Products from Heritage Landsat Missions |
title_fullStr |
Toward Long-Term Aquatic Science Products from Heritage Landsat Missions |
title_full_unstemmed |
Toward Long-Term Aquatic Science Products from Heritage Landsat Missions |
title_sort |
toward long-term aquatic science products from heritage landsat missions |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10091337 |
op_coverage |
agris |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing; Volume 10; Issue 9; Pages: 1337 |
op_relation |
https://dx.doi.org/10.3390/rs10091337 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs10091337 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
9 |
container_start_page |
1337 |
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1774720892891299840 |