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Journal articles

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Full paper

Quality-control tests for OC4, OC5 and NIR-red satellite chlorophyll-a algorithms applied to coastal waters

Participants in the publication
V. Brotas (Author)
Dep. Biologia Vegetal

Reliable satellite estimates of chlorophyll-a concentration (Chl-a) are needed in coastal waters for applications\\nsuch as eutrophication monitoring. However, because of the optical complexity of coastal waters, retrieving\\naccurate Chl-a is still challenging. Many algorithms exist and give quite different performance for different\\noptical conditions but there is no clear definition of the limits of applicability of each algorithm and no clear basis\\nfor deciding which algorithm to apply to any given image pixel (reflectance spectrum). Poor quality satellite Chla\\ndata can easily reach end-users. To remedy this and provide a clear decision on when a specific Chl-a algorithm\\ncan be used, we propose simple quality control tests, based on MERIS water leaving reflectance (ρw) bands, to\\ndetermine on a pixel-by-pixel basis if any of three popular and complementary algorithms can be used. The\\nalgorithms being tested are: 1. the OC4 blue-green band ratio algorithm which was designed for open ocean\\nwaters; 2. the OC5 algorithm which is based on look-up tables and corrects OC4 overestimation in moderately\\nturbid waters and 3. a near infrared-red (NIR-red) band ratio algorithm designed for eutrophic waters.\\nUsing a dataset of 348 in situ Chl-a / MERIS matchups, the conditions for reliable performance of each of the\\nselected algorithms are determined. The approach proposed here looks for the best compromise between the\\nminimization of the relative difference between In situ measurements and satellite estimations and the number of\\npixels processed. Conditions for a reliable application of OC4 and OC5 depend on ρw412/ρw443 and ρw560, used\\nas proxies of coloured dissolved organic matter and suspended particulate matter (SPM), as compared to ρw560/\\nρw490, used as a proxy for Chl-a. Conditions for reliable application of the NIR-red band ratio algorithm depend\\non Chl-a and SPM. These conditions are translated into pixel-based quality control (QC) tests with appropriately\\nchosen thresholds. Results show that by removing data which do not pass QC, the performance of the three\\nselected algorithms is significantly improved. After combining these algorithms, 70% of the dataset could be\\nprocessed with a median absolute percent difference of 30.5%. The QC tests and algorithm merging methodology\\nwere then tested on four MERIS images of European waters. The OC5 algorithm was found to be suitable for most\\npixels, except in very turbid and eutrophic waters along the coasts where the NIR-red band ratio algorithm helps\\nto fill the gap. Finally, a test was performed on an OLCI-S3A image. Although some validations of water\\nreflectance are still needed for the OLCI sensors, results show similar behavior to the MERIS applications which\\nsuggests that when applied to OLCI data the present methodology will help to accurately estimate Chl-a in coastal\\nwaters for the next decade.

Date of Submisson/Request
Date of Acceptance
Date of Publication


Where published
Remote Sensing of Environment

Publication Identifiers
ISSN - 0034-4257

Elsevier BV


Starting page

Document Identifiers

Web Of Science Q1 (2020) - 10.164 - ENVIRONMENTAL SCIENCES - SCIE



V. Brotas, (2021). Quality-control tests for OC4, OC5 and NIR-red satellite chlorophyll-a algorithms applied to coastal waters. Remote Sensing of Environment, 255, ISSN 0034-4257. eISSN .

V. Brotas, "Quality-control tests for OC4, OC5 and NIR-red satellite chlorophyll-a algorithms applied to coastal waters" in Remote Sensing of Environment, vol. 255, 2021. 10.1016/j.rse.2020.112237

@article{50730, author = {V. Brotas}, title = {Quality-control tests for OC4, OC5 and NIR-red satellite chlorophyll-a algorithms applied to coastal waters}, journal = {Remote Sensing of Environment}, year = 2021, volume = 255 }