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Artificial neural networks (NNs) provide an alternative approach for retrieval of Chl from space and results for northwest European shelf seas over the 2002\u20132020 period are shown. The NNs operate on 15 MODIS-Aqua visible and infrared bands and are tested using bottom of atmosphere (BOA), top of atmosphere (TOA) and Rayleigh corrected TOA reflectances (RC). In each case, a NN architecture consisting of 3 layers of 15 neurons improved performance and data availability compared to current state-of-the-art algorithms used in the region. The NN operating on TOA reflectance outperformed BOA and RC versions. By operating on TOA reflectance data, the NN approach overcomes the common but difficult problem of atmospheric correction in coastal waters. Moreover, the NN provides data for regions which other algorithms often mask out for turbid water or low zenith angle flags. A distinguishing feature of the NN approach is generation of associated product uncertainties based on multiple resampling of the training data set to produce a distribution of values for each pixel, and an example is shown for a coastal time series in the North Sea. The final output of the NN approach consists of a best-estimate image based on medians for each pixel, and a second image representing uncertainty based on standard deviation for each pixel, providing pixel-specific estimates of uncertainty in the final product.<\/jats:p>","DOI":"10.3390\/rs14143353","type":"journal-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T23:02:01Z","timestamp":1657666921000},"page":"3353","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["An Artificial Neural Network Algorithm to Retrieve Chlorophyll a for Northwest European Shelf Seas from Top of Atmosphere Ocean Colour Reflectance"],"prefix":"10.3390","volume":"14","author":[{"given":"Madjid","family":"Hadjal","sequence":"first","affiliation":[{"name":"Department of Physics, University of Strathclyde, Glasgow G4 0NG, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5163-4511","authenticated-orcid":false,"given":"Encarni","family":"Medina-Lopez","sequence":"additional","affiliation":[{"name":"Institute for Infrastructure and Environment, School of Engineering, The University of Edinburgh, Sanderson Building Robert Stevenson Road the King\u2019s Buildings, Edinburgh EH9 3FB, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6116-3194","authenticated-orcid":false,"given":"Jinchang","family":"Ren","sequence":"additional","affiliation":[{"name":"School of Computing Sciences, Robert Gordon University of Aberdeen, Aberdeen AB10 7GE, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1789-8617","authenticated-orcid":false,"given":"Alejandro","family":"Gallego","sequence":"additional","affiliation":[{"name":"Marine Scotland Science, Marine Laboratory Aberdeen, Aberdeen AB11 9DB, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8023-5923","authenticated-orcid":false,"given":"David","family":"McKee","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Strathclyde, Glasgow G4 0NG, UK"},{"name":"Department of Arctic and Marine Biology, UiT the Arctic University of Norway, 9019 Tromso, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1119","DOI":"10.1126\/science.167.3921.1119","article-title":"Spectra of backscattered light from the sea obtained from aircraft as a measure of chlorophyll concentration","volume":"167","author":"Clarke","year":"1970","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"24937","DOI":"10.1029\/98JC02160","article-title":"Ocean color chlorophyll algorithms for SeaWiFS","volume":"103","author":"Maritorena","year":"1998","journal-title":"J. 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