2019
DOI: 10.1016/j.rse.2019.111343
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Twenty years of satellite and in situ observations of surface chlorophyll-a from the northern Bay of Biscay to the eastern English Channel. Is the water quality improving?

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Cited by 64 publications
(46 citation statements)
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“…In conclusion, these results confirm the observation of Gohin et al (2019), showing a decrease of chlorophyll-a concentration in the English Channel and the North Sea. Moreover, we observe a similar negative trend in the Irish Sea.…”
Section: 8supporting
confidence: 91%
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“…In conclusion, these results confirm the observation of Gohin et al (2019), showing a decrease of chlorophyll-a concentration in the English Channel and the North Sea. Moreover, we observe a similar negative trend in the Irish Sea.…”
Section: 8supporting
confidence: 91%
“…Using satellite data in the frame of the JMP EUNOSAT project (Joint Monitoring Program of the Eutrophication of NOrth Sea with SATellite data, founded by European commission, https://www. informatiehuismarien.nl/uk/projects/algae-evaluatedfrom/, see also chapter 3.4), Gohin et al (2019) show an evolution of chlorophyll-a since 1997 with a negative trend in the English Channel. The estimation chlorophyll-a concentration by remote sensing has been successfully used for more than 20 years (SeaWiFs/NASA, Modis/NASA, Meris/ESA, Viirs/NASA) for global (Maritorena and Siegel 2005;Morel et al 2007) and coastal applications Gohin 2011;Lapucci et al 2012;Novoa et al 2012;Loisel et al 2017).…”
Section: 8mentioning
confidence: 99%
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“…In intermediate and offshore areas, conventional in situ and low-resolution data were too scarce to provide an assessment result for each geographical assessment unit. Consequently, spatially gridded (1.2 km resolution), monthly averaged (from daily images) chlorophyll-a (Chl-a) concentrations and turbidity were derived from the merging of SeaWiFS, MERIS, MODIS/AQUA, and VIIRS remote-sensing reflectance, processed by the coastal OC5 algorithm with Look-Up-Tables dedicated to each sensor [16,17] ( Table 1). The OC5 algorithm was specifically designed for waters where suspended sediment may hamper the application of the classical OCx algorithms as used for the open ocean [18,19].…”
Section: Datasetsmentioning
confidence: 99%
“…Only data with a quality control flag "good" (all QC test passed) were used. Validation of satellite-and modeling-derived products were done using classical methodologies (comparison between satellite products and in situ datasets using specific statistics as relative bias, correlation coefficients, Relative Standard Deviation, Root Mean Square Error, Taylor Diagrams) [17]. Table 2.…”
Section: Data Quality Quantity and Confidencementioning
confidence: 99%