A new area-specific bio-optical algorithm for the Bay of Biscay and assessment of its potential for SeaWiFS and MODIS/Aqua data merging
Morozov, E.; Korosov, A.; Pozdnyakov, D.; Pettersson, L.; Sychev, V. (2010). A new area-specific bio-optical algorithm for the Bay of Biscay and assessment of its potential for SeaWiFS and MODIS/Aqua data merging. Int. J. Remote Sens. 31(24): 6541-6565. http://dx.doi.org/10.1080/01431161.2010.508802
In: International Journal of Remote Sensing. Taylor & Francis: London. ISSN 0143-1161; e-ISSN 1366-5901, meer
Based on a feed-forward and error-back-propagated neural network (NN), a new bio-optical algorithm is developed for the Bay of Biscay. It is designed as a set of NNs individually dedicated to the retrieval of the phytoplankton chlorophyll (chl), and total suspended matter (tsm) from Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua data. The retrieved versus in situ measured concentrations of chl and tsm correlation coefficients for chl proved to be ~0.8 (SeaWiFS) and 0.72 (MODIS), and for tsm 0.71 (SeaWiFS) and 0.74 (MODIS). The developed NN-based bio-optical algorithms are employed to assess the compatibility of SeaWiFS and MODIS data on chl and tsm in the coastal zone of the Bay of Biscay (case 2 waters). The value of the ratio between the concentration of chl and tsm derived from the same-day SeaWiFS and MODIS data (the overflight time difference, ?t is =2.5 hours) has in most cases values of approximately 1, however, in specific cases it varies appreciably. These results indicate that, unlike the reportedly very successful cases of merging of SeaWiFS and MODIS data on chl in open ocean waters (case 1 waters), the merging of chl (and tsm) data from these sensors collected over case 2 waters needs to be supervised at a level of a few pixels. At the same time, when averaged over the entire coastal zone of the Bay of Biscay, the retrieved monthly mean chl and tsm concentrations from SeaWiFS and MODIS practically coincide throughout the years (2002–2004) of contemporaneous operation of these two satellite sensors. Thus, even in the case of such dynamic and optically complex case 2 waters that are inherent in the Bay of Biscay, the potentials for ocean colour data merging are very good. The merging efficiency is assessed and illustrated via documenting the spatio-temporal dynamics of bottom sediment re-suspension in the bay occurring in winter – the season of heaviest cloudiness over the bay.
Dataset
REPHY: REPHY (2022). Dataset of French Observation and Monitoring program for Phytoplankton and Hydrology in coastal waters since 1987. SEANOE. https://doi.org/10.17882/47248, meer
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