Abstract
We apply a neural network (NN) technique to detect/track Karenia brevis harmful algal blooms (KB HABs) plaguing West Florida shelf (WFS) coasts from Visible-Infrared Imaging Radiometer Suite (VIIRS) satellite observations. Previously KB HABs detection primarily relied on the Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-A) satellite, depending on its remote sensing reflectance signal at the 678-nm chlorophyll fluorescence band (Rrs678) needed for normalized fluorescence height and related red band difference retrieval algorithms. VIIRS, MODIS-A’s successor, does not have a 678-nm channel. Instead, our NN uses Rrs at 486-, 551-, and 671-nm VIIRS channels to retrieve phytoplankton absorption at 443 nm (aph443). The retrieved aph443 images are next filtered by applying limits, defined by (i) low Rrs551-nm backscatter and (ii) a minimum aph443 value associated with KB HABs. The filtered residual images are then converted to show chlorophyll-a concentrations [Chla] and KB cell counts. VIIRS retrievals using our NN and five other retrieval algorithms were compared and evaluated against numerous in situ measurements made over the four-year 2012 to 2016 period, for which VIIRS data are available. These comparisons confirm the viability and higher retrieval accuracies of the NN technique, when combined with the filtering constraints, for effective detection of KB HABs. Analysis of these results as well as sequential satellite observations and recent field measurements underline the importance of short-term temporal variabilities on retrieval accuracies.
Highlights
We have previously described preliminary results with a neural network (NN) approach for the detection[1] and tracking of Karenia brevis harmful algal blooms (KB HABs) that frequently plague the coasts and beaches of the West Florida shelf (WFS) using visible-infrared imaging radiometer suite (VIIRS) satellite data
Imagery[3,4,5,6,7,8,9,10,11,12] and on the remote sensing reflectance signal at 678 nm, (Rrs678) at the chlorophyll fluorescence wavelength. This was used in Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-A) with the normalized fluorescence height and related red band difference (RBD) techniques to effectively help in KB HABs retrievals
We examine VIIRS NN retrievals of KB HABs in the WFS, using the limiting F1 and F2 filter approach described in Sec. 2, against coincident, or near coincident, in situ measurements
Summary
We have previously described preliminary results with a neural network (NN) approach for the detection[1] and tracking of Karenia brevis harmful algal blooms (KB HABs) that frequently plague the coasts and beaches of the West Florida shelf (WFS) using visible-infrared imaging radiometer suite (VIIRS) satellite data. Such a monitoring capability for KB HABs is important because of their negative impacts on ecology and health. To overcome the lack of a fluorescence channel on VIIRS, the NN approach bypasses the need for measurements of chlorophyll fluorescence, allowing us to extend KB HABs satellite monitoring capabilities in the WFS to VIIRS
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.