Neural network algorithms for retrieval of harmful algal blooms in the west Florida shelf from VIIRS satellite observations and comparisons with other techniques, without the need for a fluorescence channel

A. El-habashi; S. Ahmed

doi:10.1117/12.2195339

14 October 2015 Neural network algorithms for retrieval of harmful algal blooms in the west Florida shelf from VIIRS satellite observations and comparisons with other techniques, without the need for a fluorescence channel

A. El-habashi, S. Ahmed

Author Affiliations +

Proceedings Volume 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015; 96380B (2015) https://doi.org/10.1117/12.2195339
Event: SPIE Remote Sensing, 2015, Toulouse, France

Abstract

New approaches are described that use of the Ocean Color Remote Sensing Reflectance readings (OC Rrs) available from the existing Visible Infrared Imaging Radiometer Suite (VIIRS) bands to detect and retrieve Karenia brevis (KB) Harmful Algal Blooms (HABs) that frequently plague the coasts of the West Florida Shelf (WFS). Unfortunately, VIIRS, unlike MODIS, does not have a 678 nm channel to detect Chlorophyll fluorescence, which is used with MODIS in the normalized fluorescence height (nFLH) algorithm which has been shown to help in effectively detecting and tracking KB HABs. We present here the use of neural network (NN) algorithms for KB HABS retrievals in the WFS. These NNs, previously reported by us, were trained, using a wide range of suitably parametrized synthetic data typical of coastal waters, to form a multiband inversion algorithm which models the relationship between Rrs values at the 486, 551 and 671nm VIIRS bands against the values of phytoplankton absorption (a_ph), CDOM absorption (a_g), non-algal particles (NAP) absorption (a_NAP) and the particulate backscattering bb_p coefficients, all at 443nm, and permits retrievals of these parameters. We use the NN to retrieve a_ph443 in the WFS. The retrieved a_ph443 values are then filtered by applying known limiting conditions on minimum Chlorophyll concentration [Chla] and low backscatter properties associated with KB HABS in the WFS, thereby identifying, delineating and quantifying the a_ph443 values, and hence [Chl] concentrations representing KB HABS. Comparisons with in-situ measurements and other techniques including MODIS nFLH confirm the viability of both the NN retrievals and the filtering approaches devised.

Citation Download Citation

A. El-habashi and S. Ahmed "Neural network algorithms for retrieval of harmful algal blooms in the west Florida shelf from VIIRS satellite observations and comparisons with other techniques, without the need for a fluorescence channel", Proc. SPIE 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015, 96380B (14 October 2015); https://doi.org/10.1117/12.2195339

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available