Show simple item record

dc.contributor.authorGilerson, Alexander
dc.contributor.authorOndrusek, Michael
dc.contributor.authorTzortziou, Maria
dc.contributor.authorFoster, Robert
dc.contributor.authorEl-Habashi, Ahmed
dc.contributor.authorTiwari, Surya Prakash
dc.contributor.authorAhmed, Sam
dc.date.accessioned2015-10-20T09:49:36Z
dc.date.available2015-10-20T09:49:36Z
dc.date.issued2015-10-14
dc.identifier.citationAlexander Gilerson ; Michael Ondrusek ; Maria Tzortziou ; Robert Foster ; Ahmed El-Habashi ; Surya Prakash Tiwari and Sam Ahmed " Multi-band algorithms for the estimation of chlorophyll concentration in the Chesapeake Bay ", Proc. SPIE 9638, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015, 96380A (October 14, 2015)
dc.identifier.doi10.1117/12.2195725
dc.identifier.urihttp://hdl.handle.net/10754/579922
dc.description.abstractStandard blue-green ratio algorithms do not usually work well in turbid productive waters because of the contamination of the blue and green bands by CDOM absorption and scattering by non-algal particles. One of the alternative approaches is based on the two- or three band ratio algorithms in the red/NIR part of the spectrum, which require 665, 708, 753 nm bands (or similar) and which work well in various waters all over the world. The critical 708 nm band for these algorithms is not available on MODIS and VIIRS sensors, which limits applications of this approach. We report on another approach where a combination of the 745nm band with blue-green-red bands was the basis for the new algorithms. A multi-band algorithm which includes ratios Rrs(488)/Rrs(551)and Rrs(671)/Rrs(745) and two band algorithm based on Rrs671/Rrs745 ratio were developed with the main focus on the Chesapeake Bay (USA) waters. These algorithms were tested on the specially developed synthetic datasets, well representing the main relationships between water parameters in the Bay taken from the NASA NOMAD database and available literature, on the field data collected by our group during a 2013 campaign in the Bay, as well as NASA SeaBASS data from the other group and on matchups between satellite imagery and water parameters measured by the Chesapeake Bay program. Our results demonstrate that the coefficient of determination can be as high as R2 > 0.90 for the new algorithms in comparison with R2 = 0.6 for the standard OC3V algorithm on the same field dataset. Substantial improvement was also achieved by applying a similar approach (inclusion of Rrs(667)/Rrs(753) ratio) for MODIS matchups. Results for VIIRS are not yet conclusive. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
dc.language.isoen
dc.publisherSPIE-Intl Soc Optical Eng
dc.relation.urlhttp://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2195725
dc.rightsArchived with thanks to Proceedings of SPIE
dc.titleMulti-band algorithms for the estimation of chlorophyll concentration in the Chesapeake Bay
dc.typeConference Paper
dc.contributor.departmentRed Sea Research Center (RSRC)
dc.identifier.journalRemote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015
dc.conference.date2015-09-23 to --
dc.conference.nameRemote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015
dc.conference.locationToulouse, FRA
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionThe City College of New York (United States)
dc.contributor.institutionNOAA National Environmental Satellite, Data, and Information Service (United States)
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personTiwari, Surya Prakash
refterms.dateFOA2018-06-13T12:25:55Z


Files in this item

Thumbnail
Name:
96380A.pdf
Size:
783.2Kb
Format:
PDF
Description:
Main article

This item appears in the following Collection(s)

Show simple item record