Multi-band algorithms for the estimation of chlorophyll concentration in the Chesapeake Bay

Handle URI:
http://hdl.handle.net/10754/579922
Title:
Multi-band algorithms for the estimation of chlorophyll concentration in the Chesapeake Bay
Authors:
Gilerson, Alexander; Ondrusek, Michael; Tzortziou, Maria; Foster, Robert; El-Habashi, Ahmed; Tiwari, Surya Prakash ( 0000-0001-8833-132X ) ; Ahmed, Sam
Abstract:
Standard 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).
KAUST Department:
Red Sea Research Center (RSRC)
Citation:
Alexander 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)
Publisher:
SPIE-Intl Soc Optical Eng
Journal:
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015
Conference/Event name:
Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015
Issue Date:
14-Oct-2015
DOI:
10.1117/12.2195725
Type:
Conference Paper
Additional Links:
http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2195725
Appears in Collections:
Conference Papers; Red Sea Research Center (RSRC)

Full metadata record

DC FieldValue Language
dc.contributor.authorGilerson, Alexanderen
dc.contributor.authorOndrusek, Michaelen
dc.contributor.authorTzortziou, Mariaen
dc.contributor.authorFoster, Roberten
dc.contributor.authorEl-Habashi, Ahmeden
dc.contributor.authorTiwari, Surya Prakashen
dc.contributor.authorAhmed, Samen
dc.date.accessioned2015-10-20T09:49:36Zen
dc.date.available2015-10-20T09:49:36Zen
dc.date.issued2015-10-14en
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)en
dc.identifier.doi10.1117/12.2195725en
dc.identifier.urihttp://hdl.handle.net/10754/579922en
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).en
dc.language.isoenen
dc.publisherSPIE-Intl Soc Optical Engen
dc.relation.urlhttp://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2195725en
dc.rightsArchived with thanks to Proceedings of SPIEen
dc.titleMulti-band algorithms for the estimation of chlorophyll concentration in the Chesapeake Bayen
dc.typeConference Paperen
dc.contributor.departmentRed Sea Research Center (RSRC)en
dc.identifier.journalRemote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015en
dc.conference.date2015-09-23 to --en
dc.conference.nameRemote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2015en
dc.conference.locationToulouse, FRAen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionThe City College of New York (United States)en
dc.contributor.institutionNOAA National Environmental Satellite, Data, and Information Service (United States)en
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorTiwari, Surya Prakashen
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