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Conference Paper: Monitoring long-term ocean health using remote sensing: A case study of the bay of Bengal

TitleMonitoring long-term ocean health using remote sensing: A case study of the bay of Bengal
Authors
KeywordsOcean health
sea surface temperature
season
chlorophyll-a concentration
natural disaster
Issue Date2013
PublisherSPIE - International Society for Optical Engineering. The Journal's web site is located at https://www.spiedigitallibrary.org/conference-proceedings-of-spie
Citation
SPIE Remote Sensing, Dresden, Germany, 23-26 September 2013. In Proceedings of SPIE - The International Society for Optical Engineering, 2013, v. 8888, article no. 88880K How to Cite?
AbstractOceans play a significant role in the global carbon cycle and climate change, and the most importantly it is a reservoir for plenty of protein supply, and at the center of many economic activities. Ocean health is important and can be monitored by observing different parameters, but the main element is the phytoplankton concentration (chlorophyll-a concentration) because it is the indicator of ocean productivity. Many methods can be used to estimate chlorophyll-a (Chl-a) concentration, among them, remote sensing technique is one of the most suitable methods for monitoring the ocean health locally, regionally and globally with very high temporal resolution. In this research, long term ocean health monitoring was carried out at the Bay of Bengal considering three facts i.e. i) very dynamic local weather (monsoon), ii) large number of population in the vicinity of the Bay of Bengal, and iii) the frequent natural calamities (cyclone and flooding) in and around the Bay of Bengal. Data (ten years: from 2001 to 2010) from SeaWiFS and MODIS were used. Monthly Chl-a concentration was estimated from the SeaWiFS data using OC4 algorithm, and the monthly sea surface temperature was obtained from the MODIS sea surface temperature (SST) data. Information about cyclones and floods were obtained from the necessary sources and in-situ Chl-a data was collected from the published research papers for the validation of Chl-a from the OC4 algorithm. Systematic random sampling was used to select 70 locations all over the Bay of Bengal for extracting data from the monthly Chl-a and SST maps. Finally the relationships between different aspects i.e. i) Chl-a and SST, ii) Chl-a and monsoon, iii) Chl-a and cyclones, and iv) Chl-a and floods were investigated monthly, yearly and for long term (i.e 10 years). Results indicate that SST, monsoon, cyclone, and flooding can affect Chl-a concentration but the effect of monsoon, cyclone, and flooding is temporal, and normally reduces over time. However, the effect of SST on Chl-a concentration can't be minimized very quickly although the change of temperature over this period is not very large. © 2013 SPIE.
Persistent Identifierhttp://hdl.handle.net/10722/266965
ISSN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYi, Lim Jin-
dc.contributor.authorRahman Sarker, Md Latifur-
dc.contributor.authorZhang, Lei-
dc.contributor.authorSiswanto, Eko-
dc.contributor.authorMubin, Ahmad-
dc.contributor.authorSabarudin, Saadah-
dc.date.accessioned2019-01-31T07:20:07Z-
dc.date.available2019-01-31T07:20:07Z-
dc.date.issued2013-
dc.identifier.citationSPIE Remote Sensing, Dresden, Germany, 23-26 September 2013. In Proceedings of SPIE - The International Society for Optical Engineering, 2013, v. 8888, article no. 88880K-
dc.identifier.issn0277-786X-
dc.identifier.urihttp://hdl.handle.net/10722/266965-
dc.description.abstractOceans play a significant role in the global carbon cycle and climate change, and the most importantly it is a reservoir for plenty of protein supply, and at the center of many economic activities. Ocean health is important and can be monitored by observing different parameters, but the main element is the phytoplankton concentration (chlorophyll-a concentration) because it is the indicator of ocean productivity. Many methods can be used to estimate chlorophyll-a (Chl-a) concentration, among them, remote sensing technique is one of the most suitable methods for monitoring the ocean health locally, regionally and globally with very high temporal resolution. In this research, long term ocean health monitoring was carried out at the Bay of Bengal considering three facts i.e. i) very dynamic local weather (monsoon), ii) large number of population in the vicinity of the Bay of Bengal, and iii) the frequent natural calamities (cyclone and flooding) in and around the Bay of Bengal. Data (ten years: from 2001 to 2010) from SeaWiFS and MODIS were used. Monthly Chl-a concentration was estimated from the SeaWiFS data using OC4 algorithm, and the monthly sea surface temperature was obtained from the MODIS sea surface temperature (SST) data. Information about cyclones and floods were obtained from the necessary sources and in-situ Chl-a data was collected from the published research papers for the validation of Chl-a from the OC4 algorithm. Systematic random sampling was used to select 70 locations all over the Bay of Bengal for extracting data from the monthly Chl-a and SST maps. Finally the relationships between different aspects i.e. i) Chl-a and SST, ii) Chl-a and monsoon, iii) Chl-a and cyclones, and iv) Chl-a and floods were investigated monthly, yearly and for long term (i.e 10 years). Results indicate that SST, monsoon, cyclone, and flooding can affect Chl-a concentration but the effect of monsoon, cyclone, and flooding is temporal, and normally reduces over time. However, the effect of SST on Chl-a concentration can't be minimized very quickly although the change of temperature over this period is not very large. © 2013 SPIE.-
dc.languageeng-
dc.publisherSPIE - International Society for Optical Engineering. The Journal's web site is located at https://www.spiedigitallibrary.org/conference-proceedings-of-spie-
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineering-
dc.subjectOcean health-
dc.subjectsea surface temperature-
dc.subjectseason-
dc.subjectchlorophyll-a concentration-
dc.subjectnatural disaster-
dc.titleMonitoring long-term ocean health using remote sensing: A case study of the bay of Bengal-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1117/12.2029032-
dc.identifier.scopuseid_2-s2.0-84889598874-
dc.identifier.volume8888-
dc.identifier.spagearticle no. 88880K-
dc.identifier.epagearticle no. 88880K-
dc.identifier.eissn1996-756X-
dc.identifier.isiWOS:000328345700016-

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