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

Lim Jin Yi; Md Latifur Rahman Sarker; Lei Zhang; Eko Siswanto; Ahmad Mubin; Saadah Sabarudin

doi:10.1117/12.2029032

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16 October 2013 Monitoring long-term ocean health using remote sensing: A case study of the Bay of Bengal

Lim Jin Yi, Md Latifur Rahman Sarker, Lei Zhang, Eko Siswanto, Ahmad Mubin, Saadah Sabarudin

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Proceedings Volume 8888, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2013; 88880K (2013) https://doi.org/10.1117/12.2029032
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

Oceans 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.

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Lim Jin Yi, Md Latifur Rahman Sarker, Lei Zhang, Eko Siswanto, Ahmad Mubin, and Saadah Sabarudin "Monitoring long-term ocean health using remote sensing: A case study of the Bay of Bengal", Proc. SPIE 8888, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2013, 88880K (16 October 2013); https://doi.org/10.1117/12.2029032

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