DocumentCode
1474235
Title
Interlacing Ocean Model Simulations and Remotely Sensed Biophysical Parameters to Identify Integrated Potential Fishing Zones
Author
Rahul, P.R.C. ; Sahu, Sobhan Kumar ; Salvekar, P.S.
Author_Institution
Indian Inst. of Tropical Meteorol., Pune, India
Volume
8
Issue
4
fYear
2011
fDate
7/1/2011 12:00:00 AM
Firstpage
789
Lastpage
793
Abstract
Over the global oceans (Indian, Pacific, and Atlantic), fish schools are identified using remote sensing, combining sea surface temperature (SST) and chlorophyll. Advanced Very High Resolution Radiometer-derived SST and Indian Remote Sensing Satellite-P4 Ocean Color Monitor-derived chlorophyll concentration were used to generate the integrated potential fishing zone (IPFZ) forecast over the east coast of India (16°-22° N, 81°-89° E) during April 7-9 and December 18-21, 2003. The IPFZ forecasts are validated with actual fishing using the Fishery Survey of India fishing vessels. Furthermore, we analyze Naval Research Laboratory Layered Ocean Model circulations and Jason-1-derived sea surface height anomalies in the IPFZs to report the presence of cyclonic eddies which induce upwelling and enhance biological productivity, leading to active aggregation of fish schools. The use of accurate mesoscale eddy-simulating models could be useful in the long-term prediction of pelagic fish schools.
Keywords
atmospheric movements; ocean temperature; oceanographic techniques; radiometers; remote sensing; AD 2003 04 07 to 04 09; AD 2003 12 18 to 12 21; Atlantic Ocean; Indian Ocean; Indian remote sensing satellite; Jason-1-derived sea surface height anomalies; P4 ocean color monitor-derived chlorophyll concentration; Pacific Ocean; advanced very high resolution radiometer; biological productivity analysis; cyclonic eddies analysis; east India coast; integrated potential fishing zone; interlacing ocean model simulation; mesoscale eddy-simulation model; naval research laboratory layered ocean model circulation; pelagic fish school; remotely sensed biophysical parameter; sea surface temperature; Biological system modeling; Data models; Image color analysis; Ocean temperature; Predictive models; Remote sensing; Ecosystems; ocean temperature; sea coast; sea level;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2010.2096554
Filename
5733365
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