Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/9951
Title: Analysis of IRS-P4 OCM data for estimating the suspended sediment concentrations along the Mangalore Coast, India
Authors: Warakish, G.S.D.
Natesan, U.
Nayak, S.R.
Chauhan, P.
Nagur, C.R.C.
Issue Date: 2010
Citation: International Journal of Imaging, 2010, Vol.3, 10 S, pp.23-39
Abstract: Information on Suspended Sediment Concentration (SSC) in coastal waters is necessary for the understanding and management of the coastal environment. In the present study, estimation of SSC has been carried out along the Mangalore Coast, West coast of India, using both in-situ and Indian Remote sensing Satellite (IRS) - P4 Ocean Color Monitor (OCM) data. The OCM Data Analysis Software (OCMDAS) developed by Space Applications Centre (SAC), Ahmedabad, India, which is based Tassan's algorithm was used to estimate the SSC and validated through sea-truth data collected along the Mangalore Coast. Eighty six surface water samples were collected during the post-monsoon (21.11.1999) and pre-monsoon (07.05.2000) period, near synchronized with IRS-P4-satellite overpass, and SSC was measured using 0.47?m Whatman filter papers with the help of Millipore filter assembly. Out of ninety water samples, eighty two were used to generate the SSC map of the study area and eight samples at few important locations (rivermouth with/without breakwater, man-made coastal structures, and open beaches) were selected to validate the algorithm. Measured SSC varied between 26mg/L and 48mg/L in pre-monsoon and between 16mg/L and 40mg/L during post-monsoon period. The estimated SSC varied between 11mg/L and 47mg/L in pre-monsoon and between 14mg/L and 33mg/L during post-monsoon period. The co-efficient of determination for the relationship developed between measured and estimated SSC is about 0.90 and root mean square error is <14 mg/L. 2010 by IJI (CESER Publications).
URI: http://idr.nitk.ac.in/jspui/handle/123456789/9951
Appears in Collections:1. Journal Articles

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