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    Retrieval of sea surface velocities using sequential ocean colour monitor (OCM) data

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    Proc_PORSEC_2000_1_368.pdf (362.1Kb)
    Date
    2000
    Author
    Prasad, J.S.
    Rajawat, A.S.
    Pradhan, Y.
    Chauhan, O.S.
    Nayak, S.R.
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    Abstract
    The Indian Remote Sensing Satellite, IRS-P4 (Oceansat-I) launched on May 26, 1999 carried two sensors on board, i.e., Ocean Colour Monitor (OCM) and a Multifrequency Scanning Microwave Radiometer (MSMR) to study both biological and physical parameters of oceans. OCM collects data for a wide swath of 1420 km, in eight spectral bands (Visible/NIR region) with 20/40 nm bandwidths and two days repeativity. The OCM data is found to be extremely useful in retrieving and monitoring biophysical parameters like chlorophyll-a, suspended sediments, yellow substance and aerosol optical depth at regional scale. Sequential data of IRS-P4 OCM has been analysed over parts of both east and west coast of India and a methodology to retrieve sea surface current velocities has been developed. The method is based on matching suspended sediment dispersion patterns, in sequential two time lapsed images. The pattern matching is performed on atmospherically corrected and geo-referenced sequential pair of images by Maximum Cross-Correlation (MCC) technique. The MCC technique involves computing matrices of cross-correlation coefficients and identifying correlation peaks. The movement of the pattern can be calculated knowing the displacement of windows required to match patterns in successive images. The technique provides actual flow during a specified period by integrating both tidal and wind influences. The current velocities retrieved were compared with synchronous data collected along east coast during GSI cruise ST-133 of R.V. Samudra Kaustubh in January 2000. It is observed that coefficient of determination, R-squared is 0.99 for both magnitude (cm/s) and direction (deg.).The technique may find useful applications in providing inputs to hydrodynamic modeling of coastal processes such as computation of long-shore transport, pollutants dispersion rates, siltation etc. under different tidal cycles and wind influences.
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    http://drs.nio.org/drs/handle/2264/1706
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