Binning algorithm for high-resolution IRS-P4 OCM chlorophyll image

Abstract

Daily chlorophyll-a concentration from the Ocean Colour Monitor (OCM) sensor onboard the Indian Remote Sensing satellite (IRS-P4) is used to make weekly and monthly chlorophyll-a concentration maps. The pathwise swath data at 12 noon for every alternate day over the north Indian Ocean (NIO) during February 2004 and February 2005 were used to compare the existing algorithms for binning the data. Atmospherically corrected and geocorrected OCM data were used in the comparative study of three averaging algorithms – arithmetic mean (AVG), geometric mean (GEO) and maximum likelihood estimator (MLE). The analysis shows that the AVG algorithm is best suited when compared with the two other algorithms. However, for case 1 water, MLE gives nearly the same value as AVG. Based on this result, AVG was selected for operational weekly and monthly averaging of OCM data over the NIO. These high-resolution-derived chlorophyll-a weekly and monthly products will be useful to resolve inter-annual-to-decadal changes in chlorophyll-a concentration over the NIO.