Sarangi, R.K.; Thangaradjou, T.; Poornima, D.; Shanthi, R.; Kumar, A.S., and Balasubramanian, T., 2015. Seasonal nitrate algorithms for the southwest Bay of Bengal water using in situ measurements for satellite remote-sensing applications.
Monthly coastal sampling and ship-cruise-measured in situ datasets of nitrate, sea surface temperature (SST), and chlorophyll in the SW Bay of Bengal covering Tamilnadu and Andhra Pradesh coasts of India were used to develop nitrate algorithm. A total of 15 datasets prepared during 2009–11 covered cruise data and all monthly datasets, nine datasets followed with better results with paraboloid function, and others followed linear, Gaussian, and Lorentzian function regression fits. Data collection through cruises (397 points), monthly (482 points) coastal sampling, total monthly and cruise (879 points) covering four seasons were used, and the three-dimensional (3D)-paraboloid function showed better results during the seasonal scale study with the R2 values 0.670, 0.635, 0.465, and 0.693 for the postmonsoon, summer, premonsoon, and monsoon seasons respectively. In the current study, there has been considerable improvement in R2 (0.670 with 236 points) than the earlier study using postmonsoon data (0.560 with 105 data points). Through this algorithm, a nitrate map was generated for 11 March 2011 using Oceansat-2 Ocean Color Monitor (OCM) and MODIS-aqua-derived chlorophyll and SST data, respectively. The retrieved nitrate map has been validated with in situ dataset of the same date with an R2 value of 0.718, which suggests that the developed nitrate algorithm was statistically significant with mean normalized bias (MNB) = 0.078, root mean square error (RMSE) = 0.412, and standard error of estimate (SEE) = ±0.4032, and the algorithm was observed to be working satisfactorily over the SW Bay of Bengal region.