Evaluation of the operational Chlorophyll-a product from global ocean colour sensors in the coastal waters, south-eastern Arabian Sea
D. Harshada, Mini Raman, K. S. Jayappa
Abstract
The present study aims to address the effect of spatial resolution and retrieval algorithms on the performance of operational chlorophyll-a (chl-a) product from different sensors. To meet the objective, chl-a product at different spatial resolutions derived from MODIS, SNPP-VIIRS, OC-CCI, and Sentinel-3A OLCI were compared with in-situ measurements of the coastal waters of Karnataka, south-eastern Arabian Sea and errors were quantified using statistical criteria. MODIS-derived chl-a concentrations at 4 km tends to overestimate in the nearshore waters as shown by a high mean relative percentage difference (MRPD) of 77.09%, and a low coefficient of determination (R2) of 0.35. A significant improvement was seen for MODIS 1 km chl-a product, (R2 = 0.64, MRPD = 22.30%) and Mean Absolute Percentage Deviation (MAPD) = 47.08%. Validation of SNPP-VIIRS derived chl-a of 4 km with in-situ measurements showed moderate correlation (R2 = 0.54, MAPD = 49.21%), whereas 1 km SNPP-VIIRS showed substantially better result than 4 km with majority of data points aggregated along the 1:1 line (R2 = 0.86, MAPD = 43.66%, MRPD = 20.97%). Chlorophyll-a product at original resolution (750 m) showed less error than 4 km and 1 km resolution (MAPD = 39.18%, R2 = 0.75, MRPD = 10.875%). In contrast, OC-CCI underestimated field measured chl-a concentrations as indicated by MRPD (-36.72%), with moderate R2 = 0.58. All 4 km data showed poor results than higher spatial resolution data. Sentinel-3A OLCI 300 m full-resolution (FR) derived chl-a, showed good agreement with sea-truth data (R2 = 0.80, MAPD = 33.07%, and MRPD = 23.89%), whereas Sentinel-3A reduced-resolution (RR-1.2 km) exhibited slight overestimation (MRPD = 28.43%, MAPD = 39.88%, R2 = 0.78) than Sentinel-3A(FR). Comparison of operational chl-a product from OC-CCI, MODIS, SNPP-VIIRS, and Sentinel-3A OLCI illustrated that Sentinel-3A OLCI performed best in coastal waters of Karnataka indicating the importance of higher spatial resolution and neural network-based algorithms.