The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary.

Abstract

The presence of phytoplankton in the water is important as the primary food source of various aquatic lives as well as to determine its pollution level. Among many, the ratio algorithm is one of the approaches in remote sensing used to detect chlorophyll-a in the phytoplankton for its distribution and monitoring. However, some algorithms usages are limited to spatial, temporal, and other factors, hence the performance evaluation of algorithms developed are indeed important for robust observation and monitoring purposes. This study explores the applicability of ratio algorithms for estimation of the chl-a concentration at Sungai Merbok by assessing chl-a distribution pattern built by the algorithms and evaluating each algorithm for their errors compared to in-situ data. The distribution models generated from the algorithms were utilizing Landsat-8 satellite images with B-G and B-R bands ratio. The statistical analysis employed regression models such as p-value, r, R2, and RMSE for both algorithms' performance evaluations. Overall, the chl-a distribution along Sungai Merbok shows a safe concentration with fluctuation in a wide interval, however, both algorithms predicted much low concentration values with narrow and consistent variations. On average, Sungai Merbok recorded 9.52 mg/L chl-a concentration, while B-G and B-R algorithm predicted a lower average at 1.04 and 2.83 mg/L respectively. Although B-G and B-R algorithms both have a significant relation with strong correlation, B-G shows a higher coefficient of determination with 65% variation compared to B-R with about 60%. B-R ratio performed better with a lower RMSE value of 10.22 as compared to 11.48 for B-G.  The findings of this study perhaps will be helpful to the traditional fishermen, local entrepreneurs, and relevant authorities for sustainable fisheries resources and management.