An empirical model based environmental pollution level analysis in coastal area of Gulf of Mannar using remote sensing data

Abstract

Understanding the statistical relations among the remote sensing data and observed water quality parameters is the necessary task to develop an estimator model. In order to estimate the exact water quality parameter distribution map of the study area from remote sensing data, this present study proposed an empirical mathematical relational and signature (EMRS) model. Through this EMRS model, an environmental pollution level analysis has been carried out for coastal area of Gulf of Mannar. EMRS highly facilitates to map the distribution of the water quality parameters. The insitu samples were involved with ICP‐OES and Physicochemical analysis and the test results were used for convergence of EMRS. The heavy metals such as Fe, Cu, Cd, Hg, and physicochemical parameters such as pH, dissolved oxygen (DO), biological oxygen demand (BOD), alkalinity, total suspended solids (TSS), turbidity and hardness are the experimented water quality parameters. The Landsat, Sentinal remote sensing data were used by the model to estimate the values and distribution and pollution level maps. The experimental analysis shows that the extracted element concentration using the proposed EMRS has highly correlated with the observed values based on the different measures such as R2 and root mean square error (RMSE).