Development of Satellite Data-Based Multiple Regression Equations for the Estimation of Total Coliform and Petroleum Hydrocarbons Along South West Coast of India

Abstract

Coastal waters are showing deteriorating trend in its quality. This leads to the damage of marine ecosystems and interferes in its normal use. In order to tackle this issue, it is important to know about the extent of pollution. Conventional method of water quality estimation includes analysis of water samples from various locations. This is a tiresome and costly process limiting its application to small scales and accessible sampling sites. In this paper, an attempt has been made to quickly estimate the concentration of Petroleum Hydrocarbons (PHC) and counts of Total Coliform (TC) which are important water quality parameters, along the south west coast of India. This study formulated satellite data-based multiple regression equations for determining the count of total coliform bacteria and concentration of petroleum hydrocarbons. The sea surface temperature and remote sensing reflectance values of different bands of MODIS sensor along with field values were used in the process. The developed algorithm is validated for future use. Maps are created using these equations, showing the distribution of these parameters along the coast using Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) data. Hence, the feasibility of VIIRS for determination of these parameters with the same algorithm is examined. Thus, based on the results, areas of high PHC and TC could be identified and necessary control measures could be adopted. © 2021, Springer Nature Singapore Pte Ltd.