| Abstract: | Geospatial approaches to monitoring and mapping water quality over a wide range of temporal and spatial scales have the potential to save field and laboratory efforts. The present study depicts the estimation of water quality parameters, namely turbidity and phosphate, through regression analysis using the reflectance derived from remote sensing data on the west coast of Mumbai, India. The predetermined coastal water samples were collected using the global positioning system (GPS) and were measured concurrently with satellite imagery acquisition. To study the influence of wastewater, the linear correlations were established between water quality parameters and reflectance of visible bands for either set of imagery for the study area, which was divided into three zones: creek water, shore‐line water and coastal water. Turbidity and phosphate have the correlation coefficients in the range 0.75–0.94 and 0.78–0.98, respectively, for the study area. Negative correlation was observed for creek water owing to high organic content caused by the discharges of domestic wastewater from treatment facilities and non‐point sources. Based on the least square method, equations are formulated to estimate turbidity and phosphate, to map the spatial variation on the GIS platform from simulated points. The applicability of satellite imagery for water quality pattern on the coast is verified for efficient planning and management. |
