LAUSR

Evaluation of water quality is a priority work nowadays. In order to monitor and map, the water quality for a wide range on different scales (spatial, temporal), the geospatial technique has the potential to minimize the field and laboratory work. The review has emphasized the advance of remote sensing for the effectiveness of spectral analysis, bio-optical estimation, empirical method, and application of machine learning for water quality assessment. The water quality parameters (turbidity, suspended particles, chlorophyll, etc.) and their retrieval techniques are described in a scientific manner. Available satellite, bands, resolution, and spectrum ranges for specific parameters are critically described in this review with challenges in remote sensing for water quality analysis, considering non-optical active parameters. The application of statistical programmes like linear (multiple regression analysis) and non-linear approaches is discussed for better assessment of water quality. Emphasis is given on comparison between different models to increase the accuracy level of remote sensing of water quality assessment. A direction is suggested for future development in the field of estimation of water pollution assessment through geospatial techniques.