An Analysis on the Techniques for Water Quality Prediction from Remotely Sensed data

Water Quality plays an important role in every aspect of human life as it is a major source of metabolism in every living organism. The prediction of Water Quality is very important considering the changes in the ecological and topological changes in the environment. This paper presents a systematic review of Prediction of water Quality by Remote Sensing approaches along with retrieval measures of different parameters to make the concentration of water at its purest form that is fit for consumption. The data sources are classified as Multispectral and Hyperspectral which can be achieved through satellite and airborne imagery and upon analysis and manipulation of this data, the features can be extracted and different parameters can be retrieved from water bodies. A study of this review can help in improvement in analysis by providing an insight for different approaches in Artificial Intelligence and Machine Learning Techniques for Water Quality Prediction.