An investigation into water quality monitoring models using remote sensing

Remote sensing has been used to analyse water quality since its inception. With recent breakthroughs in machine learning and satellite technology, researchers have begun to take a deeper look at the process as a viable alternative to traditional methods for water quality analysis. This study offers a systematic review of articles in which numerous researchers collectively analysed 26,160 water samples and developed 329 equations through various mathematical models that assess 13 distinct environmental parameters. The aim of this study is to better understand how researchers have addressed the challenges of creating suitable models that use remote sensing data and to identify trends or consensus on water quality parameters. This research delves deeper into the creation of these models to examine the various statistical approaches and their performance by investigating individual mathematical models in the literature. This research also explores the usage and application of various satellite bands for water quality monitoring. Key findings include a detailed examination of the spectral regions utilized by each model, reliance on band ratios, the impact of limited data, an assessment of the literature’s strengths and limitations, and recommendations for future directions.