Integration of Machine Learning and Remote Sensing for Water Quality Monitoring and Prediction: A Review
Michigan State University · M.J.P. Rohilkhand University
Abstract
Aquatic ecosystems play a crucial role in sustaining life and supporting key green and blue economic sectors globally. However, the growing population and increasing anthropogenic pressures are significantly degrading terrestrial water resources, threatening their ability to provide essential socioeconomic services. To safeguard these ecosystems and their benefits, it is critical to continuously monitor changes in water quality. Remote sensing technologies, which offer high-resolution spatial and temporal data over large geographic areas, including surface water bodies, have become indispensable for these monitoring efforts. They enable the observation of various physical, chemical, and biological water…
Citation impact
- FWCI
- 26.75
- Percentile
- 100%
- References
- 182
Authors
3Topics & keywords
- Water quality
- Quality (philosophy)
- Computer science
- Remote sensing
- Environmental science
- Machine learning
- Geology