Remote Sensing Big Data for Water Environment Monitoring: Current Status, Challenges, and Future Prospects

• Published in: Earth's future Vol. 10; no. 2
• Main Authors: Chen, Jinyue, Chen, Shuisen, Fu, Rao, Li, Dan, Jiang, Hao, Wang, Chongyang, Peng, Yongshi, Jia, Kai, Hicks, Brendan J.
• Format: Journal Article
• Language: English
• Published: Bognor Regis John Wiley & Sons, Inc 01.02.2022; Wiley
• Subjects: Algorithms; Atmospheric correction; Atmospheric models; Big Data; Climate change; Cloud computing; data fusion; Datasets; Drought; Empirical analysis; Empirical models; Environmental assessment; Learning algorithms; Machine learning; Mathematical models; Modelling; numerical simulation; quantitative estimation of water quality; Remote sensing; remote sensing big data; Satellites; Sensors; water extraction; Water monitoring; Water quality; Water shortages; United States > US; China; Russia

Accurate water extraction and quantitative estimation of water quality are two key and challenging issues for remote sensing of water environment. Recent advances in remote sensing big data, cloud computing, and machine learning have promoted these two fields into a new era. This study reviews the o...