Remote Sensing Big Data for Water Environment Monitoring: Current Status, Challenges, and Future Prospects
Shandong University · Chinese Academy of Sciences · +6 more institutions
Abstract
Abstract 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 operating framework and methods of remote sensing big data for water environment monitoring, with emphasis on water extraction and quantitative estimation of water quality. The following aspects were investigated in this study: (a) image data source and model evaluation metrics; (b) state‐of‐the‐art methods for water extraction, including threshold‐based methods, water indices, and machine learning‐based…
Citation impact
- FWCI
- 24.68
- Percentile
- 100%
- References
- 147
Authors
9- JCJinyue Chen
Shandong University, Chinese Academy of Sciences, Guangzhou Institute of Geochemistry, Guangdong Academy of Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou Institute of Geography
- SCShuisen ChenCorresponding
Chinese Academy of Sciences, Guangzhou Institute of Geochemistry, Guangdong Academy of Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou Institute of Geography
- RFRao Fu
Shandong University
- DLDan Li
Guangdong Academy of Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou Institute of Geography
- HJHao Jiang
Guangdong Academy of Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou Institute of Geography
Topics & keywords
- Cloud computing
- Computer science
- Water quality
- Big data
- Remote sensing
- Machine learning
- Data mining