Guiying Yang
Papers
1
Total Citations
11
H-Index
1
About
Guiying Yang is a leading figure in ocean color remote sensing, with a focus on advancing satellite-based retrieval of marine biogeochemical parameters. Her most prominent work introduces a novel residual network (ResNet) model for estimating sea surface chlorophyll-a concentrations from the Chinese HY-1C satellite’s COCTS sensor—a critical step toward operational monitoring of global ocean productivity. By training the deep learning model on 52 images spanning September 2018 to 2019, Yang demonstrated that neural networks can outperform traditional bio-optical algorithms in capturing complex, non-linear relationships in remote sensing reflectance data. This contribution, published in 2023 and already garnering 11 citations, underscores her impact in bridging artificial intelligence and oceanography. Her research not only enhances the utility of China’s ocean color satellite series but also provides a scalable framework for processing large volumes of satellite imagery. For students and researchers in marine science and remote sensing, Yang’s work exemplifies how modern machine learning can unlock new insights from Earth observation data, paving the way for more accurate and timely assessments of ocean health and climate-driven changes.
Research Focus
Key Achievements
Top Papers
- 1