Seonyoung Park

Seoul National University of Science and Technology

Papers

1

Total Citations

35

H-Index

1

About

Dr. Seonyoung Park is a leading figure in atmospheric remote sensing, whose work has fundamentally advanced the estimation of aerosol optical depth (AOD) from geostationary satellite data. Her primary research focuses on developing and applying deep neural networks and machine learning models to overcome the limitations of traditional physical models, which struggle to accurately separate aerosol reflectance from underlying surface signals over land. In her landmark 2021 study, cited 35 times, Dr. Park pioneered a novel deep learning method that dramatically improves the spatiotemporal estimation of hourly AOD from the GOCI geostationary satellite. This contribution is critical for monitoring air quality and understanding climate dynamics, as it provides more precise, high-frequency data essential for tracking pollution transport and radiative forcing. By bridging the gap between complex physical theory and practical, high-resolution satellite retrieval, Dr. Park’s work has set a new standard in the field, empowering researchers and policymakers with better tools for environmental monitoring and public health protection.

Research Focus

Key Achievements

1
H-Index
1
Papers
35
Total Citations
35
Avg Citations/Paper
🏆 Most Cited Paper
Estimation of the Hourly Aerosol Optical Depth From GOCI Geostationary Satellite Data: Deep Neural Network, Machine Learning, and Physical Models
35 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Seoul National University of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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