Papers
2
Total Citations
22
H-Index
2
About
Dongho Shin is an atmospheric scientist whose research focuses on aerosol classification, air quality monitoring, and the optical properties of dust particles in the atmosphere. His work is particularly relevant to understanding pollution transport and aerosol dynamics across Asia. In his most cited study (2021, 19 citations), Shin developed a satellite-based random forest model to classify aerosol types over capital cities in Asia, integrating Aerosol Robotic Network (AERONET) observations to improve accuracy. This work provides a scalable framework for monitoring urban air pollution using machine learning and remote sensing. In an earlier study (2013), Shin tackled the complex challenge of retrieving the vertical single-scattering albedo of Asian dust using a multi-wavelength Raman lidar system. By exploiting the relationship between polarization extinction and dust mixing ratios, he developed a method to separate pure dust from polluted dust, enabling more precise characterization of aerosol radiative effects. Though his citation counts are modest, Shin’s contributions are technically rigorous and address pressing environmental issues in East Asia. His work bridges lidar remote sensing, satellite data, and machine learning, offering valuable tools for atmospheric research and policy-making in regions heavily impacted by dust storms and anthropogenic aerosols.
Research Focus
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Top Papers
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