Papers
3
Total Citations
173
H-Index
3
About
Dr. Kaixu Bai is a leading figure in environmental data science, specializing in big Earth data analytics, atmospheric remote sensing, and air quality monitoring. His most transformative contribution is the development of the Long-term Gap-free High-resolution Air Pollutant concentration (LGHAP) dataset. The inaugural LGHAP paper (2022, 143 citations) introduced a novel tensor-flow-based multimodal data fusion framework to generate seamless, high-resolution air pollutant maps across China. Dr. Bai then advanced this work with LGHAP v2 (2024, 27 citations), expanding the dataset to a global scale, providing gap-free daily aerosol optical depth and PM2.5 concentrations at a 1 km resolution since 2000. This achievement is a cornerstone for environmental management and Earth system science, enabling unprecedented long-term, high-fidelity analysis of particulate pollution. His early research also includes integrating satellite and ground-based measurements to characterize severe dust events, such as the 2012 Beijing dust storm. Through his pioneering work in creating these critical, open-access datasets, Dr. Bai has empowered researchers worldwide to conduct robust epidemiological, climatic, and policy-driven studies on air quality and its impacts.
Research Focus
Key Achievements
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