Papers
8
Total Citations
1,921
H-Index
7
About
Jingfeng Huang is a prominent atmospheric scientist whose research has fundamentally advanced our understanding of aerosol retrieval from satellite remote sensing. Specializing in aerosol optical properties, satellite algorithms, and atmospheric correction techniques, Huang has made landmark contributions to improving how scientists measure particulate matter in Earth's atmosphere from space. His most celebrated work includes co-developing the Enhanced Deep Blue aerosol retrieval algorithm for MODIS, now a cornerstone methodology for studying aerosols over bright land surfaces like deserts and urban regions, amassing over 1,200 citations. Huang has also played a pivotal role in developing and validating aerosol data products for the Suomi-NPP VIIRS instrument, helping establish a new generation of operational environmental sensors capable of continuing decades of critical global aerosol observations — work collectively cited hundreds of times across multiple studies. Beyond algorithm development, Huang has tackled challenging data quality issues, including cirrus cloud contamination in aerosol retrievals and snow screening in VIIRS products, demonstrating a meticulous commitment to measurement accuracy. His research directly supports climate science, air quality monitoring, and public health applications worldwide. With a cumulative citation count exceeding 1,900, Huang's contributions represent an enduring foundation for satellite-based aerosol science.
Research Focus
Key Achievements
Top Papers
- 1Enhanced Deep Blue aerosol retrieval algorithm: The second generation1,202 citations · 2013
- 2Suomi‐NPP VIIRS aerosol algorithms and data products301 citations · 2013
- 3Preliminary evaluation of S‐NPP VIIRS aerosol optical thickness151 citations · 2014
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