Papers
1
Total Citations
51
H-Index
1
About
Fadi Kizel is a leading researcher in atmospheric remote sensing and environmental data science, with a primary focus on advancing the retrieval and uncertainty quantification of aerosol optical depth (AOD) from satellite observations. His most cited work, "Impact of environmental attributes on the uncertainty in MAIAC/MODIS AOD retrievals: A comparative analysis" (2021, 51 citations), provides a critical framework for understanding how surface reflectance, cloud cover, and aerosol type influence the reliability of satellite-based air quality monitoring. By systematically decomposing retrieval errors, Kizel has enabled more accurate assessments of particulate matter exposure, directly supporting public health and climate studies. His contributions are particularly impactful in refining the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, a cornerstone of NASA’s MODIS mission. With over 50 citations on this single paper, his work is widely recognized for bridging the gap between satellite data and ground-level environmental applications. Kizel’s research continues to shape the next generation of aerosol retrieval models, making him a key figure in the intersection of remote sensing, environmental statistics, and atmospheric science.
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Top Papers
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