ArticleIEEE International Geoscience and Remote Sensing Symposium proceedings. International Geoscience and Remote Sensing Symposium2023
INCREASING THE SPATIAL COVERAGE OF ATMOSPHERIC AEROSOL DEPTH MEASUREMENTS USING RANDOM FOREST AND MEAN FILTERS.
Article in IEEE International Geoscience and Remote Sensing Symposium proceedings. International Geoscience and Remote Sensing Symposium, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- High-Resolution Estimation of Daily PMRemote sensing · 2025Article
- Performance and generalizability impacts of incorporating location encoders into deep learning for dynamic PMGIScience & remote sensing · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
Aerosols play a critical role in atmospheric chemistry, and affect clouds, climate, and human health. However, the spatial coverage of satellite-derived aerosol optical depth (AOD) products is limited by cloud cover, orbit patterns, polar night, snow, and bright surfaces, which negatively impacts the coverage and accuracy of particulate matter modeling and health studies relying on air pollution characterization. We present a random forest model trained to capture spatial dependence of AOD and produce higher coverage through imputation. By combining the models with and without the mean filters, we are able to create full-coverage high-resolution daily AOD in the conterminous U.S., which can be used for aerosol estimation and other studies leveraging air pollutant concentration levels.
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Registered trials
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