Continuous daily maps of fine particulate matter (PM2.5) air quality in East Asia by application of a random forest algorithm to GOCI geostationary satellite data Article Swipe
Drew C. Pendergrass
,
Daniel Jacob
,
Shixian Zhai
,
Jhoon Kim
,
Ja‐Ho Koo
,
Seoyoung Lee
,
Minah Bae
,
Soontae Kim
,
Hong Liao
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7910/dvn/0l3ip7
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7910/dvn/0l3ip7
We use 2011-2019 aerosol optical depth (AOD) observations from the Geostationary Ocean Color Imager (GOCI) instrument over East Asia to infer 24-h daily surface fine particulate matter (PM2.5) concentrations at continuous 6km x 6km resolution over South Korea, eastern China, and Japan. We use PM2.5 observations from national networks to train and cross-validate a random forest (RF) algorithm that predicts PM2.5 from the gap-filled GOCI AOD, meteorological variables, and other predictor variables. The predicted 24-h PM2.5 for sites entirely withheld from training in a ten-fold crossvalidation procedure correlates highly with observed concentrations (R2 = 0.89) with single-value precision of 26-32% depending on country. Prediction of annual mean values has R2 = 0.96 and single-value precision of 12%. More information is available in the associated publication. Here we supply a NetCDF containing the inferred daily PM2.5 fields from 2011-19 for use in further research. If you use this data, please cite the associated publication, and feel free to reach out via email to discuss this work.
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Metadata
- Type
- dataset
- Language
- en
- Landing Page
- https://doi.org/10.7910/dvn/0l3ip7
- OA Status
- green
- Cited By
- 3
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4398327017
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4398327017Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.7910/dvn/0l3ip7Digital Object Identifier
- Title
-
Continuous daily maps of fine particulate matter (PM2.5) air quality in East Asia by application of a random forest algorithm to GOCI geostationary satellite dataWork title
- Type
-
datasetOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-08-22Full publication date if available
- Authors
-
Drew C. Pendergrass, Daniel Jacob, Shixian Zhai, Jhoon Kim, Ja‐Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong LiaoList of authors in order
- Landing page
-
https://doi.org/10.7910/dvn/0l3ip7Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.7910/dvn/0l3ip7Direct OA link when available
- Concepts
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Geostationary orbit, Particulates, Environmental science, Air quality index, Satellite, Remote sensing, Algorithm, Meteorology, Computer science, Geography, Chemistry, Physics, Astronomy, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
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2022: 2, 2021: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2021-08-22 |
| publication_year | 2021 |
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