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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea
Seohui Park, Minso Shin, Jungho Im, et al.
Atmospheric chemistry and physics (2019) Vol. 19, Iss. 2, pp. 1097-1113
Open Access | Times Cited: 89

Showing 1-25 of 89 citing articles:

New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)
Jhoon Kim, Ukkyo Jeong, Myoung‐Hwan Ahn, et al.
Bulletin of the American Meteorological Society (2019) Vol. 101, Iss. 1, pp. E1-E22
Open Access | Times Cited: 322
Forecasting Air Pollution Particulate Matter (PM2.5) Using Machine Learning Regression Models
Doreswamy, K S Harishkumar, Yogesh KM, et al.
Procedia Computer Science (2020) Vol. 171, pp. 2057-2066
Open Access | Times Cited: 209
Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia
Yoojin Kang, Hyunyoung Choi, Jungho Im, et al.
Environmental Pollution (2021) Vol. 288, pp. 117711-117711
Closed Access | Times Cited: 138
A review of machine learning for modeling air quality: Overlooked but important issues
Dié Tang, Yu Zhan, Fumo Yang
Atmospheric Research (2024) Vol. 300, pp. 107261-107261
Closed Access | Times Cited: 37
Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign
Myungje Choi, Hyunkwang Lim, Jhoon Kim, et al.
Atmospheric measurement techniques (2019) Vol. 12, Iss. 8, pp. 4619-4641
Open Access | Times Cited: 111
Estimating ground-level particulate matter concentrations using satellite-based data: a review
Minso Shin, Yoojin Kang, Seohui Park, et al.
GIScience & Remote Sensing (2019) Vol. 57, Iss. 2, pp. 174-189
Closed Access | Times Cited: 105
Influence of cloud, fog, and high relative humidity during pollution transport events in South Korea: Aerosol properties and PM2.5 variability
T. F. Eck, B. N. Holben, Jhoon Kim, et al.
Atmospheric Environment (2020) Vol. 232, pp. 117530-117530
Open Access | Times Cited: 71
Geographical and temporal encoding for improving the estimation of PM2.5 concentrations in China using end-to-end gradient boosting
Naisen Yang, Haoze Shi, Hong Tang, et al.
Remote Sensing of Environment (2021) Vol. 269, pp. 112828-112828
Open Access | Times Cited: 63
Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia
Seoyoung Lee, Myungje Choi, Jhoon Kim, et al.
The Science of The Total Environment (2023) Vol. 903, pp. 166504-166504
Open Access | Times Cited: 22
A continuous 2011-2022 record of fine particulate matter (PM2.5) in East Asia at daily 2-km resolution from geostationary satellite observations: population exposure and long-term trends
Drew C. Pendergrass, Daniel Jacob, Yujin J. Oak, et al.
Atmospheric Environment (2025), pp. 121068-121068
Open Access | Times Cited: 1
Estimation of spatially continuous daytime particulate matter concentrations under all sky conditions through the synergistic use of satellite-based AOD and numerical models
Seohui Park, Junghee Lee, Jungho Im, et al.
The Science of The Total Environment (2020) Vol. 713, pp. 136516-136516
Closed Access | Times Cited: 55
Application of Random Forest Algorithm for Merging Multiple Satellite Precipitation Products across South Korea
Giang V. Nguyen, Xuan-Hien Le, Linh Nguyen Van, et al.
Remote Sensing (2021) Vol. 13, Iss. 20, pp. 4033-4033
Open Access | Times Cited: 47
Two-step carbon storage estimation in urban human settlements using airborne LiDAR and Sentinel-2 data based on machine learning
Yeonsu Lee, Bokyung Son, Jungho Im, et al.
Urban forestry & urban greening (2024) Vol. 94, pp. 128239-128239
Closed Access | Times Cited: 7
A Review on Estimation of Particulate Matter from Satellite-Based Aerosol Optical Depth: Data, Methods, and Challenges
Avinash Kumar Ranjan, Aditya Kumar Patra, Amit Kumar Gorai
Asia-Pacific Journal of Atmospheric Sciences (2020) Vol. 57, Iss. 3, pp. 679-699
Closed Access | Times Cited: 40
Review of satellite-driven statistical modelsPM2.5concentration estimation with comprehensive information
Xinghan Xu, Chengkun Zhang, Yi Liang
Atmospheric Environment (2021) Vol. 256, pp. 118302-118302
Closed Access | Times Cited: 33
A data-augmentation approach to deriving long-term surface SO2 across Northern China: Implications for interpretable machine learning
Shifu Zhang, Tan Mi, Qinhuizi Wu, et al.
The Science of The Total Environment (2022) Vol. 827, pp. 154278-154278
Closed Access | Times Cited: 26
Continuous mapping of fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia at daily 6 × 6 km<sup>2</sup> resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, et al.
Atmospheric measurement techniques (2022) Vol. 15, Iss. 4, pp. 1075-1091
Open Access | Times Cited: 24
Retrieval of hourly PM2.5 using top-of-atmosphere reflectance from geostationary ocean color imagers I and II
Hyunyoung Choi, Seonyoung Park, Yoojin Kang, et al.
Environmental Pollution (2023) Vol. 323, pp. 121169-121169
Closed Access | Times Cited: 13
Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data
S. Y. Zhu, Jiayi Tang, Xiaolu Zhou, et al.
Environmental Reviews (2023) Vol. 31, Iss. 4, pp. 605-631
Open Access | Times Cited: 13
Regional Difference in the Association Between Long‐Term PM and Cardiovascular Disease Incidence and Potential Determinants of the Difference
Ok‐Jin Kim, Sun‐Young Kim
GeoHealth (2025) Vol. 9, Iss. 3
Open Access
Machine learning algorithms for air quality and air pollution monitoring using GEE
Prakriti Prakriti, Manivannan Karuppaiyan, Asfa Siddiqui, et al.
Elsevier eBooks (2025), pp. 135-175
Closed Access
Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning
Roland Stirnberg, Jan Čermák, Julia Fuchs, et al.
Journal of Geophysical Research Atmospheres (2020) Vol. 125, Iss. 4
Open Access | Times Cited: 38
Spatial mapping of short-term solar radiation prediction incorporating geostationary satellite images coupled with deep convolutional LSTM networks for South Korea
Jong‐Min Yeom, Ravinesh C. Deo, Jan Adamowski, et al.
Environmental Research Letters (2020) Vol. 15, Iss. 9, pp. 094025-094025
Open Access | Times Cited: 34
A new drought monitoring approach: Vector Projection Analysis (VPA)
Bokyung Son, Soomin Park, Jungho Im, et al.
Remote Sensing of Environment (2020) Vol. 252, pp. 112145-112145
Closed Access | Times Cited: 34
Developing a New Hourly Forest Fire Risk Index Based on Catboost in South Korea
Yoojin Kang, Eunna Jang, Jungho Im, et al.
Applied Sciences (2020) Vol. 10, Iss. 22, pp. 8213-8213
Open Access | Times Cited: 33
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