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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:

Impacts of snow and cloud covers on satellite-derived PM2.5 levels
Jianzhao Bi, Jessica H. Belle, Yujie Wang, et al.
Remote Sensing of Environment (2018) Vol. 221, pp. 665-674
Open Access | Times Cited: 111

Showing 1-25 of 111 citing articles:

Incorporating Low-Cost Sensor Measurements into High-Resolution PM2.5 Modeling at a Large Spatial Scale
Jianzhao Bi, Avani Wildani, Howard H. Chang, et al.
Environmental Science & Technology (2020) Vol. 54, Iss. 4, pp. 2152-2162
Open Access | Times Cited: 179
Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US
Marissa L. Childs, Jessica Li, Jeff Wen, et al.
Environmental Science & Technology (2022) Vol. 56, Iss. 19, pp. 13607-13621
Closed Access | Times Cited: 116
LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion
Kaixu Bai, Ke Li, Mingliang Ma, et al.
Earth system science data (2022) Vol. 14, Iss. 2, pp. 907-927
Open Access | Times Cited: 95
Global synthesis of two decades of research on improving PM2.5 estimation models from remote sensing and data science perspectives
Kaixu Bai, Ke Li, Yibing Sun, et al.
Earth-Science Reviews (2023) Vol. 241, pp. 104461-104461
Closed Access | Times Cited: 40
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: 31
Evaluation of gap-filling approaches in satellite-based daily PM2.5 prediction models
Qingyang Xiao, Guannan Geng, Jing Cheng, et al.
Atmospheric Environment (2020) Vol. 244, pp. 117921-117921
Closed Access | Times Cited: 129
Estimating PM2.5 concentrations in Northeastern China with full spatiotemporal coverage, 2005–2016
Xia Meng, Cong Liu, Lina Zhang, et al.
Remote Sensing of Environment (2020) Vol. 253, pp. 112203-112203
Open Access | Times Cited: 120
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: 104
Robust prediction of hourly PM2.5 from meteorological data using LightGBM
Junting Zhong, Xiaoye Zhang, Ke Gui, et al.
National Science Review (2020) Vol. 8, Iss. 10
Open Access | Times Cited: 102
High-Resolution Spatiotemporal Modeling for Ambient PM2.5 Exposure Assessment in China from 2013 to 2019
Conghong Huang, Jianlin Hu, Tao Xue, et al.
Environmental Science & Technology (2021) Vol. 55, Iss. 3, pp. 2152-2162
Closed Access | Times Cited: 100
A review of statistical methods used for developing large-scale and long-term PM2.5 models from satellite data
Zongwei Ma, Sagnik Dey, Sundar Christopher, et al.
Remote Sensing of Environment (2021) Vol. 269, pp. 112827-112827
Open Access | Times Cited: 99
Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models
Minghui Diao, Tracey Holloway, Seohyun Choi, et al.
Journal of the Air & Waste Management Association (2019) Vol. 69, Iss. 12, pp. 1391-1414
Open Access | Times Cited: 91
Satellite remote sensing of atmospheric particulate matter mass concentration: Advances, challenges, and perspectives
Ying Zhang, Zhengqiang Li, Kaixu Bai, et al.
Fundamental Research (2021) Vol. 1, Iss. 3, pp. 240-258
Open Access | Times Cited: 87
Contribution of low-cost sensor measurements to the prediction of PM2.5 levels: A case study in Imperial County, California, USA
Jianzhao Bi, Jennifer Stowell, Edmund Seto, et al.
Environmental Research (2019) Vol. 180, pp. 108810-108810
Open Access | Times Cited: 77
Satellite Monitoring for Air Quality and Health
Tracey Holloway, Daegan Miller, Susan C. Anenberg, et al.
Annual Review of Biomedical Data Science (2021) Vol. 4, Iss. 1, pp. 417-447
Open Access | Times Cited: 69
A machine learning model to estimate ground-level ozone concentrations in California using TROPOMI data and high-resolution meteorology
Wenhao Wang, Xiong Liu, Jianzhao Bi, et al.
Environment International (2021) Vol. 158, pp. 106917-106917
Open Access | Times Cited: 67
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: 62
Estimating daily full-coverage surface ozone concentration using satellite observations and a spatiotemporally embedded deep learning approach
Tongwen Li, Xiao Cheng
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 101, pp. 102356-102356
Open Access | Times Cited: 61
A geographic information-driven method and a new large scale dataset for remote sensing cloud/snow detection
Xi Wu, Zhenwei Shi, Zhengxia Zou
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 174, pp. 87-104
Closed Access | Times Cited: 59
Combining Machine Learning and Numerical Simulation for High-Resolution PM2.5 Concentration Forecast
Jianzhao Bi, K. Emma Knowland, Christoph A. Keller, et al.
Environmental Science & Technology (2022) Vol. 56, Iss. 3, pp. 1544-1556
Closed Access | Times Cited: 50
Air quality forecasting with artificial intelligence techniques: A scientometric and content analysis
Yanzhao Li, Ju’e Guo, Shaolong Sun, et al.
Environmental Modelling & Software (2022) Vol. 149, pp. 105329-105329
Closed Access | Times Cited: 41
Estimating daily ground-level PM2.5 in China with random-forest-based spatiotemporal kriging
Yanchuan Shao, Zongwei Ma, Jianghao Wang, et al.
The Science of The Total Environment (2020) Vol. 740, pp. 139761-139761
Closed Access | Times Cited: 64
Satellite-based estimation of hourly PM2.5 levels during heavy winter pollution episodes in the Yangtze River Delta, China
Qiannan She, Myungje Choi, Jessica H. Belle, et al.
Chemosphere (2019) Vol. 239, pp. 124678-124678
Open Access | Times Cited: 55
Mapping monthly population distribution and variation at 1-km resolution across China
Zhifeng Cheng, Jianghao Wang, Yong Ge
International Journal of Geographical Information Science (2020) Vol. 36, Iss. 6, pp. 1166-1184
Closed Access | Times Cited: 54
Estimating 2013–2019 NO2 exposure with high spatiotemporal resolution in China using an ensemble model
Conghong Huang, Kang Sun, Jianlin Hu, et al.
Environmental Pollution (2021) Vol. 292, pp. 118285-118285
Open Access | Times Cited: 46
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