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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:

A machine learning-based framework for high resolution mapping of PM2.5 in Tehran, Iran, using MAIAC AOD data
Hossein Bagheri
Advances in Space Research (2022) Vol. 69, Iss. 9, pp. 3333-3349
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Influence and prediction of PM2.5 through multiple environmental variables in China
Haoyu Jin, Xiaohong Chen, Ruida Zhong, et al.
The Science of The Total Environment (2022) Vol. 849, pp. 157910-157910
Closed Access | Times Cited: 60
Spatiotemporal distribution characteristics of PM2.5 concentration in China from 2000 to 2018 and its impact on population
Haoyu Jin, Ruida Zhong, Moyang Liu, et al.
Journal of Environmental Management (2022) Vol. 323, pp. 116273-116273
Closed Access | Times Cited: 44
Machine learning algorithms for high-resolution prediction of spatiotemporal distribution of air pollution from meteorological and soil parameters
Tao Hai, Ali H. Jawad, A.H. Shather, et al.
Environment International (2023) Vol. 175, pp. 107931-107931
Open Access | Times Cited: 30
Estimation of PM2.5 Concentration across China Based on Multi-Source Remote Sensing Data and Machine Learning Methods
Yujie Yang, Zhige Wang, Chunxiang Cao, et al.
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 467-467
Open Access | Times Cited: 11
Optimizing Urban Critical Green Space Development Using Machine Learning
Mohammad Ganjirad, M. R. Delavar, Hossein Bagheri, et al.
Sustainable Cities and Society (2025), pp. 106158-106158
Closed Access | Times Cited: 1
Modeling PM2.5 forecast using a self-weighted ensemble GRU network: Method optimization and evaluation
Hengjun Huang, Chonghui Qian
Ecological Indicators (2023) Vol. 156, pp. 111138-111138
Open Access | Times Cited: 20
Evaluation of four meteorological reanalysis datasets for satellite-based PM2.5 retrieval over China
Chen Zuo, Jiayi Chen, Yue Zhang, et al.
Atmospheric Environment (2023) Vol. 305, pp. 119795-119795
Closed Access | Times Cited: 19
Interpreting hourly mass concentrations of PM2.5 chemical components with an optimal deep-learning model
Hongyi Li, Ting Yang, Yiming Du, et al.
Journal of Environmental Sciences (2024) Vol. 151, pp. 125-139
Closed Access | Times Cited: 7
PM2.5 Estimation using Machine Learning Models and Satellite Data: A Literature Review
Mitra Unik, Imas Sukaesih Sitanggang, Lailan Syaufina, et al.
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 5
Open Access | Times Cited: 15
An investigation of PM2.5 concentration changes in Mid-Eastern China before and after COVID-19 outbreak
Yongjun Zhang, Wenpin Wu, Yiliang Li, et al.
Environment International (2023) Vol. 175, pp. 107941-107941
Open Access | Times Cited: 14
Long term spatiotemporal trends and health risk assessment of remotely sensed PM2.5 concentrations in Nigeria
Salman Tariq, Ayesha Mariam, Usman Mehmood, et al.
Environmental Pollution (2023) Vol. 324, pp. 121382-121382
Closed Access | Times Cited: 11
A Novel Evolutionary Deep Learning Approach for PM2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran
Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh
ISPRS International Journal of Geo-Information (2025) Vol. 14, Iss. 2, pp. 42-42
Open Access
Estimating PM2.5 Concentrations Using the Machine Learning RF-XGBoost Model in Guanzhong Urban Agglomeration, China
Lujun Lin, Yongchun Liang, Lei Liu, et al.
Remote Sensing (2022) Vol. 14, Iss. 20, pp. 5239-5239
Open Access | Times Cited: 18
Data level and decision level fusion of satellite multi-sensor AOD retrievals for improving PM2.5 estimations, a study on Tehran
Ali Mirzaei, Hossein Bagheri, Mehran Sattari
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 753-771
Closed Access | Times Cited: 10
State-of-art in modelling particulate matter (PM) concentration: a scoping review of aims and methods
Lorenzo Gianquintieri, Daniele Oxoli, Enrico G. Caiani, et al.
Environment Development and Sustainability (2024)
Open Access | Times Cited: 3
Characterizing Air Pollution and Its Association with Emission Sources in Lahore: A Guide to Adaptation Action Plans to Control Pollution and Smog
Mifrah Ali, Iffat Siddique, Sawaid Abbas
Applied Sciences (2022) Vol. 12, Iss. 10, pp. 5102-5102
Open Access | Times Cited: 12
Using deep ensemble forest for high-resolution mapping of PM2.5 from MODIS MAIAC AOD in Tehran, Iran
Hossein Bagheri
Environmental Monitoring and Assessment (2023) Vol. 195, Iss. 3
Closed Access | Times Cited: 6
Using satellite data on remote transportation of air pollutants for PM2.5 prediction in northern Taiwan
George Kibirige, Ming-Chuan Yang, Chao-Lin Liu, et al.
PLoS ONE (2023) Vol. 18, Iss. 3, pp. e0282471-e0282471
Open Access | Times Cited: 6
A New Attention-Based a convolutional neural network-gated recurrent unit Model for Spatial-Temporal PM2.5 Prediction
Sara Haghbayan, Mehdi Momeni, Behnam Tashayo
Research Square (Research Square) (2024)
Open Access | Times Cited: 1
Drivers and Decoupling Effects of PM2.5 Emissions in China: An Application of the Generalized Divisia Index
Shangjiu Wang, Shaohua Zhang, Liang Cheng
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 2, pp. 921-921
Open Access | Times Cited: 3
Meteorological influences on PM2.5 variation in China using a hybrid model of machine learning and the Kolmogorov-Zurbenko filter
Shuang Gao, Xin Cheng, Jie Yu, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 11, pp. 101905-101905
Closed Access | Times Cited: 3
Assessment of variability in PM2.5 and its impact on human health in a West African country
Salman Tariq, Ayesha Mariam, Zia ul Haq, et al.
Chemosphere (2023) Vol. 344, pp. 140357-140357
Closed Access | Times Cited: 3
Study on Spatial Changes in PM2.5 before and after the COVID-19 Pandemic in Southwest China
Xing Li, Jingchun Zhou, Jinliang Wang, et al.
Atmosphere (2023) Vol. 14, Iss. 4, pp. 671-671
Open Access | Times Cited: 2
Prediction of hourly PM10 concentration through a hybrid deep learning-based method
Sahar Nasabpour Molaei, Ali Salajegheh, Hassan Khosravi, et al.
Earth Science Informatics (2023) Vol. 17, Iss. 1, pp. 37-49
Closed Access | Times Cited: 2
A new attention-based CNN_GRU model for spatial–temporal PM2.5 prediction
Sara Haghbayan, Mehdi Momeni, Behnam Tashayo
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 40, pp. 53140-53155
Closed Access
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