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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:

Estimating PM2.5 concentration of the conterminous United States via interpretable convolutional neural networks
Yongbee Park, Byungjoon Kwon, Juyeon Heo, et al.
Environmental Pollution (2019) Vol. 256, pp. 113395-113395
Closed Access | Times Cited: 118

Showing 1-25 of 118 citing articles:

Deep learning in environmental remote sensing: Achievements and challenges
Qiangqiang Yuan, Huanfeng Shen, Tongwen Li, et al.
Remote Sensing of Environment (2020) Vol. 241, pp. 111716-111716
Closed Access | Times Cited: 1177
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 3, pp. 247-278
Open Access | Times Cited: 152
Associations between wildfire smoke exposure during pregnancy and risk of preterm birth in California
Sam Heft-Neal, Anne Driscoll, Wei Yang, et al.
Environmental Research (2021) Vol. 203, pp. 111872-111872
Closed Access | Times Cited: 127
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: 118
PM2.5 volatility prediction by XGBoost-MLP based on GARCH models
Hongbin Dai, Guangqiu Huang, Huibin Zeng, et al.
Journal of Cleaner Production (2022) Vol. 356, pp. 131898-131898
Closed Access | Times Cited: 79
Long-term mortality burden trends attributed to black carbon and PM2·5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study
Jing Wei, Jun Wang, Zhanqing Li, et al.
The Lancet Planetary Health (2023) Vol. 7, Iss. 12, pp. e963-e975
Open Access | Times Cited: 47
A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023
Xuying Ma, Bin Zou, Jun Deng, et al.
Environment International (2024) Vol. 183, pp. 108430-108430
Open Access | Times Cited: 42
Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning
Siyuan Shen, Chi Li, Aaron van Donkelaar, et al.
ACS ES&T Air (2024) Vol. 1, Iss. 5, pp. 332-345
Closed Access | Times Cited: 15
A Comparison of Machine Learning-Based Approaches in Estimating Surface PM2.5 Concentrations Focusing on Artificial Neural Networks and High Pollution Events
Su-Huai Wei, Kyle Shores, Yangyang Xu
Atmosphere (2025) Vol. 16, Iss. 1, pp. 48-48
Open Access | Times Cited: 2
Explore spatio-temporal PM2.5 features in northern Taiwan using machine learning techniques
Fi‐John Chang, Li‐Chiu Chang, Che-Chia Kang, et al.
The Science of The Total Environment (2020) Vol. 736, pp. 139656-139656
Closed Access | Times Cited: 83
Instance Segmentation for Large, Multi-Channel Remote Sensing Imagery Using Mask-RCNN and a Mosaicking Approach
Osmar Luiz Ferreira de Carvalho, Osmar Abílio de Carvalho Júnior, Anesmar Olino de Albuquerque, et al.
Remote Sensing (2020) Vol. 13, Iss. 1, pp. 39-39
Open Access | Times Cited: 76
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 74
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
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: 62
Deep Learning Estimation of Daily Ground‐Level NO2 Concentrations From Remote Sensing Data
Masoud Ghahremanloo, Yannic Lops, Yunsoo Choi, et al.
Journal of Geophysical Research Atmospheres (2021) Vol. 126, Iss. 21
Open Access | Times Cited: 58
Estimating daily high-resolution PM2.5 concentrations over Texas: Machine Learning approach
Masoud Ghahremanloo, Yunsoo Choi, Alqamah Sayeed, et al.
Atmospheric Environment (2021) Vol. 247, pp. 118209-118209
Open Access | Times Cited: 57
Prediction of Monthly PM2.5 Concentration in Liaocheng in China Employing Artificial Neural Network
Zhenfang He, Qingchun Guo, Zhaosheng Wang, et al.
Atmosphere (2022) Vol. 13, Iss. 8, pp. 1221-1221
Open Access | Times Cited: 55
A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency
Yoojin Kang, Eunna Jang, Jungho Im, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 2019-2035
Open Access | Times Cited: 54
Nearest neighbour distance matching Leave‐One‐Out Cross‐Validation for map validation
Carles Milà, Jorge Mateu, Edzer Pebesma, et al.
Methods in Ecology and Evolution (2022) Vol. 13, Iss. 6, pp. 1304-1316
Open Access | Times Cited: 51
Deciphering urban traffic impacts on air quality by deep learning and emission inventory
Wenjie Du, Lianliang Chen, Haoran Wang, et al.
Journal of Environmental Sciences (2022) Vol. 124, pp. 745-757
Closed Access | Times Cited: 39
An interpretable self-adaptive deep neural network for estimating daily spatially-continuous PM2.5 concentrations across China
Binjie Chen, Shixue You, Ye Yang, et al.
The Science of The Total Environment (2021) Vol. 768, pp. 144724-144724
Open Access | Times Cited: 53
Ground PM2.5 prediction using imputed MAIAC AOD with uncertainty quantification
Qiang Pu, Eun‐Hye Yoo
Environmental Pollution (2021) Vol. 274, pp. 116574-116574
Closed Access | Times Cited: 43
Daily PM2.5 concentration estimates by county, ZIP code, and census tract in 11 western states 2008–2018
Colleen E. Reid, Ellen M. Considine, M. M. Maestas, et al.
Scientific Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 42
Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter
Bavand Sadeghi, Masoud Ghahremanloo, Seyedali Mousavinezhad, et al.
Environmental Pollution (2022) Vol. 310, pp. 119863-119863
Closed Access | Times Cited: 36
A comprehensive study of the COVID-19 impact on PM2.5 levels over the contiguous United States: A deep learning approach
Masoud Ghahremanloo, Yannic Lops, Yunsoo Choi, et al.
Atmospheric Environment (2022) Vol. 272, pp. 118944-118944
Open Access | Times Cited: 35
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