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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 Regional Ground‐Level PM2.5 Directly From Satellite Top‐Of‐Atmosphere Reflectance Using Deep Belief Networks
Huanfeng Shen, Tongwen Li, Qiangqiang Yuan, et al.
Journal of Geophysical Research Atmospheres (2018) Vol. 123, Iss. 24
Open Access | Times Cited: 134

Showing 1-25 of 134 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: 1198
PM2.5 Prediction Based on Random Forest, XGBoost, and Deep Learning Using Multisource Remote Sensing Data
Mehdi Zamani, Chunxiang Cao, Xiliang Ni, et al.
Atmosphere (2019) Vol. 10, Iss. 7, pp. 373-373
Open Access | Times Cited: 417
The relationships between PM2.5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations
Qianqian Yang, Qiangqiang Yuan, Linwei Yue, et al.
Environmental Pollution (2019) Vol. 248, pp. 526-535
Open Access | Times Cited: 169
Deep learning-based air temperature mapping by fusing remote sensing, station, simulation and socioeconomic data
Huanfeng Shen, Yun Jiang, Tongwen Li, et al.
Remote Sensing of Environment (2020) Vol. 240, pp. 111692-111692
Closed Access | Times Cited: 143
Machine learning and remote sensing integration for leveraging urban sustainability: A review and framework
Fei Li, Tan Yiğitcanlar, Madhav Prasad Nepal, et al.
Sustainable Cities and Society (2023) Vol. 96, pp. 104653-104653
Open Access | Times Cited: 99
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
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
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
Estimating daily full-coverage near surface O3, CO, and NO2 concentrations at a high spatial resolution over China based on S5P-TROPOMI and GEOS-FP
Yuan Wang, Qiangqiang Yuan, Tongwen Li, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 175, pp. 311-325
Open Access | Times Cited: 98
New interpretable deep learning model to monitor real-time PM2.5 concentrations from satellite data
Xing Yan, Zhou Zang, Nana Luo, et al.
Environment International (2020) Vol. 144, pp. 106060-106060
Open Access | Times Cited: 97
Reconstructing Geostationary Satellite Land Surface Temperature Imagery Based on a Multiscale Feature Connected Convolutional Neural Network
Penghai Wu, Zhixiang Yin, Hui Yang, et al.
Remote Sensing (2019) Vol. 11, Iss. 3, pp. 300-300
Open Access | Times Cited: 92
Geographically and temporally weighted neural networks for satellite-based mapping of ground-level PM2.5
Tongwen Li, Huanfeng Shen, Qiangqiang Yuan, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 167, pp. 178-188
Open Access | Times Cited: 87
SAR Image Despeckling by Noisy Reference-Based Deep Learning Method
Xiaoshuang Ma, Chen Wang, Zhixiang Yin, et al.
IEEE Transactions on Geoscience and Remote Sensing (2020) Vol. 58, Iss. 12, pp. 8807-8818
Closed Access | Times Cited: 85
A Spatial-Temporal Interpretable Deep Learning Model for improving interpretability and predictive accuracy of satellite-based PM2.5
Xing Yan, Zhou Zang, Yize Jiang, et al.
Environmental Pollution (2021) Vol. 273, pp. 116459-116459
Open Access | Times Cited: 80
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: 78
Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder
Yihui Xiong, Renguang Zuo
Mathematical Geosciences (2021) Vol. 54, Iss. 3, pp. 623-644
Closed Access | Times Cited: 66
Reviewing the application of machine learning methods to model urban form indicators in planning decision support systems: Potential, issues and challenges
Stéphane Cédric Koumetio Tekouabou, El Bachir Diop, Rida Azmi, et al.
Journal of King Saud University - Computer and Information Sciences (2021) Vol. 34, Iss. 8, pp. 5943-5967
Open Access | Times Cited: 59
Synergistic observation of FY-4A&4B to estimate CO concentration in China: combining interpretable machine learning to reveal the influencing mechanisms of CO variations
Bin Chen, Jiashun Hu, Yixuan Wang
npj Climate and Atmospheric Science (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 11
Temporal and Spatial Features of the Correlation between PM2.5 and O3 Concentrations in China
Jiajia Chen, Huanfeng Shen, Tongwen Li, et al.
International Journal of Environmental Research and Public Health (2019) Vol. 16, Iss. 23, pp. 4824-4824
Open Access | Times Cited: 67
Estimate hourly PM2.5 concentrations from Himawari-8 TOA reflectance directly using geo-intelligent long short-term memory network
Bin Wang, Qiangqiang Yuan, Qianqian Yang, et al.
Environmental Pollution (2020) Vol. 271, pp. 116327-116327
Closed Access | Times Cited: 62
Impacts of urban form on air quality: Emissions on the road and concentrations in the US metropolitan areas
Changyeon Lee
Journal of Environmental Management (2019) Vol. 246, pp. 192-202
Closed Access | Times Cited: 61
Advancing the prediction accuracy of satellite-based PM2.5 concentration mapping: A perspective of data mining through in situ PM2.5 measurements
Kaixu Bai, Ke Li, Ni‐Bin Chang, et al.
Environmental Pollution (2019) Vol. 254, pp. 113047-113047
Closed Access | Times Cited: 59
A differential information residual convolutional neural network for pansharpening
Menghui Jiang, Huanfeng Shen, Jie Li, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 163, pp. 257-271
Closed Access | Times Cited: 59
Estimating ground-level PM2.5 using micro-satellite images by a convolutional neural network and random forest approach
Tongshu Zheng, Michael Bergin, Shijia Hu, et al.
Atmospheric Environment (2020) Vol. 230, pp. 117451-117451
Closed Access | Times Cited: 55
Investigation of the spatially varying relationships of PM2.5 with meteorology, topography, and emissions over China in 2015 by using modified geographically weighted regression
Qianqian Yang, Qiangqiang Yuan, Linwei Yue, et al.
Environmental Pollution (2020) Vol. 262, pp. 114257-114257
Open Access | Times Cited: 54
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