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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 Robust Deep Learning Approach for Spatiotemporal Estimation of Satellite AOD and PM2.5
Lianfa Li
Remote Sensing (2020) Vol. 12, Iss. 2, pp. 264-264
Open Access | Times Cited: 49

Showing 1-25 of 49 citing articles:

Exceedances and trends of particulate matter (PM2.5) in five Indian megacities
Vikas Singh, Shweta Singh, Akash Biswal
The Science of The Total Environment (2020) Vol. 750, pp. 141461-141461
Open Access | Times Cited: 153
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
Superior PM2.5 Estimation by Integrating Aerosol Fine Mode Data from the Himawari-8 Satellite in Deep and Classical Machine Learning Models
Zhou Zang, Dan Li, Yushan Guo, et al.
Remote Sensing (2021) Vol. 13, Iss. 14, pp. 2779-2779
Open Access | Times Cited: 43
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
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
A novel approach for forecasting PM2.5 pollution in Delhi using CATALYST
Abhishek Verma, Virender Ranga, Dinesh Kumar Vishwakarma
Environmental Monitoring and Assessment (2023) Vol. 195, Iss. 12
Closed Access | Times Cited: 17
Time series retrieval of Multi-wavelength Aerosol optical depth by adapting Transformer (TMAT) using Himawari-8 AHI data
Lu She, Zhengqiang Li, Gerrit de Leeuw, et al.
Remote Sensing of Environment (2024) Vol. 305, pp. 114115-114115
Open Access | Times Cited: 6
Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations
Lu She, Hankui K. Zhang, Zhengqiang Li, et al.
Remote Sensing (2020) Vol. 12, Iss. 24, pp. 4125-4125
Open Access | Times Cited: 44
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: 39
Surface UV-assisted retrieval of spatially continuous surface ozone with high spatial transferability
Ge Song, Siwei Li, Jia Xing, et al.
Remote Sensing of Environment (2022) Vol. 274, pp. 112996-112996
Closed Access | Times Cited: 23
Assessing particulate matter (PM2.5) concentrations and variability across Maharashtra using satellite data and machine learning techniques
Ganesh Machhindra Kunjir, Suvarna Tikle, Sandipan Das, et al.
Discover Sustainability (2025) Vol. 6, Iss. 1
Open Access
Analysis of deep learning approaches for air pollution prediction
Veena Gugnani, Rajeev Kumar Singh
Multimedia Tools and Applications (2022) Vol. 81, Iss. 4, pp. 6031-6049
Closed Access | Times Cited: 20
Retrieval of Fine-Grained PM2.5 Spatiotemporal Resolution Based on Multiple Machine Learning Models
Peilong Ma, Fei Tao, Gao Li-na, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 599-599
Open Access | Times Cited: 20
Remote sensing estimation of surface PM2.5 concentrations using a deep learning model improved by data augmentation and a particle size constraint
Shun‐Chao Yin, Tongwen Li, Xiao Cheng, et al.
Atmospheric Environment (2022) Vol. 287, pp. 119282-119282
Closed Access | Times Cited: 20
Spatiotemporal high-resolution imputation modeling of aerosol optical depth for investigating its full-coverage variation in China from 2003 to 2020
Qingqing He, Weihang Wang, Yimeng Song, et al.
Atmospheric Research (2022) Vol. 281, pp. 106481-106481
Open Access | Times Cited: 20
Estimation of particulate matter concentrations in Türkiye using a random forest model based on satellite AOD retrievals
Gizem Tuna Tuygun, Tolga Elbir
Stochastic Environmental Research and Risk Assessment (2023) Vol. 37, Iss. 9, pp. 3469-3491
Closed Access | Times Cited: 11
Lidar-based daytime boundary layer height variation and impact on the regional satellite-based PM2.5 estimate
Sijie Chen, Bowen Tong, Lynn M. Russell, et al.
Remote Sensing of Environment (2022) Vol. 281, pp. 113224-113224
Open Access | Times Cited: 18
A Deep-Neural-Network-Based Aerosol Optical Depth (AOD) Retrieval from Landsat-8 Top of Atmosphere Data
Lu She, Hankui K. Zhang, Ziqiang Bu, et al.
Remote Sensing (2022) Vol. 14, Iss. 6, pp. 1411-1411
Open Access | Times Cited: 16
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
Full-coverage estimation of PM2.5 in the Beijing-Tianjin-Hebei region by using a two-stage model
Qiaolin Zeng, Yeming Li, Jinhua Tao, et al.
Atmospheric Environment (2023) Vol. 309, pp. 119956-119956
Closed Access | Times Cited: 10
Explainable geospatial-artificial intelligence models for the estimation of PM2.5 concentration variation during commuting rush hours in Taiwan
Pei-Yi Wong, Huey‐Jen Su, Shih‐Chun Candice Lung, et al.
Environmental Pollution (2024) Vol. 349, pp. 123974-123974
Closed Access | Times Cited: 3
Improving spectral estimation of soil inorganic carbon in urban and suburban areas by coupling continuous wavelet transform with geographical stratification
Yongsheng Hong, Yiyun Chen, Songchao Chen, et al.
Geoderma (2022) Vol. 430, pp. 116284-116284
Open Access | Times Cited: 13
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
Investigation of Spatiotemporal Variation and Drivers of Aerosol Optical Depth in China from 2010 to 2020
Yiting Wang, Yang Lixiang, Donghui Xie, et al.
Atmosphere (2023) Vol. 14, Iss. 3, pp. 477-477
Open Access | Times Cited: 5
Research on water quality prediction method based on AE-LSTM
Huiqing Zhang, Kemei Jin
2021 6th International Conference on Automation, Control and Robotics Engineering (CACRE) (2020), pp. 602-606
Closed Access | Times Cited: 13
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