Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

The estimation of hourly PM2.5 concentrations across China based on a Spatial and Temporal Weighted Continuous Deep Neural Network (STWC-DNN)
Zhen Wang, Ruiyuan Li, Ziyue Chen, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 190, pp. 38-55
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Deep-learning architecture for PM2.5 concentration prediction: A review
Shiyun Zhou, Wei Wang, Long Zhu, et al.
Environmental Science and Ecotechnology (2024) Vol. 21, pp. 100400-100400
Open Access | Times Cited: 18
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: 54
Simulating daily PM2.5 concentrations using wavelet analysis and artificial neural network with remote sensing and surface observation data
Qingchun Guo, Zhenfang He, Zhaosheng Wang
Chemosphere (2023) Vol. 340, pp. 139886-139886
Closed Access | Times Cited: 39
PM2.5 Concentration Prediction Model: A CNN–RF Ensemble Framework
Mei-Hsin Chen, Yao-Chung Chen, Tien‐Yin Chou, et al.
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 5, pp. 4077-4077
Open Access | Times Cited: 19
A review on digital mapping of soil carbon in cropland: progress, challenge, and prospect
Haili Huang, Lin Yang, Lei Zhang, et al.
Environmental Research Letters (2022) Vol. 17, Iss. 12, pp. 123004-123004
Open Access | Times Cited: 24
The division of PM2.5-O3 composite airborne pollution across China based on spatiotemporal clustering
Jing Yang, Xiaohong Chen, Manchun Li, et al.
Journal of Cleaner Production (2023) Vol. 401, pp. 136706-136706
Closed Access | Times Cited: 13
A novel framework for river organic carbon retrieval through satellite data and machine learning
尚能 岩田, Anmeng Sha, Yi Luo, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2025) Vol. 221, pp. 109-123
Closed Access
An interpretable physics-informed deep learning model for estimating multiple air pollutants
Binjie Chen, Jiacong Hu, Yumiao Wang, et al.
GIScience & Remote Sensing (2025) Vol. 62, Iss. 1
Open Access
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
An Improved Deep Learning Approach Considering Spatiotemporal Heterogeneity for PM2.5 Prediction: A Case Study of Xinjiang, China
Yajing Wu, Zhangyan Xu, Liping Xu, et al.
Atmosphere (2024) Vol. 15, Iss. 4, pp. 460-460
Open Access | Times Cited: 3
PD-LL-Transformer: An Hourly PM2.5 Forecasting Method over the Yangtze River Delta Urban Agglomeration, China
Rongkun Zou, Heyun Huang, Xiaoman Lu, et al.
Remote Sensing (2024) Vol. 16, Iss. 11, pp. 1915-1915
Open Access | Times Cited: 3
A gap-filling hybrid approach for hourly PM2.5 prediction at high spatial resolution from multi-sourced AOD data
Qiang Pu, Eun‐Hye Yoo
Environmental Pollution (2022) Vol. 315, pp. 120419-120419
Closed Access | Times Cited: 15
A Novel Algorithm of Haze Identification Based on FY3D/MERSI-II Remote Sensing Data
Yidan Si, Lin Chen, Zhaojun Zheng, et al.
Remote Sensing (2023) Vol. 15, Iss. 2, pp. 438-438
Open Access | Times Cited: 8
Geo-STO3Net: A Deep Neural Network Integrating Geographical Spatiotemporal Information for Surface Ozone Estimation
Binjie Chen, Qiming Zheng, Weiwei Sun, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-14
Closed Access | Times Cited: 2
Retrieving ground-level PM2.5 concentrations in China (2013–2021) with a numerical-model-informed testbed to mitigate sample-imbalance-induced biases
Siwei Li, Yu Ding, Jia Xing, et al.
Earth system science data (2024) Vol. 16, Iss. 8, pp. 3781-3793
Open Access | Times Cited: 2
High-Accuracy Pm2.5 Retrieval Based on Satellite Remote Sensing and Hierarchical Machine Learning Model
Yulong Fan, Lin Sun, Xirong Liu
(2024)
Closed Access | Times Cited: 1
Estimation of fine-resolution PM2.5 concentrations using the INLA-SPDE method
Jingna Chen, Changhong Miao, Dongyang Yang, et al.
Atmospheric Pollution Research (2023) Vol. 14, Iss. 7, pp. 101781-101781
Closed Access | Times Cited: 2
High-accuracy full-coverage PM 2.5 retrieval from 2014 to 2023 over China based on satellite remote sensing and hierarchical deep learning model
Yulong Fan, Lin Sun, Xirong Liu
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access
Spatiotemporal stacking method with daily‐cycle restrictions for reconstructing missing hourly PM2.5 records
Chuanfa Chen, Kunyu Li
Transactions in GIS (2024) Vol. 28, Iss. 2, pp. 349-367
Closed Access
Retrieving Ground-Level PM2.5 Concentrations in China (2013–2021) with a Numerical Model-Informed Testbed to Mitigate Sample Imbalance-Induced Biases
Siwei Li, Yu Ding, Jia Xing, et al.
(2024)
Open Access
Comment on essd-2024-170
Siwei Li, Yu Ding, Jia Xing, et al.
(2024)
Open Access
Comment on essd-2024-170
Siwei Li, Yu Ding, Jia Xing, et al.
(2024)
Open Access
Tracking hourly PM2.5 using geostationary satellite sensor images and multiscale spatiotemporal deep learning
Zhige Wang, Ce Zhang, Su Ye, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 134, pp. 104145-104145
Open Access
An improved geographic pattern based residual neural network model for estimating PM2.5 concentrations
Heng Su, Yumin Chen, Huangyuan Tan, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 134, pp. 104174-104174
Open Access
The optimization of XGBoost model and its application in PM2.5concentrations estimation based on MODIS data in the Guanzhong region, China
Hongxia Ma, Jinling Kong, Yanling Zhong, et al.
International Journal of Remote Sensing (2023) Vol. 45, Iss. 19-20, pp. 6954-6975
Closed Access | Times Cited: 1
Page 1 - Next Page

Scroll to top