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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 Novel Heterogeneous Ensemble Framework Based on Machine Learning Models for Shallow Landslide Susceptibility Mapping
Haozhe Tang, Changming Wang, Silong An, et al.
Remote Sensing (2023) Vol. 15, Iss. 17, pp. 4159-4159
Open Access | Times Cited: 10

Showing 10 citing articles:

Integrating Machine Learning Ensembles for Landslide Susceptibility Mapping in Northern Pakistan
Nafees Ali, Jian Chen, Xiaodong Fu, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 988-988
Open Access | Times Cited: 16
Swarm optimization based heterogeneous machine learning techniques for enhanced landslide susceptibility assessment with comprehensive uncertainty quantification
Sumon Dey, Swarup Das
Earth Science Informatics (2025) Vol. 18, Iss. 1
Closed Access | Times Cited: 1
Improving landslide susceptibility prediction through ensemble recursive feature elimination and meta-learning framework
Krishnagopal Halder, Amit Kumar Srivastava, Anitabha Ghosh, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Machine Learning-Driven Landslide Susceptibility Mapping in the Himalayan China–Pakistan Economic Corridor Region
Mohib Ullah, Bingzhe Tang, Wenchao Huangfu, et al.
Land (2024) Vol. 13, Iss. 7, pp. 1011-1011
Open Access | Times Cited: 5
Landslide Susceptibility Mapping in Complex Topo‐Climatic Himalayan Terrain, India Using Machine Learning Models: A Comparative Study of XGBoost, RF and ANN
Shubham Badola, Manish Pandey, Varun Narayan Mishra, et al.
Geological Journal (2025)
Closed Access
Landslide Hazard Assessment Combined with InSAR Deformation: A Case Study in the Zagunao River Basin, Sichuan Province, Southwestern China
Yunfeng Shan, Xu Zhou, Shengsen Zhou, et al.
Remote Sensing (2023) Vol. 16, Iss. 1, pp. 99-99
Open Access | Times Cited: 9
Landslide susceptibility assessment and mapping using new ensemble model
Zhongjie Shen, Di Wang, Alireza Arabameri, et al.
Advances in Space Research (2024) Vol. 74, Iss. 7, pp. 2859-2882
Closed Access | Times Cited: 3
Radio Signal Modulation Recognition Method Based on Hybrid Feature and Ensemble Learning: For Radar and Jamming Signals
Yu Zhou, Ronggang Cao, Anqi Zhang, et al.
Sensors (2024) Vol. 24, Iss. 15, pp. 4804-4804
Open Access | Times Cited: 2
Modeling and Evaluation of the Susceptibility to Landslide Events Using Machine Learning Algorithms in the Province of Chañaral, Atacama Region, Chile
Francisco Parra, Jaime González, Máx Chacón, et al.
Sustainability (2023) Vol. 15, Iss. 24, pp. 16806-16806
Open Access | Times Cited: 6
Improving landslide susceptibility prediction through ensemble Recursive Feature Elimination and meta-learning framework
Krishnagopal Halder, Amit Kumar Srivast, Anitabha Ghosh, et al.
Research Square (Research Square) (2024)
Open Access
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