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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:

Mapping Large-Scale Forest Disturbance Types with Multi-Temporal CNN Framework
Xi Chen, Wenzhi Zhao, Jiage Chen, et al.
Remote Sensing (2021) Vol. 13, Iss. 24, pp. 5177-5177
Open Access | Times Cited: 11

Showing 11 citing articles:

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning
Thiên-Anh Nguyen, Marc Rußwurm, Gaston Lenczner, et al.
Remote Sensing of Environment (2024) Vol. 305, pp. 114109-114109
Open Access | Times Cited: 8
Automated attribution of forest disturbance types from remote sensing data: A synthesis
Amanda T. Stahl, Robert A. Andrus, Jeffrey A. Hicke, et al.
Remote Sensing of Environment (2022) Vol. 285, pp. 113416-113416
Open Access | Times Cited: 28
Evaluating deep learning methods applied to Landsat time series subsequences to detect and classify boreal forest disturbances events: The challenge of partial and progressive disturbances
Pauline Perbet, Luc Guindon, Jean-François Côté, et al.
Remote Sensing of Environment (2024) Vol. 306, pp. 114107-114107
Open Access | Times Cited: 4
Forest Disturbance Attribution under Small Sample Conditions Based on Confidence Learning Mutual Guidance Framework
Yan Yan, Ling Wu, Junji Li, et al.
Chinese Journal of Space Science (2025) Vol. 45, Iss. 2, pp. 1-1
Open Access
Research on Protective Forest Change Detection in Aral City Based on Deep Learning
Pengshuai Liu, Xiaojun Yin, Mingrui Ding, et al.
Forests (2025) Vol. 16, Iss. 5, pp. 775-775
Open Access
Towards precision forestry: Drought response from remote sensing-based disturbance monitoring and fine-scale soil information in Central Europe
Birgitta Putzenlechner, Philipp Koal, Martin Kappas, et al.
The Science of The Total Environment (2023) Vol. 880, pp. 163114-163114
Open Access | Times Cited: 8
A New Method for the Rapid Determination of Fire Disturbance Events Using GEE and the VCT Algorithm—A Case Study in Southwestern and Northeastern China
Junhong Ye, Nan Wang, Min Sun, et al.
Remote Sensing (2023) Vol. 15, Iss. 2, pp. 413-413
Open Access | Times Cited: 5
Assessment of large-scale multiple forest disturbance susceptibilities with AutoML framework: an Izmir Regional Forest Directorate case
Remzi Eker, Kamber Can Alkiş, Abdürrahim Aydın
Journal of Forestry Research (2024) Vol. 35, Iss. 1
Open Access | Times Cited: 1
Detection and Analysis of Forest Clear-Cutting Activities Using Sentinel-2 and Random Forest Classification: A Case Study on Chungcheongnam-do, Republic of Korea
Sol-E Choi, Sun Jeoung Lee, Jeongmook Park, et al.
Forests (2024) Vol. 15, Iss. 3, pp. 450-450
Open Access
Remote Sensing and Geospatial Approaches for Studying the Environment Affected by Human Activities
Chengye Zhang, Jun Li, Xinyi Shen, et al.
Remote Sensing (2024) Vol. 16, Iss. 18, pp. 3364-3364
Open Access
Analysis of the Spatial Changes and Influencing Factors of Landscape Patterns Along the Fujian-Guangdong Interconnection
Jianxun Zhang, Guowei Chen, Chang Lu
Lecture notes in civil engineering (2023), pp. 189-200
Closed Access
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