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:

Modeling soil erosion susceptibility using GIS-based different machine learning algorithms in monsoon dominated diversified landscape in India
Rabin Chakrabortty, Subodh Chandra Pal
Modeling Earth Systems and Environment (2023) Vol. 9, Iss. 2, pp. 2927-2942
Closed Access | Times Cited: 11

Showing 11 citing articles:

Geospatial assessment of soil erosion in the Basantar and Devak watersheds of the NW Himalaya: A study utilizing USLE and RUSLE models
Ajay Kumar Taloor, Varun Khajuria, Gurnam Parsad, et al.
Geosystems and Geoenvironment (2025), pp. 100355-100355
Open Access

Integrating Morphometric Analysis, Prioritization Strategies, and Machine Learning for Enhanced Watershed Management
Akil V. Memon, Nirav V. Shah, Dharam N. Thakkar, et al.
Smart innovation, systems and technologies (2025), pp. 225-249
Closed Access

Convergence of mechanistic modeling and artificial intelligence in hydrologic science and engineering
Rafael Muñoz‐Carpena, Álvaro Carmona-Cabrero, Ziwen Yu, et al.
PLOS Water (2023) Vol. 2, Iss. 8, pp. e0000059-e0000059
Open Access | Times Cited: 13

RETRACTED: Systematic review on gully erosion measurement, modelling and management: Mitigation alternatives and policy recommendations
Rabin Chakrabortty, Subodh Chandra Pal
Geological Journal (2023) Vol. 58, Iss. 9, pp. 3544-3576
Closed Access | Times Cited: 5

Prediction and mapping of land degradation in the Batanghari watershed, Sumatra, Indonesia: utilizing multi-source geospatial data and machine learning modeling techniques
Fajar Yulianto, Puguh Dwi Raharjo, Irfan Budi Pramono, et al.
Modeling Earth Systems and Environment (2023) Vol. 9, Iss. 4, pp. 4383-4404
Closed Access | Times Cited: 4

Interpretation of Bayesian-optimized deep learning models for enhancing soil erosion susceptibility prediction and management: a case study of Eastern India
Meshel Q. Alkahtani, Javed Mallick, Saeed Alqadhi, et al.
Geocarto International (2024) Vol. 39, Iss. 1
Open Access | Times Cited: 1

The study on morphological evolution process of gully headcut erosion in granite red soil hilly area based on an in situ scouring experiment
Zhe Lin, Dalan Liao, Ling He, et al.
Geomorphology (2023) Vol. 441, pp. 108900-108900
Closed Access | Times Cited: 3

Mapping of soil erosion susceptibility using advanced machine learning models at Nghe An, Vietnam
Chien Quyet Nguyen, Tuyen Thi Tran, Trang Thanh Thi Nguyen, et al.
Journal of Hydroinformatics (2023) Vol. 26, Iss. 1, pp. 72-87
Open Access | Times Cited: 3

Mapping soil erosion susceptibility: a comparison of neural networks and fuzzy-AHP techniques
Marzieh Mokarram, Hamid Reza Pourghasemi, John P. Tiefenbacher, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 19
Closed Access

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