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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:

Application of Tree-Based Ensemble Models to Landslide Susceptibility Mapping: A Comparative Study
Aihua Wei, Kaining Yu, Fenggang Dai, et al.
Sustainability (2022) Vol. 14, Iss. 10, pp. 6330-6330
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing
Wengang Zhang, Yuwei He, Luqi Wang, et al.
Geological Journal (2023) Vol. 58, Iss. 6, pp. 2372-2387
Closed Access | Times Cited: 84
Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
Taorui Zeng, Liyang Wu, Dario Peduto, et al.
Geoscience Frontiers (2023) Vol. 14, Iss. 6, pp. 101645-101645
Open Access | Times Cited: 76
Comparative Analysis of Tree-Based Ensemble Learning Algorithms for Landslide Susceptibility Mapping: A Case Study in Rize, Turkey
Ayşe Yavuz Özalp, Halil Akıncı, Mustafa Zeybek
Water (2023) Vol. 15, Iss. 14, pp. 2661-2661
Open Access | Times Cited: 29
Optimizing the Sample Selection of Machine Learning Models for Landslide Susceptibility Prediction Using Information Value Models in the Dabie Mountain Area of Anhui, China
Yanrong Liu, Zhongqiu Meng, Lei Zhu, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 1971-1971
Open Access | Times Cited: 24
Comparison of tree-based ensemble learning algorithms for landslide susceptibility mapping in Murgul (Artvin), Turkey
Ziya Usta, Halil Akıncı, Alper Tunga Akın
Earth Science Informatics (2024) Vol. 17, Iss. 2, pp. 1459-1481
Open Access | Times Cited: 16
Comparison of diverse machine learning algorithms for forest fire susceptibility mapping in Antalya, Türkiye
Hazan Alkan Akıncı, Halil Akıncı, Mustafa Zeybek
Advances in Space Research (2024) Vol. 74, Iss. 2, pp. 647-667
Closed Access | Times Cited: 10
Inventory of Landslides in the Northern Half of the Taihang Mountain Range, China
Xuewei Zhang, Chong Xu, Lei Li, et al.
Geosciences (2024) Vol. 14, Iss. 3, pp. 74-74
Open Access | Times Cited: 9
A Landslide Susceptibility Evaluation of Highway Disasters Based on the Frequency Ratio Coupling Model
Huadan Fan, Yuefeng Lu, Yulong Hu, et al.
Sustainability (2022) Vol. 14, Iss. 13, pp. 7740-7740
Open Access | Times Cited: 34
Examining the Spatially Varying Relationships between Landslide Susceptibility and Conditioning Factors Using a Geographical Random Forest Approach: A Case Study in Liangshan, China
Xiaoliang Dai, Yunqiang Zhu, Kai Sun, et al.
Remote Sensing (2023) Vol. 15, Iss. 6, pp. 1513-1513
Open Access | Times Cited: 22
Ensemble learning landslide susceptibility assessment with optimized non-landslide samples selection
Jiangang Lu, Yi He, Lifeng Zhang, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
Two-stage meta-ensembling machine learning model for enhanced water quality forecasting
Sepideh Heydari, Mohammad Reza Nikoo, Ali Mohammadi, et al.
Journal of Hydrology (2024) Vol. 641, pp. 131767-131767
Closed Access | Times Cited: 7
Application of Bagging, Boosting and Stacking Ensemble and EasyEnsemble Methods for Landslide Susceptibility Mapping in the Three Gorges Reservoir Area of China
Xueling Wu, Junyang Wang
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 6, pp. 4977-4977
Open Access | Times Cited: 16
Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods
Esteban Bravo-López, Tomás Fernández, Chester Sellers, et al.
Land (2023) Vol. 12, Iss. 6, pp. 1135-1135
Open Access | Times Cited: 15
A new approach for landslide susceptibility assessments based on KDE-MDBN: A case study from mountainous regions impacted by the Wenchuan earthquake, China
Suyue Han, Bin Liu, Xinyue Fan, et al.
Environmental Modelling & Software (2023) Vol. 167, pp. 105759-105759
Closed Access | Times Cited: 14
Synergetic use of geospatial and machine learning techniques in modelling landslide susceptibility in parts of Shimla to Kinnaur National Highway, Himachal Pradesh
Rahul Deb Das, Shovan Lal Chattoraj, Mohit Singh, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 3, pp. 4163-4183
Closed Access | Times Cited: 6
A comparative evaluation of landslide susceptibility mapping using machine learning-based methods in Bogor area of Indonesia
Dian Nuraini Melati, Raditya Panji Umbara, Astisiasari Astisiasari, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 3
Open Access | Times Cited: 5
Improving the Quality Indicators of Multilevel Data Sampling Processing Models Based on Unsupervised Clustering
Ilya Lebedev, Mikhail Sukhoparov
Emerging Science Journal (2024) Vol. 8, Iss. 1, pp. 355-371
Open Access | Times Cited: 5
A Novel Dataset Replenishment Strategy Integrating Time-Series InSAR for Refined Landslide Susceptibility Mapping in Karst Regions
Y. G. Yang, Xianglong Ma, Ding Wenrong, et al.
Water (2024) Vol. 16, Iss. 17, pp. 2414-2414
Open Access | Times Cited: 4
Landslide susceptibility mapping using combined geospatial, FR and AHP models: a case study from Ethiopia’s highlands
Tesfaldet Sisay, Tesfaye Getachew, Muralitharan Jothimani, et al.
Discover Sustainability (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 4
Landslide hazard zonation using advanced machine learning algorithms based on statistical models (Case study: Sarvabad, Iran)
Himan Rastkhadiv, Baharak Motamedvaziri, Seyed Hamed Javadi, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Closed Access
Combination of Conditioning Factors for Generation of Landslide Susceptibility Maps by Extreme Gradient Boosting in Cuenca, Ecuador
Esteban Bravo-López, Tomás Fernández, Chester Sellers, et al.
Algorithms (2025) Vol. 18, Iss. 5, pp. 258-258
Open Access
Evaluation of Land Suitability for Olive (Olea europaea L.) Cultivation Using the Random Forest Algorithm
Ayşe Yavuz Özalp, Halil Akıncı
Agriculture (2023) Vol. 13, Iss. 6, pp. 1208-1208
Open Access | Times Cited: 9
Investigating the Effects of Different Data Classification Methods on Landslide Susceptibility Mapping
Halil Akıncı, Ayşe Yavuz Özalp
Advances in Space Research (2024)
Closed Access | Times Cited: 3
A Data-Driven Based Method for Pipeline Additional Stress Prediction Subject to Landslide Geohazards
Meng Zhang, Jiatong Ling, Buyun Tang, et al.
Sustainability (2022) Vol. 14, Iss. 19, pp. 11999-11999
Open Access | Times Cited: 12
Mass movement susceptibility prediction and infrastructural risk assessment (IRA) using GIS-based Meta classification algorithms
Sk Ajim Ali, Meriame Mohajane, Farhana Parvin, et al.
Applied Soft Computing (2023) Vol. 145, pp. 110591-110591
Closed Access | Times Cited: 5
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