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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 Performance Assessment Approach Using Photogrammetric Techniques for Landslide Susceptibility Mapping with Logistic Regression, ANN and Random Forest
Eray Sevgen, Sultan Kocaman, Hakan A. Nefeslioğlu, et al.
Sensors (2019) Vol. 19, Iss. 18, pp. 3940-3940
Open Access | Times Cited: 156

Showing 1-25 of 156 citing articles:

Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
Abdelaziz Merghadi, Ali P. Yunus, Jie Dou, et al.
Earth-Science Reviews (2020) Vol. 207, pp. 103225-103225
Closed Access | Times Cited: 825
Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin, Asir Region, Saudi Arabia
Ahmed M. Youssef, Hamid Reza Pourghasemi
Geoscience Frontiers (2020) Vol. 12, Iss. 2, pp. 639-655
Open Access | Times Cited: 336
Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization
Xinzhi Zhou, Haijia Wen, Yalan Zhang, et al.
Geoscience Frontiers (2021) Vol. 12, Iss. 5, pp. 101211-101211
Open Access | Times Cited: 303
Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping
Zhice Fang, Yi Wang, Ling Peng, et al.
Computers & Geosciences (2020) Vol. 139, pp. 104470-104470
Closed Access | Times Cited: 268
Deep learning-based landslide susceptibility mapping
Mohammad Azarafza, Mehdi Azarafza, Haluk Akgün, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 266
Assessing the predictive capability of ensemble tree methods for landslide susceptibility mapping using XGBoost, gradient boosting machine, and random forest
Emrehan Kutluğ Şahin
SN Applied Sciences (2020) Vol. 2, Iss. 7
Open Access | Times Cited: 258
Comparative study of landslide susceptibility mapping with different recurrent neural networks
Yi Wang, Zhice Fang, Mao Wang, et al.
Computers & Geosciences (2020) Vol. 138, pp. 104445-104445
Closed Access | Times Cited: 230
Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression (SVR) with GWO, BAT and COA algorithms
Abdul‐Lateef Balogun, Fatemeh Rezaie, Quoc Bao Pham, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 3, pp. 101104-101104
Open Access | Times Cited: 144
Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea
Wahyu Luqmanul Hakim, Fatemeh Rezaie, Arip Syaripudin Nur, et al.
Journal of Environmental Management (2021) Vol. 305, pp. 114367-114367
Closed Access | Times Cited: 142
National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data
Qigen Lin, Pedro Lima, Stefan Steger, et al.
Geoscience Frontiers (2021) Vol. 12, Iss. 6, pp. 101248-101248
Open Access | Times Cited: 125
A Comprehensive Assessment of XGBoost Algorithm for Landslide Susceptibility Mapping in the Upper Basin of Ataturk Dam, Turkey
R. Can, Sultan Kocaman, Candan Gökçeoğlu
Applied Sciences (2021) Vol. 11, Iss. 11, pp. 4993-4993
Open Access | Times Cited: 124
A comparison among fuzzy multi-criteria decision making, bivariate, multivariate and machine learning models in landslide susceptibility mapping
Quoc Bao Pham, Yacine Achour, Sk Ajim Ali, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 1741-1777
Open Access | Times Cited: 115
Assessment of landslide susceptibility along mountain highways based on different machine learning algorithms and mapping units by hybrid factors screening and sample optimization
Deliang Sun, Qingyu Gu, Haijia Wen, et al.
Gondwana Research (2022) Vol. 123, pp. 89-106
Closed Access | Times Cited: 94
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
Landslide Susceptibility Assessment for Maragheh County, Iran, Using the Logistic Regression Algorithm
Ahmed Cemiloglu, Li-Cai Zhu, Agab Bakheet Mohammednour, et al.
Land (2023) Vol. 12, Iss. 7, pp. 1397-1397
Open Access | Times Cited: 56
Forest fire susceptibility mapping with sensitivity and uncertainty analysis using machine learning and deep learning algorithms
Mohd Rihan, Ahmed Ali Bindajam, Swapan Talukdar, et al.
Advances in Space Research (2023) Vol. 72, Iss. 2, pp. 426-443
Closed Access | Times Cited: 51
Deep learning and benchmark machine learning based landslide susceptibility investigation, Garhwal Himalaya (India)
Soumik Saha, Paromita Majumdar, Biswajit Bera
Quaternary Science Advances (2023) Vol. 10, pp. 100075-100075
Open Access | Times Cited: 44
Comprehensive risk assessment for identifying suitable residential zones in Manavgat, Mediterranean Region
Sedat Doğan, Cem Kılıçoğlu, Halil Akıncı, et al.
Evaluation and Program Planning (2024) Vol. 106, pp. 102465-102465
Closed Access | Times Cited: 20
Uncertainties in landslide susceptibility prediction modeling: A review on the incompleteness of landslide inventory and its influence rules
Faming Huang, Daxiong Mao, Shui‐Hua Jiang, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 6, pp. 101886-101886
Open Access | Times Cited: 19
Deciphering decision-making mechanisms for the susceptibility of different slope geohazards: A case study on a SMOTE-RF-SHAP hybrid model
Junhao Huang, Haijia Wen, Jiwei Hu, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024)
Open Access | Times Cited: 18
Reliability of Information-Theoretic Displacement Detection and Risk Classification for Enhanced Slope Stability and Safety at Highway Construction Sites
Odey Alshboul, Ali Shehadeh, Ghassan Almasabha
Reliability Engineering & System Safety (2025), pp. 110813-110813
Closed Access | Times Cited: 5
Landslide Susceptibility Prediction Modeling Based on Remote Sensing and a Novel Deep Learning Algorithm of a Cascade-Parallel Recurrent Neural Network
Li Zhu, Liang-Hao Huang, Linyu Fan, et al.
Sensors (2020) Vol. 20, Iss. 6, pp. 1576-1576
Open Access | Times Cited: 99
Dynamic development of landslide susceptibility based on slope unit and deep neural networks
Hua Ye, Xianmin Wang, LI Yong-wei, et al.
Landslides (2020) Vol. 18, Iss. 1, pp. 281-302
Closed Access | Times Cited: 99
Ensemble modeling of landslide susceptibility using random subspace learner and different decision tree classifiers
Binh Thai Pham, Tran Van Phong, T. Nguyen‐Thoi, et al.
Geocarto International (2020) Vol. 37, Iss. 3, pp. 735-757
Closed Access | Times Cited: 92
Comparing classical statistic and machine learning models in landslide susceptibility mapping in Ardanuc (Artvin), Turkey
Halil Akıncı, Mustafa Zeybek
Natural Hazards (2021) Vol. 108, Iss. 2, pp. 1515-1543
Closed Access | Times Cited: 76
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