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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:

Essential insights into decision mechanism of landslide susceptibility mapping based on different machine learning models
Deliang Sun, Yuekai Ding, Jialan Zhang, et al.
Geocarto International (2022) Vol. 38, Iss. 1, pp. 1-29
Open Access | Times Cited: 22

Showing 22 citing articles:

A LightGBM-based landslide susceptibility model considering the uncertainty of non-landslide samples
Deliang Sun, WU Xiao-qing, Haijia Wen, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 52
Landslide Susceptibility Mapping Based on Interpretable Machine Learning from the Perspective of Geomorphological Differentiation
Deliang Sun, D C Chen, Jialan Zhang, et al.
Land (2023) Vol. 12, Iss. 5, pp. 1018-1018
Open Access | Times Cited: 35
Application and interpretability of ensemble learning for landslide susceptibility mapping along the Three Gorges Reservoir area, China
Bo Liu, Haixiang Guo, Jinling Li, et al.
Natural Hazards (2024) Vol. 120, Iss. 5, pp. 4601-4632
Closed Access | Times Cited: 15
Dynamic landslide susceptibility mapping based on the PS-InSAR deformation intensity
Bijing Jin, Taorui Zeng, Kunlong Yin, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 5, pp. 7872-7888
Open Access | Times Cited: 11
Landslide susceptibility mapping (LSM) based on different boosting and hyperparameter optimization algorithms: A case of Wanzhou District, China
Deliang Sun, Jing Wang, Haijia Wen, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024) Vol. 16, Iss. 8, pp. 3221-3232
Open Access | Times Cited: 10
Feature adaptation for landslide susceptibility assessment in “no sample” areas
Yan Su, Y. Chen, Xiaohe Lai, et al.
Gondwana Research (2024) Vol. 131, pp. 1-17
Closed Access | Times Cited: 9
Application of Artificial Intelligence and Remote Sensing for Landslide Detection and Prediction: Systematic Review
Stephen Akosah, Ivan Gratchev, Donghyun Kim, et al.
Remote Sensing (2024) Vol. 16, Iss. 16, pp. 2947-2947
Open Access | Times Cited: 9
Ensemble models based on radial basis function network for landslide susceptibility mapping
Le-Minh Nguyen, Pham The Truyen, Tran Van Phong, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 44, pp. 99380-99398
Closed Access | Times Cited: 16
Landslide Susceptibility Mapping Methods—A Review
Evangelin Ramani Sujatha, J. S. Sudharsan
Advances in natural and technological hazards research (2024), pp. 87-102
Closed Access | Times Cited: 4
Sample size effects on landslide susceptibility models: A comparative study of heuristic, statistical, machine learning, deep learning and ensemble learning models with SHAP analysis
Shilong Yang, Jiayao Tan, Danyuan Luo, et al.
Computers & Geosciences (2024), pp. 105723-105723
Closed Access | Times Cited: 4
Machine learning methods for landslide mapping studies: A comparative study of SVM and RF algorithms in the Oued Aoulai watershed (Morocco)
Latifa Ladel, Mohamed Mastere, Shuraik Kader, et al.
Open Geosciences (2025) Vol. 17, Iss. 1
Open Access
Distribution of ancient landslides and landslide hazard assessment in the Western Himalayan Syntaxis area
Yulong Cui, Wenhao Yang, Chong Xu, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 9
Learning a Deep Attention Dilated Residual Convolutional Neural Network for Landslide Susceptibility Mapping in Hanzhong City, Shaanxi Province, China
Yu Ma, Shenghua Xu, Tao Jiang, et al.
Remote Sensing (2023) Vol. 15, Iss. 13, pp. 3296-3296
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
Investigation of Landslide Susceptibility Decision Mechanisms in Different Ensemble-Based Machine Learning Models with Various Types of Factor Data
Jiakai Lu, Chao Ren, Weiting Yue, et al.
Sustainability (2023) Vol. 15, Iss. 18, pp. 13563-13563
Open Access | Times Cited: 7
An information quantity and machine learning integrated model for landslide susceptibility mapping in Jiuzhaigou, China
Yunjie Yang, Rui Zhang, Tianyu Wang, et al.
Natural Hazards (2024) Vol. 120, Iss. 11, pp. 10185-10217
Closed Access | Times Cited: 2
Co-seismic landslide susceptibility mapping for the Luding earthquake area based on heterogeneous ensemble machine learning models
Rui Zhang, Yunjie Yang, Tianyu Wang, et al.
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 2
Theoretical Insights into Neural Networks and Deep Learning: Advancing Understanding, Interpretability, and Generalization
Usman Ahmad Usmani, Mohammed Umar Usmani
(2023), pp. 1-8
Closed Access | Times Cited: 5
Insights into landslide susceptibility in different karst erosion landforms based on interpretable machine learning
Deliang Sun, Jing Wang, Haijia Wen, et al.
Earth Surface Processes and Landforms (2023) Vol. 49, Iss. 3, pp. 1006-1027
Closed Access | Times Cited: 5
Improving generalization performance of landslide susceptibility model considering spatial heterogeneity by using the geomorphic label-based LightGBM
Deliang Sun, WU Xiao-qing, Haijia Wen, et al.
Bulletin of Engineering Geology and the Environment (2024) Vol. 83, Iss. 9
Closed Access | Times Cited: 1
Exploring class imbalance with under-sampling, over-sampling, and hybrid sampling based on Mahalanobis distance for landslide susceptibility assessment: a case study of the 2018 Iburi earthquake induced landslides in Hokkaido, Japan
Kounghoon Nam, Jongtae Kim, Byung‐Gon Chae
Geosciences Journal (2023) Vol. 28, Iss. 1, pp. 71-94
Closed Access | Times Cited: 3
An Interpretation Study on the ML Models for Landslide Susceptibility Mapping
Liang Lv, Tao Chen, Jun Li
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (2023), pp. 7241-7244
Closed Access | Times Cited: 1
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