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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:

Landslide susceptibility mapping and dynamic response along the Sichuan-Tibet transportation corridor using deep learning algorithms
Wubiao Huang, Mingtao Ding, Zhenhong Li, et al.
CATENA (2022) Vol. 222, pp. 106866-106866
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Modelling landslide susceptibility prediction: A review and construction of semi-supervised imbalanced theory
Faming Huang, Haowen Xiong, Shui‐Hua Jiang, et al.
Earth-Science Reviews (2024) Vol. 250, pp. 104700-104700
Closed Access | Times Cited: 57
Physics-informed optimization for a data-driven approach in landslide susceptibility evaluation
Songlin Liu, Luqi Wang, Wengang Zhang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024) Vol. 16, Iss. 8, pp. 3192-3205
Open Access | Times Cited: 28
GIS-based landslide susceptibility mapping of the Meghalaya-Shillong Plateau region using machine learning algorithms
Navdeep Agrawal, Jagabandhu Dixit
Bulletin of Engineering Geology and the Environment (2023) Vol. 82, Iss. 5
Closed Access | Times Cited: 27
Modeling landslide susceptibility based on convolutional neural network coupling with metaheuristic optimization algorithms
Zhuo Chen, Danqing Song
International Journal of Digital Earth (2023) Vol. 16, Iss. 1, pp. 3384-3416
Open Access | Times Cited: 23
Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm
Hongzhi Cui, Jian Ji, Marcel Hürlimann, et al.
Landslides (2024) Vol. 21, Iss. 6, pp. 1461-1481
Closed Access | Times Cited: 15
Landslide Susceptibility Mapping Considering Landslide Local-Global Features Based on CNN and Transformer
Zeyang Zhao, Tao Chen, Jie Dou, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 7475-7489
Open Access | Times Cited: 12
Refined landslide susceptibility mapping in township area using ensemble machine learning method under dataset replenishment strategy
Fancheng Zhao, Fasheng Miao, Yiping Wu, et al.
Gondwana Research (2024) Vol. 131, pp. 20-37
Closed Access | Times Cited: 11
Hybridizing genetic random forest and self-attention based CNN-LSTM algorithms for landslide susceptibility mapping in Darjiling and Kurseong, India
Armin Moghimi, Chiranjit Singha, Mahdiyeh Fathi, et al.
Quaternary Science Advances (2024) Vol. 14, pp. 100187-100187
Open Access | Times Cited: 10
Exploring the spatial patterns of landslide susceptibility assessment using interpretable Shapley method: Mechanisms of landslide formation in the Sichuan-Tibet region
Jichao Lv, Rui Zhang, Age Shama, et al.
Journal of Environmental Management (2024) Vol. 366, pp. 121921-121921
Closed Access | Times Cited: 10
Landslide Susceptibility Mapping Using an LSTM Model with Feature-Selecting for the Yangtze River Basin in China
Peng Zuo, Wen Zhao, Wenjun Yan, et al.
Water (2025) Vol. 17, Iss. 2, pp. 167-167
Open Access | Times Cited: 1
Landslide susceptibility assessment for Uttarakhand, a Himalayan state of India, using multi-criteria decision making, bivariate, and machine learning models
Vipin Chauhan, Laxmi Gupta, Jagabandhu Dixit
Geoenvironmental Disasters (2025) Vol. 12, Iss. 1
Open Access | Times Cited: 1
Integrating a multi-dimensional deep convolutional neural network with optimized sample selection for landslide susceptibility assessment
Yueyue Wang, Xueling Wu, Kun Zou, et al.
Geo-spatial Information Science (2025), pp. 1-21
Open Access | Times Cited: 1
A comparative study of regional landslide susceptibility mapping with multiple machine learning models
Yunhao Wang, Luqi Wang, Songlin Liu, et al.
Geological Journal (2023) Vol. 59, Iss. 9, pp. 2383-2400
Closed Access | Times Cited: 19
Refined Landslide Susceptibility Mapping by Integrating the SHAP-CatBoost Model and InSAR Observations: A Case Study of Lishui, Southern China
Zhaowei Yao, Meihong Chen, Jiewei Zhan, et al.
Applied Sciences (2023) Vol. 13, Iss. 23, pp. 12817-12817
Open Access | Times Cited: 18
Landslide susceptibility assessment using locally weighted learning integrated with machine learning algorithms
Haoyuan Hong
Expert Systems with Applications (2023) Vol. 237, pp. 121678-121678
Closed Access | Times Cited: 17
Detailed Inventory and Spatial Distribution Analysis of Rainfall-Induced Landslides in Jiexi County, Guangdong Province, China in August 2018
Chenchen Xie, Yuandong Huang, Lei Li, et al.
Sustainability (2023) Vol. 15, Iss. 18, pp. 13930-13930
Open Access | Times Cited: 17
A physics-informed machine learning solution for landslide susceptibility mapping based on three-dimensional slope stability evaluation
Yunhao Wang, Luqi Wang, Wengang Zhang, et al.
Journal of Central South University (2024)
Closed Access | Times Cited: 7
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
Land subsidence susceptibility mapping in urban settlements using time-series PS-InSAR and random forest model
Fancheng Zhao, Fasheng Miao, Yiping Wu, et al.
Gondwana Research (2023) Vol. 125, pp. 406-424
Closed Access | Times Cited: 16
Old Landslide Detection Using Optical Remote Sensing Images Based on Improved YOLOv8
Yunlong Li, Mingtao Ding, Qian Zhang, et al.
Applied Sciences (2024) Vol. 14, Iss. 3, pp. 1100-1100
Open Access | Times Cited: 5
Comparison of different open‐source Digital Elevation Models for landslide susceptibility mapping
Dingyang Lu, Guoan Tang, Ge Yan, et al.
Earth Surface Processes and Landforms (2024) Vol. 49, Iss. 4, pp. 1411-1427
Closed Access | Times Cited: 5
What ecological factors to integrate in landslide susceptibility mapping? An exploratory review of current trends in support of eco-DRR
Mélanie Broquet, Pedro Cabral, Felipe S. Campos
Progress in Disaster Science (2024) Vol. 22, pp. 100328-100328
Open Access | Times Cited: 5
Refined landslide inventory and susceptibility of Weining County, China, inferred from machine learning and Sentinel‐1 InSAR analysis
Xuguo Shi, Dianqiang Chen, Jianing Wang, et al.
Transactions in GIS (2024) Vol. 28, Iss. 6, pp. 1594-1616
Closed Access | Times Cited: 5
Comparison of informative modelling and machine learning methods in landslide vulnerability evaluation – a case study of Wenchuan County, China
Yutao Chen, Ning Li, Boju Zhao, et al.
Geocarto International (2024) Vol. 39, Iss. 1
Open Access | Times Cited: 4
Spatiotemporal changes of landslide susceptibility in response to rainfall and its future prediction — A case study of Sichuan Province, China
Hao Zheng, Mingtao Ding
Ecological Informatics (2024), pp. 102862-102862
Open Access | Times Cited: 4
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