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:

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: 52

Showing 1-25 of 52 citing articles:

PSLSA v2.0: An automatic Python package integrating machine learning models for regional landslide susceptibility assessment
Zizheng Guo, Haojie Wang, Jun He, et al.
Environmental Modelling & Software (2025) Vol. 186, pp. 106367-106367
Closed Access | Times Cited: 1

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: 13

Landslide susceptibility mapping core-base factors and models’ performance variability: a systematic review
Santos D. Chicas, Heng Li, Nobuya Mizoue, et al.
Natural Hazards (2024) Vol. 120, Iss. 14, pp. 12573-12593
Closed Access | Times Cited: 7

Optimization method of conditioning factors selection and combination for landslide susceptibility prediction
Faming Huang, K Y Liu, Shui‐Hua Jiang, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024)
Open Access | Times Cited: 6

Advanced risk assessment framework for land subsidence impacts on transmission towers in salt lake region
Bijing Jin, Taorui Zeng, Tengfei Wang, et al.
Environmental Modelling & Software (2024) Vol. 177, pp. 106058-106058
Closed Access | Times Cited: 5

A benchmark dataset and workflow for landslide susceptibility zonation
Massimiliano Alvioli, Marco Loche, Liesbet Jacobs, et al.
Earth-Science Reviews (2024) Vol. 258, pp. 104927-104927
Open Access | Times Cited: 5

Global Dynamic Landslide Susceptibility Modeling Based on ResNet18: Revealing Large-Scale Landslide Hazard Evolution Trends in China
Hui Jiang, Mingtao Ding, Liangzhi Li, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 2038-2038
Open Access

Investigating the landslide susceptibility assessment methods for multi-scale slope units based on SDGSAT-1 and Graph Neural Networks
Xiangqi Lei, Hanhu Liu, Zhe Chen, et al.
International Journal of Digital Earth (2025) Vol. 18, Iss. 1
Open Access

Overcoming the data limitations in landslide susceptibility modeling
Jacob Woodard, Benjamin B. Mirus
Science Advances (2025) Vol. 11, Iss. 8
Open Access

Evolution of landslide susceptibility in the Three Gorges Reservoir area over the three decades from 1991 to 2020
Jiahui Dong, Jinrong Duan, Runqing Ye, et al.
Geomatics Natural Hazards and Risk (2025) Vol. 16, Iss. 1
Open Access

Effect of different mapping units, spatial resolutions, and machine learning algorithms on landslide susceptibility mapping at the township scale
Xiaokang Liu, Shuai Shao, Chen Zhang, et al.
Environmental Earth Sciences (2025) Vol. 84, Iss. 5
Closed Access

Insights into landslide susceptibility: a comparative evaluation of multi-criteria analysis and machine learning techniques
Zuleide Alves Ferreira, Bruna Almeida, Ana Cristina Costa, et al.
Geomatics Natural Hazards and Risk (2025) Vol. 16, Iss. 1
Open Access

Zoning Landslide Hazard in the Masal to Gilvan Road Using a Neural Network Algorithm
sayyad Asghari Sarasekanrood, Zeinab Sharifi, Zahra Shahbazi
Deleted Journal (2025) Vol. 11, Iss. 4
Closed Access

Landslide susceptibility assessment using deep learning considering unbalanced samples distribution
Deborah Simon Mwakapesa, Xiaoji Lan, Yimin Mao
Heliyon (2024) Vol. 10, Iss. 9, pp. e30107-e30107
Open Access | Times Cited: 4

Considering the effect of non-landslide sample selection on landslide susceptibility assessment
Youchen Zhu, Deliang Sun, Haijia Wen, et al.
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4

Landslide susceptibility assessment using novel hybridized methods based on the support vector regression
Abolfazl Jaafari
Ecological Engineering (2024) Vol. 208, pp. 107372-107372
Closed Access | Times Cited: 4

Improving ML-based landslide susceptibility using ensemble method for sample selection: a case study of Kangra district in Himachal Pradesh, India
Ankit Singh, Nitesh Dhiman, K. C. Niraj, et al.
Environmental Science and Pollution Research (2024)
Closed Access | Times Cited: 3

Exploring deep learning models for roadside landslide prediction: Insights and implications from comparative analysis
Tiep Nguyen Viet, Dam Duc Nguyen, Manh Nguyen Duc, et al.
Physics and Chemistry of the Earth Parts A/B/C (2024), pp. 103741-103741
Closed Access | Times Cited: 2

Incorporating modelling uncertainty and prior knowledge into landslide susceptibility mapping using Bayesian neural networks
Chongzhi Chen, Zhangquan Shen, Luming Fang, et al.
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2024), pp. 1-20
Closed Access | Times Cited: 2

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