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:

An updating of landslide susceptibility prediction from the perspective of space and time
Zhilu Chang, Faming Huang, Jinsong Huang, et al.
Geoscience Frontiers (2023) Vol. 14, Iss. 5, pp. 101619-101619
Open Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Refined and dynamic susceptibility assessment of landslides using InSAR and machine learning models
Yingdong Wei, Haijun Qiu, Zijing Liu, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 6, pp. 101890-101890
Open Access | Times Cited: 44

Improving pixel-based regional landslide susceptibility mapping
Xin Wei, Paolo Gardoni, Lulu Zhang, et al.
Geoscience Frontiers (2024) Vol. 15, Iss. 4, pp. 101782-101782
Open Access | Times Cited: 21

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

Predicting Max Scour Depths near Two-Pier Groups Using Ensemble Machine-Learning Models and Visualizing Feature Importance with Partial Dependence Plots and SHAP
Buddhadev Nandi, Subhasish Das
Journal of Computing in Civil Engineering (2025) Vol. 39, Iss. 2
Closed Access | Times Cited: 2

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method
Faming Huang, Zuokui Teng, Chi Yao, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 16, Iss. 1, pp. 213-230
Open Access | Times Cited: 31

Autonomous prediction of rock deformation in fault zones of coal roadways using supervised machine learning
Feng Guo, Nong Zhang, Xiaowei Feng, et al.
Tunnelling and Underground Space Technology (2024) Vol. 147, pp. 105724-105724
Closed Access | Times Cited: 12

A landslide susceptibility assessment method considering the similarity of geographic environments based on graph neural network
Qing Zhang, Yi He, Lifeng Zhang, et al.
Gondwana Research (2024) Vol. 132, pp. 323-342
Closed Access | Times Cited: 9

Comprehensive review of remote sensing integration with deep learning in landslide forecasting and future directions
Nilesh Suresh Pawar, Kul Vaibhav Sharma
Natural Hazards (2025)
Closed Access | Times Cited: 1

Landslide spatial prediction using cluster analysis
Zheng Zhao, Hengxing Lan, Langping Li, et al.
Gondwana Research (2024) Vol. 130, pp. 291-307
Closed Access | Times Cited: 8

Single landslide risk assessment considering rainfall‐induced landslide hazard and the vulnerability of disaster‐bearing body
Faming Huang, K Y Liu, Zhiyong Li, et al.
Geological Journal (2024) Vol. 59, Iss. 9, pp. 2549-2565
Closed Access | Times Cited: 8

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: 8

A Deep Neural Network Framework for Landslide Susceptibility Mapping by Considering Time-Series Rainfall
Binghai Gao, Yi He, Xueye Chen, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 5946-5969
Open Access | Times Cited: 5

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

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

Near-surface soil hydrothermal response feedbacks landslide activity and mechanism
Xiao Ye, Hong‐Hu Zhu, Bing Wu, et al.
Engineering Geology (2024) Vol. 341, pp. 107690-107690
Closed Access | Times Cited: 5

Integrating Knowledge Graph and Machine Learning Methods for Landslide Susceptibility Assessment
Qirui Wu, Zhong Xie, Miao Tian, et al.
Remote Sensing (2024) Vol. 16, Iss. 13, pp. 2399-2399
Open Access | Times Cited: 4

Debris flow susceptibility assessment based on information value and machine learning coupling method: from the perspective of sustainable development
Jiasheng Cao, Shengwu Qin, Jingyu Yao, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 37, pp. 87500-87516
Closed Access | Times Cited: 10

Domain Knowledge-Guided Intelligent Recognition of Multi-Type Potential Landslides
Qinghao Liu, Hui Li, Qing Lan, et al.
Knowledge-Based Systems (2025) Vol. 310, pp. 112979-112979
Closed 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

Evaluating the uncertainty in landslide susceptibility prediction: effect of spatial data variability and evaluation unit choices
Shengwu Qin, Jiasheng Cao, Jingyu Yao, et al.
Bulletin of Engineering Geology and the Environment (2025) Vol. 84, Iss. 3
Closed Access

Production and Analysis of a Landslide Susceptibility Map Covering Entire China
Guo Zhang, Yutao Liu, Zhenwei Chen, et al.
Remote Sensing (2025) Vol. 17, Iss. 9, pp. 1615-1615
Open Access

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