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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:

Improved landslide susceptibility mapping using unsupervised and supervised collaborative machine learning models
Chenxu Su, Bijiao Wang, Yunhong Lv, et al.
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2022) Vol. 17, Iss. 2, pp. 387-405
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Vulnerability of buildings to landslides: The state of the art and future needs
Hongyu Luo, Limin Zhang, LingQiang ZHANG, et al.
Earth-Science Reviews (2023) Vol. 238, pp. 104329-104329
Closed Access | Times Cited: 46
Effects of non-landslide sampling strategies on machine learning models in landslide susceptibility mapping
Tengfei Gu, Ping Duan, Mingguo Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 21
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: 18
Comparison of hybrid data-driven and physical models for landslide susceptibility mapping at regional scales
Xin Wei, Lulu Zhang, Paolo Gardoni, et al.
Acta Geotechnica (2023) Vol. 18, Iss. 8, pp. 4453-4476
Closed Access | Times Cited: 32
Data-driven landslide forecasting: Methods, data completeness, and real-time warning
Te Xiao, Limin Zhang
Engineering Geology (2023) Vol. 317, pp. 107068-107068
Closed Access | Times Cited: 24
Quantification of climate change impact on rainfall-induced shallow landslide susceptibility: a case study in central Norway
Emir Ahmet Oguz, Rasmus Benestad, Kajsa M. Parding, et al.
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2024) Vol. 18, Iss. 2, pp. 467-490
Open Access | Times Cited: 12
Assessing landslide susceptibility in Lake Abya catchment, Rift Valley, Ethiopia: A GIS-based frequency ratio analysis
Yonas Oyda, Muralitharan Jothimani, Hailu Regasa
Journal of Degraded and Mining Lands Management (2024) Vol. 11, Iss. 3, pp. 5885-5895
Open Access | Times Cited: 11
Optimizing the Sample Selection of Machine Learning Models for Landslide Susceptibility Prediction Using Information Value Models in the Dabie Mountain Area of Anhui, China
Yanrong Liu, Zhongqiu Meng, Lei Zhu, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 1971-1971
Open Access | Times Cited: 22
Deep learning characterization of rock conditions based on tunnel boring machine data
Xu Li, Min Yao, Jidong Yuan, et al.
Underground Space (2023) Vol. 12, pp. 89-101
Open Access | Times Cited: 15
Predicting landslide runout paths using terrain matching-targeted machine learning
Lu-Yu Ju, Te Xiao, Jian He, et al.
Engineering Geology (2022) Vol. 311, pp. 106902-106902
Closed Access | Times Cited: 20
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
The influence of the selection of non-geological disasters sample spatial range on the evaluation of environmental geological disasters susceptibility: a case study of Liulin County
Jianping Chen, Zepeng Wang, Wei Chen, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 15, pp. 44756-44772
Closed Access | Times Cited: 10
Quantitative evaluation of uncertainty and interpretability in machine learning-based landslide susceptibility mapping through feature selection and explainable AI
Xuan-Hien Le, Chanul Choi, Song Eu, et al.
Frontiers in Environmental Science (2024) Vol. 12
Open Access | Times Cited: 3
Landslide Susceptibility Mapping Using DIvisive ANAlysis (DIANA) and RObust Clustering Using linKs (ROCK) Algorithms, and Comparison of Their Performance
Deborah Simon Mwakapesa, Yimin Mao, Xiaoji Lan, et al.
Sustainability (2023) Vol. 15, Iss. 5, pp. 4218-4218
Open Access | Times Cited: 7
Influence of buffer distance on environmental geological hazard susceptibility assessment
Zepeng Wang, J J Chen, Zechen Lian, et al.
Environmental Science and Pollution Research (2024)
Closed Access | Times Cited: 2
Hybrid method for rainfall-induced regional landslide susceptibility mapping
Shuangyi Wu, Huaan Wang, Jie Zhang, et al.
Stochastic Environmental Research and Risk Assessment (2024)
Closed Access | Times Cited: 2
Landslide susceptibility mapping using O-CURE and PAM clustering algorithms
Deborah Simon Mwakapesa, Xiaoji Lan, Yaser A. Nanehkaran, et al.
Frontiers in Environmental Science (2023) Vol. 11
Open Access | Times Cited: 6
GBDT-based multivariate structural stress data analysis for predicting the sinking speed of an open caisson foundation
Xuechao Dong, Mingwei Guo, Shuilin Wang
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2023) Vol. 18, Iss. 2, pp. 333-345
Closed Access | Times Cited: 4
Reliability assessment of open-source multiscale landslide susceptibility maps and effects of their fusion
Giandomenico Mastrantoni, Gian Marco Marmoni, Carlo Esposito, et al.
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2023) Vol. 18, Iss. 3, pp. 628-645
Open Access | Times Cited: 3
A Comparative Study of Landslide Susceptibility Mapping Using Bagging PU Learning in Class-Prior Probability Shift Datasets
Lingran Zhao, Hangling Ma, Jiahui Dong, et al.
Remote Sensing (2023) Vol. 15, Iss. 23, pp. 5547-5547
Open Access | Times Cited: 3
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: 2
The generative adversarial neural network with multi-layers stack ensemble hybrid model for landslide prediction in case of training sample imbalance
Wajid Hussain, Shu Hong, Hasnain Abbas, et al.
Stochastic Environmental Research and Risk Assessment (2024)
Closed Access
Benchmarking landslide inventory data handling strategies for landslide susceptibilitymodeling based on different random forest machine learning workflows
Guruh Samodra, Ngadisih, Ferman Setia Nugroho
Artificial Intelligence in Geosciences (2024) Vol. 5, pp. 100093-100093
Open Access
Physically based probabilistic prediction of regional rainfall-induced shallow landslides: from initiation to runout analysis
Chenguang Wu, Jie Zhang, Hongxin Chen, et al.
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2024), pp. 1-14
Closed Access
Prediction of landslide induced debris’ severity using machine learning algorithms: a case of South Korea
Jérémie Tuganishuri, Chan-Young Yune, Gihong Kim, et al.
(2023)
Open Access
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