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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:

The importance of input data on landslide susceptibility mapping
Krzysztof Gaidzik, María Teresa Ramírez‐Herrera
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 90

Showing 1-25 of 90 citing articles:

A comprehensive review of machine learning‐based methods in landslide susceptibility mapping
Songlin Liu, Luqi Wang, Wengang Zhang, et al.
Geological Journal (2023) Vol. 58, Iss. 6, pp. 2283-2301
Closed Access | Times Cited: 114
Landslide susceptibility prediction using artificial neural networks, SVMs and random forest: hyperparameters tuning by genetic optimization algorithm
Mehrdad Daviran, Mehdi Shamekhi, Reza Ghezelbash, et al.
International Journal of Environmental Science and Technology (2022) Vol. 20, Iss. 1, pp. 259-276
Closed Access | Times Cited: 83
High resolution landslide susceptibility mapping using ensemble machine learning and geospatial big data
Nirdesh Sharma, Manabendra Saharia, G. V. Ramana
CATENA (2023) Vol. 235, pp. 107653-107653
Open Access | Times Cited: 46
Deep learning and benchmark machine learning based landslide susceptibility investigation, Garhwal Himalaya (India)
Soumik Saha, Paromita Majumdar, Biswajit Bera
Quaternary Science Advances (2023) Vol. 10, pp. 100075-100075
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
Towards a holistic assessment of landslide susceptibility models: insights from the Central Eastern Alps
Matthias Schlögl, Raphael Spiekermann, Stefan Steger
Environmental Earth Sciences (2025) Vol. 84, Iss. 4
Open Access | Times Cited: 2
Comparative assessment of machine learning models for landslide susceptibility mapping: a focus on validation and accuracy
Mohamed M. Abdelkader, Árpád Csámer
Natural Hazards (2025)
Open Access | Times Cited: 2
Comparison of LiDAR- and UAV-derived data for landslide susceptibility mapping using Random Forest algorithm
Felicia França Pereira, Tatiana Sussel Gonçalves Mendes, Silvio Jorge Coelho Simões, et al.
Landslides (2023) Vol. 20, Iss. 3, pp. 579-600
Closed Access | Times Cited: 25
Selection of contributing factors for predicting landslide susceptibility using machine learning and deep learning models
Cheng Chen, Lei Fan
Stochastic Environmental Research and Risk Assessment (2023)
Open Access | Times Cited: 23
Landslide susceptibility, ensemble machine learning, and accuracy methods in the southern Sinai Peninsula, Egypt: Assessment and Mapping
Ahmed M. Youssef, Bosy A. El‐Haddad, Hariklia D. Skilodimou, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 15
Uncertainties of landslide susceptibility prediction: influences of different study area scales and mapping unit scales
Faming Huang, Yu Cao, Wenbin Li, et al.
International Journal of Coal Science & Technology (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 14
Seismic landslide susceptibility assessment using principal component analysis and support vector machine
Ziyao Xu, Ailan Che, Hanxu Zhou
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 12
National‐Scale Rainfall‐Triggered Landslide Susceptibility and Exposure in Nepal
Mark Kincey, Nick Rosser, Zuzanna Swirad, et al.
Earth s Future (2024) Vol. 12, Iss. 2
Open Access | Times Cited: 9
Spatiotemporal analysis, simulation, and early warning of landslides based on landslide sensitivity and multisource precipitation products in Southwestern China
Rui Zhang, Sheng Chen
Landslides (2025)
Closed Access | Times Cited: 1
Landslide Susceptibility Assessment Using the Geographical-Optimal-Similarity Model
Yonghong Xiao, Guolong Li, Wei Lu, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 1843-1843
Open Access | Times Cited: 1
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 | Times Cited: 1
RER2023: the landslide inventory dataset of the May 2023 Emilia-Romagna meteorological event
Matteo Berti, Marco Pizziolo, Michele Scaroni, et al.
Earth system science data (2025) Vol. 17, Iss. 3, pp. 1055-1074
Open Access | Times Cited: 1
Advanced machine learning techniques for enhanced landslide susceptibility mapping: Integrating geotechnical parameters in the case of Southwestern Cyprus
Ploutarchos Tzampoglou, Dimitrios Loukidis, Aristodemos Anastasiades, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 2
Open Access | Times Cited: 1
Hybrid machine learning approach for landslide prediction, Uttarakhand, India
Poonam Kainthura, Neelam Sharma
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 38
A Data-Driven Model on Google Earth Engine for Landslide Susceptibility Assessment in the Hengduan Mountains, the Qinghai–Tibetan Plateau
Wenhuan Wu, Qiang Zhang, Vijay P. Singh, et al.
Remote Sensing (2022) Vol. 14, Iss. 18, pp. 4662-4662
Open Access | Times Cited: 36
An Efficient User-Friendly Integration Tool for Landslide Susceptibility Mapping Based on Support Vector Machines: SVM-LSM Toolbox
Wubiao Huang, Mingtao Ding, Zhenhong Li, et al.
Remote Sensing (2022) Vol. 14, Iss. 14, pp. 3408-3408
Open Access | Times Cited: 31
Influences of non-landslide sample selection strategies on landslide susceptibility mapping by machine learning
Hongqiang Dou, Junbin He, Siyi Huang, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 21
Redefining landslide susceptibility under extreme rainfall events using deep learning
A.L. Achu, Jobin Thomas, C. D. Aju, et al.
Geomorphology (2023) Vol. 448, pp. 109033-109033
Closed Access | Times Cited: 19
Landslide susceptibility mapping in Badakhshan province, Afghanistan: a comparative study of machine learning algorithms
Abdul Baser Qasimi, Vahid Isazade, Enayatullah Enayat, et al.
Geocarto International (2023) Vol. 38, Iss. 1
Open Access | Times Cited: 17
A Meta-Learning Approach of Optimisation for Spatial Prediction of Landslides
Biswajeet Pradhan, Maher Ibrahim Sameen, Husam A. H. Al-Najjar, et al.
Remote Sensing (2021) Vol. 13, Iss. 22, pp. 4521-4521
Open Access | Times Cited: 36
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