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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:

Sedimentological characteristics and application of machine learning techniques for landslide susceptibility modelling along the highway corridor Nahan to Rajgarh (Himachal Pradesh), India
Vijendra Kumar Pandey, Kaushal Kumar Sharma, Hamid Reza Pourghasemi, et al.
CATENA (2019) Vol. 182, pp. 104150-104150
Closed Access | Times Cited: 58

Showing 1-25 of 58 citing articles:

A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
Dong Van Dao, Abolfazl Jaafari, Mahmoud Bayat, et al.
CATENA (2020) Vol. 188, pp. 104451-104451
Closed Access | Times Cited: 292
Landslide Susceptibility Prediction Based on Remote Sensing Images and GIS: Comparisons of Supervised and Unsupervised Machine Learning Models
Zhilu Chang, Zhen Du, Fan Zhang, et al.
Remote Sensing (2020) Vol. 12, Iss. 3, pp. 502-502
Open Access | Times Cited: 238
Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Abolfazl Baghbani, Tanveer Choudhury, Susanga Costa, et al.
Earth-Science Reviews (2022) Vol. 228, pp. 103991-103991
Closed Access | Times Cited: 199
Spatial prediction of landslide susceptibility using hybrid support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS) with various metaheuristic algorithms
Mahdi Panahi, Amiya Gayen, Hamid Reza Pourghasemi, et al.
The Science of The Total Environment (2020) Vol. 741, pp. 139937-139937
Closed Access | Times Cited: 155
Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine
Bakhtiar Feizizadeh, Davoud Omarzadeh, Mohammad Kazemi Garajeh, et al.
Journal of Environmental Planning and Management (2021) Vol. 66, Iss. 3, pp. 665-697
Closed Access | Times Cited: 139
Uncertainty study of landslide susceptibility prediction considering the different attribute interval numbers of environmental factors and different data-based models
Faming Huang, Ye Zhou, Shui‐Hua Jiang, et al.
CATENA (2021) Vol. 202, pp. 105250-105250
Closed Access | Times Cited: 112
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
Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China)
Yue Wang, Deliang Sun, Haijia Wen, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 12, pp. 4206-4206
Open Access | Times Cited: 120
Application of learning vector quantization and different machine learning techniques to assessing forest fire influence factors and spatial modelling
Hamid Reza Pourghasemi, Amiya Gayen, Rosa Lasaponara, et al.
Environmental Research (2020) Vol. 184, pp. 109321-109321
Closed Access | Times Cited: 109
Torrential rainfall-induced landslide susceptibility assessment using machine learning and statistical methods of eastern Himalaya
Indrajit Chowdhuri, Subodh Chandra Pal, Rabin Chakrabortty, et al.
Natural Hazards (2021) Vol. 107, Iss. 1, pp. 697-722
Closed Access | Times Cited: 81
Influence of human activity on landslide susceptibility development in the Three Gorges area
Yongwei Li, Xianmin Wang, Hang Mao
Natural Hazards (2020) Vol. 104, Iss. 3, pp. 2115-2151
Closed Access | Times Cited: 72
A critical review on landslide susceptibility zonation: recent trends, techniques, and practices in Indian Himalaya
Suvam Das, Shantanu Sarkar, Debi Prasanna Kanungo
Natural Hazards (2022) Vol. 115, Iss. 1, pp. 23-72
Closed Access | Times Cited: 52
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
Comparative analysis of the TabNet algorithm and traditional machine learning algorithms for landslide susceptibility assessment in the Wanzhou Region of China
Song Yingze, Song Yingxu, Xin Zhang, et al.
Natural Hazards (2024) Vol. 120, Iss. 8, pp. 7627-7652
Closed Access | Times Cited: 10
Landslide susceptibility assessment in mountainous area: a case study of Sichuan–Tibet railway, China
Ruian Wu, Yongshuang Zhang, Changbao Guo, et al.
Environmental Earth Sciences (2020) Vol. 79, Iss. 6
Closed Access | Times Cited: 59
Evaluation of the landslide susceptibility and its spatial difference in the whole Qinghai-Tibetan Plateau region by five learning algorithms
Payam Sajadi, Yan‐Fang Sang, Mehdi Gholamnia, et al.
Geoscience Letters (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 35
Influence of anthropogenic activities on landslide susceptibility: A case study in Solan district, Himachal Pradesh, India
Sangeeta, Sanjay Kumar Singh
Journal of Mountain Science (2023) Vol. 20, Iss. 2, pp. 429-447
Closed Access | Times Cited: 21
Landslide susceptibility mapping using state-of-the-art machine learning ensembles
Binh Thai Pham, Vu Duy Vinh, Romulus Costache, et al.
Geocarto International (2021) Vol. 37, Iss. 18, pp. 5175-5200
Closed Access | Times Cited: 35
Mapping of earthquake hotspot and coldspot zones for identifying potential landslide hotspot areas in the Himalayan region
Indrajit Chowdhuri, Subodh Chandra Pal, Asish Saha, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 7
Closed Access | Times Cited: 23
Performance Analysis of Random Forest on Quartile Classification Journal
Cornaldo Beliarding Sucahyo, Fajriwati Qoyyum Rizqini, Ayyub Naufal, et al.
Applied Engineering and Technology (2024) Vol. 3, Iss. 1, pp. 1-17
Open Access | Times Cited: 6
Landslide Susceptibility Mapping Using Machine Learning in Himalayan Region: A Review
Shubham Badola, Surya Parkash
Springer eBooks (2024), pp. 123-143
Closed Access | Times Cited: 6
Assessing, mapping, and optimizing the locations of sediment control check dams construction
Hamid Reza Pourghasemi, Saleh Yousefi, Nitheshnirmal Sãdhasivam, et al.
The Science of The Total Environment (2020) Vol. 739, pp. 139954-139954
Closed Access | Times Cited: 35
Debris-flow susceptibility assessment in Dongchuan using stacking ensemble learning including multiple heterogeneous learners with RFE for factor optimization
Kun Li, Junsan Zhao, Yilin Lin
Natural Hazards (2023) Vol. 118, Iss. 3, pp. 2477-2511
Open Access | Times Cited: 13
Debris flow susceptibility assessment based on boosting ensemble learning techniques: a case study in the Tumen River basin, China
Zelu Chen, Hechun Quan, Ri Jin, et al.
Stochastic Environmental Research and Risk Assessment (2024) Vol. 38, Iss. 6, pp. 2359-2382
Closed Access | Times Cited: 4
Experimental study of stony debris flow and its feature importance with varying coarse grain and water content
Nikhil Kumar Pandey, Braj Pal Singh, Neelima Satyam
Environmental Earth Sciences (2024) Vol. 83, Iss. 22
Closed Access | Times Cited: 4
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