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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:

Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment
Dieu Tien Bui, Paraskevas Tsangaratos, Viet-Tien Nguyen, et al.
CATENA (2020) Vol. 188, pp. 104426-104426
Closed Access | Times Cited: 379

Showing 26-50 of 379 citing articles:

Deep Learning for Exploring Landslides with Remote Sensing and Geo-Environmental Data: Frameworks, Progress, Challenges, and Opportunities
Qi Zhang, Teng Wang
Remote Sensing (2024) Vol. 16, Iss. 8, pp. 1344-1344
Open Access | Times Cited: 19
Predictive modeling of air quality in the Tehran megacity via deep learning techniques
Abdullah Kaviani Rad, Mohammad Javad Nematollahi, Abbas Pak, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Remote Sensing for Assessing Landslides and Associated Hazards
Candide Lissak, Annett Bartsch, Marcello de Michele, et al.
Surveys in Geophysics (2020) Vol. 41, Iss. 6, pp. 1391-1435
Closed Access | Times Cited: 118
Gully erosion spatial modelling: Role of machine learning algorithms in selection of the best controlling factors and modelling process
Hamid Reza Pourghasemi, Nitheshnirmal Sãdhasivam, Narges Kariminejad, et al.
Geoscience Frontiers (2020) Vol. 11, Iss. 6, pp. 2207-2219
Open Access | Times Cited: 114
A novel approach for classification of soils based on laboratory tests using Adaboost, Tree and ANN modeling
Binh Thai Pham, Manh Duc Nguyen, T. Nguyen‐Thoi, et al.
Transportation Geotechnics (2020) Vol. 27, pp. 100508-100508
Closed Access | Times Cited: 100
A Novel GIS-Based Random Forest Machine Algorithm for the Spatial Prediction of Shallow Landslide Susceptibility
Viet-Hung Dang, Nhat‐Duc Hoang, Le-Mai-Duyen Nguyen, et al.
Forests (2020) Vol. 11, Iss. 1, pp. 118-118
Open Access | Times Cited: 76
Rainfall Induced Landslide Susceptibility Mapping Based on Bayesian Optimized Random Forest and Gradient Boosting Decision Tree Models—A Case Study of Shuicheng County, China
Guangzhi Rong, Si Alu, Kaiwei Li, et al.
Water (2020) Vol. 12, Iss. 11, pp. 3066-3066
Open Access | Times Cited: 75
Prediction of spatiotemporal stability and rainfall threshold of shallow landslides using the TRIGRS and Scoops3D models
Jianyin He, Haijun Qiu, Feihang Qu, et al.
CATENA (2020) Vol. 197, pp. 104999-104999
Closed Access | Times Cited: 75
Landslide susceptibility index based on the integration of logistic regression and weights of evidence: A case study in Popayan, Colombia
Paul Goyes-Peñafiel, Alejandra Hernandez-Rojas
Engineering Geology (2020) Vol. 280, pp. 105958-105958
Closed Access | Times Cited: 75
Comparing classical statistic and machine learning models in landslide susceptibility mapping in Ardanuc (Artvin), Turkey
Halil Akıncı, Mustafa Zeybek
Natural Hazards (2021) Vol. 108, Iss. 2, pp. 1515-1543
Closed Access | Times Cited: 73
Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India
Rabin Chakrabortty, Subodh Chandra Pal, Fatemeh Rezaie, et al.
Geocarto International (2021) Vol. 37, Iss. 23, pp. 6713-6735
Closed Access | Times Cited: 73
Application of Bayesian Hyperparameter Optimized Random Forest and XGBoost Model for Landslide Susceptibility Mapping
Wang Shibao, Jianqi Zhuang, Jia Zheng, et al.
Frontiers in Earth Science (2021) Vol. 9
Open Access | Times Cited: 72
Combining a class-weighted algorithm and machine learning models in landslide susceptibility mapping: A case study of Wanzhou section of the Three Gorges Reservoir, China
Huijuan Zhang, Yingxu Song, Shiluo Xu, et al.
Computers & Geosciences (2021) Vol. 158, pp. 104966-104966
Open Access | Times Cited: 68
Evaluation of different DEMs for gully erosion susceptibility mapping using in-situ field measurement and validation
Indrajit Chowdhuri, Subodh Chandra Pal, Asish Saha, et al.
Ecological Informatics (2021) Vol. 65, pp. 101425-101425
Closed Access | Times Cited: 60
Susceptibility assessment for rainfall-induced landslides using a revised logistic regression method
Xinfu Xing, Chenglong Wu, Jinhui Li, et al.
Natural Hazards (2021) Vol. 106, Iss. 1, pp. 97-117
Closed Access | Times Cited: 58
Mapping prospectivity for regolith-hosted REE deposits via convolutional neural network with generative adversarial network augmented data
Tong Li, Renguang Zuo, Xin-Fu Zhao, et al.
Ore Geology Reviews (2022) Vol. 142, pp. 104693-104693
Open Access | Times Cited: 56
Deep Neural Networks to Detect Weeds from Crops in Agricultural Environments in Real-Time: A Review
Ildar Rakhmatulin, Andreas Kamilaris, Christian Andreasen
Remote Sensing (2021) Vol. 13, Iss. 21, pp. 4486-4486
Open Access | Times Cited: 55
A GIS-Based Landslide Susceptibility Mapping and Variable Importance Analysis Using Artificial Intelligent Training-Based Methods
Pengxiang Zhao, Zohreh Masoumi, Maryam Kalantari, et al.
Remote Sensing (2022) Vol. 14, Iss. 1, pp. 211-211
Open Access | Times Cited: 53
Bibliometric analysis of landslide research based on the WOS database
Yuandong Huang, Chong Xu, Xujiao Zhang, et al.
Natural Hazards Research (2022) Vol. 2, Iss. 2, pp. 49-61
Open Access | Times Cited: 47
Flood susceptibility mapping of Northeast coastal districts of Tamil Nadu India using Multi-source Geospatial data and Machine Learning techniques
Subbarayan Saravanan, Devanantham Abijith
Geocarto International (2022) Vol. 37, Iss. 27, pp. 15252-15281
Closed Access | Times Cited: 44
Explainable step-wise binary classification for the susceptibility assessment of geo-hydrological hazards
Ömer Ekmekcioğlu, Kerim Koç
CATENA (2022) Vol. 216, pp. 106379-106379
Closed Access | Times Cited: 42
Landslide identification using machine learning techniques: Review, motivation, and future prospects
S. Sreelakshmi, S. S. Vinod Chandra, E. Shaji
Earth Science Informatics (2022) Vol. 15, Iss. 4, pp. 2063-2090
Closed Access | Times Cited: 39
Dynamic landslides susceptibility evaluation in Baihetan Dam area during extensive impoundment by integrating geological model and InSAR observations
Keren Dai, Chen Chen, Xianlin Shi, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 116, pp. 103157-103157
Open Access | Times Cited: 39
Landslide susceptibility modeling by interpretable neural network
Khalid Youssef, Kun Shao, Seulgi Moon, et al.
Communications Earth & Environment (2023) Vol. 4, Iss. 1
Open Access | Times Cited: 38
Assessing landslide susceptibility based on hybrid Best-first decision tree with ensemble learning model
Haoyuan Hong
Ecological Indicators (2023) Vol. 147, pp. 109968-109968
Open Access | Times Cited: 37

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