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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:

An Ensemble Approach of Feature Selection and Machine Learning Models for Regional Landslide Susceptibility Mapping in the Arid Mountainous Terrain of Southern Peru
Chandan Kumar, Gabriel Walton, Paul M. Santi, et al.
Remote Sensing (2023) Vol. 15, Iss. 5, pp. 1376-1376
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Modelling landslide susceptibility prediction: A review and construction of semi-supervised imbalanced theory
Faming Huang, Haowen Xiong, Shui‐Hua Jiang, et al.
Earth-Science Reviews (2024) Vol. 250, pp. 104700-104700
Closed Access | Times Cited: 56
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: 41
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: 18
Multi-Stage Corn Yield Prediction Using High-Resolution UAV Multispectral Data and Machine Learning Models
Chandan Kumar, Partson Mubvumba, Yanbo Huang, et al.
Agronomy (2023) Vol. 13, Iss. 5, pp. 1277-1277
Open Access | Times Cited: 39
Machine learning-based field geological mapping: A new exploration of geological survey data acquisition strategy
Wenlei Wang, Congcong Xue, Jie Zhao, et al.
Ore Geology Reviews (2024) Vol. 166, pp. 105959-105959
Open Access | Times Cited: 14
Random Cross-Validation Produces Biased Assessment of Machine Learning Performance in Regional Landslide Susceptibility Prediction
Chandan Kumar, Gabriel Walton, Paul M. Santi, et al.
Remote Sensing (2025) Vol. 17, Iss. 2, pp. 213-213
Open Access | Times Cited: 1
Identifying the Areas at Risk of Huaico Occurrences in the Department of Lima, Peru
Geise Macedo dos Santos, Vânia Elisabete Schneider, Gisele Cemin, et al.
Climate (2025) Vol. 13, Iss. 1, pp. 11-11
Open Access
Explainable machine learning models for corn yield prediction using UAV multispectral data
Chandan Kumar, Jagmandeep Dhillon, Yanbo Huang, et al.
Computers and Electronics in Agriculture (2025) Vol. 231, pp. 109990-109990
Open Access
Artificial Intelligence for Predicting Climate and Natural Disasters in Peru
Ciro Rodríguez, Omart Tello-Malpartida, Pedro Infantes-Rivera, et al.
Lecture notes in networks and systems (2025), pp. 203-213
Closed Access
Landslide Susceptibility Mapping in Complex Topo‐Climatic Himalayan Terrain, India Using Machine Learning Models: A Comparative Study of XGBoost, RF and ANN
Shubham Badola, Manish Pandey, Varun Narayan Mishra, et al.
Geological Journal (2025)
Closed Access
Geospatial modeling of landslide susceptibility in Debek, South Wollo, Ethiopia: comparative analysis of frequency ratio and analytical hierarchy process models for geohazards management
Alemnew Ali, Degfie Teku, Tesfaldet Sisay, et al.
Frontiers in Earth Science (2025) Vol. 13
Open Access
Stacking Ensemble Technique Using Optimized Machine Learning Models with Boruta–XGBoost Feature Selection for Landslide Susceptibility Mapping: A Case of Kermanshah Province, Iran
Zeynab Yousefi, Ali Asghar Alesheikh, Ali Jafari, et al.
Information (2024) Vol. 15, Iss. 11, pp. 689-689
Open Access | Times Cited: 3
A novel local-global dependency deep learning model for soil mapping
Qingliang Li, Cheng Zhang, Wei Shangguan, et al.
Geoderma (2023) Vol. 438, pp. 116649-116649
Open Access | Times Cited: 8
A modular framework for FAIR shallow landslide susceptibility mapping based on machine learning
Ann-Kathrin Edrich, Anil Yıldiz, Ribana Roscher, et al.
Natural Hazards (2024) Vol. 120, Iss. 9, pp. 8953-8982
Open Access | Times Cited: 2
Landslide susceptibility mapping using ensemble machine learning methods: a case study in Lombardy, Northern Italy
Qiongjie Xu, Vasil Yordanov, Lorenzo Amici, et al.
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 2
A Systematic review of machine learning based landslide susceptibility mapping
Semachew Molla Kassa
Put i saobraćaj (2024) Vol. 70, Iss. 2, pp. 23-30
Open Access | Times Cited: 2
Enhancing flood mapping through ensemble machine learning in the Gamasyab watershed, Western Iran
Mohammad Bashirgonbad, Behnoush Farokhzadeh, Vahid Gholami
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 38, pp. 50427-50442
Closed Access | Times Cited: 2
Risk Mapping of Geological Hazards in Plateau Mountainous Areas Based on Multisource Remote Sensing Data Extraction and Machine Learning (Fuyuan, China)
Shaohan Zhang, Shucheng Tan, Yongqi Sun, et al.
Land (2024) Vol. 13, Iss. 9, pp. 1361-1361
Open Access | Times Cited: 2
Multi-scale analysis of the susceptibility of different landslide types and identification of the main controlling factors
Yuqian Yang, Shuangyun Peng, Bangmei Huang, et al.
Ecological Indicators (2024) Vol. 168, pp. 112797-112797
Open Access | Times Cited: 2
Assessing the Dimensionality Reduction of the Geospatial Dataset Using Principal Component Analysis (PCA) and Its Impact on the Accuracy and Performance of Ensembled and Non-ensembled Algorithms
Farkhanda Abbas, Feng Zhang, Javed Iqbal, et al.
(2023)
Open Access | Times Cited: 6
Modeling and Evaluation of the Susceptibility to Landslide Events Using Machine Learning Algorithms in the Province of Chañaral, Atacama Region, Chile
Francisco Parra, Jaime González, Máx Chacón, et al.
Sustainability (2023) Vol. 15, Iss. 24, pp. 16806-16806
Open Access | Times Cited: 6
Comparison between Machine Learning and Physical Models Applied to the Evaluation of Co-Seismic Landslide Hazard
José Carlos Román-Herrera, Martín Jesús Rodríguez-Peces, Julio Garzón-Roca
Applied Sciences (2023) Vol. 13, Iss. 14, pp. 8285-8285
Open Access | Times Cited: 5
Comparison of Multi-Criteria Decision Making, Statistics, and Machine Learning Models for Landslide Susceptibility Mapping in Van Yen District, Yen Bai Province, Vietnam
Tung Khuc, X.Q. Truong, Tran Van Anh, et al.
International Journal of Geoinformatics (2023), pp. 33-45
Open Access | Times Cited: 5
Evaluating the influence of road construction on landslide susceptibility in Saudi Arabia’s mountainous terrain: a Bayesian-optimised deep learning approach with attention mechanism and sensitivity analysis
Saeed Alqadhi, Javed Mallick, Hoang Thi Hang, et al.
Environmental Science and Pollution Research (2023) Vol. 31, Iss. 2, pp. 3169-3194
Closed Access | Times Cited: 4
Landslide Susceptibility Mapping Through Hyperparameter Optimized Bagging and Boosting Ensembles: Case Study of NH-10, West Bengal, India
Sumon Dey, Swarup Das
Advances in geographic information science (2024), pp. 123-140
Closed Access | Times Cited: 1
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