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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:

Performance Evaluation of GIS-Based Artificial Intelligence Approaches for Landslide Susceptibility Modeling and Spatial Patterns Analysis
Xinxiang Lei, Wei Chen, Binh Thai Pham
ISPRS International Journal of Geo-Information (2020) Vol. 9, Iss. 7, pp. 443-443
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

GIS-based landslide susceptibility assessment using optimized hybrid machine learning methods
Xi Chen, Wei Chen
CATENA (2020) Vol. 196, pp. 104833-104833
Closed Access | Times Cited: 247
Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility
Wei Chen, Xinxiang Lei, Rabin Chakrabortty, et al.
Journal of Environmental Management (2021) Vol. 284, pp. 112015-112015
Closed Access | Times Cited: 131
Applying deep learning and benchmark machine learning algorithms for landslide susceptibility modelling in Rorachu river basin of Sikkim Himalaya, India
Kanu Mandal, Sunil Saha, Sujit Mandal
Geoscience Frontiers (2021) Vol. 12, Iss. 5, pp. 101203-101203
Open Access | Times Cited: 131
A comparison among fuzzy multi-criteria decision making, bivariate, multivariate and machine learning models in landslide susceptibility mapping
Quoc Bao Pham, Yacine Achour, Sk Ajim Ali, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 1741-1777
Open Access | Times Cited: 115
GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran
Xinxiang Lei, Wei Chen, Mohammadtaghi Avand, et al.
Remote Sensing (2020) Vol. 12, Iss. 15, pp. 2478-2478
Open Access | Times Cited: 121
Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential
Yunzhi Chen, Wei Chen, Subodh Chandra Pal, et al.
Geocarto International (2021) Vol. 37, Iss. 19, pp. 5564-5584
Closed Access | Times Cited: 97
Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments
Wei Chen, Yunzhi Chen, Paraskevas Tsangaratos, et al.
Remote Sensing (2020) Vol. 12, Iss. 23, pp. 3854-3854
Open Access | Times Cited: 86
Flood susceptibility assessment using extreme gradient boosting (EGB), Iran
Sajjad Mirzaei, Mehdi Vafakhah, Biswajeet Pradhan, et al.
Earth Science Informatics (2020) Vol. 14, Iss. 1, pp. 51-67
Closed Access | Times Cited: 82
Landslide susceptibility assessment in the Himalayan range based along Kasauli – Parwanoo road corridor using weight of evidence, information value, and frequency ratio
Abdullah H. Alsabhan, Kanwarpreet Singh, Abhishek Sharma, et al.
Journal of King Saud University - Science (2021) Vol. 34, Iss. 2, pp. 101759-101759
Open Access | Times Cited: 59
A Robust Deep-Learning Model for Landslide Susceptibility Mapping: A Case Study of Kurdistan Province, Iran
Bahareh Ghasemian, Himan Shahabi, Ataollah Shirzadi, et al.
Sensors (2022) Vol. 22, Iss. 4, pp. 1573-1573
Open Access | Times Cited: 44
SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan
Isma Kulsoom, Weihua Hua, Sadaqat Hussain, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 42
Assessment of the effects of characterization methods selection on the landslide susceptibility: a comparison between logistic regression (LR), naive bayes (NB) and radial basis function network (RBF Network)
Hui Shang, Lixiang Su, Yang Liu, et al.
Bulletin of Engineering Geology and the Environment (2025) Vol. 84, Iss. 3
Closed Access | Times Cited: 1
Modeling Spatial Flood using Novel Ensemble Artificial Intelligence Approaches in Northern Iran
Alireza Arabameri, Sunil Saha, Kaustuv Mukherjee, et al.
Remote Sensing (2020) Vol. 12, Iss. 20, pp. 3423-3423
Open Access | Times Cited: 69
Bagging-based machine learning algorithms for landslide susceptibility modeling
Tingyu Zhang, Quan Fu, Hao Wang, et al.
Natural Hazards (2021) Vol. 110, Iss. 2, pp. 823-846
Open Access | Times Cited: 50
Prediction of spatial landslide susceptibility applying the novel ensembles of CNN, GLM and random forest in the Indian Himalayan region
Sunil Saha, Anik Saha, Tusar Kanti Hembram, et al.
Stochastic Environmental Research and Risk Assessment (2022) Vol. 36, Iss. 10, pp. 3597-3616
Closed Access | Times Cited: 32
Landslide Susceptibility Modeling Using Remote Sensing Data and Random SubSpace-Based Functional Tree Classifier
Tao Peng, Yunzhi Chen, Wei Chen
Remote Sensing (2022) Vol. 14, Iss. 19, pp. 4803-4803
Open Access | Times Cited: 31
Performance assessment of the landslide susceptibility modelling using the support vector machine, radial basis function network, and weight of evidence models in the N'fis river basin, Morocco
Hassan Ait Naceur, Hazem Ghassan Abdo, Brahim Igmoullan, et al.
Geoscience Letters (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 29
Comparison of LR, 5-CV SVM, GA SVM, and PSO SVM for landslide susceptibility assessment in Tibetan Plateau area, China
Yingbin Zhang, Peiyi Xu, Jing Liu, et al.
Journal of Mountain Science (2023) Vol. 20, Iss. 4, pp. 979-995
Closed Access | Times Cited: 22
Landslide susceptibility mapping in three Upazilas of Rangamati hill district Bangladesh: application and comparison of GIS-based machine learning methods
Yasin Wahid Rabby, Md Belal Hossain, Joynal Abedin
Geocarto International (2020) Vol. 37, Iss. 12, pp. 3371-3396
Closed Access | Times Cited: 50
GIS-based landslide susceptibility mapping using hybrid MCDM models
Amin Salehpour Jam, Jamal Mosaffaie, Faramarz Sarfaraz, et al.
Natural Hazards (2021) Vol. 108, Iss. 1, pp. 1025-1046
Closed Access | Times Cited: 38
Enhancing the Accuracy of the REPTree by Integrating the Hybrid Ensemble Meta-Classifiers for Modelling the Landslide Susceptibility of Idukki District, South-western India
R. S. Ajin, Sunil Saha, Anik Saha, et al.
Journal of the Indian Society of Remote Sensing (2022) Vol. 50, Iss. 11, pp. 2245-2265
Closed Access | Times Cited: 26
Flood hazard potential evaluation using decision tree state‐of‐the‐art models
Romulus Costache, Alireza Arabameri, Iulia Costache, et al.
Risk Analysis (2023) Vol. 44, Iss. 2, pp. 439-458
Closed Access | Times Cited: 10
Advanced AI techniques for landslide susceptibility mapping and spatial prediction: A case study in Medellín, Colombia
Ingry Natalia Gómez Miranda, Camilo Restrepo‐Estrada, Alejandro Builes‐Jaramillo, et al.
Applied Computing and Geosciences (2025) Vol. 25, pp. 100226-100226
Open Access
Review on the progress and future prospects of geological disasters prediction in the era of artificial intelligence
Xiang Zhang, Minghui Zhang, Xin Liu, et al.
Natural Hazards (2024) Vol. 120, Iss. 13, pp. 11485-11525
Closed Access | Times Cited: 3
Modeling landslide susceptibility using an evidential belief function-based multiclass alternating decision tree and logistic model tree
Qifei Zhao, Wei Chen, Chaohong Peng, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 15
Closed Access | Times Cited: 13
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