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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:

Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM
Jie Dou, Ali P. Yunus, Dieu Tien Bui, et al.
Remote Sensing (2019) Vol. 11, Iss. 6, pp. 638-638
Open Access | Times Cited: 147

Showing 1-25 of 147 citing articles:

Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
Abdelaziz Merghadi, Ali P. Yunus, Jie Dou, et al.
Earth-Science Reviews (2020) Vol. 207, pp. 103225-103225
Closed Access | Times Cited: 825
Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan
Jie Dou, Ali P. Yunus, Dieu Tien Bui, et al.
Landslides (2019) Vol. 17, Iss. 3, pp. 641-658
Closed Access | Times Cited: 437
Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning
Jie Dou, Ali P. Yunus, Abdelaziz Merghadi, et al.
The Science of The Total Environment (2020) Vol. 720, pp. 137320-137320
Closed Access | Times Cited: 240
Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques
Kuan-Tsung Chang, Abdelaziz Merghadi, Ali P. Yunus, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 231
Comparative study of landslide susceptibility mapping with different recurrent neural networks
Yi Wang, Zhice Fang, Mao Wang, et al.
Computers & Geosciences (2020) Vol. 138, pp. 104445-104445
Closed Access | Times Cited: 230
Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
Viet‐Ha Nhu, Ataollah Shirzadi, Himan Shahabi, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 8, pp. 2749-2749
Open Access | Times Cited: 221
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
A hybrid ensemble-based deep-learning framework for landslide susceptibility mapping
Liang Lv, Tao Chen, Jie Dou, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 108, pp. 102713-102713
Open Access | Times Cited: 120
GIS-Based Landslide Susceptibility Mapping for Land Use Planning and Risk Assessment
Anna Roccati, Guido Paliaga, Fabio Luino, et al.
Land (2021) Vol. 10, Iss. 2, pp. 162-162
Open Access | Times Cited: 110
Uncertainty analysis of non-landslide sample selection in landslide susceptibility prediction using slope unit-based machine learning models
Zhilu Chang, Jinsong Huang, Faming Huang, et al.
Gondwana Research (2023) Vol. 117, pp. 307-320
Closed Access | Times Cited: 76
A review of recent earthquake-induced landslides on the Tibetan Plateau
Bo Zhao, Lijun Su, Qiang Xu, et al.
Earth-Science Reviews (2023) Vol. 244, pp. 104534-104534
Closed Access | Times Cited: 47
Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique: The DakNong Province Case-study, Vietnam
Phong Tung Nguyen, Duong Hai Ha, Abolfazl Jaafari, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 7, pp. 2473-2473
Open Access | Times Cited: 125
Spatial predicting of flood potential areas using novel hybridizations of fuzzy decision-making, bivariate statistics, and machine learning
Romulus Costache, Mihnea Cristian Popa, Dieu Tien Bui, et al.
Journal of Hydrology (2020) Vol. 585, pp. 124808-124808
Closed Access | Times Cited: 113
A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping
Binh Thai Pham, Tran Van Phong, Huu Duy Nguyen, et al.
Water (2020) Vol. 12, Iss. 1, pp. 239-239
Open Access | Times Cited: 111
Machine Learning-Based Gully Erosion Susceptibility Mapping: A Case Study of Eastern India
Sunil Saha, Jagabandhu Roy, Alireza Arabameri, et al.
Sensors (2020) Vol. 20, Iss. 5, pp. 1313-1313
Open Access | Times Cited: 95
Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam
Tran Van Phong, Phan Trọng Trịnh, Indra Prakash, et al.
Geocarto International (2019) Vol. 36, Iss. 15, pp. 1685-1708
Closed Access | Times Cited: 92
Rapidly assessing earthquake-induced landslide susceptibility on a global scale using random forest
Qian He, Ming Wang, Kai Liu
Geomorphology (2021) Vol. 391, pp. 107889-107889
Closed Access | Times Cited: 82
GIS-based comparative study of Bayes network, Hoeffding tree and logistic model tree for landslide susceptibility modeling
Wenwu Chen, Shuai Zhang
CATENA (2021) Vol. 203, pp. 105344-105344
Closed Access | Times Cited: 77
Landslide Detection Mapping Employing CNN, ResNet, and DenseNet in the Three Gorges Reservoir, China
Tong Liu, Tao Chen, Ruiqing Niu, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2021) Vol. 14, pp. 11417-11428
Open Access | Times Cited: 62
Rainfall-induced landslide susceptibility mapping using machine learning algorithms and comparison of their performance in Hilly area of Fujian Province, China
Peng Ye, Bin Yu, Wenhong Chen, et al.
Natural Hazards (2022) Vol. 113, Iss. 2, pp. 965-995
Closed Access | Times Cited: 48
Vegetation-landslide nexus and topographic changes post the 2004 Mw 6.6 Chuetsu earthquake
Zilin Xiang, Jie Dou, Ali P. Yunus, et al.
CATENA (2023) Vol. 223, pp. 106946-106946
Closed Access | Times Cited: 25
Exploring machine learning and statistical approach techniques for landslide susceptibility mapping in Siwalik Himalayan Region using geospatial technology
Abhik Saha, Lakshya Tripathi, Vasanta Govind Kumar Villuri, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 7, pp. 10443-10459
Closed Access | Times Cited: 13
Impacts of Resampling and Downscaling Digital Elevation Model and Its Morphometric Factors: A Comparison of Hopfield Neural Network, Bilinear, Bicubic, and Kriging Interpolations
Quang Minh Nguyen, Nguyễn Thị Thu Hương, Pham Quoc Khanh, et al.
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 819-819
Open Access | Times Cited: 10
Forecasting step-like landslide displacement through diverse monitoring frequencies
Fei Guo, XU Zhi-zhen, Jilei Hu, et al.
Journal of Mountain Science (2025)
Open Access | Times Cited: 1
Integrating a multi-dimensional deep convolutional neural network with optimized sample selection for landslide susceptibility assessment
Yueyue Wang, Xueling Wu, Kun Zou, et al.
Geo-spatial Information Science (2025), pp. 1-21
Open Access | Times Cited: 1
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