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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.

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Showing 1-25 of 64 citing articles:

Uncertainties of landslide susceptibility prediction considering different landslide types
Faming Huang, Haowen Xiong, Chi Yao, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 15, Iss. 11, pp. 2954-2972
Open Access | Times Cited: 70
Machine learning based forest fire susceptibility assessment of Manavgat district (Antalya), Turkey
Hazan Alkan Akıncı, Halil Akıncı
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 397-414
Closed Access | Times Cited: 53
A Novel Hybrid Method for Landslide Susceptibility Mapping-Based GeoDetector and Machine Learning Cluster: A Case of Xiaojin County, China
Wei Xie, Xiaoshuang Li, Wenbin Jian, et al.
ISPRS International Journal of Geo-Information (2021) Vol. 10, Iss. 2, pp. 93-93
Open Access | Times Cited: 91
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: 75
Landslide susceptibility mapping using frequency ratio model: the case of Gamo highland, South Ethiopia
Leulalem Shano, Tarun Kumar Raghuvanshi, Matebie Meten
Arabian Journal of Geosciences (2021) Vol. 14, Iss. 7
Closed Access | Times Cited: 69
A Comparative Assessment of Machine Learning Models for Landslide Susceptibility Mapping in the Rugged Terrain of Northern Pakistan
Naeem Shahzad, Xiaoli Ding, Sawaid Abbas
Applied Sciences (2022) Vol. 12, Iss. 5, pp. 2280-2280
Open Access | Times Cited: 42
Spatial prediction of groundwater potential and driving factor analysis based on deep learning and geographical detector in an arid endorheic basin
Zitao Wang, Jianping Wang, Jinjun Han
Ecological Indicators (2022) Vol. 142, pp. 109256-109256
Closed Access | Times Cited: 42
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 rainfall-induced landslide susceptibility in Artvin, Turkey using machine learning techniques
Halil Akıncı
Journal of African Earth Sciences (2022) Vol. 191, pp. 104535-104535
Closed Access | Times Cited: 41
Application of artificial neural networks and geographic information system to provide hazard susceptibility maps for rockfall failures
Yaser A. Nanehkaran, Li-Cai Zhu, Junde Chen, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 19
Closed Access | Times Cited: 41
Comparative Analysis of Tree-Based Ensemble Learning Algorithms for Landslide Susceptibility Mapping: A Case Study in Rize, Turkey
Ayşe Yavuz Özalp, Halil Akıncı, Mustafa Zeybek
Water (2023) Vol. 15, Iss. 14, pp. 2661-2661
Open Access | Times Cited: 29
Analysis of landslide susceptibility prediction accuracy with an event-based inventory: The 6 February 2023 Turkiye earthquakes
Gizem Karakaş, Erdinç Örsan Ünal, Sinem Çetınkaya, et al.
Soil Dynamics and Earthquake Engineering (2024) Vol. 178, pp. 108491-108491
Closed Access | Times Cited: 12
Refined landslide susceptibility mapping in township area using ensemble machine learning method under dataset replenishment strategy
Fancheng Zhao, Fasheng Miao, Yiping Wu, et al.
Gondwana Research (2024) Vol. 131, pp. 20-37
Closed Access | Times Cited: 11
Urban flood susceptibility mapping using frequency ratio and multiple decision tree-based machine learning models
Hemal Dey, Wanyun Shao, Hamid Moradkhani, et al.
Natural Hazards (2024) Vol. 120, Iss. 11, pp. 10365-10393
Closed Access | Times Cited: 11
Comparison of diverse machine learning algorithms for forest fire susceptibility mapping in Antalya, Türkiye
Hazan Alkan Akıncı, Halil Akıncı, Mustafa Zeybek
Advances in Space Research (2024) Vol. 74, Iss. 2, pp. 647-667
Closed Access | Times Cited: 10
Landslide susceptibility assessment using weights-of-evidence model and cluster analysis along the highways in the Hubei section of the Three Gorges Reservoir Area
Linfei Chen, Haixiang Guo, Peisong Gong, et al.
Computers & Geosciences (2021) Vol. 156, pp. 104899-104899
Closed Access | Times Cited: 56
Comprehensive performance assessment of landslide susceptibility mapping with MLP and random forest: a case study after Elazig earthquake (24 Jan 2020, Mw 6.8), Turkey
Gizem Karakaş, Sultan Kocaman, Candan Gökçeoğlu
Environmental Earth Sciences (2022) Vol. 81, Iss. 5
Closed Access | Times Cited: 29
A Hybrid Multi-Hazard Susceptibility Assessment Model for a Basin in Elazig Province, Türkiye
Gizem Karakaş, Sultan Kocaman, Candan Gökçeoğlu
International Journal of Disaster Risk Science (2023) Vol. 14, Iss. 2, pp. 326-341
Open Access | Times Cited: 22
Landslide susceptibility analysis using random forest model with SMOTE-ENN resampling algorithm
LU Ming-xi, Lea Tien Tay, Junita Mohamad–Saleh
Geomatics Natural Hazards and Risk (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 8
The potential evaluation of groundwater by integrating rank sum ratio (RSR) and machine learning algorithms in the Qaidam Basin
Zitao Wang, Jianping Wang, Dongmei Yu, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 23, pp. 63991-64005
Closed Access | Times Cited: 15
Spatial Mapping of Flood Susceptibility Using Decision Tree–Based Machine Learning Models for the Vembanad Lake System in Kerala, India
Parthasarathy Kulithalai Shiyam Sundar, Subrahmanya Kundapura
Journal of Water Resources Planning and Management (2023) Vol. 149, Iss. 10
Closed Access | Times Cited: 15
A multi-criteria landslide susceptibility mapping using deep multi-layer perceptron network: A case study of Srinagar-Rudraprayag region (India)
Devara Meghanadh, Vipin Kumar Maurya, Ashutosh Tiwari, et al.
Advances in Space Research (2021) Vol. 69, Iss. 4, pp. 1883-1893
Closed Access | Times Cited: 30
Suggestion for a new deterministic model coupled with machine learning techniques for landslide susceptibility mapping
Dae-Hong Min, Hyung‐Koo Yoon
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 29
Landslide susceptibility assessment using triangular fuzzy number-analytic hierarchy processing (TFN-AHP), contributing weight (CW) and random forest weighted frequency ratio (RF weighted FR) at the Pengyang county, Northwest China
Zhengjun Mao, Shuojie Shi, Huan Li, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 3
Closed Access | Times Cited: 22
Tracking the origin of trace metals in a watershed by identifying fingerprints of soils, landscape and river sediments
Farzaneh Derakhshan-Babaei, Fahimeh Mirchooli, Maziar Mohammadi, et al.
The Science of The Total Environment (2022) Vol. 835, pp. 155583-155583
Closed Access | Times Cited: 22
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