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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:

Slope-Unit Scale Landslide Susceptibility Mapping Based on the Random Forest Model in Deep Valley Areas
Hui Deng, Xiantan Wu, Wenjiang Zhang, et al.
Remote Sensing (2022) Vol. 14, Iss. 17, pp. 4245-4245
Open Access | Times Cited: 51

Showing 1-25 of 51 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: 61
GIS-based landslide susceptibility mapping using logistic regression, random forest and decision and regression tree models in Chattogram District, Bangladesh
Md. Sharafat Chowdhury, Md. Naimur Rahman, Md. Sujon Sheikh, et al.
Heliyon (2023) Vol. 10, Iss. 1, pp. e23424-e23424
Open Access | Times Cited: 33
Integrating Machine Learning Ensembles for Landslide Susceptibility Mapping in Northern Pakistan
Nafees Ali, Jian Chen, Xiaodong Fu, et al.
Remote Sensing (2024) Vol. 16, Iss. 6, pp. 988-988
Open Access | Times Cited: 17
Implementation of random forest, adaptive boosting, and gradient boosting decision trees algorithms for gully erosion susceptibility mapping using remote sensing and GIS
Hassan Ait Naceur, Hazem Ghassan Abdo, Brahim Igmoullan, et al.
Environmental Earth Sciences (2024) Vol. 83, Iss. 3
Closed Access | Times Cited: 9
Bivariate landslide susceptibility analysis for parts of Kumaon Himalayas: A case study of Nainital town and its surroundings, India
Anil Bhandari, H.A.R.S.H.A.R.A.J.L. WANKHADE
Natural Hazards Research (2025)
Open Access | Times Cited: 1
Interpretable machine learning models and decision-making mechanisms for landslide hazard assessment under different rainfall conditions
Haijia Wen, Fangyi Yan, Junhao Huang, et al.
Expert Systems with Applications (2025), pp. 126582-126582
Closed Access | Times Cited: 1
Potential impacts of future climate on the spatio-temporal variability of landslide susceptibility in Iran using machine learning algorithms and CMIP6 climate-change scenarios
Saeid Janizadeh, Sayed M. Bateni, Changhyun Jun, et al.
Gondwana Research (2023) Vol. 124, pp. 1-17
Closed Access | Times Cited: 21
Geospatial Modeling Based-Multi-Criteria Decision-Making for Flash Flood Susceptibility Zonation in an Arid Area
M. Shawky, Quazi K. Hassan
Remote Sensing (2023) Vol. 15, Iss. 10, pp. 2561-2561
Open Access | Times Cited: 19
Land subsidence susceptibility mapping in urban settlements using time-series PS-InSAR and random forest model
Fancheng Zhao, Fasheng Miao, Yiping Wu, et al.
Gondwana Research (2023) Vol. 125, pp. 406-424
Closed Access | Times Cited: 18
Refined Landslide Susceptibility Mapping by Integrating the SHAP-CatBoost Model and InSAR Observations: A Case Study of Lishui, Southern China
Zhaowei Yao, Meihong Chen, Jiewei Zhan, et al.
Applied Sciences (2023) Vol. 13, Iss. 23, pp. 12817-12817
Open Access | Times Cited: 18
Modeling rules of regional flash flood susceptibility prediction using different machine learning models
Yuguo Chen, Xinyi Zhang, Kejun Yang, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 16
Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods
Esteban Bravo-López, Tomás Fernández, Chester Sellers, et al.
Land (2023) Vol. 12, Iss. 6, pp. 1135-1135
Open Access | Times Cited: 15
Enhancing landslide management with hyper-tuned machine learning and deep learning models: Predicting susceptibility and analyzing sensitivity and uncertainty
Mohammed Dahim, Saeed Alqadhi, Javed Mallick
Frontiers in Ecology and Evolution (2023) Vol. 11
Open Access | Times Cited: 14
Assessing landslide susceptibility based on the random forest model and multi-source heterogeneous data
Mengxia Li, Haiying Wang, Jinlong Chen, et al.
Ecological Indicators (2024) Vol. 158, pp. 111600-111600
Open Access | Times Cited: 6
KNN-GCN: A Deep Learning Approach for Slope-Unit-Based Landslide Susceptibility Mapping Incorporating Spatial Correlations
Ding Xia, Huiming Tang, Thomas Glade, et al.
Mathematical Geosciences (2024) Vol. 56, Iss. 5, pp. 1011-1039
Closed Access | Times Cited: 6
Application of machine learning in the assessment of landslide susceptibility: A case study of mountainous eastern Mediterranean region, Syria
Hazem Ghassan Abdo, Sahar Mohammed Richi
Journal of King Saud University - Science (2024) Vol. 36, Iss. 5, pp. 103174-103174
Open Access | Times Cited: 6
Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm: A case study of Baihetan Reservoir Area
Junqi Guo, Wenfei Xi, Zhiquan Yang, et al.
Journal of Mountain Science (2024) Vol. 21, Iss. 3, pp. 952-972
Closed Access | Times Cited: 5
Landslide susceptibility evaluation based on active deformation and graph convolutional network algorithm
Xianmin Wang, Aiheng Du, Fengchang Hu, et al.
Frontiers in Earth Science (2023) Vol. 11
Open Access | Times Cited: 13
Quantifying soil erosion and influential factors in Guwahati's urban watershed using statistical analysis, machine and deep learning
Ishita Afreen Ahmed, Swapan Talukdar, Mirza Razi Imam Baig, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 33, pp. 101088-101088
Closed Access | Times Cited: 13
Insights into spatial differential characteristics of landslide susceptibility from sub-region to whole-region cased by northeast Chongqing, China
Rui Liu, Yuekai Ding, Deliang Sun, et al.
Geomatics Natural Hazards and Risk (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 11
An innovative method for landslide susceptibility mapping supported by fractal theory, GeoDetector, and random forest: a case study in Sichuan Province, SW China
Zhuo Chen, Danqing Song, Lihu Dong
Natural Hazards (2023) Vol. 118, Iss. 3, pp. 2543-2568
Open Access | Times Cited: 11
Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning
Xianmin Wang, Xinlong Zhang, Jia Bi, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 21, pp. 14241-14241
Open Access | Times Cited: 18
Integrated deep learning with explainable artificial intelligence for enhanced landslide management
Saeed Alqadhi, Javed Mallick, Meshel Q. Alkahtani
Natural Hazards (2023) Vol. 120, Iss. 2, pp. 1343-1365
Closed Access | Times Cited: 10
Geomorphological and Geological Characteristics Slope Unit: Advancing Township-Scale Landslide Susceptibility Assessment Strategies
Gang Chen, Taorui Zeng, Dongsheng Liu, et al.
Land (2025) Vol. 14, Iss. 2, pp. 355-355
Open Access
Slope unit-based comprehensive geohazard susceptibility assessment: SHAP interpretability and local InSAR deformation analysis
Peng Wang, Hongwei Deng, Jielin Li, et al.
Advances in Space Research (2025)
Closed Access
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