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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:

Landslide Susceptibility Mapping: Machine and Ensemble Learning Based on Remote Sensing Big Data
Bahareh Kalantar, Naonori Ueda, Vahideh Saeidi, et al.
Remote Sensing (2020) Vol. 12, Iss. 11, pp. 1737-1737
Open Access | Times Cited: 130

Showing 26-50 of 130 citing articles:

A Multi-Criteria Decision Analysis (MCDA) Approach for Landslide Susceptibility Mapping of a Part of Darjeeling District in North-East Himalaya, India
Abhik Saha, Vasanta Govind Kumar Villuri, Ashutosh Bhardwaj, et al.
Applied Sciences (2023) Vol. 13, Iss. 8, pp. 5062-5062
Open Access | Times Cited: 25
Leveraging GIS-based AHP, remote sensing, and machine learning for susceptibility assessment of different flood types in peshawar, Pakistan
Muhammad Tayyab, Muhammad Hussain, Jiquan Zhang, et al.
Journal of Environmental Management (2024) Vol. 371, pp. 123094-123094
Closed Access | Times Cited: 9
Modeling the effects of climate change scenarios on the potential distribution of Vespa crabro Linnaeus, 1758 (Hymenoptera: Vespidae) in a Mediterranean biodiversity hotspot
Erika Bazzato, Arturo Cocco, Emanuele Salaris, et al.
Ecological Informatics (2025), pp. 103006-103006
Open Access | Times Cited: 1
Assessing Wildfire Susceptibility in Iran: Leveraging Machine Learning for Geospatial Analysis of Climatic and Anthropogenic Factors
Ehsan Masoudian, Ali Mirzaei, Hossein Bagheri
Trees Forests and People (2025), pp. 100774-100774
Open Access | Times Cited: 1
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
Integrated Machine Learning Approaches for Landslide Susceptibility Mapping Along the Pakistan–China Karakoram Highway
Mohib Ullah, Haijun Qiu, Wenchao Huangfu, et al.
Land (2025) Vol. 14, Iss. 1, pp. 172-172
Open Access | Times Cited: 1
An integrated hybrid deep learning data driven approaches for spatiotemporal mapping of land susceptibility to salt/dust emissions
Bakhtiar Feizizadeh, Peyman Yariyan, Murat Yakar, et al.
Advances in Space Research (2025)
Closed Access | Times Cited: 1
Landslide Mapping Using Two Main Deep-Learning Convolution Neural Network Streams Combined by the Dempster–Shafer Model
Omid Ghorbanzadeh, Sansar Raj Meena, Hejar Shahabi, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2020) Vol. 14, pp. 452-463
Open Access | Times Cited: 56
Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region
Yunzhi Chen, Wei Chen, Saeid Janizadeh, et al.
Geocarto International (2021) Vol. 37, Iss. 16, pp. 4628-4654
Closed Access | Times Cited: 48
Global sea surface salinity via the synergistic use of SMAP satellite and HYCOM data based on machine learning
Eunna Jang, Young Jun Kim, Jungho Im, et al.
Remote Sensing of Environment (2022) Vol. 273, pp. 112980-112980
Closed Access | Times Cited: 36
Understanding land degradation induced by gully erosion from the perspective of different geoenvironmental factors
Abolfazl Jaafari, Saeid Janizadeh, Hazem Ghassan Abdo, et al.
Journal of Environmental Management (2022) Vol. 315, pp. 115181-115181
Closed Access | Times Cited: 35
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: 33
Evaluation of debris flow and landslide hazards using ensemble framework of Bayesian- and tree-based models
Subodh Chandra Pal, Rabin Chakrabortty, Asish Saha, et al.
Bulletin of Engineering Geology and the Environment (2022) Vol. 81, Iss. 1
Closed Access | Times Cited: 30
Implementation of free and open-source semi-automatic feature engineering tool in landslide susceptibility mapping using the machine-learning algorithms RF, SVM, and XGBoost
Emrehan Kutluğ Şahin
Stochastic Environmental Research and Risk Assessment (2022) Vol. 37, Iss. 3, pp. 1067-1092
Closed Access | Times Cited: 30
A New Approach to Spatial Landslide Susceptibility Prediction in Karst Mining Areas Based on Explainable Artificial Intelligence
Haoran Fang, Yun Shao, Chou Xie, et al.
Sustainability (2023) Vol. 15, Iss. 4, pp. 3094-3094
Open Access | Times Cited: 23
Does machine learning adequately predict earthquake induced landslides?
Ajaya Pyakurel, Bhim Kumar Dahal, Dipendra Gautam
Soil Dynamics and Earthquake Engineering (2023) Vol. 171, pp. 107994-107994
Closed Access | Times Cited: 23
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
Development and assessment of a novel hybrid machine learning-based landslide susceptibility mapping model in the Darjeeling Himalayas
Abhik Saha, Vasanta Govind Kumar Villuri, Ashutosh Bhardwaj
Stochastic Environmental Research and Risk Assessment (2023)
Closed Access | Times Cited: 19
Landslide susceptibility mapping in Badakhshan province, Afghanistan: a comparative study of machine learning algorithms
Abdul Baser Qasimi, Vahid Isazade, Enayatullah Enayat, et al.
Geocarto International (2023) Vol. 38, Iss. 1
Open Access | Times Cited: 17
Monitoring Slope Movement and Soil Hydrologic Behavior Using IoT and AI Technologies: A Systematic Review
Md. Jobair Bin Alam, Luis Salgado Manzano, Rahul Debnath, et al.
Hydrology (2024) Vol. 11, Iss. 8, pp. 111-111
Open Access | Times Cited: 7
Novel Credal Decision Tree-Based Ensemble Approaches for Predicting the Landslide Susceptibility
Alireza Arabameri, Ebrahim Karimi Sangchini, Subodh Chandra Pal, et al.
Remote Sensing (2020) Vol. 12, Iss. 20, pp. 3389-3389
Open Access | Times Cited: 49
Uncertainties Analysis of Collapse Susceptibility Prediction Based on Remote Sensing and GIS: Influences of Different Data-Based Models and Connections between Collapses and Environmental Factors
Wenbin Li, Xuanmei Fan, Faming Huang, et al.
Remote Sensing (2020) Vol. 12, Iss. 24, pp. 4134-4134
Open Access | Times Cited: 47
Active-Learning Approaches for Landslide Mapping Using Support Vector Machines
Zhihao Wang, Alexander Brenning
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2588-2588
Open Access | Times Cited: 38
Comparison of Machine Learning Methods for Potential Active Landslide Hazards Identification with Multi-Source Data
Xiangxiang Zheng, Guojin He, Shanshan Wang, et al.
ISPRS International Journal of Geo-Information (2021) Vol. 10, Iss. 4, pp. 253-253
Open Access | Times Cited: 35
Multi-hazards (landslides, floods, and gully erosion) modeling and mapping using machine learning algorithms
Ahmed M. Youssef, Ali M. Mahdi, Mohamed M. Al-Katheri, et al.
Journal of African Earth Sciences (2022) Vol. 197, pp. 104788-104788
Closed Access | Times Cited: 28

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