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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:

Predicting landslide susceptibility and risks using GIS-based machine learning simulations, case of upper Nyabarongo catchment
Jean Baptiste Nsengiyumva, Roberto Valentino
Geomatics Natural Hazards and Risk (2020) Vol. 11, Iss. 1, pp. 1250-1277
Open Access | Times Cited: 73

Showing 1-25 of 73 citing articles:

Machine Learning in Disaster Management: Recent Developments in Methods and Applications
Vasileios Linardos, Maria Drakaki, Panagiotis Tzionas, et al.
Machine Learning and Knowledge Extraction (2022) Vol. 4, Iss. 2, pp. 446-473
Open Access | Times Cited: 148
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
Slow-moving landslide risk assessment combining Machine Learning and InSAR techniques
Alessandro Novellino, Mara Cesarano, Piergiulio Cappelletti, et al.
CATENA (2021) Vol. 203, pp. 105317-105317
Open Access | Times Cited: 113
Soil erosion susceptibility mapping using ensemble machine learning models: A case study of upper Congo river sub-basin
Luc Cimusa Kulimushi, Janvier Bashagaluke, Pankaj Prasad, et al.
CATENA (2022) Vol. 222, pp. 106858-106858
Closed Access | Times Cited: 44
Landslide susceptibility mapping in the Loess Plateau of northwest China using three data-driven techniques-a case study from middle Yellow River catchment
Zizheng Guo, Bixia Tian, Guangming Li, et al.
Frontiers in Earth Science (2023) Vol. 10
Open Access | Times Cited: 29
GIS-based landslide susceptibility mapping of Western Rwanda: an integrated artificial neural network, frequency ratio, and Shannon entropy approach
Vincent E. Nwazelibe, Johnbosco C. Egbueri, Chinanu O. Unigwe, et al.
Environmental Earth Sciences (2023) Vol. 82, Iss. 19
Closed Access | Times Cited: 26
Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia
Javed Mallick, Swapan Talukdar, Majed Alsubih, et al.
Geocarto International (2021) Vol. 37, Iss. 15, pp. 4361-4389
Closed Access | Times Cited: 44
Combining Machine Learning (ML) and Participatory Rural Appraisal (PRA) for Disaster Risk Preparedness (DRP): Evidence from the Poorest Region of Luzon, Philippines
Emmanuel A. Onsay, Jomar F. Rabajante
International Journal of Disaster Risk Reduction (2024) Vol. 112, pp. 104809-104809
Closed Access | Times Cited: 7
Erosion risk assessment through prioritization of sub-watersheds in Nyabarongo river catchment, Rwanda
Luc Cimusa Kulimushi, Pandurang Choudhari, Abias Maniragaba, et al.
Environmental Challenges (2021) Vol. 5, pp. 100260-100260
Open Access | Times Cited: 35
Application of Bagging, Boosting and Stacking Ensemble and EasyEnsemble Methods for Landslide Susceptibility Mapping in the Three Gorges Reservoir Area of China
Xueling Wu, Junyang Wang
International Journal of Environmental Research and Public Health (2023) Vol. 20, Iss. 6, pp. 4977-4977
Open Access | Times Cited: 16
Catastropheguard
Jayasudha Subburaj, M. Kavitha, P. Keerthana, et al.
Advances in computational intelligence and robotics book series (2024), pp. 28-55
Closed Access | Times Cited: 5
Landslide hazard zonation and evaluation around Debre Markos town, NW Ethiopia—a GIS-based bivariate statistical approach
Dawit Asmare
Scientific African (2022) Vol. 15, pp. e01129-e01129
Open Access | Times Cited: 21
Adaptive neuro fuzzy inference system (ANFIS) machine learning algorithm for assessing environmental and socio-economic vulnerability to drought: a study in Godavari middle sub-basin, India
Md Masroor, Seyed Vahid Razavi-Termeh, Md Hibjur Rahaman, et al.
Stochastic Environmental Research and Risk Assessment (2022) Vol. 37, Iss. 1, pp. 233-259
Closed Access | Times Cited: 21
Modelling the rainfall threshold for shallow landslides considering the landslide predisposing factors in Portugal
Caio Vidaurre Nassif Villaça, Pedro Pinto Santos, José Luı́s Zêzere
Landslides (2024) Vol. 21, Iss. 9, pp. 2119-2133
Open Access | Times Cited: 4
GIS-based and Naïve Bayes for nitrogen soil mapping in Lendah, Indonesia
Anton Yudhana, Dedy Sulistyo, Ilham Mufandi
Sensing and Bio-Sensing Research (2021) Vol. 33, pp. 100435-100435
Open Access | Times Cited: 27
A CA–Markov-Based Simulation and Prediction of LULC Changes over the Nyabarongo River Basin, Rwanda
Aboubakar Gasirabo, Xi Chen, Baligira R. Hamad, et al.
Land (2023) Vol. 12, Iss. 9, pp. 1788-1788
Open Access | Times Cited: 10
Beyond boundaries: AI-optimized global landslide susceptibility mapping
Mahdi Panahi, Fatemeh Rezaie, Khabat Khosravi, et al.
Geomatics Natural Hazards and Risk (2025) Vol. 16, Iss. 1
Open Access
Rainfall-Induced Geological Hazard Susceptibility Assessment in the Henan Section of the Yellow River Basin: Multi-Model Approaches Supporting Disaster Mitigation and Sustainable Development
Y. Zhang, Hui Ci, Hui Yang, et al.
Sustainability (2025) Vol. 17, Iss. 10, pp. 4348-4348
Open Access
A comparative evaluation of machine learning algorithms and an improved optimal model for landslide susceptibility: a case study
Yue Liu, Peihua Xu, Chen Cao, et al.
Geomatics Natural Hazards and Risk (2021) Vol. 12, Iss. 1, pp. 1973-2001
Open Access | Times Cited: 21
Utilization of frequency ratio method for the production of landslide susceptibility maps: Karaburun Peninsula case, Turkey
Muhittin Ozan Karaman, Saye Nihan Çabuk, Emrah Pekkan
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 60, pp. 91285-91305
Closed Access | Times Cited: 15
Mapping Post-Earthquake Landslide Susceptibility Using U-Net, VGG-16, VGG-19, and Metaheuristic Algorithms
Mahyat Shafapour Tehrany, Fatemeh Rezaie, Changhyun Jun, et al.
Remote Sensing (2023) Vol. 15, Iss. 18, pp. 4501-4501
Open Access | Times Cited: 9
Regional-scale landslide modeling using machine learning and GIS: a case study for Idukki district, Kerala, India
M. Dhanya, G. Nithya, S. Sreekala, et al.
Natural Hazards (2024) Vol. 120, Iss. 11, pp. 9935-9956
Closed Access | Times Cited: 3
The use of hybrid machine learning models for improving the GALDIT model for coastal aquifer vulnerability mapping
Mojgan Bordbar, Khabat Khosravi, Dorina Murgulet, et al.
Environmental Earth Sciences (2022) Vol. 81, Iss. 15
Closed Access | Times Cited: 14
Landslide susceptibility prediction mapping with advanced ensemble models: Son La province, Vietnam
Quynh Duy Bui, Hang Ha, Dong Thanh Khuc, et al.
Natural Hazards (2022)
Open Access | Times Cited: 14
Potential of satellite-derived hydro-meteorological information for landslide initiation thresholds in Rwanda
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, et al.
Natural hazards and earth system sciences (2022) Vol. 22, Iss. 11, pp. 3641-3661
Open Access | Times Cited: 11
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