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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:

A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland
Wisdom M. Dlamini
Environmental Modelling & Software (2009) Vol. 25, Iss. 2, pp. 199-208
Closed Access | Times Cited: 169

Showing 1-25 of 169 citing articles:

Bayesian networks in environmental modelling
Pedro A. Aguilera, Antonio Fernández, Rosa Fernández, et al.
Environmental Modelling & Software (2011) Vol. 26, Iss. 12, pp. 1376-1388
Closed Access | Times Cited: 605
Good practice in Bayesian network modelling
Serena H. Chen, Carmel Pollino
Environmental Modelling & Software (2012) Vol. 37, pp. 134-145
Closed Access | Times Cited: 590
A review of machine learning applications in wildfire science and management
Piyush Jain, Sean C. P. Coogan, Sriram Ganapathi Subramanian, et al.
Environmental Reviews (2020) Vol. 28, Iss. 4, pp. 478-505
Open Access | Times Cited: 550
A review of Bayesian belief networks in ecosystem service modelling
Dries Landuyt, Steven Broekx, Rob D'hondt, et al.
Environmental Modelling & Software (2013) Vol. 46, pp. 1-11
Closed Access | Times Cited: 345
Metrics for evaluating performance and uncertainty of Bayesian network models
Bruce G. Marcot
Ecological Modelling (2012) Vol. 230, pp. 50-62
Closed Access | Times Cited: 316
Advances in Bayesian network modelling: Integration of modelling technologies
Bruce G. Marcot, Trent D. Penman
Environmental Modelling & Software (2018) Vol. 111, pp. 386-393
Closed Access | Times Cited: 313
Uncertainty and risk in wildland fire management: A review
Matthew P. Thompson, Dave Calkin
Journal of Environmental Management (2011) Vol. 92, Iss. 8, pp. 1895-1909
Closed Access | Times Cited: 292
Ten years of global burned area products from spaceborne remote sensing—A review: Analysis of user needs and recommendations for future developments
Florent Mouillot, Martin G. Schultz, Chao Yue, et al.
International Journal of Applied Earth Observation and Geoinformation (2013) Vol. 26, pp. 64-79
Open Access | Times Cited: 260
A big data urban growth simulation at a national scale: Configuring the GIS and neural network based Land Transformation Model to run in a High Performance Computing (HPC) environment
Bryan C. Pijanowski, Amin Tayyebi, Jarrod Doucette, et al.
Environmental Modelling & Software (2013) Vol. 51, pp. 250-268
Closed Access | Times Cited: 255
Constructing a Bayesian network model for improving safety behavior of employees at workplaces
Iraj Mohammadfam, Fakhradin Ghasemi, Omid Kalatpour, et al.
Applied Ergonomics (2016) Vol. 58, pp. 35-47
Closed Access | Times Cited: 194
A Survey of Machine Learning Algorithms Based Forest Fires Prediction and Detection Systems
Faroudja Abid
Fire Technology (2020) Vol. 57, Iss. 2, pp. 559-590
Closed Access | Times Cited: 156
Recyclable waste image recognition based on deep learning
Qiang Zhang, Xujuan Zhang, Xiaojun Mu, et al.
Resources Conservation and Recycling (2021) Vol. 171, pp. 105636-105636
Closed Access | Times Cited: 122
A Brief Review of Machine Learning Algorithms in Forest Fires Science
Ramez Alkhatib, Wahib Sahwan, Anas Alkhatieb, et al.
Applied Sciences (2023) Vol. 13, Iss. 14, pp. 8275-8275
Open Access | Times Cited: 65
Human-caused fire occurrence modelling in perspective: a review
Sergi Costafreda-Aumedes, Carles Comas, Cristina Vega‐García
International Journal of Wildland Fire (2017) Vol. 26, Iss. 12, pp. 983-983
Open Access | Times Cited: 150
Predicting fire occurrence patterns with logistic regression in Heilongjiang Province, China
Yu Chang, Zhiliang Zhu, Rencang Bu, et al.
Landscape Ecology (2013) Vol. 28, Iss. 10, pp. 1989-2004
Closed Access | Times Cited: 136
Recommendations for using the relative operating characteristic (ROC)
Robert Gilmore Pontius, Benoît Parmentier
Landscape Ecology (2014) Vol. 29, Iss. 3, pp. 367-382
Closed Access | Times Cited: 115
A spatial assessment of urban waterlogging risk based on a Weighted Naïve Bayes classifier
Xianzhe Tang, Yuqin Shu, Yanqing Lian, et al.
The Science of The Total Environment (2018) Vol. 630, pp. 264-274
Closed Access | Times Cited: 113
A Sybil attack detection scheme for a forest wildfire monitoring application
Mian Ahmad Jan, Priyadarsi Nanda, Xiangjian He, et al.
Future Generation Computer Systems (2016) Vol. 80, pp. 613-626
Open Access | Times Cited: 112
Flood susceptibility assessment based on a novel random Naïve Bayes method: A comparison between different factor discretization methods
Xianzhe Tang, Jiufeng Li, Minnan Liu, et al.
CATENA (2020) Vol. 190, pp. 104536-104536
Closed Access | Times Cited: 101
Forest-Fire Response System Using Deep-Learning-Based Approaches With CCTV Images and Weather Data
Dai Quoc Tran, Minsoo Park, Yuntae Jeon, et al.
IEEE Access (2022) Vol. 10, pp. 66061-66071
Open Access | Times Cited: 47
Comparing machine learning algorithms to predict vegetation fire detections in Pakistan
Fahad Shahzad, Kaleem Mehmood, Khadim Hussain, et al.
Fire Ecology (2024) Vol. 20, Iss. 1
Open Access | Times Cited: 15
Forest Fire Prediction: A Spatial Machine Learning and Neural Network Approach
Sanjeev Sharma, Puskar Khanal
Fire (2024) Vol. 7, Iss. 6, pp. 205-205
Open Access | Times Cited: 9
A Review on Current Modelling Techniques for Predicting Forest Fires
Piyush Pandey, Avinash Pratap Gupta
Advances in geographical and environmental sciences (2025), pp. 269-304
Closed Access | Times Cited: 1
Assessing spatial likelihood of flooding hazard using naïve Bayes and GIS: a case study in Bowen Basin, Australia
Rui Liu, Yun Chen, Jianping Wu, et al.
Stochastic Environmental Research and Risk Assessment (2015) Vol. 30, Iss. 6, pp. 1575-1590
Closed Access | Times Cited: 81
Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks
Jens Frayer, Zhanli Sun, Daniel Müller, et al.
Land Use Policy (2013) Vol. 36, pp. 248-258
Closed Access | Times Cited: 72
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