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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:

Global Wildfire Susceptibility Mapping Based on Machine Learning Models
Assaf Shmuel, Eyal Heifetz
Forests (2022) Vol. 13, Iss. 7, pp. 1050-1050
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

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: 66
Integrating geospatial, remote sensing, and machine learning for climate-induced forest fire susceptibility mapping in Similipal Tiger Reserve, India
Chiranjit Singha, Kishore Chandra Swain, Armin Moghimi, et al.
Forest Ecology and Management (2024) Vol. 555, pp. 121729-121729
Open Access | Times Cited: 27
Assessment of Wildfire Susceptibility and Wildfire Threats to Ecological Environment and Urban Development Based on GIS and Multi-Source Data: A Case Study of Guilin, China
Weiting Yue, Chao Ren, Yueji Liang, et al.
Remote Sensing (2023) Vol. 15, Iss. 10, pp. 2659-2659
Open Access | Times Cited: 27
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 risk assessment model optimized by stochastic average gradient descent
Zexin Fu, Adu Gong, Jia Wan, et al.
Ecological Indicators (2025) Vol. 170, pp. 113006-113006
Open Access | Times Cited: 1
Assessment of forest fire vulnerability prediction in Indonesia: Seasonal variability analysis using machine learning techniques
Wulan Salle Karurung, Kangjae Lee, W. K. Lee
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 138, pp. 104435-104435
Closed Access | Times Cited: 1
Review of wildfire modeling considering effects on land surfaces
Dani Or, Eden Furtak‐Cole, Markus Berli, et al.
Earth-Science Reviews (2023) Vol. 245, pp. 104569-104569
Closed Access | Times Cited: 20
Creation of wildfire susceptibility maps in the Mediterranean Region (Turkey) using convolutional neural networks and multilayer perceptron techniques
Mehmet İsmail Gürsoy, Osman Orhan, Senem Tekin
Forest Ecology and Management (2023) Vol. 538, pp. 121006-121006
Closed Access | Times Cited: 18
Wildfire susceptibility mapping by incorporating damage proxy maps, differenced normalized burn Ratio, and deep learning algorithms based on sentinel-1/2 data: a case study on Maui Island, Hawaii
Suci Ramayanti, Bong-Chan Kim, Sungjae Park, et al.
GIScience & Remote Sensing (2024) Vol. 61, Iss. 1
Open Access | Times Cited: 8
Predicting forest fire probability in Similipal Biosphere Reserve (India) using Sentinel-2 MSI data and machine learning
Rajkumar Guria, Manoranjan Mishra, Richarde Marques da Silva, et al.
Remote Sensing Applications Society and Environment (2024) Vol. 36, pp. 101311-101311
Closed Access | Times Cited: 7
Global Wildfire Danger Predictions Based on Deep Learning Taking into Account Static and Dynamic Variables
Yuheng Ji, Dan Wang, Qingliang Li, et al.
Forests (2024) Vol. 15, Iss. 1, pp. 216-216
Open Access | Times Cited: 6
Can Ensemble Techniques and Large-Scale Fire Datasets Improve Predictions of Forest Fire Probability Due to Climate Change?—A Case Study from the Republic of Korea
Hyeon Kwon Ahn, Huicheul Jung, Chul-Hee Lim
Forests (2024) Vol. 15, Iss. 3, pp. 503-503
Open Access | Times Cited: 6
Synergetic use of geospatial and machine learning techniques in modelling landslide susceptibility in parts of Shimla to Kinnaur National Highway, Himachal Pradesh
Rahul Deb Das, Shovan Lal Chattoraj, Mohit Singh, et al.
Modeling Earth Systems and Environment (2024) Vol. 10, Iss. 3, pp. 4163-4183
Closed Access | Times Cited: 6
Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii
Saeid Janizadeh, Trang Thi Kieu Tran, Sayed M. Bateni, et al.
Expert Systems with Applications (2024) Vol. 258, pp. 124963-124963
Closed Access | Times Cited: 4
Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
İrem Üstek, Miguel Arana‐Catania, Alexander Farr, et al.
Earth and Space Science (2024) Vol. 11, Iss. 11
Open Access | Times Cited: 4
Developing novel machine-learning-based fire weather indices
Assaf Shmuel, Eyal Heifetz
Machine Learning Science and Technology (2023) Vol. 4, Iss. 1, pp. 015029-015029
Open Access | Times Cited: 11
Improving wildland fire spread prediction using deep U-Nets
Fadoua Khennou, Moulay A. Akhloufi
Science of Remote Sensing (2023) Vol. 8, pp. 100101-100101
Open Access | Times Cited: 10
Assessing Wildfire Susceptibility and Spatial Patterns in Diverse Forest Ecosystems Across China: An Integrated Geospatial Analysis
Yuping Tian, Zechuan Wu, Shuai Cui, et al.
Journal of Cleaner Production (2025), pp. 144800-144800
Closed Access
Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models
Assaf Shmuel, Teddy Lazebnik, Oren Glickman, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Modeling the Spatial Distribution of Wildfire Risk in Chile Under Current and Future Climate Scenarios
John Gajardo, Marco A. Yáñez, Robert S. Padilla, et al.
Fire (2025) Vol. 8, Iss. 3, pp. 113-113
Open Access
Exploration of geo-spatial data and machine learning algorithms for robust wildfire occurrence prediction
Svetlana Illarionova, Dmitrii Shadrin, Fedor Gubanov, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Advancements in Artificial Intelligence Applications for Forest Fire Prediction
Hui Liu, Lifu Shu, Xiaodong Liu, et al.
Forests (2025) Vol. 16, Iss. 4, pp. 704-704
Open Access
A Comprehensive Framework for Forest Restoration after Forest Fires in Theory and Practice: A Systematic Review
Rahaf Alayan, Brian Rotich, Zoltán Lakner
Forests (2022) Vol. 13, Iss. 9, pp. 1354-1354
Open Access | Times Cited: 15
Improved Lithological Map of Large Complex Semi-Arid Regions Using Spectral and Textural Datasets within Google Earth Engine and Fused Machine Learning Multi-Classifiers
Imane Serbouti, Mohammed Raji, Mustapha Hakdaoui, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5498-5498
Open Access | Times Cited: 15
A Machine-Learning Approach to Predicting Daily Wildfire Expansion Rate
Assaf Shmuel, Eyal Heifetz
Fire (2023) Vol. 6, Iss. 8, pp. 319-319
Open Access | Times Cited: 9
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