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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:

Deep neural networks for global wildfire susceptibility modelling
Guoli Zhang, Ming Wang, Kai Liu
Ecological Indicators (2021) Vol. 127, pp. 107735-107735
Open Access | Times Cited: 94

Showing 1-25 of 94 citing articles:

Machine learning based wildfire susceptibility mapping using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey
Muzaffer Can İban, Aliihsan Şekertekin
Ecological Informatics (2022) Vol. 69, pp. 101647-101647
Closed Access | Times Cited: 112
Wildfire Danger Prediction and Understanding With Deep Learning
Spyros Kondylatos, Ioannis Prapas, Michele Ronco, et al.
Geophysical Research Letters (2022) Vol. 49, Iss. 17
Open Access | Times Cited: 90
Explainable artificial intelligence in disaster risk management: Achievements and prospective futures
Saman Ghaffarian, Firouzeh Taghikhah, Holger R. Maier
International Journal of Disaster Risk Reduction (2023) Vol. 98, pp. 104123-104123
Open Access | Times Cited: 61
Prediction of forest fire susceptibility applying machine and deep learning algorithms for conservation priorities of forest resources
Soumik Saha, Biswajit Bera, Pravat Kumar Shit, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 29, pp. 100917-100917
Closed Access | Times Cited: 60
Machine learning based forest fire susceptibility assessment of Manavgat district (Antalya), Turkey
Hazan Alkan Akıncı, Halil Akıncı
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 397-414
Closed Access | Times Cited: 53
Deep Learning Approaches for Wildland Fires Using Satellite Remote Sensing Data: Detection, Mapping, and Prediction
Rafik Ghali, Moulay A. Akhloufi
Fire (2023) Vol. 6, Iss. 5, pp. 192-192
Open Access | Times Cited: 46
Leveraging the power of internet of things and artificial intelligence in forest fire prevention, detection, and restoration: A comprehensive survey
Sofia Giannakidou, Panagiotis Radoglou-Grammatikis, Θωμάς Λάγκας, et al.
Internet of Things (2024) Vol. 26, pp. 101171-101171
Open Access | Times Cited: 24
Artificial intelligence for modeling and understanding extreme weather and climate events
Gustau Camps‐Valls, Miguel‐Ángel Fernández‐Torres, Kai-Hendrik Cohrs, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 3
A deep learning ensemble model for wildfire susceptibility mapping
Alexandra Bjånes, Rodrigo De la Fuente, Pablo Mena
Ecological Informatics (2021) Vol. 65, pp. 101397-101397
Closed Access | Times Cited: 91
Artificial neural network approaches for disaster management: A literature review
Sreeparna Guha, Rabin K. Jana, Manas Kumar Sanyal
International Journal of Disaster Risk Reduction (2022) Vol. 81, pp. 103276-103276
Closed Access | Times Cited: 58
Burnt-Net: Wildfire burned area mapping with single post-fire Sentinel-2 data and deep learning morphological neural network
Seyd Teymoor Seydi, Mahdi Hasanlou, Jocelyn Chanussot
Ecological Indicators (2022) Vol. 140, pp. 108999-108999
Open Access | Times Cited: 52
Defining Wildfire Susceptibility Maps in Italy for Understanding Seasonal Wildfire Regimes at the National Level
Andrea Trucchia, Giorgio Meschi, Paolo Fiorucci, et al.
Fire (2022) Vol. 5, Iss. 1, pp. 30-30
Open Access | Times Cited: 48
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
Forest fire pattern and vulnerability mapping using deep learning in Nepal
Bhogendra Mishra, Saroj Panthi, Shobha Poudel, et al.
Fire Ecology (2023) Vol. 19, Iss. 1
Open Access | Times Cited: 40
Forest-Fire-Risk Prediction Based on Random Forest and Backpropagation Neural Network of Heihe Area in Heilongjiang Province, China
Chao Gao, Honglei Lin, Haiqing Hu
Forests (2023) Vol. 14, Iss. 2, pp. 170-170
Open Access | Times Cited: 25
Integration of a Deep‐Learning‐Based Fire Model Into a Global Land Surface Model
Rackhun Son, Tobias Stacke, Veronika Gayler, et al.
Journal of Advances in Modeling Earth Systems (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 15
Classification Assessment Tool: A program to measure the uncertainty of classification models in terms of class-level metrics
Szilárd Szabó, I. J. Holb, Vanda Éva Molnár, et al.
Applied Soft Computing (2024) Vol. 155, pp. 111468-111468
Open Access | Times Cited: 10
Comparison of diverse machine learning algorithms for forest fire susceptibility mapping in Antalya, Türkiye
Hazan Alkan Akıncı, Halil Akıncı, Mustafa Zeybek
Advances in Space Research (2024) Vol. 74, Iss. 2, pp. 647-667
Closed Access | Times Cited: 10
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
Sub-hourly forecasting of fire potential using machine learning on time series of surface weather variables
Alberto Ardid, Andrés Valencia, Anthony Power, et al.
International Journal of Wildland Fire (2025) Vol. 34, Iss. 1
Closed Access | Times Cited: 1
Permafrost degradation induced thaw settlement susceptibility research and potential risk analysis in the Qinghai-Tibet Plateau
Renwei Li, Mingyi Zhang, Pavel Konstantinov, et al.
CATENA (2022) Vol. 214, pp. 106239-106239
Closed Access | Times Cited: 31
Assessing the predictive efficacy of six machine learning algorithms for the susceptibility of Indian forests to fire
Laxmi Kant Sharma, Rajit Gupta, Naureen Fatima
International Journal of Wildland Fire (2022) Vol. 31, Iss. 8, pp. 735-758
Open Access | Times Cited: 30
Artificial neural networks for assessing forest fire susceptibility in Türkiye
Omer Kantarcioglu, Sultan Kocaman, Konrad Schindler
Ecological Informatics (2023) Vol. 75, pp. 102034-102034
Closed Access | Times Cited: 22
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
Improving the prediction of wildfire susceptibility on Hawaiʻi Island, Hawaiʻi, using explainable hybrid machine learning models
Trang Thi Kieu Tran, Saeid Janizadeh, Sayed M. Bateni, et al.
Journal of Environmental Management (2023) Vol. 351, pp. 119724-119724
Closed Access | Times Cited: 18
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