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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:

Prediction of forest fires occurrences with area-level Poisson mixed models
Miguel Boubeta, María José Lombardía, Manuel Francisco Marey Pérez, et al.
Journal of Environmental Management (2015) Vol. 154, pp. 151-158
Closed Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

Forest Fire Occurrence Prediction in China Based on Machine Learning Methods
Yongqi Pang, Yudong Li, Zhongke Feng, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5546-5546
Open Access | Times Cited: 81
Advancing forest fire prediction: A multi-layer stacking ensemble model approach
Fahad Shahzad, Kaleem Mehmood, Shoaib Ahmad Anees, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 3
Closed Access | Times Cited: 2
Wildfire spatial pattern analysis in the Zagros Mountains, Iran: A comparative study of decision tree based classifiers
Abolfazl Jaafari, Eric K. Zenner, Binh Thai Pham
Ecological Informatics (2017) Vol. 43, pp. 200-211
Closed Access | Times Cited: 160
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
Mapping China’s Forest Fire Risks with Machine Learning
Yakui Shao, Zhongke Feng, Linhao Sun, et al.
Forests (2022) Vol. 13, Iss. 6, pp. 856-856
Open Access | Times Cited: 52
Forest Fire Susceptibility Zonation in Eastern India Using Statistical and Weighted Modelling Approaches
Jayshree Das, Susanta Mahato, P. K. Joshi, et al.
Remote Sensing (2023) Vol. 15, Iss. 5, pp. 1340-1340
Open Access | Times Cited: 23
Ensembling machine learning models to identify forest fire-susceptible zones in Northeast India
Mriganka Shekhar Sarkar, Bishal Kumar Majhi, Bhawna Pathak, et al.
Ecological Informatics (2024) Vol. 81, pp. 102598-102598
Open Access | Times Cited: 16
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
Machine Learning for Predicting Forest Fire Occurrence in Changsha: An Innovative Investigation into the Introduction of a Forest Fuel Factor
Xin Wu, Gui Zhang, Yang Zhi-gao, et al.
Remote Sensing (2023) Vol. 15, Iss. 17, pp. 4208-4208
Open Access | Times Cited: 19
Predicting wildfire vulnerability using logistic regression and artificial neural networks: a case study in Brazil's Federal District
Pablo Pozzobon de, Osmar Abílio de Carvalho Júnior, Eraldo Aparecido Trondoli Matricardi, et al.
International Journal of Wildland Fire (2018) Vol. 28, Iss. 1, pp. 35-35
Closed Access | Times Cited: 58
Wildfires and the role of their drivers are changing over time in a large rural area of west-central Spain
Olga Viedma, Itziar R. Urbieta, José M. Moreno
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 47
Unit-level and area-level small area estimation under heteroscedasticity using digital aerial photogrammetry data
Johannes Breidenbach, Steen Magnussen, Johannes Rahlf, et al.
Remote Sensing of Environment (2018) Vol. 212, pp. 199-211
Open Access | Times Cited: 39
The importance of ground-truth and crowdsourcing data for the statistical and spatial analyses of the NASA FIRMS active fires in the Mediterranean Turkish forests
E. Çolak, F. Sunar
Remote Sensing Applications Society and Environment (2020) Vol. 19, pp. 100327-100327
Closed Access | Times Cited: 36
Modeling fire ignition probability and frequency using Hurdle models: a cross-regional study in Southern Europe
Marina D’Este, Antonio Ganga, Mario Elia, et al.
Ecological Processes (2020) Vol. 9, Iss. 1
Open Access | Times Cited: 33
GIS applied to location of fires detection towers in domain area of tropical forest
Fernando Coelho Eugênio, Alexandre Rosa dos Santos, Nilton César Fiedler, et al.
The Science of The Total Environment (2016) Vol. 562, pp. 542-549
Closed Access | Times Cited: 37
Integrated spatial generalized additive modeling for forest fire prediction: a case study in Fujian Province, China
Chunhui Li, Zhangwen Su, Ruijing Ni, et al.
Journal of Forestry Research (2025) Vol. 36, Iss. 1
Closed Access
Climate variability and forest fires: trends, correlation, spatiotemporal patterns in the Seven Sister States of northeastern India (2001–2022)
Manoranjan Mishra, Rajkumar Guria, Biswaranjan Baraj, et al.
Remote Sensing Applications Society and Environment (2025), pp. 101586-101586
Closed Access
Analysis of area level and unit level models for small area estimation in forest inventories assisted with LiDAR auxiliary information
Francisco Mauro, Vicente J. Monleón, Hailemariam Temesgen, et al.
PLoS ONE (2017) Vol. 12, Iss. 12, pp. e0189401-e0189401
Open Access | Times Cited: 32
Spatio-Temporal Configurations of Human-Caused Fires in Spain through Point Patterns
Sergi Costafreda-Aumedes, Carles Comas, Cristina Vega‐García
Forests (2016) Vol. 7, Iss. 9, pp. 185-185
Open Access | Times Cited: 28
Improving fire season definition by optimized temporal modelling of daily human-caused ignitions
Sergi Costafreda-Aumedes, Cristina Vega‐García, Carles Comas
Journal of Environmental Management (2018) Vol. 217, pp. 90-99
Closed Access | Times Cited: 27
Predicting the occurrence of wildfires with binary structured additive regression models
Laura Ríos-Pena, Thomas Kneib, Carmén Cadarso-Suárez, et al.
Journal of Environmental Management (2016) Vol. 187, pp. 154-165
Open Access | Times Cited: 25
Wildfire prediction using zero-inflated negative binomial mixed models: Application to Spain
María Bugallo, M. Dolores Esteban, Manuel Francisco Marey Pérez, et al.
Journal of Environmental Management (2022) Vol. 328, pp. 116788-116788
Open Access | Times Cited: 14
Wildfires as collateral effects of wildlife electrocution: An economic approach to the situation in Spain in recent years
Francisco Guil, Ma. Ángeles Soria, Antoni Margalida, et al.
The Science of The Total Environment (2017) Vol. 625, pp. 460-469
Closed Access | Times Cited: 24
Poisson mixed models for predicting number of fires
Miguel Boubeta, María José Lombardía, Manuel Francisco Marey Pérez, et al.
International Journal of Wildland Fire (2019) Vol. 28, Iss. 3, pp. 237-237
Open Access | Times Cited: 21
Predictive analysis of fire frequency based on daily temperatures
Dingli Liu, Zhisheng Xu, Chuangang Fan
Natural Hazards (2019) Vol. 97, Iss. 3, pp. 1175-1189
Closed Access | Times Cited: 21
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