98 citations as recorded by crossref.

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45. Assessment of China’s forest fire occurrence with deep learning, geographic information and multisource data Y. Shao et al. https://doi.org/10.1007/s11676-022-01559-1
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51. Decision Support Models and Methodologies for Fire Suppression B. Granda et al. https://doi.org/10.3390/fire6020037
52. Wildfire Exposure Analysis on the National Forests in the Pacific Northwest, USA A. Ager et al. https://doi.org/10.1111/j.1539-6924.2012.01911.x
53. Regional forest-fire susceptibility analysis in central Portugal using a probabilistic ratings procedure and artificial neural network weights assignment L. Dimuccio et al. https://doi.org/10.1071/WF09083
54. Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy M. Elia et al. https://doi.org/10.1007/s00267-015-0531-z
55. Exploratory Spatial Analysis of Social Vulnerability and Forest Fire Risk in the Pinhal Interior Sul (Central Portugal) J. Farinha et al. https://doi.org/10.3390/su14053010
56. A combined structural and seasonal approach to assess wildfire susceptibility and hazard in summertime R. Bergonse et al. https://doi.org/10.1007/s11069-021-04554-7
57. Promoting Low-Risk Fire Regimes: An Agent-Based Model to Explore Wildfire Mitigation Policy Options P. Ribeiro et al. https://doi.org/10.3390/fire6030102
58. Evaluation of Machine Learning Performance in Wildfire Susceptibility Mapping Under Limited Training Data Condition M. SHAFAPOURTEHRANY https://doi.org/10.46387/bjesr.1174006
59. Assessment of forest fire severity and land surface temperature using Google Earth Engine: a case study of Gujarat State, India K. Jodhani et al. https://doi.org/10.1186/s42408-024-00254-2
60. Integrated forest management to prevent wildfires under Mediterranean environments P. Corona et al. https://doi.org/10.12899/asr-946
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62. The Influence of Wildfire Climate on Wildfire Incidence: The Case of Portugal M. Pereira et al. https://doi.org/10.3390/fire7070234
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64. A Choice-Modeling Approach to Inform Policies Aimed at Reducing Wildfire Hazard through the Promotion of Fuel Management by Forest Owners J. Santos et al. https://doi.org/10.3390/f12040403
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67. Variable selection for estimating individual tree height using genetic algorithm and random forest E. Nunes Miranda et al. https://doi.org/10.1016/j.foreco.2021.119828
68. Open Data and Machine Learning to Model the Occurrence of Fire in the Ecoregion of “Llanos Colombo–Venezolanos” J. Barreto & D. Armenteras https://doi.org/10.3390/rs12233921
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72. A Study on the Susceptibility of Wildfire Disasters in Wuzhou City Based on Interpretability Model L. Zou et al. https://doi.org/10.1109/ACCESS.2025.3583089
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