47 citations as recorded by crossref.

1. Assessing human-caused wildfire ignition likelihood across Europe P. Gelabert et al.
2. Assessing Wildfire Risk in South Korea Under Climate Change Using the Maximum Entropy Model and Shared Socioeconomic Pathway Scenarios J. Choi & H. Chae
3. Integrated wildfire danger models and factors: A review I. Zacharakis & V. Tsihrintzis
4. Wildfire activity and related weather patterns in Ukraine I. Semenova
5. Mathematical models for estimate of the ecological consequences of the impact of the pyrogenic factor on forest ecosystems L. Chernogor et al.
6. Study on the Wildfires Occurring Risk Based on Fuzzy FTA C. Chen et al.
7. Seasonal Differences in the Spatial Patterns of Wildfire Susceptibility and Drivers in Southwest Mountains, China W. Wang et al.
8. Global and Regional Trends and Drivers of Fire Under Climate Change M. Jones et al.
9. Managing Wildfire Risk in Mosaic Landscapes: A Case Study of the Upper Gata River Catchment in Sierra de Gata, Spain M. Bertomeu et al.
10. Lightning-caused fires in the Alps: Identifying the igniting strokes J. Moris et al.
11. Defining Wildfire Susceptibility Maps in Italy for Understanding Seasonal Wildfire Regimes at the National Level A. Trucchia et al.
12. Assessing the Role of Forest Grazing in Reducing Fire Severity: A Mitigation Strategy R. Lovreglio et al.
13. How Can Grazing Mitigate Wildfires? A Review of Fuel Management, Ecological Trade-Offs, and Adaptive Frameworks S. Xu et al.
14. Analysis of Wildfire Fault Based on F-FTA Method C. Chen et al.
15. Natural disturbances risks in European Boreal and Temperate forests and their links to climate change – A review of modelling approaches J. Machado Nunes Romeiro et al.
16. Wildfire Risk Assessment Considering Seasonal Differences: A Case Study of Nanning, China W. Yue et al.
17. Forest fire risk under climate change in Austria and comparable European regions D. Henner & G. Kirchengast
18. Parameters and environmental consequences of catastrophic fires in Ukraine: modeling, quantitative estimates L. Chernogor et al.
19. Seasonal differences in the spatial patterns of wildfire drivers and susceptibility in the southwest mountains of China W. Wang et al.
20. A Machine Learning-Based Approach for Wildfire Susceptibility Mapping. The Case Study of the Liguria Region in Italy M. Tonini et al.
21. Evaluating Seasonal Wildfire Susceptibility and Wildfire Threats to Local Ecosystems in the Largest Forested Area of China X. Tang et al.
22. Advancements in Wildfire Detection and Prediction: An In-Depth Review R. SALMAN et al.
23. Towards an integrated forest fire danger assessment system for the European Alps M. Müller et al.
24. Identifying anthropogenic and natural causes of wildfires by maximum entropy method-based ignition susceptibility distribution models F. Sari
25. Environmental drivers and spatial prediction of forest fires in the Western Ghats biodiversity hotspot, India: An ensemble machine learning approach K. Babu et al.
26. Evaluation of Natural Fire Hazard Factors of the Forest Area in the Kostanay Region O. Zhanar et al.
27. An Integrated Grassland Fire-Danger-Assessment System for a Mountainous National Park Using Geospatial Modelling Techniques O. Mofokeng et al.
28. Assessing Fire Risk in Wildland–Urban Interface Regions Using a Machine Learning Method and GIS data: The Example of Istanbul’s European Side E. Aksoy et al.
29. Fire classification in natural ecosystems by physical and environmental characteristics L. Chernogor et al.
30. Modelling Fire Behavior to Assess Community Exposure in Europe: Combining Open Data and Geospatial Analysis P. Palaiologou et al.
31. Explainable artificial intelligence (XAI) detects wildfire occurrence in the Mediterranean countries of Southern Europe R. Cilli et al.
32. Uncovering current pyroregions in Italy using wildfire metrics M. Elia et al.
33. Recommendations for Ensuring Environmental Safety of Ecosystem Restoration After Fire
34. Determination of forest fire risk with respect to Marchalina hellenica potential distribution to protect pine honey production sites in Turkey F. Sarı et al.
35. Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability A. Jaafari et al.
36. A review of machine learning applications in wildfire science and management P. Jain et al.
37. Wildfire risk modeling S. Oliveira et al.
38. A deep learning ensemble model for wildfire susceptibility mapping A. Bjånes et al.
39. Assessment of the effects of different variable weights on wildfire susceptibility F. Sari
40. A Combination of Human Activity and Climate Drives Forest Fire Occurrence in Central Europe: The Case of the Czech Republic R. Berčák et al.
41. Modeling the seasonal wildfire cycle and its possible effects on the distribution of focal species in Kermanshah Province, western Iran M. Morovati et al.
42. Modelling wildfire activity in wildland–urban interface (WUI) areas of Sardinia, Italy C. Scarpa et al.
43. Leveraging the power of internet of things and artificial intelligence in forest fire prevention, detection, and restoration: A comprehensive survey S. Giannakidou et al.
44. Identifying the Areas at Risk of Huaico Occurrences in the Department of Lima, Peru G. Santos et al.
45. Modeling Seasonal Fire Probability in Thailand: A Machine Learning Approach Using Multiyear Remote Sensing Data E. Bihari et al.
46. Fire susceptibility assessment in the Carpathians using an interpretable framework M. Manczinger et al.
47. Determination of Forest Structure from Remote Sensing Data for Modeling the Navigation of Rescue Vehicles M. Rybansky