8 citations as recorded by crossref.

1. Global Wildfire Danger Predictions Based on Deep Learning Taking into Account Static and Dynamic Variables Y. Ji et al. 10.3390/f15010216
2. Comparing Machine Learning and Time Series Approaches in Predictive Modeling of Urban Fire Incidents: A Case Study of Austin, Texas Y. Yuan & A. Wylie 10.3390/ijgi13050149
3. Development Process, Quantitative Models, and Future Directions in Driving Analysis of Urban Expansion X. Guan et al. 10.3390/ijgi12040174
4. Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0 R. Tang et al. 10.5194/gmd-17-1525-2024
5. Boreal–Arctic wetland methane emissions modulated by warming and vegetation activity K. Yuan et al. 10.1038/s41558-024-01933-3
6. Harnessing deep learning for forecasting fire-burning locations and unveiling $$PM_{2.5}$$ emissions S. Gaikwad et al. 10.1007/s40808-023-01831-1
7. Machine Learning-Based Land Use and Land Cover Mapping Using Multi-Spectral Satellite Imagery: A Case Study in Egypt R. Mahmoud et al. 10.3390/su15129467
8. The role of terrain-mediated hydroclimate in vegetation recovery after wildfire R. Webb et al. 10.1088/1748-9326/acd803