USING MACHINE LEARNING COUPLED WITH REMOTE SENSING FOR FOREST FIRE SUSCEPTIBILITY MAPPING. CASE STUDY TETOUAN PROVINCE, NORTHERN MOROCCO

13 citations as recorded by crossref.

1. Assessment of Wildfire Susceptibility and Wildfire Threats to Ecological Environment and Urban Development Based on GIS and Multi-Source Data: A Case Study of Guilin, China W. Yue et al. https://doi.org/10.3390/rs15102659
2. An integrated approach leveraging remote sensing, geospatial analysis, and machine learning algorithms for high-resolution wildfire susceptibility assessment and identification of environmental drivers in El Tarf Province, Algeria A. Goumrasa et al. https://doi.org/10.1007/s10661-026-15080-z
3. Forest fire probability zonation using dNBR and machine learning models: a case study at the Similipal Biosphere Reserve (SBR), Odisha, India R. Guria et al. https://doi.org/10.1007/s11356-025-35976-6
4. A Geospatial Approach to Wildfire Risk Modeling Using Machine Learning and Remote Sensing Data R. Gupta & H. Kim https://doi.org/10.1109/JSTARS.2024.3434368
5. Artificial Intelligence for Early Wildfire Detection in Northern Morocco: A Robust and Interpretable CatBoost–Transformer Framework Using Multisource Environmental Data C. Ouazri et al. https://doi.org/10.1109/ACCESS.2026.3688023
6. Predicting the occurrence of root rot in tree stumps based on harvester data S. Berg https://doi.org/10.1080/14942119.2025.2533084
7. Integrating Long term Satellite Data and Machine Learning to Spatiotemporal Fire Analysis in Hour al Azim International Wetland S. Hashemi & H. Mohammad Asgari https://doi.org/10.1007/s11270-024-07233-y
8. Assessment of forest fire vulnerability prediction in Indonesia: Seasonal variability analysis using machine learning techniques W. Karurung et al. https://doi.org/10.1016/j.jag.2025.104435
9. A Forest Fire Prediction Model Based on Cellular Automata and Machine Learning X. Sun et al. https://doi.org/10.1109/ACCESS.2024.3389035
10. Ormancılıkta makine öğrenmesi kullanımı R. EKER et al. https://doi.org/10.18182/tjf.1282768
11. Advancing wildfire susceptibility mapping through maching learning and SHapley Additive exPlanations-integrated geospatial analysis in Northern Morocco’s Mediterranean region A. Moumane et al. https://doi.org/10.3389/ffgc.2025.1705341
12. Fire risk mapping using machine learning method and remote sensing in the Mediterranean region F. Sivrikaya & D. Demirel https://doi.org/10.1016/j.asr.2025.01.050
13. Predicting the number of forest firefighters considering fire scenarios features: A case analysis of 67 Chinese forest fires with the random forest model X. Li et al. https://doi.org/10.1016/j.jnlssr.2026.100327