12 citations as recorded by crossref.

1. Opening the Black Box: A systematic review on explainable artificial intelligence in remote sensing A. Höhl et al. 10.1109/MGRS.2024.3467001
2. Volcanic Ash Classification Through Machine Learning D. Benet et al. 10.1029/2023GC011224
3. Insight into the 2021 Semeru volcano eruption from rapid monitoring of its pyroclastic deposits using Google Earth Engine and multi-sensor data F. Kurnianto et al. 10.1016/j.rsase.2024.101380
4. Satellite measurement of forest disturbance, recovery and deposit distribution following explosive volcanic eruptions M. Udy et al. 10.1016/j.jvolgeores.2024.108204
5. Grain size modulates volcanic ash retention on crop foliage and potential yield loss N. Ligot et al. 10.5194/nhess-23-1355-2023
6. How well do concentric radii approximate population exposure to volcanic hazards? S. Biass et al. 10.1007/s00445-023-01686-5
7. Linking hazard intensity to impact severity: mini review of vulnerability models for volcanic impact and risk assessment J. Hayes et al. 10.3389/feart.2023.1278283
8. Explainable Multimodal Learning in Remote Sensing: Challenges and Future Directions A. Günther et al. 10.1109/LGRS.2024.3404596
9. Explainable artificial intelligence in disaster risk management: Achievements and prospective futures S. Ghaffarian et al. 10.1016/j.ijdrr.2023.104123
10. Mapping the global distribution of lead and its isotopes in seawater with explainable machine learning A. Olivelli et al. 10.5194/essd-17-3679-2025
11. Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data S. Biass et al. 10.5194/nhess-22-2829-2022
12. Study of the impact of ash fallout from the Icelandic volcano Eyjafjöll (2010) on vegetation using MODIS data M. Ifkirne et al. 10.1007/s11069-022-05544-z