A Sentinel-2 benchmark dataset for deep-learning active-fire segmentation across 25 California wildfires

arXiv:2609.16199 · eess.IV, cs.CV, cs.LG, eess.SP, physics.geo-ph · Submitted 2026-09-14 · Read on arXiv

eess.IV, cs.CV, cs.LG, eess.SP, physics.geo-ph

Submitted: 2026-09-14

Updated: 2026-09-14

Comments: 13 pages, 9 figures, 5 tables. Preprint submitted to Elsevier. Data: https://doi.org/10.5281/zenodo.22713948 Code: https://github.com/MohammadrezaNarimaniUCDavis/California_Sentinel2_Active_Fire_Dataset

Code: https://github.com/MohammadrezaNarimaniUCDavis/California_Sentinel2_Active_Fire_Dataset

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 4× in this paper · explained in 2 episodes
• National Interagency Fire Center — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Spectral Signature — 1× in this paper · explained in 2 episodes
• Wildland Fire Interagency Geospatial Services — 1× in this paper

Sources

• Farmland Extent and Visible Boundary Mapping from 1 m NAIP Imagery Using Residual U-Net and Text-Prompted SAM 3 Refinement

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