wildfire
Published April 3, 2026 | Version v1
Dataset Open

DLSR-FireCNet: A deep learning framework for burned area mapping based on decision level super-resolution

Authors/Creators

  • 1. EDMO icon Boise State University

Description

Associated Publication: Seydi, S.T. & Sadegh, M. (2025). DLSR-FireCNet: A deep learning framework for burned area mapping based on decision level super-resolution. Remote Sensing Applications: Society and Environment, 37, 101513. https://doi.org/10.1016/j.rsase.2025.101513

Input Features

  • Source: MODIS surface reflectance product
  • Spectral bands used: Red (Band 1) and Near-Infrared / NIR (Band 2)
  • Native input resolution: 250 m
  • Image structure: Bi-temporal pairs — one pre-fire image and one post-fire image per event
  • Architecture target: The model is trained to produce burned area maps at 30 m effective resolution via decision-level super-resolution

Files

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