Published 2025
| Version v1
Conference paper
Open
Deep Learning Approach to Improve Spatial Resolution of GOES-R Satellite Imagery for Active Fire Detection Using VIIRS Satellite Data
Authors/Creators
-
1.
University of Wisconsin–Madison
- 2. University of Wisconsin-Madiso
Description
This study proposes a two-step framework: (1) super-resolution (SR) of GOES-R data to approximate VIIRS-level detail, and (2) application of a transformer based deep learning (DL) model to detect active fires in super-resolved images. The approach exploits the complementary spatial and temporal strengths of both sensors, enabling detection of small, low-intensity, and fast-spreading fires often missed by threshold-based methods.
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GIScience2025_Abstract_Huang.pdf
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Additional details
Funding
- National Institute of Food and Agriculture
- 2022-67021-36468
- University of Wisconsin–Madison
- Wisconsin Alumni Research Foundation