Lee et al. (2026) Enhancement of the Operational GK2A Fog Detection Product over South Korea Through Integrated Surface–Satellite Post-Processing (2021–2023, Part II)

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-03-27
• Authors: Hyun Kyoung Lee, Myoung-Seok Suh, Ji-Hye Han
• DOI: 10.3390/rs18071013

Research Groups

Not explicitly stated in the provided text.

Short Summary

This study developed and optimized a post-processing algorithm for the Geo-KOMPSAT-2A fog detection algorithm (GK2A_FDA) by integrating high-resolution gridded surface observations, significantly reducing false alarms and bias with minimal impact on detection probability.

Objective

• To mitigate the over-detection tendency of the Geo-KOMPSAT-2A fog detection algorithm (GK2A_FDA) by developing and applying a post-processing algorithm that integrates surface observations.

Study Configuration

• Spatial Scale: South Korea
• Temporal Scale: Data from 2021 to 2023

Methodology and Data

• Models used: Interpretable decision tree model
• Data sources: Geo-KOMPSAT-2A (GK2A) satellite data, high-resolution gridded surface analysis data (including relative humidity (RH), clear-sky background minus fog-top brightness temperature (ΔFTs), air temperature (Ta), wind speed, and solar zenith angle).

Main Results

• The probability of detection (POD) decreased only slightly (0.08–0.27%).
• The false alarm ratio (FAR) was reduced by 5.13–13.68%.
• The bias was reduced by 16.13–52.61%.
• Improvements were more pronounced during drier seasons compared to wet seasons.
• A residual high daytime bias (3.348–5.319) was observed, indicating a need for further refinement of the GK2A_FDA.

Contributions

• Demonstrated an effective method for integrating satellite and surface observations to address the limitations of satellite-based fog detection algorithms, specifically mitigating over-detection.
• Provided a robust, optimized post-processing algorithm applicable to different sub-algorithms (inland/coastal × daytime/nighttime/twilight) and seasonally adjusted for regional conditions.

Funding

Not explicitly stated in the provided text.

Citation

@article{Lee2026Enhancement,
  author = {Lee, Hyun Kyoung and Suh, Myoung-Seok and Han, Ji-Hye},
  title = {Enhancement of the Operational GK2A Fog Detection Product over South Korea Through Integrated Surface–Satellite Post-Processing (2021–2023, Part II)},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18071013},
  url = {https://doi.org/10.3390/rs18071013}
}