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<p>The accurate estimation of land surface temperature (LST) is crucial for environmental and meteorological applications. This study investigates the estimation of LST using data from the GEO-KOMPSAT-2A (GK-2A) satellite, focusing on the analysis of seasonal, diurnal, and cloud-cover variations in the Korean Peninsula. The GK-2A satellite, launched in 2018, is equipped with 16 channels, providing high-resolution imagery for precise meteorological observations. The LST-related factors were derived from the satellite’s infrared bands (IR13 and IR15) and compared with ground-based measurements from the Korea Meteorological Administration's Agro-Meteorological Observation Stations (AAOS). The results show that the multiple regression model, incorporating both IR13 and IR15 bands, provided a stronger correlation with ground temperatures compared to single-band models. Seasonal analysis indicated that the correlation was highest during winter, while summer data showed increased error due to factors such as high atmospheric water vapor, cloud cover, and precipitation. Diurnal analysis revealed that evening data yielded more reliable LST estimates than morning data, potentially due to reduced solar reflection. Cloud cover was found to significantly impact the accuracy of LST estimates, with minimal cloud cover yielding the most reliable results. These findings emphasize the importance of considering seasonal, diurnal, and cloud-cover conditions when using satellite data for LST estimation, and suggest that combining multiple infrared bands improves accuracy.</p>

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Impact of seasonal, diurnal, and cloud-cover variations on evaluation of land surface temperature using GK-2A satellite data

  • 期刊论文

  • 发表日期：

    2025年2月25日

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  • Byung-Kyu Kim,
  • Wooyoung Na,
  • Sang Yeob Kim

摘要

The accurate estimation of land surface temperature (LST) is crucial for environmental and meteorological applications. This study investigates the estimation of LST using data from the GEO-KOMPSAT-2A (GK-2A) satellite, focusing on the analysis of seasonal, diurnal, and cloud-cover variations in the Korean Peninsula. The GK-2A satellite, launched in 2018, is equipped with 16 channels, providing high-resolution imagery for precise meteorological observations. The LST-related factors were derived from the satellite’s infrared bands (IR13 and IR15) and compared with ground-based measurements from the Korea Meteorological Administration's Agro-Meteorological Observation Stations (AAOS). The results show that the multiple regression model, incorporating both IR13 and IR15 bands, provided a stronger correlation with ground temperatures compared to single-band models. Seasonal analysis indicated that the correlation was highest during winter, while summer data showed increased error due to factors such as high atmospheric water vapor, cloud cover, and precipitation. Diurnal analysis revealed that evening data yielded more reliable LST estimates than morning data, potentially due to reduced solar reflection. Cloud cover was found to significantly impact the accuracy of LST estimates, with minimal cloud cover yielding the most reliable results. These findings emphasize the importance of considering seasonal, diurnal, and cloud-cover conditions when using satellite data for LST estimation, and suggest that combining multiple infrared bands improves accuracy.