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Cloud Screening Method in Complex Background Areas Containing Snow and Ice Based on Landsat 9 Images
Tingting Wu1, Qing Liu2, Ying Jing3
1School of Geomatics, Anhui University of Science and Technology, Huainan 232001, China.
International Journal of Environmental Research and Public Health
|October 27, 2022
Summary
Accurate cloud screening in satellite imagery is crucial for climate research. This study introduces a dynamic threshold algorithm to overcome cloud-snow confusion in snow and ice environments, improving remote sensing data reliability.
Area of Science:
- Earth and Space Sciences
- Atmospheric Science
- Remote Sensing
Background:
- Cloud screening is essential for satellite imagery analysis, particularly for climate studies like the International Satellite Cloud Climatology Project (ISCCP).
- Distinguishing clouds from snow and ice surfaces in satellite images presents a significant challenge for accurate remote sensing data.
- Existing cloud screening methods often struggle with surface-type interference, limiting their effectiveness in icy environments.
Purpose of the Study:
- To develop an improved cloud screening algorithm specifically designed for environments with snow and ice.
- To address the challenge of cloud-snow confusion that hinders accurate cloud identification in satellite imagery.
- To overcome the limitations of empirical and statistical thresholds in snow and ice-covered regions.
Main Methods:
- Proposing a novel cloud screening algorithm that accounts for the interference from snow and ice.
- Developing a dynamic threshold approach to enhance cloud recognition accuracy.
- Focusing on exploiting heterogeneous information from clouds and snow/ice subsurface.
Main Results:
- The proposed algorithm effectively mitigates cloud-snow confusion in satellite images.
- The dynamic threshold method proves more suitable for snow and ice environments than static thresholds.
- The research provides a new perspective on handling surface-type interference in cloud screening.
Conclusions:
- The developed dynamic threshold cloud screening algorithm offers a robust solution for snow and ice environments.
- This advancement improves the reliability of Landsat 9 imagery analysis and climate research.
- The findings contribute to overcoming persistent challenges in remote sensing data processing.
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