Channel selection of atmospheric remote sensing

Area of Science:

• Atmospheric remote sensing
• Integral equations
• Signal processing

Background:

• Atmospheric remote sensing often involves solving Fredholm integral equations of the first kind.
• Selecting optimal spectral channels is crucial for accurate retrieval of atmospheric properties.
• Existing methods may not fully account for various error sources and function characteristics.

Purpose of the Study:

• To introduce a novel channel selection method for atmospheric remote-sensing problems.
• To provide a quantitative measure (degree of predominance) for comparing channel sets.
• To simplify the selection process based on data characteristics and error influences.

Main Methods:

• Developed a degree of predominance (DP) metric to evaluate channel set suitability.
• Formulated DP based on influences of measurement errors, noise, kernel relativity, and sensing blindness.
• Defined selection criteria based on DP values and the number of channels.

Main Results:

• The proposed method allows quantitative comparison of different channel sets.
• Suitability is determined by higher DP values and a greater number of channels.
• The method simplifies to conventional approaches under specific error-free conditions.

Conclusions:

• The introduced channel selection method enhances the accuracy of atmospheric remote sensing.
• The degree of predominance provides a robust metric for channel optimization.
• This approach offers a systematic way to improve data retrieval in remote sensing applications.