Multispectral Imaging for Atmospheric Chemical Species Detection
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Solution Overview
Problem
The availability and accuracy of surface and atmospheric observations from satellite and aerial imagery are limited by the revisit rate of aeronautical vehicles and the type of on-board sensors.
Innovation Solution
A method using multispectral imagery captured through an atmospheric environment to optically detect a subject chemical species by obtaining image data, removing albedo background, generating a background reflectance map, and comparing it to the sample spectral band to generate an index array of intensity variance values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satellite and aerial imagery are used for atmospheric observations, then surface and atmospheric data can be collected, but the availability and accuracy are limited by revisit rate and sensor type
Solution Approach 1:
The patent applies multi-functionality by using existing aeronautical vehicles and their onboard sensors for multiple purposes: original mission objectives plus atmospheric chemical species detection. This allows the same platform to collect both operational data and atmospheric observations without requiring dedicated atmospheric observation satellites, thereby improving availability without adding new hardware.
Solution Approach 2:
The patent transforms atmospheric observation from a time-constrained operation to a continuous capability by changing the observation parameter from periodic satellite passes to continuous onboard sensor data collection during routine flights. This parameter change eliminates revisit rate limitations while maintaining observation accuracy through spectral analysis.
2Device complexity
If existing aeronautical vehicles and sensors are used, then device complexity is reduced, but detection capability for chemical species is limited
Solution Approach 1:
The patent achieves enhanced chemical species detection by changing the analysis parameters of existing sensor data through multispectral imaging and spectral band comparison, rather than by adding specialized detection hardware. This maintains device simplicity while improving measurement precision through computational analysis of reflectance patterns across multiple spectral bands.
Solution Approach 2:
The patent introduces an intermediary computational processing layer that analyzes existing sensor data through spectral band comparison and background reflectance mapping. This intermediary processing layer extracts chemical species information from ordinary multispectral imagery without requiring specialized detection sensors, thereby maintaining device simplicity while enhancing detection capability.
3Measurement precision
If multispectral imagery processing is performed, then chemical species detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the data processing into distinct computational stages: albedo background removal, background reflectance map generation from grouped reference spectral bands, and comparison with sample spectral bands. This segmentation organizes the complex processing into manageable steps, improving detection accuracy while making the processing complexity systematic and manageable rather than monolithic.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method improves the availability and accuracy of surface and atmospheric observations by leveraging existing aeronautical vehicles to detect and track chemical species, such as methane, in an unsupervised fashion.
Implementation Method 1
a sample spectral band having increased sensitivity to the subject chemical species as compared to the plurality of reference spectral bands
Data Source
AI summary
Techniques for optically detecting a subject chemical species within an atmospheric environment are disclosed. Image data is obtained representing multispectral imagery of a geographic region captured through the atmospheric environment. The image data includes an array of band-specific intensity values for each of a plurality of spectral bands, including a sample spectral band having increased sensitivity to the subject chemical species as compared to a plurality of reference spectral bands. A background reflectance map is generated that includes an array of inter-band intensity values in which each inter-band intensity value represents a filtered combination of band-specific intensity values of albedo-normalized arrays for a grouped subset of the plurality of reference spectral bands. The albedo-normalized array of band-specific intensity values for the sample spectral band is compared to the background reflectance map to obtain an index array of intensity variance values for the subject chemical species.