Hyperspectral Sensing System for Water Quality Assessment
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Solution Overview
Problem
Existing hyperspectral sensing systems are limited by their single mode of deployment, size, cost, power requirements, and sensitivity to vibration, making them unsuitable for autonomous field use in water-quality assessment and remote sensing applications.
Innovation Solution
A computer-implemented method for assessing water quality that includes simulating light spectra and correcting for non-water-leaving light contributions, using a hyperspectral sensing system capable of measuring light at high spectral resolution, which can be deployed in various environments and is designed to be compact, cost-effective, and vibration-resistant.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a hyperspectral sensor measures light at high spectral resolution to detect wavelength-dependent characteristics, then measurement precision is improved, but device complexity and size increase
Solution Approach 1:
The optical spectrum is segmented into multiple discrete wavelength bands using a array of detectors, each sensitive to a specific wavelength range. This allows high spectral resolution to be achieved through parallel measurement of multiple wavelength segments rather than requiring a single complex high-resolution instrument.
Solution Approach 2:
The system transitions from measuring light intensity at a single wavelength to measuring across multiple wavelength dimensions simultaneously using an array of detectors. This dimensional expansion enables high spectral resolution without proportionally increasing device complexity, as each detector element provides an independent wavelength measurement.
2Measurement precision
If a hyperspectral sensing system is designed for high spectral resolution to quantify concentrations of substances, then measurement precision is improved, but the system becomes unsuitable for autonomous deployment due to size and power requirements
Solution Approach 1:
Multiple spectral measurement functions are merged into a single integrated sensor array that simultaneously measures light at multiple wavelengths. This consolidation reduces the overall system size and power consumption compared to separate instruments, making it suitable for autonomous deployment while maintaining high measurement precision for concentration quantification.
Solution Approach 2:
The sensor array is designed with universal applicability across different deployment environments (aquatic, terrestrial, atmospheric) and measurement scenarios. The same hardware platform can quantify various substances including sediment, biological matter, vegetation, and minerals, providing multi-functional capability that reduces the need for separate specialized instruments.
3Quantity of substance
If a hyperspectral sensor collects light from multiple directions including surface-reflected light, then the quantity of measured light increases, but the purity of water-leaving light signal decreases due to contamination from non-water-leaving light
Solution Approach 1:
The system extracts and isolates the water-leaving light signal from the total measured light by using wavelength-dependent characteristics that differ between water-leaving and surface-reflected light. Specific wavelength bands are selected and processed to separate the desired water-leaving signal from contaminating surface-reflected light, maintaining signal purity while collecting light from multiple directions.
Solution Approach 2:
Different wavelength regions are assigned different functional qualities: certain wavelength bands are optimized for detecting water-leaving light from specific directions, while other bands are used to characterize surface-reflected light. This local differentiation of spectral quality allows the system to maintain measurement precision for water-quality assessment while collecting comprehensive optical data from multiple sources.
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
Enables accurate and efficient hyperspectral data collection in diverse environments, including aquatic and terrestrial settings, providing high-resolution data for water-quality assessment and remote sensing without the limitations of traditional systems.
Implementation Method 1
the optical model is configured to predict interactions between light and at least one feature of the geographic location
Implementation Method 2
performing a ray-tracing simulation of rays of light arriving at the sensor after interacting with at least one of the one or more features of the geographic location
Implementation Method 3
A hyperspectral sensor, which can measure the spectrum of light at each spatial pixel in a region of interest, would provide a large amount of high-resolution data
Data Source
AI summary
A method for retrieving a corrected spectrum from a measured spectrum (e.g., retrieving a top-of-water spectrum from a measured top-of-atmosphere spectrum) includes creating a scene-specific model of a region of interest and performing a ray-tracing simulation to simulate rays of light that would reach an airborne (or spaceborne) sensor. The region of interest can be an optically complex area such as an inland or coastal body of water. Based on the ray-tracing simulation, a scene-specific correction for unwanted effects (e.g., adjacency effects, variable atmospheric conditions, and/or other suitable effects) is obtained. A corrected spectrum is obtained by correcting the measured spectrum using the scene-specific correction. The ray-tracing simulation may be performed using a graphical processing unit, allowing the scene-specific correction to be performed in real time or near real time.