Parallax Cloud Height Determination for Remote Sensing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The challenge in obtaining high-quality satellite and aerial imagery is the scattering of light by atmospheric water vapor and aerosols, and the occlusion of ground areas by clouds, which also block sunlight, leading to inaccurate material classification and reduced usable pixels in images.
Innovation Solution
A method using a pair of radiant energy sensors positioned at a small parallax angle to determine the height of objects, such as clouds, by comparing light energy collected from different directions, allowing for the calculation of cloud height and compensation for shadow effects in imagery, thereby improving image quality and classification accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single-direction light collection is used, then device complexity is reduced, but measurement precision of cloud height is insufficient
Solution Approach 1:
The patent transitions from single-direction light collection to multi-directional collection by introducing a second sensor oriented at a different angle. This dimensional change in observation direction enables parallax measurement, allowing calculation of cloud height through geometric relationships between the two sensor views and the ground target.
Solution Approach 2:
The patent uses the ground target as an intermediary reference point. By measuring light reflection from the ground target at different angles and comparing the differences, the system indirectly determines cloud height without requiring direct vertical measurement or complex three-dimensional sensor arrays.
2Manufacturing precision
If cloud shadow effects are not accounted for, then image processing is simplified, but material classification accuracy deteriorates
Solution Approach 1:
The patent performs preliminary measurement of cloud height and shadow effect parameters before conducting material classification. By pre-determining the cloud's vertical position and its projected shadow areas using parallax geometry, the system can then compensate for these effects during image processing, improving classification accuracy without requiring complex real-time adjustments.
Solution Approach 2:
The system uses the measured cloud height and shadow information as feedback to correct and adjust the image data during processing. The parallax-derived cloud position information feeds back into the image analysis to identify and compensate for shadowed areas, thereby improving material classification while maintaining manageable processing complexity through structured correction algorithms.
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 approach enhances image quality by increasing the number of usable pixels and improving material classification accuracy by accounting for cloud shadows and illumination variations, resulting in a significant gain in usable image data.
Implementation Method 1
receiving radiant energy with the sensors
Implementation Method 2
This atmosphere has water vapor and aerosols therein that can cause the scattering of light
Data Source
AI summary
Techniques for using small parallax angles in remote sensing to determine cloud feature height include exploiting two identical medium-resolution SWIR bands with parallax to estimate cloud edge feature heights well enough to enable assessments of the impacts of shadows and proximate cloud scattering on ground illumination, and hence, on reflectance calculations. The bands are intentionally designed to have a suitable parallax angle, in one embodiment approximately 1.5 degrees. With this parallax, one band will see more ground pixels than the other band as they encounter a leading edge of a cloud and the other band will see more ground pixels than the one band as they encounter the lagging edge of the cloud. From these numbers of pixels, the height of the leading and lagging edges of the cloud can be determined.