Blue-Green Water Depth Retrieval Using Wavelet-Spline Tidal Correction
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Solution Overview
Problem
Existing remote sensing water depth retrieval methods fail to accurately account for the linear correlation between blue-green light attenuation and depth, tidal height smoothness, and the characteristics of consistent convergence, first-order and second-order continuous derivation of tidal height with time change, leading to significant errors in tidal height calculation and water depth retrieval.
Innovation Solution
A method for remote sensing blue-green wave band ratio logarithmic water depth retrieval using wavelet spline instantaneous tidal height correction, which involves constructing a satellite image retrieval model, decomposing tidal height data with a wavelet function, and interpolating low-frequency coefficients to reconstruct tidal height data, ensuring accurate tidal height correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional remote sensing water depth retrieval methods are used, then the retrieval process is simple, but the retrieval precision is low due to not considering tidal height characteristics and light attenuation correlations
Solution Approach 1:
The patent transforms tidal height data from discrete sampling points into continuous functions by changing the representation parameters. Wavelet decomposition breaks down tidal height signals into different frequency components, and spline interpolation transforms these into smooth continuous functions with derivatives, enabling precise calculation of tidal characteristics at any moment including satellite过境 time
Solution Approach 2:
The patent introduces wavelet decomposition and spline interpolation as intermediary mathematical tools between raw tidal height data and water depth retrieval. These intermediaries extract essential tidal characteristics (height, first derivative, second derivative) that mediate the relationship between tidal observations and satellite measurement moments, improving retrieval accuracy without direct complex modeling
2Measurement precision
If tidal height data are acquired by setting up temporary tide gauge stations, then accurate tidal height data can be obtained, but the process is difficult and time-consuming due to weather constraints and long periods required
Solution Approach 1:
The patent creates mathematical copies of tidal height behavior through wavelet-spline models. Instead of physically measuring tidal height at every satellite过境 moment with tide gauge stations, the model generates accurate tidal height values and their derivatives at any required time point by copying the underlying tidal patterns from available observation data, eliminating the need for extensive field measurements
Solution Approach 2:
The patent performs preliminary wavelet decomposition and spline fitting on available tidal height data before satellite water depth retrieval. This preliminary action prepares continuous tidal height functions and their derivatives in advance, so that when satellite data arrives, the tidal correction can be immediately and accurately applied without waiting for additional field measurements
3Measurement precision
If the characteristics of uniform convergence, first-order continuous derivation and second-order continuous derivation of tidal height are not considered, then the calculation process is simpler, but the tidal height calculation error increases significantly
Solution Approach 1:
The patent makes the tidal height model dynamic by incorporating first and second derivatives through spline interpolation. Instead of using static tidal height values, the model dynamically calculates instantaneous tidal height, its rate of change (first derivative), and its acceleration (second derivative) at any moment, capturing the temporal dynamics of tidal variations to improve accuracy
Solution Approach 2:
The patent replaces physical tide gauge measurement systems with a mathematical computation system based on wavelet-spline models. The mechanical/physical system of continuous field measurements is substituted by a computational system that uses mathematical functions to generate tidal height and its derivatives, reducing field complexity while maintaining or improving accuracy
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
The method significantly reduces errors in water depth retrieval by considering the linear correlation between blue-green light attenuation and depth, tidal height smoothness, and tidal height derivatives, improving precision by up to 9% compared to existing methods.
Implementation Method 1
decomposing tidal height data with a wavelet function db1 to obtain a low-frequency coefficient
Implementation Method 2
fully considers a linear correlation between an attenuation ratio of blue-green light in water and a depth
Data Source
AI summary
The present disclosure provides a method for remote sensing blue-green wave band ratio logarithmic water depth retrieval of wavelet spline instantaneous tidal height correction, and belongs to the field of remote sensing water depth retrieval. Aiming at water depth retrieval precision reduced by blue-green light and a tidal height in a remote sensing water depth retrieval process, the model fully considers a linear correlation between an attenuation ratio of the blue-green light in water and a depth, the smoothness of the tidal height, and the characteristics of consistent convergence, first-order continuous derivation and second-order continuous derivation of the tidal height with time change, and constructs the method for remote sensing blue-green wave band ratio logarithmic water depth retrieval of wavelet spline instantaneous tidal height correction, and according to Molokai experiment verification, compared with an early model, the invention improves the remote sensing water depth retrieval precision.