A method and system for determining universal rayleigh scattering in water color remote sensing

Abstract

The application provides a universal Rayleigh scattering determination method and system for water color remote sensing, introduces Rayleigh optical thickness into one of the input dimensions of a lookup table, so that the same lookup table can be used across platforms and across bands, greatly improving the flexibility and engineering adaptability of the system. At the same time, the depolarization factor varying with the wavelength is introduced, effectively representing the anisotropic characteristics of atmospheric molecules under different bands, so that the Rayleigh scattering correction result is more physically reasonable and the band response is more accurate. The application simulates the Rayleigh scattering characteristics under different sea conditions, and introduces the influence of the earth curvature on the scattering path and the polarization characteristics, greatly expanding the physical adaptation range of the lookup table, and is especially suitable for marine remote sensing and high-precision correction tasks under complex atmospheric conditions. In addition, the lookup table constructed by the application adopts a standardized data structure, cooperates with a modular lookup table interface, is convenient for system integration and engineering deployment, and supports automatic processing of large-scale remote sensing data.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of remote sensing, and particularly relates to a water color remote sensing general Rayleigh scattering determination method and system. BACKGROUND

[0002] Accurate atmospheric correction is the basis for quantitative retrieval in water color remote sensing. The top-of-atmosphere radiance received by the satellite is mainly composed of the following parts: Rayleigh scattering radiance, aerosol scattering radiance, and the cross-scattering term between Rayleigh and aerosol. Among them, Rayleigh scattering dominates in the shortwave band, and its accurate estimation is crucial for removing background interference and improving remote sensing retrieval accuracy.

[0003] The current commonly used Rayleigh scattering radiance estimation method is mostly based on offline simulation of the vector radiation transfer model, and a look-up table (LUT) is constructed for quick call in the remote sensing retrieval process. Typical schemes include customized LUT based on 6S model, OSOAA model, and Rayleigh lookup table designed for different sensors such as MODIS / VIIRS in SeaDAS system. In recent years, scholars have proposed a general G-LUT applicable to various observation geometries and atmospheric conditions based on the PCOART radiation transfer model, which has made certain progress in improving the efficiency of table lookup and sensor adaptability.

[0004] However, the existing lookup table still has the following significant technical defects:

[0005] 1) The influence of the Earth's curvature is not considered: In the existing lookup table, the influence of the Earth's curvature on Rayleigh scattering is usually not considered. However, the influence of the Earth's curvature on the calculation of Rayleigh scattering can reach 8.3%, so ignoring the role of the Earth's curvature in atmospheric correction will lead to a decrease in calculation accuracy, especially in the case of large solar or observation zenith angles, it is particularly important to consider this influence.

[0006] 2) Simplification of the depolarization factor is unreasonable: Traditional lookup tables mostly use a fixed depolarization factor for approximation, without fully considering the differences in anisotropy of atmospheric molecules with wavelength changes, leading to increased scattering correction errors in wide-band sensor applications (such as ultraviolet to short-wave infrared).

[0007] 3) Lack of cross-platform generality: Most lookup tables are customized for specific sensors, making it difficult to migrate or extend to other platforms, limiting their application in multi-source remote sensing data fusion and new tasks.

[0008] 4) Non-uniform interface and data structure: The structure of the existing lookup table is not standardized, the calling interface is not uniform, and there is a lack of standardized design, increasing the complexity of system integration and engineering deployment.

[0009] Therefore, it is urgent to develop a structure universal, physically reasonable, broad-spectrum adaptive Rayleigh scattering lookup table and its supporting application system, especially considering the influence of the earth curvature and the wavelength-dependent depolarization factor, to meet the actual needs of high-precision, large-scale, cross-platform atmospheric correction support under the current rapid development of water color remote sensing. SUMMARY

[0010] The application provides a water color remote sensing universal Rayleigh scattering determination method and system to solve the problems that the existing lookup table does not consider the influence of the earth curvature, the simplified treatment of the depolarization factor is unreasonable, lacks cross-platform universality, and the interface and data structure are not unified.

[0011] To solve the above technical problems, the embodiments of the application disclose the following technical solutions:

[0012] One aspect of the application provides a water color remote sensing universal Rayleigh scattering determination method, comprising:

[0013] using a first radiative transfer model or a second radiative transfer model to simulate Rayleigh scattering simulation data corresponding to different parameter values of a plurality of observation scene parameters, wherein the observation scene parameters at least include sea surface wind speed, solar zenith angle, observation zenith angle, relative azimuth angle, Rayleigh optical thickness and depolarization factor;

[0014] constructing a Rayleigh scattering multidimensional lookup table based on different observation scene parameter values and corresponding Rayleigh scattering simulation data;

[0015] obtaining observation scene parameter values corresponding to each pixel in a target remote sensing image;

[0016] inputting the observation scene parameter values of each pixel into the Rayleigh scattering multidimensional lookup table to obtain corresponding Rayleigh scattering data.

[0017] Optionally, the method further comprises:

[0018] pre-establishing a plurality of different sets of observation scene parameter data, and each set of data includes parameter values of sea surface wind speed, solar zenith angle, observation zenith angle, relative azimuth angle, Rayleigh optical thickness and depolarization factor.

[0019] Optionally, the using a first radiative transfer model or a second radiative transfer model to simulate Rayleigh scattering simulation data corresponding to different parameter values of a plurality of observation scene parameters comprises:

[0020] for each set of observation scene parameter data, the corresponding Rayleigh scattering simulation data is obtained in the following manner:

[0021] determining the selected radiative transfer model according to the parameter values of the solar zenith angle and the observation zenith angle, wherein the radiative transfer model is a first radiative transfer model or a second radiative transfer model;

[0022] inputting the parameter value of each observed scene parameter into the selected radiation transfer model to obtain the corresponding Rayleigh scattering Stokes vector.

[0023] Optionally, the determining the selected radiation transfer model according to the parameter values of the solar zenith angle and the observed zenith angle comprises:

[0024] adopting a first radiation transfer model to simulate Rayleigh scattering simulation data under the condition that the solar zenith angle is less than a first threshold value and the observed zenith angle is less than a second threshold value; and adopting a second radiation transfer model to simulate Rayleigh scattering simulation data under the condition that the solar zenith angle is not less than the first threshold value or the observed zenith angle is not less than the second threshold value.

[0025] Optionally, the method further comprises:

[0026] pre-setting the value mode of each observed scene parameter, comprising:

[0027] setting the parameter value of the solar zenith angle in the range of 0 degrees to 80 degrees with a step of 2 degrees;

[0028] setting the parameter value of the observed zenith angle in the range of 0 degrees to 80 degrees with a step of 2 degrees;

[0029] setting the parameter value of the relative azimuth angle in the range of 0 degrees to 180 degrees with a step of 10 degrees;

[0030] setting the parameter value of the sea surface wind speed in the range of 0 m / s to 30 m / s with a step of 3 m / s;

[0031] setting the parameter value of the Rayleigh optical thickness covering the ultraviolet band to the near-infrared band in the range of 0.001 to 1.0 with a step of 0.001;

[0032] looking up the depolarization factor parameter value corresponding to the Rayleigh optical thickness according to the preset depolarization factor lookup table.

[0033] Optionally, the constructing the Rayleigh scattering multidimensional lookup table based on different observed scene parameter values and the corresponding Rayleigh scattering simulation data comprises:

[0034] constructing the Rayleigh scattering multidimensional lookup table based on each set of observed scene parameter data and the corresponding Rayleigh scattering simulation data, the input parameters of the lookup table being the solar zenith angle, the observed zenith angle, the relative azimuth angle, the sea surface wind speed and the Rayleigh optical thickness, and the output parameter being the Rayleigh scattering Stokes vector.

[0035] Optionally, the acquiring the observed scene parameter value corresponding to each pixel in the target remote sensing image comprises:

[0036] Extract the solar zenith angle, observation zenith angle and relative azimuth angle of each pixel in the target remote sensing image, and the Rayleigh optical thickness value under standard atmospheric pressure;

[0037] Obtain the sea surface wind speed and actual atmospheric pressure data of the target remote sensing image shooting time and position from the meteorological data platform;

[0038] Correct the Rayleigh optical thickness value under standard atmospheric pressure by using the actual atmospheric pressure data to obtain the Rayleigh optical thickness value of each wave band under actual atmospheric pressure.

[0039] Optionally, the Rayleigh optical thickness value under standard atmospheric pressure is corrected by using the actual atmospheric pressure data to obtain the Rayleigh optical thickness value of each wave band under actual atmospheric pressure, comprising:

[0040] The Rayleigh optical thickness value under actual atmospheric pressure is calculated according to the following formula:

[0041]

[0042] Wherein The Rayleigh optical thickness value under standard atmospheric pressure is represented by R, The Rayleigh optical thickness value corrected by the actual atmospheric pressure data is represented by R', and P represents the actual atmospheric pressure data.

[0043] Optionally, the observation scene parameter value of each pixel is input into the Rayleigh scattering multi-dimensional lookup table to obtain the corresponding Rayleigh scattering data, comprising:

[0044] The Rayleigh scattering Stokes vector corresponding to the observation scene parameter value is calculated based on the Rayleigh scattering multi-dimensional lookup table by using a preset multi-dimensional interpolation function.

[0045] Another aspect of the present application provides a water color remote sensing general Rayleigh scattering determination system, which applies the water color remote sensing general Rayleigh scattering determination method provided in the foregoing aspect.

[0046] The water color remote sensing general Rayleigh scattering determination method and system disclosed in the present application introduce the Rayleigh optical thickness into one of the input dimensions of the lookup table, break through the limitation that the traditional lookup table is only applicable to fixed wavelengths or specific sensors, make the same lookup table applicable across platforms and wave bands, and greatly improve the flexibility and engineering adaptability of the system. At the same time, the depolarization factor varying with the wavelength is introduced, which effectively represents the anisotropic characteristics of atmospheric molecules under different wave bands, makes the Rayleigh scattering correction result more physically reasonable and the wave band response more accurate, and significantly improves the correction accuracy of the short wave to infrared wave band.

[0047] The method and system disclosed by the application consider roughness effect caused by sea surface wind speed, simulate Rayleigh scattering characteristics under different sea conditions, introduce influence of earth curvature on scattering path and polarization characteristics, greatly expand physical adaptation range of the lookup table, and are particularly suitable for ocean remote sensing and high-precision correction tasks under complex atmospheric conditions.

[0048] In addition, the lookup table constructed by the application adopts a standardized data structure, cooperates with a modular lookup table interface, is convenient for system integration and engineering deployment, supports automatic processing of large-scale remote sensing data, simplifies cross-platform application and data processing procedures, and improves system efficiency and convenience of engineering deployment.

[0049] The summary is provided to introduce selected concepts of the application in a simplified form, which will be further described below in the detailed description. The summary is not intended to identify key or essential features of the disclosure, nor is it intended to limit the scope of the disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0050] The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings in which like reference characters refer to like parts throughout the figures, in which exemplary embodiments of the present disclosure are shown.

[0051] Figure 1 A flowchart of a water color remote sensing general Rayleigh scattering determination method provided by an embodiment of the application is shown in the figure.

[0052] Figure 2 A flowchart of a method for implementing step S100 in the method is shown in the figure. Figure 1

[0053] Figure 3 A flowchart of a method for selecting a radiation transmission model provided by an embodiment of the application is shown in the figure.

[0054] Figure 4 A flowchart of a method for implementing step S300 in the method is shown in the figure. Figure 1 DETAILED DESCRIPTION

[0055] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0056] ​​The term "includes," "including," "has," "having," "contains" or "containing" used herein means "including, but not limited to." The term "or" means "and / or" unless expressly stated otherwise. The term "based on" means "based, at least in part, on." The terms "one example embodiment" and "an embodiment" mean "at least one example embodiment." The term "another embodiment" means "at least one additional embodiment." The terms "first," "second," and the like can refer to different or identical objects. Other explicitly and implicitly recited definitions can also be included below.

[0057] Figure 1 A flowchart of a general Rayleigh scattering determination method for water color remote sensing provided by an embodiment of the present application is shown in FIG. 1, which includes the following steps: Figure 1

[0058] Step S100: Simulate Rayleigh scattering simulation data corresponding to different parameter values of a plurality of observation scene parameters by using a first radiation transfer model or a second radiation transfer model.

[0059] In one embodiment of the present application, a plurality of groups of different observation scene parameter data are established in advance, each group of data including parameter values of sea surface wind speed, solar zenith angle, observation zenith angle, relative azimuth angle, Rayleigh optical thickness and depolarization factor. The sea surface wind speed is used to determine the sea surface roughness and the specular reflection characteristics, and has a significant influence on the propagation path and polarization characteristics of light at the sea-air boundary. The solar zenith angle and the observation zenith angle jointly determine the propagation path length of light in the atmosphere, and directly affect the intensity and angular distribution of Rayleigh scattering. The relative azimuth angle reflects the angle between the sun and the observation direction, and is an important geometric factor affecting the calculation of polarization components. The Rayleigh optical thickness represents the scattering ability of molecules in the atmosphere to light. The depolarization factor is used to describe the scattering difference of polarized light by atmospheric molecules at different wavelengths.

[0060] For each group of observation scene parameter data, the corresponding Rayleigh scattering simulation data is obtained in the following manner, as shown in FIG. 2: Figure 2

[0061] Step S101: Determine the selected radiation transfer model according to the parameter values of the solar zenith angle and the observation zenith angle.

[0062] In one embodiment of the present application, step S101 is implemented in the following manner:

[0063] Under the condition that the solar zenith angle is less than a first threshold value and the observation zenith angle is less than a second threshold value, the first radiation transfer model is used to simulate the Rayleigh scattering simulation data; under the condition that the solar zenith angle is not less than the first threshold value or the observation zenith angle is not less than the second threshold value, the second radiation transfer model is used to simulate the Rayleigh scattering simulation data.

[0064] ​​Specifically, the first threshold is the critical value of the solar zenith angle, which can be set to 70°; the second threshold is the critical value of the observed zenith angle, which can be set to 60°. For example... Figure 3 As shown, when the solar zenith angle in a set of observation scene parameter data is less than the first threshold (low to medium solar zenith angle), and the observed zenith angle is less than the second threshold (low to medium observed zenith angle), it indicates that the current observation geometry is relatively stable and the optical path is short. In this case, using a first radiative transfer model based on the parallel plane layering assumption (such as the PCOART vector radiative transfer model) for simulation can quickly obtain Rayleigh scattering Stokes vector data with high reliability. The radiative transfer model generates Rayleigh scattering Stokes vector data under standard atmospheric pressure (1013.25 hPa).

[0065] Conversely, when the solar zenith angle in the observation scene parameters is not less than the first threshold (high solar zenith angle), or the observed zenith angle is not less than the second threshold (high observed zenith angle), it indicates that the incident or outgoing light path has been significantly elongated, and the effects of atmospheric curvature, path integral error, and multiple scattering are significantly enhanced. Under such complex geometric conditions, traditional models (based on the parallel plane assumption) may experience a decrease in accuracy, or even underestimate the Rayleigh scattering polarization effect. Therefore, switching to a second spherical radiative transfer model (such as the SSA-MC radiative transfer model based on the Monte Carlo method), which is more adaptable to complex paths, is necessary to ensure that accurate and physically consistent Rayleigh scattering simulation data can still be generated under large-angle observation conditions.

[0066] Step S102: Input the parameter values ​​of each observation scenario into the selected radiative transfer model to obtain the corresponding Rayleigh scattering Stokes vector.

[0067] After determining the radiative transfer model suitable for the observation scenarios, the parameter values ​​for each observation scenario are input into the model for high-precision Rayleigh scattering simulation. Within the model, these parameters drive the radiative transfer algorithm to perform a series of precise optical calculations, simulating the elastic scattering process of light in atmospheric molecules, thereby obtaining the Stokes vector components (I, Q, U) of the scattered light. Here, the I component represents the total radiance, and the Q and U components represent the distribution characteristics along the linear polarization direction.

[0068] To more realistically reflect the band response differences of atmospheric molecules, this invention introduces a wavelength-varying depolarization factor (see Bodhaine et al., 1999) to replace the fixed value processing used in traditional lookup tables, thereby improving the simulation accuracy in short-band and broadband remote sensing systems.

[0069] And, the embodiment of the present application introduces the Rayleigh optical thickness into one of the input dimensions of the lookup table, breaking through the limitation of the traditional lookup table being only applicable to fixed wavelengths or specific sensors, so that the same lookup table can be used across platforms and across wavebands, greatly improving the flexibility and engineering adaptability of the system.

[0070] In one embodiment disclosed in the present application, the observation scene parameter range and settings can be as follows:

[0071] In the range of 0 degrees to 80 degrees, the parameter value of the solar zenith angle is set at a step of 2 degrees, with a total of 41 values. The solar zenith angle represents the angle of sunlight incident on the earth's surface relative to the vertical direction, and is a key factor affecting the optical path length and scattering intensity. A smaller solar zenith angle indicates near-perpendicular incidence of sunlight, shorter optical path, and weaker scattering effect; when the solar zenith angle is close to 80°, the atmospheric path of the light is lengthened, Rayleigh scattering is enhanced, and the influence of the earth's curvature needs to be considered. By setting a fine angle step, the influence of solar height change on Rayleigh scattering can be fully captured.

[0072] In the range of 0 degrees to 80 degrees, the parameter value of the observation zenith angle is set at a step of 2 degrees, with a total of 41 values. The observation zenith angle refers to the observation angle of the sensor relative to the normal direction of the ground, and is an important parameter that determines the observation path length and scattering path structure. A larger observation zenith angle means a more inclined viewing angle, which has a more significant impact on scattering.

[0073] In the range of 0 degrees to 180 degrees, the parameter value of the relative azimuth angle is set at a step of 10 degrees, with a total of 19 values. The relative azimuth angle represents the angle between the sun direction and the observation direction in the horizontal plane, which has a great influence on the polarization characteristics.

[0074] In the range of 0 m / s to 30 m / s, the parameter value of the sea surface wind speed is set at a step of 3 m / s, with a total of 11 values. The sea surface wind speed directly affects the sea surface roughness, thereby changing the reflection and scattering characteristics of light at the sea-air interface. Rayleigh scattering is caused by atmospheric molecules, while wind speed can affect the propagation direction and intensity of Rayleigh radiation by adjusting the sea surface specular reflection component, changing the photon path and multiple scattering path. Including wind speed in the model input helps improve the adaptability of the lookup table under different sea conditions.

[0075] In the range of 0.001 to 1.0, the parameter value of the Rayleigh optical thickness covering the ultraviolet band to the near-infrared band is set at a step of 0.001. The Rayleigh optical thickness is a quantitative indicator of the weakening of light intensity by the Rayleigh scattering process in the atmosphere, and is highly related to the wavelength, usually large in the ultraviolet band and decreasing in the infrared band. Using a high-resolution step setting, the lookup table can accurately adapt to different waveband remote sensing sensors and can reflect the small differences in optical path and scattering behavior between wavebands in detail.

[0076] According to the preset depolarization factor lookup table, the depolarization factor parameter value corresponding to the Rayleigh optical thickness is found. The depolarization factor is not stepped, but is obtained by table lookup according to the experimental results of Bodhaine et al. (1999). The depolarization factor describes the degree of molecular deviation from isotropy in Rayleigh scattering, and affects the ratio of polarization components, especially in the short wave band. The depolarization factor takes different values at different wavelengths, so according to the Rayleigh optical thickness of the current wave band, the corresponding depolarization factor value is automatically selected.

[0077] The above limitation of step length is only an example, and other step lengths can be set in actual application.

[0078] Step S200: Construct a Rayleigh scattering multidimensional lookup table based on different observation scene parameter values and corresponding Rayleigh scattering simulation data.

[0079] In one embodiment of the present disclosure, after the simulation of the Rayleigh scattering Stokes vector is completed, the data is constructed into a multidimensional lookup table in a unified format to support efficient calling and cross-platform application.

[0080] Based on a large number of preset observation scene parameter combinations and Rayleigh scattering simulation results, a structure specification and strong adaptability Rayleigh scattering multidimensional lookup table is constructed. The lookup table takes the solar zenith angle, observation zenith angle, relative azimuth angle, sea surface wind speed and Rayleigh optical thickness as the input parameter dimension, and outputs the Rayleigh scattering Stokes vector (I, Q, U) under the corresponding conditions. Through systematic modeling and high-resolution sampling of the above key physical parameters, the lookup table can comprehensively cover the common observation geometry and atmospheric conditions in water color remote sensing, and realize accurate description of the Rayleigh scattering characteristics.

[0081] In the design, the effect of the depolarization factor has been embedded in the data generation stage through the band characteristics of the Rayleigh optical thickness, so the depolarization factor does not need to be listed as an independent dimension in the lookup table. This processing method not only reduces the data dimension, improves the lookup efficiency, but also improves the physical reasonableness and band adaptability of the model. Each set of observation scene parameter data corresponds to a complete Rayleigh scattering Stokes vector output, which is used to express the Rayleigh scattering radiance and polarization distribution under the geometric and meteorological state.

[0082] In terms of data organization, the lookup table is stored in NetCDF (.nc) format. This format supports multi-dimensional array data structure, can flexibly record meta-information such as each input dimension and its unit, value range, and can embed metadata content such as data generation time, data source, and interpolation strategy, facilitating engineering deployment, system integration, and version management. The lookup table design also fully considers the needs of cross-platform calls, supporting reading and interpolation operations in multiple common scientific programming environments such as Python, IDL, Matlab, and Fortran.

[0083] To achieve efficient calling and parallel processing, a multi-dimensional interpolation algorithm is used to search and interpolate the lookup table, making it capable of large-scale remote sensing image processing, adapting to remote sensing image data of different resolutions and different platforms. Finally, users only need to provide the Rayleigh optical thickness corresponding to the observed band of the sensor, the geometric parameter data and the meteorological data, and the corresponding Rayleigh scattering value can be quickly obtained, completing the cross-platform, cross-band, and automated atmospheric correction process, greatly improving the quantitative inversion efficiency and accuracy of water color remote sensing data.

[0084] Step S300: Obtain the observed scene parameter value corresponding to each pixel in the target remote sensing image.

[0085] To obtain the Rayleigh scattering data of each pixel in the remote sensing image, the observed scene parameter value related to it is first obtained as the input basis for subsequent lookup table interpolation calculation.

[0086] In one embodiment of the present disclosure, as shown in Figure 4 Step S300 can be implemented in the following way:

[0087] Step S301: Extract the solar zenith angle, observation zenith angle, and relative azimuth angle of each pixel in the target remote sensing image, as well as the Rayleigh optical thickness value under standard atmospheric pressure conditions.

[0088] The above data can be directly parsed from the metadata of the target remote sensing image or the sensor geometric model.

[0089] Step S302: Obtain the sea surface wind speed and actual atmospheric pressure data of the target remote sensing image shooting time and location from the meteorological data platform.

[0090] According to the shooting time and geographic coordinates of the image, the sea surface wind speed and actual atmospheric pressure data under the corresponding spatio-temporal conditions are obtained by accessing public meteorological data platforms such as Ocean Color. These meteorological information is crucial for accurately modeling the atmospheric state at that time and improving the accuracy of scattering correction. In particular, the atmospheric pressure parameter fluctuates significantly in different weather systems and ocean areas. If a fixed standard atmospheric pressure value is still used, it is easy to cause estimation error of Rayleigh optical thickness, and then affect the final radiance correction result.

[0091] Step S303: correcting the Rayleigh optical thickness value under the standard atmospheric pressure by using the actual atmospheric pressure data to obtain the Rayleigh optical thickness value of each wave band under the actual atmospheric pressure.

[0092] By adjusting the Rayleigh optical thickness under the standard atmospheric pressure by a proportional factor, the corrected Rayleigh optical thickness of each wave band under the current actual atmospheric pressure is obtained. The correction process effectively compensates for the influence of atmospheric pressure changes on the Rayleigh scattering path length and molecular density, so that the lookup table input is closer to the real observation condition, thereby improving the accuracy and robustness of the final Rayleigh scattering correction.

[0093] In the embodiments disclosed in the present application, the Rayleigh optical thickness value under the actual atmospheric pressure is calculated according to the following formula:

[0094]

[0095] wherein, represents the Rayleigh optical thickness value under the standard atmospheric pressure, represents the Rayleigh optical thickness value corrected by the actual atmospheric pressure data, and P represents the actual atmospheric pressure data.

[0096] Step S400: inputting the observed scene parameter value of each pixel into the Rayleigh scattering multidimensional lookup table to obtain the corresponding Rayleigh scattering data.

[0097] Using a preset multidimensional interpolation function, the Rayleigh scattering Stokes vector corresponding to the observed scene parameter value is calculated based on the Rayleigh scattering multidimensional lookup table.

[0098] The extracted solar zenith angle, observation zenith angle, relative azimuth angle, sea surface wind speed and Rayleigh optical thickness corrected according to the actual atmospheric pressure of each pixel jointly constitute a five-dimensional input vector, which is used as a lookup key to access the lookup table.

[0099] Because the lookup table only stores the data of discrete sampling points, the embodiments of the present application further introduce a multidimensional interpolation mechanism to realize continuous estimation of any observed scene parameter combination.

[0100] A preset efficient multidimensional interpolation function, such as scipy.interpolate.RegularGridInterpolator widely used in Python, supports linear or high-order interpolation of multidimensional data on a regular grid. In the actual calling process, the interpolation function can automatically identify the grid unit in which the input parameter point is located according to the position of the input parameter point in the lookup table coordinate system, and perform weighted interpolation calculation on the Rayleigh scattering data (I, Q, U components) at each vertex of the unit, thereby obtaining the Rayleigh scattering Stokes vector of the current pixel.

[0101] The interpolation calculation not only guarantees the physical continuity and precision of the search result, but also significantly improves the calculation efficiency of the system in processing large range high resolution remote sensing images.

[0102] The embodiment of the present application also discloses a water color remote sensing general Rayleigh scattering determination system, which applies the water color remote sensing general Rayleigh scattering determination method disclosed in the foregoing embodiment.

[0103] The above has described the embodiments of the present disclosure, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those skilled in the art without departing from the scope and spirit of the described embodiments. The selection of the terms used herein is intended to best explain the principles of the embodiments, practical application, or technical improvement to the technology in the market, or to enable other ordinary skilled persons in the art to understand the embodiments disclosed herein.

Claims

1. A method for determining the Rayleigh scattering in water color remote sensing, characterized in that, The method comprises the following steps: Simulate the corresponding Rayleigh scattering simulation data when the parameter values of the various observation scene parameters are taken by using the first radiation transfer model or the second radiation transfer model, which comprises the following steps: Pre-establish a plurality of different observation scene parameter data, each of which contains the parameter values of the sea surface wind speed, the solar zenith angle, the observation zenith angle, the relative azimuth angle, the Rayleigh optical thickness and the depolarization factor; For each set of observation scene parameter data, the corresponding Rayleigh scattering simulation data is obtained in the following manner: Determine the selected radiation transfer model according to the parameter values of the solar zenith angle and the observation zenith angle, which comprises the following steps: under the condition that the solar zenith angle is less than a first threshold value and the observation zenith angle is less than a second threshold value, the first radiation transfer model is used to simulate the Rayleigh scattering simulation data; and under the condition that the solar zenith angle is not less than the first threshold value or the observation zenith angle is not less than the second threshold value, the second radiation transfer model is used to simulate the Rayleigh scattering simulation data; the first radiation transfer model is the PCOART vector radiation transfer model, and the second radiation transfer model is the SSA-MC radiation transfer model based on the Monte Carlo method; the first threshold value is 70°, and the second threshold value is 60°; Input the parameter values of each observation scene parameter into the selected radiation transfer model to obtain the corresponding Rayleigh scattering Stokes vector; Construct a Rayleigh scattering multidimensional lookup table based on different observation scene parameter values and the corresponding Rayleigh scattering simulation data; Obtain the observation scene parameter values corresponding to each pixel in the target remote sensing image; Input the observation scene parameter values of each pixel into the Rayleigh scattering multidimensional lookup table to obtain the corresponding Rayleigh scattering data.

2. The method of claim 1, wherein, The method further comprises the following steps: Pre-set the value mode of each observation scene parameter, which comprises the following steps: In the range of 0° to 80°, set the parameter values of the solar zenith angle with a step of 2°; In the range of 0° to 80°, set the parameter values of the observation zenith angle with a step of 2°; In the range of 0° to 180°, set the parameter values of the relative azimuth angle with a step of 10°; In the range of 0 m / s to 30 m / s, set the parameter values of the sea surface wind speed with a step of 3 m / s; In the range of 0.001 to 1.0, set the parameter values of the Rayleigh optical thickness covering the ultraviolet band to the near-infrared band with a step of 0.001; According to the pre-set depolarization factor lookup table, the parameter values of the depolarization factor corresponding to the Rayleigh optical thickness are found.

3. The method of claim 1, wherein, The method of constructing a Rayleigh scattering multidimensional lookup table based on different observation scene parameter values and the corresponding Rayleigh scattering simulation data comprises the following steps: Construct a Rayleigh scattering multidimensional lookup table based on each set of observation scene parameter data and the corresponding Rayleigh scattering simulation data, the input parameters of the lookup table are the solar zenith angle, the observation zenith angle, the relative azimuth angle, the sea surface wind speed and the Rayleigh optical thickness, and the output parameter is the Rayleigh scattering Stokes vector.

4. The method of claim 1, wherein, The method of obtaining the observation scene parameter values corresponding to each pixel in the target remote sensing image comprises the following steps: Extract the solar zenith angle, the observation zenith angle and the relative azimuth angle of each pixel in the target remote sensing image, and the Rayleigh optical thickness value under the standard atmospheric pressure; Obtain the sea surface wind speed and the actual atmospheric pressure data of the target remote sensing image shooting time and position from a meteorological data platform; The Rayleigh optical thickness value under the standard atmospheric pressure is corrected by using the actual atmospheric pressure data to obtain the Rayleigh optical thickness value under the actual atmospheric pressure in each wave band.

5. The method of claim 4, wherein, The Rayleigh optical thickness value under the standard atmospheric pressure is corrected by using the actual atmospheric pressure data to obtain the Rayleigh optical thickness value under the actual atmospheric pressure in each wave band. The Rayleigh optical thickness value under the actual atmospheric pressure is calculated according to the following formula: wherein represents a value of the Rayleigh optical thickness under a standard atmospheric pressure, represents a value of the Rayleigh optical thickness corrected by actual atmospheric pressure data, P represents actual atmospheric pressure data.

6. The method of claim 1, wherein, The observed scene parameter value of each pixel is input into the Rayleigh scattering multi-dimensional lookup table to obtain corresponding Rayleigh scattering data, including: A preset multi-dimensional interpolation function is used to calculate the Rayleigh scattering Stokes vector corresponding to the observed scene parameter value based on the Rayleigh scattering multi-dimensional lookup table.

7. A water color remote sensing universal Rayleigh scattering determination system, characterized in that, The system applies the general Rayleigh scattering determination method for water color remote sensing according to any one of claims 1 to 6.

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