A method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation

Abstract

The present invention relates to a method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation. The method first uses the AERONET seasonal average aerosol optical depth (AOD) and ground feature homogeneity index over the past 10 years to select a site for the radiation stability verification field, and collects the latitude and longitude, ground feature type, and geographical environment of the verification field. Long-term series visible and near-infrared TOA radiance data of the low-orbit small satellite constellation are collected, and combined with MODTRAN, AERONET measured AOD, DEM, etc., the 3-albedo method is used to obtain the surface reflectivity of the verification field. Based on the surface reflectivity dataset and a kernel-driven semi-empirical model or Staylor-Suttles model, the BRDF coefficients of each verification field are fitted to construct a BRDF lookup table for the verification field. The method solves the difficulties of long revisit periods for high-resolution satellites and long time spans for collecting characteristic datasets. The constructed visible sensor radiation stability verification field provides data support for normalized radiation performance monitoring and radiation consistency verification of visible payloads of the constellation.

Description

Technical Field

[0001] The present invention relates to a method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation, and belongs to the field of absolute radiation calibration of optical sensors. Background Art

[0002] Low-Earth Orbit (LEO) small satellite constellations consist of multiple or even hundreds of satellites deployed in the same orbit or multiple orbital planes. Working collaboratively through networking, they achieve high-frequency, high-spatial-resolution Earth observations, significantly improving the ability to acquire information from sensitive hotspots. Low-Earth Orbit (LEO) remote sensing optical small satellite constellations utilize a series of optical sensors with identical design specifications and manufacturing processes, capable of acquiring visible and near-infrared data with high temporal resolution (15 minutes) and high spatial resolution (above the meter level). Due to their shared design specifications, the observation data from each optical sensor in the constellation is highly consistent. With advances in LEO small satellite constellation technology, high-spatial-resolution visible and near-infrared data is increasingly being used in various fields, and the radiometric performance of each constellation satellite is attracting significant attention. However, due to the low latitude coverage of LEO high-inclination remote sensing small satellite constellations (approximately less than 40°), the majority of currently available global radiometric calibration networks are located outside their observation area, making them difficult to use for monitoring the radiometric stability of the constellation's sensors. In this case, it is of great significance to construct a visible and near-infrared radiation stability verification field for the high-resolution low-orbit remote sensing satellite constellation to quickly and normally verify the radiation stability of the visible and near-infrared channels in the constellation and improve the on-orbit radiation consistency of each sensor in the constellation. Summary of the Invention

[0003] The technical problems solved by the present invention are: to overcome the shortcomings of the existing technology and to provide a method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation; to solve the problem that most of the existing radiation verification fields are located at high latitudes and are insufficient to support the radiation stability verification work of a low-orbit high-resolution remote sensing satellite constellation.

[0004] The present invention is achieved through the following technical solutions.

[0005] The present invention discloses a method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation, comprising:

[0006] The average optical aerosol thickness of the AERONET global automatic aerosol observation station over many years was calculated, and the observation stations with the average optical aerosol thickness not greater than the threshold were selected;

[0007] Combined with the coverage of the low-orbit small satellite constellation, aerosol observation sites with more satellite observation times were further selected from the selected observation sites;

[0008] A large, uniform surface with stable radiation characteristics is selected within a preset distance from the observation site as a radiation stability verification field for the high-resolution visible and near-infrared (HNR) of the low-orbiting small satellite constellation.

[0009] Collect long-term visible and near-infrared top-of-atmosphere (AOT) radiance data from a constellation of low-orbiting small satellites covering the radiation stability verification field, and construct an AOT radiance dataset.

[0010] Using the observation stations, the measured optical aerosol thickness was obtained;

[0011] Based on the AOT radiance dataset and the measured optical aerosol thickness, atmospheric correction is performed to obtain the surface reflectance at different observation zenith angles, observation azimuth angles, solar zenith angles, and solar azimuth angles, forming a surface reflectance dataset.

[0012] According to the type of ground object in the radiation stability verification field, a BRDF model is selected and the BRDF coefficients of the radiation stability verification field are fitted based on the surface reflectance dataset.

[0013] Based on the BRDF model of each verification site and the observation geometry and illumination geometry of the visible and near-infrared data of the low-orbit small satellite constellation to be verified, the surface reflectance corresponding to the visible and near-infrared data to be verified is calculated;

[0014] The corresponding AOT radiance is obtained based on the surface reflectance corresponding to the visible and near-infrared data to be verified and the aerosol optical depth calculated from the AERONET station observation data;

[0015] Radiation stability verification is performed based on the AOT radiance.

[0016] Furthermore, in the above method, a large uniform feature with stable radiation characteristics is selected. The specific method is: if the standard deviation of the radiation value of the large uniform feature within the range of 10×10 pixels divided by the mean is less than 0.02, it is determined to be a stable large uniform feature.

[0017] Furthermore, in the above method, the preset distance is: different values ​​are determined according to the different terrain and landforms near the observation site, and the preset distance is 20KM-60KM.

[0018] Furthermore, in the above method, the surface reflectivity is specifically:

[0019]

[0020] Where ρ is the surface reflectivity, L m is the AOT radiance of the satellite observation channel, L0 is the path radiation, s is the spherical albedo of the atmosphere, F d is the total radiation flux density received by the surface, and τ is the atmospheric transmittance.

[0021] Furthermore, in the above method, the BRDF model is selected as follows:

[0022] For bare surfaces in non-desert or arid areas, the BRDF model used is a kernel-driven semi-empirical model, specifically:

[0023]

[0024] Where ρ is the surface bidirectional reflectivity; f iso is the isotropic reflection component, is the reflection component caused by volume scattering, calculated by the Ross-Thick model; is the reflection part caused by geometric scattering, calculated by the Li-Sparse model; λ,θ,β, They are the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle of the visible and near-infrared sensors of the low-orbit small satellite constellation.

[0025] Furthermore, in the above method, the BRDF model is selected as follows:

[0026] For bare surfaces in deserts or arid areas, the BRDF model used is the Staylor-Suttles model, specifically:

[0027]

[0028] μ i =cosθ i , μ v =cosθ v

[0029] Where R is the bidirectional reflectivity, c1, c2, c3 and N are free parameters, θ i is the solar zenith angle, θ v is the observation zenith angle, φ is the relative azimuth angle between the sun and the sensor, which is the absolute value of the sun azimuth angle minus the sensor azimuth angle. When φ is greater than 180 degrees, φ is taken as 360-φ.

[0030] Furthermore, in the above method, the Ross-Thick model is:

[0031]

[0032] where ξ is the phase angle between the observation direction and the direction of solar incidence.

[0033] Furthermore, in the above method, the Li-Sparse model is:

[0034]

[0035] Where h is the height of the crown center from the ground, b is the major axis radius of the ellipsoid, and r is the minor axis radius of the ellipsoid; h / b = 2 and h / r = 1 represent the crown shape and relative height, respectively.

[0036] Furthermore, in the above method, the BRDF coefficient of the radiation stability verification field is fitted by:

[0037] Using the surface reflectance dataset under different observation geometry and illumination geometry, the BRDF model coefficient f is fitted using the least squares method for the bare surface in non-desert or arid areas. iso 、f vol 、f geo ;

[0038] Using surface reflectance datasets under different observation and illumination geometries, and targeting bare surfaces in deserts or arid areas, the BRDF Staylor-Suttles free parameters c1, c2, c3, and N are fitted using the least squares method.

[0039] Furthermore, in the above method, the surface reflectivity corresponding to the visible and near-infrared data to be verified is calculated by combining the ground feature type of the verification point, based on the BRDF model and BRDF coefficient, substituting the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle of the visible and near-infrared sensor of the low-orbit small satellite constellation to be verified for radiation stability, to obtain the surface reflectivity at the moment of satellite transit.

[0040] The beneficial effects of the present invention compared with the prior art are:

[0041] (1) This invention proposes to construct a long-term reflectance characteristic dataset of the radiation verification field by using high-resolution visible and near-infrared data from optical sensors of a low-orbit small satellite constellation, which solves the difficulties of long revisit periods of high-spatial-resolution satellites and long time spans for collecting characteristic datasets.

[0042] (2) The present invention builds a global radiation stability verification field for high-resolution visible light / near-infrared sensors of a low-orbit small satellite constellation based on the AERONET site. The number of radiation verification fields is large, which can realize rapid and normalized on-orbit radiation stability monitoring of the constellation and identify individual satellites with changed radiation performance without affecting the observation mission of the constellation.

[0043] (3) The visible-near-infrared on-orbit radiation stability verification field constructed by the present invention is adjacent to the AERONET aerosol station, and can obtain the aerosol measurement data released by the station. Combined with the BRDF lookup table of the verification field, it can be used to perform absolute radiation calibration on other high spatial resolution visible light / near-infrared sensors with similar sensor designs, thereby reducing the cost of radiation calibration. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of the method of the present invention;

[0045] Figure 2 Schematic diagram of the YUMA_SL radiation stability verification field. DETAILED DESCRIPTION

[0046] The present invention discloses a method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation, comprising:

[0047] The average optical aerosol thickness of the AERONET global automatic aerosol observation station over many years was calculated, and the observation stations with the average optical aerosol thickness not greater than the threshold were selected;

[0048] Combined with the coverage of the low-orbit small satellite constellation, aerosol observation sites with more satellite observation times were further selected from the selected observation sites;

[0049] A large, uniform surface with stable radiation characteristics is selected within a preset distance from the observation site as a radiation stability verification field for the high-resolution visible and near-infrared (HNR) of the low-orbiting small satellite constellation.

[0050] Collect long-term visible and near-infrared top-of-atmosphere (AOT) radiance data from a constellation of low-orbiting small satellites covering the radiation stability verification field, and construct an AOT radiance dataset.

[0051] Using the observation stations, the measured optical aerosol thickness was obtained;

[0052] Based on the AOT radiance dataset and the measured optical aerosol thickness, atmospheric correction is performed to obtain the surface reflectance under different observation geometries (observation zenith angle and observation azimuth angle) and illumination geometries (solar zenith angle and solar azimuth angle), forming a surface reflectance dataset.

[0053] According to the type of ground object in the radiation stability verification field, a BRDF model is selected and the BRDF coefficients of the radiation stability verification field are fitted based on the surface reflectance dataset.

[0054] Based on the BRDF model of each verification site and the observation geometry and illumination geometry of the visible and near-infrared data of the low-orbit small satellite constellation to be verified, the surface reflectance corresponding to the visible and near-infrared data to be verified is calculated;

[0055] The corresponding AOT radiance is obtained based on the surface reflectance corresponding to the visible and near-infrared data to be verified and the aerosol optical depth calculated from the AERONET station observation data;

[0056] Radiation stability verification is performed based on the AOT radiance.

[0057] Preferably, a large uniform feature with stable radiation characteristics is selected. Specifically, if the standard deviation of the radiation value of the large uniform feature within a 10×10 pixel range divided by the mean is less than 0.02, it is determined to be a stable large uniform feature.

[0058] Preferably, the preset distance is: different values ​​are determined according to the different terrain and landforms near the observation site, and the preset distance is 20KM-60KM.

[0059] Preferably, the surface reflectivity is specifically:

[0060]

[0061] Where ρ is the surface reflectivity, L m is the AOT radiance of the satellite observation channel, L0 is the path radiation, s is the spherical albedo of the atmosphere, F d is the total radiation flux density received by the surface, and τ is the atmospheric transmittance.

[0062] Preferably, a BRDF model is selected, specifically:

[0063] For bare surfaces in non-desert or arid areas, the BRDF model used is a kernel-driven semi-empirical model, specifically:

[0064]

[0065] Where ρ is the surface bidirectional reflectivity; f iso is the isotropic reflection component, is the reflection component caused by volume scattering, calculated by the Ross-Thick model;

[0066] is the reflection part caused by geometric scattering, calculated by the Li-Sparse model; λ,θ,β, They are the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle of the visible and near-infrared sensors of the low-orbit small satellite constellation.

[0067] Preferably, a BRDF model is selected, specifically:

[0068] For bare surfaces in deserts or arid areas, the BRDF model used is the Staylor-Suttles model, specifically:

[0069]

[0070] μ i =cosθ i , μ v =cosθ v

[0071] Where R is the bidirectional reflectivity, c1, c2, c3 and N are free parameters, θ i is the solar zenith angle, θ v is the observation zenith angle, φ is the relative azimuth angle between the sun and the sensor, which is the absolute value of the sun azimuth angle minus the sensor azimuth angle. When φ is greater than 180 degrees, φ is taken as 360-φ.

[0072] Preferably, the Ross-Thick model is:

[0073]

[0074] where ξ is the phase angle between the observation direction and the direction of solar incidence.

[0075] Preferably, the Li-Sparse model is:

[0076]

[0077]

[0078] Where h is the height of the crown center from the ground, b is the major axis radius of the ellipsoid, and r is the minor axis radius of the ellipsoid; h / b = 2 and h / r = 1 represent the crown shape and relative height, respectively.

[0079] Preferably, the BRDF coefficient of the radiation stability verification field is fitted, and the specific method is:

[0080] Using the surface reflectance dataset under different observation geometry and illumination geometry, the BRDF model coefficient f is fitted using the least squares method for the bare surface in non-desert or arid areas. iso 、f vol 、f geo ;

[0081] Using surface reflectance datasets under different observation and illumination geometries, and targeting bare surfaces in deserts or arid areas, the BRDF Staylor-Suttles free parameters c1, c2, c3, and N are fitted using the least squares method.

[0082] Preferably, the surface reflectance corresponding to the visible and near-infrared data to be verified is calculated. The specific method is: based on the BRDF model and BRDF coefficient, combined with the ground feature type of the verification point, the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle of the visible and near-infrared sensor of the low-orbit small satellite constellation to be verified for radiation stability are substituted to obtain the surface reflectance at the moment of satellite transit.

[0083] Example

[0084] The AERONET aerosol observation network is a ground-based aerosol remote sensing observation network jointly established by NASA and LOA-PHOTONS (CNRS). The network now covers major regions of the world, with more than 500 stations worldwide, using the CIMEL automatic sun photometer (SPAM) as the basic observation instrument. The present invention calculates the aerosol optical depth at 550nm by processing the aerosol observation data measured at the AERONET station, and uses the 3-albedo method to obtain the surface reflectance of the radiation stability verification site based on the MODTRAN radiation transfer model. Compared with other methods, the surface reflectance obtained is more accurate. The specific embodiments of the present invention are further described in detail below with reference to the accompanying drawings.

[0085] like Figure 1 As shown in the figure, the present invention proposes a method for constructing a visible-near-infrared radiation stability verification field for a low-orbit small satellite constellation. The verification field construction content includes: verification field site name, longitude, latitude, verification field object type, verification field geographical environment, BRDF lookup table, and applicable season. It includes the following steps:

[0086] (1) Calculate the average optical aerosol thickness (AOD) of the AERONET global automatic aerosol observation stations that are currently in normal operation for the past 10 years on a quarterly basis, and select the AERONET stations with an AOD of no more than 0.02;

[0087] Existing studies have shown that some uniform features with stable reflectivity have obvious seasonal characteristics. Therefore, when constructing a radiation stability verification field, the AOD is calculated by season to provide the applicable time of the verification field.

[0088] (2) Combined with the simulation results of the orbit coverage of the low-orbit small satellite constellation, select the station with a high satellite observation frequency from the stations selected in step (1), and use the high-resolution satellite observation data of the station; through visual interpretation, select large uniform landforms with stable radiation characteristics within the preset distance of the station, such as deserts, bare soil, etc. Large uniform landforms meet the requirement that the standard deviation divided by the mean within the range of 10×10 pixels on the satellite image is less than a threshold (for example, 1%), record their latitude and longitude as a visible light / near-infrared radiation stability verification field, and record their geographical environment, such as city, country, desert, etc., to provide a reference for the subsequent selection of aerosol models for atmospheric radiation transmission calculations, such as Figure 2 The preset distance varies due to the different terrain and landforms near the site. For example, in areas with complex terrain types and obvious undulations, the preset distance will be smaller, and the preset distance is 20KM-60KM.

[0089] (3) Collect a long-term series of multispectral top-of-atmosphere radiance datasets from a low-orbiting small satellite constellation covering the radiation stability verification field in step (2), perform atmospheric correction using the aerosol optical depth measured at the AERONET site, and obtain surface reflectance under different observation and illumination geometries;

[0090] In this step, the accuracy of the surface reflectance is affected by the accuracy of the atmospheric correction. The present invention uses the MODTRAN atmospheric radiation transfer model and performs rapid atmospheric correction based on the 3-albedo method. The principle formula of this method is as follows:

[0091]

[0092] Where: L m is the top of atmosphere (TOA) radiance of the satellite observation channel, L0 is the path radiation, ρ is the surface reflectivity, s is the spherical albedo of the atmosphere, and F d is the total radiation flux density received by the surface, including direct solar radiation and atmospheric scattering. L0,s and Parameters related to the atmospheric state are related to the observation geometry and illumination geometry. The surface reflectance 0, 0.5, 0.8, aerosol mode, aerosol optical depth, atmospheric mode (determination method is shown in Table 1), verification field elevation (obtained from global DEM data) and satellite observation geometry and illumination geometry are input into the atmospheric radiation transfer model MODTRAN to obtain the corresponding satellite observation channel equivalent radiance. The equation system is constructed and solved to obtain L0, s and After obtaining the solution, the TOA radiance of the satellite observation channel is substituted into formula (1) to obtain the surface reflectance under the corresponding satellite observation geometry and lighting conditions.

[0093] Table 1 Atmospheric mode selection table

[0094]

[0095] (4) Based on the results of step (3), and according to the type of objects in the radiation verification field, select a suitable BRDF model to fit the BRDF coefficients of the radiation verification field.

[0096] To date, a wide variety of BRDF theoretical models have been established. These models can be broadly categorized into three types, depending on the mechanisms used to calculate BRDF: empirical statistical models, physical models, and semi-empirical models. Empirical statistical models are simple and highly applicable, making them suitable for situations where the physical mechanism is unclear, such as the Walthall model. Physical models have a well-established theoretical foundation, with model parameters having clear physical meanings and mathematically describing the interaction between light and surface objects. These models primarily fall into four categories: radiation transfer models, geometric optics models, hybrid models, and computer simulation models. Semi-empirical models combine the advantages of both empirical and physical models. While the model parameters are empirical, they possess certain physical meanings.

[0097] In this invention, for the bare surface verification field in non-desert or arid areas, a kernel-driven BRDF model is adopted, and the formula is as follows:

[0098]

[0099] Where ρ represents the surface bidirectional reflectivity, which is the wavelength λ, the solar zenith angle θ, the sensor observation zenith angle β and the relative azimuth angle between the sun and the sensor. The first term in the equation on the right represents the isotropic reflection component (iso), the second term represents the reflection component due to volume scattering (vol), calculated using the Ross-Thick model, and the third term represents the reflection component due to geometric scattering (geo), calculated using the Li-Sparse model. The surface bidirectional reflectivity is a weighted average of these three terms, with a weighting factor of f.

[0100] The Ross-Thick model and Li-Sparse model expressions are as follows:

[0101]

[0102] where ξ is the phase angle between the observation direction and the direction of solar incidence.

[0103] The intermediate variables in equations (2) and (3) above are defined as follows:

[0104]

[0105]

[0106] Where h is the height of the crown center from the ground, b is the radius of the major axis of the ellipsoid, and r is the radius of the minor axis of the ellipsoid. h / b = 2 and h / r = 1 represent the crown shape and relative height, respectively.

[0107] The long time series field characteristic data set collected in step (3) is used to verify the BRDF fitting coefficients (see Table 2).

[0108] Table 2. BRDF model fitting coefficients for a certain star in the YUMA_SL verification field.

[0109]

[0110] For bare surfaces in deserts or arid areas, the Staylor-Suttles model proposed by Staylor and Suttles in 1986 is used to fit the verification field BRDF. The Staylor-Suttles model is shown in the following formula:

[0111]

[0112] in,

[0113]

[0114] Where c1, c2, c3 and N are free parameters, μ i =cosθ i , μ v =cosθ v ,θ i is the solar zenith angle, θ v is the observed zenith angle, φ is the relative sun-sensor azimuth angle, and is the absolute value of the sun azimuth minus the sensor azimuth angle. When φ is greater than 180 degrees, φ is calculated as 360-φ. The Staylor-Suttles model coefficient fitting results are shown in Table 3.

[0115] Table 3 Schematic diagram of the fitting coefficients of the visible near-infrared channel BRDF model of a certain star in a desert verification field

[0116]

[0117] By using the BRDF model and its coefficients of each verification field and substituting the observation zenith angle, observation azimuth, solar zenith angle and solar azimuth of the satellite to be verified for radiation stability, the surface reflectivity at the moment of satellite transit can be obtained, which is used to calculate the top of atmosphere radiance and perform radiation stability verification.

[0118] The technical solution of the present invention is aimed at the on-orbit radiation stability verification requirements of visible light / near-infrared sensors of low-orbit small satellite constellations, with the goal of constructing a radiation stability verification field and its BRDF model. It describes the relevant technical methods for site selection of the radiation stability verification field, acquisition of high-precision surface reflectance of the verification field, and simulation of BRDF model coefficients, providing technical and data support for the on-orbit radiation stability verification of visible light / near-infrared sensors of low-orbit small satellite constellations.

[0119] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation, characterized in that: include: The average optical aerosol thickness of the AERONET global automatic aerosol observation station over many years was calculated, and the observation stations with the average optical aerosol thickness not greater than the threshold were selected; Combined with the coverage of the low-orbit small satellite constellation, aerosol observation sites with more satellite observation times were further selected from the selected observation sites; A large, uniform surface with stable radiation characteristics is selected within a preset distance from the observation site as a radiation stability verification field for the high-resolution visible and near-infrared (HNR) of the low-orbiting small satellite constellation. Collect long-term visible and near-infrared top-of-atmosphere (AOT) radiance data from a constellation of low-orbiting small satellites covering the radiation stability verification field, and construct an AOT radiance dataset. Using the observation stations, the measured optical aerosol thickness was obtained; Based on the AOT radiance dataset and the measured optical aerosol thickness, atmospheric correction is performed to obtain the surface reflectance at different observation zenith angles, observation azimuth angles, solar zenith angles, and solar azimuth angles, forming a surface reflectance dataset. According to the type of ground object in the radiation stability verification field, a BRDF model is selected and the BRDF coefficients of the radiation stability verification field are fitted based on the surface reflectance dataset. Based on the BRDF model of each verification site and the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle of the visible and near-infrared data of the low-orbit small satellite constellation to be verified, the surface reflectance corresponding to the visible and near-infrared data to be verified is calculated; Based on the observation zenith angle, observation azimuth angle, solar zenith angle, solar azimuth angle, surface reflectivity and AERONET station observation data of the visible and near-infrared data to be verified, the calculated aerosol optical depth is used to obtain the corresponding AOT radiance using the atmospheric radiation transfer model; Radiation stability verification is performed based on the AOT radiance.

2. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 1 is characterized in that: Large uniform features with stable radiation characteristics are selected. The specific method is as follows: if the standard deviation of the radiation value of a large uniform feature within the range of 10×10 pixels divided by the mean is less than 0.02, it is determined to be a stable large uniform feature.

3. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 1 is characterized in that: The preset distance is: different values ​​are determined according to the terrain and landforms near the observation site, and the preset distance is 20KM-60KM.

4. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 1 is characterized in that: The surface reflectivity is specifically: Where ρ is the surface reflectivity, L m is the AOT radiance of the satellite observation channel, L0 is the path radiation, s is the spherical albedo of the atmosphere, F d is the total radiation flux density received by the surface, and τ is the atmospheric transmittance.

5. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 1 is characterized in that: The BRDF model is selected as follows: For bare surfaces in non-desert or arid areas, the BRDF model used is a kernel-driven semi-empirical model, specifically: Where ρ is the surface bidirectional reflectivity; f iso is the isotropic reflection component, is the reflection component caused by volume scattering, calculated by the Ross-Thick model; is the reflection part caused by geometric scattering, calculated by the Li-Sparse model; They are the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle of the visible and near-infrared sensors of the low-orbit small satellite constellation.

6. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 1 is characterized in that: The BRDF model is selected as follows: For bare surfaces in deserts or arid areas, the BRDF model used is the Staylor-Suttles model, specifically: m i =cosθ i ,m v =cosθ v Where R is the bidirectional reflectivity, c1, c2, c3 and N are free parameters, θ i is the solar zenith angle, θ v is the observation zenith angle, φ is the relative azimuth angle between the sun and the sensor, which is the absolute value of the sun azimuth angle minus the sensor azimuth angle. When φ is greater than 180 degrees, φ is taken as 360-φ.

7. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 5 is characterized in that: The Ross-Thick model is: where ξ is the phase angle between the observation direction and the direction of solar incidence.

8. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 5 is characterized in that: The Li-Sparse model is: Where h is the height of the crown center from the ground, b is the major axis radius of the ellipsoid, and r is the minor axis radius of the ellipsoid; h / b = 2 and h / r = 1 represent the crown shape and relative height, respectively.

9. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 5 is characterized in that: The BRDF coefficient of the fitting radiation stability verification field is specifically measured as follows: Using the surface reflectance dataset under different observation geometry and illumination geometry, the BRDF model coefficient f is fitted using the least squares method for the bare surface in non-desert or arid areas. iso 、f vol 、f geo ; Using surface reflectance datasets under different observation and illumination geometries, and targeting bare surfaces in deserts or arid areas, the BRDF Staylor-Suttles free parameters c1, c2, c3, and N are fitted using the least squares method.

10. The method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation according to claim 1, characterized in that: The specific method for calculating the surface reflectance corresponding to the visible and near-infrared data to be verified is as follows: combining the ground feature type of the verification point, based on the BRDF model and BRDF coefficient, substituting the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle of the visible and near-infrared sensor of the low-orbit small satellite constellation to be verified for radiation stability, to obtain the surface reflectance at the time of satellite transit.

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