Low-orbit small satellite constellation visible near-infrared radiation stability verification field construction method

Abstract

The invention relates to a low-orbit moonlet constellation visible near-infrared radiation stability verification field construction method, which comprises the following steps: firstly, carrying out radiation stability verification field site selection by adopting AERONET average aerosol optical thickness AOD in recent 10 years and ground feature uniformity indexes, and collecting verification field latitude and longitude, ground feature types and geographical environments; the method comprises the following steps: collecting visible near-infrared TOA radiance data of a long-time sequence low-orbit moonlet constellation, actually measuring AOD, DEM and the like in combination with MODTRAN and AERONET, and obtaining the surface reflectivity of a verification field by adopting a 3-albedo method; and fitting each verification field BRDF coefficient based on the surface reflectance data set and a kernel-driven semi-empirical model or a Stayer-Suttles model so as to construct a verification field BRDF lookup table. According to the method, the problems of long revisit period and long characteristic data set collection span time of the high-resolution satellite are solved, and the constructed visible sensor radiation stability verification field provides data support for constellation visible load normalized radiation performance monitoring and radiation consistency verification.

Description

Technical Field

[0001] The present invention relates to a method for constructing a visible 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] The low-orbit small satellite constellation is composed of multiple or hundreds of satellites, which are deployed in the same orbit or multi-orbit plane. Through networking and collaborative work, high-frequency and high-spatial-resolution observations of the earth are achieved, which greatly improves the ability to obtain information from hotspot sensitive areas. The low-orbit remote sensing optical small satellite constellation is equipped with a series of optical sensors with the same design indicators and manufacturing processes, which can obtain visible and near-infrared data with high temporal resolution (15 minutes) and high spatial resolution (above meters). Due to the same design indicators, the observation data of each optical sensor in the constellation are highly consistent. With the advancement of low-orbit small satellite constellation technology, high-spatial-resolution constellation visible and near-infrared data are becoming more and more widely used in various fields, and the radiation performance of each constellation satellite has also attracted much attention. However, due to the low coverage latitude of the low-orbit large-angle remote sensing small satellite constellation (approximately less than 40°), most of the global radiation calibration field networks currently open to the public are outside its observation area, making it difficult to use them to monitor the radiation stability of each sensor in the constellation. 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 problem solved by the present invention is: to overcome the shortcomings of the prior art 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 global automatic aerosol observation station AERONET for many years was calculated, and the observation stations whose average optical aerosol thickness was not greater than the threshold were selected;

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

[0008] Within the preset distance from the observation site, a large uniform ground object with stable radiation characteristics is selected as the radiation stability verification field of the high-resolution visible and near-infrared of the low-orbit small satellite constellation;

[0009] Collect long-term series of visible and near-infrared top-of-atmosphere AOT radiance data from a low-orbit small satellite constellation covering the radiation stability verification field, and construct an AOT radiance data set;

[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 to form a surface reflectance dataset.

[0012] According to the type of ground objects in the radiation stability verification field, the 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 field 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] Based on the surface reflectivity corresponding to the visible and near-infrared data to be verified and the aerosol optical depth calculated from the AERONET station observation data, the corresponding AOT radiance is obtained;

[0015] The radiation stability is verified based on the AOT radiance.

[0016] Furthermore, in the above method, a large uniform land object with stable radiation characteristics is selected. The specific method is: if the standard deviation of the radiation value of the large uniform land object 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 land object.

[0017] Furthermore, in the above method, the preset distance is: different values ​​are determined according to 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 satellite observation channel AOT radiance, 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 bidirectional reflectivity of the surface; 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 selected is the Staylor-Suttles model, which is as follows:

[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 observed zenith angle, φ is the relative azimuth angle of 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 solar incidence direction.

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

[0034]

[0035] Among them, 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 fitting radiation stability verification field is specifically measured as follows:

[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 bare surfaces in non-desert or arid areas. iso 、f vol 、f geo ;

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

[0039] Furthermore, in the above method, the surface reflectivity corresponding to the visible and near-infrared data to be verified is calculated by 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 into the type of ground objects at the verification point based on the BRDF model and BRDF coefficient 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) The present invention proposes to construct a long-term reflectance characteristic data set of the radiation verification field through high-resolution visible and near-infrared data of optical sensors of a low-orbit small satellite constellation, which solves the difficulties of long revisit cycles of high-spatial-resolution satellites and long time spans for collecting characteristic data sets;

[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 single 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 measured data released by the station. Combined with the BRDF lookup table of the verification field, it can be used for absolute radiation calibration of 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 global automatic aerosol observation station AERONET for many years was calculated, and the observation stations whose average optical aerosol thickness was not greater than the threshold were selected;

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

[0049] Within the preset distance from the observation site, a large uniform ground object with stable radiation characteristics is selected as the radiation stability verification field of the high-resolution visible and near-infrared of the low-orbit small satellite constellation;

[0050] Collect long-term series of visible and near-infrared top-of-atmosphere AOT radiance data from a low-orbit small satellite constellation covering the radiation stability verification field, and construct an AOT radiance data set;

[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 objects in the radiation stability verification field, the 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 field 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] Based on the surface reflectivity corresponding to the visible and near-infrared data to be verified and the aerosol optical depth calculated from the AERONET station observation data, the corresponding AOT radiance is obtained;

[0056] The radiation stability is verified based on the AOT radiance.

[0057] Preferably, 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.

[0058] Preferably, the preset distance is: different values ​​are determined according to 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 satellite observation channel AOT radiance, 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 bidirectional reflectivity of the surface; 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 selected is the Staylor-Suttles model, which is as follows:

[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 observed zenith angle, φ is the relative azimuth angle of 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 solar incidence direction.

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

[0076]

[0077]

[0078] Among them, 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 bare surfaces in non-desert or arid areas. iso 、f vol 、f geo ;

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

[0082] Preferably, the surface reflectivity 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, 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 in combination with the type of ground objects at the verification point to obtain the surface reflectivity at the moment of satellite transit.

[0083] Example

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

[0085] like Figure 1 As shown, 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) The average optical aerosol thickness (AOD) of the AERONET global automatic aerosol observation stations currently in normal operation in the past 10 years was collected quarterly, and the AERONET stations with an AOD of no more than 0.02 were selected;

[0087] Existing studies have shown that some uniform objects with stable reflection characteristics have obvious seasonal characteristics. Therefore, when constructing a radiation stability verification field, the AOD is counted by season and the applicable time of the verification field is given;

[0088] (2) Combined with the simulation results of the orbital 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%), and record their longitude and latitude as a visible light / near-infrared radiation stability verification field, and record their geographical environment, such as cities, villages, deserts, 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 terrain 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 data sets from a low-orbiting small satellite constellation covering the radiation stability verification field in step (2), use the measured aerosol optical thickness at the AERONET site for atmospheric correction, and obtain the surface reflectance under different observation geometry and illumination geometry;

[0090] In this step, the accuracy of the surface reflectivity 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 satellite observation channel top of atmosphere (TOA) radiance, 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 The 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 as 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, and the equation group is constructed and solved to obtain L0, s and After the solution is obtained, the satellite observation channel TOA radiance is substituted into formula (1) to obtain the surface reflectivity 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), select a suitable BRDF model to fit the BRDF coefficients of the radiation verification field according to the object type of the radiation verification field.

[0096] So far, a wide variety of BRDF theoretical models have been established, which can be roughly divided into three categories: empirical statistical models, physical models, and semi-empirical models due to different mechanisms for calculating BRDF. The empirical statistical model is simple and has strong applicability, and is suitable for situations where the physical mechanism is unclear, such as the Walthall model. The physical model has a sound theoretical basis, and its model parameters have clear physical meanings, and mathematically describes the mechanism of light and surface objects. There are mainly four categories: radiation transfer model, geometric optical model, hybrid model, and computer simulation model. The semi-empirical model combines the advantages of empirical models and physical models. Although the model parameters are empirical parameters, they have certain physical meanings.

[0097] In the present 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 bidirectional reflectivity of the surface, 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 right-hand equation represents the isotropic reflection component (iso), the second term represents the reflection component caused by volume scattering (vol), which is calculated by the Ross-Thick model, and the third term represents the reflection part caused by geometric scattering (geo), which is calculated by the Li-Sparse model. The surface bidirectional reflectivity is the weighted average of the above three terms, with a weight coefficient 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 solar incidence direction.

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

[0104]

[0105]

[0106] In the formula, 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.

[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 star in the visible and near-infrared channel of 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 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 360-φ. The fitting results of the Staylor-Suttles model coefficients are shown in Table 3.

[0115] Table 3 Schematic diagram of BRDF model fitting coefficients for a satellite 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 radiance at the top of the atmosphere and conduct 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 building 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 global automatic aerosol observation station AERONET for many years was calculated, and the observation stations whose average optical aerosol thickness was not greater than the threshold were selected; Combined with the coverage of low-orbit small satellite constellation visits, aerosol observation sites with more satellite observation times are further selected from the selected observation sites; Within the preset distance from the observation site, a large uniform ground object with stable radiation characteristics is selected as the radiation stability verification field of the high-resolution visible and near-infrared of the low-orbit small satellite constellation; Collect long-term series of visible and near-infrared top-of-atmosphere AOT radiance data from a low-orbit small satellite constellation covering the radiation stability verification field, and construct an AOT radiance data set; 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 to form a surface reflectance dataset. According to the type of ground objects in the radiation stability verification field, the 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 field and the visible near-infrared data of the low-orbit small satellite constellation to be verified, the observation zenith angle, observation azimuth angle, solar zenith angle and solar azimuth angle are used to calculate the surface reflectance corresponding to the visible near-infrared data to be verified; Based on the observed zenith angle, observed azimuth, solar zenith angle, solar azimuth, surface reflectivity and AERONET station observation data of the visible and near-infrared data to be verified, the calculated aerosol optical thickness is used to obtain the corresponding AOT radiance using the atmospheric radiation transfer model; The radiation stability is verified based on the AOT radiance.

2. According to the method for constructing a low-orbit small satellite constellation visible and near-infrared radiation stability verification field according to claim 1, it is characterized in that: Select large uniform objects with stable radiation characteristics. The specific method is: if the standard deviation of the radiation value of a large uniform object 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 object.

3. According to the method for constructing a low-orbit small satellite constellation visible and near-infrared radiation stability verification field according to claim 1, it is characterized in that: 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.

4. According to claim 1, a method for constructing a visible and near-infrared radiation stability verification field for a low-orbit small satellite constellation is characterized in that: The surface reflectivity is specifically: Where ρ is the surface reflectivity, L m is the satellite observation channel AOT radiance, 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. According to the method for constructing a low-orbit small satellite constellation visible and near-infrared radiation stability verification field according to claim 1, it 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 bidirectional reflectivity of the surface; f iso is the isotropic reflection component, is the reflection component caused by volume scattering, calculated by the Ross-Thick model; It is the reflection part caused by geometric scattering, calculated by 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. According to the method for constructing a low-orbit small satellite constellation visible and near-infrared radiation stability verification field according to claim 1, it is characterized in that: The BRDF model is selected as follows: For bare surfaces in deserts or arid areas, the BRDF model selected is the Staylor-Suttles model, which is as follows: 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 observed zenith angle, φ is the relative azimuth angle of 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 solar incidence direction.

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: Among them, 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 bare surfaces in non-desert or arid areas. iso 、f vol 、f geo ; Using the surface reflectance dataset under different observation geometry and illumination geometry, the BRDF Staylor-Suttles free parameters c1, c2, c3 and N are fitted using the least squares method for bare surfaces in deserts or arid areas.

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 is characterized in that: The specific method for calculating the surface reflectivity corresponding to the visible and near-infrared data to be verified is as follows: combining the ground object type of the verification point, based on the BRDF model and the 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.

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