A method and device for characterizing the physical parameters of light scattering of the earth's atmosphere

Abstract

The application provides a ground-air optical scattering physical parameterization characterization method and device. The method comprises the following steps: dividing a detection scene of a detector according to relative positions of the sun, the earth and the detector; the detection scene comprises a limb detection scene and a non-limb detection scene; acquiring geometric feature parameter values and environmental feature parameter values in a plurality of limb detection scenes and a plurality of non-limb detection scenes respectively; traversing array set of the geometric feature parameter values and the environmental feature parameter values in the two detection scenes respectively, and coupling radiation transmission simulation on each array set to obtain a first massive database and a second massive database respectively; obtaining equivalent scattering distribution function models in the limb detection scene and the non-limb detection scene respectively according to the first massive database and the second massive database to perform parameterization characterization on ground-air optical scattering physical properties. The method meets actual requirements of space-time dynamic evolution of the ground-air system and has high optical scattering calculation precision.

Description

Technical Field

[0001] This invention relates to the field of geothermal background light scattering radiation technology, and in particular to a method and apparatus for parameterizing and characterizing geothermal light scattering properties. Background Technology

[0002] Atmosphere-surface coupled radiative transfer is used to calculate the Earth-atmosphere scattering / radiation of the Earth-atmosphere system. The Earth-atmosphere system refers to the space system with the Earth's surface as the lower limit and the upper limit of the atmosphere as the upper limit. Earth-atmosphere scattering / radiation is a unique perspective for space exploration, generally referring to the various types of scattering / radiation released by the Earth-atmosphere system into outer space, also known as Earth-atmosphere light. In the visible and near-infrared bands, Earth-atmosphere light is mainly formed by the Earth and atmosphere scattering sunlight.

[0003] The characteristics of ground-atmosphere light scattering are influenced by numerous factors, and are strongly correlated with the reflectivity of ground objects and clouds, spatial distribution, temporal variation, illumination and detection direction, atmospheric scattering and transmission states, etc. Furthermore, these factors are strongly coupled with each other, such as... Figure 1 As shown. However, existing methods for calculating radiative transfer only consider static scenarios and cannot meet the practical requirements for high accuracy under spatiotemporal dynamic evolution conditions.

[0004] Therefore, there is an urgent need to provide a method and apparatus for parameterizing and characterizing the properties of ground-atmosphere light scattering. Summary of the Invention

[0005] To address the problem that traditional radiative transfer methods cannot meet the high-precision practical requirements of spatiotemporal dynamic evolution conditions, this invention provides a method and apparatus for parameterizing and characterizing the properties of Earth-atmosphere light scattering.

[0006] In a first aspect, embodiments of the present invention provide a method for parameterizing and characterizing the physical properties of ground-atmosphere light scattering, the method comprising:

[0007] The probe's detection scenarios are divided according to the relative positions of the Sun, Earth, and the probe; the detection scenarios include near-edge detection scenarios and non-near-edge detection scenarios.

[0008] Obtain geometric feature parameter values ​​and environmental feature parameter values ​​for several edge detection scenarios and non-edge detection scenarios respectively;

[0009] The array sets of geometric feature parameter values ​​and environmental feature parameter values ​​under the two detection scenarios are traversed respectively, and coupled radiative transfer simulation is performed on each array set to obtain the first massive database and the second massive database respectively;

[0010] Based on the first and second massive databases, equivalent scattering distribution function models for near-edge detection scenarios and non-near-edge detection scenarios are obtained respectively, and parameterized characterization is performed using the physical properties of ground-atmosphere light scattering.

[0011] Secondly, embodiments of the present invention also provide a device for parameterizing and characterizing the physical properties of ground-atmosphere light scattering, the device comprising:

[0012] A partitioning unit is used to divide the probe's detection scenarios based on the relative positions of the sun, earth, and the probe; the detection scenarios include near-edge detection scenarios and non-near-edge detection scenarios.

[0013] The acquisition unit is used to acquire geometric feature parameter values ​​and environmental feature parameter values ​​for several edge detection scenarios and non-edge detection scenarios, respectively.

[0014] The simulation unit is used to traverse the array sets of geometric feature parameter values ​​and environmental feature parameter values ​​under two detection scenarios respectively, and perform coupled radiative transfer simulation on each array set to obtain the first massive database and the second massive database respectively;

[0015] The characterization unit is used to obtain the equivalent scattering distribution function models for near-edge detection scenarios and non-near-edge detection scenarios based on the first and second massive databases, respectively, and to perform parameterized characterization using the geo-atmosphere light scattering properties.

[0016] Thirdly, embodiments of the present invention also provide a computing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the method described in any embodiment of this specification.

[0017] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the methods described in any embodiment of this specification.

[0018] On the other hand, embodiments of this application also provide a computer program product, which includes a computer program, wherein a processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, causing the computer device to perform any of the methods described in the above embodiments.

[0019] This invention provides a method and apparatus for parameterizing and characterizing the physical properties of Earth-atmosphere light scattering. First, based on the relative positions of the Sun, Earth, and the probe, the probe's detection scenario is divided into limb-edge detection scenarios and non-limb-edge detection scenarios. Then, several geometric and environmental feature parameter values ​​for each detection scenario are arranged and combined to form array sets. Simulations are performed on each array set to obtain a first and a second massive database. Finally, equivalent scattering distribution function models for the two detection scenarios are constructed based on the two massive databases. Based on the equivalent scattering distribution function models for the two detection scenarios, the scattering radiance distribution in a hemispherical space under any Earth-atmosphere background can be output based on environmental feature parameter values ​​such as those of the Earth's surface, clouds, and aerosols, which have spatial latitude and longitude distributions, combined with geometric feature parameter values. Thus, while meeting the practical needs of the spatiotemporal dynamic evolution of the Earth-atmosphere system, it also has high accuracy in light scattering calculation. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of complex coupled radiative transfer in a spatiotemporal dynamic Earth-atmosphere system provided by an embodiment of the present invention;

[0022] Figure 2 This is a flowchart of a method for parameterizing and characterizing the properties of ground-atmosphere light scattering provided in an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of the parameterized characterization of light scattering in a non-near-edge detection scenario provided by an embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of the parameterized characterization of light scattering in an edge detection scenario provided by an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram of a parameterized characterization method for equivalent ground-atmosphere light scattering properties in a detection scenario provided by an embodiment of the present invention;

[0026] Figure 6 This is a schematic diagram of the scattering distribution function provided in an embodiment of the present invention;

[0027] Figures 7 to 8 This is a graph showing the verification results of the corrected EBRDF radiance calculation accuracy provided in an embodiment of the present invention;

[0028] Figure 9This is a hardware architecture diagram of a computing device provided in an embodiment of the present invention;

[0029] Figure 10 This is a structural diagram of a ground-atmosphere light scattering property parameterization characterization device provided in an embodiment of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0031] As mentioned above, Figure 1 As shown, the light scattering characteristics of the Earth and atmosphere are greatly affected by the Earth's surface, atmosphere, and clouds. However, existing radiative transfer algorithms mostly average the optical properties of the Earth's surface features, clouds, aerosols, and atmosphere, which makes them poorly adaptable to scenarios with large differences between the Earth and atmosphere. As a result, they cannot meet the actual needs for high accuracy under spatiotemporal dynamic evolution conditions.

[0032] To address this issue, the inventors proposed a method to reduce the dimensionality of the complex coupled radiative transfer process of the Earth-atmosphere system. This method extracts environmental characteristic parameters and eigenvalues ​​of light scattering properties under different detection scenarios and constructs an equivalent scattering distribution function model for parameterized characterization. This approach ensures high accuracy while satisfying the spatiotemporal dynamic evolution conditions of the optical properties of the Earth's surface, clouds, aerosols, and atmosphere. Furthermore, the equivalent scattering distribution model reduces the dimensionality of the physical process by extracting key characteristic parameters, simplifying it into a functional relationship of parameters, thereby significantly improving computational efficiency.

[0033] The following describes the specific implementation of the above concept.

[0034] Please refer to Figure 2 This invention provides a method for parameterizing and characterizing the physical properties of ground-atmosphere light scattering, the method comprising:

[0035] Step 100: Based on the relative positions of the Sun, Earth, and the probe, divide the probe into detection scenarios; the detection scenarios include near-edge detection scenarios and non-near-edge detection scenarios;

[0036] Step 102: Obtain geometric feature parameter values ​​and environmental feature parameter values ​​for several edge detection scenarios and non-edge detection scenarios respectively;

[0037] Step 104: Iterate through the array sets of geometric feature parameter values ​​and environmental feature parameter values ​​under the two detection scenarios respectively, and perform coupled radiative transfer simulation on each array set to obtain the first massive database and the second massive database respectively;

[0038] Step 106: Based on the first and second massive databases, obtain the equivalent scattering distribution function models for near-edge detection scenarios and non-near-edge detection scenarios, respectively, and perform parameterization characterization using the geo-atmosphere light scattering properties.

[0039] In this embodiment of the invention, the probe's detection scenario is first divided into limb-edge detection scenario and non-limb-edge detection scenario based on the relative positions of the Sun, Earth, and the probe. Then, several geometric feature parameter values ​​and environmental feature parameter values ​​under each detection scenario are arranged and combined to form array sets. Simulation is performed on each array set to obtain a first massive database and a second massive database. Finally, equivalent scattering distribution function models for the two detection scenarios are constructed based on the two massive databases. Based on the equivalent scattering distribution function models for the two detection scenarios, the scattering radiance distribution in hemispherical space under any Earth-atmosphere background can be output based on environmental feature parameter values ​​such as surface, cloud, and aerosol elements with spatial latitude and longitude distributions, combined with geometric feature parameter values. Thus, while meeting the practical needs of the spatiotemporal dynamic evolution of the Earth-atmosphere system, it also has high accuracy.

[0040] For step 100:

[0041] In some implementations, dividing the probe's exploration scene according to the relative positions of the sun, earth, and probe includes:

[0042] Based on the relative positions of the Sun, Earth, and the probe, a discriminant formula for the intersection of the probe's detection rays with the Earth is constructed.

[0043] The detection scene of the detector is divided according to the intersection discriminant.

[0044] If the intersection discriminant is greater than zero, then the detector's detection ray intersects with the Earth, and the current detection scene is classified as a non-near-edge detection scene.

[0045] If the intersection discriminant is less than zero, then the detector's detection ray has no intersection with the Earth, and the current detection scene is classified as an edge detection scene.

[0046] In this embodiment of the invention, in the Earth-fixed coordinate system, with the origin of the coordinate system as the geocenter, a discriminant formula for the intersection point of the probe's ray and the Earth is constructed based on the relative positions of the Sun, Earth, and the probe:

[0047] Δ=(p·d) 2 -(p·pRE 2 )

[0048] In the formula, p is the coordinate position of the detector, d is the direction of the detector, and R... E The radius is the Earth's radius.

[0049] In both near-edge and non-near-edge detection scenarios, geometric parameters characterize the spatial relationship between incident and scattered light. In non-near-edge detection scenarios: the solar zenith angle represents the direction of incident light, the observed zenith angle represents the direction of scattered light, and the relative azimuth angle represents the relative position of the incident and scattered light rays relative to the reflecting surface. Therefore, the spatial relationship between incident and scattered light in non-near-edge detection scenarios can be characterized by these three geometric parameters. In near-edge detection scenarios: the solar zenith angle represents the direction of incident light, the tangential height represents the spatial height of scattered light, and the relative azimuth angle represents the relative position of the incident and scattered light rays relative to the reflecting surface. Therefore, the spatial relationship between incident and scattered light in near-edge detection scenarios can be characterized by these three geometric parameters.

[0050] Considering the different geometric characteristic parameters corresponding to the two detection scenarios, in this embodiment of the invention, based on the intersection of the detector's ray and the Earth's surface during the calculation of the Earth's atmospheric background light radiation transmission, the detection scenario can be divided into a near-edge detection scenario or a non-near-edge detection scenario. Intersecting points are considered non-near-edge detection scenarios, and non-intersecting points are considered near-edge detection scenarios. For example... Figure 3 As shown, in a non-edge detection scenario, the detection ray intersects the Earth's surface at a point, and the scattered ray is distributed in a hemispherical space; as... Figure 4 As shown, in the edge detection scenario, the detection ray does not intersect with the Earth's surface.

[0051] For steps 102 to 104:

[0052] Considering that the distribution range of scattered light varies under different detection scenarios, this embodiment of the invention first observes the distribution range of geometric feature parameter values ​​and environmental feature parameter values ​​under two different detection scenarios using satellite observation data, and then extracts feature values ​​at intervals within this distribution range to achieve full coverage of the detection scenario conditions of complex Earth-atmosphere systems. Next, based on the feature parameter values ​​(including geometric feature parameter values ​​and environmental feature parameter values) extracted under the two detection scenarios, the entire set of feature parameter values ​​is traversed, and coupled radiative transfer simulation (such as Monte Carlo simulation) is performed on each set of values. Finally, a massive database containing geometric feature parameter values, environmental feature parameter values, and light scattered radiance values ​​under different detection scenarios can be obtained.

[0053] In some implementations, the geometric feature parameters in the near-edge detection scenario include the solar zenith angle, relative azimuth angle, and tangent height; the geometric feature parameters in the non-near-edge detection scenario include the solar zenith angle, relative azimuth angle, and observation zenith angle.

[0054] The environmental characteristic parameters in both the near-edge detection scenario and the non-near-edge scenario include surface environmental parameters, aerosol environmental parameters, and cloud environmental parameters; wherein, the surface environmental parameters include surface reflectivity, the aerosol environmental parameters include aerosol type and aerosol optical thickness, and the cloud environmental parameters include cloud top height and cloud optical thickness.

[0055] Surface albedo characterizes the ratio of reflected energy to total incident energy. Different types of surfaces have different albedoes, thus affecting the intensity and spatial distribution of scattered light. Therefore, in this embodiment of the invention, based on statistical distribution information of surface types, surface types such as forests, snowfields, lakes, seas, and deserts are extracted, and surface albedo is extracted as a characteristic physical quantity to distinguish different surfaces. Furthermore, different types of aerosols have different optical properties, exhibiting varying abilities to scatter and absorb light. Aerosol optical thickness reflects the extinction effect of the entire aerosol layer, highly summarizing the influence of aerosol concentration, particle size distribution, and other factors on light scattering. Therefore, in this embodiment of the invention, based on statistical distribution information of aerosols, aerosol types such as rural areas, towns, and oceans are extracted, and aerosol type and aerosol optical thickness are extracted as characteristic physical quantities to distinguish different aerosols. Simultaneously, cloud top height determines the path length between incident light passing through the atmosphere and reaching the scattering surface; the longer the optical path, the more pronounced the scattering effect. Cloud optical thickness describes the absorption and scattering ability of clouds, highly summarizing the influence of cloud particle size, structure, and other factors on light scattering. Therefore, in this embodiment of the invention, based on the statistical distribution information of cloud clusters, cloud types such as stratus, cumulus, cirrus, and nimbostratus are extracted, and cloud top height and cloud optical thickness are extracted as characteristic physical quantities to distinguish different cloud clusters.

[0056] Regarding step 106:

[0057] In this embodiment of the invention, based on the massive database already available in step 104, the functional relationship between light scattering characteristics and characteristic parameter physical quantities can be obtained, and equivalent scattering distribution function models under two detection scenarios can be obtained respectively. By inputting specific geometric characteristic parameters and environmental characteristic parameters into the model, the light scattering intensity under the condition can be obtained, thereby realizing the parameterized characterization of light scattering properties for complex geo-atmosphere systems.

[0058] Furthermore, as shown in Table 2, based on the statistical distribution patterns of meteorological factors, it was found that within the 0-20km range, the surface, aerosols, and cloud types have a significant coupling effect on light scattering. However, beyond 20km, the propagation path of the probe light in the atmosphere is long, and after multiple scattering and attenuation processes, it has a significant impact on the detected values. Therefore, in the embodiments of this invention, as... Figure 5 As shown, a virtual spherical shell is established in a region 20 km above the Earth's surface. The equivalent scattering distribution function model is established at the height of the virtual spherical shell (20 km). By performing complex coupled high-precision radiative transfer simulations within the atmospheric range (0-20 km) from the Earth's surface to the height of the virtual spherical shell, the influence of various surface, aerosol, and cloud types on light scattering is fully considered, thus obtaining the hemispherical spatial light scattering distribution under various Earth-atmosphere backgrounds at the virtual spherical shell. In the range of 20-180 km, by simultaneously considering the attenuation and multiple scattering effects of the upper atmosphere, a correction term is introduced into the equivalent scattering distribution function model, thereby further improving the accuracy of the equivalent scattering distribution function model.

[0059] Table 1. Statistical table of atmospheric, aerosol, and cloud height distribution.

[0060]

[0061]

[0062] like Figure 6 As shown, the directionality of light scattering distribution within the virtual spherical shell space is determined by the solar zenith angle θ. i Observing the zenith angle θ r Relative azimuth Characterization:

[0063]

[0064] In the formula, λ is the wavelength, and L λ,i Let L be the intensity of the scattered radiation of light with incident wavelength λ. λ,o Ω represents the intensity of light scattered by the reflected wavelength λ. i For solid angle, φ = |φ i -φ o |, φ is the relative azimuth angle, φ o To observe the azimuth angle.

[0065] Therefore, in some specific embodiments, when the detector's detection altitude is 0-20km:

[0066] The equivalent scattering distribution function model for the edge detection scenario is as follows:

[0067] f EBRDF =f(ρ,L1,COD,AT,AOD,θ) i ,H,θr )

[0068] The equivalent scattering distribution function model for the non-near-edge detection scenario is as follows:

[0069]

[0070] In the formula, f EBRDF and f' EBRDF ρ represents the light scattering intensity output by the equivalent scattering distribution function model for near-edge detection scenarios and non-near-edge detection scenarios, respectively; ρ is the surface reflectivity; L1 is the cloud top height; COD is the cloud optical thickness; AT is the aerosol type; AOD is the aerosol optical thickness; and θ is the cloud optical thickness. i Let θ be the solar zenith angle, H be the tangent height, and θ be the tangent height. r To observe the zenith angle, This refers to the relative azimuth angle.

[0071] In some implementations, when the detector's detection altitude is 20-180km, the equivalent scattering distribution function model needs to be corrected;

[0072] The correction formula is as follows:

[0073] R = R EBRDF ·(τ+α)

[0074]

[0075] In the formula, R is the light scattering radiance value output by the corrected equivalent scattering distribution function model, W / (m²). 2 ×sr), R EBRDF The light scattering radiance value output by the equivalent scattering distribution function model under near-edge detection scenarios or non-near-edge detection scenarios, in W / (m²). 2 τ is the atmospheric path transmittance from 20km to the detector position, and α is the influence coefficient of atmospheric light scattering on the ground above 20km.

[0076] As can be seen, the present invention proposes an equivalent ground-atmosphere light scattering (EBRDF) parameterized model to characterize the numerical distribution of scattered light in hemispherical space. In real detection scenarios, considering the altitude distribution of dominant influencing factors such as atmosphere, aerosols, and clouds, the altitude of the EBRDF parameterized model is set to 20km. At the same time, considering the attenuation and multiple scattering effects of the upper atmosphere, transmittance τ and correction factors are introduced to further improve the accuracy of the parameterized characterization model.

[0077] To better understand the scheme, the specific application of the Equivalent scattering distribution function model (EBRDF) in the calculation of Earth-atmosphere light scattering characteristics is further described in the following manner.

[0078] Figure 5To characterize the influence of the Earth-atmosphere background system on light scattering under a single detection direction, this embodiment first focuses on the Earth-atmosphere background detection scenario. As shown in Table 2, environmental characteristic parameters that dominate the light scattering properties are extracted, namely, surface albedo ρ, aerosol type AT, aerosol optical thickness AOD, cloud top height L1, and cloud optical thickness COD. The value ranges of these characteristic physical quantities are given through satellite observation numerical distribution, ensuring the accuracy and full coverage of the characteristic values. Then, for any environmental characteristic parameter and geometric characteristic parameter, based on known satellite detection results, characteristic values ​​are extracted at intervals within the value range. The light scattering characteristic distribution is simulated using complex coupled radiative transfer (such as the Monte Carlo method) to obtain a massive database. Finally, the equivalent scattering distribution function model (EBRDF) is introduced to characterize the distribution characteristics of light scattering properties in the virtual spherical shell space, such as... Figure 6 As shown, this enables parameterized characterization of light scattering properties under arbitrary environmental backgrounds and detection scenarios.

[0079] Table 2. Statistical Table of Characteristic Physical Quantities of Earth Atmosphere Background

[0080]

[0081] Based on statistical distribution patterns and physical definitions, the characteristic values ​​of eight physical quantities under the non-proximal detection scenario were selected (as shown in Table 3). All array sets of the characteristic values ​​of the eight physical quantities were traversed, and the numerical distribution of ground-atmosphere light scattering was simulated through coupled radiative transfer to obtain a massive dataset with high precision and full coverage. Furthermore, the equivalent scattering distribution function model (EBRDF) under the non-proximal detection scenario was obtained, thereby characterizing the emission distribution characteristics of scattered light in different directions under specific ground-atmosphere background conditions and incident angles (as shown in Table 4).

[0082] Table 3. Statistical Table of Characteristic Parameters of Non-Limited Edge Detection Model

[0083]

[0084] Table 4 Output data of the equivalent scattering distribution function model in non-near edge detection scenarios (×10) -2 )

[0085]

[0086] Table 4 shows the hemispherical spatial distribution of scattered light under non-liminal detection scenarios with a surface albedo of 0.5, cloud top height of 8 km, cloud optical thickness of 10, rural aerosols, aerosol optical thickness of 0.03, and a solar zenith angle of 30°. The data in the table are the results of the equivalent scattering distribution function model (EBRDF) under non-liminal detection scenarios. As can be seen from Table 4, light scattering has significant variation characteristics with angle, and multiplying by the solar constant gives the radiance result.

[0087] Furthermore, based on statistical distribution patterns and physical definitions, the characteristic values ​​of eight characteristic physical quantities under the edge detection scenario were selected (as shown in Table 5). All array sets of the characteristic values ​​of the eight characteristic physical quantities were traversed, and the numerical distribution of ground-atmosphere light scattering was simulated through coupled radiative transfer to obtain a massive dataset with high precision and full coverage. Furthermore, the equivalent scattering distribution function model (EBRDF) under the edge detection scenario was obtained, thereby characterizing the emission distribution characteristics of scattered light in different directions under specific ground-atmosphere background conditions and incident angles (as shown in Table 6).

[0088] Table 5. Statistical Table of Feature Parameters of the Edge Detection Model

[0089]

[0090] Table 6 Output data of the equivalent scattering distribution function model in the edge detection scenario (×10) -2 )

[0091]

[0092]

[0093] Table 6 shows the hemispherical spatial distribution of scattered light under lip-detection conditions: surface albedo 0.7, cloud top height 2 km, cloud optical thickness 3, rural aerosols, aerosol optical thickness 0.03, and solar zenith angle 60°. The data in the table are the results of the equivalent scattering distribution function (EBRDF) model under the lip-detection scenario. As shown in Table 6, the shear height is the main influencing factor of light scattering properties; multiplying it by the solar constant yields the radiance result.

[0094] Furthermore, in this embodiment of the invention, the accuracy of the parameterization method for light scattering properties and its comparison with the complex radiative transfer calculation method were verified. After correcting the equivalent scattering distribution function model using the correction method described in this embodiment of the invention, under all detection angles, Figure 7 The average relative deviation was approximately 0.588%, and the maximum relative deviation was approximately 1.754%. Figure 8 The average relative deviation is approximately 0.257%, and the maximum relative deviation is approximately 0.502%. The results are consistent with the complex coupled radiative transfer model. Validation results are shown in [link to validation results]. Figures 7 to 8 .

[0095] In summary, in this embodiment of the invention, by fully considering the influence of environmental parameters of the land surface, atmosphere, aerosols, and clouds, as well as detection geometric parameters on light scattering, and by extracting key feature parameters for dimensionality reduction, the physical process is simplified into a functional relationship of parameters. An equivalent scattering distribution function model (EBRDF) is proposed to reduce the dimensionality of the complex coupled radiative transfer process, thereby realizing the multi-dimensional characterization of the spatiotemporal, spectral, and directional light scattering characteristics of the land-atmosphere system. This solves the problem that current methods of treating the background light scattering of the land-atmosphere system by averaging physical properties and only considering static scenes. While satisfying the spatiotemporal dynamic evolution conditions of the optical characteristics of the land surface, clouds, aerosols, and atmosphere, the computational load is reduced, and the high accuracy of the complex coupled radiative transfer calculation process is preserved.

[0096] like Figure 9 , Figure 10 As shown, this embodiment of the invention provides a device for parameterizing and characterizing the physical properties of ground-atmosphere light scattering. The device embodiment can be implemented through software, hardware, or a combination of both. From a hardware perspective, such as... Figure 9 The diagram shown is a hardware architecture diagram of a computing device housing a ground-atmosphere light scattering property parameterization characterization device provided in an embodiment of the present invention, except for... Figure 9 In addition to the processor, memory, network interface, and non-volatile memory shown, the computing device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 10 As shown, a device in a logical sense is formed by the CPU of its computing device reading the corresponding computer program from the non-volatile memory into memory and running it. This embodiment provides a device for parameterizing and characterizing the physical properties of ground-atmosphere light scattering. The device includes:

[0097] The partitioning unit 901 is used to partition the probe's detection scenarios based on the relative positions of the sun, the earth, and the probe; the detection scenarios include near-edge detection scenarios and non-near-edge detection scenarios.

[0098] The acquisition unit 902 is used to acquire geometric feature parameter values ​​and environmental feature parameter values ​​for several edge detection scenarios and non-edge detection scenarios, respectively.

[0099] Simulation unit 903 is used to traverse the array sets of geometric feature parameter values ​​and environmental feature parameter values ​​under two detection scenarios respectively, and perform coupled radiative transfer simulation on each array set to obtain the first massive database and the second massive database respectively;

[0100] The characterization unit 904 is used to obtain the equivalent scattering distribution function models for near-edge detection scenarios and non-near-edge detection scenarios based on the first massive database and the second massive database, and to perform parameterized characterization using the geo-atmosphere light scattering properties.

[0101] In this embodiment of the invention, the division unit 901 can be used to execute step 100 in the above method embodiment, the acquisition unit 902 can be used to execute step 102 in the above method embodiment, the simulation unit 903 can be used to execute step 104 in the above method embodiment, and the characterization unit 904 can be used to execute step 106 in the above method embodiment.

[0102] In one embodiment of the present invention, the partitioning unit 901, when partitioning the probe's detection scene according to the relative positions of the sun, earth, and probe, includes:

[0103] Based on the relative positions of the Sun, Earth, and the probe, a discriminant formula for the intersection of the probe's detection rays with the Earth is constructed.

[0104] The detection scene of the detector is divided according to the intersection discriminant.

[0105] If the intersection discriminant is greater than zero, then the detector's detection ray intersects with the Earth, and the current detection scene is classified as a non-near-edge detection scene.

[0106] If the intersection discriminant is less than zero, then the detector's detection ray has no intersection with the Earth, and the current detection scene is classified as an edge detection scene.

[0107] In one embodiment of the present invention, in the dividing unit 901, the discriminant formula for the intersection point of the detector's detection ray and the Earth is as follows;

[0108] Δ=(p·d) 2 -(p·pR E 2 )

[0109] In the formula, p is the coordinate position of the detector, d is the direction of the detector, and R... E The radius is the Earth's radius.

[0110] In one embodiment of the present invention, the geometric feature parameters in the edge detection scenario include the solar zenith angle, relative azimuth angle, and tangent height; the geometric feature parameters in the non-edge detection scenario include the solar zenith angle, relative azimuth angle, and observation zenith angle.

[0111] The environmental characteristic parameters in both the near-edge detection scenario and the non-near-edge scenario include surface environmental parameters, aerosol environmental parameters, and cloud environmental parameters; wherein, the surface environmental parameters include surface reflectivity, the aerosol environmental parameters include aerosol type and aerosol optical thickness, and the cloud environmental parameters include cloud top height and cloud optical thickness.

[0112] In one embodiment of the present invention, in the characterization unit 904, when the detector's detection altitude is 0-20km:

[0113] The equivalent scattering distribution function model for the edge detection scenario is as follows:

[0114] f EBRDF =f(ρ,L1,COD,AT,AOD,θ) i ,H,θ r )

[0115] The equivalent scattering distribution function model for the non-near-edge detection scenario is as follows:

[0116]

[0117] In the formula, f EBRDF and f' EBRDF ρ represents the light scattering intensity output by the equivalent scattering distribution function model for near-edge detection scenarios and non-near-edge detection scenarios, respectively; ρ is the surface reflectivity; L1 is the cloud top height; COD is the cloud optical thickness; AT is the aerosol type; AOD is the aerosol optical thickness; and θ is the cloud optical thickness. i Let θ be the solar zenith angle, H be the tangent height, and θ be the tangent height. r To observe the zenith angle, This refers to the relative azimuth angle.

[0118] In one embodiment of the present invention, when the detection altitude of the detector is 20-180km, the equivalent scattering distribution function model needs to be corrected;

[0119] The correction formula is as follows:

[0120] R = R EBRDF ·(τ+α)

[0121]

[0122] In the formula, R is the light scattering radiance value output by the corrected equivalent scattering distribution function model. EBRDF τ is the light scattering radiance value output by the equivalent scattering distribution function model under near-edge detection scenarios or non-near-edge detection scenarios, τ is the atmospheric path transmittance from 20km to the detector location, and α is the influence coefficient of atmospheric light scattering on the ground above 20km.

[0123] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on a device for parameterizing and characterizing the properties of ground-atmosphere light scattering. In other embodiments of the present invention, a device for parameterizing and characterizing the properties of ground-atmosphere light scattering may include more or fewer components than illustrated, or combine some components, split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0124] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description in the method embodiment of the present invention, and will not be repeated here.

[0125] This invention also provides a computing device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a method for parameterizing and characterizing the geo-atmosphere light scattering properties according to any embodiment of this invention.

[0126] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform a method for parameterizing and characterizing the properties of ground-atmosphere light scattering according to any embodiment of this invention.

[0127] Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the embodiments described above is stored, and the computer (or CPU or MPU) of the system or apparatus may read and execute the program code stored in the storage medium.

[0128] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of the present invention.

[0129] Examples of storage media used to provide program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0130] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating system or other components operating on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby achieving the function of any of the embodiments described above.

[0131] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0132] Embodiments of this application also provide a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement a method for parameterizing and characterizing the ground-atmosphere light scattering properties provided in the above-described method embodiments.

[0133] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0134] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for parameterizing and characterizing the physical properties of land-atmosphere light scattering, characterized in that, The method comprises the following steps: According to the relative positions of the sun, the earth and the probe, the detection scene of the probe is divided; the detection scene comprises a limb detection scene and a non-limb detection scene; Geometric feature parameter values and environmental feature parameter values in a plurality of limb detection scenes and a plurality of non-limb detection scenes are respectively obtained; Array set of the geometric feature parameter values and the environmental feature parameter values in the two detection scenes is respectively traversed, and coupled radiation transmission simulation is performed on each array set to obtain a first massive database and a second massive database respectively; According to the first massive database and the second massive database, equivalent scattering distribution function models in the limb detection scene and the non-limb detection scene are respectively obtained, and are parameterized by ground-atmosphere light scattering properties.

2. The method of claim 1, wherein, The step of dividing the detection scene of the probe according to the relative positions of the sun, the earth and the probe comprises the following steps: Based on the relative positions of the sun, the earth and the probe, a detection ray intersection discriminant of the probe with the earth is constructed; According to the intersection discriminant, the detection scene of the probe is divided; If the intersection discriminant is greater than zero, the detection ray of the probe intersects with the earth, and the current detection scene is divided into a non-limb detection scene; If the intersection discriminant is less than zero, the detection ray of the probe does not intersect with the earth, and the current detection scene is divided into a limb detection scene.

3. The method of claim 2, wherein, The intersection discriminant of the detection ray of the probe with the earth is as follows: Δ = (p · d) 2 - (p · p - R E 2 ) where p is the coordinate position of the probe, d is the direction of the probe, R E is the earth radius.

4. The method of claim 1, wherein, The geometric feature parameters in the limb detection scene comprise a solar zenith angle, a relative azimuth angle and a tangent height; the geometric feature parameters in the non-limb detection scene comprise a solar zenith angle, a relative azimuth angle and an observation zenith angle; The environmental feature parameters in the limb detection scene and the non-limb detection scene comprise ground surface environmental parameters, aerosol environmental parameters and cloud environmental parameters; the ground surface environmental parameters comprise a ground surface reflectivity, the aerosol environmental parameters comprise an aerosol type and an aerosol optical thickness, and the cloud environmental parameters comprise a cloud top height and a cloud optical thickness.

5. The method according to claim 1 or 4, characterized in that, When the detection height of the probe is 0-20 km: The equivalent scattering distribution function model in the limb detection scene is as follows: f EBRDF = f(p, L1, COD, AT, AOD, θ i , H, θ r ) The equivalent scattering distribution function model in the non-limb detection scene is as follows: In the formula, f EBRDF and f' EBRDF are the light scattering brightness output by the equivalent scattering distribution function model under the edge detection scene and the non-edge detection scene, respectively, p is the ground reflectivity, L1 is the cloud top height, COD is the cloud optical thickness, AT is the aerosol type, AOD is the aerosol optical thickness, theta i is the solar zenith angle, H is the cutting height, theta r is the observation zenith angle, is the relative azimuth angle.

6. The method of claim 5, wherein, When the detection height of the probe is 20-180 km, the equivalent scattering distribution function model needs to be modified; The modification formula is as follows: R = R EBRDF • (τ + α) In the formula, R is the light scattering radiation brightness value of the modified equivalent scattering distribution function model output, R EBRDF is the light scattering radiation brightness value of the equivalent scattering distribution function model output under the edge detection scene or the non-edge detection scene, τ is the atmospheric path transmittance from 20 km to the detector position, and α is the atmospheric influence coefficient on the ground-gas light scattering above 20 km.

7. A device for parameterizing and characterizing the physical properties of ground-atmosphere light scattering, characterized in that, The method comprises the following steps: A division unit is configured to divide the detection scene of the probe according to the relative positions of the sun, the earth and the probe; The detection scene comprises a limb detection scene and a non-limb detection scene; An acquisition unit is configured to obtain geometric feature parameter values and environmental feature parameter values in a plurality of limb detection scenes and a plurality of non-limb detection scenes respectively; An simulation unit is configured to traverse array sets of the geometric feature parameter values and the environmental feature parameter values in the two detection scenes respectively, and perform coupled radiation transmission simulation on each array set to obtain a first massive database and a second massive database respectively; The characterization unit is configured to obtain an equivalent scattering distribution function model under a boundary detection scenario and an equivalent scattering distribution function model under a non-boundary detection scenario respectively according to the first mass database and the second mass database, and to perform parameterization characterization on the ground-atmosphere light scattering properties. 8.A computing device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1-6. 9.A computer readable storage medium storing a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the method of any one of claims 1-6.

10. A computer program product, characterised in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1-6.

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