Quantitative evaluation method and device for satellite radiometric calibration field based on airship platform

Abstract

This application relates to the field of radiometric calibration technology, providing a method and apparatus for quantitative evaluation of satellite radiometric calibration fields based on an airship platform. The method includes: constructing an optimized surface directional reflectance function based on multi-angle surface reflectance data collected by an unmanned aerial vehicle (UAV) and ground-measured reference data; constructing an apparent radiance function of the top of the atmosphere based on atmospheric column data collected by the airship platform, the optimized surface directional reflectance function, and ground-measured reference data; and retrieving an evaluation index of the satellite radiometric calibration field based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value. This application effectively overcomes the shortcomings of existing technologies, such as temporal discontinuity, strong meteorological constraints, and limited spatial representativeness, achieving high-frequency, high-precision, and high-stability quantitative evaluation of the radiometric calibration field.

Description

Technical Field

[0001] This application relates to the field of radiation calibration technology, specifically to a method and apparatus for quantitative evaluation of satellite radiation calibration fields based on an airship platform. Background Technology

[0002] The key to quantitative applications of satellite remote sensing lies in the accuracy of radiometric calibration. Digital signals acquired by satellite payloads must be converted into radiance or reflectance using radiometric calibration coefficients before they can be used for surface inversion, ecological monitoring, atmospheric aerosol inversion, and climate model input. However, as time in orbit increases, the response sensitivity of satellite sensors changes due to factors such as radiation aging, optical contamination, and gain drift. Regular calibration is essential to ensure the long-term stability and cross-platform consistency of observational data. Therefore, the satellite's radiometric calibration field must also meet quantitative requirements.

[0003] However, existing methods for quantitatively evaluating radiation calibration fields still have significant shortcomings: 1. Temporal discontinuity: Most site assessments rely on synchronous observations at the time of satellite transit, which typically have a cycle of 2 to 16 days, making it difficult to reflect short-term atmospheric changes; 2. Strong meteorological constraints: Multiple meteorological effects can affect the availability of observations, leading to large fluctuations in evaluation results; 3. Limited spatial representativeness: Ground and UAV observation ranges are limited and are affected by terrain, wind speed and airflow, making it difficult to form large-scale continuous data.

[0004] In summary, existing methods for quantitative evaluation of radiation calibration fields have significant shortcomings, such as time discontinuity, strong meteorological constraints, and limited spatial representativeness, which prevent them from achieving high-frequency, high-precision, and high-stability quantitative evaluation of radiation calibration fields. Summary of the Invention

[0005] This application provides a method and apparatus for quantitative evaluation of satellite radiometric calibration fields based on an airship platform, which solves the technical problem that existing methods for quantitative evaluation of radiometric calibration fields have significant shortcomings such as time discontinuity, strong meteorological constraints, and limited spatial representativeness, and cannot achieve high-frequency, high-precision, and high-stability quantitative evaluation of radiometric calibration fields.

[0006] In a first aspect, embodiments of this application provide a method for quantitative evaluation of satellite radiation calibration fields based on an airship platform, including: The system acquires atmospheric column data from the satellite radiometric calibration field, multi-angle surface reflectance data, and ground-measured benchmark data; the atmospheric column data is collected by an airship platform, and the multi-angle surface reflectance data is collected by an unmanned aerial vehicle (UAV). Based on the multi-angle surface reflectance data and the ground measured reference data, a surface directional reflectance optimization function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured benchmark data, an atmospheric top apparent radiance function is constructed. The evaluation index of the satellite radiometric calibration field is inverted based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

[0007] In one embodiment, the ground-measured reference data includes surface reference reflectance; the step of constructing a surface directional reflectance optimization function based on the multi-angle surface reflectance data and the ground-measured reference data includes: Based on the multi-angle surface reflectance data, the bidirectional reflectance distribution function is inverted to obtain the surface directional reflectance function. Based on the surface reference reflectance, the surface directional reflectance function is modified to obtain the surface directional reflectance optimization function.

[0008] In one embodiment, the ground-based measured reference data includes direct solar radiation reference values; the construction of the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-based measured reference data includes: By inputting the atmospheric column data, the optimized surface directional reflectance function, and the direct solar radiation reference value into the radiative transfer model, the apparent radiance function of the top of the atmosphere is obtained.

[0009] In one embodiment, the evaluation index for retrieving the satellite radiometric calibration field based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite's measured value includes: With the goal of minimizing the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiation calibration field are retrieved. Based on the radiation uniformity index, the temporal stability index, and the atmospheric suitability index, the evaluation index of the satellite radiation calibration field is calculated.

[0010] In one embodiment, the radiation uniformity index value is calculated based on the average and standard deviation of the multi-angle surface reflectance data in the spatial dimension; The temporal stability index value is calculated based on the average value of the multi-angle surface reflectance data over time and the number of observations. The atmospheric suitability index value is calculated based on the standard deviation of the atmospheric column data over time.

[0011] In one embodiment, after inverting the evaluation index of the satellite radiometric calibration field, the following is included: The evaluation index within the target time period is smoothed to obtain the time series curve of the evaluation index.

[0012] Secondly, embodiments of this application provide a satellite radiation calibration field quantitative evaluation device based on an airship platform, comprising: The multi-source data acquisition module is used to acquire atmospheric column data, multi-angle surface reflectance data, and ground-measured reference data from the satellite radiometric calibration field; the atmospheric column data is collected by the airship platform, and the multi-angle surface reflectance data is collected by the UAV. The reflectance function construction module is used to: construct an optimized surface directional reflectance function based on the multi-angle surface reflectance data and the ground measured reference data; The radiance function construction module is used to: construct the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the optimized surface directional reflectance function, and the ground measured reference data; The calibration field quantitative evaluation module is used to: invert the evaluation index of the satellite radiation calibration field based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

[0013] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the computer program to implement the steps of the quantitative evaluation method for satellite radiation calibration fields based on an airship platform as described in the first aspect.

[0014] Fourthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the quantitative evaluation method for satellite radiation calibration fields based on an airship platform as described in the first aspect.

[0015] Fifthly, embodiments of this application provide a non-transitory computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the quantitative evaluation method for satellite radiation calibration fields based on an airship platform as described in the first aspect.

[0016] The method and apparatus for quantitative evaluation of satellite radiometric calibration fields based on an airship platform provided in this application acquire atmospheric column data, multi-angle surface reflectance data, and ground-measured reference data of the satellite radiometric calibration field. The atmospheric column data is collected by the airship platform, and the multi-angle surface reflectance data is collected by an unmanned aerial vehicle (UAV). Based on the multi-angle surface reflectance data and the ground-measured reference data, an optimized surface directional reflectance function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured reference data, an apparent radiance function of the top of the atmosphere is constructed. Based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value, the evaluation index of the satellite radiometric calibration field is inverted. This application utilizes atmospheric column data continuously collected by an airship platform over a calibration field, combined with ground-measured benchmark data and multi-angle surface reflectance data collected by UAVs. Starting with an optimized surface directional reflectance function, an apparent radiance function of the atmospheric top is constructed. Based on the deviation between the output value of the apparent radiance function and the satellite's measured value, an evaluation index of the satellite radiometric calibration field can be derived, enabling a quantitative evaluation of the satellite radiometric calibration field. The airship platform, as a near-space observation platform capable of long-duration loitering, stable attitude, and carrying multiple types of sensors, can, on the one hand, operate continuously for hours to days within its operating altitude range, continuously monitoring various key atmospheric column data based on a real-time observation channel constructed at the altitude between the ground and the satellite. On the other hand, it possesses strong wind resistance and wide-area spatial coverage capabilities, forming an integrated "ground-atmosphere-space" observation chain with ground and UAVs. This effectively overcomes the shortcomings of existing technologies, such as temporal discontinuity, strong meteorological constraints, and limited spatial representativeness, achieving high-frequency, high-precision, and high-stability quantitative evaluation of the radiometric calibration field. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this application 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the quantitative evaluation method for satellite radiation calibration fields based on an airship platform provided in this application embodiment; Figure 2 This is a schematic diagram of the vertical observation relationship between the ground, UAV, airship platform and satellite provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the satellite radiation calibration field quantitative evaluation device based on the airship platform provided in the embodiments of this application; Figure 4This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] It should be noted that in the description of the embodiments of this application, 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 includes 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. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The terms "upper," "lower," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly, for example, they can be fixed connections, detachable connections, or integral connections; they can be mechanical connections or electrical connections; they can be direct connections or indirect connections through an intermediate medium; and they can be internal connections between two elements. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0021] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects have an "or" relationship.

[0022] Figure 1 This is a flowchart illustrating the quantitative evaluation method for satellite radiometric calibration fields based on an airship platform provided in this application. (Refer to...) Figure 1 This application provides a method for quantitative evaluation of satellite radiometric calibration fields based on an airship platform, which may include: Step 101: Obtain atmospheric column data, multi-angle surface reflectance data, and ground-measured reference data from the satellite radiometric calibration field; Atmospheric column data were collected by an airship platform, while multi-angle surface reflectance data were collected by drones. Step 102: Based on multi-angle surface reflectance data and ground-measured benchmark data, construct an optimization function for surface directional reflectance; Step 103: Based on atmospheric column data, surface directional reflectance optimization function, and ground-measured benchmark data, construct the apparent radiance function of the top of the atmosphere; Step 104: Based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, invert the evaluation index of the satellite radiative calibration field.

[0023] In step 101, the airship platform can be deployed above the satellite radiometric calibration field and equipped with various sensors to collect various atmospheric column data. The specific number, type, and corresponding atmospheric column data of the sensors are not limited here. In this embodiment, it can be equipped with an aerosol radiometer, a solar photometer, and a spectrometer. The aerosol radiometer can be used to collect aerosol optical thickness, the solar photometer can be used to collect water vapor content, and the spectrometer can be used to collect ozone column concentration. That is, the atmospheric column data includes aerosol optical thickness, water vapor content, and ozone column concentration.

[0024] Furthermore, the airship platform can adopt a helium-filled buoyancy system, with a hovering altitude of 3 to 30 kilometers, an attitude stability accuracy better than ±0.5 degrees, and a loiter time of not less than 24 hours; the airship platform is equipped with an automatic attitude control and data transmission system, with a sampling frequency of 1 minute / time to 5 minutes / time.

[0025] The drone can fly around at multiple angles within an altitude range of 100 to 500 meters to collect hyperspectral reflectance data of the ground surface.

[0026] Ground-based benchmark data can be obtained by collecting standard equipment deployed on the ground.

[0027] In step 102, the multi-angle surface reflectance data can be expressed as: ,in For wavelength, The zenith angle of the sun. For the sensor zenith angle, If it is a relative azimuth angle, then Related to observation geometry, an optimized function for surface directional reflectance can be constructed by combining ground-based measured benchmark data.

[0028] In step 103, since the apparent radiance of the top of the atmosphere is related to various factors such as atmospheric effects, surface reflection characteristics, and observation geometry, the apparent radiance function of the top of the atmosphere can be constructed by using atmospheric column data that characterizes atmospheric effects, the surface directional reflectance optimization function that characterizes the relationship between surface reflection characteristics and observation geometry, and ground-measured benchmark data.

[0029] In step 104, the representativeness of the satellite radiometric calibration field can be assessed based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value. The evaluation index of the satellite radiometric calibration field can be continuously adjusted based on the good representativeness.

[0030] This embodiment provides a quantitative evaluation method for satellite radiometric calibration fields based on an airship platform. It acquires atmospheric column data, multi-angle surface reflectance data, and ground-measured benchmark data for the satellite radiometric calibration field. The atmospheric column data is collected by the airship platform, and the multi-angle surface reflectance data is collected by an unmanned aerial vehicle (UAV). Based on the multi-angle surface reflectance data and the ground-measured benchmark data, an optimized surface directional reflectance function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured benchmark data, an apparent radiance function at the top of the atmosphere is constructed. Based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, the evaluation index of the satellite radiometric calibration field is retrieved. In this embodiment, atmospheric column data continuously collected by an airship platform over the calibration field is combined with ground-measured benchmark data and multi-angle surface reflectance data collected by UAVs. Starting from constructing an optimized surface directional reflectance function, an apparent radiance function of the top of the atmosphere is constructed. Based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite's measured value, an evaluation index of the satellite radiometric calibration field can be obtained, achieving a quantitative evaluation of the satellite radiometric calibration field. As a near-space observation platform capable of long-term loitering, stable attitude, and carrying multiple types of sensors, the airship platform can, on the one hand, operate continuously for hours to days within its working altitude range, continuously monitoring various key atmospheric column data based on a real-time observation channel constructed at the altitude between the ground and the satellite. On the other hand, it possesses strong wind resistance and wide-area spatial coverage capabilities, forming an integrated "ground-atmosphere-space" observation chain with ground and UAVs. This effectively overcomes the shortcomings of existing technologies, such as time discontinuity, strong meteorological constraints, and limited spatial representativeness, achieving a high-frequency, high-precision, and high-stability quantitative evaluation of the radiometric calibration field.

[0031] In one embodiment, the ground-measured reference data may include the surface reference reflectance; step 102 may include: Based on multi-angle surface reflectance data, the bidirectional reflectance distribution function is inverted to obtain the surface directional reflectance function. Based on the surface reference reflectance, the surface directional reflectance function is corrected to obtain the optimized surface directional reflectance function.

[0032] The ground reference reflectance can be obtained by collecting data from standard reflectors deployed on the ground. The bidirectional reflectance distribution function is inverted using the Ross Thick-LiSparse R (Ross Thick Kernel-Li Sparse Reciprocal Kernel) method. The Ross Thick Kernel is based on the assumption of "optical thickness" of the vegetation canopy, meaning the canopy is sufficiently dense, the contribution of soil transmission is negligible, and surface reflection is dominated by multiple volume scattering. Its core function is to characterize the volume scattering properties of vegetation elements (leaves, stems). The kernel function of the Ross Thick Kernel... It can accurately reproduce the hotspot effect (when the sun coincides with the observation direction, the disappearance of shadows leads to a sudden increase in reflectivity), and is suitable for dense vegetation scenarios such as grasslands, farmland, and broad-leaved forests. The Lie's sparse reciprocal kernel targets "optically sparse" canopies (such as savannahs, early crops, and sparse shrubs), where the soil background contributes significantly. The self-shading and mutual shading of the vegetation's three-dimensional structure are the core sources of reflectivity anisotropy. Based on a rigorous geometrical optics derivation of a randomly distributed cylinder, it precisely describes the interaction between vegetation and soil by integrating and analyzing shadow length, projected area, and the proportion of visible soil. The kernel function of the Lie's sparse reciprocal kernel... Including elliptic integral approximation and geometric constraints, it can effectively fit the bidirectional reflection distribution characteristics of sparse vegetation-soil mixed scenes. The "reciprocity" property ensures that the model satisfies the optical path reversibility and improves the inversion stability. The Ross thick kernel-Lee sparse reciprocal kernel can achieve dual-kernel complementarity: the Ross thick kernel is responsible for the canopy reflection dominated by volume scattering, and the Lee sparse reciprocal kernel is responsible for the soil-vegetation interaction dominated by geometric shadow. The combination of the two can comprehensively cover vegetation types from sparse to dense, and the data fitting ability and inversion stability are significantly better than the single kernel model.

[0033] The bidirectional reflection distribution function can be expressed as follows: ; in, Let be the surface reflectance in the function. , , These are the isotropic component, the volume scattering component, and the geometric scattering component, respectively. , For the corresponding kernel function.

[0034] Then, based on the multi-angle surface reflectance data collected by the drone, the... , , By performing inversion, we obtain the surface directional reflectance function represented by the above equation. This surface directional reflectance function can describe the surface reflectance under any... The combined surface reflectance can describe the directional reflection characteristics of the surface under different observation geometries.

[0035] Furthermore, to improve the accuracy of the surface directional reflectivity function, the following formula can be used... After correction, the surface directional reflectance optimization function is obtained. : ; in, The reference reflectance of the Earth's surface. For the Earth's surface under different observation geometry The average value.

[0036] This embodiment uses multi-angle surface reflectance data collected by UAVs to perform parameter inversion on the bidirectional reflectance distribution function, obtaining a surface directional reflectance function that can describe the directional reflectance characteristics of the surface under different observation geometries. Based on the surface reference reflectance, it is corrected to obtain an optimized surface directional reflectance function, thereby enabling a more accurate description of the directional reflectance characteristics of the surface under different observation geometries.

[0037] In one embodiment, the ground-based measured reference data includes direct solar radiation reference values; step 103 may include: By inputting atmospheric column data, the optimized surface directional reflectance function, and the reference value of direct solar radiation into the radiative transfer model, the apparent radiance function of the top of the atmosphere is obtained.

[0038] The direct solar reference radiation value can be obtained by a solar standard radiometer deployed on the ground, and any radiation transfer model can be used, without limitation. In this embodiment, MODTRAN (MODerateresolution atmospheric TRANsmission) or 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) can be used.

[0039] The radiative transfer model can be represented as follows: ; in, The apparent radiance of the top of the atmosphere. Atmospheric transmittance, determined from atmospheric column data. This is the reference value for direct solar radiation. This refers to atmospheric path radiation.

[0040] Since the input data for the radiative transfer model can be collected at different times, the apparent radiance function of the top of the atmosphere obtained by combining the surface directional reflectance optimization function to characterize the data under different observation geometries can describe the radiative performance of the satellite radiative calibration field under different observation geometries and at different times.

[0041] This embodiment is based on a radiative transfer model, which integrates atmospheric column data, surface directional reflectivity optimization function, and direct solar reference radiation value to construct an apparent radiance function of the top of the atmosphere, which can accurately describe the radiation performance of the satellite radiation calibration field under different observation geometries and different time periods.

[0042] In one embodiment, step 104 may include: With the goal of minimizing the deviation between the output value of the apparent radiance function at the top of the atmosphere and the measured value from the satellite, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiometric calibration field are retrieved. Based on the radiation uniformity index, temporal stability index, and atmospheric suitability index, the evaluation index of the satellite radiometric calibration field is calculated.

[0043] Assuming the output value of the apparent radiance function at the top of the atmosphere is Satellite measured value Then the deviation between the two It can be represented as: ; It can be set based on actual needs. The threshold value is not limited here; in this embodiment, the threshold value can be set to 2%, then if When the value is greater than or equal to 2%, the observation geometry and / or time period are continuously adjusted to update the input of the apparent radiance function at the top of the atmosphere, thereby obtaining a new output value, and the calculation is repeated. until If the value is less than 2%, it can be considered that the minimum value has been reached. In this case, the satellite radiometric calibration field has the best satellite observation representativeness in the current observation geometry and / or the current time period, that is, the adaptability and consistency of satellite payload calibration have reached the best.

[0044] Furthermore, the radiation uniformity index is calculated based on the average and standard deviation of multi-angle surface reflectance data in the spatial dimension; the temporal stability index is calculated based on the average and number of observations of multi-angle surface reflectance data in the temporal dimension; and the atmospheric suitability index is calculated based on the standard deviation of atmospheric column data in the temporal dimension. Therefore: 1. The radiation uniformity index value can be calculated based on the following formula. This index value characterizes the uniformity of the spatial distribution of reflectivity in the calibration field: ; in, The standard deviation of multi-angle surface reflectance data within the calibration field; This represents the average value of multi-angle surface reflectance data within the calibration field. The closer a value is to 1, the more uniform the surface reflectivity of the calibration site, making it suitable as a satellite radiometric calibration area.

[0045] 2. The time series stability index value can be calculated based on the following formula. Used to measure the stability of the calibration field over different time periods: ; in, For a certain period of time, the drone's first The surface reflectance was collected in the second sample. This refers to the number of times the drone collected surface reflectance data during that period. This represents the average surface reflectance collected multiple times by the drone within that time period. It is typically assessed using several consecutive days or months as a time period. ,but The higher the value, the stronger the radiation stability of the calibration field under diurnal or seasonal variations.

[0046] 3. The atmospheric suitability index value can be calculated based on the following formula. Used to assess the availability of atmospheric conditions in the calibration field: ; in, The standard deviation of the aerosol optical thickness collected multiple times by the airship within a certain period is given. This represents the standard deviation of water vapor content collected by the airship multiple times during this period. This represents the standard deviation of the ozone column concentration collected by the airship multiple times during this period. This is an empirical coefficient. The closer the value is to 1, the more stable the atmosphere is, making it suitable for calibration observations.

[0047] when When it is less than 2%, it means , and All criteria were met, meaning that the satellite's radiometric calibration field met the requirements for radiometric uniformity, temporal stability, and atmospheric applicability.

[0048] Furthermore, the evaluation index of the satellite's radiometric calibration field can be calculated based on the following formula. : ; in, , and Let be the weighting coefficient, satisfying .

[0049] This embodiment aims to minimize the deviation between the output value of the apparent radiance function at the top of the atmosphere and the measured value from the satellite. It retrieves the input data of the apparent radiance function at the top of the atmosphere, thereby calculating the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiometric calibration field based on the input data. Then, it calculates the evaluation index of the satellite radiometric calibration field based on these index values, realizing a comprehensive evaluation of the calibration field under multiple time periods and multiple geometric conditions and multiple dimensions. By establishing a comprehensive quantitative evaluation index, it is possible to achieve comprehensive scoring, classification, and suitability ranking of the calibration field, providing scientific support for the site selection and long-term performance monitoring of the satellite calibration field.

[0050] In one embodiment, after step 104, the following may be included: The evaluation index within the target period is smoothed to obtain the time series curve of the evaluation index.

[0051] The evaluation index within the target time period can be smoothed using any method, and no particular method is specified here. In this embodiment, a sliding time window or an index-weighted moving average can be used to smooth the evaluation index within the target time period. The specific formula is as follows: ; in, For the first The evaluation index after smoothing the time period. As the response factor, For the first Evaluation index before smoothing of time periods. For the first Evaluation index after smoothing of time periods.

[0052] Furthermore, the time series curves of the evaluation index can be visualized and updated and automated at the minute or hour level to monitor changes in the calibration field status, thereby achieving automated and dynamic high-frequency radiation field evaluation.

[0053] Reference Figure 2 In one embodiment, the quantitative evaluation method for satellite radiation calibration fields based on an airship platform of this application is briefly described as follows: Sunlight strikes the Earth's surface from top to bottom, and after reflection and scattering, it is received by satellites; airship platforms collect atmospheric column data in real time, including atmospheric radiation parameters such as aerosol optical thickness, water vapor content, and ozone column concentration; drones collect hyperspectral reflectance data of the Earth's surface from multiple angles in real time; ground observations collect ground-measured reference data, including reference surface reflectance and reference direct solar radiation values. The data center acquires atmospheric column data, multi-angle hyperspectral reflectance data of the surface from the satellite radiometric calibration field, and ground-measured reference data. Based on the multi-angle surface reflectance data and the surface reference reflectance, an optimized surface directional reflectance function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the direct solar radiation reference value, an apparent radiance function of the top of the atmosphere is constructed. Based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiometric calibration field are retrieved, and thus the evaluation index is obtained.

[0054] This embodiment has the following significant advantages: 1. High frequency and continuity: Continuous observation of the atmosphere and the earth's surface is achieved through airship platforms, drones, and ground observations, breaking through the limitations of satellite overpasses and supporting minute-level or hour-level evaluation updates; 2. Comprehensive Quantification: Establish a multi-dimensional index system to systematically evaluate the radiation uniformity, temporal stability, and atmospheric applicability of the calibration field; 3. High authenticity and representativeness: The measured atmospheric parameters of the airship improve the accuracy of radiative transfer calculation, making the evaluation results closer to the actual observation environment; 4. Automation and scalability: The system can operate around the clock and supports parallel monitoring and long-term trend analysis at multiple sites; 5. Satellite compatibility analysis: Through function-satellite comparison, the calibration consistency between different satellite payloads is assessed.

[0055] In summary, this embodiment establishes a dynamic evaluation technology for radiometric calibration fields that is timely, accurate, and quantifiable, providing new technical support for the site selection, operation and maintenance, and performance verification of satellite on-orbit calibration fields.

[0056] The following describes the satellite radiation calibration field quantitative evaluation device based on the airship platform provided in the embodiments of this application. The satellite radiation calibration field quantitative evaluation device based on the airship platform described below can be referred to in correspondence with the satellite radiation calibration field quantitative evaluation method based on the airship platform described above.

[0057] Figure 3 This is a schematic diagram of the structure of the satellite radiation calibration field quantitative evaluation device based on an airship platform provided in this application embodiment. (Refer to...) Figure 3 This application provides a satellite radiometric calibration field quantitative evaluation device based on an airship platform, which may include: The multi-source data acquisition module 301 is used to: acquire atmospheric column data, multi-angle surface reflectance data, and ground-measured reference data from the satellite radiometric calibration field; the atmospheric column data is collected by the airship platform, and the multi-angle surface reflectance data is collected by the UAV. The reflectance function construction module 302 is used to: construct a surface directional reflectance optimization function based on the multi-angle surface reflectance data and the ground measured reference data; The radiance function construction module 303 is used to: construct the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the surface directional reflectance optimization function, and the ground measured reference data; The calibration field quantitative evaluation module 304 is used to: invert the evaluation index of the satellite radiation calibration field based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

[0058] The satellite radiometric calibration field quantitative evaluation device based on an airship platform provided in this embodiment acquires atmospheric column data, multi-angle surface reflectance data, and ground-measured reference data of the satellite radiometric calibration field. The atmospheric column data is collected by the airship platform, and the multi-angle surface reflectance data is collected by an unmanned aerial vehicle (UAV). Based on the multi-angle surface reflectance data and the ground-measured reference data, an optimized surface directional reflectance function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured reference data, an apparent radiance function of the top of the atmosphere is constructed. Based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value, the evaluation index of the satellite radiometric calibration field is inverted. In this embodiment, atmospheric column data continuously collected by an airship platform over the calibration field is combined with ground-measured benchmark data and multi-angle surface reflectance data collected by UAVs. Starting from constructing an optimized surface directional reflectance function, an apparent radiance function of the top of the atmosphere is constructed. Based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite's measured value, an evaluation index of the satellite radiometric calibration field can be obtained, achieving a quantitative evaluation of the satellite radiometric calibration field. As a near-space observation platform capable of long-term loitering, stable attitude, and carrying multiple types of sensors, the airship platform can, on the one hand, operate continuously for hours to days within its working altitude range, continuously monitoring various key atmospheric column data based on a real-time observation channel constructed at the altitude between the ground and the satellite. On the other hand, it possesses strong wind resistance and wide-area spatial coverage capabilities, forming an integrated "ground-atmosphere-space" observation chain with ground and UAVs. This effectively overcomes the shortcomings of existing technologies, such as time discontinuity, strong meteorological constraints, and limited spatial representativeness, achieving a high-frequency, high-precision, and high-stability quantitative evaluation of the radiometric calibration field.

[0059] In one embodiment, the ground-measured reference data includes the surface reference reflectance; the reflectance function construction module 302 is specifically used for: Based on the multi-angle surface reflectance data, the bidirectional reflectance distribution function is inverted to obtain the surface directional reflectance function. Based on the surface reference reflectance, the surface directional reflectance function is modified to obtain the surface directional reflectance optimization function.

[0060] In one embodiment, the ground-based measured reference data includes direct solar radiation reference values; the radiance function construction module 303 is specifically used for: By inputting the atmospheric column data, the optimized surface directional reflectance function, and the direct solar radiation reference value into the radiative transfer model, the apparent radiance function of the top of the atmosphere is obtained.

[0061] In one embodiment, the calibration field quantitative evaluation module 304 is specifically used for: With the goal of minimizing the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiation calibration field are retrieved. The evaluation index of the satellite radiometric calibration field is calculated based on the radiation uniformity index, the temporal stability index, and the atmospheric suitability index.

[0062] In one embodiment, the radiation uniformity index value is calculated based on the average and standard deviation of the multi-angle surface reflectance data in the spatial dimension; The temporal stability index value is calculated based on the average value of the multi-angle surface reflectance data over time and the number of observations. The atmospheric suitability index value is calculated based on the standard deviation of the atmospheric column data over time.

[0063] In one embodiment, an exponential smoothing processing module (not shown in the figure) is further included for: The evaluation index within the target time period is smoothed to obtain the time series curve of the evaluation index.

[0064] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 can call the computer program in the memory 430 to execute the steps of the quantitative evaluation method for satellite radiometric calibration fields based on the airship platform, such as including: The system acquires atmospheric column data from the satellite radiometric calibration field, multi-angle surface reflectance data, and ground-measured benchmark data; the atmospheric column data is collected by an airship platform, and the multi-angle surface reflectance data is collected by an unmanned aerial vehicle (UAV). Based on the multi-angle surface reflectance data and the ground measured reference data, a surface directional reflectance optimization function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured benchmark data, an atmospheric top apparent radiance function is constructed. The evaluation index of the satellite radiometric calibration field is inverted based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

[0065] Furthermore, the ground-measured reference data includes the ground-based reference reflectance; the step of constructing a ground-based directional reflectance optimization function based on the multi-angle ground-based reflectance data and the ground-measured reference data includes: Based on the multi-angle surface reflectance data, the parameters of the bidirectional reflectance distribution function are inverted to obtain the surface directional reflectance function. Based on the surface reference reflectance, the surface directional reflectance function is modified to obtain the surface directional reflectance optimization function.

[0066] Furthermore, the ground-based measured reference data includes the direct solar radiation reference value; the construction of the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-based measured reference data includes: By inputting the atmospheric column data, the optimized surface directional reflectance function, and the direct solar radiation reference value into the radiative transfer model, the apparent radiance function of the top of the atmosphere is obtained.

[0067] Furthermore, the evaluation index for retrieving the satellite radiative calibration field based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite's measured value includes: With the goal of minimizing the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiation calibration field are retrieved. Based on the radiation uniformity index, temporal stability index, and atmospheric suitability index, the evaluation index of the satellite radiation calibration field is calculated.

[0068] Furthermore, the radiation uniformity index value is calculated based on the average value and standard deviation of the multi-angle surface reflectance data in the spatial dimension; The temporal stability index value is calculated based on the average value of the multi-angle surface reflectance data over time and the number of observations. The atmospheric suitability index value is calculated based on the standard deviation of the atmospheric column data over time.

[0069] Furthermore, the evaluation index within the target time period is smoothed to obtain the time series curve of the evaluation index.

[0070] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0071] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the quantitative evaluation method for satellite radiometric calibration fields based on an airship platform provided in the above embodiments, such as including: The system acquires atmospheric column data from the satellite radiometric calibration field, multi-angle surface reflectance data, and ground-measured benchmark data; the atmospheric column data is collected by an airship platform, and the multi-angle surface reflectance data is collected by an unmanned aerial vehicle (UAV). Based on the multi-angle surface reflectance data and the ground measured reference data, a surface directional reflectance optimization function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured benchmark data, an atmospheric top apparent radiance function is constructed. The evaluation index of the satellite radiometric calibration field is inverted based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

[0072] Furthermore, the ground-measured reference data includes the ground-based reference reflectance; the step of constructing a ground-based directional reflectance optimization function based on the multi-angle ground-based reflectance data and the ground-measured reference data includes: Based on the multi-angle surface reflectance data, the parameters of the bidirectional reflectance distribution function are inverted to obtain the surface directional reflectance function. Based on the surface reference reflectance, the surface directional reflectance function is modified to obtain the surface directional reflectance optimization function.

[0073] Furthermore, the ground-based measured reference data includes the direct solar radiation reference value; the construction of the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-based measured reference data includes: By inputting the atmospheric column data, the optimized surface directional reflectance function, and the direct solar radiation reference value into the radiative transfer model, the apparent radiance function of the top of the atmosphere is obtained.

[0074] Furthermore, the evaluation index for retrieving the satellite radiative calibration field based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite's measured value includes: With the goal of minimizing the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiation calibration field are retrieved. Based on the radiation uniformity index, temporal stability index, and atmospheric suitability index, the evaluation index of the satellite radiation calibration field is calculated.

[0075] Furthermore, the radiation uniformity index value is calculated based on the average value and standard deviation of the multi-angle surface reflectance data in the spatial dimension; The temporal stability index value is calculated based on the average value of the multi-angle surface reflectance data over time and the number of observations. The atmospheric suitability index value is calculated based on the standard deviation of the atmospheric column data over time.

[0076] Furthermore, the evaluation index within the target time period is smoothed to obtain the time series curve of the evaluation index.

[0077] On the other hand, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program thereon, the computer program being used to cause a processor to execute the steps of the quantitative evaluation method for satellite radiometric calibration fields based on an airship platform provided in the above embodiments, for example including: The system acquires atmospheric column data from the satellite radiometric calibration field, multi-angle surface reflectance data, and ground-measured benchmark data; the atmospheric column data is collected by an airship platform, and the multi-angle surface reflectance data is collected by an unmanned aerial vehicle (UAV). Based on the multi-angle surface reflectance data and the ground measured reference data, a surface directional reflectance optimization function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured benchmark data, an atmospheric top apparent radiance function is constructed. The evaluation index of the satellite radiometric calibration field is inverted based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

[0078] Furthermore, the ground-measured reference data includes the ground-based reference reflectance; the step of constructing a ground-based directional reflectance optimization function based on the multi-angle ground-based reflectance data and the ground-measured reference data includes: Based on the multi-angle surface reflectance data, the parameters of the bidirectional reflectance distribution function are inverted to obtain the surface directional reflectance function. Based on the surface reference reflectance, the surface directional reflectance function is modified to obtain the surface directional reflectance optimization function.

[0079] Furthermore, the ground-based measured reference data includes the direct solar radiation reference value; the construction of the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-based measured reference data includes: By inputting the atmospheric column data, the optimized surface directional reflectance function, and the direct solar radiation reference value into the radiative transfer model, the apparent radiance function of the top of the atmosphere is obtained.

[0080] Furthermore, the evaluation index for retrieving the satellite radiative calibration field based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite's measured value includes: With the goal of minimizing the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiation calibration field are retrieved. Based on the radiation uniformity index, temporal stability index, and atmospheric suitability index, the evaluation index of the satellite radiation calibration field is calculated.

[0081] Furthermore, the radiation uniformity index value is calculated based on the average value and standard deviation of the multi-angle surface reflectance data in the spatial dimension; The temporal stability index value is calculated based on the average value of the multi-angle surface reflectance data over time and the number of observations. The atmospheric suitability index value is calculated based on the standard deviation of the atmospheric column data over time.

[0082] Furthermore, the evaluation index within the target time period is smoothed to obtain the time series curve of the evaluation index.

[0083] The non-transitory computer-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0084] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0085] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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. Such 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 this application.

Claims

1. A method for quantitative evaluation of satellite radiometric calibration fields based on an airship platform, characterized in that, include: Acquire atmospheric column data of satellite radiometric calibration field, multi-angle surface reflectance data, and ground-measured reference data; The atmospheric column data was collected by the airship platform, and the multi-angle surface reflectance data was collected by the UAV. Based on the multi-angle surface reflectance data and the ground measured reference data, a surface directional reflectance optimization function is constructed. Based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-measured benchmark data, an atmospheric top apparent radiance function is constructed. The evaluation index of the satellite radiometric calibration field is inverted based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

2. The method for quantitative evaluation of satellite radiometric calibration fields based on an airship platform according to claim 1, characterized in that, The measured ground reference data includes the ground reference reflectance; the construction of the ground directional reflectance optimization function based on the multi-angle ground reflectance data and the measured ground reference data includes: Based on the multi-angle surface reflectance data, the bidirectional reflectance distribution function is inverted to obtain the surface directional reflectance function. Based on the surface reference reflectance, the surface directional reflectance function is modified to obtain the surface directional reflectance optimization function.

3. The method for quantitative evaluation of satellite radiometric calibration fields based on an airship platform according to claim 1, characterized in that, The ground-based measured reference data includes the direct solar radiation reference value; the construction of the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the optimized surface directional reflectance function, and the ground-based measured reference data includes: By inputting the atmospheric column data, the optimized surface directional reflectance function, and the direct solar radiation reference value into the radiative transfer model, the apparent radiance function of the top of the atmosphere is obtained.

4. The method for quantitative evaluation of satellite radiation calibration fields based on an airship platform according to claim 1, characterized in that, The evaluation index for retrieving the satellite radiometric calibration field based on the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite's measured value includes: With the goal of minimizing the deviation between the output value of the apparent radiance function at the top of the atmosphere and the satellite measured value, the radiation uniformity index, temporal stability index, and atmospheric suitability index of the satellite radiation calibration field are retrieved. The evaluation index of the satellite radiometric calibration field is calculated based on the radiation uniformity index, the temporal stability index, and the atmospheric suitability index.

5. The method for quantitative evaluation of satellite radiometric calibration fields based on an airship platform according to claim 4, characterized in that, The radiation uniformity index value is calculated based on the average value and standard deviation of the multi-angle surface reflectance data in the spatial dimension; The temporal stability index value is calculated based on the average value of the multi-angle surface reflectance data over time and the number of observations. The atmospheric suitability index value is calculated based on the standard deviation of the atmospheric column data over time.

6. The method for quantitative evaluation of satellite radiometric calibration fields based on an airship platform according to claim 1, characterized in that, After retrieving the evaluation index of the satellite radiometric calibration field, the following is included: The evaluation index within the target time period is smoothed to obtain the time series curve of the evaluation index.

7. A quantitative evaluation device for satellite radiation calibration fields based on an airship platform, characterized in that, include: The multi-source data acquisition module is used to acquire atmospheric column data from the satellite radiometric calibration field, multi-angle surface reflectance data, and ground-measured reference data. The atmospheric column data was collected by the airship platform, and the multi-angle surface reflectance data was collected by the UAV. The reflectance function construction module is used to: construct an optimized surface directional reflectance function based on the multi-angle surface reflectance data and the ground measured reference data; The radiance function construction module is used to: construct the apparent radiance function of the top of the atmosphere based on the atmospheric column data, the optimized surface directional reflectance function, and the ground measured reference data; The calibration field quantitative evaluation module is used to: invert the evaluation index of the satellite radiation calibration field based on the deviation between the output value of the apparent radiance function of the top of the atmosphere and the satellite measured value.

8. An electronic device comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the quantitative evaluation method for satellite radiation calibration field based on an airship platform as described in any one of claims 1 to 6.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the quantitative evaluation method for satellite radiation calibration fields based on an airship platform as described in any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the quantitative evaluation method for satellite radiation calibration fields based on an airship platform as described in any one of claims 1 to 6.

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