Satellite on-orbit radiometric calibration methods, devices and electronic equipment

Abstract

The present disclosure provides a satellite in-orbit radiation calibration method, device and electronic equipment, comprising: obtaining a set of atmospheric parameters associated with a calibration field; using the set of atmospheric parameters and a first image data set of a first satellite sensor in the calibration field area, constructing a bidirectional reflectance distribution function model of the calibration field; according to the center wavelength of each channel in the first satellite sensor, linearly interpolating the coefficients of the bidirectional reflectance distribution function model to obtain a target model with target coefficients, wherein the target model is a spectrally continuous bidirectional reflectance distribution function model; using a second image data set of a second satellite sensor in the calibration field area, the set of atmospheric parameters and the target model, determining the correction relationship between the simulated apparent radiance simulated by the target model and the actual apparent radiance; using a third image data set of a satellite sensor to be calibrated in the calibration field area, the set of atmospheric parameters, the target model and the correction relationship to calculate the radiation calibration coefficient of the satellite sensor to be calibrated.

Description

Technical Field

[0001] This disclosure relates to the field of satellite calibration technology, and more specifically, to a satellite on-orbit radiometric calibration method, apparatus, and electronic equipment. Background Technology

[0002] On-orbit radiometric calibration of satellite sensors is a prerequisite for the quantitative application of remote sensing data, and the absolute radiometric calibration accuracy of satellite sensors directly affects the accuracy of quantitative inversion of remote sensing parameters. For domestically produced satellites carrying solar reflectance spectrum sensors, they typically lack onboard calibrators, making it difficult to achieve operational on-orbit radiometric calibration as is the case with foreign satellite sensors (such as TERRA / AQUA MODIS, Landsat-8OLI, Sentinel-2A / 2B MSI). Currently, my country's solar reflectance spectrum satellite sensors primarily use field-based alternative calibration to achieve operational on-orbit radiometric calibration, relying on ground-synchronous measurement data during satellite transit. This is especially true for domestically produced Landsat sensors. Satellite operations departments conduct annual ground-synchronous measurements at the Dunhuang field, or use foreign satellite sensors for cross-calibration, which is currently the main method used by domestic Landsat satellites to supplement operational field-based alternative calibration.

[0003] However, the study found that the current calibration methods still have some shortcomings: the accuracy of field substitution calibration is limited by factors such as satellite-to-ground spatiotemporal matching and atmospheric radiation transfer simulation errors; manual measurement of surface and atmospheric parameters at calibration sites requires a lot of manpower and resources, and is affected by weather, making it difficult to achieve high-frequency, high-stability operational radiometric calibration; when conducting cross-calibration with foreign satellite sensors, it is affected by the time and angle differences between the reference satellite and the satellite to be calibrated, and the cross-calibration opportunities between the two satellites are limited, which also makes it difficult to guarantee high-frequency, high-stability on-orbit radiometric calibration of domestic land satellite sensors. Summary of the Invention

[0004] In view of the above, embodiments of this disclosure provide a satellite on-orbit radiometric calibration method, apparatus, electronic device, storage medium, and computer program product.

[0005] One aspect of this disclosure provides a satellite on-orbit radiometric calibration method, including:

[0006] Obtain the set of atmospheric parameters associated with the calibration field;

[0007] Using the above atmospheric parameter set and the first image dataset of the first satellite sensor in the calibration field area, a two-way reflectance distribution function model of the above calibration field is constructed;

[0008] Based on the center wavelength of each channel in the first satellite sensor, the coefficients of the bidirectional reflectance distribution function model are linearly interpolated to obtain a target model with target coefficients, wherein the target model is a spectrally continuous bidirectional reflectance distribution function model;

[0009] Using the second image dataset from the second satellite sensor in the aforementioned calibration field area, the aforementioned atmospheric parameter set, and the aforementioned target model, the correction relationship between the simulated apparent radiance simulated by the aforementioned target model and the actual apparent radiance is determined.

[0010] The radiometric calibration coefficients of the satellite sensor to be calibrated are calculated using the third image dataset of the satellite sensor in the calibration field area, the atmospheric parameter set, the target model, and the correction relationship.

[0011] Another aspect of this disclosure provides a satellite on-orbit radiometric calibration apparatus, comprising:

[0012] The parameter acquisition module is used to acquire the set of atmospheric parameters associated with the calibration field;

[0013] The model building module is used to construct a two-way reflectance distribution function model of the calibration field using the above atmospheric parameter set and the first image dataset of the first satellite sensor in the calibration field area.

[0014] The target model determination module is used to perform linear interpolation on the coefficients of the bidirectional reflectance distribution function model based on the center wavelength of each channel in the first satellite sensor to obtain a target model with target coefficients, wherein the target model is a spectrally continuous bidirectional reflectance distribution function model;

[0015] The relationship determination module is used to determine the correction relationship between the simulated apparent radiance simulated by the target model and the actual apparent radiance using the second image dataset of the second satellite sensor in the above-mentioned calibration field area, the above-mentioned atmospheric parameter set, and the above-mentioned target model.

[0016] The calibration coefficient determination module is used to calculate the radiometric calibration coefficients of the satellite sensor to be calibrated using the third image dataset of the satellite sensor to be calibrated in the above-mentioned calibration field area, the above-mentioned atmospheric parameter set, the above-mentioned target model, and the above-mentioned correction relationship.

[0017] Another aspect of this disclosure provides an electronic device, including: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method described above.

[0018] Another aspect of this disclosure provides a computer-readable storage medium storing computer-executable instructions that, when executed, are used to implement the method described above.

[0019] Another aspect of this disclosure provides a computer program product including computer-executable instructions that, when executed, implement the method described above.

[0020] According to the embodiments of this disclosure, because a bidirectional reflectance distribution function model is constructed using image datasets from calibrated satellite sensors, and a correction relationship between the simulated apparent radiance and the actual apparent radiance is determined using satellite image datasets with high radiometric calibration accuracy, the radiometric calibration coefficients of the satellite sensor to be calibrated can be calculated using image datasets of the sensor in the calibration field area, atmospheric parameter sets that do not require manual measurement, the bidirectional reflectance distribution function model, and the correction relationship. Therefore, this at least partially overcomes the technical problem that satellite sensor calibration requires reliance on ground-based synchronous measurement data, thereby achieving high-frequency, operational on-orbit radiometric calibration of satellites. At the same time, because the correction relationship between simulated and actual apparent radiance is used to correct the simulated apparent radiance of the satellite sensor to be calibrated, the systematic errors present in the simulated apparent radiance are at least partially eliminated, thereby resulting in high accuracy and high stability of the calibration results. Attached Figure Description

[0021] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0022] Figure 1 A schematic flowchart of a satellite on-orbit radiometric calibration method according to an embodiment of the present disclosure is shown.

[0023] Figure 2 A block diagram schematically illustrates a satellite on-orbit radiometric calibration apparatus according to an embodiment of the present disclosure; and

[0024] Figure 3 A block diagram schematically illustrates an electronic device suitable for implementing an on-orbit radiometric calibration method for satellites according to embodiments of the present disclosure. Detailed Implementation

[0025] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0026] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0027] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0028] When using expressions such as "at least one of A, B, and C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.). Similarly, when using expressions such as "at least one of A, B, or C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, or C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0029] In recent years, foreign countries, represented by the European Space Agency (ESA), have continuously developed pseudo-invariant field calibration technology. Multiple pseudo-invariant calibration fields have been selected in the Sahara Desert region of Africa, and the surface and atmospheric characteristics of these fields have been studied. By constructing a TOA reflectivity model for the pseudo-invariant calibration fields, on-orbit radiometric calibration of satellite sensors is performed. This calibration method does not rely on ground-synchronous measurement data during satellite transit and has advantages such as simplicity, convenience, and high calibration frequency. However, the imaging resources of China's land satellites are mainly concentrated domestically. Some sensors have different sensor settings between domestic and foreign imaging, making it difficult to directly apply radiometric calibration methods based on pseudo-invariant calibration to domestic land satellite sensors.

[0030] In view of this, embodiments of the present disclosure provide a satellite on-orbit radiometric calibration method. The method includes: acquiring an atmospheric parameter set associated with a calibration field; constructing a bidirectional reflectance distribution function (BRF) model of the calibration field using the atmospheric parameter set and a first image dataset from a first satellite sensor in the calibration field region; linearly interpolating the coefficients of the BRF model based on the center wavelengths of each channel in the first satellite sensor to obtain a target model with target coefficients, wherein the target model is a spectrally continuous BRF model; determining the correction relationship between the simulated apparent radiance simulated by the target model and the actual apparent radiance using a second image dataset from a second satellite sensor in the calibration field region, the atmospheric parameter set, and the target model; and calculating the radiometric calibration coefficients of the satellite sensor to be calibrated using a third image dataset from the calibration field region, the atmospheric parameter set, the target model, and the correction relationship.

[0031] Figure 1 A flowchart illustrating a satellite on-orbit radiometric calibration method according to an embodiment of the present disclosure is shown schematically.

[0032] like Figure 1 As shown, the method includes operations S101 to S105.

[0033] In operation S101, obtain the set of atmospheric parameters associated with the calibration field.

[0034] According to embodiments of this disclosure, the set of atmospheric parameters associated with the calibration field can be derived from reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF).

[0035] According to embodiments of this disclosure, the atmospheric parameter set of the calibration field is obtained from ECMWF reanalysis data, avoiding manual measurement and at least partially overcoming the problems of requiring manpower and resources and being affected by weather. This demonstrates that the satellite on-orbit radiometric calibration method of this disclosure can enable satellites to be calibrated at high frequency and stably.

[0036] According to embodiments of this disclosure, the atmospheric parameter set includes: aerosol optical thickness τ, atmospheric water vapor content w, and ozone content O3.

[0037] According to embodiments of this disclosure, the aerosol optical thickness can be 550 nm.

[0038] In operation S102, a two-way reflection distribution function model of the calibration field is constructed using the atmospheric parameter set and the first image dataset of the first satellite sensor in the calibration field area.

[0039] According to embodiments of this disclosure, the first satellite sensor may be a calibrated satellite sensor, such as a TERRA / MODIS satellite sensor.

[0040] According to embodiments of this disclosure, a bidirectional reflection distribution function (BRDF) model of the calibration field is constructed using an atmospheric parameter set and a first satellite sensor for each target time period. Each target time period can be monthly, i.e., a monthly BRDF model is constructed. The time series data of the first image dataset and the atmospheric parameter set can be selected for more than 5 years, such as 2016-2021, to ensure that the constructed BRDF model has sufficient surface reflectance.

[0041] According to embodiments of this disclosure, based on the known coordinates of the calibration field region, the brightness values ​​of first remote sensing image pixels, first observation geometric parameters, and first satellite imaging time are extracted from the first image data of the first satellite sensor in the calibration field region; the first apparent radiance is calculated using the brightness values ​​of the first remote sensing image pixels and the radiometric calibration coefficient of the first satellite sensor; a first atmospheric parameter set is extracted from the atmospheric parameter set based on the coordinates of the calibration field region and the first satellite imaging time; atmospheric correction is performed on the first apparent radiance, the first observation geometric parameters, and the first atmospheric parameter set using an atmospheric correction model to obtain the surface reflectance of the calibration field; the surface reflectance is divided according to the target time period to obtain the first surface reflectance for multiple target time periods; and a bidirectional reflectance distribution function model of the calibration field is constructed using the first surface reflectance and a semi-empirical bidirectional reflectance distribution function model.

[0042] According to embodiments of this disclosure, based on the known coordinates of the calibration field area, the first remote sensing image pixel brightness (Digital Number, abbreviated as DN) value, the first observation geometric parameter, and the first satellite imaging time of each channel are extracted from the first image data of the first satellite sensor in the calibration field area. The observation geometric parameter includes: solar zenith angle, solar azimuth angle, satellite zenith angle, and satellite azimuth angle.

[0043] According to embodiments of this disclosure, the calculation process for calculating the first apparent radiance using the first DN value and the radiometric calibration coefficient of the first satellite sensor is as follows:

[0044] L = scales × (DN - offsets) (I)

[0045] Where L is the apparent radiance of each channel of the first satellite sensor, DN is the DN value of each channel, and scales and offsets are the radiometric calibration coefficients inherent in the first satellite image data.

[0046] According to embodiments of this disclosure, if the first satellite sensor uses a TERRA / MODIS satellite sensor, its channel information is shown in Table 1 below:

[0047] Table 1 Channel Information of MODIS Sensors

[0048]

[0049]

[0050] According to an embodiment of this disclosure, since the atmospheric parameter set obtained from ECMWF reanalysis data has a total of 6 time points in a day, a first atmospheric parameter set is obtained after linear interpolation based on the satellite imaging time, wherein the satellite imaging time can be the satellite transit time.

[0051] According to embodiments of this disclosure, the atmospheric correction model can be an SMAC model.

[0052] According to embodiments of this disclosure, the obtained surface reflectance of the calibration field is divided according to the target time period to obtain multi-angle surface reflectance data for each target time period of the calibration field. Using the multi-angle surface reflectance data, the model coefficients in the semi-empirical BRDF model are fitted to obtain the BRDF model for each target time period. The target time period can be monthly, and the surface reflectance data is divided monthly. The semi-empirical bidirectional reflectance distribution function model can be a Roujean model or a Ross-Li model.

[0053] According to embodiments of this disclosure, the basic form of the bidirectional reflection distribution function model is:

[0054]

[0055] Where f0, f1, and f2 represent the kernel functions of the isotropic homogeneous scattering component in the surface scattering, respectively. These represent channel b respectively. i The corresponding semi-empirical two-way reflection distribution function model coefficients, θ s θ v , These represent the solar zenith angle, the satellite-observed zenith angle, and the relative azimuth angle, respectively.

[0056] According to embodiments of this disclosure, a two-way reflectance distribution function model is constructed using image data from calibrated satellite sensors and a set of atmospheric parameters that do not require manual measurement. This facilitates a more convenient and accurate determination of the simulated apparent radiance of satellite sensors, thereby avoiding reliance on ground-based synchronous measurement data during calibration. This, in turn, helps to achieve high-frequency, operational on-orbit radiometric calibration of satellites.

[0057] In operation S103, based on the center wavelength of each channel in the first satellite sensor, the coefficients of the bidirectional reflectance distribution function model are linearly interpolated to obtain a target model with target coefficients, wherein the target model is a spectrally continuous bidirectional reflectance distribution function model.

[0058] According to embodiments of this disclosure, the coefficients of the BRDF model are linearly interpolated using the center wavelengths of each channel in the first satellite sensor to calculate the BRDF model coefficients at different wavelengths, thereby obtaining the spectrally continuous calibration field BRDF model coefficients. The spectrally continuous calibration field BRDF model coefficients are then imported into the BRDF model to obtain a spectrally continuous BRDF model. The formula for linearly interpolating the coefficients of the BRDF model is shown below:

[0059]

[0060] Where Interp represents the interpolation function, λ represents the wavelength, n represents the number of channels, i = 1, ..., m represents the channel index, and c = 1, 2, 3 represents the index of the BRDF model coefficients. These represent channel b respectively. i The corresponding semi-empirical BRDF model coefficients are the BRDF model coefficients.

[0061] According to embodiments of this disclosure, the wavelength range of the spectrum is 400 nm to 1000 nm, and the wavelength interval is 10 nm.

[0062] According to embodiments of this disclosure, the wavelength range of the spectral continuous BRDF model coefficient spectrum is 400 nm to 1000 nm, with a wavelength interval of 10 nm.

[0063] In operation S104, using the second image dataset, atmospheric parameter set, and target model of the second satellite sensor in the calibration field area, the correction relationship between the simulated apparent radiance of the target model and the actual apparent radiance is determined.

[0064] According to embodiments of this disclosure, the second satellite sensor can be a satellite sensor known to have high radiometric calibration accuracy, such as the Landsat-8 / OLI sensor.

[0065] According to embodiments of this disclosure, satellite sensors with high radiometric calibration accuracy are used to calibrate the observation data of the calibration field, and the simulated apparent radiance simulated by the BRDF model based on each target time period of the calibration field is corrected to obtain the correction relationship between the simulated apparent radiance and the actual apparent radiance.

[0066] According to embodiments of this disclosure, using a second image dataset from a second satellite sensor in a calibration field region, pixel brightness values ​​of the second remote sensing image, second observation geometric parameters, and the imaging time of the second satellite are extracted; the actual apparent radiance of each channel of the second satellite sensor is calculated using the pixel brightness values ​​of the second remote sensing image and the radiometric calibration coefficients of the second satellite sensor; based on the imaging time of the second satellite, the second observation geometric parameters are input into the corresponding target model to obtain the spectral reflectance of the first calibration field; based on the coordinates of the calibration field region and the imaging time of the second satellite, a second atmospheric parameter set is extracted from the atmospheric parameter set; the spectral reflectance of the first calibration field, the second atmospheric parameter set, and the spectral response function of the second satellite sensor are input into the atmospheric radiative transfer model to obtain the simulated apparent radiance of each channel of the second satellite sensor; and a correction relationship is established based on the actual apparent radiance and the simulated apparent radiance.

[0067] According to embodiments of this disclosure, the second image dataset can be a time-series satellite image dataset, the satellite imaging time can be the satellite transit time, and the actual apparent radiance L of each channel of the second satellite sensor is calculated using the second DN value and the radiometric calibration coefficient of the second satellite sensor. OLI (b i ,t j ), where b i The channel identifier for the satellite sensor, t j Different imaging times are represented by j = 1, ..., n, which represents the index of the imaging time. Based on the imaging time of the second satellite sensor, the spectral reflectance ρ(λ,t) of the corresponding first calibration field is calculated in the BRDF model that matches the spectral continuity of the target time. j Next, after linear interpolation of the atmospheric parameter set, the aerosol optical thickness τ, water vapor content w, and ozone content O3 of the calibration field at the satellite transit time are extracted; then ρ(λ,t) is used to calculate the aerosol optical thickness τ, water vapor content w, and ozone content O3. j ), τ, w, O3, and the spectral response function ξ of the second satellite sensor OLI (b i The simulated apparent radiance of each channel of the second satellite sensor is obtained by inputting the data into the atmospheric radiative transfer model. The atmospheric radiative transfer model can be the MODTRAN model; the actual apparent radiance L from the second satellite sensor at different times and in different bands is also considered. OLI (b i ,t j and simulated apparent radiance Establish the correction relationship between actual apparent radiance and simulated apparent radiance.

[0068] According to embodiments of this disclosure, the formula for the correction relationship includes:

[0069]

[0070] Among them, L OLI (b i ,t j () represents the actual apparent radiance. b represents the simulated apparent radiance. i This indicates the channel identifier for the second satellite sensor, i = 1, ..., m, t j The numbers represent different satellite imaging times, j = 1, ..., n, m represents the number of channels of the second satellite sensor, n represents the amount of time-series data, and A and B represent the correction coefficients for the simulated apparent radiance.

[0071] According to embodiments of this disclosure, if the second satellite sensor is a Landat-8 / OLI sensor, its channel information is shown in Table 2 below:

[0072] Table 2 Channel Information for Landat-8 / OLI Sensors

[0073]

[0074] According to embodiments of this disclosure, by utilizing a satellite image dataset known for its high radiometric calibration accuracy, the correction relationship between the simulated apparent radiance and the actual apparent radiance can be used to correct the simulated apparent radiance simulated by subsequent satellite sensors to be calibrated, eliminating systematic errors in the simulated apparent radiance measurement, thereby enabling the calibration results to have high accuracy and high stability.

[0075] In operation S105, the radiometric calibration coefficients of the satellite sensor to be calibrated are calculated using the third image dataset, atmospheric parameter set, target model, and correction relationship of the satellite sensor in the calibration field area.

[0076] According to embodiments of this disclosure, the simulated apparent radiance of the satellite sensor to be calibrated is calculated using image datasets of the calibration field region of the satellite sensor to be calibrated, a monthly BRDF model of the spectrally continuous calibration field, and atmospheric parameters at the time of the satellite's transit. The actual apparent radiance of the satellite sensor to be calibrated is calculated based on the correction relationship between the simulated apparent radiance and the actual apparent radiance. Finally, the radiometric calibration coefficient of the satellite sensor to be calibrated is calculated using the actual apparent radiance and the least squares method.

[0077] According to embodiments of this disclosure, the satellite sensor to be calibrated can be a GF-1 / WFV sensor.

[0078] According to embodiments of this disclosure, the pixel brightness values ​​of the third remote sensing image, the third observation geometric parameters, and the satellite transit time are extracted using the third image dataset of the satellite sensor to be calibrated in the calibration field area; a third atmospheric parameter set is obtained from the atmospheric parameter set based on the coordinates of the calibration field area and the satellite transit time; radiative transfer simulation is performed using the target model, the third observation geometric parameters, and the third atmospheric parameter set to obtain the simulated apparent radiance of each channel of the satellite sensor to be calibrated; the simulated apparent radiance of each channel of the satellite sensor to be calibrated is corrected according to the correction relationship to obtain the actual apparent radiance of each channel of the satellite sensor to be calibrated; and the radiometric calibration coefficients of each channel of the satellite sensor to be calibrated are calculated using the actual apparent radiance of each channel of the satellite sensor to be calibrated and the pixel brightness values ​​of the third remote sensing image.

[0079] According to embodiments of this disclosure, a third DN value (DN) is extracted from a third image dataset in a calibration field using the satellite sensor to be calibrated. wfv (b i The parameters include the satellite transit time t and the third observation geometric parameters, where the satellite transit time can be data from the satellite imaging time.

[0080] According to an embodiment of this disclosure, a third atmospheric parameter set is obtained by linear interpolating the atmospheric parameter set based on the satellite transit time t of the satellite sensor to be calibrated. The third atmospheric parameters include: aerosol optical thickness, atmospheric water vapor content, and ozone content at the satellite transit time of the sensor to be calibrated.

[0081] According to embodiments of this disclosure, based on the satellite's transit time, a third observation geometric parameter is input into the corresponding target model to obtain the second calibration field spectral reflectance; the second calibration field spectral reflectance, the third atmospheric parameter set, and the spectral response function ξ of the satellite sensor to be calibrated are then combined. WFV (b i The simulated apparent radiance of each channel of the sensor to be calibrated is obtained by inputting the data into the atmospheric radiative transfer model. Among them, the atmospheric radiative transfer model can be MODTRAN.

[0082] According to embodiments of this disclosure, the calibration relationship between simulated apparent radiance and actual apparent radiance is used to determine the simulated apparent radiance of each channel of the sensor to be calibrated. Correction is performed to obtain the final apparent radiance. The calculation process is as follows:

[0083]

[0084] Among them, b i The channel identifier represents the satellite sensor to be calibrated, and A and B represent the correction coefficients for the simulated apparent radiance.

[0085] According to embodiments of this disclosure, based on formula (vi), and combining the actual apparent radiance of each channel of the satellite sensor to be calibrated and the third DN value of the satellite sensor to be calibrated, DN wfv (b i By solving the least squares problem, the radiometric calibration coefficients G(b) of each channel of the satellite sensor to be calibrated can be obtained. i ) and Bias(b i Formula (vi) is shown below:

[0086]

[0087] According to the embodiments of this disclosure, because a bidirectional reflectance distribution function model is constructed using image datasets from calibrated satellite sensors, and the simulated apparent radiance simulated by the bidirectional reflectance distribution function model is corrected using satellite image datasets with high radiometric calibration accuracy, the correction relationship between the simulated apparent radiance and the actual apparent radiance is determined. This allows the radiometric calibration coefficients of the satellite sensor to be calibrated to be calculated using image datasets of the sensor in the calibration field area, atmospheric parameter sets that do not require manual measurement, the bidirectional reflectance distribution function model, and the correction relationship. Therefore, this at least partially overcomes the technical problem of satellite sensor calibration relying on ground-based synchronous measurement data, thereby achieving high-frequency, operational satellite on-orbit radiometric calibration. At the same time, because the correction relationship between simulated and actual apparent radiance is used to correct the simulated apparent radiance of the satellite sensor to be calibrated, the systematic errors present in the simulated apparent radiance are at least partially eliminated, resulting in high accuracy and high stability of the calibration results.

[0088] Figure 2 A block diagram of a satellite on-orbit radiometric calibration apparatus according to an embodiment of the present disclosure is shown schematically.

[0089] like Figure 2 As shown, the satellite on-orbit radiometric calibration device 200 includes a parameter acquisition module 210, a model construction module 220, a target model determination module 230, a relationship determination module 240, and a calibration coefficient determination module 250.

[0090] The parameter acquisition module 210 is used to acquire the set of atmospheric parameters associated with the calibration field.

[0091] Model building module 220 is used to construct a two-way reflection distribution function model of the calibration field using atmospheric parameter set and first image dataset of the first satellite sensor in the calibration field area.

[0092] The target model determination module 230 is used to perform linear interpolation on the coefficients of the bidirectional reflectance distribution function model based on the center wavelength of each channel in the first satellite sensor, so as to obtain a target model with target coefficients, wherein the target model is a spectrally continuous bidirectional reflectance distribution function model.

[0093] The relationship determination module 240 is used to determine the correction relationship between the simulated apparent radiance simulated by the target model and the actual apparent radiance by utilizing the second image dataset, atmospheric parameter set and target model of the second satellite sensor in the calibration field area.

[0094] The calibration coefficient determination module 250 is used to calculate the radiometric calibration coefficients of the satellite sensor to be calibrated using the third image dataset, atmospheric parameter set, target model, and correction relationship of the satellite sensor in the calibration field area.

[0095] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuits, such as Field Programmable Gate Arrays (FPGAs), Programmable Logic Arrays (PLAs), Systems-on-Chip, Systems-on-Substrate, Systems-on-Package, Application-Specific Integrated Circuits (ASICs), or implemented by hardware or firmware through any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, or firmware, or in a suitable combination of any one or more of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0096] For example, any and more of the parameter acquisition module 210, model building module 220, target model determination module 230, relationship determination module 240, and scaling coefficient determination module 250 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least some of the functionality of one or more of these modules / units / subunits can be combined with at least some of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the parameter acquisition module 210, model building module 220, target model determination module 230, relationship determination module 240, and scaling coefficient determination module 250 can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the parameter acquisition module 210, model building module 220, target model determination module 230, relationship determination module 240, and scaling coefficient determination module 250 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0097] It should be noted that the satellite on-orbit radiometric calibration device section in the embodiments of this disclosure corresponds to the satellite on-orbit radiometric calibration method section in the embodiments of this disclosure. For a detailed description of the satellite on-orbit radiometric calibration device section, please refer to the satellite on-orbit radiometric calibration method section, which will not be repeated here.

[0098] Figure 3 A block diagram schematically illustrates an electronic device suitable for implementing an on-orbit radiometric calibration method for satellites according to embodiments of the present disclosure. Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0099] like Figure 3As shown, an electronic device 300 according to an embodiment of the present disclosure includes a processor 301, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 302 or a program loaded from storage portion 308 into random access memory (RAM) 303. The processor 301 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 301 may also include onboard memory for caching purposes. The processor 301 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0100] RAM 303 stores various programs and data required for the operation of electronic device 300. Processor 301, ROM 302, and RAM 303 are interconnected via bus 304. Processor 301 executes various operations of the satellite on-orbit radiometric calibration method flow according to embodiments of the present disclosure by executing programs in ROM 302 and / or RAM 303. It should be noted that programs may also be stored in one or more memories other than ROM 302 and RAM 303. Processor 301 may also execute various operations of the satellite on-orbit radiometric calibration method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.

[0101] According to embodiments of this disclosure, the electronic device 300 may further include an input / output (I / O) interface 305, which is also connected to a bus 304. The system 300 may also include one or more of the following components connected to the I / O interface 303: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 303 as needed. A removable medium 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 310 as needed so that computer programs read from it can be installed into the storage section 308 as needed.

[0102] According to embodiments of this disclosure, the satellite on-orbit radiometric calibration method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the satellite on-orbit radiometric calibration method shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by processor 301, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0103] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the satellite on-orbit radiometric calibration method according to embodiments of this disclosure.

[0104] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0105] For example, according to embodiments of this disclosure, a computer-readable storage medium may include the ROM 302 and / or RAM 303 described above and / or one or more memories other than ROM 302 and RAM 303.

[0106] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for executing the satellite on-orbit radiometric calibration method provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the satellite on-orbit radiometric calibration method provided in the embodiments of this disclosure.

[0107] When the computer program is executed by the processor 301, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0108] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via communication section 309, and / or installed from removable medium 311. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0109] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0110] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features recited in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not expressly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0111] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A satellite in-orbit radiometric calibration method, comprising: obtaining a set of atmospheric parameters associated with a calibration field; constructing a bidirectional reflectance distribution function model of the calibration field using the set of atmospheric parameters and a first image data set of a first satellite sensor in a calibration field area; linearly interpolating coefficients of the bidirectional reflectance distribution function model according to central wavelengths of channels in the first satellite sensor to obtain a target model with target coefficients, wherein the target model is a spectrally continuous bidirectional reflectance distribution function model; determining a correction relationship between simulated apparent radiance simulated by the target model and actual apparent radiance using a second image data set of a second satellite sensor in the calibration field area, the set of atmospheric parameters, and the target model; calculating radiometric calibration coefficients of a satellite sensor to be calibrated using a third image data set of the satellite sensor to be calibrated in the calibration field area, the set of atmospheric parameters, the target model, and the correction relationship; the determining a correction relationship between simulated apparent radiance simulated by the target model and actual apparent radiance using a second image data set of a second satellite sensor in the calibration field area, the set of atmospheric parameters, and the target model, comprises: extracting second remote sensing image pixel brightness values, second observation geometry parameters, and a second satellite imaging time using the second image data set of the second satellite sensor in the calibration field area; calculating actual apparent radiance of channels of the second satellite sensor using the second remote sensing image pixel brightness values and radiometric calibration coefficients of the second satellite sensor; inputting the second observation geometry parameters into the corresponding target model according to the second satellite imaging time to obtain first calibration field spectral reflectance; extracting a second set of atmospheric parameters from the set of atmospheric parameters according to calibration field area coordinates and the second satellite imaging time; inputting the first calibration field spectral reflectance, the second set of atmospheric parameters, and a spectral response function of the second satellite sensor into an atmospheric radiation transfer model to obtain simulated apparent radiance of channels of the second satellite sensor; establishing the correction relationship according to the actual apparent radiance and the simulated apparent radiance; a formula for the establishing the correction relationship according to the apparent radiance and the simulated apparent radiance comprises: wherein, represents the actual apparent radiance, represents the simulated apparent radiance, represents the channel identification of the second satellite sensor, , represents the different satellite imaging times, , represents the number of channels of the second satellite sensor, represents the number of time series data, and represents the correction factor on the simulated apparent radiance.

2. The method of claim 1, wherein, the constructing a bidirectional reflectance distribution function model of the calibration field using the set of atmospheric parameters and a first image data set of a first satellite sensor in a calibration field area, comprises: extracting first remote sensing image pixel brightness values, first observation geometry parameters, and a first satellite imaging time from the first image data set of the first satellite sensor in the calibration field area according to known calibration field area coordinates; calculating first apparent radiance using the first remote sensing image pixel brightness values and radiometric calibration coefficients of the first satellite sensor; extracting a first set of atmospheric parameters from the set of atmospheric parameters according to the calibration field area coordinates and the first satellite imaging time; atmospherically correcting the first apparent radiance, the first observation geometry parameters, and the first set of atmospheric parameters using an atmospheric correction model to obtain ground reflectance of the calibration field; The ground reflectivity is divided according to a target time period to obtain first ground reflectivity of multiple target time periods; A bidirectional reflectance distribution function model of the calibration field is constructed by using the first ground reflectivity and a semi-empirical bidirectional reflectance distribution function model.

3. The method of claim 2, wherein, The bidirectional reflectance distribution function model has a basic form of: where, respectively represent the kernel functions of the isotropic scattering part in the surface scattering, respectively represent the channel corresponding semi-empirical bidirectional reflectance distribution function model coefficients, respectively represent the solar zenith angle, satellite observation zenith angle and relative azimuth angle.

4. The method of claim 1, wherein the calculating the radiometric calibration coefficients of the satellite sensor to be calibrated by using the third image data set of the satellite sensor to be calibrated in the calibration field region, the atmospheric parameter set, the target model, and the correction relationship comprises: extracting third remote sensing image pixel brightness values, third observation geometric parameters, and satellite passing time from the third image data set of the satellite sensor to be calibrated in the calibration field region; obtaining a third atmospheric parameter set from the atmospheric parameter set according to the calibration field region coordinates and the satellite passing time; performing radiative transfer simulation by using the target model, the third observation geometric parameters, and the third atmospheric parameter set to obtain simulated apparent radiance of each channel of the satellite sensor to be calibrated; correcting the simulated apparent radiance of each channel of the satellite sensor to be calibrated according to the correction relationship to obtain actual apparent radiance of each channel of the satellite sensor to be calibrated; calculating the radiometric calibration coefficients of each channel of the satellite sensor to be calibrated by using the actual apparent radiance of each channel of the satellite sensor to be calibrated and the third remote sensing image pixel brightness values.

5. The method of claim 1, wherein, The wavelength range of the spectrum is 400 nm to 1000 nm, and the wavelength interval is 10 nm.

6. The method of claim 1, the set of atmospheric parameters comprising: The aerosol optical depth, the atmospheric water vapor content, and the ozone content.

7. A satellite on-orbit radiometric calibration device, comprising: a parameter acquisition module configured to acquire an atmospheric parameter set associated with a calibration field; a model construction module configured to construct a bidirectional reflectance distribution function model of the calibration field by using the atmospheric parameter set and a first image data set of a first satellite sensor in a calibration field region; a target model determination module configured to perform linear interpolation on coefficients of the bidirectional reflectance distribution function model according to central wavelengths of each channel of the first satellite sensor to obtain a target model having target coefficients, wherein the target model is a spectrally continuous bidirectional reflectance distribution function model; a relationship determination module configured to determine a correction relationship between simulated apparent radiance and actual apparent radiance simulated by the target model by using a second image data set of a second satellite sensor in the calibration field region, the atmospheric parameter set, and the target model; a calibration coefficient determination module configured to calculate radiometric calibration coefficients of a satellite sensor to be calibrated by using a third image data set of the satellite sensor to be calibrated in the calibration field region, the atmospheric parameter set, the target model, and the correction relationship; the relationship determination module is configured to: extract second remote sensing image pixel brightness values, second observation geometric parameters, and second satellite imaging time from the second image data set of the second satellite sensor in the calibration field region; calculate actual apparent radiance of each channel of the second satellite sensor by using the second remote sensing image pixel brightness values and the radiometric calibration coefficients of the second satellite sensor; inputting the second observation geometry parameter into the corresponding target model according to the second satellite imaging time, to obtain first calibration field spectral reflectance; extracting a second set of atmospheric parameters from the set of atmospheric parameters according to the calibration field region coordinates and the second satellite imaging time; inputting the first calibration field spectral reflectance, the second set of atmospheric parameters and a spectral response function of a second satellite sensor into an atmospheric radiation transfer model, to obtain simulated apparent radiance of each channel of the second satellite sensor; establishing the correction relationship according to the actual apparent radiance and the simulated apparent radiance; the formula for establishing the correction relationship according to the apparent radiance and the simulated apparent radiance comprises: wherein, represents the actual apparent radiance, represents the simulated apparent radiance, represents the channel identification of the second satellite sensor, , represents the different satellite imaging times, , represents the number of channels of the second satellite sensor, represents the number of time series data, and represents the correction factor on the simulated apparent radiance. 8.An electronic device, comprising: one or more processors; memory storing one or more programs, wherein the one or more programs, when executed by the one or more processors, enable the one or more processors to implement the method of any one of claims 1-6.

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