Heterogeneous multi-spectral satellite joint calculation and radiation consistency processing method

Abstract

The present invention relates to the field of remote sensing science and geographic information processing technology, and in particular to a method for joint solution and radiation consistency processing of heterogeneous multi-spectral satellites. By performing heterogeneous satellite cross-radiation calibration, joint radiation correction, spectrum matching and relative radiation correction on heterogeneous multi-spectral satellite remote sensing images, a heterogeneous satellite joint solution scheme is provided to solve the problem of spectral radiation inconsistency caused by differences in sensor design and imaging conditions of heterogeneous satellite multi-spectral observation data, thereby ensuring data consistency and comparability.

Description

Technical Field

[0001] The present invention relates to the field of remote sensing science and geographic information processing technology, and in particular to a method, device, computer equipment and storage medium for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites. Background Art

[0002] In recent years, the generation of dense time series datasets for remote sensing observations using medium- and high-resolution land resource satellites has been mostly based on the observation data of the Landsat and Sentinel series satellites in the United States. For example, the Landsat / Sentinel-2 homogenization product generation project for the "virtual constellation" target carried out by the United States Geological Survey (USGS) has initially achieved the radiation uniformity processing of heterogeneous multispectral satellites from Europe and the United States. The homogenized surface sub-satellite reflectance time series dataset has received high attention since its launch and has been widely used in high-resolution vegetation phenology mapping and various types of surface cover characteristics. Research such as refined dynamic monitoring. However, the current uniformity processing scheme does not take into account the radiation inconsistency caused by the rugged terrain, and lacks a joint solution and radiation uniformity scheme for heterogeneous multispectral data for domestic data. If domestic satellite data (such as the high-resolution series satellites) can be included, it can not only enrich the observation data of the virtual constellation, but also significantly improve the revisit period, thereby improving the spatiotemporal resolution and coverage of the time series dataset, which is of great significance for further improving the accuracy and real-time performance of dynamic monitoring. Summary of the invention

[0003] Based on this, the purpose of the present invention is to provide a method, device, computer equipment and storage medium for joint solution and radiation consistency processing of heterogeneous multi-spectral satellites. By performing heterogeneous satellite cross-radiation calibration, joint radiation correction, spectral matching and radiation consistency on heterogeneous multi-spectral satellite remote sensing images, a heterogeneous satellite joint solution solution is provided to solve the spectral radiation inconsistency problem caused by differences in sensor design and imaging conditions of heterogeneous satellite multi-spectral observation data, thereby ensuring data consistency and comparability.

[0004] In a first aspect, an embodiment of the present application provides a method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites, including the following steps:

[0005] Obtaining a reference multispectral satellite remote sensing image, a target multispectral satellite remote sensing image, and corresponding auxiliary data, wherein the auxiliary data includes atmospheric auxiliary data, observation geometry data, and terrain data;

[0006] Preprocessing the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, wherein the preprocessing step includes geo-registration and resampling processing;

[0007] According to the preprocessed reference multispectral satellite remote sensing image, the target multispectral satellite remote sensing image and the corresponding auxiliary data, a heterogeneous satellite cross-radiation calibration is performed to obtain a cross-radiation calibration coefficient, and according to the cross-radiation calibration coefficient and the target multispectral satellite remote sensing image after the geo-registration and resampling processing, a target multispectral satellite remote sensing image after cross-radiation calibration is obtained;

[0008] According to the corresponding auxiliary data, respectively, the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration are subjected to joint radiation correction to obtain the sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and the sub-satellite surface reflectance after terrain correction corresponding to the reference multispectral satellite remote sensing image is used as the radiation-consistent reflectance to obtain the radiation-consistent reflectance corresponding to the reference multispectral satellite remote sensing image;

[0009] Spectral matching is performed on the terrain-corrected surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image to obtain the spectrally matched reflectance corresponding to the target multispectral satellite remote sensing image; invariant feature points are extracted based on the terrain-corrected surface reflectance under the satellite corresponding to the reference multispectral satellite remote sensing image and the spectrally matched surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image; relative radiation correction is performed based on the extracted invariant feature points to obtain the radiation-consistent reflectance corresponding to the target multispectral satellite remote sensing image.

[0010] In a second aspect, the embodiment of the present application provides a heterogeneous multi-spectral satellite joint solution and radiation consistency processing device, including:

[0011] A data acquisition module, used to obtain reference multispectral satellite remote sensing images, target multispectral satellite remote sensing images and corresponding auxiliary data, wherein the auxiliary data includes atmospheric auxiliary data, observation geometry data and terrain data;

[0012] A preprocessing module, used for preprocessing the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, wherein the preprocessing step includes geo-registration and resampling processing;

[0013] A cross-radiation calibration module is used to perform heterogeneous satellite cross-radiation calibration according to the pre-processed reference multi-spectral satellite remote sensing image, the target multi-spectral satellite remote sensing image and the corresponding auxiliary data to obtain a cross-radiation calibration coefficient, and obtain a target multi-spectral satellite remote sensing image after cross-radiation calibration according to the cross-radiation calibration coefficient and the target multi-spectral satellite remote sensing image after geo-registration and resampling processing;

[0014] A joint radiation correction module is used to perform joint radiation correction on the pre-processed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross radiation calibration according to the corresponding auxiliary data, obtain the sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, use the sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image as the radiation consistent reflectance, and obtain the radiation consistent reflectance corresponding to the reference multispectral satellite remote sensing image;

[0015] The radiation consistency adjustment module is used to perform spectral matching on the terrain-corrected surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image, obtain the spectrally matched surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image, extract invariant feature points based on the terrain-corrected surface reflectance under the satellite corresponding to the reference multispectral satellite remote sensing image and the spectrally matched surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image, perform relative radiation correction based on the extracted invariant feature points, and obtain the radiation consistent reflectance corresponding to the target multispectral satellite remote sensing image.

[0016] In a third aspect, an embodiment of the present application provides a computer device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, the steps of the method for joint solution and radiation consistency processing of heterogeneous multi-spectral satellites as described in the first aspect are implemented.

[0017] In a fourth aspect, an embodiment of the present application provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for joint solution and radiation consistency processing of heterogeneous multi-spectral satellites as described in the first aspect.

[0018] In an embodiment of the present application, a method, apparatus, computer equipment and storage medium for joint solution and radiation consistency processing of heterogeneous multispectral satellites are provided. By performing heterogeneous satellite cross-radiation calibration, joint radiation correction, spectral matching and radiation consistency on heterogeneous multispectral satellite remote sensing images, a heterogeneous satellite joint solution solution is provided to solve the spectral radiation inconsistency problem caused by differences in sensor design and imaging conditions of heterogeneous satellite multispectral observation data, thereby ensuring data consistency and comparability.

[0019] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a process flow of a method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application;

[0021] Figure 2 A schematic diagram of the process of S3 in the method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application;

[0022] Figure 3 A schematic diagram of the process of S4 in the method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application;

[0023] Figure 4 A schematic diagram of the process of S41 in the method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application;

[0024] Figure 5 A schematic diagram of the process of S42 in the method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application;

[0025] Figure 6 A schematic diagram of the process of S43 in the method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application;

[0026] Figure 7 A schematic diagram of the structure of a device for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application;

[0027] Figure 8 A schematic diagram of the structure of a computer device provided for one embodiment of the present application. DETAILED DESCRIPTION

[0028] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0029] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0030] It should be understood that, although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" / "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determination".

[0031] See also Figure 1 , Figure 1 A schematic flow chart of a method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application, the method comprising the following steps:

[0032] S1: Obtain reference multispectral satellite remote sensing images, target multispectral satellite remote sensing images and corresponding auxiliary data.

[0033] The execution subject of the heterogeneous multi-spectral satellite joint solution and radiation consistency processing method is a processing device of the heterogeneous multi-spectral satellite joint solution and radiation consistency processing method (hereinafter referred to as the processing device). In an optional embodiment, the processing device can be a computer device, a server, or a server cluster composed of multiple computer devices.

[0034] In this embodiment, the processing device can obtain the reference multispectral satellite remote sensing image, the target multispectral satellite remote sensing image and the corresponding auxiliary data input by the user, or obtain the reference multispectral satellite remote sensing image, the target multispectral satellite remote sensing image and the corresponding auxiliary data from a preset database. Specifically, the reference multispectral satellite remote sensing image is the European Space Agency Sentinel-2L1C multispectral satellite remote sensing image, and the target multispectral satellite remote sensing image is the domestic GF-6L1A multispectral satellite remote sensing image.

[0035] The auxiliary data include atmospheric auxiliary data, observation geometry data and terrain data. The atmospheric auxiliary data include atmospheric aerosol optical thickness and water vapor data. The observation geometry data include solar geometry angle parameters, observation geometry angle parameters, sub-satellite point solar geometry angle parameters and sub-satellite point observation geometry angle parameters; the solar geometry angle parameters include solar zenith angle parameters and solar azimuth angle parameters; the observation geometry angle parameters include observation zenith angle parameters and observation azimuth angle parameters; the terrain data include digital elevation model DEM data.

[0036] S2: Preprocessing the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

[0037] In this embodiment, the processing device preprocesses the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, wherein the preprocessing step includes geographic registration and resampling processing.

[0038] S3: Perform heterogeneous satellite cross-radiation calibration according to the preprocessed reference multispectral satellite remote sensing image, the target multispectral satellite remote sensing image and the corresponding auxiliary data to obtain a cross-radiation calibration coefficient; and obtain the target multispectral satellite remote sensing image after cross-radiation calibration according to the cross-radiation calibration coefficient and the target multispectral satellite remote sensing image after geo-registration and resampling.

[0039] Since different satellite observations have differences in sensor design, on-orbit calibration schemes and processes, there is a problem in the comparability of the apparent radiation brightness of the top of the atmosphere. In this embodiment, the processing equipment performs heterogeneous satellite cross-radiation calibration based on the preprocessed reference multispectral satellite remote sensing image, the target multispectral satellite remote sensing image and the corresponding auxiliary data to obtain a cross-radiation calibration coefficient. Based on the cross-radiation calibration coefficient and the target multispectral satellite remote sensing image after geo-registration and resampling, a target multispectral satellite remote sensing image after cross-radiation calibration is obtained to deal with the radiation inconsistency problem caused by calibration differences.

[0040] See also Figure 2 , Figure 2 The schematic flow chart of S3 in the method for joint solution and radiation uniformization of heterogeneous multi-spectral satellites provided in one embodiment of the present application includes steps S31 to S34, which are specifically as follows:

[0041] S31: Perform atmospheric correction and BRDF correction according to the preprocessed reference multispectral satellite remote sensing image and the corresponding atmospheric auxiliary data and observation geometry data in the auxiliary data to obtain the sub-satellite surface reflectance of the reference multispectral satellite remote sensing image.

[0042] In this embodiment, the processing device performs atmospheric correction based on the Libradtran radiation transfer model according to the preprocessed reference multispectral satellite remote sensing image and the corresponding atmospheric auxiliary data and observation geometry data in the auxiliary data, using the atmospheric conditions and observation geometry conditions during imaging, to obtain the surface reflectivity of the reference multispectral satellite remote sensing image; based on a preset surface bidirectional reflectance distribution correction model (bi-directional reflectance distribution function, BRDF), the surface reflectivity of the reference multispectral satellite remote sensing image is corrected by BRDF to obtain the sub-satellite surface reflectivity of the reference multispectral satellite remote sensing image.

[0043] S32: Obtain the heterogeneous satellite spectral matching coefficient, calculate according to the sub-satellite surface reflectance of the reference multispectral satellite remote sensing image and the heterogeneous satellite spectral matching coefficient, obtain the simulated sub-satellite surface reflectance of the target multispectral satellite remote sensing image, perform inverse BRDF simulation on the simulated sub-satellite surface reflectance of the target multispectral satellite remote sensing image, and obtain the simulated observation direction surface reflectance of the target multispectral satellite remote sensing image.

[0044] In this embodiment, the processing device obtains the heterogeneous satellite spectral matching coefficient. Specifically, the processing device obtains the sensor spectral response functions corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and performs simulated spectral reflectance calculations on the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image according to the corresponding sensor spectral response functions and a preset United States Geological Survey (USGS) ground feature spectral library to obtain the simulated spectral reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image. According to the simulated spectral reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, the heterogeneous satellite spectral matching coefficient is obtained.

[0045] The processing device calculates the sub-satellite surface reflectance of the reference multispectral satellite remote sensing image and the heterogeneous satellite spectral matching coefficient to obtain the simulated sub-satellite surface reflectance of the target multispectral satellite remote sensing image, and uses the surface bidirectional reflectance distribution correction model to perform inverse BRDF simulation on the simulated sub-satellite surface reflectance of the target multispectral satellite remote sensing image according to the observed geometric data of the target multispectral satellite remote sensing image to obtain the simulated observation direction surface reflectance of the target multispectral satellite remote sensing image.

[0046] S33: Perform radiation transmission simulation according to the atmospheric auxiliary data, observation geometry data and a preset LibRadtran model in the auxiliary data corresponding to the target multispectral satellite remote sensing image to obtain the simulated top-of-atmosphere radiance of the target multispectral satellite remote sensing image.

[0047] LibRadtran is a publicly available radiation transfer package library used in various scientific fields to calculate radiance values, irradiance values ​​and photochemical flux in different spectral regions. The raw L1 level data can be atmospherically corrected using the Uvspec model in LibRadtran, atmospheric profile data such as aerosol optical depth and water vapor during imaging, and angle files provided by wide-band satellites. LibRadtran is used to calculate radiation transfer in the Earth's atmosphere, such as irradiance, radiance, brightness, temperature and solar flux.

[0048] In this embodiment, the processing device performs radiation transmission simulation based on the atmospheric auxiliary data, observation geometry data and a preset LibRadtran model in the auxiliary data corresponding to the target multispectral satellite remote sensing image to obtain the simulated top-of-atmosphere radiance of the target multispectral satellite remote sensing image.

[0049] S34: Perform radiation calibration on the target multispectral satellite remote sensing image to obtain the original top-of-atmosphere radiance of the target multispectral satellite remote sensing image, extract invariant feature points based on the simulated top-of-atmosphere radiance of the target multispectral satellite remote sensing image and the original top-of-atmosphere radiance, calculate cross-radiance calibration coefficients based on the invariant feature points, and obtain the cross-radiance calibration coefficients.

[0050] In this embodiment, the processing device performs radiometric calibration on the target multispectral satellite remote sensing image to obtain the original top-of-atmosphere radiance of the target multispectral satellite remote sensing image.

[0051] The processing device performs invariant feature analysis based on the simulated top-of-atmosphere radiance and the original top-of-atmosphere radiance of the target multispectral satellite remote sensing image to obtain the cross-radiance calibration coefficient.

[0052] Specifically, the processing device adopts an iteratively weighted multivariate alteration detection (IR-MAD) method to perform invariant feature analysis on the simulated top-of-atmosphere radiance and the original top-of-atmosphere radiance of the target multispectral satellite remote sensing image, extract a number of radiation stable ground target points as invariant feature points, construct a first invariant feature point set, perform regression fitting on the first invariant feature point set, obtain a regression fitting line between the simulated top-of-atmosphere radiance and the original top-of-atmosphere radiance, calculate a cross-radiation calibration coefficient based on the regression fitting line between the simulated top-of-atmosphere radiance and the original top-of-atmosphere radiance, and obtain the cross-radiation calibration coefficient.

[0053] S4: According to the corresponding auxiliary data, a joint radiation correction is performed on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration, and the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image is obtained. The terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image is used as the radiation-consistent reflectance to obtain the radiation-consistent reflectance corresponding to the reference multispectral satellite remote sensing image.

[0054] In this embodiment, the processing device performs joint radiation correction on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration according to the corresponding auxiliary data, obtains the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and uses the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image as the radiation-consistent reflectance to obtain the radiation-consistent reflectance corresponding to the reference multispectral satellite remote sensing image.

[0055] See also Figure 3 , Figure 3 The schematic flow chart of S4 in the method for joint solution and radiation uniformization of heterogeneous multi-spectral satellites provided in one embodiment of the present application includes steps S41 to S43, which are specifically as follows:

[0056] S41: According to the corresponding auxiliary data, atmospheric correction is performed on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration, so as to obtain the atmospherically corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

[0057] In this embodiment, the processing device performs atmospheric correction on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration according to the corresponding auxiliary data, and obtains the atmospherically corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

[0058] Taking into account the influence of observation angle on the atmospheric radiation transmission path, a pixel-by-pixel atmospheric correction method is adopted. The same radiation transfer model and atmospheric parameters are used in the joint atmospheric correction process. The pixel-level observation geometry information of each satellite is used as input condition to perform atmospheric correction on the satellite apparent reflectivity, so as to improve the consistency of atmospheric correction of heterogeneous satellite radiation.

[0059] See also Figure 4 , Figure 4 The schematic flow chart of S41 in the method for joint solution and radiation uniformization of heterogeneous multi-spectral satellites provided in one embodiment of the present application includes steps S411 to S412, which are specifically as follows:

[0060] S411: Obtain pixel brightness values ​​of several pixels in the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration, and obtain pixel top atmosphere radiation brightness data corresponding to the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration based on the pixel brightness values ​​and the top atmosphere radiation brightness formula.

[0061] In this embodiment, the processing device obtains the pixel brightness values ​​of several pixels in the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration, and obtains the pixel top atmosphere radiation brightness data corresponding to the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration according to the pixel brightness values ​​and the top atmosphere radiation brightness formula, wherein the pixel top atmosphere radiation brightness data includes the top atmosphere radiation brightness values ​​of several pixels, and the top atmosphere radiation brightness formula is:

[0062] L=Gain×DN+offset

[0063] Where, L TOA is the atmospheric top layer radiation brightness value, Gain is the gain coefficient, DN is the pixel brightness value, and offset is the offset coefficient.

[0064] S412: Obtain the atmospherically corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image based on the preprocessed reference multispectral satellite remote sensing image, the pixel atmospheric top layer radiation brightness data corresponding to the target multispectral satellite remote sensing image after cross-radiation calibration, and the atmospheric auxiliary data, observation geometry data and atmospheric correction formula in the corresponding auxiliary data.

[0065] The atmospheric correction formula is:

[0066]

[0067] Where ρ is the surface reflectivity, L0 is the atmospheric path radiation parameter, and E dir is the surface direct radiation parameter, F dif is the surface diffuse radiation parameter, θ is the solar zenith angle parameter, T dir is the direct transmittance of the sensor, T dif is the diffuse transmittance of the sensor, and S is the spherical albedo.

[0068] In this embodiment, the processing device obtains the atmospherically corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image based on the preprocessed reference multispectral satellite remote sensing image, the pixel atmospheric top layer radiation brightness data corresponding to the target multispectral satellite remote sensing image after cross-radiation calibration, and the atmospheric auxiliary data, observation geometry data and atmospheric correction formula in the corresponding auxiliary data, thereby solving the shortcomings of long search time and low accuracy of atmospheric correction results in traditional lookup tables, and improving the accuracy and efficiency of surface reflectance correction corresponding to multispectral satellite remote sensing images.

[0069] S42: Performing terrain correction on the atmospherically corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, respectively, based on the corresponding auxiliary data, to obtain the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

[0070] In this embodiment, the processing device performs terrain correction on the atmospherically corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image according to the corresponding auxiliary data, so as to obtain the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, thereby further improving the consistency of heterogeneous satellite radiation.

[0071] See also Figure 5 , Figure 5The schematic flow chart of S42 in the method for joint solution and radiation uniformization of heterogeneous multi-spectral satellites provided in one embodiment of the present application includes steps S421 to S422, which are specifically as follows:

[0072] S421: Based on the terrain data in the auxiliary data corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, terrain factors corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image are respectively obtained according to a terrain correction formula.

[0073] The terrain factor calculation formula is:

[0074]

[0075] Where P is the terrain factor, is the path length along the sun on the inclined terrain, is the path length along the observation direction on the inclined terrain, θ1 is the solar zenith angle parameter, θ2 is the observation zenith angle parameter, is the solar azimuth parameter, is the observation azimuth parameter, α is the inclined ground slope, and β is the inclined ground aspect.

[0076] In this embodiment, the processing device obtains the path length along the sun direction, the path length along the observation direction, the inclined ground slope and the inclined ground slope aspect on the inclined terrain corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image based on the terrain data in the auxiliary data corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and obtains the terrain factors corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image according to the terrain correction formula.

[0077] S422: Multiply the atmospherically corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image by the corresponding terrain factors, respectively, to obtain the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

[0078] In this embodiment, the processing device multiplies the atmospherically corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image by the corresponding terrain factors, respectively, to obtain the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image. The joint terrain correction takes into account the radiation difference problem under the undulating terrain conditions in mountainous area to further eliminate the radiation difference problem caused by the rugged terrain in the mountainous area.

[0079] S43: According to the corresponding auxiliary data, BRDF correction is performed on the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, respectively, to obtain the sub-satellite surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

[0080] In this embodiment, the processing device performs BRDF correction on the terrain-corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image according to the corresponding auxiliary data, and obtains the terrain-corrected surface reflectance under the satellite corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, further improving the consistency of heterogeneous satellite radiation.

[0081] See also Figure 6 , Figure 6 The schematic flow chart of S43 in the method for joint solution and radiation uniformization of heterogeneous multi-spectral satellites provided in one embodiment of the present application includes steps S431 to S432, which are specifically as follows:

[0082] S431: Based on the observation geometry data in the auxiliary data corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and according to the BRDF correction formula, the BRDF correction factors corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image are respectively obtained.

[0083] The BRDF correction factor calculation formula is:

[0084]

[0085] Where C is the correction factor; is the reflectivity under actual observation conditions, is the reflectivity under the observation condition under the star, Ω1 is the solar geometric angle parameter, Ω2 is the observation geometric angle parameter, Ω 1nadir is the sun geometry parameter at the subsatellite point, Ω 2nadir is the geometric angle parameter of the sub-satellite point observation, K vol is the volume scattering kernel, K geo is the geometric optics kernel, f iso is the isotropic nuclear coefficient, f vol is the volume scattering kernel coefficient, f geo is the geometric optics kernel coefficient.

[0086] In this embodiment, the processing device obtains the BRDF correction factors corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image based on the observation geometry data in the auxiliary data corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image according to the BRDF correction formula.

[0087] S432: Multiply the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image by the corresponding BRDF correction factors respectively to obtain the sub-satellite surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

[0088] In this embodiment, the processing equipment multiplies the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image by the corresponding BRDF correction factors, respectively, to obtain the sub-satellite surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and uses the kernel coefficient provided by the MODIS BRDF product to more accurately reflect the BRDF effects of different regions, further eliminating the radiation differences caused by the BRDF effect.

[0089] S5: spectrally match the terrain-corrected surface reflectance corresponding to the target multispectral satellite remote sensing image to obtain the spectrally matched surface reflectance corresponding to the target multispectral satellite remote sensing image; extract invariant feature points based on the surface reflectance corresponding to the reference multispectral satellite remote sensing image and the spectrally matched surface reflectance corresponding to the target multispectral satellite remote sensing image; perform relative radiation correction based on the extracted invariant feature points to obtain the radiation-consistent reflectance corresponding to the target multispectral satellite remote sensing image.

[0090] In this embodiment, the processing device performs spectral matching on the sub-satellite surface reflectance corresponding to the target multi-spectral satellite remote sensing image to obtain the spectrally matched reflectance corresponding to the target multi-spectral satellite remote sensing image. Specifically, the processing device performs inversion based on the sub-satellite surface reflectance corresponding to the target multi-spectral satellite remote sensing image and the spectral matching coefficient of the heterogeneous satellite to obtain the spectrally matched sub-satellite surface reflectance corresponding to the target multi-spectral satellite remote sensing image, so as to eliminate the radiation inconsistency problem caused by the spectral response differences of each band of the heterogeneous satellite.

[0091] The processing equipment extracts invariant feature points based on the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the spectrally matched reflectance corresponding to the target multispectral satellite remote sensing image, performs relative radiation correction based on the extracted invariant feature points, and obtains the radiation-consistent reflectance corresponding to the target multispectral satellite remote sensing image. Specifically, the processing device adopts an iteratively weighted multivariate change detection (IR-MAD) method to perform invariant feature analysis on the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the spectral matching reflectance corresponding to the target multispectral satellite remote sensing image, extract a number of radiation stable ground target points as invariant feature points, construct a second invariant feature point set, perform regression fitting on the second invariant feature point set, obtain a regression fitting line between the sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the sub-satellite surface reflectance corresponding to the target multispectral satellite remote sensing image after spectral matching, obtain a relative radiation calibration coefficient, multiply the sub-satellite surface reflectance after spectral matching corresponding to the target multispectral satellite remote sensing image by the relative radiation calibration coefficient, and obtain the radiation consistent reflectance corresponding to the target multispectral satellite remote sensing image.

[0092] By performing heterogeneous satellite cross-radiance calibration, joint radiation correction, spectral matching and relative radiation correction on heterogeneous multispectral satellite remote sensing images, a heterogeneous satellite joint solution is provided to solve the spectral radiation inconsistency problem caused by differences in sensor design and imaging conditions in heterogeneous satellite multispectral observation data, ensuring data consistency and comparability.

[0093] Please refer to Figure 7 , Figure 7 A schematic diagram of the structure of a device for joint calculation and radiation consistency processing of heterogeneous multi-spectral satellites provided in one embodiment of the present application. The device can implement all or part of the device for joint calculation and radiation consistency processing of heterogeneous multi-spectral satellites through software, hardware or a combination of both. The device 7 includes:

[0094] A data acquisition module 71 is used to obtain a reference multispectral satellite remote sensing image, a target multispectral satellite remote sensing image and corresponding auxiliary data, wherein the auxiliary data includes atmospheric auxiliary data, observation geometry data and terrain data;

[0095] A preprocessing module 72 is used to preprocess the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, wherein the preprocessing step includes geo-registration and resampling processing;

[0096] The cross-radiation calibration module 73 is used to perform heterogeneous satellite cross-radiation calibration according to the pre-processed reference multi-spectral satellite remote sensing image, the target multi-spectral satellite remote sensing image and the corresponding auxiliary data to obtain a cross-radiation calibration coefficient, and obtain a target multi-spectral satellite remote sensing image after cross-radiation calibration according to the cross-radiation calibration coefficient and the target multi-spectral satellite remote sensing image after geo-registration and resampling processing;

[0097] The joint radiation correction module 74 is used to perform joint radiation correction on the pre-processed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross radiation calibration according to the corresponding auxiliary data, obtain the sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, use the sub-satellite surface reflectance after terrain correction corresponding to the reference multispectral satellite remote sensing image as the radiation uniform reflectance, and obtain the radiation uniform reflectance corresponding to the reference multispectral satellite remote sensing image;

[0098] The radiation consistency adjustment module 75 is used to perform spectral matching on the surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image, obtain the surface reflectance under the satellite after spectral matching corresponding to the target multispectral satellite remote sensing image, extract invariant feature points based on the surface reflectance under the satellite after terrain correction corresponding to the reference multispectral satellite remote sensing image and the reflectance after spectral matching corresponding to the target multispectral satellite remote sensing image, perform relative radiation correction based on the extracted invariant feature points, and obtain the radiation consistent reflectance corresponding to the target multispectral satellite remote sensing image.

[0099] In an embodiment of the present application, a reference multispectral satellite remote sensing image, a target multispectral satellite remote sensing image and corresponding auxiliary data are obtained through a data acquisition module, wherein the auxiliary data include atmospheric auxiliary data, observation geometry data and terrain data; a preprocessing module is used to preprocess the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain preprocessed reference multispectral satellite remote sensing image and target multispectral satellite remote sensing image, wherein the preprocessing step includes geographic registration and resampling processing; a cross-radiation calibration module is used to perform heterogeneous satellite cross-radiation calibration based on the preprocessed reference multispectral satellite remote sensing image, the target multispectral satellite remote sensing image and the corresponding auxiliary data to obtain a cross-radiation calibration coefficient, and a target multispectral satellite remote sensing image after cross-radiation calibration is obtained based on the cross-radiation calibration coefficient and the target multispectral satellite remote sensing image after the geographic registration and resampling processing; a joint radiation correction module is used to perform cross-radiation calibration based on the corresponding The auxiliary data are used to perform joint radiation correction on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross radiation calibration, respectively, to obtain the surface reflectances under the satellite corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and the surface reflectance under the satellite corresponding to the reference multispectral satellite remote sensing image is used as the radiation consistent reflectance to obtain the radiation consistent reflectance corresponding to the reference multispectral satellite remote sensing image; through the radiation consistent adjustment module, spectral matching is performed on the surface reflectance under the satellite after terrain correction corresponding to the target multispectral satellite remote sensing image to obtain the surface reflectance under the satellite after spectral matching corresponding to the target multispectral satellite remote sensing image, invariant feature points are extracted according to the surface reflectance under the satellite corresponding to the reference multispectral satellite remote sensing image and the surface reflectance under the satellite after spectral matching corresponding to the target multispectral satellite remote sensing image, and relative radiation correction is performed according to the extracted invariant feature points to obtain the radiation consistent reflectance corresponding to the target multispectral satellite remote sensing image. By performing heterogeneous satellite cross-radiance calibration, joint radiation correction, spectral matching and relative radiation correction on heterogeneous multispectral satellite remote sensing images, a heterogeneous satellite joint solution is provided to solve the spectral radiation inconsistency problem caused by differences in sensor design and imaging conditions in heterogeneous satellite multispectral observation data, ensuring data consistency and comparability.

[0100] Please refer to Figure 8 , Figure 8 The computer device 8 is a schematic diagram of a structure of a computer device provided in an embodiment of the present application. The computer device 8 includes: a processor 81, a memory 82, and a computer program 83 stored in the memory 82 and executable on the processor 81; the computer device may store multiple instructions, which are suitable for being loaded and executed by the processor 81. Figures 1 to 6 The method steps of the embodiment shown in the figure can be found in the specific implementation process. Figures 1 to 6The specific description of the illustrated embodiment will not be repeated here.

[0101] Among them, the processor 81 may include one or more processing cores. The processor 81 uses various interfaces and lines to connect various parts in the server, and executes various functions and processes data of the heterogeneous multi-spectral satellite joint solution and radiation consistency processing device 7 by running or executing instructions, programs, code sets or instruction sets stored in the memory 82, and calling the data in the memory 82. Optionally, the processor 81 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programble Logic Array, PLA). The processor 81 can integrate one or more combinations of a central processing unit 81 (Central Processing Unit, CPU), an image processor 81 (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the touch display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 81, and it can be implemented by a single chip.

[0102] Among them, the memory 82 may include a random access memory 82 (Random Access Memory, RAM), and may also include a read-only memory 82 (Read-Only Memory). Optionally, the memory 82 includes a non-transitory computer-readable storage medium. The memory 82 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 82 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch instructions, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 82 may also be optionally at least one storage device located away from the aforementioned processor 81.

[0103] The present application also provides a storage medium that can store multiple instructions, which are suitable for the processor to load and execute the above-mentioned Figures 1 to 6 The method steps of the embodiment shown in the figure can be found in the specific implementation process. Figures 1 to 6The specific description of the illustrated embodiment will not be repeated here.

[0104] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0105] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0106] Those skilled in the art will appreciate that the units and formula steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraint formula of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0107] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0108] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0110] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc.

[0111] The present invention is not limited to the above-mentioned embodiments. If various changes or modifications to the present invention do not depart from the spirit and scope of the present invention, and if these changes and modifications fall within the scope of the claims and equivalent technologies of the present invention, the present invention is also intended to include these changes and modifications.

Claims

1. A method for joint calculation and radiation uniformity processing of heterogeneous multi-spectral satellites, characterized in that: The following steps are involved: Obtaining a reference multispectral satellite remote sensing image, a target multispectral satellite remote sensing image, and corresponding auxiliary data, wherein the auxiliary data includes atmospheric auxiliary data, observation geometry data, and terrain data; Preprocessing the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, wherein the preprocessing step includes geo-registration and resampling processing; According to the preprocessed reference multispectral satellite remote sensing image, the target multispectral satellite remote sensing image and the corresponding auxiliary data, a heterogeneous satellite cross-radiation calibration is performed to obtain a cross-radiation calibration coefficient, and according to the cross-radiation calibration coefficient and the target multispectral satellite remote sensing image after the geo-registration and resampling processing, a target multispectral satellite remote sensing image after cross-radiation calibration is obtained; According to the corresponding auxiliary data, a joint radiation correction is performed on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration to obtain the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, and the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image is used as the radiation-consistent reflectance to obtain the radiation-consistent reflectance corresponding to the reference multispectral satellite remote sensing image; Spectral matching is performed on the terrain-corrected surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image to obtain the spectrally matched surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image; invariant feature points are extracted based on the terrain-corrected surface reflectance under the satellite corresponding to the reference multispectral satellite remote sensing image and the spectrally matched surface reflectance under the satellite corresponding to the target multispectral satellite remote sensing image; relative radiation correction is performed based on the extracted invariant feature points to obtain the radiation-consistent reflectance corresponding to the target multispectral satellite remote sensing image.

2. The method for joint calculation and radiation uniformity processing of heterogeneous multi-spectral satellites according to claim 1 is characterized by: The atmospheric auxiliary data include atmospheric aerosol optical thickness and water vapor data; the observation geometry data include solar geometry angle parameters, observation geometry angle parameters, sub-satellite point solar geometry angle parameters and sub-satellite point observation geometry angle parameters; the solar geometry angle parameters include solar zenith angle parameters and solar azimuth angle parameters; the observation geometry angle parameters include observation zenith angle parameters and observation azimuth angle parameters; the terrain data include digital elevation model DEM data.

3. The method for joint calculation and radiation consistency processing of heterogeneous multi-spectral satellites according to claim 2 is characterized in that: The method of performing heterogeneous satellite cross-radiation calibration based on the pre-processed reference multi-spectral satellite remote sensing image, the target multi-spectral satellite remote sensing image and the corresponding auxiliary data to obtain a cross-radiation calibration coefficient comprises the following steps: According to the preprocessed reference multispectral satellite remote sensing image and the corresponding atmospheric auxiliary data and observation geometry data in the auxiliary data, atmospheric correction and BRDF correction are performed to obtain the sub-satellite surface reflectance of the reference multispectral satellite remote sensing image; Obtaining a heterogeneous satellite spectral matching coefficient, calculating according to the sub-satellite surface reflectance of the reference multispectral satellite remote sensing image and the heterogeneous satellite spectral matching coefficient, obtaining a simulated sub-satellite surface reflectance of the target multispectral satellite remote sensing image, performing an inverse BRDF simulation on the simulated sub-satellite surface reflectance of the target multispectral satellite remote sensing image, and obtaining a simulated observation direction surface reflectance of the target multispectral satellite remote sensing image; Perform radiation transmission simulation according to the atmospheric auxiliary data, observation geometry data and a preset LibRadtran model in the auxiliary data corresponding to the target multispectral satellite remote sensing image, to obtain the simulated top-of-atmosphere radiance of the target multispectral satellite remote sensing image; The target multispectral satellite remote sensing image is radiated and calibrated to obtain the original top-of-atmosphere radiance of the target multispectral satellite remote sensing image; invariant feature points are extracted based on the simulated top-of-atmosphere radiance of the target multispectral satellite remote sensing image and the original top-of-atmosphere radiance; cross-radiation calibration coefficients are calculated based on the invariant feature points to obtain the cross-radiation calibration coefficients.

4. The method for joint calculation and radiation uniformity processing of heterogeneous multi-spectral satellites according to claim 3 is characterized in that: The method comprises the steps of performing joint radiation correction on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross radiation calibration according to the corresponding auxiliary data, so as to obtain the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image. According to the corresponding auxiliary data, atmospheric correction is performed on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration, so as to obtain the atmospherically corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image; According to the corresponding auxiliary data, terrain correction is performed on the atmospherically corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, respectively, to obtain the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image; According to the corresponding auxiliary data, BRDF correction is performed on the terrain-corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, respectively, to obtain the terrain-corrected surface reflectance under the satellite corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

5. The method for joint calculation and radiation uniformity processing of heterogeneous multi-spectral satellites according to claim 4 is characterized in that: The method of performing atmospheric correction on the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration according to the corresponding auxiliary data to obtain the atmospherically corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image comprises the following steps: Obtain pixel brightness values ​​of several pixels in the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration, and obtain pixel top atmosphere radiation brightness data corresponding to the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross-radiation calibration according to the pixel brightness values ​​and the top atmosphere radiation brightness formula, wherein the pixel top atmosphere radiation brightness data includes the top atmosphere radiation brightness values ​​of several pixels, and the top atmosphere radiation brightness formula is: L=Gain×DN+offset Where, L TOA is the atmospheric top layer radiation brightness value, Gain is the gain coefficient, DN is the pixel brightness value, and offset is the offset coefficient; According to the preprocessed reference multispectral satellite remote sensing image, the pixel atmospheric top layer radiation brightness data corresponding to the target multispectral satellite remote sensing image after cross-radiation calibration, and the atmospheric auxiliary data, observation geometry data and atmospheric correction formula in the corresponding auxiliary data, the atmospheric corrected surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image is obtained, wherein the atmospheric correction formula is: Where ρ is the surface reflectivity, L0 is the atmospheric path radiation parameter, and E dir is the surface direct radiation parameter, E dif is the surface diffuse radiation parameter, θ is the solar zenith angle parameter, T dir is the direct transmittance of the sensor, T dif is the diffuse transmittance of the sensor, and S is the spherical albedo.

6. The method for joint calculation and radiation uniformity processing of heterogeneous multi-spectral satellites according to claim 4 is characterized in that: The method of performing terrain correction on the atmospherically corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image respectively according to the corresponding auxiliary data to obtain the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, comprises the steps of: Based on the terrain data in the auxiliary data corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, the terrain factors corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image are obtained according to the terrain correction formula, wherein the terrain correction formula is: Where P is the terrain factor, is the path length along the sun on the inclined terrain, is the path length along the observation direction on the inclined terrain, θ1 is the solar zenith angle parameter, θ2 is the observation zenith angle parameter, is the solar azimuth parameter, is the observation azimuth parameter, α is the inclined ground slope, and β is the inclined ground aspect; The atmospherically corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image are respectively multiplied by the corresponding terrain factors to obtain the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

7. The method for joint calculation and radiation uniformity processing of heterogeneous multi-spectral satellites according to claim 4 is characterized in that: The method comprises the steps of performing BRDF correction on the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image respectively according to the corresponding auxiliary data, and obtaining the terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image. Based on the observed geometric data in the auxiliary data corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, the BRDF correction factors corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image are obtained respectively according to the BRDF correction formula, wherein the BRDF correction formula is: Where C is the BRDF correction factor; is the reflectivity under actual observation conditions, is the reflectivity under the observation condition under the star, Ω1 is the solar geometric angle parameter, Ω2 is the observation geometric angle parameter, Ω 1nadir is the sun geometry parameter at the subsatellite point, Ω 2nadir is the geometric angle parameter of the sub-satellite point observation, K vol is the volume scattering kernel, K geo is the geometric optics kernel, f iso is the isotropic nuclear coefficient, f vol is the volume scattering kernel coefficient, f geo is the geometric optics kernel coefficient; The terrain-corrected surface reflectances corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image are respectively multiplied by the corresponding BRDF correction factors to obtain the terrain-corrected surface reflectances under the satellite corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image.

8. A device for joint calculation and radiation uniformity processing of heterogeneous multi-spectral satellites, characterized in that: include: A data acquisition module, used to obtain reference multispectral satellite remote sensing images, target multispectral satellite remote sensing images and corresponding auxiliary data, wherein the auxiliary data includes atmospheric auxiliary data, observation geometry data and terrain data; A preprocessing module is used to preprocess the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image to obtain the preprocessed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, wherein the preprocessing step includes geo-registration and resampling processing; A cross-radiation calibration module is used to perform heterogeneous satellite cross-radiation calibration according to the pre-processed reference multi-spectral satellite remote sensing image, the target multi-spectral satellite remote sensing image and the corresponding auxiliary data to obtain a cross-radiation calibration coefficient, and obtain a target multi-spectral satellite remote sensing image after cross-radiation calibration according to the cross-radiation calibration coefficient and the target multi-spectral satellite remote sensing image after geo-registration and resampling processing; A joint radiation correction module is used to perform joint radiation correction on the pre-processed reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image after cross radiation calibration according to the corresponding auxiliary data, obtain the sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the target multispectral satellite remote sensing image, use the sub-satellite surface reflectance after terrain correction corresponding to the reference multispectral satellite remote sensing image as the radiation consistent reflectance, and obtain the radiation consistent reflectance corresponding to the reference multispectral satellite remote sensing image; The radiation consistency adjustment module is used to perform spectral matching on the terrain-corrected sub-satellite surface reflectance corresponding to the target multispectral satellite remote sensing image to obtain the spectrally matched reflectance corresponding to the target multispectral satellite remote sensing image, extract invariant feature points based on the terrain-corrected sub-satellite surface reflectance corresponding to the reference multispectral satellite remote sensing image and the spectrally matched reflectance corresponding to the target multispectral satellite remote sensing image, perform relative radiation correction based on the extracted invariant feature points, and obtain the radiation consistent reflectance corresponding to the target multispectral satellite remote sensing image.

9. A computer device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor; when the computer program is executed by the processor, the steps of the method for joint solution and radiation uniformity processing of heterogeneous multi-spectral satellites as described in any one of claims 1 to 7 are implemented.

10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of heterogeneous multi-spectral satellite joint solution and radiation uniformity processing as described in any one of claims 1 to 7 are implemented.

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