A thermal infrared multispectral surface parameter retrieval method based on channel correlation

Abstract

The application provides a thermal infrared multispectral surface parameter retrieval method based on channel correlation, and belongs to the technical field of remote sensing. The application determines the atmospheric water vapor content through a split window covariance ratio method, and then calculates the preliminary atmospheric transmittance of each channel; the correlation of the atmospheric transmittance is used as an optimization function to correct the preliminary atmospheric transmittance between adjacent channels; the atmospheric uplink radiation is obtained based on an atmospheric multilayer model and the atmospheric transmittance; the ASTER-TES is used to retrieve the surface temperature from the ground radiation brightness after the atmospheric correction, and the preliminary surface parameters are obtained; the transmittance ratio is used to correct the atmospheric transmittance, and the surface temperature is refined. The application directly retrieves the surface temperature and emissivity based on the thermal infrared multispectral image, avoids the restriction of the traditional surface temperature retrieval depending on the auxiliary parameters of the atmosphere and the surface emissivity, and the retrieval error problem caused by the space-time inconsistency of the auxiliary information of the atmosphere and the ground, and improves the accuracy of the surface temperature and the emissivity in the retrieval process.

Description

Technical Field

[0001] This invention relates to the field of remote sensing technology, specifically to a method for inverting surface temperature and emissivity from thermal infrared multispectral images based on atmospheric transmittance channel correlation. Background Technology

[0002] Surface temperature is a key parameter of land surface system processes at regional and global scales. It is a result of the interaction between the surface and the atmosphere, as well as the energy exchange between the atmosphere and the land. As a key parameter in many basic disciplines and applied fields, surface temperature provides information on the spatiotemporal variations of the surface energy balance and is widely used in numerical weather prediction, global circulation models, and regional climate models.

[0003] Thermal infrared remote sensing technology, as a primary means of acquiring large-scale, periodic surface temperature information, has been developed for decades. With the rapid development of domestic Earth observation satellite technology, spaceborne thermal infrared remote sensing sensors have been greatly improved in terms of spatial resolution, detection channels, and detection capabilities. China now possesses a variety of high-resolution, multi-channel thermal infrared sensors, including SDGSAT-1 and GF-5B, providing valuable data sources for conducting refined surface temperature retrieval research.

[0004] Based on the number of channels in a satellite thermal infrared payload, various inversion algorithms have been developed, including single-channel (SC), split-window (SW), and temperature emissivity separation (TES) algorithms. For multi-channel thermal infrared sensors, split-window and temperature emissivity separation algorithms are commonly used for surface temperature inversion, but both algorithms have their own challenges. The split-window algorithm, as a mature technology for surface temperature inversion, has the advantage of directly performing atmospheric correction without relying on atmospheric profile data, often utilizing two channels (11 μm and 12 μm) within an atmospheric window to invert surface temperature. However, the split-window algorithm requires pre-acquiring the surface emissivity of both channels, which is often difficult to obtain accurately over a large area in practical applications. While the temperature emissivity separation algorithm can simultaneously invert surface temperature and emissivity and can handle more complex surface conditions, this type of method is limited by atmospheric compensation accuracy, is sensitive to noise information, and has high scene requirements.

[0005] Since surface temperature inversion essentially involves solving an underdetermined system of equations consisting of multiple channel radiative transfer equations, both split-window and temperature-emissivity separation algorithms require additional parameters. These external parameters introduce additional errors, often leading to a decrease in accuracy during practical applications. Utilizing the information inherent in thermal infrared imagery to explore the potential relationships between channels and reduce the input of auxiliary atmospheric parameters is one approach to avoid introducing errors. Summary of the Invention

[0006] To address the shortcomings of the existing technologies, this invention provides a method for inverting land surface temperature and emissivity based on atmospheric transmittance channel correlation in thermal infrared multispectral images, enabling the inversion of land surface temperature and emissivity without the need for auxiliary information.

[0007] To achieve the above objectives, the specific technical solution of the present invention is as follows:

[0008] A first aspect of the present invention provides a method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation, comprising the following steps:

[0009] For atmospheric components that have absorption peaks in the thermal infrared band, the thermal infrared band is divided into multiple atmospheric windows based on the absorption peaks.

[0010] Based on the simulated atmospheric uplift radiation and transmittance spectra generated by the atmospheric profile library, the linear relationship between atmospheric water vapor content and atmospheric transmittance in all bands is fitted. The atmospheric water vapor content is determined using the split window covariance ratio method, and the preliminary atmospheric transmittance of each channel is calculated based on the atmospheric water vapor content and the linear relationship.

[0011] Construct the atmospheric transmittance correlation equation F between adjacent channels within the atmospheric window, and the atmospheric up-radiation and atmospheric transmittance correlation equation G on a single band.

[0012] An optimization function is constructed using equation F to correct the initial atmospheric transmittance of adjacent channels. Based on the corrected atmospheric transmittance, atmospheric upward radiation is calculated using equation G, and atmospheric correction is performed on the entrance pupil radiance according to the radiative transfer equation to obtain the above-ground radiation.

[0013] Surface temperature is calculated (e.g., using the ASTER-TES algorithm) based on atmospherically corrected above-ground radiation and down-going radiation from the TIGR atmospheric profile database. and emissivity ;

[0014] Based on land-atmosphere parameters, the atmospheric transmittance ratio of adjacent channels is calculated using the radiative transfer equation. This ratio is then subtracted from the corrected atmospheric transmittance ratio of the adjacent channels. The atmospheric transmittance is corrected using this difference. If the difference is less than a threshold or the cycle reaches a set number of iterations, the land surface temperature is output. and emissivity The algorithm ends when the convergence condition is not met (the difference is less than the threshold or the set number of iterations is reached), then it returns to the atmospheric transmittance correction and atmospheric correction steps to recalculate.

[0015] Furthermore, using the linear least squares method, a linear relationship between atmospheric water vapor content and atmospheric transmittance across all bands was fitted.

[0016] Furthermore, the formula for determining atmospheric water vapor content using the split-window covariance ratio method is as follows:

[0017] ;

[0018] in, Atmospheric water content; The number of adjacent pixels; and Adjacent channels; and Channels , The Middle Brightness temperature of each pixel; and To be respectively adjacent channels and middle Average brightness temperature of each pixel; , The fitting coefficients are obtained through pre-fitting of simulated data and are wavelength dependent.

[0019] Furthermore, the method for determining adjacent channels within the atmospheric window is as follows: the thermal infrared band is divided according to the absorption peaks of the gases that make up the atmosphere, and sensor channels located in the same atmospheric window are considered adjacent channels.

[0020] Furthermore, the atmospheric transmittance correlation equation F between adjacent channels is as follows:

[0021] ;

[0022] in, and Indicates adjacent channels and Corrected atmospheric transmittance; , , The correlation coefficient is obtained through prefitting of simulated data and is wavelength dependent.

[0023] Furthermore, the correlation equation G between atmospheric upward radiation and atmospheric transmittance in the single band is as follows:

[0024] ;

[0025] in, Indicates upward atmospheric radiation; This represents atmospheric transmittance (atmospheric transmittance after optimization function correction). , The correlation coefficient is obtained through prefitting of simulated data and is wavelength dependent.

[0026] Furthermore, the calculation formula for the optimization function is as follows:

[0027] ;

[0028] in, Indicates adjacent channels and Correct the deviation in atmospheric transmittance before and after correction; and Indicates adjacent channels and Preliminary atmospheric transmittance obtained from atmospheric water vapor content; and Indicates adjacent channels and Corrected atmospheric transmittance; , A parameter that is inversely proportional to atmospheric water vapor content. A parameter that is directly proportional to atmospheric water vapor content; For the revised version Substitute into the atmospheric transmittance correlation equation F.

[0029] Furthermore, the formula for obtaining the above-ground radiation by performing atmospheric correction on the entrance pupil radiance according to the radiative transfer equation is as follows:

[0030] ;

[0031] in, Radiation above ground, The entrance pupil radiance, This is upward atmospheric radiation. Atmospheric transmittance.

[0032] Furthermore, the formula for calculating the ratio of atmospheric transmittance between adjacent channels based on Earth-atmosphere parameters using the radiative transfer equation is as follows:

[0033] ;

[0034] in, and Indicates adjacent channels and Corrected atmospheric transmittance; and Indicates adjacent channels and Observed radiance; and Indicates adjacent channels and Atmospheric upward radiation; and Indicates adjacent channels and Surface emissivity; and Indicates adjacent channels and Surface radiance; and Indicates adjacent channels and Downward atmospheric radiation.

[0035] Furthermore, the formula for correcting atmospheric transmittance using the difference in atmospheric transmittance ratios is as follows:

[0036] ;

[0037] ;

[0038] in, The difference between the ratios; The correction coefficient is obtained by solving this equation; For the pre-calibration channel Atmospheric transmittance; is the correlation coefficient in the atmospheric transmittance correlation equation F; For the corrected channel Atmospheric transmittance.

[0039] Specifically, the method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation includes the following steps:

[0040] Step 1: For atmospheric components that have absorption peaks in the thermal infrared band, divide the thermal infrared band into multiple atmospheric windows based on their absorption peaks, and determine the atmospheric component channels with higher transmittance within the atmospheric windows.

[0041] Step 2: Based on the simulated atmospheric updraft and transmittance spectra generated from the atmospheric profile library, the linear least squares method is used to fit the linear relationship between atmospheric water vapor content and atmospheric transmittance in all bands.

[0042] Step 3: For a given thermal infrared multispectral load, obtain the atmospheric water vapor content by using the split-window covariance ratio method for the entrance pupil radiance of the bands within the atmospheric window, and calculate the preliminary atmospheric transmittance of all channels using the fitted linear relationship.

[0043] Step 4: Construct the atmospheric transmittance correlation equation F between adjacent channels within the atmospheric window, and the atmospheric up-radiation and atmospheric transmittance correlation equation G on a single band.

[0044] Step 5: Based on the atmospheric transmittance correlation equation F, construct an optimization function for the atmospheric transmittance of adjacent channels within the atmospheric window, and optimize the initial atmospheric transmittance.

[0045] Step 6: Based on the updated atmospheric transmittance, calculate the atmospheric upward radiation using the correlation equation G between atmospheric upward radiation and atmospheric transmittance, and perform atmospheric correction on the entrance pupil radiance to obtain the ground-level radiation.

[0046] Step 7: Using the atmospheric down-going radiation lookup table generated by the atmospheric profile library, match the ground radiance with each atmospheric down-going radiation in the lookup table to perform a temperature emissivity separation calculation, evaluate the smoothness of the corresponding emissivity, select the result with the smoothest emissivity among all calculation results, and obtain the corresponding temperature and emissivity.

[0047] Step 8: Substitute the atmospheric upward radiation, atmospheric downward radiation, and ground object parameters (temperature and emissivity) into the radiative transfer equation of the adjacent channel to obtain the atmospheric transmittance ratio of the adjacent channel; calculate the difference between the atmospheric transmittance ratio of the adjacent channel based on the radiative transfer equation and the initial atmospheric transmittance ratio of the adjacent channel. When the difference is less than the threshold or the set number of cycles is reached, use the temperature and emissivity in Step 7 as the inversion result. If the convergence condition is not met (the difference is less than the threshold or the set number of cycles is reached), repeat Steps 5-8 (when repeating Step 5, use the atmospheric transmittance at this time as the initial atmospheric transmittance and substitute it into the optimization function for optimization).

[0048] A second aspect of the present invention provides a surface temperature and emissivity inversion system based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation, for implementing the method shown, comprising:

[0049] Acquisition and Analysis Module: Used to acquire atmospheric thermal infrared multispectral data and divide the thermal infrared band into multiple atmospheric windows based on absorption peaks;

[0050] Atmospheric correlation model construction module: used to fit the linear relationship between atmospheric water vapor content and atmospheric transmittance of all bands, construct the correlation equation of atmospheric transmittance of adjacent channels within the atmospheric window and the correlation equation between atmospheric upward radiation and atmospheric transmittance on a single band.

[0051] The calculation module is used to determine the atmospheric water vapor content using the split-window covariance ratio method, obtain the preliminary atmospheric transmittance of each channel based on the atmospheric water vapor content, construct an optimization function using equation F to correct the preliminary atmospheric transmittance of adjacent channels, calculate the atmospheric upward radiation based on the corrected atmospheric transmittance through the correlation equation between atmospheric upward radiation and atmospheric transmittance, perform atmospheric correction on the entrance pupil radiance, and obtain the above-ground radiation.

[0052] Inversion module: Used to calculate surface temperature and emissivity based on atmospherically corrected above-ground radiation and downlink radiation from the TIGR atmospheric profile database;

[0053] Iterative convergence control module: used to determine whether the difference between the ratio of atmospheric transmittance of adjacent channels based on the radiative transfer equation and the corrected ratio of atmospheric transmittance of adjacent channels is less than a threshold or whether the cycle has reached the set number of times.

[0054] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores program instructions, and when the processor executes the program instructions, it implements the inversion method.

[0055] Compared with the prior art, the advantages of the present invention are:

[0056] (1) The present invention directly retrieves atmospheric transmittance, up-flow radiation, surface temperature and emissivity parameters based on thermal infrared multispectral images, avoiding the limitations of traditional surface temperature retrieval that relies on atmospheric auxiliary parameters and surface emissivity, as well as the retrieval error problem caused by the spatiotemporal inconsistency of ground-atmosphere auxiliary information, thus improving the accuracy of surface temperature and emissivity in the retrieval process.

[0057] (2) This invention utilizes the correlation constraint characteristics between atmospheric transmittance and uplink radiation to construct a direct solution method for surface and atmospheric parameters through the parameter correlation between adjacent bands, thereby avoiding dependence on external prior input data, enhancing the universality of the method and improving real-time processing capabilities. Attached Figure Description

[0058] Figure 1 This is a block diagram of the land-atmosphere parameter inversion system according to an embodiment of the present invention.

[0059] Figure 2 This is a flowchart of the simulation data construction process according to an embodiment of the present invention.

[0060] Figure 3 This is a flowchart of temperature emissivity separation combined with an atmospheric downdraft lookup table, according to an embodiment of the present invention. Detailed Implementation

[0061] To enable those skilled in the art to clearly and completely understand the technical solution of the present invention, the present invention will be further described in detail below with reference to embodiments. Obviously, the embodiments described herein are only for explaining the present invention and are not intended to limit the scope of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0062] This invention is mainly based on the imaging mechanism of thermal infrared multispectral imaging, considering the correlation characteristics between atmospheric parameters, and proposes a method for inverting land surface temperature and emissivity based on the correlation of atmospheric transmittance channels in thermal infrared multispectral images. This method achieves land surface temperature and emissivity inversion without the need for auxiliary information, and includes the following steps:

[0063] For atmospheric components that have absorption peaks in the thermal infrared band, the thermal infrared band is divided into multiple atmospheric windows based on the absorption peaks.

[0064] Based on simulated atmospheric uplift radiation and transmittance spectra generated from an atmospheric profile library, the linear least squares method was used to fit the linear relationship between atmospheric water vapor content and atmospheric transmittance for all bands. The split-window covariance ratio method was used to determine the atmospheric water vapor content, and the preliminary atmospheric transmittance for each channel was calculated based on the atmospheric water vapor content and the aforementioned linear relationship. The calculation formula for determining atmospheric water vapor content using the split-window covariance ratio method is as follows:

[0065] ;

[0066] in, Atmospheric water content; The number of adjacent pixels; and Adjacent channels; and Channels , The Middle Brightness temperature of each pixel; and To be respectively adjacent channels and middle Average brightness temperature of each pixel; , The fitting coefficients are obtained through pre-fitting of simulated data and are wavelength dependent.

[0067] Construct the atmospheric transmittance correlation equation F between adjacent channels within the atmospheric window, and the atmospheric up-radiation and atmospheric transmittance correlation equation G on a single band.

[0068] The atmospheric transmittance correlation equation F between adjacent channels is as follows:

[0069] ;

[0070] in, and Indicates adjacent channels and Corrected atmospheric transmittance; , , The correlation coefficient is obtained through prefitting of simulated data and is wavelength dependent.

[0071] The correlation equation G between atmospheric upward radiation and atmospheric transmittance in a single band is as follows:

[0072] ;

[0073] in, Indicates upward atmospheric radiation; This represents atmospheric transmittance (atmospheric transmittance after optimization function correction). , The correlation coefficient is obtained through prefitting of simulated data and is wavelength dependent.

[0074] The method for determining adjacent channels within the atmospheric window is as follows: the thermal infrared band is divided according to the absorption peaks of the gases that make up the atmosphere, and sensor channels located in the same atmospheric window are considered adjacent channels.

[0075] The atmospheric transmittance correlation is used as an optimization function to correct the initial atmospheric transmittance of adjacent channels. Based on the corrected atmospheric transmittance, the upward atmospheric radiation is calculated using equation G, and the entrance pupil radiance is atmospherically corrected according to the radiative transfer equation to obtain the above-ground radiation. The calculation formula of the optimization function is as follows:

[0076] ;

[0077] in, Indicates adjacent channels and Correct the deviation in atmospheric transmittance before and after correction; and Indicates adjacent channels and Preliminary atmospheric transmittance obtained from atmospheric water vapor content; and Indicates adjacent channels and Corrected atmospheric transmittance; , A parameter that is inversely proportional to atmospheric water vapor content. A parameter that is directly proportional to atmospheric water vapor content; For the revised version Substitute into the atmospheric transmittance correlation equation F;

[0078] The formula for obtaining the above-ground radiation by performing atmospheric correction on the entrance pupil radiance according to the radiative transfer equation is as follows:

[0079] ;

[0080] in, Radiation above ground, The entrance pupil radiance, This is upward atmospheric radiation. Atmospheric transmittance.

[0081] Surface temperature is calculated (e.g., using the ASTER-TES algorithm) based on atmospherically corrected above-ground radiation and down-going radiation from the TIGR atmospheric profile database. and emissivity ;

[0082] Based on land-atmosphere parameters, the atmospheric transmittance ratio of adjacent channels is calculated using the radiative transfer equation. This ratio is then subtracted from the corrected atmospheric transmittance ratio of the adjacent channels. The atmospheric transmittance is corrected using this difference. If the difference is less than a threshold or the cycle reaches a set number of iterations, the land surface temperature is output. and emissivity The algorithm terminates; if the convergence condition is not met (difference less than the threshold or the set number of iterations is reached), it returns to the atmospheric transmittance correction and atmospheric adjustment steps for recalculation; the formula for calculating the ratio of atmospheric transmittance between adjacent channels using land-atmosphere parameters is as follows:

[0083] ;

[0084] in, and Indicates adjacent channels and Corrected atmospheric transmittance; and Indicates adjacent channels and Observed radiance; and Indicates adjacent channels and Atmospheric upward radiation; and Indicates adjacent channels and Surface emissivity; and Indicates adjacent channels and Surface radiance; and Indicates adjacent channels and Downward atmospheric radiation;

[0085] The formula for correcting atmospheric transmittance using the difference in atmospheric transmittance ratios is as follows:

[0086] ;

[0087] ;

[0088] in, The difference between the ratios; For correction factors; For the pre-calibration channel Atmospheric transmittance; is the correlation coefficient in the atmospheric transmittance correlation equation F; For the corrected channel Atmospheric transmittance.

[0089] The method described in this invention fully considers the low signal-to-noise ratio characteristic of thermal infrared multispectral imaging. By leveraging the correlation of atmospheric parameters in adjacent image channels, it reduces the required atmospheric parameters and avoids the input of external auxiliary information, resulting in more scientific and accurate results.

[0090] Specifically, Figure 1 The block diagram of the surface temperature and emissivity inversion system based on atmospheric transmittance channel correlation of thermal infrared multispectral imagery provided in this embodiment of the invention can be divided into three stages to achieve direct temperature and emissivity inversion of input airborne thermal infrared hyperspectral imagery. This embodiment takes the inversion of land-atmosphere parameters from the VIMI thermal infrared multispectral imagery of the Gaofen-5 thermal infrared payload as an example to specifically illustrate the process of the invention, as follows:

[0091] The first step is to prepare the data model, see [link / reference]. Figure 2 Considering that different thermal infrared multispectral sensors possess different imaging optical characteristics in terms of channels, wavelengths, and spectral response functions, it is necessary to conduct simulations based on these optical characteristics. According to the thermal infrared radiative transfer model, five types of land-atmosphere parameters need to be prepared, including atmospheric transmittance, upward and downward radiation, as well as surface temperature and surface emissivity.

[0092] For atmospheric parameters, given the known imaging optical characteristics of VIMI, the MODTRAN atmospheric radiative transfer model is first used, employing any atmospheric profile library. Taking the temperature and humidity profiles and carbon dioxide profiles from the open-source TIGR atmospheric profile library as examples, these are used as inputs to the MODTRAN atmospheric model. The output spectral range covers the VIMI imaging spectral range, obtaining effective hyperspectral atmospheric transmittance and atmospheric uplink and downlink radiation spectra. Then, based on the VIMI spectral response function, the hyperspectral atmospheric parameters are downsampled to generate atmospheric parameters matching VIMI. Simultaneously, the equivalent atmospheric mean temperature is recorded, thus completing the atmospheric simulation database. Preparation complete;

[0093] For the surface emissivity parameter, any surface emissivity spectral library data can be selected. Taking the open-source ECOSTRESS spectral library as an example, all surface emissivity spectra in this library are in hyperspectral form, and the spectral resolution is higher than that of all imaging spectrometers in actual applications. Therefore, all hyperspectral data covering the VIMI spectral imaging range are downsampled, and the corresponding spectral response function is used to downsample them to VIMI-matched bands.

[0094] For surface temperature, the lowest atmospheric temperature is based on the selected TIGR temperature profile, with an additional random additive bias term ranging from -5K to +15K. This completes the preparation of the five basic land-atmosphere parameters. These five parameters are then combined directly based on the radiative transfer model to obtain simulated spectra representing theoretical VIMI observations at different atmospheric levels and surface types. It is important to note that atmospheric transmittance, upward radiation, and downward radiation generated for each atmospheric profile are a single set of parameters and cannot be combined across different profiles.

[0095] Based on the absorption peaks of carbon dioxide, water vapor, and ozone, the four channels of VIMI are divided into two groups of adjacent channels located within the same atmospheric window: Channel 1, Channel 2, and Channels 3 and 4. The absorption rates of various atmospheric components within adjacent channels of the same atmospheric window are similar, leading to similar atmospheric transmittance and a strong correlation.

[0096] Once the simulation dataset suitable for VIMI is completed, atmospheric parameters can be fitted based on this simulation data. The atmospheric parameter correlation model includes three components: the linear relationship between atmospheric water vapor content and atmospheric transmittance in each channel, the correlation equation F between atmospheric transmittance in adjacent channels, and the correlation equation G between atmospheric upward radiation and atmospheric transmittance.

[0097] Regarding the linear relationship between atmospheric water vapor content and atmospheric transmittance in each channel, in the initially constructed atmospheric simulation parameter library... In this process, the atmospheric water vapor content and atmospheric transmittance of each channel generated by each atmospheric profile are used to obtain the atmospheric water vapor content and atmospheric transmittance of each channel by linear least squares.

[0098] For the atmospheric transmittance correlation equation F between adjacent channels, in the initially constructed atmospheric simulation parameter library In the middle, adjacent channels located in the same atmospheric window As a set of objective equations The input is used to obtain the target equation through nonlinear least squares fitting. Fitting coefficients, objective equation Adjacent channels can be realized Atmospheric permeability is subject to initial experimental constraints;

[0099] The correlation equation G between atmospheric upward radiation and atmospheric transmittance is also in the initially constructed atmospheric simulation parameter library. In this process, paired atmospheric uplift radiation and atmospheric transmittance are used as inputs to equation G, and a simplified equation for atmospheric uplift radiation applicable to target channel i is obtained using nonlinear least squares. The coefficient.

[0100] After completing the basic atmospheric correlation model construction, the atmospheric water vapor content of each pixel is obtained using the split-window covariance ratio method on the thermal infrared image. The preliminary atmospheric transmittance of each channel for the corresponding pixel is obtained by using the fitted linear relationship between atmospheric water vapor content and atmospheric transmittance of each channel. An optimization function is used for the atmospheric transmittance of adjacent channels. Correcting atmospheric transmittance, among which, , Set as After obtaining the corrected atmospheric transmittance for each channel, the corrected atmospheric transmittance is used as input, and equation G is used to obtain the atmospheric uplift radiation for each channel, thereby completing the atmospheric correction of the thermal infrared image and obtaining the ground-based radiance.

[0101] Based on the estimated above-ground radiance, combined with the atmospheric downdraft obtained from previous simulations... Under the assumption of spectral smoothing constraint of ground object emissivity, the separation of surface temperature and emissivity is achieved using the statistical empirical relationship equation between maximum and minimum emissivity, with reference to... Figure 3 In this process, the first step is to use a simulated surface emissivity spectral library. Converted to relative emissivity spectrum Then calculate each line The maximum and minimum difference (MMD) is the minimum value of each emissivity spectrum. A pairwise relationship was established with MMD, and the coefficients of equation T were obtained by nonlinear least squares fitting using the nonlinear relationship equation T. This was achieved using a previously generated atmospheric parameter database. In the downlink radiation pool, the temperature emissivity separation result is calculated for each downlink radiation pool using equation T, and then further evaluated using a smoothness evaluation function. The smoothness of each emissivity is calculated, and the temperature and emissivity corresponding to the minimum smoothness are selected as the surface temperature and emissivity inversion results for that pixel. At the same time, the downlink radiation spectrum corresponding to this smoothness is also regarded as the corresponding atmospheric parameter result. Thus, the land-atmosphere parameter inversion of a pixel on the VIMI image is completed.

[0102] For adjacent channels, the ratio formula of atmospheric transmittance of adjacent channels can be obtained by transforming the radiative transfer equation. Substituting the inverted land-atmosphere parameters, the ratio of inverted transmittance can be obtained. The difference is calculated with the corrected atmospheric transmittance ratio of adjacent channels. The difference is used to correct the atmospheric transmittance. Then, the atmospheric parameters are fitted and the temperature and emissivity are inverted again until the difference is less than a certain threshold or the number of iterations reaches the set maximum number. The inverted surface temperature and emissivity are then output as the result.

[0103] The aforementioned method for inverting land surface temperature and emissivity based on atmospheric transmittance channel correlation in thermal infrared multispectral images can be implemented using computer software technology. This invention also provides a system for inverting land surface temperature and emissivity based on atmospheric transmittance channel correlation in thermal infrared multispectral images, comprising: an acquisition and analysis module for acquiring atmospheric thermal infrared multispectral data and dividing the thermal infrared bands into multiple atmospheric windows according to absorption peaks; and an atmospheric correlation model construction module for fitting the linear relationship between atmospheric water vapor content and atmospheric transmittance in all bands, constructing correlation equations for atmospheric transmittance of adjacent channels within the atmospheric window, and establishing correlation equations for individual bands. The system includes: a correlation equation between atmospheric upward radiation and atmospheric transmittance; a calculation module to determine atmospheric water vapor content using the split-window covariance ratio method, obtain preliminary atmospheric transmittance for each channel based on atmospheric water vapor content, correct the preliminary atmospheric transmittance using atmospheric transmittance correlation as an optimization function, calculate atmospheric upward radiation based on the corrected atmospheric transmittance using the correlation equation between atmospheric upward radiation and atmospheric transmittance, perform atmospheric correction on the entrance pupil radiance, and obtain ground-level radiation; an inversion module to calculate surface temperature and emissivity based on atmospherically corrected ground-level radiation and downward radiation from the TIGR atmospheric profile database; and an iterative convergence control module to determine whether the difference between the ratio of atmospheric transmittance of adjacent channels based on the radiative transfer equation and the updated ratio of atmospheric transmittance of adjacent channels is less than a threshold or whether the set number of iterations has been reached.

[0104] Furthermore, embodiments of the present invention also provide an electronic device, including a memory and a processor. The memory stores program instructions, and when the processor executes the program instructions, it implements the method for inverting surface temperature and emissivity based on thermal infrared multispectral images with atmospheric transmittance channel correlation.

[0105] The above detailed embodiments describe the implementation of the present invention; however, the present invention is not limited to the specific details described in the above embodiments. Within the scope of the claims and technical concept of the present invention, various simple modifications and changes can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

Claims

1. A method for inverting land surface temperature and emissivity based on atmospheric transmittance channel correlation in thermal infrared multispectral imagery, characterized in that, Includes the following steps: The thermal infrared band is divided into multiple atmospheric windows based on the absorption peaks of atmospheric components. Based on the simulated atmospheric uplift radiation and transmittance spectra generated by the atmospheric profile library, the linear relationship between atmospheric water vapor content and atmospheric transmittance in all bands is fitted. The atmospheric water vapor content is determined using the split window covariance ratio method, and the preliminary atmospheric transmittance of each channel is calculated based on the atmospheric water vapor content and the linear relationship. Construct the atmospheric transmittance correlation equation F between adjacent channels within the atmospheric window, and the atmospheric up-radiation and atmospheric transmittance correlation equation G on a single band. An optimization function is constructed using equation F to correct the initial atmospheric transmittance of adjacent channels. Based on the corrected atmospheric transmittance, atmospheric upward radiation is calculated using equation G, and atmospheric correction is performed on the entrance pupil radiance according to the radiative transfer equation to obtain the above-ground radiation. Surface temperature was calculated based on atmospherically corrected above-ground radiation and downdraft radiation from the TIGR atmospheric profile database. and emissivity ; Based on land-atmosphere parameters, the atmospheric transmittance ratio of adjacent channels is calculated using the radiative transfer equation. This ratio is then subtracted from the corrected atmospheric transmittance ratio of the adjacent channels. The atmospheric transmittance is corrected using this difference. If the difference is less than a threshold or the cycle reaches a set number of iterations, the land surface temperature is output. and emissivity The algorithm terminates; if the convergence condition is not met, it returns to the atmospheric transmittance correction and atmospheric correction steps for recalculation.

2. The method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery using atmospheric transmittance channel correlation as described in claim 1, characterized in that, The formula for determining atmospheric water vapor content using the split-window covariance ratio method is as follows: ； in, Atmospheric water content; The number of adjacent pixels; and Adjacent channels; and Channels , The Middle Brightness temperature of each pixel; and To be respectively adjacent channels and middle Average brightness temperature of each pixel; , The fitting coefficients are denoted as .

3. The method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation as described in claim 1, characterized in that, The atmospheric transmittance correlation equation F between adjacent channels is as follows: ； in, and Indicates adjacent channels and Corrected atmospheric transmittance; , , This is the correlation coefficient.

4. The method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation as described in claim 1, characterized in that, The correlation equation G between atmospheric upward radiation and atmospheric transmittance in a single band is as follows: ； in, Indicates upward atmospheric radiation; Indicates atmospheric transmittance; , This is the correlation coefficient.

5. The method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation according to claim 3, characterized in that, The formula for calculating the optimization function is as follows: ； in, Indicates adjacent channels and Correct the deviation in atmospheric transmittance before and after correction; and Indicates adjacent channels and Preliminary atmospheric transmittance obtained from atmospheric water vapor content; and Indicates adjacent channels and Corrected atmospheric transmittance; , A parameter that is inversely proportional to atmospheric water vapor content. A parameter that is directly proportional to atmospheric water vapor content; For the revised version Substitute into the atmospheric transmittance correlation equation F.

6. The method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation according to claim 1, characterized in that, The formula for obtaining the above-ground radiation by performing atmospheric correction on the entrance pupil radiance according to the radiative transfer equation is as follows: ； in, Radiation above ground, The entrance pupil radiance, This is upward atmospheric radiation. Atmospheric transmittance.

7. The method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation according to claim 1, characterized in that, The formula for calculating the ratio of atmospheric transmittance between adjacent channels using the radiative transfer equation based on Earth-atmosphere parameters is as follows: ； in, and Indicates adjacent channels and Corrected atmospheric transmittance; and Indicates adjacent channels and Observed radiance; and Indicates adjacent channels and Atmospheric upward radiation; and Indicates adjacent channels and Surface emissivity; and Indicates adjacent channels and Surface radiance; and Indicates adjacent channels and Downward atmospheric radiation.

8. The method for inverting land surface temperature and emissivity based on thermal infrared multispectral imagery with atmospheric transmittance channel correlation according to claim 7, characterized in that, The formula for correcting atmospheric transmittance using the difference in atmospheric transmittance ratios is as follows: ； ； in, The difference between the ratios; For correction factors; For the pre-calibration channel Atmospheric transmittance; is the correlation coefficient in the atmospheric transmittance correlation equation F; For the corrected channel Atmospheric transmittance.

9. A system for retrieving surface temperature and emissivity from thermal infrared multispectral imagery based on atmospheric transmittance channel correlation, used to implement the method described in any one of claims 1-8, characterized in that, include: Acquisition and Analysis Module: Used to acquire atmospheric thermal infrared multispectral data and divide the thermal infrared band into multiple atmospheric windows based on absorption peaks; Atmospheric correlation model construction module: used to fit the linear relationship between atmospheric water vapor content and atmospheric transmittance of all bands, construct the correlation equation of atmospheric transmittance of adjacent channels within the atmospheric window and the correlation equation between atmospheric upward radiation and atmospheric transmittance on a single band. The calculation module is used to determine the atmospheric water vapor content using the split-window covariance ratio method, obtain the preliminary atmospheric transmittance of each channel based on the atmospheric water vapor content, construct an optimization function using equation F to correct the preliminary atmospheric transmittance of adjacent channels, calculate the atmospheric upward radiation based on the corrected atmospheric transmittance through the correlation equation between atmospheric upward radiation and atmospheric transmittance, perform atmospheric correction on the entrance pupil radiance, and obtain the above-ground radiation. Inversion module: Used to calculate surface temperature and emissivity based on atmospherically corrected above-ground radiation and downlink radiation from the TIGR atmospheric profile database; Iterative convergence control module: used to determine whether the difference between the ratio of atmospheric transmittance of adjacent channels based on the radiative transfer equation and the corrected ratio of atmospheric transmittance of adjacent channels is less than a threshold or whether the cycle has reached the set number of times.

10. An electronic device comprising a memory and a processor, the memory storing program instructions, characterized in that, When the processor executes the program instructions, it implements the method according to any one of claims 1-8.

Images