Method and device for verifying authenticity of land surface temperature product and electronic equipment

Abstract

The application provides a method and device for verifying the authenticity of a land surface temperature product and electronic equipment, and relates to the technical field of remote sensing. The method comprises the following steps: determining a measured land surface temperature based on measured data of each station within the pixel scale of the land surface temperature product; performing quality evaluation on the measured land surface temperature based on the variation range of the daily land surface temperature in a year to obtain a quality evaluation result; and in the case where the quality evaluation result represents that the measured land surface temperature is within a target variation range of the daily land surface temperature, obtaining the true value of the land surface temperature at the pixel scale of the land surface temperature product based on the measured land surface temperature and a pre-constructed land surface temperature spatial scale conversion model. The application can reduce the order-of-magnitude difference between the pixel spatial range of satellite images and the spatial range of ground stations, and improve the accuracy of the authenticity verification of the land surface temperature product.

Description

Technical Field

[0001] This invention relates to the field of remote sensing technology, and in particular to a method, apparatus, and electronic equipment for verifying the authenticity of surface temperature products. Background Technology

[0002] Land surface temperature is a crucial indicator reflecting the interaction and energy exchange between the atmosphere and the Earth's surface. Satellite remote sensing technology is widely used in global dynamic change monitoring research due to its ability to rapidly and accurately provide regional and global high spatiotemporal resolution Earth observation data at a relatively low cost. Furthermore, conducting authenticity verification of satellite land surface temperature products helps to objectively evaluate their accuracy and stability, effectively improves the quantitative level of remote sensing, and is of great significance for the inversion and application of land surface temperature.

[0003] Verification based on ground-based measured data is the mainstream and most direct method for verifying the authenticity of surface temperature data. Its basic idea is to compare the surface temperature obtained by temporally and spatially matching the measured data from ground stations with the data retrieved from satellite data. However, surface temperature is a parameter with strong spatial scale effects, and there is a significant order of magnitude difference between the pixel spatial range of satellite imagery and the spatial range of ground stations. The "true value" of surface temperature at the pixel scale is difficult to obtain. Therefore, this work mainly focuses on areas with relatively uniform ground features (such as lakes and grasslands), directly comparing the pixel values ​​of ground observations and satellite remote sensing products. This does not solve the problem of scale mismatch between the measured data from ground stations and the pixel values ​​of satellite remote sensing products, resulting in poor accuracy in verifying the authenticity of surface temperature products. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention provides a method, apparatus, and electronic device for verifying the authenticity of surface temperature products.

[0005] In a first aspect, the present invention provides a method for verifying the authenticity of a surface temperature product, comprising:

[0006] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product.

[0007] Based on the daily variation range of surface temperature throughout the year, the measured surface temperature is evaluated to obtain the quality evaluation results.

[0008] When the quality evaluation result characterizes the measured surface temperature within the target range of the daily surface temperature variation range, the true value of the surface temperature at the pixel scale of the surface temperature product is obtained based on the measured surface temperature and the pre-constructed surface temperature spatial scale transformation model.

[0009] The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale.

[0010] Optionally, according to the method for verifying the authenticity of a land surface temperature product provided by the present invention, before obtaining the true value of the land surface temperature at the pixel scale based on the measured land surface temperature and a pre-constructed land surface temperature spatial scale transformation model, the method further includes:

[0011] The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale;

[0012] Based on the regression factor and the target surface temperature product at the first preset resolution scale, a surface temperature spatial downscaling model is constructed, and based on the surface temperature spatial downscaling model, a target resolution surface temperature consistent with the spatial resolution of the visible-near infrared band at the second preset resolution scale is obtained.

[0013] Based on the target resolution land surface temperature and the regression factor, a spatial upscaling model for land surface temperature is constructed, and the spatial upscaling model for land surface temperature is used as the spatial scale transformation model for land surface temperature.

[0014] Optionally, according to the method for verifying the authenticity of a surface temperature product provided by the present invention, the measured data includes surface brightness temperature;

[0015] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product, including:

[0016] The surface brightness temperature is corrected based on surface emissivity and atmospheric downdraft radiation to obtain the measured surface temperature.

[0017] Optionally, according to the method for verifying the authenticity of a surface temperature product provided by the present invention, the measured data includes surface upward longwave radiation and atmospheric downward longwave radiation;

[0018] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product, including:

[0019] The measured surface temperature is determined based on the surface upward longwave radiation, the atmospheric downward longwave radiation, the surface broadband emissivity, and the Stefan-Boltzmann constant.

[0020] Optionally, according to the method for verifying the authenticity of a surface temperature product provided by the present invention, before evaluating the quality of the measured surface temperature pairs based on the daily surface temperature variation range over a year and obtaining the quality evaluation result, the method further includes:

[0021] Determine the historical surface temperature observation data for each of the aforementioned stations;

[0022] Based on the historical observation data of surface temperature, a model for simulating the annual temperature variation of surface temperature is developed.

[0023] Based on the annual temperature variation model, the range of daily surface temperature variation during the year is determined.

[0024] Optionally, according to the method for verifying the authenticity of a surface temperature product provided by the present invention, determining the regression factor based on the reflectance of the visible-near-infrared band at the second preset resolution scale includes:

[0025] The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale using the following formula:

[0026]

[0027] Wherein, NDVI is the normalized vegetation index, and as the regression factor, Ref red Represents the reflectivity of the red band at the second preset resolution scale, Ref nir This represents the reflectance of the near-infrared band at the second preset resolution scale.

[0028] Optionally, according to the method for verifying the authenticity of a land surface temperature product provided by the present invention, the step of constructing a spatial downscaling model of land surface temperature based on the regression factor and the target land surface temperature product at the first preset resolution scale includes:

[0029] Based on the regression factor and the target land surface temperature product at the first preset resolution scale, the spatial downscaling model of land surface temperature is constructed using the random forest method.

[0030] Optionally, according to the method for verifying the authenticity of a land surface temperature product provided by the present invention, a spatial upscaling model of land surface temperature is constructed based on the target resolution land surface temperature and the regression factor, including:

[0031] Based on the target resolution land surface temperature and the regression factor, the spatial upscaling model of land surface temperature is constructed using the random forest method.

[0032] Secondly, the present invention also provides a device for verifying the authenticity of surface temperature products, comprising:

[0033] The determination module is used to determine the measured land surface temperature based on the measured data of each station within the pixel scale of the land surface temperature product.

[0034] The quality assessment module is used to assess the quality of the measured surface temperature based on the daily variation range of surface temperature throughout the year, and to obtain the quality assessment results.

[0035] The spatial scale conversion module is used to obtain the true value of the surface temperature at the pixel scale of the surface temperature product based on the measured surface temperature and the pre-built surface temperature spatial scale conversion model, when the quality evaluation result characterizes the first surface temperature within the target range of the daily surface temperature variation.

[0036] The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale.

[0037] Thirdly, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for verifying the authenticity of the surface temperature product as described in the first aspect.

[0038] The present invention provides a method, apparatus, and electronic device for verifying the authenticity of land surface temperature products. By using measured data from various stations within the pixel scale of the land surface temperature product, the measured land surface temperature is determined. Then, based on the daily variation range of land surface temperature throughout the year, a quality evaluation is performed on the measured land surface temperature to obtain a quality evaluation result. When the quality evaluation result indicates that the measured land surface temperature falls within the target variation range of the daily land surface temperature variation range, the true value of the land surface temperature at the pixel scale is obtained based on the measured land surface temperature and a land surface temperature spatial scale conversion model. Furthermore, the land surface temperature spatial scale conversion model is based on a target land surface temperature at a first preset resolution scale. The reflectance of the surface temperature product and the visible-near-infrared band at the second preset resolution scale of the same phase is used to construct the surface temperature spatial scale conversion model. In other words, by quality control of the measured surface temperature, the accuracy of the measured data is ensured. Moreover, a surface temperature spatial scale conversion model is constructed based on the target surface temperature product at the first preset resolution scale and the reflectance of the visible-near-infrared band at the second preset resolution scale of the same phase. Through this surface temperature spatial scale conversion model and the measured surface temperature, the true value of the surface temperature at the pixel scale of the surface temperature product is obtained, which reduces the order of magnitude difference between the pixel spatial range of the satellite image and the spatial range of the ground station, and improves the accuracy of the authenticity verification of the surface temperature product. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0040] Figure 1 This is one of the flowcharts illustrating the method for verifying the authenticity of surface temperature products provided by this invention;

[0041] Figure 2 This is a schematic diagram illustrating the construction of the spatial scale conversion model for land surface temperature provided by this invention;

[0042] Figure 3 This is a schematic diagram of the range of surface temperature quality control values ​​provided by the present invention;

[0043] Figure 4 This is the second flowchart illustrating the method for verifying the authenticity of surface temperature products provided by this invention.

[0044] Figure 5 This is a schematic diagram of the structure of the surface temperature product authenticity verification device provided by the present invention;

[0045] Figure 6 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0047] To facilitate a clearer understanding of the various embodiments of the present invention, some relevant background knowledge will be introduced as follows.

[0048] Currently, there are four main methods for verifying the authenticity of land surface temperature products: authenticity verification based on measured data from ground stations, authenticity verification based on radiance, cross-validation, and long-term series verification. The first two methods can obtain absolute accuracy for land surface temperature products, while cross-validation and long-term series verification are simple to implement and widely used, but they only provide relative accuracy.

[0049] Among all verification methods, verification based on ground station measured data is the mainstream and most direct and reliable method for verifying the authenticity of surface temperature. Its basic idea is to compare the surface temperature retrieved from satellite data with the measured data from ground stations in a temporal and spatial match. However, surface temperature is a parameter with strong spatial scale effects, and there is a significant order of magnitude difference between the pixel spatial range of satellite imagery and the spatial range of ground stations. The "true value" of surface temperature at the pixel scale is difficult to obtain. Therefore, this work mainly focuses on areas with relatively uniform ground features (such as lakes and grasslands), directly comparing ground observations with the pixel values ​​of satellite remote sensing products. This does not solve the problem of scale mismatch between ground station measured data and satellite remote sensing product pixel values, which is a key challenge in verifying the authenticity of surface temperature products. Furthermore, relatively uniform ground stations are not easily obtained, and existing observation networks are not specifically designed for verifying the authenticity of surface temperature. Therefore, making full use of existing observation data is also an important issue in verifying the authenticity of surface temperature.

[0050] In summary, the authenticity verification method based on ground station measured data is limited by the scale difference between the two types of surface temperatures, making it difficult to meet the needs of extensive verification of satellite remote sensing products.

[0051] The following description, in conjunction with the accompanying drawings, provides an exemplary description of the method, apparatus, and electronic equipment for verifying the authenticity of surface temperature products provided by the present invention.

[0052] Figure 1 This is one of the flowcharts illustrating the method for verifying the authenticity of surface temperature products provided by this invention, such as... Figure 1 As shown, the method includes:

[0053] Step 100: Determine the measured surface temperature based on the measured data of each station within the pixel scale of the surface temperature product;

[0054] Step 110: Based on the daily variation range of surface temperature throughout the year, evaluate the quality of the measured surface temperature and obtain the quality evaluation result;

[0055] Step 120: If the quality evaluation result characterizes the first surface temperature within the target range of the daily surface temperature variation range, then based on the measured surface temperature and the pre-constructed surface temperature spatial scale conversion model, obtain the true value of the surface temperature at the pixel scale of the surface temperature product.

[0056] The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale.

[0057] It should be noted that the execution subject of the surface temperature product authenticity verification method provided in this embodiment of the invention can be an electronic device, a component in the electronic device, an integrated circuit, or a chip. The electronic device can be a mobile electronic device or a non-mobile electronic device. For example, a mobile electronic device can be a mobile phone, tablet computer, laptop computer, PDA, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc., while a non-mobile electronic device can be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This embodiment of the invention does not specifically limit the specific implementation of these methods.

[0058] The following example uses a computer to execute the method for verifying the authenticity of the surface temperature product provided by this invention to illustrate the technical solution of the present invention in detail.

[0059] Specifically, to overcome the significant order-of-magnitude difference between the pixel spatial range of satellite imagery and the spatial range of ground stations in existing technologies, which leads to poor accuracy in verifying the authenticity of land surface temperature products, this invention determines the measured land surface temperature based on measured data from each station within the pixel scale of the land surface temperature product. Then, based on the daily variation range of land surface temperature over a year, a quality assessment of the measured land surface temperature is performed to obtain a quality assessment result. Furthermore, given that the quality assessment result indicates that the measured land surface temperature falls within the target variation range of the daily variation range, the true value of the land surface temperature at the pixel scale of the land surface temperature product is obtained based on a conversion model between the measured land surface temperature and the land surface temperature spatial scale. The conversion model is constructed based on the reflectance of the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale in the same phase. That is, by quality control of the measured surface temperature, the accuracy of the measured data is ensured. Moreover, the surface temperature spatial scale conversion model is constructed based on the reflectance of the target surface temperature product at the first preset resolution scale and the visible-near infrared band at a second preset resolution scale in the same phase. Through this surface temperature spatial scale conversion model and the measured surface temperature, the true value of the surface temperature at the pixel scale of the surface temperature product is obtained, which reduces the order of magnitude difference between the pixel spatial range of satellite imagery and the spatial range of ground stations, and improves the accuracy of the authenticity verification of surface temperature products.

[0060] It should be noted that the surface temperature products in the embodiments of the present invention can be satellite surface temperature products of various resolutions.

[0061] Optionally, in this embodiment of the invention, the measured surface temperature corresponding to each measured data point can be determined based on the measured data of each station within the pixel scale of the surface temperature product.

[0062] It should be noted that there are two main types of instruments used for observing surface temperature: the SI-111 infrared radiometer (8-14 μm, half-angle field of view 22°) and the CNR1 / CNR4 four-component radiometer. The SI-111 infrared radiometer observes surface brightness temperature, while the four-component radiometer observes long-wave upward and downward radiation. First, the measured data from these two devices need to be converted into actual temperature data, i.e., converted into measured surface temperature.

[0063] Optionally, in this embodiment of the invention, after obtaining the measured surface temperature, the quality of the measured surface temperature can be evaluated based on the daily variation range of the surface temperature over a year, and a quality evaluation result can be obtained.

[0064] Optionally, if the measured surface temperature is determined to be within the target range of the given daily surface temperature variation range, the measured surface temperature is determined to be of good quality, and its corresponding quality evaluation result is marked as 0.

[0065] Optionally, if it is determined that the measured surface temperature is not within the target range of the given daily surface temperature variation range, the measured surface temperature is determined to be of poor quality, and its corresponding quality evaluation result is marked as 1.

[0066] Optionally, if it is determined that the measured surface temperature does not exist or is a missing value, the measured surface temperature is determined to be unusable, and its corresponding quality evaluation result is marked as 2.

[0067] For example, Table 1 shows an example of the measured surface temperature quality evaluation label.

[0068] Table 1 Examples of Identification Markers for Measured Surface Temperature Quality

[0069] logo Explanation 0 Good quality (within the given range) 1 Poor quality (outside the given range) 2 Unavailable (data does not exist or contains missing values).

[0070] Optionally, a surface temperature spatial scale conversion model can be constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near-infrared band at a second preset resolution scale in the same phase.

[0071] Optionally, the first preset resolution scale can be any coarse resolution scale within the range of 100 meters to 1000 meters.

[0072] Optionally, the second preset resolution scale can be any high-resolution scale within the range of 10 meters to 30 meters.

[0073] It is understood that, in the embodiments of the present invention, the target surface temperature product at the first preset resolution scale used to construct the surface temperature spatial scale conversion model and the reflectance of the visible-near infrared band at the second preset resolution scale have the same pixel scale.

[0074] Optionally, if the quality assessment result of the measured surface temperature is determined to represent the target range of the daily surface temperature variation range in a year, the measured surface temperature can be input into a pre-constructed surface temperature spatial scale transformation model to obtain the true surface temperature value at the pixel scale of the surface temperature product output by the surface temperature spatial scale transformation model.

[0075] The method for verifying the authenticity of land surface temperature products provided by this invention determines the measured land surface temperature based on measured data from various stations within the pixel scale of the land surface temperature product. Then, based on the daily variation range of land surface temperature throughout the year, a quality evaluation is performed on the measured land surface temperature to obtain a quality evaluation result. When the quality evaluation result indicates that the measured land surface temperature falls within the target variation range of the daily land surface temperature variation range, the true value of the land surface temperature at the pixel scale is obtained based on the measured land surface temperature and a pre-constructed land surface temperature spatial scale conversion model. Furthermore, the land surface temperature spatial scale conversion model is based on a target land surface temperature product at a first preset resolution scale. The reflectance of the target surface temperature product at the first preset resolution scale and the reflectance of the visible-near infrared band at the second preset resolution scale of the same phase are used to construct a surface temperature spatial scale conversion model. By performing quality control on the measured surface temperature, the accuracy of the measured data is ensured. Moreover, a surface temperature spatial scale conversion model is constructed based on the target surface temperature product at the first preset resolution scale and the reflectance of the visible-near infrared band at the second preset resolution scale of the same phase. The true value of the surface temperature at the pixel scale of the surface temperature product is obtained through this surface temperature spatial scale conversion model and the measured surface temperature, which reduces the order of magnitude difference between the pixel spatial range of the satellite image and the spatial range of the ground station, and improves the accuracy of the authenticity verification of the surface temperature product.

[0076] Optionally, before obtaining the true value of the land surface temperature at the pixel scale of the land surface temperature product based on the measured land surface temperature and the pre-constructed land surface temperature spatial scale transformation model, the method further includes:

[0077] The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale;

[0078] Based on the regression factor and the target surface temperature product at the first preset resolution scale, a surface temperature spatial downscaling model is constructed, and based on the surface temperature spatial downscaling model, a target high-resolution surface temperature consistent with the spatial resolution of the visible-near-infrared band at the second preset resolution scale is obtained.

[0079] Based on the target resolution land surface temperature and the regression factor, a spatial upscaling model for land surface temperature is constructed, and the spatial upscaling model for land surface temperature is used as the spatial scale transformation model for land surface temperature.

[0080] Specifically, in this embodiment of the invention, in order to construct a spatial scale conversion model for land surface temperature, a regression factor for constructing the spatial scale conversion model for land surface temperature can first be determined based on the reflectance of the visible-near-infrared band at a second preset resolution scale. Then, based on the regression factor and the target land surface temperature product at a first preset resolution scale, a spatial downscaling model for land surface temperature can be constructed. Based on this spatial downscaling model, a target resolution land surface temperature with the same spatial resolution as the visible-near-infrared band at the second preset resolution scale can be obtained. Then, using the target resolution land surface temperature and the regression factor, a spatial upscaling model for land surface temperature can be constructed. This spatial upscaling model is the constructed spatial scale conversion model for land surface temperature. Then, based on the measured land surface temperature and the spatial upscaling model for land surface temperature (the spatial scale conversion model for land surface temperature), the true value of the land surface temperature at the pixel scale of the land surface temperature product can be obtained.

[0081] Optionally, determining the regression factor based on the reflectance in the visible-near-infrared band at the second preset resolution scale includes:

[0082] The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale using the following formula:

[0083]

[0084] Wherein, NDVI is the normalized vegetation index, and as the regression factor, Ref red Represents the reflectivity of the red band at the second preset resolution scale, Ref nir This represents the reflectance of the near-infrared band at the second preset resolution scale.

[0085] Optionally, the step of constructing a spatial downscaling model of land surface temperature based on the regression factor and the target land surface temperature product at the first preset resolution scale includes:

[0086] Based on the regression factor and the target land surface temperature product at the first preset resolution scale, the spatial downscaling model of land surface temperature is constructed using the random forest method.

[0087] Optionally, constructing a spatial upscaling model of land surface temperature based on the target resolution land surface temperature and the regression factor includes:

[0088] Based on the target resolution land surface temperature and the regression factor, the spatial upscaling model of land surface temperature is constructed using the random forest method.

[0089] Optionally, in this embodiment of the invention, when constructing the spatial scale conversion model of land surface temperature, a regression factor for the spatial scale conversion model of land surface temperature can be constructed first. This regression factor can be used for both the spatial downscaling model and the upscaling model of land surface temperature. The reflectance of the visible-near-infrared band in a medium-to-high resolution sensor can be selected to construct the regression factor. The NDVI (Normalized Difference Vegetation Index) is used as the regression factor. The NDVI is calculated from the reflectance of the red band and the near-infrared band, as shown in the above formula (1).

[0090] Optionally, in embodiments of the present invention, the target land surface temperature product LST can be based on NDVI and a first preset resolution scale. sensor By constructing a spatial downscaling model for land surface temperature, a target resolution land surface temperature (LST) consistent with the spatial resolution of the reflectivity band (visible-near-infrared band) can be obtained. high .

[0091] Figure 2 This is a schematic diagram illustrating the construction of the spatial scale transformation model for land surface temperature provided by this invention, as shown below. Figure 2 As shown, taking the ASTER sensor as an example, the spatial resolution of the ASTER sensor in the thermal infrared band is 90m, the spatial resolution of its surface temperature product is 90m, and the spatial resolution in the visible-near infrared band is 15m. The NDVI is calculated using the reflectance of the red band and the near infrared band. The regression factor of the 15m spatial resolution can be obtained by bilinear interpolation. The surface temperature spatial downscaling model is established using the data within a 10×10 window around the coarse resolution pixel, as shown in formulas (2) and (3):

[0092] LST 15 =RF(X) 15m X 90m LST 90m (2)

[0093] X 15 X 90m =[ρ1, ρ2, ρ 3N ,NDVI] (3)

[0094] The surface temperature downscaling model is based on the random forest algorithm, where RF represents the random forest algorithm, and X... 15m and X 90m These are two independent variables with different spatial resolutions, related to reflectance ρ and NDVI data in the visible-near-infrared band. Reflectance ρ includes the reflectance (ρ1, ρ2, ρ3) of ASTER bands 1, 2, and 3N. 3N ), NDVI is calculated from ASTER bands 2 and 3N.

[0095] Optionally, in embodiments of the present invention, the target resolution surface temperature (LST) obtained after downscaling can be used. high A spatial upscaling model of land surface temperature is constructed using (15m) and regression factors. Then, the measured land surface temperature from the stations is input into this model to obtain the true value of the land surface temperature product at the pixel scale.

[0096] like Figure 2 As shown, taking the ASTER sensor as an example, the surface temperature data after correction and downscaling of the measured surface temperature at the station within a 90m spatial range is used to establish a surface temperature upscaling model with a 15m resolution regression factor to obtain the true value of the satellite surface temperature product at the pixel scale, as shown in formula (4):

[0097]

[0098] The spatial upscaling model for land surface temperature is also based on the Random Forest (RF) algorithm, where LST... 15m By T S Correction, X 15m The independent variable is set at a resolution of 15m and is related to the reflectance ρ and NDVI data in the visible-near infrared band. The reflectance ρ includes the reflectance of ASTER bands 1, 2, and 3N (ρ1, ρ2, ρ3). 3N ), NDVI is calculated from ASTER bands 2 and 3N.

[0099] It should be noted that for high-resolution infrared sensors, when the footprint of the surface temperature observation instrument can represent one pixel, spatial scale transformation is not required. The spatial scale transformation identifiers provided in this embodiment are shown in Table 2.

[0100] Table 2. Spatial Scale Conversion Symbols for Land Surface Temperature

[0101] logo Explanation 0 The data is of reliable quality and has undergone spatial scale transformation. 1 The point of spatial scale transformation is not in the image. 2 There is no corresponding quality-controlled measured data for the points of spatial scale transformation and the image observation time. 3 The instrument footprint at the measuring point does not require spatial scale transformation. 4 The measured data is unavailable, making spatial scale transformation impossible. 5 The image has too few effective pixels to perform spatial scale transformation.

[0102] Optionally, the measured data includes surface brightness temperature;

[0103] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product, including:

[0104] The surface brightness temperature is corrected based on surface emissivity and atmospheric downdraft radiation to obtain the measured surface temperature.

[0105] It should be noted that the SI-111 infrared radiometer has an absolute accuracy of ±0.2K for a temperature range of 238K to 338K. The surface brightness temperature measured by the SI-111 infrared radiometer needs to be corrected for surface emissivity and downward atmospheric radiation.

[0106] Assume T r If the surface brightness temperature is measured by the SI-111 infrared radiometer, then the true surface temperature T is... s The measured surface temperature can be calculated using the following formula (5):

[0107]

[0108] Where B represents the Planck function, ε represents the surface emissivity of channel SI-111 (calculated based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Emissivity Database (ASTER-GED)), and L... ↓ This indicates downward atmospheric radiation.

[0109] Optionally, the measured data includes surface upward longwave radiation and atmospheric downward longwave radiation;

[0110] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product, including:

[0111] The measured surface temperature is determined based on the surface upward longwave radiation, the atmospheric downward longwave radiation, the surface broadband emissivity, and the Stefan-Boltzmann constant.

[0112] Optionally, for the surface longwave radiation and atmospheric downwave longwave radiation data observed by the four-component radiometer, the measured surface temperature T can be calculated using the following formula (6). s :

[0113]

[0114] Among them, F ↑ F represents the upward long-wave radiation at the Earth's surface. ↓ This represents longwave radiation descending through the atmosphere (unit: W·m).2 ), ε b ε represents the broadband emissivity (BBE) of the Earth's surface. b The emissivity was estimated using the ASTER GED broadband method, where σ represents the Stefan-Boltzmann constant (valued at 5.67 × 10⁻⁶). -8 W·m 2 ·K -4 ).

[0115] Optionally, before evaluating the quality of the measured surface temperature pairs based on the daily surface temperature variation range over a year and obtaining the quality evaluation result, the method further includes:

[0116] Determine the historical surface temperature observation data for each of the aforementioned stations;

[0117] Based on the historical observation data of surface temperature, a model for simulating the annual temperature variation of surface temperature is developed.

[0118] Based on the annual temperature variation model, the range of daily surface temperature variation during the year is determined.

[0119] Specifically, in this embodiment of the invention, in order to determine the range of daily surface temperature variation throughout the year, the historical observation data of surface temperature at each station can be determined first, and then an annual temperature variation model of surface temperature can be simulated based on the historical observation data of surface temperature at each station. Finally, based on the annual temperature variation model, the range of daily surface temperature variation throughout the year can be determined.

[0120] Optionally, in embodiments of the present invention, the range of daily surface temperature variation throughout the year can be calculated based on years of historical observation data of the site or remote sensing surface temperature products.

[0121] It should be noted that surface temperature has obvious diurnal and seasonal variation characteristics. Historical observation data of surface temperature for each station should be collected. If historical observation data for a station is not available, MODIS surface temperature products can be used as a substitute. The daily maximum and minimum surface temperature values ​​are determined by the annual temperature cycle (ATC) model of surface temperature simulated by the daily maximum and minimum temperatures, as shown in formula (7):

[0122]

[0123] Where LST represents the annual surface temperature variation, MAST represents the annual average surface temperature, YAST represents the annual amplitude of surface temperature (≥0K), Theta represents the phase shift relative to the vernal equinox in the Northern Hemisphere, and the surface temperature effective values ​​that are included three or more times in a year can be solved by the least squares method, and d represents the Julian day.

[0124] Figure 3 This is a schematic diagram of the surface temperature quality control value range provided by the present invention, as shown below. Figure 3 As shown, the data are the measured surface temperature of the DM station (100.3722°E, 38.8556°N) in 2016 and the MODIS surface temperature product (MYD11A1) from the Aqua afternoon satellite, respectively. The left-hand lines in the legend represent the MYD11A1 surface temperature product values ​​and the temperature ranges they determine, while the right-hand lines represent the measured surface temperature values ​​at the station and the temperature ranges they determine. The horizontal axis represents Julian Day. It can be seen that the temperature ranges determined using the MYD11A1 product are largely consistent with those determined using the measured values. The ATC model can accurately depict the temperature variations at the station using both types of surface temperature data. It should be noted that in this embodiment of the invention, MYD11A1 data from 2012 to 2019 were used to characterize the annual surface temperature variations at the ground station, and this was used as the basis for evaluating the quality of the measured data at the station.

[0125] Figure 4 This is the second flowchart illustrating the method for verifying the authenticity of surface temperature products provided by this invention. Figure 4 As shown, the method includes: firstly, calculating the measured surface temperature based on the ground observation values ​​of each station; then, performing quality control on the measured surface temperature; and finally, obtaining the true surface temperature value at the pixel scale of the surface temperature product based on the measured surface temperature after quality control and the surface temperature spatial scale transformation model. The surface temperature spatial scale transformation model is constructed based on the coarse-resolution surface temperature product (the target surface temperature product at the first preset resolution scale) and the reflectance of the mid-to-high resolution visible-near-infrared band (the reflectance of the visible-near-infrared band at the second preset resolution scale). Moreover, the surface temperature spatial scale transformation model includes a surface temperature spatial downscaling model and a surface temperature spatial upscaling model, which can reduce the order-of-magnitude difference between the pixel spatial range of satellite imagery and the spatial range of ground stations, and improve the accuracy of the surface temperature product authenticity verification.

[0126] It is understood that the embodiments of the present invention fully consider the difficulties faced in verifying the authenticity of ground station measured data. Combining the characteristics of the spatial resolution difference between visible-near infrared and thermal infrared data, a method for verifying the authenticity of land surface temperature products is provided. On the one hand, this method uses the ATC model and historical land surface temperature observation data to determine the daily variation range of land surface temperature throughout the year, thereby achieving quality control of ground station measured data and ensuring the accuracy of the measured data. On the other hand, this method only uses the reflectivity of high-resolution visible-near infrared bands and coarse-resolution land surface temperature products to establish a land surface temperature spatial scale conversion model. Based on the measured land surface temperature and this model, the true value of the satellite land surface temperature product at the pixel scale is obtained, ensuring the universality of the model and its applicability to most sensors.

[0127] The method for verifying the authenticity of land surface temperature products provided by this invention determines the measured land surface temperature based on measured data from various stations within the pixel scale of the land surface temperature product. Then, based on the daily variation range of land surface temperature over a year, a quality evaluation is performed on the measured land surface temperature to obtain a quality evaluation result. When the quality evaluation result indicates that the measured land surface temperature falls within the target variation range of the daily surface temperature variation range, the true value of the land surface temperature at the pixel scale of the land surface temperature product is obtained based on the measured land surface temperature and a land surface temperature spatial scale conversion model. Furthermore, the land surface temperature spatial scale conversion model is based on a target land surface temperature product at a first preset resolution scale. The reflectance of the visible-near-infrared band at the second preset resolution scale of the same phase is used to construct the surface temperature data. This ensures the accuracy of the measured data by quality control of the measured surface temperature. Furthermore, a surface temperature spatial scale conversion model is constructed based on the target surface temperature product at the first preset resolution scale and the reflectance of the visible-near-infrared band at the second preset resolution scale of the same phase. The true value of the surface temperature at the pixel scale of the surface temperature product is obtained through this surface temperature spatial scale conversion model and the measured surface temperature. This reduces the order-of-magnitude difference between the pixel spatial range of the satellite image and the spatial range of the ground station, and improves the accuracy of the surface temperature product authenticity verification.

[0128] The authenticity verification device for surface temperature products provided by the present invention will be described below. The authenticity verification device for surface temperature products described below can be referred to in correspondence with the authenticity verification method for surface temperature products described above.

[0129] Figure 5 This is a schematic diagram of the structure of the surface temperature product authenticity verification device provided by the present invention, as shown below. Figure 5 As shown, the device includes: a determination module 510, a quality evaluation module 520, and a spatial scale conversion module 530; wherein:

[0130] The determination module 510 is used to determine the measured surface temperature based on the measured data of each station within the pixel scale of the surface temperature product.

[0131] The quality evaluation module 520 is used to evaluate the quality of the measured surface temperature based on the daily variation range of surface temperature throughout the year, and to obtain the quality evaluation result.

[0132] The spatial scale conversion module 530 is used to obtain the true value of the surface temperature at the pixel scale of the surface temperature product based on the measured surface temperature and the pre-constructed spatial scale conversion model of the surface temperature, when the quality evaluation result characterizes the measured surface temperature within the target range of the daily surface temperature variation.

[0133] The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale.

[0134] The land surface temperature product authenticity verification device provided by this invention determines the measured land surface temperature based on measured data from various stations within the pixel scale of the land surface temperature product. Then, based on the daily variation range of land surface temperature over a year, it performs a quality evaluation of the measured land surface temperature, obtaining a quality evaluation result. When the quality evaluation result indicates that the measured land surface temperature falls within the target variation range of the daily surface temperature variation range, it obtains the true value of the land surface temperature at the pixel scale of the land surface temperature product based on the measured land surface temperature and a land surface temperature spatial scale conversion model. Furthermore, the land surface temperature spatial scale conversion model is based on a target land surface temperature product at a first preset resolution scale. The reflectance of the visible-near-infrared band at the second preset resolution scale of the same phase is used to construct the surface temperature data. This ensures the accuracy of the measured data by quality control of the measured surface temperature. Furthermore, a surface temperature spatial scale conversion model is constructed based on the target surface temperature product at the first preset resolution scale and the reflectance of the visible-near-infrared band at the second preset resolution scale of the same phase. The true value of the surface temperature at the pixel scale of the surface temperature product is obtained through this surface temperature spatial scale conversion model and the measured surface temperature. This reduces the order-of-magnitude difference between the pixel spatial range of the satellite image and the spatial range of the ground station, and improves the accuracy of the surface temperature product authenticity verification.

[0135] Optionally, the apparatus further includes a model building module, the model building module being used for:

[0136] The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale;

[0137] Based on the regression factor and the target surface temperature product at the first preset resolution scale, a spatial downscaling model for surface temperature is constructed, and based on the spatial downscaling model for surface temperature, a target resolution surface temperature consistent with the spatial resolution of the visible-near-infrared band is obtained.

[0138] Based on the target resolution land surface temperature and the regression factor, a spatial upscaling model for land surface temperature is constructed, and the spatial upscaling model for land surface temperature is used as the spatial scale transformation model for land surface temperature.

[0139] Optionally, the measured data includes surface brightness temperature, and the determining module 510 is specifically used for:

[0140] The surface brightness temperature is corrected based on surface emissivity and atmospheric downdraft radiation to obtain the measured surface temperature.

[0141] Optionally, the measured data includes surface upward longwave radiation and atmospheric downward longwave radiation, and the determining module 510 is specifically used for:

[0142] The measured surface temperature is determined based on the surface upward longwave radiation, the atmospheric downward longwave radiation, the surface broadband emissivity, and the Stefan-Boltzmann constant.

[0143] Optionally, the determining module 510 is further configured to:

[0144] Determine the historical surface temperature observation data for each of the aforementioned stations;

[0145] Based on the historical observation data of surface temperature, a model for simulating the annual temperature variation of surface temperature is developed.

[0146] Based on the annual temperature variation model, the range of daily surface temperature variation during the year is determined.

[0147] Optionally, the model building module is further specifically used for:

[0148] The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale using the following formula:

[0149]

[0150] Wherein, NDVI is the normalized vegetation index, and as the regression factor, Ref red Represents the reflectivity of the red band at the second preset resolution scale, Ref nir This represents the reflectance of the near-infrared band at the second preset resolution scale.

[0151] Optionally, the spatial scale conversion module 530 is further specifically used for:

[0152] Based on the regression factor and the target land surface temperature product at the first preset resolution scale, the spatial downscaling model of land surface temperature is constructed using the random forest method.

[0153] Optionally, the spatial scale conversion module 530 is further specifically used for:

[0154] Based on the target resolution land surface temperature and the regression factor, the spatial upscaling model of land surface temperature is constructed using the random forest method.

[0155] The land surface temperature product authenticity verification device provided by this invention determines the measured land surface temperature based on measured data from various stations within the pixel scale of the land surface temperature product. Then, based on the daily variation range of land surface temperature throughout the year, it performs a quality evaluation of the measured land surface temperature, obtaining a quality evaluation result. When the quality evaluation result indicates that the first land surface temperature falls within the target variation range of the daily land surface temperature variation range, it obtains the true value of the land surface temperature at the pixel scale of the land surface temperature product based on the measured land surface temperature and a land surface temperature spatial scale conversion model. Furthermore, the land surface temperature spatial scale conversion model is based on a target land surface temperature product at a first preset resolution scale and... The reflectance of the visible-near-infrared band at the second preset resolution scale of the same phase is used to construct the surface temperature data. This ensures the accuracy of the measured data by quality control of the measured surface temperature. Furthermore, a surface temperature spatial scale conversion model is constructed based on the target surface temperature product at the first preset resolution scale and the reflectance of the visible-near-infrared band at the second preset resolution scale of the same phase. The true value of the surface temperature at the pixel scale of the surface temperature product is obtained through this surface temperature spatial scale conversion model and the measured surface temperature. This reduces the order-of-magnitude difference between the pixel spatial range of the satellite image and the spatial range of the ground station, and improves the accuracy of the surface temperature product authenticity verification.

[0156] It should be noted that the above-mentioned surface temperature product authenticity verification device provided in the embodiments of the present invention can realize all the method steps implemented in the above-mentioned surface temperature product authenticity verification method embodiments, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiments and the beneficial effects will not be described in detail.

[0157] Figure 6 This is a schematic diagram of the physical structure of the electronic device provided by the present invention, such as... Figure 6As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630, and a communication bus 640, wherein the processor 610, the communication interface 620, and the memory 630 communicate with each other via the communication bus 640. The processor 610 can call logical instructions in the memory 630 to execute the authenticity verification method for the surface temperature product provided by the above methods, which includes:

[0158] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product.

[0159] Based on the daily variation range of surface temperature throughout the year, the measured surface temperature is evaluated to obtain the quality evaluation results.

[0160] When the quality evaluation result characterizes the measured surface temperature within the target range of the daily surface temperature variation range, the true value of the surface temperature at the pixel scale of the surface temperature product is obtained based on the measured surface temperature and the pre-constructed surface temperature spatial scale transformation model.

[0161] The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale.

[0162] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0163] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is capable of executing the method for verifying the authenticity of the land surface temperature product provided by the above methods, the method comprising:

[0164] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product.

[0165] Based on the daily variation range of surface temperature throughout the year, the measured surface temperature is evaluated to obtain the quality evaluation results.

[0166] When the quality evaluation result characterizes the measured surface temperature within the target range of the daily surface temperature variation range, the true value of the surface temperature at the pixel scale of the surface temperature product is obtained based on the measured surface temperature and the pre-constructed surface temperature spatial scale transformation model.

[0167] The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale.

[0168] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods for verifying the authenticity of the surface temperature products provided above, the methods comprising:

[0169] The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product.

[0170] Based on the daily variation range of surface temperature throughout the year, the measured surface temperature is evaluated to obtain the quality evaluation results.

[0171] When the quality evaluation result characterizes the measured surface temperature within the target range of the daily surface temperature variation range, the true value of the surface temperature at the pixel scale of the surface temperature product is obtained based on the measured surface temperature and the pre-constructed surface temperature spatial scale transformation model.

[0172] The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale.

[0173] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0174] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0175] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for verifying the authenticity of a surface temperature product, characterized in that, include: The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product. Based on the daily variation range of surface temperature throughout the year, the measured surface temperature is evaluated to obtain the quality evaluation results. When the quality evaluation result characterizes the measured surface temperature within the target range of the daily surface temperature variation range, the true value of the surface temperature at the pixel scale of the surface temperature product is obtained based on the measured surface temperature and the pre-constructed surface temperature spatial scale transformation model. The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale at the same time. Before obtaining the true value of the land surface temperature at the pixel scale of the land surface temperature product based on the measured land surface temperature and the pre-constructed land surface temperature spatial scale transformation model, the method further includes: The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale; Based on the regression factor and the target surface temperature product at the first preset resolution scale, a surface temperature spatial downscaling model is constructed, and based on the surface temperature spatial downscaling model, a target resolution surface temperature consistent with the spatial resolution of the visible-near infrared band at the second preset resolution scale is obtained. Based on the target resolution land surface temperature and the regression factor, a spatial upscaling model for land surface temperature is constructed, and the spatial upscaling model for land surface temperature is used as the spatial scale transformation model for land surface temperature.

2. The method for verifying the authenticity of surface temperature products according to claim 1, characterized in that, The measured data includes surface brightness temperature; The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product, including: The surface brightness temperature is corrected based on surface emissivity and atmospheric downdraft radiation to obtain the measured surface temperature.

3. The method for verifying the authenticity of surface temperature products according to claim 1, characterized in that, The measured data include surface upward longwave radiation and atmospheric downward longwave radiation; The measured surface temperature is determined based on the measured data of each station within the pixel scale of the surface temperature product, including: The measured surface temperature is determined based on the surface upward longwave radiation, the atmospheric downward longwave radiation, the surface broadband emissivity, and the Stefan-Boltzmann constant.

4. The method for verifying the authenticity of surface temperature products according to any one of claims 1-3, characterized in that, Before obtaining the quality assessment results by evaluating the measured surface temperature pairs based on the daily surface temperature variation range throughout the year, the method further includes: Determine the historical surface temperature observation data for each of the aforementioned stations; Based on the historical observation data of surface temperature, a model for simulating the annual temperature variation of surface temperature is developed. Based on the annual temperature variation model, the range of daily surface temperature variation during the year is determined.

5. The method for verifying the authenticity of surface temperature products according to claim 1, characterized in that, The determination of the regression factor based on the reflectance of the visible-near-infrared band at the second preset resolution scale includes: The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale using the following formula: ； in, The normalized vegetation index (NDI) is used as the regression factor. This represents the reflectivity of the red light band at the second preset resolution scale. This represents the reflectance of the near-infrared band at the second preset resolution scale.

6. The method for verifying the authenticity of surface temperature products according to claim 1, characterized in that, The construction of a spatial downscaling model for land surface temperature based on the regression factor and the target land surface temperature product at the first preset resolution scale includes: Based on the regression factor and the target land surface temperature product at the first preset resolution scale, the spatial downscaling model of land surface temperature is constructed using the random forest method.

7. The method for verifying the authenticity of surface temperature products according to claim 1, characterized in that, The construction of a spatial upscaling model for land surface temperature based on the target resolution land surface temperature and the regression factor includes: Based on the target resolution land surface temperature and the regression factor, the spatial upscaling model of land surface temperature is constructed using the random forest method.

8. A device for verifying the authenticity of a surface temperature product, characterized in that, include: The determination module is used to determine the measured land surface temperature based on the measured data of each station within the pixel scale of the land surface temperature product. The quality assessment module is used to assess the quality of the measured surface temperature based on the daily variation range of surface temperature throughout the year, and to obtain the quality assessment results. The spatial scale conversion module is used to obtain the true value of the land surface temperature at the pixel scale of the land surface temperature product based on the measured land surface temperature and a pre-built spatial scale conversion model, when the quality evaluation result characterizes the measured land surface temperature within the target range of the daily land surface temperature variation. The surface temperature spatial scale conversion model is constructed based on the target surface temperature product at a first preset resolution scale and the reflectance of the visible-near infrared band at a second preset resolution scale at the same time. Before obtaining the true value of the land surface temperature at the pixel scale of the land surface temperature product based on the measured land surface temperature and the pre-constructed land surface temperature spatial scale transformation model, the method further includes: The regression factor is determined based on the reflectance of the visible-near-infrared band at the second preset resolution scale; Based on the regression factor and the target surface temperature product at the first preset resolution scale, a surface temperature spatial downscaling model is constructed, and based on the surface temperature spatial downscaling model, a target resolution surface temperature consistent with the spatial resolution of the visible-near infrared band at the second preset resolution scale is obtained. Based on the target resolution land surface temperature and the regression factor, a spatial upscaling model for land surface temperature is constructed, and the spatial upscaling model for land surface temperature is used as the spatial scale transformation model for land surface temperature.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for verifying the authenticity of the surface temperature product as described in any one of claims 1 to 7.

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