CN112198814B - High-precision thermal radiation directivity semi-empirical semi-physical simulation method - Google Patents

High-precision thermal radiation directivity semi-empirical semi-physical simulation method Download PDF

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CN112198814B
CN112198814B CN202011096835.3A CN202011096835A CN112198814B CN 112198814 B CN112198814 B CN 112198814B CN 202011096835 A CN202011096835 A CN 202011096835A CN 112198814 B CN112198814 B CN 112198814B
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曹彪
杜永明
卞尊健
历华
肖青
柳钦火
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Aerospace Information Research Institute of CAS
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Abstract

The invention discloses a high-precision thermal radiation directivity semi-empirical semi-physical simulation method, which provides a novel trinuclear linear simulation method consisting of a basic shape nucleus (LiStrahlerFriedl nucleus), a hot spot nucleus (Roujean Lagouarde nucleus) and an isotropic nucleus by recombining the conventional thermal infrared band semi-empirical semi-physical nucleus. The hot spot core of the new method has the capability of adjusting the hot spot width and the hot spot height simultaneously, and contains four free variables. The verification of the multi-angle data set based on DART and 4SAIL model simulation shows that compared with the existing semi-empirical semi-physical simulation method only containing three free variables, the method provided by the invention obviously improves the simulation precision of the earth surface heat radiation directivity, is expected to be used for angle correction of earth surface temperature products, and is used for angle normalization of the earth surface temperature products, namely, the earth surface temperature result in the vertical direction is obtained through the earth surface temperature data fitting in multiple groups of inclined directions. The method has important application value in the technical field of spatial information, particularly in the field of quantitative remote sensing.

Description

High-precision thermal radiation directivity semi-empirical semi-physical simulation method
Technical Field
The invention relates to a simulation method, which can be used for correcting the angle of a surface temperature product, belongs to the technical field of satellite remote sensing, and particularly relates to a high-precision thermal radiation directivity semi-empirical semi-physical simulation method.
Background
The surface temperature remote sensing product is widely applied to the fields of hydrology, ecology, meteorology, environment, biological geochemistry and the like, is a direct index for representing the changes in temperature of the earth, and is a basic climate variable in the global change research. Geostationary satellites represented by GOES, MSG, himwari, and FengYun-4 and polar satellites represented by NOAA, Terra/Aqua, and FengYun-3 are all provided with thermal infrared channels to observe thermal radiation information on the earth surface. In the business algorithms for producing these satellite earth surface temperature products, earth surface thermal radiation is assumed to be isotropic and earth observation is usually performed from an oblique direction due to the field of view effect of the sensor.
However, ground, aviation, and satellite scale studies have shown that earth surface thermal radiation is anisotropic and this phenomenon is referred to as thermal radiation directionality. For the different-temperature pixel with a complex three-dimensional structure, the direction brightness and temperature difference observed in different directions can be up to 10K due to the heat radiation directivity, and the precision of a ground surface temperature product is severely restricted. Even on the earth surfaces such as uniform desert, water surface and the like, the phenomenon of obvious heat radiation directivity exists, so that the aim that the precision of earth surface temperature remote sensing products is better than 1K cannot be realized at present.
Therefore, for different earth surface types (vegetation, cities, soil, water, ice and snow and the like), researchers at home and abroad propose a plurality of physical models to describe the phenomenon of heat radiation directivity, establish the relationship between direction brightness temperature and parameters such as earth surface structure, attributes, spectrum, temperature difference and the like, and try to correct the earth surface direction brightness temperature and the earth surface temperature to realize angle normalization. However, these physical models cannot be put into practical use because of too many driving parameters, so in recent years, a semi-empirical semi-physical simulation model of a thermal infrared band is proposed, the solution of the nuclear coefficient is realized by directly inputting the bright temperatures/temperatures in multiple directions, and then the bright temperatures/temperatures in any directions are calculated based on the nuclear coefficient. When the observation angles of all the pixels are corrected to be in the vertical direction, the angle normalization of the surface temperature product is realized.
The thermal infrared semi-empirical semi-physical simulation method which can be used for the surface temperature angle normalization at present mainly comprises four methods: a RossThiick-LiSpareR model and a Roujean Lagouarde model which are directly extended from a visible light band, and a LiStrahlerFriedl-LiDenseR model and a Vinnikov model which are proposed based on a heat radiation characteristic. The results of the prior studies show that the accuracy of the RossThick-LiSpareR and Roujean Lagouarde models is limited by the property of not considering thermal radiation, the Vinnikov model is limited by the fact that the two non-isotropic nuclei in the Vinnikov model are pure examined nuclei, and in contrast, the LiStrahlerFrieFriedl-LiDenseR model has the highest accuracy at present. However, there is still a significant phenomenon of hot spot underestimation, and improvement based on heat radiation characteristics is required.
Disclosure of Invention
In order to solve the defects of the technology, the invention provides a high-precision heat radiation directivity semi-empirical semi-physical simulation method.
In order to solve the technical problems, the invention adopts the technical scheme that: a high-precision thermal radiation directivity semi-empirical semi-physical simulation method comprises the following steps:
step one, constructing a LiStrahlerFriedl-Roujean Lagouarde model:
the LiDenseR geometric optical kernel in the LiStrehlerFriedl-LiDenseR semi-empirical semi-physical model is modified into a Roujean Lagouarde hot spot kernel to obtain a LiStrehlerFriedl-Roujean Lagouarde model, and the formula of the LiStrehlerFriedl-Roujean Lagouarde model is as follows:
Figure GDA0003015444260000021
Figure GDA0003015444260000022
Figure GDA0003015444260000023
wherein the content of the first and second substances,
Figure GDA0003015444260000031
direction light temperature/temperature;
Figure GDA0003015444260000032
is the nucleus of the basic shape of LiStrahlerFriedl;
Figure GDA0003015444260000033
is Roujean Lagouarde hot spot core; f. ofLiStrahlerFriedl，fRoujeanLagouarde，fisoRespectively, the LiStrahlerFriedl basic shape nucleus, the Roujean Lagouarde heat point nucleus and eachNuclear coefficient to isotropic nuclei; thetasIs the solar zenith angle; thetavObserving a zenith angle;
Figure GDA0003015444260000034
k is the hotspot width factor, the relative azimuth of the sun and the direction of observation.
Step two, inverting four unknowns in the LiStrahlerFriedl-Roujean Lagouarde model:
the LiStrahlerFriedl-Roujean Lagouarde model comprises four unknowns which are the basic shape nucleus coefficients f of the LiStrahlerFriedlLiStrahlerFriedlRoujean Lagouarde hot spot nuclear coefficient fRoujeanLagouardeIsotropic nuclear factor fisoAnd a hotspot width factor k;
for inversion, for the zenith angle theta of the sunsObserving the zenith angle thetavRelative azimuth of sun and direction of observation
Figure GDA0003015444260000035
Observing for four times or more to obtain four or more angle values, then calculating an optimal solution by adopting a nonlinear least square method, and realizing inversion of four unknowns by adopting an nlinfit function in MATLAB, wherein fLiStrahlerFriedl、fRoujeanLagouarde、fisoAnd the initial values of the k four parameters are respectively set as: 1. 1, Tmean1; wherein T ismeanThe average value of the input multi-angle observed brightness temperature/temperature is obtained.
Step three, verifying the constructed LiStrahlerFriedl-Roujean Lagouarde model:
the simulation capability of LiStrahlerFriedl-Roujean Lagouarde is verified to be divided into two parts: firstly, verifying the fitting precision of the LiStrahlerFriedl-Roujean Lagouarde model by using the brightness temperature of the 4SAIL standard physical model and the DART standard physical model in the multi-angle direction; then the fitting result is compared with the LiStrahlerFriedl-LiDenseR model before improvement and the RossThick-LiSpareR thermal infrared semi-empirical semi-physical model, Roujean Lagouarde thermal infrared semi-empirical semi-physical model, Vinnikov thermal infrared semi-empirical modelComparing the semi-physical models, and selecting evaluation indexes including root mean square error RMSE, maximum absolute fitting error | Bias-maxAnd the correlation coefficient R2。
And step four, fitting the data obtained in the step three, normalizing the angle of the surface temperature product, and correcting the observation angles of all the pixels from the inclined direction to the vertical direction.
Further, the formula of the listahlerpriedl-LiDenseR semi-empirical semi-physical model can be expressed as:
Figure GDA0003015444260000041
wherein the content of the first and second substances,
Figure GDA0003015444260000042
direction light temperature/temperature;
Figure GDA0003015444260000043
is the nucleus of the basic shape of LiStrahlerFriedl;
Figure GDA0003015444260000044
is LiDenseR geometric optical nucleus; f. ofLiStrahlerFriedl，fLiDenseR，fisoCoefficients for the listahlerpriedl basic shape nucleus, the LiDenseR geometric optical nucleus and the isotropic nucleus, respectively; thetasIs the solar zenith angle; thetavObserving a zenith angle;
Figure GDA0003015444260000045
the relative azimuth of the sun and the direction of observation.
Further, both the listahlerpriedl basic shape kernel and the LiDenseR geometric optics kernel are non-isotropic kernels, and both are a function of sun and observation angle.
The invention overcomes the problem that the hot spot underestimation phenomenon is generated when the geometric optical kernel based on discrete vegetation derivation is applied to a continuous vegetation scene. By replacing the geometric optical kernel with the hot spot kernel, the free variables are increased from three to four, and the fitting precision in the hot spot area is improved. The method has the advantages that the multi-angle brightness temperature/temperature of the discrete vegetation scene is guaranteed to be fitted with high precision, the fitting capability of the continuous vegetation multi-angle brightness temperature/temperature is remarkably improved, and the problem of continuous vegetation scene hotspot underestimation existing in the conventional thermal infrared semi-empirical semi-physical model is solved.
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FIG. 1 is an overall flow chart of the present invention.
FIG. 2 is a graph of simulation results of a DART model for discrete vegetation.
Fig. 3 is a graph of simulation results of the 4SAIL model for continuous vegetation.
FIG. 4 is a graph of simulation results of the present invention and DART models for discrete vegetation.
Fig. 5 is a graph of simulation results for continuous vegetation for the present invention and 4SAIL model.
Fig. 6 is a graph of simulation results of four prior thermal infrared semi-empirical semi-physical methods for discrete vegetation.
Fig. 7 is a graph of simulation results of the prior four thermal infrared semi-empirical semi-physical methods for continuous vegetation.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The high-precision heat radiation directivity semi-empirical semi-physical simulation method shown in FIG. 1 comprises the following steps:
step one, constructing a LiStrahlerFriedl-Roujean Lagouarde model:
geometric optical models of canopy reflectivity for dense forest canopies were proposed by Li et al in 1992, and 1995Wanner et al proposed a LiDenseR kernel based on this model to characterize the contributions of illumination and shadow components. Subsequently, Li, Strahler and Friedl et al have proposed a conceptual model of the directionality of thermal radiation of heterogeneous terrain in 1999, Su et al have proposed a simplified anisotropic kernel (called LiStrahlerFriedl kernel) based on this conceptual model in 2002 to characterize the contributions of the upper and lower layers of vegetation canopy, and have further proposed a semi-empirical semi-physical model of the directionality of thermal radiation consisting of the LiStrahlerFriedl kernel, LiDenseR kernel and isotropic kernel (i.e., LiStrahlerFriedel-LiDenseR model).
The LiStrahlerFriedl nucleus is a function of angle and can be expressed as:
Figure GDA0003015444260000051
wherein the content of the first and second substances,
Figure GDA0003015444260000052
is the nucleus of the basic shape of LiStrahlerFriedl; thetasIs the solar zenith angle; thetavObserving a zenith angle;
Figure GDA0003015444260000053
the relative azimuth of the sun and the direction of observation.
The LiDenseR kernel is also a function of angle, and its formula can be expressed as:
Figure GDA0003015444260000054
Figure GDA0003015444260000055
Figure GDA0003015444260000056
Figure GDA0003015444260000057
Figure GDA0003015444260000058
Figure GDA0003015444260000061
Figure GDA0003015444260000062
the formula of the LiStrahlerFriedl-LiDenseR semi-empirical semi-physical model can be expressed as:
Figure GDA0003015444260000063
wherein the content of the first and second substances,
Figure GDA0003015444260000064
direction light temperature/temperature;
Figure GDA0003015444260000065
is LiDenseR geometric optical nucleus;
Figure GDA0003015444260000066
is the nucleus of the basic shape of LiStrahlerFriedl; f. ofLiStrahlerFriedl，fLiDenseR，fisoCoefficients for the listahlerpriedl basic shape nucleus, the LiDenseR geometric optical nucleus and the isotropic nucleus, respectively; thetasIs the solar zenith angle; thetavObserving a zenith angle;
Figure GDA0003015444260000067
the relative azimuth of the sun and the direction of observation.
Based on the formula (1), the LiStrahlerFriedl-LiDenseR model contains three unknowns to be solved: f. ofLiStrahlerFriedl，fLiDenseRAnd fiso。
The LiStrahlerFriedl basic shape kernel in the model is used for describing basic characteristics of a bowl shape, and the LiDenseR geometric optical kernel is used for describing a hot spot phenomenon caused by geometric occlusion; since the LiDenseR geometric optical kernel is derived from a discrete vegetation scene, the LiDenseR geometric optical kernel can achieve a good simulation effect in the heat radiation directivity fitting of the discrete scene, but can generate a significant hot point underestimation problem for the widely existing continuous vegetation scenes (grassland, farmland and the like), and therefore the LiDenseR geometric optical kernel is only suitable for the discrete vegetation.
Based on this, the present invention proposes to modify the LiDenseR geometric-optical kernel only applicable to discrete vegetation in the listahler friedl-LiDenseR semi-empirical semi-physical model to Roujean Lagouarde hot spot kernel, originally proposed by Roujean et al, which first proposed a non-linear kernel fitting the crown layer reflectivity hot spot characteristics in 2000, and then Lagouarde extended the model to the thermal infrared band in 2008, so called Roujean Lagouarde kernel, whose formula is shown below:
Figure GDA0003015444260000068
Figure GDA0003015444260000071
the LiStrahlerFriedl-Roujean Lagouarde model is obtained after the semi-empirical semi-physical model of LiStrahlerFriedl-LiDenseR is modified, and the formula of the LiStrahlerFriedl-Roujean Lagouarde model is as follows:
Figure GDA0003015444260000072
Figure GDA0003015444260000073
Figure GDA0003015444260000074
wherein the content of the first and second substances,
Figure GDA0003015444260000075
direction light temperature/temperature;
Figure GDA0003015444260000076
is the nucleus of the basic shape of LiStrahlerFriedl;
Figure GDA0003015444260000077
is Roujean Lagouarde hot spot core; f. ofLiStrahlerFriedl，fRoujeanLagouarde，fisoThe nuclear coefficients of the LiStrahlerFriedl basic shape nucleus, the Roujean Lagouarde hot spot nucleus and the isotropic nucleus respectively; thetasIs the solar zenith angle; thetavObserving a zenith angle;
Figure GDA0003015444260000078
k is the hotspot width factor, the relative azimuth of the sun and the direction of observation.
Step two, inverting four unknowns in the LiStrahlerFriedl-Roujean Lagouarde model:
the LiStrahlerFriedl-Roujean Lagouarde model comprises four unknowns which are the basic shape nucleus coefficients f of the LiStrahlerFriedlLiStrahlerFriedlRoujean Lagouarde hot spot nuclear coefficient fRoujeanLagouardeIsotropic nuclear factor fisoAnd a hotspot width factor k;
for inversion, for the zenith angle theta of the sunsObserving the zenith angle thetavRelative azimuth of sun and direction of observation
Figure GDA0003015444260000079
Observing for four times or more to obtain four or more angle values, then calculating an optimal solution by adopting a nonlinear least square method, and realizing inversion of four unknowns by adopting an nlinfit function in MATLAB, wherein fLiStrahlerFriedl、fRoujeanLagouarde、fisoAnd the initial values of the k four parameters are respectively set as: 1. 1, Tmean1; wherein T ismeanThe average value of the input multi-angle observed brightness temperature/temperature is obtained.
Step three, verifying the constructed LiStrahlerFriedl-Roujean Lagouarde model:
the simulation capability of LiStrahlerFriedl-Roujean Lagouarde is verified to be divided into two parts: first using 4SAIL standard physical model and DART standardVerifying the fitting precision of the LiStrahlerFriedl-Roujean Lagouarde model, particularly the fitting precision in a hot spot region, by using the multi-angle direction brightness and temperature simulated by the physical model; then comparing the fitting result with the LiStrahlerFriedl-LiDenseR model, the RossThick-LiSpareR thermal infrared semi-empirical semi-physical model, the Roujean Lagouarde thermal infrared semi-empirical semi-physical model and the Vinnikov thermal infrared semi-empirical semi-physical model before improvement to represent the advantages of the invention, wherein the selected evaluation indexes comprise root mean square error RMSE, maximum absolute fitting error | BiasmaxAnd the correlation coefficient R2。
And step four, fitting the data obtained in the step three, normalizing the angle of the surface temperature product, and correcting the observation angles of all the pixels from the inclined direction to the vertical direction.
The method solves the problem that the phenomenon of hot point underestimation is generated when the geometric optical core based on discrete vegetation derivation is applied to a continuous vegetation scene, and the fitting precision in a hot point area is improved by replacing the geometric optical core with the hot point core and increasing the number of free variables from three to four. The method provided by the invention ensures the multi-angle brightness temperature/temperature of the high-precision fitting discrete vegetation scene, obviously improves the fitting capability aiming at the multi-angle brightness temperature/temperature of the continuous vegetation, solves the problem of underestimation of the hot spot of the continuous vegetation scene existing in the conventional thermal infrared semi-empirical semi-physical model, and can be used for angle correction of surface temperature products, so that the method has an important application value in the technical field of spatial information, especially the field of quantitative remote sensing.
The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention.
Example 1:
the DART model is widely used for researching the heat radiation directivity of discrete vegetation, the 4SAIL model is widely used for researching the heat radiation directivity of continuous vegetation, the two physical models with the highest current precision are selected to simulate a multi-angle direction bright temperature data set and used as driving data to solve the unknown number of a semi-empirical semi-physical model, the difference between multi-angle data fitted by the semi-empirical semi-physical model and simulated multi-angle data of the DART/4SAIL model used as driving data is compared, and the fitting precision of the invention is evaluated. The specific implementation steps are shown in figure 1.
Fig. 2 shows the simulation results of typical discrete vegetation direction light and temperature in the solar main plane for DART simulation, and fig. 3 shows the simulation results of typical continuous vegetation direction light and temperature in the solar main plane for 4SAIL simulation, both of which can see significant hot spots, where the hot spots in fig. 3 are sharper than those in fig. 2 because the aperture between the continuous vegetation blades is smaller than that between the crowns.
FIG. 4 shows the simulation result of the LiStrahlerFriedl-Roujean Lagouarde model in the discrete vegetation scene, the dotted line part in the figure is the simulation result of the invention, it can be seen that the simulation of the invention has high precision in both the non-hot spot area and the hot spot area, the maximum deviation in the hot spot area is 0.62K, R is R2Up to 0.996. FIG. 5 shows the simulation results of the LiStrahlerFriedl-Roujean Lagouarde model in the continuous vegetation scene, wherein the dotted line part in the figure is the simulation result of the LiStrahlerFriedl-Roujean Lagouarde model, and the simulation results are high-precision simulation in the non-hot spot area and the hot spot area, and the maximum deviation in the hot spot area is 0.37K, R is R2Is 0.996. Figures 4 and 5 demonstrate the superior performance of the present invention in both discrete and continuous vegetation scenes.
Fig. 6 shows simulation results of the existing four semi-empirical semi-physical models in a discrete vegetation scene, wherein curves from top to bottom at an observation zenith angle of-60 ° sequentially include simulation results of a roujean lagouarde model, simulation results of a Vinnikov model, simulation results of a listahler friedl-lienser model, simulation results of a RossThick-lispearser model, and simulation results of a DART model.
The maximum deviation of the Roujean Lagouarde model in a hot spot region is 2.63K, R2Is 0.798; the maximum deviation of the Vinnikov model in a hot spot region is 1.9K, R2Is 0.906; the maximum deviation of the LiStrahlerFriedl-LiDenseR model in a hot spot region is 0.9K, R2Is 0.977; the maximum deviation of the RossThick-LiSpareR model in the hot spot region is 1.53K, R2Was 0.981.
It can be seen that the Vinnikov model cannot simulate the hot spot phenomenon, resulting in low precision; the Roujean Lagouarde model leads to low precision after forward underestimation and overestimation, and the RossThiick-LiSpareR model is | Bias | when in large observation anglemaxThe accuracy of the LiStrahlerFriedl-LiDenseR model is relatively high up to 1.53K, but the maximum deviation reaches 0.9K, R2Less than 0.98.
FIG. 7 shows the simulation results of the prior four semi-empirical semi-physical models in a continuous vegetation scene, wherein curves from top to bottom at an observation zenith angle of-60 degrees are the simulation result of a Roujean Lagouarde model, the simulation result of a Vinnikov model, the simulation result of a LiStrahlerFriedl-LiDenseR model, the simulation result of a 4SAIL model and the simulation result of a Rosstclick-LiSpareR model.
The maximum deviation of the Roujean Lagouarde model in the hot spot area is 2.88K, R2Is 0.651; the maximum deviation of the Vinnikov model in a hot spot region is 3.7K, R2Is 0.927; the maximum deviation of the LiStrahlerFriedl-LiDenseR model in the hot spot region is 3.12K, R2Is 0.964; the maximum deviation of the RossThick-LiSpareR model in the hot spot region is 2.41K, R2It was 0.962.
It can be seen that the Vinnikov model cannot simulate the hot spot phenomenon, resulting in low precision; the other three models were able to model the hot spot phenomenon but there was a significant underestimation, 2.41K, 2.88K, 3.12K for ross thick-lissparser r, roujean lagouard, listahler friedl-lidense r at the hot spot, respectively. Fig. 6 and 7 show the deficiency of the prior semi-empirical semi-physical model in the simulation capability of continuous vegetation hot spots, and indirectly prove the importance of the invention.
The above embodiments are not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art may make variations, modifications, additions or substitutions within the technical scope of the present invention.

Claims (3)

1. A high-precision thermal radiation directivity semi-empirical semi-physical simulation method is characterized by comprising the following steps: the method comprises the following steps:
step one, constructing a LiStrahlerFriedl-Roujean Lagouarde model:
the LiDenseR geometric optical kernel in the LiStrehlerFriedl-LiDenseR semi-empirical semi-physical model is modified into a Roujean Lagouarde hot spot kernel to obtain a LiStrehlerFriedl-Roujean Lagouarde model, and the formula of the LiStrehlerFriedl-Roujean Lagouarde model is as follows:
Figure FDA0003015444250000011
Figure FDA0003015444250000012
Figure FDA0003015444250000013
wherein the content of the first and second substances,
Figure FDA0003015444250000014
direction light temperature/temperature;
Figure FDA0003015444250000015
is the nucleus of the basic shape of LiStrahlerFriedl;
Figure FDA0003015444250000016
is Roujean Lagouarde hot spot core; f. ofLiStrahlerFriedl，fRoujeanLagouarde，fisoThe nuclear coefficients of the LiStrahlerFriedl basic shape nucleus, the Roujean Lagouarde hot spot nucleus and the isotropic nucleus respectively; thetasIs the solar zenith angle; thetavObserving a zenith angle;
Figure FDA0003015444250000018
is the relative azimuth angle of the sun and the observation direction, and k is the hotspot width factor;
step two, inverting four unknowns in the LiStrahlerFriedl-Roujean Lagouarde model:
the LiStrahlerFriedl-Roujean Lagouarde model comprises four unknowns which are the basic shape nucleus coefficients f of the LiStrahlerFriedlLiStrahlerFriedlRoujean Lagouarde hot spot nuclear coefficient fRoujeanLagouardeIsotropic nuclear factor fisoAnd a hotspot width factor k;
for inversion, for the zenith angle theta of the sunsObserving the zenith angle thetavRelative azimuth of sun and direction of observation
Figure FDA0003015444250000017
Observing for four times or more to obtain four or more angle values, then calculating an optimal solution by adopting a nonlinear least square method, and realizing inversion of four unknowns by adopting an nlinfit function in MATLAB, wherein fLiStrahlerFriedl、fRoujeanLagouarde、fisoAnd the initial values of the k four parameters are respectively set as: 1. 1, Tmean1; wherein T ismeanThe average value of the input brightness temperature/temperature observed in multiple angles is obtained;
step three, verifying the constructed LiStrahlerFriedl-Roujean Lagouarde model:
the simulation capability of LiStrahlerFriedl-Roujean Lagouarde is verified to be divided into two parts: firstly, verifying the fitting precision of the LiStrahlerFriedl-Roujean Lagouarde model by using the brightness temperature of the 4SAIL standard physical model and the DART standard physical model in the multi-angle direction; then comparing the fitting result with the LiStrahlerFriedl-LiDenseR model, the RossThick-LiSpareR thermal infrared semi-empirical semi-physical model, the Roujean Lagouarde thermal infrared semi-empirical semi-physical model and the Vinnikov thermal infrared semi-empirical semi-physical model before improvement, wherein the selected evaluation indexes comprise root mean square error RMSE and maximum absolute fitting error | BiasmaxAnd the correlation coefficient R2；
And step four, fitting the data obtained in the step three, normalizing the angle of the surface temperature product, and correcting the observation angles of all the pixels from the inclined direction to the vertical direction.
2. The high precision thermal radiation directivity semi-empirical semi-physical simulation method of claim 1, characterized in that: the formula of the LiStrahlerFriedl-LiDenseR semi-empirical semi-physical model can be expressed as follows:
Figure FDA0003015444250000021
wherein the content of the first and second substances,
Figure FDA0003015444250000022
direction light temperature/temperature;
Figure FDA0003015444250000023
is the nucleus of the basic shape of LiStrahlerFriedl;
Figure FDA0003015444250000024
is LiDenseR geometric optical nucleus; f. ofLiStrahlerFriedl，fLiDenseR，fisoCoefficients for the listahlerpriedl basic shape nucleus, the LiDenseR geometric optical nucleus and the isotropic nucleus, respectively; thetasIs the solar zenith angle; thetavObserving a zenith angle;
Figure FDA0003015444250000025
the relative azimuth of the sun and the direction of observation.
3. The high precision thermal radiation directivity semi-empirical semi-physical simulation method of claim 2, characterized in that: the LiStrahlerFriedl basic shape kernel and the LiDenseR geometric optics kernel are both non-isotropic kernels, and both are a function of sun and observation angle.
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