CN111983333A - Method for separating soil radiation signals of passive microwave remote sensing mixed pixel components - Google Patents
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Abstract
The invention relates to the field of microwave remote sensing, and discloses a method for separating soil radiation signals of passive microwave remote sensing mixed pixel components, which comprises the steps of establishing a mixed pixel multi-angle microwave radiation model by using a microwave radiation transmission model; calculating parameters in the mixed pixel multi-angle microwave radiation model by using the vegetation index; acquiring the relation between soil microwave remote sensing radiation signals under different observation angles by using a bare soil surface emission theoretical model; and resolving the multi-angle microwave radiation model of the mixed pixel to obtain the microwave emissivity of the vegetation covered soil and the microwave emissivity of the bare soil in the mixed pixel. The invention fully excavates passive microwave remote sensing multi-angle observation information, separates the mixed pixel microwave remote sensing radiation signals, obtains the microwave emissivity of vegetation cover soil and the emissivity of bare soil in the mixed pixel, and improves the passive microwave remote sensing data processing depth and the applicability and the product precision of surface parameter inversion products.
Description
Technical Field
The invention relates to the field of microwave remote sensing, in particular to a method for separating soil radiation signals of passive microwave remote sensing mixed pixel components.
Background
Microwave remote sensing is a technology for observing scattering and radiation characteristics of a target by using a microwave band. Compared with an optical remote sensing means, the microwave has the advantages of all-weather operation and all-weather operation, has certain penetrating power for the vegetation layer, and can obtain soil information covered by the vegetation. This is also one of the important advantages of microwave remote sensing for inversion of vegetation and soil parameters. In addition, the passive microwave remote sensing mode has the characteristics of short revisiting period and low spatial resolution, and is favorable for obtaining long-term earth observation data with large regional scale. Therefore, the passive microwave remote sensing data is one of important data sources for products such as global or regional long-time vegetation, soil, freeze thawing, snow cover and the like. However, the spatial resolution of the passive microwave remote sensing pixel is usually on the scale of tens of kilometers or even tens of kilometers, the spatial resolution is low, various types of earth surface coverage such as vegetation, water bodies, bare soil, towns and the like may exist in the same pixel at the same time, and the pixel is called as a mixed pixel. Because the microwave radiation difference of different earth surface coverage types is large, the spatial heterogeneity brings great difficulty to the inversion of the earth surface parameters of the mixed pixels.
The traditional passive microwave remote sensing data processing method has the main problems that the microwave radiation signal difference of different earth surface coverage types is not considered, the whole mixed pixel is considered as a whole, and thus inverted earth surface parameters can only be the average value of the mixed pixel, so that a great deal of uncertainty is brought to the processing of passive microwave remote sensing data and the application of earth surface parameter products.
With the development of the passive microwave remote sensing sensor technology, a microwave radiometer capable of carrying out multi-angle observation appears, multi-angle earth observation information can be provided, and the separation of microwave radiation signals of mixed pixel components is possible. Because the common ground surface coverage mixed pixel of the ground surface mainly has vegetation coverage and bare soil in the pixel, how to fully mine the observation information of passive microwave remote sensing multi-angle, separate the mixed pixel mixed vegetation coverage soil and bare soil radiation signal, improve the passive microwave remote sensing data processing depth, improve the applicability and product precision of ground surface parameter inversion products becomes one of the key problems of passive microwave remote sensing data processing and accurate ground surface parameter inversion at present.
Disclosure of Invention
The invention provides a method for separating soil radiation signals of passive microwave remote sensing mixed pixel components, thereby solving the problems in the prior art.
A method for separating passive microwave remote sensing mixed pixel component soil radiation signals comprises the following steps:
s1) establishing a microwave radiation transmission model, and establishing a mixed pixel multi-angle microwave radiation model by using the microwave radiation transmission model;
s2) calculating parameters in the mixed pixel multi-angle microwave radiation model by using the vegetation index;
s3) establishing a soil radiation simulation database and a bare soil surface emission theoretical model, and acquiring the relation between soil microwave remote sensing radiation signals under different observation angles according to the soil radiation simulation database and the bare soil surface emission theoretical model;
s4) calculating the mixed pixel multi-angle microwave radiation model by using the parameters in the mixed pixel multi-angle microwave radiation model in the step S2) and the relation between soil microwave remote sensing radiation signals under different observation angles in the step S3), and obtaining the microwave emissivity of vegetation covered soil and the microwave emissivity of bare soil in the mixed pixel.
Further, in step S1), a microwave radiation transmission model is established, and a mixed pixel multi-angle microwave radiation model is established by using the microwave radiation transmission model, including the following steps:
s11) obtaining mixed pixel microwave radiation TB of vegetation cover soil and bare soilp(θ), θ represents the observation angle, and subscript P represents either horizontal polarization H or vertical polarization V;
s12) acquiring four parts of mixed pixel microwave radiation, wherein the four parts are respectively a vegetation layer uplink radiation part G1(theta) the downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part G2(theta) the upward radiation part of the soil transmits the upward part G through the vegetation3(theta), the soil upgoing radiation part G4(θ)；
S13) establishing a microwave radiation transmission model TB by using the mixed pixel microwave radiation and four parts of the mixed pixel microwave radiationP(θ)＝G1(θ)+G2(θ)+G3(θ)+G4(θ)；
S14) establishing a mixed pixel multi-angle microwave radiation model by using the microwave radiation transmission model, wherein the mixed pixel multi-angle microwave radiation model is expressed as follows:
TBp(θ1) Representing an observation angle of theta1Microwave radiation of the measured mixed pixel; TBP(θi) Representing an observation angle of thetaiMicrowave radiation of the measured mixed pixel; TBp(θN) Representing an observation angle of thetaNThe measured mixed pixels are subjected to microwave radiation.
Further, a radiation part G on the vegetation layer1(θ)＝Fveg(θ)·(1-ω)·(1-exp(-τ·secθ))·Tv(ii) a The downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part
The soil upward radiation part transmits the upward part through the vegetation
Up radiation part of soil
Wherein, Fveg(theta) represents the proportion of the vegetation coverage area at the observation angle theta, 1-Fveg(theta) represents the proportion of the coverage area of the bare soil under the observation angle theta, E represents the soil emissivity, superscript vs represents the soil covered by the vegetation, superscript bs represents the bare soil, tau represents the optical thickness of the vegetation, and T represents the optical thickness of the vegetationvIndicating the surface temperature, T, of the soil covered by the vegetationsThe surface temperature of the bare soil is shown, and omega represents the vegetation single scattering albedo.
The invention expresses the microwave radiation of mixed pixel elements of vegetation cover soil and bare soil as four parts which are respectively the upstream radiation part G of the vegetation layer1(theta) the downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part G2(theta) the upward radiation part of the soil transmits the upward part G through the vegetation3(theta), the soil upgoing radiation part G4(theta). Wherein, the vegetation layer up-radiation part G1(theta) the downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part G2(theta) the upward radiation part of the soil transmits the upward part G through the vegetation3(θ) is a function of the vegetation optical thickness τ. In addition, because the proportion of the vegetation coverage area is different under different observation angles, the vegetation coverage area and the bare soil area in the mixed pixel are respectively multiplied by the proportion of the vegetation coverage area and the proportion of the bare soil coverage area, wherein the sum of the proportion of the vegetation coverage area and the proportion of the bare soil coverage area in the mixed pixelIs 1. According to the method, parameters such as the optical thickness of the vegetation, the vegetation coverage area proportion at different observation angles and the like are respectively substituted into microwave radiation transmission models at different observation angles, so that a mixed pixel multi-angle microwave radiation model consisting of the microwave radiation transmission models at different observation angles is established.
Further, in step S1), the method further includes simplifying the mixed pixel multi-angle microwave radiation model into a mixed pixel multi-angle microwave radiation model after preserving the variable related to the observation angle θ, where the mixed pixel multi-angle microwave radiation model after preserving the variable related to the observation angle θ is:
Further, in the step S2), calculating parameters in the mixed pixel multi-angle microwave radiation model by using the vegetation index, wherein the parameters comprise the vegetation optical thickness and the vegetation coverage area ratio; wherein the vegetation is optically thick
b represents an empirical parameter of the relation between the optical thickness of the vegetation and NDVI, SF represents an empirical parameter of the contribution of the wood structure of the vegetation to the optical thickness, NDVI (theta) is a normalized difference vegetation index, alpha represents a first regression coefficient, and beta represents a second regression coefficient; proportion of vegetation coverage area
NDVImax (theta) represents the maximum value of all pixel normalized vegetation indexes in the research area range; NDVImin(θ) represents the minimum value of the normalized vegetation index for all pixels in the area of the study.
The Normalized Difference Vegetation Index (NDVI) is a remote sensing Index reflecting the covering condition of the earth surface Vegetation, regression analysis is carried out on a large amount of ground measured data, the optical thickness of the Vegetation and the proportion of the covering area of the Vegetation are respectively expressed as functions of the Normalized Difference Vegetation Index, and the value of the empirical parameter b of the optical thickness of the Vegetation and the value of the empirical parameter SF of the wood of the Vegetation are changed according to the change of the Vegetation type. The first regression coefficient alpha and the second regression coefficient beta in the formula for calculating the vegetation optical thickness tau are obtained by regression of ground measured data. The vegetation wood experience parameter SF represents the contribution of the wood part of the vegetation (relative to the leaf part of the vegetation) to the vegetation optical thickness, and the value of the vegetation wood experience parameter SF is larger when the wood content of different vegetation is different, for example, coniferous or broadleaf forests are more than the wood structure of crops.
Further, in step S3), a soil radiation simulation database and a bare soil surface emission theoretical model are established, and a relationship between soil microwave remote sensing radiation signals at different observation angles is obtained according to the soil radiation simulation database and the bare soil surface emission theoretical model, including the following steps:
s31) obtaining surface parameters and radiometer observation parameters to be input into the bare soil surface emission theoretical model; the surface parameters comprise surface temperature, soil water content and surface roughness; the observation parameters of the radiometer comprise polarization, observation angle and observation frequency;
s32) determining a reasonable value range of the surface parameters and a reasonable value range of the radiometer observation parameters, carrying out equal interval value taking on the surface parameters in the reasonable value range of the surface parameters, and carrying out equal interval value taking on the radiometer observation parameters in the reasonable value range of the radiometer observation parameters to generate a soil radiation simulation database, wherein the soil radiation simulation database comprises a surface parameter set and an observation parameter set;
s33), establishing a bare soil surface emission theoretical model, inputting a surface parameter set and the observation parameter set into the bare soil surface emission theoretical model, and simulating the bare soil emissivity under different surface parameters and radiometer observation parameters by using the bare soil surface emission theoretical model;
s34) obtaining the relation among the soil microwave remote sensing radiation signals under different observation angles
Wherein the content of the first and second substances,
expressed at an observation angle of thetajThe emissivity of the vegetation cover soil in the case of (1),
expressed at an observation angle of thetakThe emissivity of the vegetation cover soil in the case of (1),
expressed at an observation angle of thetajThe emissivity of the bare soil in the case of (1),
expressed at an observation angle of thetakThe bare soil emissivity of (1) with a representing the first fitting parameter and B representing the second fitting parameter.
The invention discloses a bare soil surface emission theoretical Model, which adopts an Advanced Integral Equation Model (AIEM), wherein the Advanced Integral Equation Model has wider application range and can be used for wider surface conditions compared with the traditional geometric optical Model and physical Model
Obtaining the relation between the emissivity of the bare soil under two different observation angles
Further, in step S4), the method for calculating the mixed pixel multi-angle microwave radiation model by using the parameters in the mixed pixel multi-angle microwave radiation model in step S2) and the relationship between the soil microwave remote sensing radiation signals at different observation angles in step S3) includes the following steps:
s41) utilizing the relation among soil microwave remote sensing radiation signals of different angles, and substituting the parameters in the mixed pixel multi-angle microwave radiation model in the step S2) into the mixed pixel multi-angle microwave radiation model after the variables related to the observation angle theta are reserved;
s42) constructing a cost function
Obtaining a value which minimizes said cost function gamma
And
the microwave emissivity of the vegetation cover soil in the mixed pixel,
the microwave emissivity of the bare soil in the mixed pixel element.
According to the method, parameters such as the relation among soil microwave remote sensing radiation signals at different angles, optical thickness and vegetation coverage area ratio are substituted into a mixed pixel multi-angle microwave radiation model for calculation; because the known equations in the multi-angle microwave radiation model of the mixed pixel are more than the unknown quantity to be solved, and correlation possibly exists between the known equations, a cost function is constructed, the observed values of multiple angles (namely the mixed pixel microwave radiation of the vegetation cover soil and the bare soil under different angles) are brought into the cost function, and the microwave emissivity of the vegetation cover soil and the bare soil in the mixed pixel is solved by using a least square method. Minimizing the cost function gamma in the solution when the cost function is minimal
And
namely the microwave emissivity of the vegetation cover soil in the mixed pixel and the emissivity of the bare soil.
The invention has the beneficial effects that: the invention utilizes the vegetation index to calculate the parameters such as the vegetation optical thickness, the vegetation coverage area ratio and the like in the mixed pixel multi-angle microwave radiation model, the relation among the soil emissivity of different angles is obtained through correlation analysis and regression analysis of the soil emissivity of different angles, a mixed pixel multi-angle microwave radiation model is constructed, the relation among the soil emissivity of different angles is utilized to solve the mixed pixel multi-angle microwave radiation model, the invention fully excavates the observation information of passive microwave remote sensing multi-angle, the microwave remote sensing radiation signals of the mixed pixels are separated, so that the microwave emissivity of vegetation cover soil and the emissivity of bare soil in the mixed pixels are obtained, the passive microwave remote sensing data processing depth and the applicability and the product precision of a surface parameter inversion product are improved, and key data information is provided for further passive microwave remote sensing data processing and accurate surface parameter inversion.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments are briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a method for separating microwave remote sensing radiation signals in a mixed pixel according to an embodiment of the present invention.
Fig. 2 is a correlation coefficient distribution diagram between soil emissivity at different observation angles according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. It is noted that the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
In a first embodiment, a method for separating soil radiation signals of passive microwave remote sensing mixed pixel components, as shown in fig. 1, includes the following steps:
s1), establishing a microwave radiation transmission model, and establishing a mixed pixel multi-angle microwave radiation model by using the microwave radiation transmission model;
s2) calculating parameters in the mixed pixel multi-angle microwave radiation model by using the vegetation index;
s3) establishing a soil radiation simulation database and a bare soil surface emission theoretical model, and acquiring the relation between soil microwave remote sensing radiation signals under different observation angles according to the soil radiation simulation database and the bare soil surface emission theoretical model;
s4) calculating the mixed pixel multi-angle microwave radiation model by using the parameters in the mixed pixel multi-angle microwave radiation model in the step S2) and the relation between soil microwave remote sensing radiation signals under different observation angles in the step S3), and obtaining the microwave emissivity of vegetation covered soil and the microwave emissivity of bare soil in the mixed pixel.
Step S1), a microwave radiation transmission model is established, and a mixed pixel multi-angle microwave radiation model is established by using the microwave radiation transmission model, which comprises the following steps:
s11) obtaining mixed pixel microwave radiation TB of vegetation cover soil and bare soilp(θ), θ represents the observation angle, and subscript P represents either horizontal polarization H or vertical polarization V;
s12) acquiring four parts of mixed pixel microwave radiation, wherein the four parts are respectively a vegetation layer uplink radiation part G1(theta) the downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part G2(theta) the upward radiation part of the soil transmits the upward part G through the vegetation3(theta), the soil upgoing radiation part G4(θ)；
S13) establishing a microwave radiation transmission model TB by using the mixed pixel microwave radiation and four parts of the mixed pixel microwave radiationP(θ)＝G1(θ)+G2(θ)+G3(θ)+G4(θ)；
S14) establishing a mixed pixel multi-angle microwave radiation model by using the microwave radiation transmission model, wherein the mixed pixel multi-angle microwave radiation model is expressed as follows:
TBp(θ1) Representing an observation angle of theta1Microwave radiation of the measured mixed pixel; TBP(θj) Representing an observation angle of thetaiMicrowave radiation of the measured mixed pixel; TBP(θN) Representing an observation angle of thetaNThe measured mixed pixels are subjected to microwave radiation.
Vegetation layer upward radiation part G1(θ)＝Fveg(θ)·(1-ω)·(1-exp(-τ·secθ))·Tv(ii) a The downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part
The soil upward radiation part transmits the upward part through the vegetation
Up radiation part of soil
Wherein, Fveg(theta) represents the proportion of the vegetation coverage area at the observation angle theta, 1-Fveg(theta) denotes the bare at observation angle thetaThe ratio of the covered area of the soil, E represents the emissivity of the soil, the superscript vs represents the soil covered by the vegetation, the superscript bs represents the bare soil, tau represents the optical thickness of the vegetation, and T represents the optical thickness of the vegetationvIndicating the surface temperature, T, of the soil covered by the vegetationsThe surface temperature of the bare soil is shown, and omega represents the vegetation single scattering albedo.
The invention expresses the microwave radiation of mixed pixel elements of vegetation cover soil and bare soil into four parts, wherein the four parts have a vegetation layer uplink radiation part G1(theta) the downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part G2(theta) the upward radiation part of the soil transmits the upward part G through the vegetation3(theta), the soil upgoing radiation part G4(theta). Wherein, the vegetation layer up-radiation part G1(theta) the downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part G2(theta) the upward radiation part of the soil transmits the upward part G through the vegetation3(θ) is a function of the vegetation optical thickness τ. In addition, because the vegetation coverage area proportion is different under different observation angles, the vegetation coverage area and the bare soil area in the mixed pixel are respectively multiplied by the vegetation coverage area proportion and the bare soil coverage area proportion, wherein the sum of the vegetation coverage area proportion and the bare soil coverage area proportion in the mixed pixel is 1. According to the method, parameters such as the optical thickness of the vegetation, the vegetation coverage area proportion at different observation angles and the like are respectively substituted into microwave radiation transmission models at different observation angles, so that a mixed pixel multi-angle microwave radiation model consisting of the microwave radiation transmission models at different observation angles is established.
Step S1), the method further comprises the step of simplifying the mixed pixel multi-angle microwave radiation model into a mixed pixel multi-angle microwave radiation model after the variables related to the observation angle theta are reserved, wherein the mixed pixel multi-angle microwave radiation model after the variables related to the observation angle theta are reserved is as follows:
In the step S2), calculating parameters in the mixed pixel multi-angle microwave radiation model by using the vegetation index, wherein the parameters comprise the vegetation optical thickness and the vegetation coverage area ratio; wherein the vegetation is optically thick
b represents an empirical parameter of the relation between the optical thickness of the vegetation and NDVI, SF represents an empirical parameter of the contribution of the wood structure of the vegetation to the optical thickness, NDVI (theta) is a normalized difference vegetation index, alpha represents a first regression coefficient, and beta represents a second regression coefficient; proportion of vegetation coverage area
NDVImax(theta) represents the maximum value of the normalized vegetation index of all pixels in the study area range; NDVImin(θ) represents the minimum value of the normalized vegetation index for all pixels in the area of the study.
The Normalized Difference Vegetation Index (NDVI) is a remote sensing Index reflecting the covering condition of the earth surface Vegetation, regression analysis is carried out on a large amount of ground measured data (such as the Normalized Difference Vegetation Index and the Vegetation optical thickness), the optical thickness of the Vegetation and the proportion of the Vegetation covering area are respectively expressed as functions of the Normalized Difference Vegetation Index, and the value of the Vegetation optical thickness empirical parameter b and the value of the Vegetation wood empirical parameter SF are changed according to the change of the Vegetation type. In this embodiment, the value range of the optical thickness empirical parameter b of the vegetation is 0.12 ± 0.03, and the value range of the wood empirical parameter SF of the vegetation is 1.5 to 20. The first regression coefficient alpha and the second regression coefficient in the formula for calculating the vegetation optical thickness tau are obtained by regression of ground measured data. In this embodiment, the value of the first regression coefficient is 1.9134, and the value of the second regression coefficient β is 0.3215. The vegetation wood experience parameter SF represents the contribution of the wood part of the vegetation (relative to the contribution of the plant leaf quality) to the vegetation optical thickness, and the wood content of different vegetation is different (for example, coniferous or broadleaf forests have more wood structure than crops, the value of the vegetation wood experience parameter SF is larger).
Step S3), a soil radiation simulation database and a bare soil surface emission theoretical model are established, and the relation between soil microwave remote sensing radiation signals under different observation angles is obtained according to the soil radiation simulation database and the bare soil surface emission theoretical model, and the method comprises the following steps:
s31) obtaining surface parameters and radiometer observation parameters to be input into the bare soil surface emission theoretical model; the surface parameters comprise surface temperature, soil water content and surface roughness; the radiometer observation parameters comprise polarization, observation angle and observation frequency;
s32) determining a reasonable value range of the surface parameters and a reasonable value range of the radiometer observation parameters, carrying out equal interval value taking on the surface parameters in the reasonable value range of the surface parameters, and carrying out equal interval value taking on the radiometer observation parameters in the reasonable value range of the radiometer observation parameters to generate a soil radiation simulation database, wherein the soil radiation simulation database comprises a surface parameter set and an observation parameter set;
s33), establishing a bare soil surface emission theoretical model, inputting a surface parameter set and an observation parameter set into the bare soil surface emission theoretical model, and simulating the bare soil emissivity under different surface parameters and radiometer observation parameters by using the bare soil surface emission theoretical model;
s34) obtaining the relation among the soil microwave remote sensing radiation signals under different observation angles
Wherein the content of the first and second substances,
expressed at an observation angle of thetajThe emissivity of the vegetation cover soil in the case of (1),
expressed at an observation angle of thetakThe emissivity of the vegetation cover soil in the case of (1),
expressed at an observation angle of thetajThe emissivity of the bare soil in the case of (1),
expressed at an observation angle of thetakThe bare soil emissivity of (1) with a representing the first fitting parameter and B representing the second fitting parameter.
The bare soil surface emission theoretical Model adopts an Advanced Integral Equation Model (AIEM), and compared with the traditional geometric optical Model and physical Model, the Advanced Integral Equation Model has wider application range and can be used for wider surface conditions. In this embodiment, the parameters in the surface parameter set and the observation parameter set are as follows, and the observation frequency is: l band (1.4 GHz); horizontal polarization H and vertical polarization V; the observation angle is 1-60 degrees, and the interval is 1 degree; soil water content: 0.02-0.44 cm3/cm3At an interval of 0.02cm3/cm3(ii) a The root-mean-square height of the soil surface is 0.25-3 cm, and the interval is 0.25 cm; the related length of the surface is 2.5-3 cm, and the interval is 2.5 cm.
According to the soil emissivity correlation analysis and regression analysis of different observation angles, the soil emissivity correlation analysis and regression analysis of the invention show that the soil emissivity of two different observation angles has high correlation (see fig. 2) and can be approximately expressed as a linear relation, the abscissa and the ordinate of the graph 2 respectively represent different observation angle values, and the correlation coefficient between the soil emissivity of different observation angles is represented by different color depths in the graph 2. Relation between emissivity of vegetation cover soil under two different observation angles
Relationship between bare soil emissivity under two different observation angles
In the step S4), the parameters in the mixed pixel multi-angle microwave radiation model in the step S2) and the relation between the soil microwave remote sensing radiation signals under different observation angles in the step S3) are used for calculating the mixed pixel multi-angle microwave radiation model, and the method comprises the following steps:
s41) utilizing the relation among soil microwave remote sensing radiation signals of different angles, and substituting the parameters in the mixed pixel multi-angle microwave radiation model in the step S2) into the mixed pixel multi-angle microwave radiation model after the variables related to the observation angle theta are reserved;
s42) constructing a cost function
Obtaining a value which minimizes said cost function gamma
And
the microwave emissivity of the vegetation cover soil in the mixed pixel,
the microwave emissivity of the bare soil in the mixed pixel element.
According to the method, parameters such as the relation among soil microwave remote sensing radiation signals at different angles, optical thickness and vegetation coverage area ratio are substituted into a mixed pixel multi-angle microwave radiation model for calculation; because the known equations in the multi-angle microwave radiation model of the mixed pixel are more than the unknown quantity to be solved, and correlation possibly exists between the known equations, a cost function is constructed, the observed values of multiple angles (namely the mixed pixel microwave radiation of the vegetation cover soil and the bare soil under different angles) are brought into the cost function, and the microwave emissivity of the vegetation cover soil and the bare soil in the mixed pixel is solved by using a least square method. Minimizing the cost function gamma in the solution when the cost function is minimal
And
namely the microwave emissivity of the vegetation cover soil in the mixed pixel and the emissivity of the bare soil.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
according to the method, a mixed pixel multi-angle microwave radiation model is constructed, observation information of passive microwave remote sensing multi-angles is fully mined, and mixed pixel microwave remote sensing radiation signals are separated, so that the microwave emissivity of vegetation cover soil and the emissivity of bare soil in the mixed pixel are obtained, the passive microwave remote sensing data processing depth and the applicability and product precision of surface parameter inversion products are improved, and key data information is provided for further passive microwave remote sensing data processing and accurate surface parameter inversion.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and such modifications and improvements should also be considered within the scope of the present invention.
Claims (7)
1. A method for separating passive microwave remote sensing mixed pixel component soil radiation signals is characterized by comprising the following steps:
s1) establishing a microwave radiation transmission model, and establishing a mixed pixel multi-angle microwave radiation model by using the microwave radiation transmission model;
s2) calculating parameters in the mixed pixel multi-angle microwave radiation model by using the vegetation index;
s3) establishing a soil radiation simulation database and a bare soil surface emission theoretical model, and acquiring the relation between soil microwave remote sensing radiation signals under different observation angles according to the soil radiation simulation database and the bare soil surface emission theoretical model;
s4) calculating the mixed pixel multi-angle microwave radiation model by using the parameters in the mixed pixel multi-angle microwave radiation model in the step S2) and the relation between soil microwave remote sensing radiation signals under different observation angles in the step S3), and obtaining the microwave emissivity of vegetation covered soil and the microwave emissivity of bare soil in the mixed pixel.
2. The method for separating the soil radiation signal of the passive microwave remote sensing mixed pixel component according to claim 1, wherein in the step S1), a microwave radiation transmission model is established, and a mixed pixel multi-angle microwave radiation model is established by using the microwave radiation transmission model, and the method comprises the following steps:
s11) obtaining mixed pixel microwave radiation TB of vegetation cover soil and bare soilP(θ), θ represents the observation angle, and subscript P represents the horizontal polarization H or the vertical polarization V;
s12) obtaining four parts of mixed pixel microwave radiation, wherein the four parts are respectively a vegetation layer uplink radiation part G1(theta) the downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part G2(theta) the upward radiation part of the soil transmits the upward part G through the vegetation3(theta), the soil upgoing radiation part G4(θ)；
S13) establishing a microwave radiation transmission model TB by using the mixed pixel microwave radiation and four parts of the mixed pixel microwave radiationP(θ)＝G1(θ)+G2(θ)+G3(θ)+G4(θ)；
S14) establishing a mixed pixel multi-angle microwave radiation model by using a microwave radiation transmission model, wherein the mixed pixel multi-angle microwave radiation model is expressed as follows:
TBp(θ1) Representing an observation angle of theta1Microwave radiation of the measured mixed pixel; TBP(θi) Representing an observation angle of thetaiMicrowave radiation of the measured mixed pixel; TBP(θN) Representing observation angleIs thetaNThe measured mixed pixels are subjected to microwave radiation.
3. The method for separating the soil radiation signal of the passive microwave remote sensing mixed pixel component as claimed in claim 2, wherein the vegetation layer uplink radiation part G1(θ)＝Fveg(θ)·(1-ω)·(1-exp(-τ·secθ))·Tv(ii) a The downward radiation of the vegetation layer is reflected by the soil and then transmitted by the vegetation to the upward part
The soil upward radiation part transmits the upward part through the vegetation
Up radiation part of soil
Wherein, Fveg(theta) represents the proportion of the vegetation coverage area at the observation angle theta, 1-Fveg(theta) represents the proportion of the coverage area of the bare soil under the observation angle theta, E represents the soil emissivity, superscript vs represents the soil covered by the vegetation, superscript bs represents the bare soil, tau represents the optical thickness of the vegetation, and T represents the optical thickness of the vegetationvIndicating the surface temperature, T, of the soil covered by the vegetationsThe surface temperature of the bare soil is shown, and omega represents the vegetation single scattering albedo.
4. The method for separating the soil radiation signal of the passive microwave remote sensing mixed pixel component according to claim 3, wherein in step S1), the method further comprises simplifying the mixed pixel multi-angle microwave radiation model into a mixed pixel multi-angle microwave radiation model after preserving a variable related to an observation angle theta, wherein the mixed pixel multi-angle microwave radiation model after preserving the variable related to the observation angle theta is as follows:
5. The method for separating the passive microwave remote sensing mixed pixel component soil radiation signal according to claim 1 or 4, characterized in that in step S2), parameters in the multi-angle microwave radiation model of the mixed pixel are calculated by using the vegetation index, the parameters comprise vegetation optical thickness and vegetation coverage area ratio, wherein the vegetation optical thickness
6. The method for separating the radiation signals of vegetation cover soil and bare soil in a mixed pixel according to claim 5, wherein in step S3), a soil radiation simulation database and a bare soil surface emission theoretical model are established, and the relationship between the soil microwave remote sensing radiation signals under different observation angles is obtained according to the soil radiation simulation database and the bare soil surface emission theoretical model, comprising the following steps:
s31) obtaining surface parameters and radiometer observation parameters to be input into the bare soil surface emission theoretical model; the surface parameters comprise surface temperature, soil water content and surface roughness; the radiometer observation parameters comprise polarization, observation angle and observation frequency;
s32) determining a reasonable value range of the surface parameters and a reasonable value range of the radiometer observation parameters, carrying out equal interval value taking on the surface parameters in the reasonable value range of the surface parameters, and carrying out equal interval value taking on the radiometer observation parameters in the reasonable value range of the radiometer observation parameters to generate a soil radiation simulation database, wherein the soil radiation simulation database comprises a surface parameter set and an observation parameter set;
s33), establishing a bare soil surface emission theoretical model, inputting the surface parameter set and the observation parameter set into the bare soil surface emission theoretical model, and simulating the bare soil emissivity under different surface parameters and radiometer observation parameters by using the bare soil surface emission theoretical model;
s34) obtaining the relation among the soil microwave remote sensing radiation signals under different observation angles
Wherein the content of the first and second substances,
expressed at an observation angle of thetajThe emissivity of the vegetation cover soil in the case of (1),
expressed at an observation angle of thetakThe emissivity of the vegetation cover soil in the case of (1),
expressed at an observation angle of thetajThe emissivity of the bare soil in the case of (1),
expressed at an observation angle of thetakBare soil emission under the circumstances ofThe ratio, a, represents the first fitting parameter, and B represents the second fitting parameter.
7. The method for separating the radiation signals of vegetation cover soil and bare soil in a mixed pixel according to claim 6, wherein in step S4), the multi-angle microwave radiation model of the mixed pixel is solved by using the parameters in the multi-angle microwave radiation model of the mixed pixel in step S2) and the relationship between the soil microwave remote sensing radiation signals under different observation angles in step S3), and the method comprises the following steps:
s41) utilizing the relation among soil microwave remote sensing radiation signals of different angles, and substituting the parameters in the mixed pixel multi-angle microwave radiation model in the step S2) into the mixed pixel multi-angle microwave radiation model after the variables related to the observation angle theta are reserved;
S42)
obtaining a value which minimizes said cost function gamma
And
the microwave emissivity of the vegetation cover soil in the mixed pixel,
the microwave emissivity of bare soil.
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