CN115061112A

CN115061112A - Planar snow water equivalent obtaining method and device and electronic equipment

Info

Publication number: CN115061112A
Application number: CN202210946563.4A
Authority: CN
Inventors: 房世峰; 杨亦尘; 王小虎
Original assignee: Institute of Geographic Sciences and Natural Resources of CAS
Current assignee: Institute of Geographic Sciences and Natural Resources of CAS
Priority date: 2022-08-09
Filing date: 2022-08-09
Publication date: 2022-09-16

Abstract

The invention provides a planar snow water equivalent obtaining method and device and electronic equipment. The method comprises the steps of obtaining an SAR image of a research area; acquiring a ratio of a backscattering coefficient in autumn to a backscattering coefficient in winter based on the SAR image; acquiring the accumulated snow thermal resistance of a specified observation point in a research area; establishing a fitting equation based on the ratio and the thermal resistance of the accumulated snow, and obtaining a planar thermal resistance of the accumulated snow based on the fitting equation; performing characteristic decomposition on the SAR image by adopting an S3H polarization decomposition method to obtain the planar snow density of the research area; and acquiring the planar snow water equivalent based on the planar snow heat resistance and the planar snow density. The method adopts an S3H polarization decomposition method to obtain the planar snow density with higher precision, thereby realizing the high-resolution snow water equivalent extraction with rapidness, high efficiency and long sequence.

Description

Planar snow water equivalent obtaining method and device and electronic equipment

Technical Field

The invention relates to the technical field of polarimetric SAR inversion, in particular to a method and a device for acquiring surface snow water equivalent and electronic equipment.

Background

The accumulated snow is used as the most widely distributed freezing circle and the most obvious corresponding component to the seasonal variation and can be used as the climatic variationIs also an important component of the earth energy balance system. The research on physical parameters of the accumulated snow not only is a key indication for knowing climate change, but also can improve the water resource assessment and utilization efficiency of regions and provide more accurate suggestions for flood control and disaster prevention. Wherein the surface Snow Water Equivalent (SWE) is the product of snow depth and density, and is used for representing the water amount stored in the snow cover in mm or mm

Is a unit. The successful estimation of the surface-shaped snow water equivalent can improve the accuracy of snow melting runoff prediction and water supply management, and has important significance for improving the water resource utilization efficiency and flood control prediction in Xinjiang.

At present, many surface snow water equivalent researches are positioned on a large scale, and the observation and inversion mainly adopt means such as field on-site measurement, long-term observation of a ground station, observation of a satellite remote sensing area and the like. The method is sufficient for hydrological study in a drainage basin, and the estimation of the surface snow water equivalent is a main problem to be solved in the study. At present, three methods are mainly used for estimating the river basin scale surface snow water equivalent. First, the area snow water equivalent is estimated based on the measured data. The method mainly comprises the steps of obtaining the surface snow water equivalent of different observation points (usually weather stations) through ground observation, and estimating the spatial distribution information by using a spatial interpolation method. The first hand data of the face-shaped snow water equivalent can be obtained by ground observation, the accuracy is high, and the method is one of indispensable means for the research of the face-shaped snow water equivalent, but the information of the face-shaped snow water equivalent on a limited number of points can be obtained, and the space-time change of the face-shaped snow water equivalent in a face-shaped area is difficult to accurately reflect. Although spatial interpolation can estimate the distribution information of the surface snow equivalent, it is still difficult to satisfy the requirement of high-precision surface snow equivalent research due to the limitation of the number and distribution of observation points and the factors such as terrain conditions. The second method is to use an optical remote sensing product and an SWE reconstruction technology to realize the SWE inversion of the high resolution of the drainage basin scale, and the optical remote sensing data mainly adopted is MODIS. However, the spatial resolution of the MODIS is 500 meters, and the problem of image estimation accuracy of sub-pixels and the like cannot be solved. Although some learners use the degree-day model in combination with the snow information extracted by the sentinel-2 to reconstruct the sweden area SWE after the high-resolution optical satellite such as the sentinel-2 is put into use, the main advantage of the optical remote sensing is still snow surface parameter inversion, which has no physical basis for estimating snow layer information such as the planar snow water equivalent and is easily influenced by the weather, and the estimation accuracy is limited to a certain extent. The third method is a planar snow water equivalent inversion using passive microwaves. The resolution ratio of the passive microwave sensor mainly used at present is mainly 10-25km, and the fine surface snow water equivalent inversion of the drainage basin scale cannot be met.

Compared with a passive microwave sensor with lower resolution, the Synthetic Aperture Radar (SAR) reserves the advantages of microwave remote sensing of all-day time and difficulty in being limited by external conditions such as weather, and is one of the most promising methods for searching physical characteristics of accumulated snow by using the unique sensitivity to dielectric and geometric characteristics of an object and the potential of providing scattering medium characteristics. The method for realizing inversion of the river basin surface snow water equivalent by using the SAR mainly comprises three methods. The first is an inversion algorithm based on a theoretical model, which is developed based on a backscattering theoretical model of snow and an underlying surface, and is represented by a multi-frequency and dual-polarization data inversion algorithm developed by Shi and Dozier. The principle of the method is based on an accumulated snow backscattering theoretical model, the attenuation coefficient and the dielectric constant of accumulated snow are obtained by separating the contribution of snow depth and snow density to backscattering coefficients, and then the snow depth and the snow density are inverted to obtain the planar snow water equivalent. The inversion algorithm has strict derivation process and definite physical basis. However, such algorithms are too complex, a complete snow parameter model simulation database needs to be established, the calculation efficiency is low, the requirement on data is high, multi-frequency and multi-polarization data needs to be input for solving, the cost is high, and the popularization and application of the algorithms are not facilitated. The second method is to use InSAR technology to realize surface snow water equivalent inversion. The principle of the method is that when radar electromagnetic waves penetrate through a snow layer, refraction occurs at the interface of air and snow to cause the change of a propagation path. The InSAR uses SAR data of repeated crossing to obtain the phase difference of the images before and after snow cover; a determined geometric relationship exists between the phase difference and the planar snow equivalent, and the direct inversion of the planar snow equivalent can be realized according to the relationship. The method has a definite geometric relation, but the InSAR technology has strict requirements on the orbit base line using data, and the loss of coherence phenomenon is often caused by the change of the snow characteristics, so that the generation of the interference phase is not easy, and the application of the method is limited. The third method is a planar snow water equivalent inversion algorithm based on the thermal resistance principle, and is subsequently developed to be called an EQeau model. The method is an inversion algorithm for the shallow snow region of the ebb river basin, quebec, canada, first proposed in 1998 by Bernier m. The method is based on the principle that a function semi-empirical expression between the snow thermal resistance and the ratio of the radar backscattering coefficients in autumn and winter is established, and surface snow water equivalent inversion of the watershed scale is achieved. The method is then applied to surface snow water equivalent inversion of flow area scales of Ribayone, China Xinjiang Marnus river basin and China northeast, and a better inversion effect is obtained. The method has a relatively simple calculation formula, has relatively good universality and accuracy, does not need C-band radar data with strict requirements on a track base line, and can realize high-resolution surface snow water equivalent inversion of the watershed scale only by combining with ground observation points. However, uncertainty problems of the method such as the influence of snow density on model accuracy, the low correlation between the ratio of the built snow thermal resistance and the backscattering coefficient and the like also affect the popularization and application of the model. The method aims to realize rapid, efficient and long-time sequence high-resolution planar snow water equivalent extraction by improving the EQeau model.

Disclosure of Invention

Objects of the invention

The invention aims to provide a planar snow water equivalent obtaining method, a planar snow water equivalent obtaining device and electronic equipment, and aims to solve the problem that the existing snow water equivalent obtaining method is low in precision.

(II) technical scheme

In order to solve the above problem, a first aspect of an embodiment of the present invention provides a planar snow water equivalent obtaining method, including:

acquiring an SAR image of a research area;

obtaining a ratio of an autumn backscattering coefficient and a winter backscattering coefficient based on the SAR image;

acquiring the accumulated snow thermal resistance of a specified observation point in the research area;

establishing a fitting equation based on the ratio and the thermal resistance of the accumulated snow, and obtaining a planar thermal resistance of the accumulated snow based on the fitting equation;

performing characteristic decomposition on the SAR image by adopting an S3H polarization decomposition method to obtain the planar snow density of the research area;

and acquiring a planar snow water equivalent based on the planar snow thermal resistance and the planar snow density.

In some embodiments, obtaining the asiatic heat resistance of a given observation point in the area of interest comprises:

classifying the research area based on environmental factors to obtain multiple types of subareas;

establishing the specified observation point on the sub-region of the specified category;

and establishing a fitting equation based on the ratio and the snow thermal resistance, and obtaining the planar snow thermal resistance based on the fitting equation.

In some embodiments, the environmental factors include: soil conditions and terrain conditions.

In some embodiments, performing feature decomposition on the SAR image using the S3H polarization decomposition method to obtain an areal snow density of the region of interest comprises:

acquiring a first expression of a volume scattering coefficient by adopting an S3H polarization decomposition method;

obtaining a second expression of the volume scattering coefficient based on the Fresnel transmission coefficient;

combining the first expression and the second expression to obtain an expression of the dielectric constant of the accumulated snow;

and obtaining the planar accumulated snow density based on the expression of the accumulated snow dielectric constant.

In some embodiments, obtaining the first expression for the volume scattering coefficient using the S3H polarization decomposition method includes:

rotating the polarized coherent matrix of the SAR image by a set angle around the radar sight;

and obtaining the first expression based on the rotated polarized coherent matrix.

In some embodiments, the rotated polarized coherence matrix is as follows:

the first expression is as follows:

wherein the content of the first and second substances,

、

and

surface scattering, double-elastic scattering and volume scattering power coefficients respectively;

is the scattering phase of the scattering;

is the volume scattering coefficient.

In some embodiments, deriving the second expression for the volumetric scattering coefficient based on the fresnel transmission coefficient comprises:

acquiring a Fresnel transmission coefficient of HH polarization of the SAR image;

acquiring a Fresnel transmission coefficient of the SAR image VV polarization;

the second expression is obtained based on a fresnel transmission coefficient of the HH polarization and a fresnel transmission coefficient of the VV polarization.

In some embodiments, the fresnel transmission coefficient of HH polarization of the SAR image is as follows:

the Fresnel transmission coefficient of the SAR image VV polarization is as follows:

the second expression is as follows:

wherein the content of the first and second substances,

and

the fresnel transmission coefficients of HH and VV polarization of the SAR image,

the dielectric constant of the accumulated snow is,

and

and volume scattering matrixes representing HH and VV polarization of the SAR images.

In some embodiments, the dielectric constant of the accumulated snow is expressed as follows:

wherein the content of the first and second substances,

to represent

The elements of the first row and the first column of the matrix,

to represent

The third row and column of the matrix.

A second aspect of an embodiment of the present invention provides a planar snow water equivalent obtaining apparatus, including:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring an SAR image of a research area;

the first data processing module is used for acquiring the ratio of the backscattering coefficient in autumn to the backscattering coefficient in winter based on the SAR image;

the second acquisition module is used for acquiring the snow thermal resistance of a specified observation point in the research area;

the fitting module is used for establishing a fitting equation based on the ratio and the thermal resistance of the accumulated snow, and obtaining a planar thermal resistance of the accumulated snow based on the fitting equation;

the second data processing module is used for performing characteristic decomposition on the SAR image by adopting an S3H polarization decomposition method to obtain the planar snow density of the research area;

and the third acquisition module is used for acquiring the planar snow water equivalent based on the planar snow thermal resistance and the planar snow density.

A third aspect of the embodiments of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in a storage medium of the memory and executable on the processor, wherein the processor implements the method according to any one of the above when executing the computer program.

(III) advantageous effects

The technical scheme of the invention has the following beneficial technical effects: by adopting the S3H polarization decomposition method, the planar snow density with higher precision can be obtained, and the high-resolution snow water equivalent extraction with high speed, high efficiency and long sequence can be further realized.

Drawings

Fig. 1 is a schematic flow chart of a planar snow water equivalent obtaining method according to a first embodiment of the present invention;

fig. 2 is a schematic flow chart of a method for obtaining surface equivalent of snow water according to a second embodiment of the present invention;

FIG. 3 is an exploded general block diagram of S3H according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a planar snow water equivalent obtaining apparatus 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 will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.

The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements, but may alternatively include: steps or elements not listed, or optionally further comprising: other steps or elements inherent to such processes, methods, articles or devices.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other. The invention will be described in more detail below with reference to the accompanying drawings.

Fig. 1 is a schematic flow chart of a method for acquiring a surface snow water equivalent according to a first embodiment of the present invention.

In a first embodiment of the present invention, as shown in fig. 1, a planar snow water equivalent obtaining method is provided, which includes the following steps:

s101: acquiring a Synthetic Aperture Radar (SAR) image of a research area;

s102: and acquiring the ratio of the backscattering coefficient in autumn to the backscattering coefficient in winter based on the SAR image. In this embodiment, the difference between dB values of the two images extracted after the acquired SAR images in autumn and winter are subjected to preprocessing such as multiview processing and filtering is calculated to obtain the ratio of the backscattering coefficient in autumn to the backscattering coefficient in winter.

S103: the thermal resistance of the snow at a specified observation point in the study area is obtained. In the embodiment, a plurality of observation points are designated and used for detecting key snow or meteorological elements such as snow depth, snow density, temperature, wind speed and the like; meanwhile, an Internet of things platform for snow melt runoff simulation and forecasting is constructed (based on JAVA prototype development and coupled or called with GIS and other tools); then networking through GPRS and transmitting data in real time, integrating the data into a developed Internet of things platform and managing the data in library; and then, calling a data-model-calculation-platform integrated Internet of things platform to carry out data processing and space-time analysis. In this embodiment, the snow thermal resistance is calculated by specifying the snow depth and the snow density of the observation point.

S104: and establishing a fitting equation based on the ratio and the snow thermal resistance, and obtaining the planar snow thermal resistance based on the fitting equation.

S105: and (3) performing characteristic decomposition on the SAR image by adopting an S3H polarization decomposition method to obtain the planar snow density of the research area.

Specifically, in the present embodiment, a single-cloud Three-Component Hybrid polarization decomposition method (S3H polarization decomposition) is used to replace the snow density obtained by the spatial interpolation method in the related art, and the SAR image decomposition characteristics are directly used to establish the relation with the snow dielectric constant, so that the empirical formula is used to extract the snow density. By optimizing the EQeau model structure in the related art, the influence of errors caused by problems such as observation means on the overall precision of the model can be reduced. Meanwhile, the snow density distribution on the whole surface cannot be completely reflected by using the spatial interpolation method, and the snow water equivalent acquisition method provided by the embodiment can be used for generating more accurate high-resolution planar snow density. S3H is an improvement over the three-component hybrid decomposition scheme of Cloude, using a rotated 3 × 3 coherence matrix [ T [ ]]Rotation around the line of sight to resolve the orientation angle

And an extended volume scattering model is implemented.

S106: and acquiring the planar snow water equivalent based on the planar snow heat resistance and the planar snow density.

By adopting the method for acquiring the planar snow water equivalent, provided by the embodiment, the planar snow water equivalent can be acquired with higher precision by adopting the S3H polarization decomposition method, and then the high-resolution snow water equivalent extraction with high speed, high efficiency and long sequence can be realized.

Fig. 2 is a schematic flow chart of a method for obtaining a surface equivalent of snow water according to a second embodiment of the present invention. As shown in fig. 2, a planar snow water equivalent obtaining method according to a second embodiment of the present invention includes:

s201: and classifying the research area based on the environmental factors to obtain multiple types of subregions. Specifically, the ratio of the backscattering coefficient in autumn to the backscattering coefficient in winter is influenced by environmental factors, and the environmental factors are related to the land utilization type and the terrain condition, so that auxiliary conditions are added, classification is performed based on the soil condition and the terrain condition, the soil condition and the terrain condition are restrained, the fitting influence of the ratio of the environmental factors to the backscattering coefficients and the snow thermal resistance is reduced, and the fitting precision is improved. The high-resolution land cover data can be obtained by remote sensing interpretation of a sentinel-2 satellite, and the terrain data is extracted by a high-resolution DEM.

Establishing the specified observation point on the sub-region of the specified category. Specifically, on the basis of classifying a research area to obtain multiple types of sub-areas, representative point locations in the research area are selected to build an internet of things of the snow parameter observation point. The purchased probe or other device is arranged in a representative region of the study region to form an observation point.

S202: the snow density and the snow depth of the appointed observation point are obtained in real time through the Internet of things. And obtaining the snow thermal resistance of the appointed observation point based on the snow density and the snow depth.

S203: acquiring a ratio of a backscattering coefficient in autumn to a backscattering coefficient in winter based on the SAR image;

s204: and establishing a fitting equation based on the ratio and the snow thermal resistance, and obtaining the planar snow thermal resistance based on the fitting equation. The designated category is determined according to the terrain condition and the land utilization condition of the map where the remote sensing image is located. The terrain conditions are obtained from a Digital Elevation Model (DEM) of the map frame, and the land use conditions are obtained from land use data of the map frame. For example, according to the digital elevation model and the land utilization data, the map is divided into different sub-areas such as grassland, cultivated land, bare land, residential land and the like. And in different sub-regions, performing equation fitting on the obtained backscattering coefficient ratio and the snow thermal resistance. The backscattering coefficient ratio can be used as a dependent variable, the accumulated snow thermal resistance is used as an independent variable, a fitting equation is established, and the fitting relation is logarithmic fitting. In this embodiment, the specified fitting equation is established based on the environmental factors of the sub-regions of the specified category. And performing physical relation fitting on the ratio of the backscattering coefficients and the snow thermal resistance of the specified observation point based on a specified fitting equation to obtain the planar snow thermal resistance.

S205: and (3) performing characteristic decomposition on the SAR image by adopting an S3H polarization decomposition method to obtain the planar snow density of the research area.

S206: and (3) performing characteristic decomposition on the SAR image by adopting an S3H polarization decomposition method to obtain the planar snow density of the research area.

In the embodiment, the classification of the research area is realized by using the high-resolution land cover data and the topographic data of the research area, and the accuracy of the fitting of the representativeness and the physical relation of the positions of the subsequent observation points is improved.

Fig. 3 is an exploded general framework diagram of S3H according to an embodiment of the present invention. As shown in fig. 3, the principle of S3H polarization decomposition to extract the area-shaped snow density of the study area is to establish a relationship between the volume scattering coefficient after decomposition and the volume scattering coefficient obtained by the fresnel transmission equation, and then obtain the dielectric constant of the snow. And calculating the density of the accumulated snow according to the relation between the dielectric constant of the accumulated snow and the density of the accumulated snow. For polarized SAR images, the image is processed by a polarized coherent matrix

Rotate it by a certain angle around the radar sight

Obtaining a rotated matrix

. The principle formula of the S3H decomposition is shown in (5).

（1）

Wherein the content of the first and second substances,

、

and

surface scattering, double-elastic scattering and volume scattering power coefficients, respectively.

Is the scattering phase of the scattering; the method applies to the orthogonalization of the surface and dihedral componentsPrinciple of sexuality. The orthogonality condition is expressed as

，

。

And

the rotation angles of the surface scattering and the doublet scattering are indicated, respectively.

And

the scattering phases of surface scattering and double-elastic scattering, respectively. Combining both into equation (5) by orthogonality conditions

. And since a large number of randomly distributed snow particles can be used as Rayleigh scatterers, the average volume scattering coherence matrix can be expressed at all possible angles

To obtain the integral of the volume scattering coherence matrix of randomly distributed small spherical particles within one resolution cell:

（2）

（3）

wherein the content of the first and second substances,

representing a polarized coherence matrix

The volume scattering coherence matrix in (1).

Is the rayleigh scattering phase function.

Is the volume scattering coefficient. The Fresnel transmission equation and Snell's law can be used to obtain the target. According to the Fresnel transmission equation and Snell's law, the Fresnel transmission coefficient is expressed as follows:

（4）

and

and

and volume scattering matrixes representing HH and VV polarization of the SAR images. According to the fresnel transmission equation and snell's law, the fresnel transmission coefficient is expressed as follows:

（5）

（6）

wherein the content of the first and second substances,

for SAR imagesA partial angle of incidence;

is the dielectric constant of the accumulated snow. The local incidence angle is obtained by preprocessing the SAR image. Preprocessing refers to processing images in advance before remote sensing image analysis is performed. Due to the limitation of the conditions such as space and time for receiving the remote sensing image, the information of the complex earth surface is difficult to be accurately recorded, so that errors are generated in the data acquisition process. These errors degrade the quality of the remote sensing data and thus affect the accuracy of the image analysis. Therefore, the remote sensing original image needs to be preprocessed before the image analysis and processing. The SAR image preprocessing mainly comprises multi-view processing, filtering and geocoding, and different remote sensing software can be selected for processing according to different specific SAR images.

After preprocessing, the terrain condition in the SAR image range, SAR satellite orbit dip angle and SAR incident angle are combined to be related. The specific relationship of the point position local incidence angles is obtained as follows:

（7）

wherein the content of the first and second substances,

is the local angle of incidence of the spot;

indicating taking when the radar is looking right

In the left view, it is taken as-;

the radar incidence angle of the point based on the ground level surface can be obtained by interpolation of the radar incidence angle of a near point and the radar incidence angle of a far point according to the size of an oblique distance pixel;

the slope angle representing the point can be calculated by a Digital Elevation Model (DEM);

the inclination extracted by DEM is the azimuth angle of the inclination relative to the flight direction of the satellite and represents the included angle (increasing clockwise) between the projection of the normal of the tangent plane of the point on the horizontal plane and the direction opposite to the azimuth direction

Inclination angle with satellite orbit

And calculating to obtain the following formula:

（8）

the local incidence angles of the SAR images are derived from equations (7) and (8), and then the fresnel transmission coefficients in equations (5) and (6) can be calculated.

In solving for (1), due to double-bullet scattering of accumulated snow

And the flow rate of the gas tends to zero,

can be expressed as

（9）

Wherein the content of the first and second substances,

represent

The elements of the first row and the first column of the matrix,

to represent

The third row and column of the matrix, and so on.

Therefore, the following relationships can be established by connecting equations (4), (5), (6) and (9):

（10）

equation (10) establishes the dielectric constant of the accumulated snow

And the association of the decomposition matrix. The only variable, namely the dielectric constant of the accumulated snow can be calculated by the formula (10)

Distribution of (2). Meanwhile, the relation between the snow dielectric constant and the snow density can be established according to a formula (12), so that the process of extracting the snow density from the SAR image is realized.

（11）

Fitting of the ratio of backscattering coefficients in autumn and winter and thermal resistance of accumulated snow: the snow thermal resistance is calculated by the snow depth and the snow density of an observation point. And meanwhile, classifying the observation points and the ratio values of the autumn and winter backscattering coefficients of the corresponding positions of the observation points according to the result of the land classification. And (4) utilizing a fitting method in different classes, and observing errors of different fitting equations to obtain the equation with the highest precision as the final fitting equation. And calculating the planar thermal resistance of accumulated snow through a fitting equation and the ratio of planar autumn and winter backscattering coefficients.

And (3) extracting the planar high-resolution snow water equivalent by using the optimized EQeau model according to a formula (12) through the planar snow density and the snow thermal resistance.

（12）

SWE is equivalent of snow water, A, B and C are empirical constants, and the values are respectively

，

，

。

The density of the accumulated snow is shown as,

fitting equations with the backscattering coefficient ratio as the argument.

Fig. 4 is a schematic structural diagram of a planar snow water equivalent obtaining apparatus according to an embodiment of the present invention. As shown in fig. 4, based on the same inventive concept, an embodiment of the present invention provides a planar snow water equivalent obtaining apparatus, including:

a first obtaining module 41, configured to obtain an SAR image of a research area;

a first data processing module 42, configured to obtain a ratio of a backscattering coefficient in autumn to a backscattering coefficient in winter based on the SAR image;

a second obtaining module 43, configured to obtain a thermal resistance of snow at a specified observation point in the research area;

the fitting module 44 is used for establishing a fitting equation based on the ratio and the thermal resistance of the snow cover, and obtaining a planar thermal resistance of the snow cover based on the fitting equation;

the second data processing module 45 is configured to perform feature decomposition on the SAR image by using an S3H polarization decomposition method to obtain a planar snow density of the research area;

and a third obtaining module 46, configured to obtain a planar snow water equivalent based on the planar snow thermal resistance and the planar snow density.

Based on the same inventive concept, embodiments of the present invention provide an electronic device, which includes a memory, a processor, and a computer program stored in a storage medium of the memory and executable on the processor, and when the processor executes the computer program, the method of any of the above embodiments is implemented.

The invention has been described above with reference to embodiments thereof. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. The scope of the invention is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the invention, and these alternatives and modifications are intended to be within the scope of the invention.

Claims

1. A planar snow water equivalent obtaining method is characterized by comprising the following steps:

acquiring an SAR image of a research area;

2. The planar snow water equivalent obtaining method according to claim 1, wherein before obtaining the snow heat resistance of a specified observation point in the study area, the obtaining comprises:

establishing the specified observation point on the sub-region of the specified category.

3. The planar snow water equivalent obtaining method according to claim 2, wherein the environmental factors include: soil conditions and terrain conditions.

4. The planar snow water equivalent acquisition method as claimed in claim 1, wherein the performing feature decomposition on the SAR image by using S3H polarization decomposition method to obtain the planar snow density of the research area comprises:

obtaining an expression of the dielectric constant of the accumulated snow by combining the first expression and the second expression;

5. The area snow water equivalent obtaining method as claimed in claim 4, wherein obtaining the first expression of the volume scattering coefficient by the S3H polarization decomposition method comprises:

6. An area snow water equivalent obtaining method according to claim 5,

the rotated polarization coherence matrix is as follows:

the first expression is as follows:

wherein the content of the first and second substances,

、

and

is the scattering phase of the scattering;

is the volume scattering coefficient.

7. The area snow water equivalent obtaining method as set forth in claim 4, wherein obtaining the second expression of the volume scattering coefficient based on the transmission coefficient of fresnel includes:

acquiring a Fresnel transmission coefficient of the SAR image VV polarization;

obtaining the second expression based on the Fresnel transmission coefficient of the HH polarization and the Fresnel transmission coefficient of the VV polarization;

the Fresnel transmission coefficient of HH polarization of the SAR image is as follows:

the second expression is as follows:

wherein the content of the first and second substances,

and

the dielectric constant of the accumulated snow is,

and

8. The planar snow water equivalent obtaining method according to claim 4, wherein the expression of the snow dielectric constant is as follows:

wherein the content of the first and second substances,

to represent

The elements of the first row and the first column of the matrix,

to represent

The third row and column of the matrix.

9. A planar snow water equivalent obtaining apparatus, comprising:

10. An electronic device comprising a memory, a processor, and a computer program stored in a storage medium of the memory and executable on the processor, characterized in that the processor implements the method according to any one of claims 1 to 8 when executing the computer program.