A method for constructing a GPR prediction model for detecting peat reserves

Abstract

The present application discloses a method for constructing a GPR applicable parameter prediction model for detecting peat reserves, and relates to the technical field of peat resource detection. By acquiring characteristic information of a variety of typical peatlands in a target area; determining a target GPR that matches all typical peatlands in the target area based on the characteristic information; obtaining the actual dielectric constant and actual radar transmission parameters obtained by field detection of typical peatlands by the target GPR; determining the spatiotemporal variation characteristics of each typical peatland based on the actual dielectric constant and actual radar transmission parameters of each typical peatland; determining the GPR application potential information of peatlands in different regions based on the spatiotemporal variation characteristics of each typical peatland and the mineral deposit genesis type of peatlands in different regions; constructing a GPR applicable parameter prediction model based on the GPR application potential information of peatlands in different regions. The technical solution of the present application reduces the blindness of GPR selection and improves the effectiveness of peat resource detection.

Description

Technical Field

[0001] The present application relates to the technical field of peat resource detection, and in particular to a method for constructing a GPR applicable parameter prediction model for detecting peat reserves. Background Art

[0002] GPR (Ground Penetrating Radar) technology is a detection technology that uses GPR to detect peat resources. It can enter the ground by emitting high-frequency electromagnetic waves. When the electromagnetic waves encounter a medium interface with different electrical properties, they will be reflected. The receiver captures these reflected signals. GPR can infer the distribution of underground materials by analyzing the time, intensity and shape of the signal. GPR equipment has the advantages of fast speed, less time consumption, and can accurately obtain the thickness, volume and geometric size information of peat over a large area in the survey of peat resources.

[0003] At present, when users use GPR to detect peat resources, they are not familiar with the soil characteristics of peatlands and tend to blindly select a GPR to detect the peatland. However, by blindly selecting GPR for detection, problems such as not being able to see or clearly see the interface between peat and surrounding soil in the radar image, or the interface seen is inconsistent with the actual thickness of the peat may occur, resulting in the inability to effectively survey peat resources. Summary of the invention

[0004] Based on the above problems, the present application provides a method for constructing a suitable parameter prediction model of GPR for detecting peat reserves, with the aim of reducing the blindness of GPR selection and improving the effectiveness of peat resource detection.

[0005] The embodiments of the present application disclose the following technical solutions:

[0006] In a first aspect of the present application, a method for constructing a GPR applicable parameter prediction model for detecting peat reserves is provided, the method comprising:

[0007] Obtain characteristic information corresponding to various typical peatlands in the target area; the characteristic information includes soil physical and chemical parameters, peat types and peat layers of typical peatlands;

[0008] According to the characteristic information of each typical peatland, the target GPR matching all the typical peatlands in the target area and the applicable radar parameters corresponding to each typical peatland are determined;

[0009] The actual dielectric constant and actual radar transmission parameters of each typical peatland are obtained; the actual dielectric constant and actual radar transmission parameters of each typical peatland are parameters of the target GPR, which are adjusted to the applicable radar parameters corresponding to the typical peatland, and the parameters are obtained by field detection of the typical peatland; the actual radar transmission parameters at least include: the penetration depth and reflection intensity of the electromagnetic wave emitted by the target GPR in the typical peatland;

[0010] Based on the actual dielectric constant and actual radar transmission parameters of each typical peatland, the temporal and spatial variation characteristics of each typical peatland are determined; the temporal and spatial variation characteristics are used to characterize the changes in the electromagnetic properties and electromagnetic scattering of the soil in the temporal and spatial dimensions of the typical peatland;

[0011] Based on the temporal and spatial variation characteristics of each typical peatland and the deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions is determined; the GPR application potential information is used to characterize the detection capability of ground penetrating radar to detect peatlands in different locations and seasons;

[0012] A GPR applicable parameter prediction model is constructed based on the GPR application potential information of peatlands in different regions; the GPR applicable parameter prediction model is used to predict the GPR radar applicable parameters and radar detection season that match the peatlands to be predicted.

[0013] In an optional implementation, based on the characteristic information of each typical peatland, a target GPR matching all typical peatlands in the target area and radar applicable parameters corresponding to each typical peatland are determined, including:

[0014] Inputting soil physicochemical parameters and peat types of each typical peatland into the dielectric mixing model, and obtaining the first predicted dielectric constant of each typical peatland output by the dielectric mixing model;

[0015] The peat type, peat layer and first predicted dielectric constant of each typical peatland are input into the multi-layer dielectric model to obtain the first predicted radar transmission parameters of each typical peatland output by the multi-layer dielectric model; the first predicted radar transmission parameters are propagation parameters of simulated electromagnetic waves in each peatland;

[0016] Based on the first predicted dielectric constant and the first predicted radar transmission parameter of each typical peatland, a target GPR matching all typical peatlands in the target area and radar applicable parameters corresponding to each typical peatland are determined.

[0017] In an optional implementation, the temporal and spatial variation characteristics of each typical peatland are determined based on the actual dielectric constant and actual radar transmission parameters of each typical peatland, including:

[0018] The first predicted dielectric constant, first predicted radar transmission parameter, actual dielectric constant and actual radar transmission parameter of each typical peatland were compared and analyzed to obtain the spatiotemporal variation characteristics of each typical peatland.

[0019] In an optional implementation, the GPR application potential information of peatlands in different regions is determined based on the spatiotemporal variation characteristics of each typical peatland and the deposit genesis types of peatlands distributed in different regions, including:

[0020] Based on the temporal and spatial variation characteristics of each typical peatland, the variation factor of each typical peatland is determined; the variation factor is used to characterize the temporal and spatial differences of the electromagnetic characteristics and electromagnetic scattering characteristics of each typical peatland;

[0021] Based on the variation factors of each typical peatland and the actual dielectric constant corresponding to each typical peatland, an electromagnetic property prediction model is constructed;

[0022] Based on the variation factors of each typical peatland and the actual radar transmission parameters corresponding to each typical peatland, an electromagnetic transmission prediction model is constructed;

[0023] Through the electromagnetic property prediction model and the electromagnetic transmission prediction model, as well as the mineral deposit types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions is determined.

[0024] In an optional implementation, the GPR application potential information of peatlands in different regions is determined by using the electromagnetic property prediction model and the electromagnetic transmission prediction model, as well as the deposit genesis types of peatlands distributed in different regions, including:

[0025] The soil physical and chemical parameters and peat types of each typical peatland are respectively input into the electromagnetic property prediction model to obtain the second predicted dielectric constant of each typical peatland output by the electromagnetic property prediction model;

[0026] Inputting the peat type, peat layer and second predicted dielectric constant of each typical peatland into the electromagnetic transmission prediction model, and obtaining the second predicted radar transmission parameter of each typical peatland output by the electromagnetic transmission prediction model;

[0027] Based on the second predicted dielectric constant and the second predicted radar transmission parameters of each typical peatland, as well as the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions is determined.

[0028] In an optional implementation, based on the second predicted dielectric constant and the second predicted radar transmission parameter of each typical peatland, and the deposit genesis type of the peatlands distributed in different regions, the GPR application potential information of the peatlands in different regions is determined, including:

[0029] Adjusting the parameters of the electromagnetic property prediction model based on the actual dielectric constant of each typical peatland and the second predicted dielectric constant to obtain a target electromagnetic property prediction model;

[0030] adjusting the parameters of the electromagnetic transmission prediction model based on the actual radar transmission parameters of each typical peatland and the second predicted radar transmission parameters to obtain a target electromagnetic transmission prediction model;

[0031] Based on the target electromagnetic property prediction model and the target electromagnetic transmission prediction model, an initial GPR application potential prediction model is constructed;

[0032] The soil physicochemical parameters, peat types and peat layers of each typical peatland are input into the initial GPR application potential prediction model to obtain the third predicted dielectric constant and the third predicted radar transmission parameter of each typical peatland output by the initial GPR application potential prediction model;

[0033] Based on the third predicted dielectric constant and the third predicted radar transmission parameters of each typical peatland and the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions is determined.

[0034] In an optional implementation, based on the third predicted dielectric constant and the third predicted radar transmission parameter of each typical peatland, and the deposit genesis type of the peatlands distributed in different regions, the GPR application potential information of the peatlands in different regions is determined, including:

[0035] Based on the third predicted dielectric constant, the third predicted radar transmission parameter, the actual radar transmission parameter and the actual dielectric constant of each typical peatland, the temporal and spatial variation distribution information of the GPR application potential corresponding to the target area is determined; the temporal and spatial variation distribution information of the GPR application potential is used to characterize the effectiveness of the target GPR detection of typical peatlands at different locations and in different seasons within the target area;

[0036] Based on the actual radar transmission parameters, actual dielectric constant, temporal and spatial distribution information of GPR application potential and the initial GPR application potential prediction model of each typical peatland, a target GPR application potential prediction model was constructed;

[0037] Input soil physicochemical parameters, peat types and peat layers of each typical peatland into the target GPR application potential prediction model to obtain the fourth predicted dielectric constant and fourth predicted radar transmission parameter of each typical peatland output by the target GPR application potential prediction model;

[0038] Based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland and the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions is determined.

[0039] In an optional implementation, based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in different regions, the GPR application potential information of the peatlands in different regions is determined, including:

[0040] Obtain the genesis of peat deposits in each typical peatland in the target area and the genesis of peat deposits in peatlands in other areas; the genesis of peat deposits in peatlands in other areas has a similar relationship with the genesis of peat deposits in typical peatlands;

[0041] The genesis of peat deposits in each typical peatland is analyzed with that in peatlands in other regions, and the genesis types of peat deposits in different regions are obtained.

[0042] Based on the fourth predicted dielectric constant and fourth predicted radar transmission parameters of each typical peatland and the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions is determined.

[0043] In an optional implementation, a GPR applicable parameter prediction model is constructed based on the GPR application potential information of peatlands in different regions, including:

[0044] Acquire a sample data set; the sample data set includes a plurality of combinations of dielectric constants and radar transmission parameters, and a target label corresponding to each combination of dielectric constants and radar transmission parameters, wherein the target label is a radar applicable parameter of the GPR matching the combination of dielectric constants and radar transmission parameters;

[0045] Based on the GPR application potential information of peatlands in different regions, sample data sets and target GPR application potential prediction model, a GPR applicable parameter prediction model was constructed.

[0046] In a second aspect of the present application, there is provided a device for constructing a GPR applicable parameter prediction model for detecting peat reserves, the device comprising:

[0047] The first acquisition module is used to obtain characteristic information corresponding to various typical peatlands in the target area; the characteristic information includes soil physical and chemical parameters, peat types and peat layers of each typical peatland;

[0048] The GPR determination module is used to determine the target GPR matching all typical peatlands in the target area and the radar applicable parameters corresponding to each typical peatland based on the characteristic information of each typical peatland;

[0049] The second acquisition module is used to obtain the actual dielectric constant and actual radar transmission parameters of each typical peatland; the actual dielectric constant and actual radar transmission parameters of each typical peatland are parameters of the target GPR, which are adjusted to the applicable radar parameters corresponding to the typical peatland, and the parameters are obtained by field detection of the typical peatland; the actual radar transmission parameters at least include: the penetration depth and reflection intensity of the electromagnetic wave emitted by the target GPR in the typical peatland;

[0050] The module for determining the spatiotemporal variation characteristics is used to determine the spatiotemporal variation characteristics of each typical peatland based on the actual dielectric constant and actual radar transmission parameters of each typical peatland. The spatiotemporal variation characteristics are used to characterize the changes in the electromagnetic characteristics and electromagnetic scattering of the soil in the time and space dimensions of the typical peatland.

[0051] The GPR application potential information determination module is used to determine the GPR application potential information of peatlands in different regions based on the spatiotemporal variation characteristics of each typical peatland and the deposit genesis types of peatlands distributed in different regions; the GPR application potential information is used to characterize the detection capability of ground penetrating radar to detect peatlands in different locations and seasons;

[0052] The model building module is used to build a GPR applicable parameter prediction model based on the GPR application potential information of peatlands in different regions; the GPR applicable parameter prediction model is used to predict the GPR radar applicable parameters and radar detection season that match the peatland to be predicted.

[0053] Compared with the prior art, this application has the following beneficial effects:

[0054] In the technical solution of the present application, based on the characteristic information of various typical peatlands in the target area, the target GPR matching all the typical peatlands in the target area and the applicable radar parameters corresponding to each typical peatland can be determined, so that the target GPR and the applicable radar parameters corresponding to each typical peatland can be used to detect each typical peatland on the spot, and the accurate actual dielectric constant and actual radar transmission parameters can be obtained; based on the accurate actual dielectric constant and actual radar transmission parameters obtained, the electromagnetic characteristics and electromagnetic scattering changes of the soil of each typical peatland in the time dimension and the space dimension (i.e. spatiotemporal variation characteristics); based on the spatiotemporal variation characteristics of each typical peatland, combined with the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions can be determined, wherein the GPR application potential information is used to characterize the detection capability of ground penetrating radar to detect typical peatlands in different locations and seasons; the applicable parameter prediction model of GPR constructed based on the GPR application potential information can accurately predict the radar applicable parameters of GPR and the radar detection season that match the peatland to be predicted, thereby reducing the blindness of GPR selection and improving the effectiveness of peat resource detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0056] Figure 1 A flowchart of a method for constructing a GPR applicable parameter prediction model for detecting peat reserves provided in an embodiment of the present application;

[0057] Figure 2 A flowchart of another method for constructing a GPR applicable parameter prediction model for detecting peat reserves provided in an embodiment of the present application;

[0058] Figure 3 A flowchart of a process for determining a target GPR provided in an embodiment of the present application;

[0059] Figure 4 A flowchart of a process for constructing a GPR applicable parameter prediction model provided in an embodiment of the present application;

[0060] Figure 5 A schematic diagram of the structure of a device for constructing a GPR applicable parameter prediction model for detecting peat reserves provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] As described above, currently, when users use GPR to detect peat resources, they are not familiar with the soil characteristics of peatlands and tend to blindly select a GPR to detect the peatland. However, by blindly selecting GPR for detection, there may be problems such as not being able to see or clearly see the interface between the peat and the surrounding soil in the radar image, or the interface seen is inconsistent with the actual thickness of the peat, which makes it impossible to effectively survey peat resources.

[0062] After research, the inventors proposed a method for constructing a GPR applicable parameter prediction model for detecting peat reserves. The method can determine the target GPR that matches all typical peatlands in the target area and the radar applicable parameters corresponding to each typical peatland based on the characteristic information of multiple typical peatlands in the target area. Therefore, through the target GPR and the radar applicable parameters corresponding to each typical peatland, each typical peatland can be detected on the spot to obtain accurate actual dielectric constant and actual radar transmission parameters; based on the obtained accurate actual dielectric constant and actual radar transmission parameters, the soil of each typical peatland can be determined in the time dimension and space dimension. The electromagnetic characteristics and changes in electromagnetic scattering (i.e., spatiotemporal variation characteristics) of each typical peatland can be determined based on the spatiotemporal variation characteristics of each typical peatland, combined with the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions can be determined, among which the GPR application potential information is used to characterize the detection capability of ground penetrating radar to detect typical peatlands in different locations and seasons; the GPR applicable parameter prediction model constructed based on the GPR application potential information can accurately predict the GPR radar applicable parameters and radar detection season that match the peatland to be predicted, thereby reducing the blindness of GPR selection and improving the effectiveness of peat resource detection.

[0063] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0064] Keyword definitions:

[0065] Electromagnetic scattering characteristics: refers to the phenomenon and characteristics of electromagnetic waves being scattered when they encounter different media or targets due to reasons such as the inhomogeneity of the medium or the geometric shape of the target.

[0066] Method Embodiment

[0067] The present application provides an embodiment of a method for constructing a parameter prediction model applicable to GPR for detecting peat reserves. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer device such as a set of computer executable instructions. In addition, although the logical order is shown in the flowchart, it is only an example order provided. In some cases, the steps shown or described can be performed in a different order than here.

[0068] See also Figure 1 , which is a flow chart of a method for constructing a GPR applicable parameter prediction model for detecting peat reserves provided in an embodiment of the present application, the method comprising the following steps:

[0069] Step S101, obtaining characteristic information corresponding to a plurality of typical peatlands in a target area.

[0070] In an optional implementation, such as Figure 2 As shown in the figure, various typical peatlands are peatlands with obvious peat deposition characteristics selected on the basis of consulting historical archives, such as high peatlands, middle peatlands and low peatlands. The characteristic information of typical peatlands includes soil physical and chemical parameters, peat types and peat layers of typical peatlands. Among them, the soil physical and chemical parameters of typical peatlands include soil volume water content, soil dry bulk density (i.e. soil density, which is the ratio of the mass of dry matrix material to the total volume), soil organic matter content, peat decomposition degree, mineral content, total salinity of peat water, particle size percentage and pH value. Peat types include: moss peat, herbaceous-moss peat, herbaceous-woody-moss peat and woody-moss peat in high peatlands; herbaceous peat, moss-herbaceous peat, woody-herbaceous-moss peat in middle peatlands; herbaceous peat, woody peat and woody-herbaceous peat in low peatlands. Peat layers include: peat layer, mineral sediment layer, organic mixed layer, root layer, humus layer, ash layer, fossil layer, transition layer, etc.

[0071] In an optional embodiment, a system for constructing a GPR applicable parameter prediction model for detecting peat reserves can be used as an execution subject of the method for constructing a GPR applicable parameter prediction model for detecting peat reserves in the embodiment of the present application. For the convenience of description, the system for constructing a GPR applicable parameter prediction model for detecting peat reserves is referred to as the system below.

[0072] It should be noted that by obtaining information such as soil physical and chemical parameters, peat types and peat strata of a variety of typical peatlands, the soil characteristics of various typical peatlands can be accurately reflected, thereby providing accurate data for the subsequent construction of an applicable parameter prediction model for GPR.

[0073] Step S102, determining a target GPR matching all typical peatlands in the target area and radar applicable parameters corresponding to each typical peatland based on characteristic information of each typical peatland.

[0074] In order to accurately obtain the actual dielectric constant and actual radar transmission parameters of each typical peatland, so as to provide accurate electromagnetic property parameters (i.e. dielectric constant) and radar transmission parameters for the subsequent construction of the applicable parameter prediction model of GPR, in this embodiment, the system can determine the target GPR that matches all typical peatlands in the target area and the applicable radar parameters corresponding to each typical peatland based on the characteristic information of each typical peatland, so that when the parameters of the target GPR are adjusted to the applicable radar parameters corresponding to the typical peatland, the field detection (i.e. Figure 2 The actual dielectric constant and actual radar transmission parameters can be obtained from the target GPR field detection of this typical peatland shown in the figure.

[0075] Specifically, the system can Figure 3 The target GPR determination process shown in FIG. 1 is used to determine the target GPR that matches all typical peatlands in the target area. The process includes the following steps:

[0076] Step S301 : inputting soil physical and chemical parameters and peat types of each typical peatland into a dielectric mixing model to obtain a first predicted dielectric constant of each typical peatland output by the dielectric mixing model.

[0077] In this embodiment, Figure 2 The dielectric mixture model shown in can be a four-term dielectric mixture model (such as the Dobson dielectric model). According to the soil electromagnetic properties of the Dobson dielectric model, the soil is regarded as a four-phase mixture consisting of air, solid soil, bound water and free water. The electromagnetic properties of soil are mainly affected by factors such as soil texture (the proportion of sand, clay, etc.), moisture (free water and bound water), porosity (saturation), etc. Since peatland soil includes the top plate, bottom plate and peat soil of the peat deposit, the top plate contains a large number of plant roots and buried clay, and the bottom plate contains a large amount of clay and gravel. In addition to water, air and minerals, peat itself also contains a large amount of organic matter. Therefore, the soil of a typical peatland can be regarded as a four-phase mixture consisting of mineral bodies, plant bodies, free water and bound water. The model can be expressed by the following formula:

[0078]

[0079] in, The predicted value of the soil dielectric constant for a typical peatland output by the dielectric mixing model (e.g., the first predicted dielectric constant); , , , are the dielectric constants of mineral bodies, plant bodies, free water and bound water, respectively; S v , V v , V fw and V bw They are the volume ratios of mineral matter, plant matter, free water and bound water in soil respectively.

[0080] It should be noted that the dielectric mixing model can be used to predict the dielectric constant of typical peatland soil using the soil physical and chemical parameters and peat types of typical peatlands, thereby realizing the prediction of the electromagnetic properties of peatland soil based on the soil physical and chemical parameters and peat types of peatland soil, providing a data basis for the subsequent construction of an applicable parameter prediction model for GPR.

[0081] Step S302: input the peat type, peat layer and first predicted dielectric constant of each typical peatland into a multi-layer dielectric model to obtain the first predicted radar transmission parameter of each typical peatland output by the multi-layer dielectric model.

[0082] In step S302, the first predicted radar transmission parameter is the propagation parameter of the simulated electromagnetic wave in each peatland, for example, the penetration depth and reflection intensity, transmission speed, transmission wavelength, background noise type and noise interference intensity of the electromagnetic wave simulated by the multi-layer dielectric model in a typical peatland.

[0083] In this embodiment, Figure 2 The multi-layer dielectric model shown in the figure is a peatland multi-layer dielectric physical model established to simulate the soil profile of field sampling in the peatland. It uses the finite-difference time-domain method (FDTD) to clearly and accurately interpret the soil information of each layer of the peatland. The multi-layer dielectric model can use the electromagnetic properties of the soil (i.e., dielectric constant) as the boundary conditions for analyzing the multi-layer soil of the peatland using numerical simulation methods, and calculate the propagation parameters of radar waves in the multi-layer medium of the peatland when the top plate of the peatland is air, plant layer, grass root layer or inorganic sediment layer, and the middle layer and bottom plate are inorganic sediment layers. Therefore, the multi-layer dielectric model can predict the penetration depth and reflection intensity, transmission speed, transmission wavelength, background noise type and noise interference intensity of electromagnetic waves in typical peatlands based on the peat type, peat layer and the first predicted dielectric constant of typical peatlands. It can also predict the propagation law of electromagnetic waves in multi-layer media of peatlands based on the peat type, peat layer and soil dielectric constant of peatlands, providing a data basis for the subsequent construction of an applicable parameter prediction model for GPR.

[0084] Step S303, based on the first predicted dielectric constant and the first predicted radar transmission parameter of each typical peatland, determine the target GPR matching all typical peatlands in the target area and the radar applicable parameters corresponding to each typical peatland.

[0085] In this embodiment, the target GPR may be any one of an amplitude modulated pulse radar, a frequency modulated continuous wave radar, a pulse stretching and compression technology radar, a polarization modulation radar, etc.; applicable radar parameters include but are not limited to radar frequency, bandwidth, antenna type and other parameters that affect detection effect and data quality. For example, the radar frequency of the GPR suitable for detecting a typical peatland A may be 100 MHz, the bandwidth may be 50 MHz, and the antenna type may be a horn antenna; the radar frequency of the GPR suitable for detecting a typical peatland B may be 400 MHz, the bandwidth may be 200 MHz, and the antenna type may be a monopole antenna.

[0086] It should be noted that, based on the first predicted dielectric constant and the first predicted radar transmission parameters of each typical peatland predicted by the model, the target GPR matching all typical peatlands in the target area and the radar applicable parameters corresponding to each typical peatland are determined, which reduces the errors in the dielectric constant and radar transmission parameters of the typical peatlands detected in the field due to the mismatch between the radar applicable parameters of the GPR and the typical peatlands, thereby improving the accuracy of the dielectric constant and radar transmission parameters of the typical peatlands detected in the field by the GPR.

[0087] Step S103, obtaining the actual dielectric constant and actual radar transmission parameters of each typical peatland; the actual dielectric constant and actual radar transmission parameters of each typical peatland are parameters of the target GPR, which are obtained by field detection of the typical peatland when the parameters are adjusted to the applicable radar parameters corresponding to the typical peatland.

[0088] In step S103, the actual radar transmission parameters of each typical peatland include at least the penetration depth and reflection intensity of the electromagnetic wave emitted by the target GPR in the typical peatland. In addition, the actual radar transmission parameters also include the transmission speed, transmission wavelength, background noise type and noise background intensity of the electromagnetic wave in the typical peatland.

[0089] Step S104, determining the spatiotemporal variation characteristics of each typical peatland according to the actual dielectric constant and actual radar transmission parameters of each typical peatland.

[0090] In step S104, Figure 2 The temporal and spatial variation characteristics shown in are used to characterize the changes in electromagnetic properties and electromagnetic scattering of soils in typical peatlands in the temporal and spatial dimensions.

[0091] In this embodiment, the system can determine the changes in electromagnetic characteristics and electromagnetic scattering of soil in each typical peatland in the time dimension and space dimension based on the actual dielectric constant, actual radar transmission parameter, first predicted dielectric constant and first predicted radar transmission parameter of each typical peatland. Specifically, the system can compare and analyze the first predicted dielectric constant, first predicted radar transmission parameter, actual dielectric constant and actual radar transmission parameter of each typical peatland to obtain the temporal and spatial variation characteristics of each typical peatland.

[0092] For example, a comparative analysis is conducted on the first predicted dielectric constant, the first predicted radar transmission parameters, the actual dielectric constant and the actual radar transmission parameters of each typical peatland, and the penetration depth, reflection intensity, background noise type and background noise intensity of radar waves in the multi-layer media of peatlands in different seasons (such as winter and summer) and different waterlogging periods are calculated. In addition, the electromagnetic scattering characteristics of targets in typical peatlands at different locations of radar waves (such as scattering intensity, scattering direction, scattering phase, scattering polarization, scattering matrix, scattering time delay and scattering spectrum) are analyzed, so as to obtain the electromagnetic characteristics and changes in electromagnetic scattering of the soil in the time and space dimensions of each typical peatland.

[0093] It should be noted that by determining the changes in the electromagnetic characteristics and electromagnetic scattering of the soil in the time and space dimensions of each typical peatland based on the actual dielectric constant, actual radar transmission parameters, the first predicted dielectric constant and the first predicted radar transmission parameters of each typical peatland, the detection mechanism of different types of peatlands in GPR in different seasons can be determined, thereby providing a data basis for the subsequent construction of an applicable parameter prediction model for GPR.

[0094] Step S105, determining the GPR application potential information of peatlands in different regions based on the temporal and spatial variation characteristics of each typical peatland and the mineral deposit genesis types of peatlands distributed in different regions.

[0095] In step S105, the GPR application potential information is used to characterize the detection capability of the ground penetrating radar to detect peatlands in different locations and seasons. For example, the detection capability of the ground penetrating radar to detect the location of peatland A in spring: the radar signal penetration depth is good, but due to the high water content, the signal attenuation is large, the resolution is slightly low, and the peat layer thickness measurement result is relatively accurate, but the details are not clear enough; the detection capability of the ground penetrating radar to detect the location of peatland A in summer: the radar signal penetration depth is moderate and the resolution is high. The peat layer thickness measurement result is accurate and the image details are clear.

[0096] In this embodiment, the deposit genesis types of peatlands distributed in different regions include, but are not limited to, piedmont depression type, river floodplain type, lake conversion type, swamp type, permafrost type and intertidal zone type.

[0097] In order to accurately determine the GPR application potential information of peatlands in different regions, in this embodiment, the system can determine the GPR application potential information of peatlands in different regions based on the spatiotemporal variation characteristics of each typical peatland, the electromagnetic property prediction model, the electromagnetic transmission prediction model, and the mineral deposit genesis type of peatlands distributed in different regions. Specifically, the system can determine the GPR application potential information of peatlands in different regions through the following steps:

[0098] Step 1: Determine the variation factor of each typical peatland based on its spatiotemporal variation characteristics.

[0099] In step 1, the variation factor is used to characterize the temporal and spatial differences in the electromagnetic properties and electromagnetic scattering characteristics of each typical peatland, for example, factors such as moisture content, organic matter content, density, and temperature of a typical peatland.

[0100] Step 2: Construct an electromagnetic property prediction model based on the variation factors of each typical peatland and the actual dielectric constant corresponding to each typical peatland.

[0101] Step 3: construct an electromagnetic transmission prediction model based on the variation factors of each typical peatland and the actual radar transmission parameters corresponding to each typical peatland.

[0102] In this embodiment, Figure 2 The electromagnetic property prediction model shown in is a prediction model built on the basis of the dielectric mixture model. Figure 2 The electromagnetic transmission prediction model shown in is a prediction model built on the basis of a multi-layer dielectric model. Since the variation factor has an important influence on the propagation and scattering characteristics of electromagnetic waves, an electromagnetic property prediction model that can accurately predict the dielectric constant of peatland soil can be obtained based on the dielectric mixing model, the variation factor of each typical peatland, and the actual dielectric constant corresponding to each typical peatland; an electromagnetic transmission prediction model that can accurately predict the radar transmission parameters corresponding to peatlands can be obtained based on the multi-layer dielectric model, the variation factor of each typical peatland, and the actual radar transmission parameters corresponding to each typical peatland.

[0103] Step 4: Determine the GPR application potential information of peatlands in different regions through the electromagnetic property prediction model and the electromagnetic transmission prediction model, as well as the mineral deposit genesis types of peatlands distributed in different regions.

[0104] It should be noted that the above steps 1 to 4 are not shown in the figure.

[0105] In order to further accurately determine the GPR application potential information of peatlands in different regions, in this embodiment, the system can determine the GPR application potential information of peatlands in different regions through the second predicted dielectric constant of each typical peatland predicted by the electromagnetic property prediction model, the second predicted radar transmission parameter of each typical peatland predicted by the electromagnetic transmission prediction model, and the mineral deposit genesis type of peatlands distributed in different regions. Specifically, the system can determine the GPR application potential information of peatlands in different regions through the following steps:

[0106] Step 41 : inputting soil physical and chemical parameters and peat types of each typical peatland into the electromagnetic property prediction model respectively, and obtaining the second predicted dielectric constant of each typical peatland output by the electromagnetic property prediction model.

[0107] Step 42, inputting the peat type, peat layer and second predicted dielectric constant of each typical peatland into the electromagnetic transmission prediction model to obtain the second predicted radar transmission parameters of each typical peatland output by the electromagnetic transmission prediction model.

[0108] Step 43, based on the second predicted dielectric constant and the second predicted radar transmission parameter of each typical peatland, and the mineral deposit genesis type of the peatlands distributed in different regions, determine the GPR application potential information of the peatlands in different regions.

[0109] It should be noted that the above steps 41 to 43 are not shown in the figure.

[0110] In this embodiment, the system can determine the GPR application potential information of peatlands in different regions based on the second predicted dielectric constant of each typical peatland, the second predicted radar transmission parameter, the initial GPR application potential prediction model, and the mineral deposit genesis type of the peatlands distributed in different regions. Specifically, the system can determine the GPR application potential information of peatlands in different regions through the following steps:

[0111] Step 431 : adjusting the parameters of the electromagnetic property prediction model based on the actual dielectric constant of each typical peatland and the second predicted dielectric constant to obtain a target electromagnetic property prediction model.

[0112] In this embodiment, by adjusting the parameters of the electromagnetic property prediction model based on the actual dielectric constant of each typical peatland and the second predicted dielectric constant, a target electromagnetic property prediction model with higher prediction accuracy can be obtained, so that the dielectric constant of the peatland can be accurately predicted based on the target electromagnetic property prediction model.

[0113] Step 432 : adjusting the parameters of the electromagnetic transmission prediction model based on the actual radar transmission parameters of each typical peatland and the second predicted radar transmission parameters to obtain a target electromagnetic transmission prediction model.

[0114] In this embodiment, by adjusting the parameters of the electromagnetic transmission prediction model through the actual radar transmission parameters of each typical peatland and the second predicted radar transmission parameters, a target electromagnetic transmission prediction model with higher prediction accuracy can be obtained, so that the radar transmission parameters corresponding to the peatland can be accurately predicted based on the target electromagnetic transmission prediction model.

[0115] Step 433: construct an initial GPR application potential prediction model based on the target electromagnetic property prediction model and the target electromagnetic transmission prediction model.

[0116] Step 434, input the soil physical and chemical parameters, peat type and peat layer system of each typical peatland into the initial GPR application potential prediction model to obtain the third predicted dielectric constant and third predicted radar transmission parameter of each typical peatland output by the initial GPR application potential prediction model.

[0117] In this embodiment, a target electromagnetic property prediction model and a target electromagnetic transmission prediction model are constructed. Figure 2 The initial GPR application potential prediction model shown in can provide a data basis for the subsequent accurate determination of the GPR application potential information of peatlands in different regions.

[0118] Step 435 , based on the third predicted dielectric constant and the third predicted radar transmission parameter of each typical peatland, and the mineral deposit genesis type of the peatlands distributed in different regions, determine the GPR application potential information of the peatlands in different regions.

[0119] It should be noted that the above steps 431 to 435 are not shown in the figure.

[0120] In this embodiment, the system can determine the GPR application potential information of peatlands in different regions based on the third predicted dielectric constant of each typical peatland, the third predicted radar transmission parameter, the temporal and spatial variation distribution information of the GPR application potential corresponding to the target area, and the mineral deposit genesis type of the peatlands distributed in different regions. Specifically, the system can determine the GPR application potential information of peatlands in different regions through the following steps:

[0121] Step 4351, based on the third predicted dielectric constant, the third predicted radar transmission parameter, the actual radar transmission parameter and the actual dielectric constant of each typical peatland, determine the spatiotemporal variation distribution information of the GPR application potential corresponding to the target area.

[0122] In step 4351, Figure 2The temporal and spatial variation distribution information of the GPR application potential shown in the figure is used to characterize the effectiveness of the target GPR detection of typical peatlands at different locations and seasons within the target area. For example, the location where the target GPR detection of typical peatland B is located, the effectiveness in spring is characterized by good radar signal penetration depth, but due to the high water content, the signal attenuation is large and the resolution is slightly low. The peat layer thickness measurement results are relatively accurate, but the details are not clear enough; the effectiveness in summer is characterized by moderate radar signal penetration depth and high resolution. The peat layer thickness measurement results are accurate and the image details are clear; the effectiveness in winter is characterized by both radar signal penetration depth and resolution being affected by temperature. There is more noise in the image, and the peat layer thickness measurement results have large errors.

[0123] Step 4352, based on the actual radar transmission parameters, actual dielectric constant, spatiotemporal distribution information of GPR application potential and the initial GPR application potential prediction model of each typical peatland, a target GPR application potential prediction model is constructed.

[0124] In this embodiment, Figure 2 The target GPR application potential prediction model shown in is a GPR application potential prediction model constructed on the basis of the initial GPR application potential prediction model using the temporal and spatial variation distribution information of the GPR application potential, actual radar transmission parameters, and actual dielectric constant.

[0125] Step 4353, input the soil physical and chemical parameters, peat type and peat layer system of each typical peatland into the target GPR application potential prediction model to obtain the fourth predicted dielectric constant and fourth predicted radar transmission parameter of each typical peatland output by the target GPR application potential prediction model.

[0126] Step 4354, based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland, and the mineral deposit genesis types of peatlands distributed in different regions, determine the GPR application potential information of peatlands in different regions.

[0127] It should be noted that the above steps 4351 to 4354 are not shown in the figure.

[0128] In this embodiment, the system determines the GPR application potential information of peatlands in different regions based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in different regions, specifically including the following steps:

[0129] Step 43541, obtaining the genesis of peat deposits of each typical peatland in the target area and the genesis of peat deposits of peatlands in other areas.

[0130] In step 43541, the genesis of peat deposits in peatlands in other regions has a similar relationship to that of peat deposits in typical peatlands. For example, the genesis of peat deposits in typical peatland A is: easy accumulation of water, humid climate, low temperature environment, stable water environment, a large amount of organic matter source, and suitable soil type and geology; then the genesis of peat deposits in peatland a in region 1 and peatland b in region 2 is the same as the above-mentioned genesis of peat deposits.

[0131] Step 43542, analyzing the genesis of the peat deposits in each typical peatland and the genesis of the peat deposits in other regions, and obtaining the genesis types of the peat deposits in the peatlands distributed in different regions.

[0132] For example, Figure 2 As shown in the comparative analysis of regions with the same or similar genesis types of peat deposits as typical peatlands, after analyzing the genesis of peat deposits in each typical peatland with that in peatlands in other regions, it is determined that regions 1 and 2 have the same or similar genesis as typical peatland A, regions 2 and 3 have the same or similar genesis as typical peatland B, and region 4 has the same or similar genesis as typical peatland C. Based on the above information, the genesis types of peatlands in regions 1-4 and the target area are obtained.

[0133] Step 43543, based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland, and the mineral deposit genesis type of the peatlands distributed in different regions, determine the GPR application potential information of the peatlands in different regions.

[0134] It should be noted that the above steps 43541 to 43543 are not shown in the figure.

[0135] In this embodiment, by analyzing the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland, the GPR application potential of ground penetrating radar detection of each typical peatland is accurately evaluated. On the basis of the accurate GPR application potential of the typical peatland, combined with the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions can be accurately determined.

[0136] Step S106, constructing a GPR applicable parameter prediction model based on the GPR application potential information of peatlands in different regions.

[0137] In step S106, the GPR applicable parameter prediction model is used to predict the radar applicable parameters and radar detection season of the GPR that match the peatland to be predicted.

[0138] In order to accurately predict the radar applicable parameters and radar detection season of GPR that match the peatland to be predicted, reduce the blindness of GPR selection, and improve the effectiveness of peat resource detection, in this embodiment, the system can build a GPR application potential prediction model based on the GPR application potential information of peatlands in different regions and the target GPR application potential prediction model. Figure 2 Applicable parameter prediction model for GPR shown in .

[0139] Specifically, see Figure 4 , Figure 4 A flowchart of a process for constructing a GPR applicable parameter prediction model provided in an embodiment of the present application, the process comprising the following steps:

[0140] Step S401, obtaining a sample data set.

[0141] In step S401, the sample data set includes a plurality of combinations of dielectric constants and radar transmission parameters, and a target label corresponding to each combination of dielectric constants and radar transmission parameters, wherein the target label is a radar applicable parameter of the GPR matching the combination of dielectric constants and radar transmission parameters.

[0142] Step S402: constructing a GPR applicable parameter prediction model based on the GPR application potential information of peatlands in different regions, the sample data set and the target GPR application potential prediction model.

[0143] In an embodiment of the present application, the soil physical and chemical parameters, peat type and peat layer system of the peatland are input into the applicable parameter prediction model of the GPR. The applicable parameter prediction model of the GPR can be input into the radar based on the soil physical and chemical parameters, peat type and peat layer system of the peatland, predict the dielectric constant and radar transmission parameters of the peatland, and determine the GPR application potential of the peatland based on the dielectric constant and radar transmission parameters, so as to match the accurate GPR radar applicable parameters and radar detection season for the peatland based on the GPR application potential, dielectric constant and radar transmission parameters, thereby reducing the blindness of GPR selection and improving the effectiveness of peat resource detection.

[0144] Optionally, in order to improve the model prediction accuracy of the applicable parameter prediction model of GPR, in this embodiment, the system may Figure 2 Based on the sampling verification shown in (the actual dielectric constant and actual radar transmission parameters of at least one area are detected by target GPR in the field), the applicable parameter prediction model of GPR is constructed by combining the GPR application potential information of peatlands in different regions, sample data sets and target GPR application potential prediction model.

[0145] The method for constructing a GPR applicable parameter prediction model for detecting peat reserves provided in the embodiment of the present application realizes that, based on the changes in the electromagnetic characteristics and electromagnetic scattering of the soil in each typical peatland in the time and space dimensions, combined with the mineral deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions can be accurately determined. Therefore, the GPR applicable parameter prediction model constructed on the basis of accurate GPR application potential information of peatlands in different regions can accurately predict the GPR radar applicable parameters and radar detection season that match the peatland to be predicted, thereby reducing the blindness of GPR selection and improving the effectiveness of peat resource detection, thereby providing technical support for the establishment of multi-regional peatland GPR soil applicability maps in the future and for large-scale peat surveys using GPR technology.

[0146] Device Embodiment

[0147] The present application embodiment provides a device for constructing a GPR applicable parameter prediction model for detecting peat reserves, wherein: Figure 5 A schematic diagram of a structure of a device for constructing a GPR applicable parameter prediction model for detecting peat reserves provided in an embodiment of the present application, such as Figure 5 As shown, the device includes: a first acquisition module 11, a GPR determination module 12, a second acquisition module 13, a spatiotemporal variation feature determination module 14, a GPR application potential information determination module 15 and a model building module 16. Figure 5 You can see the connection relationship between several modules.

[0148] The first acquisition module 11 is used to acquire characteristic information corresponding to various typical peatlands in the target area; the characteristic information includes soil physical and chemical parameters, peat types and peat layers of each typical peatland;

[0149] The GPR determination module 12 is used to determine the target GPR matching all the typical peatlands in the target area and the radar applicable parameters corresponding to each typical peatland based on the characteristic information of each typical peatland;

[0150] The second acquisition module 13 is used to obtain the actual dielectric constant and actual radar transmission parameters of each typical peatland; the actual dielectric constant and actual radar transmission parameters of each typical peatland are parameters of the target GPR, which are adjusted to the applicable radar parameters corresponding to the typical peatland, and the parameters are obtained by field detection of the typical peatland; the actual radar transmission parameters at least include: the penetration depth and reflection intensity of the electromagnetic wave emitted by the target GPR in the typical peatland;

[0151] The spatiotemporal variation characteristic determination module 14 is used to determine the spatiotemporal variation characteristics of each typical peatland based on the actual dielectric constant and actual radar transmission parameters of each typical peatland; the spatiotemporal variation characteristics are used to characterize the electromagnetic characteristics and electromagnetic scattering changes of the soil of the typical peatland in the time dimension and the space dimension;

[0152] The GPR application potential information determination module 15 is used to determine the GPR application potential information of peatlands in different regions based on the spatiotemporal variation characteristics of each typical peatland and the mineral deposit genesis types of peatlands distributed in different regions; the GPR application potential information is used to characterize the detection capability of ground penetrating radar to detect peatlands in different locations and seasons;

[0153] The model building module 16 is used to build a GPR applicable parameter prediction model based on the GPR application potential information of peatlands in different regions; the GPR applicable parameter prediction model is used to predict the GPR radar applicable parameters and radar detection season that match the peatland to be predicted.

[0154] Optionally, the GPR determination module includes: a first prediction unit, a second prediction unit and a first determination unit.

[0155] The first prediction unit is used to input the soil physical and chemical parameters and peat type of each typical peatland into the dielectric mixing model to obtain the first predicted dielectric constant of each typical peatland output by the dielectric mixing model;

[0156] The second prediction unit is used to input the peat type, peat layer and first predicted dielectric constant of each typical peatland into the multi-layer dielectric model to obtain the first predicted radar transmission parameters of each typical peatland output by the multi-layer dielectric model; the first predicted radar transmission parameters are propagation parameters of simulated electromagnetic waves in each peatland;

[0157] The first determination unit is used to determine the target GPR matching all typical peatlands in the target area and the radar applicable parameters corresponding to each typical peatland based on the first predicted dielectric constant and the first predicted radar transmission parameter of each typical peatland.

[0158] Optionally, the spatiotemporal variation characteristic determination module includes: a first analysis unit, used to compare and analyze the first predicted dielectric constant, the first predicted radar transmission parameter, the actual dielectric constant and the actual radar transmission parameter of each typical peatland to obtain the spatiotemporal variation characteristics of each typical peatland.

[0159] Optionally, the GPR application potential information determination module includes: a second determination unit, a first construction unit, a second construction unit and a third determination unit.

[0160] The second determination unit is used to determine the variation factor of each typical peatland based on the temporal and spatial variation characteristics of each typical peatland; the variation factor is used to characterize the temporal and spatial differences of the electromagnetic characteristics and electromagnetic scattering characteristics of each typical peatland;

[0161] The first construction unit is used to construct an electromagnetic property prediction model based on the variation factors of each typical peatland and the actual dielectric constant corresponding to each typical peatland;

[0162] The second construction unit is used to construct an electromagnetic transmission prediction model according to the variation factors of each typical peatland and the actual radar transmission parameters corresponding to each typical peatland;

[0163] The third determination unit is used to determine the GPR application potential information of peatlands in different regions through the electromagnetic property prediction model and the electromagnetic transmission prediction model, as well as the mineral deposit genesis types of peatlands distributed in different regions.

[0164] Optionally, the third determining unit includes: a third prediction unit, a fourth prediction unit and a fourth determining unit.

[0165] The third prediction unit is used to input the soil physical and chemical parameters and peat type of each typical peatland into the electromagnetic property prediction model, and obtain the second predicted dielectric constant of each typical peatland output by the electromagnetic property prediction model;

[0166] A fourth prediction unit is used to input the peat type, peat layer and second predicted dielectric constant of each typical peatland into the electromagnetic transmission prediction model to obtain the second predicted radar transmission parameter of each typical peatland output by the electromagnetic transmission prediction model;

[0167] The fourth determination unit is used to determine the GPR application potential information of peatlands in different regions based on the second predicted dielectric constant and the second predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in different regions.

[0168] Optionally, the fourth determining unit includes: a first parameter adjusting unit, a second parameter adjusting unit, a third constructing unit, a fourth constructing unit and a fifth determining unit.

[0169] The first parameter adjustment unit is used to adjust the parameters of the electromagnetic property prediction model based on the actual dielectric constant of each typical peatland and the second predicted dielectric constant to obtain a target electromagnetic property prediction model;

[0170] A second parameter adjustment unit is used to adjust the parameters of the electromagnetic transmission prediction model based on the actual radar transmission parameters of each typical peatland and the second predicted radar transmission parameters to obtain a target electromagnetic transmission prediction model;

[0171] The third construction unit is used to construct an initial GPR application potential prediction model based on the target electromagnetic property prediction model and the target electromagnetic transmission prediction model;

[0172] The fourth construction unit is used to input the soil physical and chemical parameters, peat type and peat layer of each typical peatland into the initial GPR application potential prediction model to obtain the third predicted dielectric constant and the third predicted radar transmission parameter of each typical peatland output by the initial GPR application potential prediction model;

[0173] The fifth determination unit is used to determine the GPR application potential information of peatlands in different regions based on the third predicted dielectric constant and the third predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in different regions.

[0174] Optionally, the fifth determining unit includes: a sixth determining unit, a fifth constructing unit, a fifth predicting unit and a seventh determining unit.

[0175] The sixth determination unit is used to determine the spatiotemporal variation distribution information of the GPR application potential corresponding to the target area based on the third predicted dielectric constant, the third predicted radar transmission parameter, the actual radar transmission parameter and the actual dielectric constant of each typical peatland; the spatiotemporal variation distribution information of the GPR application potential is used to characterize the effectiveness of the target GPR detection of typical peatlands at different locations and in different seasons within the target area;

[0176] The fifth construction unit is used to construct a target GPR application potential prediction model based on actual radar transmission parameters, actual dielectric constant, spatiotemporal variation distribution information of GPR application potential and an initial GPR application potential prediction model of each typical peatland;

[0177] a fifth prediction unit, for inputting soil physical and chemical parameters, peat types and peat layers of each typical peatland into the target GPR application potential prediction model, and obtaining a fourth predicted dielectric constant and a fourth predicted radar transmission parameter of each typical peatland output by the target GPR application potential prediction model;

[0178] The seventh determination unit is used to determine the GPR application potential information of peatlands in different regions based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in different regions.

[0179] Optionally, the seventh determining unit includes: a first acquiring unit, a second analyzing unit and an eighth determining unit.

[0180] The first acquisition unit is used to acquire the genesis of peat deposits in each typical peatland in the target area and the genesis of peat deposits in peatlands in other areas; the genesis of peat deposits in peatlands in other areas has a similar relationship with the genesis of peat deposits in typical peatlands;

[0181] The second analysis unit is used to analyze the genesis of peat deposits in each typical peatland and the genesis of peat deposits in other regions, so as to obtain the genesis types of peatlands distributed in different regions;

[0182] The eighth determination unit is used to determine the GPR application potential information of peatlands in different regions based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in different regions.

[0183] Optionally, the model building module includes: a second acquisition unit and a sixth building unit.

[0184] The second acquisition unit is used to acquire a sample data set; the sample data set includes a combination of multiple dielectric constants and radar transmission parameters, and a target label corresponding to each combination of dielectric constants and radar transmission parameters, and the target label is a radar applicable parameter of the GPR that matches the combination of dielectric constants and radar transmission parameters;

[0185] The sixth construction unit is used to construct a GPR applicable parameter prediction model based on the GPR application potential information of peatlands in different regions, the sample data set and the target GPR application potential prediction model.

[0186] It should be noted that each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiment described above is merely schematic, in which the unit described as a separate component may or may not be physically separated, and the component prompted as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0187] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for constructing a GPR applicable parameter prediction model for detecting peat reserves, characterized in that: include: Obtain characteristic information corresponding to various typical peatlands in the target area; The characteristic information includes soil physical and chemical parameters, peat types and peat layers of the typical peatland; Determining target GPRs matching all the typical peatlands in the target area and radar applicable parameters corresponding to each of the typical peatlands based on characteristic information of each of the typical peatlands; The actual dielectric constant and actual radar transmission parameter of each of the typical peatlands are obtained; the actual dielectric constant and actual radar transmission parameter of each of the typical peatlands are parameters of the target GPR that are adjusted to the applicable radar parameters corresponding to the typical peatland, and the parameters are obtained by field detection of the typical peatland; The actual radar transmission parameters include at least: the penetration depth and reflection intensity of the electromagnetic waves emitted by the target GPR in the typical peatland; Determine the spatiotemporal variation characteristics of each typical peatland based on the actual dielectric constant and the actual radar transmission parameters; the spatiotemporal variation characteristics are used to characterize the electromagnetic properties and electromagnetic scattering changes of the soil of the typical peatland in the time dimension and the space dimension; According to the spatiotemporal variation characteristics of each of the typical peatlands and the types of mineral deposit genesis of the peatlands distributed in different regions, the GPR application potential information of the peatlands in different regions is determined; the GPR application potential information is used to characterize the detection capability of the ground penetrating radar to detect peatlands in different locations and different seasons; the different regions include the target region and other regions except the target region, and the genesis of the peat deposits of the peatlands in the other regions has a similar relationship to the genesis of the peat deposits of the typical peatlands; A GPR applicable parameter prediction model is constructed based on the GPR application potential information of the peatlands in different regions; the GPR applicable parameter prediction model is used to predict the GPR radar applicable parameters and radar detection season that match the peatlands to be predicted.

2. The method according to claim 1, characterized in that Determining the target GPR matching all the typical peatlands in the target area and the radar applicable parameters corresponding to each typical peatland according to the characteristic information of each typical peatland includes: Inputting soil physicochemical parameters and peat types of each of the typical peatlands into a dielectric mixing model to obtain a first predicted dielectric constant of each of the typical peatlands output by the dielectric mixing model; Inputting the peat type, the peat layer system and the first predicted dielectric constant of each typical peatland into a multi-layer dielectric model, obtaining the first predicted radar transmission parameter of each typical peatland output by the multi-layer dielectric model; the first predicted radar transmission parameter is a propagation parameter of a simulated electromagnetic wave in each peatland; Based on the first predicted dielectric constant of each of the typical peatlands and the first predicted radar transmission parameters, a target GPR matching all typical peatlands in the target area and radar applicable parameters corresponding to each of the typical peatlands are determined.

3. The method according to claim 2, characterized in that Determining the spatiotemporal variation characteristics of each typical peatland based on the actual dielectric constant of each typical peatland and the actual radar transmission parameter includes: The first predicted dielectric constant, the first predicted radar transmission parameter, the actual dielectric constant and the actual radar transmission parameter of each of the typical peatlands are compared and analyzed to obtain the spatiotemporal variation characteristics of each of the typical peatlands.

4. The method according to claim 3, characterized in that According to the temporal and spatial variation characteristics of each typical peatland and the deposit genesis types of peatlands distributed in different regions, the GPR application potential information of peatlands in different regions is determined, including: Determine the variation factor of each typical peatland based on the temporal and spatial variation characteristics of each typical peatland; the variation factor is used to characterize the temporal and spatial differences of the electromagnetic characteristics and electromagnetic scattering characteristics of each typical peatland; According to the variation factors of each typical peatland and the actual dielectric constant corresponding to each typical peatland, an electromagnetic property prediction model is constructed; According to the variation factors of each typical peatland and the actual radar transmission parameters corresponding to each typical peatland, an electromagnetic transmission prediction model is constructed; The GPR application potential information of the peatlands in the different regions is determined by using the electromagnetic property prediction model and the electromagnetic transmission prediction model as well as the mineral deposit genesis types of the peatlands distributed in the different regions.

5. The method according to claim 4, characterized in that Determining the GPR application potential information of the peatlands in the different regions by using the electromagnetic property prediction model and the electromagnetic transmission prediction model, as well as the deposit genesis types of the peatlands distributed in the different regions, includes: Inputting the soil physicochemical parameters and the peat type of each typical peatland into the electromagnetic property prediction model, respectively, to obtain the second predicted dielectric constant of each typical peatland output by the electromagnetic property prediction model; Inputting the peat type, the peat layer system and the second predicted dielectric constant of each of the typical peatlands into the electromagnetic transmission prediction model to obtain the second predicted radar transmission parameters of each of the typical peatlands output by the electromagnetic transmission prediction model; Based on the second predicted dielectric constant and the second predicted radar transmission parameter of each of the typical peatlands, and the mineral deposit genesis types of the peatlands distributed in different regions, the GPR application potential information of the peatlands in the different regions is determined.

6. The method according to claim 5, characterized in that The method of determining the GPR application potential information of the peatlands in the different regions based on the second predicted dielectric constant and the second predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in the different regions comprises: Adjusting the parameters of the electromagnetic property prediction model based on the actual dielectric constant of each of the typical peatlands and the second predicted dielectric constant to obtain a target electromagnetic property prediction model; adjusting the parameters of the electromagnetic transmission prediction model based on the actual radar transmission parameters of each of the typical peatlands and the second predicted radar transmission parameters to obtain a target electromagnetic transmission prediction model; Based on the target electromagnetic property prediction model and the target electromagnetic transmission prediction model, construct an initial GPR application potential prediction model; Inputting the soil physicochemical parameters of each typical peatland, the peat type and the peat layer system into the initial GPR application potential prediction model, and obtaining the third predicted dielectric constant and the third predicted radar transmission parameter of each typical peatland output by the initial GPR application potential prediction model; Based on the third predicted dielectric constant of each typical peatland, the third predicted radar transmission parameter, and the mineral deposit genesis type of the peatlands distributed in different regions, the GPR application potential information of the peatlands in the different regions is determined.

7. The method according to claim 6, characterized in that Determining the GPR application potential information of the peatlands in the different regions based on the third predicted dielectric constant of each of the typical peatlands, the third predicted radar transmission parameter, and the mineral deposit genesis types of the peatlands distributed in the different regions includes: Based on the third predicted dielectric constant of each of the typical peatlands, the third predicted radar transmission parameter, the actual radar transmission parameter and the actual dielectric constant, determining the spatiotemporal variation distribution information of the GPR application potential corresponding to the target area; the spatiotemporal variation distribution information of the GPR application potential is used to characterize the effectiveness of the target GPR in detecting typical peatlands at different locations and in different seasons within the target area; Based on the actual radar transmission parameters of each of the typical peatlands, the actual dielectric constant, the spatiotemporal variation distribution information of the GPR application potential, and the initial GPR application potential prediction model, a target GPR application potential prediction model is constructed; Inputting the soil physicochemical parameters of each of the typical peatlands, the peat type and the peat layer system into the target GPR application potential prediction model, and obtaining the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each of the typical peatlands output by the target GPR application potential prediction model; Based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland and the mineral deposit genesis types of the peatlands distributed in different regions, the GPR application potential information of the peatlands in the different regions is determined.

8. The method according to claim 7, characterized in that Determining the GPR application potential information of the peatlands in the different regions based on the fourth predicted dielectric constant and the fourth predicted radar transmission parameter of each typical peatland and the mineral deposit genesis type of the peatlands distributed in the different regions includes: Obtaining the genesis of peat deposits of each of the typical peatlands in the target area and the genesis of peat deposits of peatlands in other areas; Analyze the genesis of peat deposits in each of the typical peatlands and the genesis of peat deposits in the other regions to obtain the genesis types of the peatlands distributed in different regions; Based on the fourth predicted dielectric constant of each typical peatland, the fourth predicted radar transmission parameter, and the mineral deposit genesis type of the peatlands distributed in different regions, the GPR application potential information of the peatlands in the different regions is determined.

9. The method according to claim 7, characterized in that: The GPR applicable parameter prediction model is constructed based on the GPR application potential information of the peatlands in different regions, including: Acquire a sample data set; the sample data set includes a plurality of combinations of dielectric constants and radar transmission parameters, and a target tag corresponding to each combination of the dielectric constants and radar transmission parameters, wherein the target tag is a radar applicable parameter of the GPR matching the combination of the dielectric constants and radar transmission parameters; Based on the GPR application potential information of the peatlands in the different regions, the sample data set and the target GPR application potential prediction model, an applicable parameter prediction model of the GPR is constructed.

10. A device for constructing a GPR applicable parameter prediction model for detecting peat reserves, characterized in that: include: The first acquisition module is used to obtain characteristic information corresponding to various typical peatlands in the target area; The characteristic information includes soil physical and chemical parameters, peat types and peat layers of each of the typical peatlands; A GPR determination module, for determining a target GPR matching all the typical peatlands in the target area and radar applicable parameters corresponding to each of the typical peatlands according to the characteristic information of each of the typical peatlands; The second acquisition module is used to obtain the actual dielectric constant and actual radar transmission parameters of each of the typical peatlands; the actual dielectric constant and actual radar transmission parameters of each of the typical peatlands are parameters obtained by field detection of the typical peatlands when the parameters of the target GPR are adjusted to the applicable radar parameters corresponding to the typical peatlands; The actual radar transmission parameters include at least: the penetration depth and reflection intensity of the electromagnetic waves emitted by the target GPR in the typical peatland; A module for determining spatiotemporal variation characteristics, for determining the spatiotemporal variation characteristics of each typical peatland according to the actual dielectric constant of each typical peatland and the actual radar transmission parameter; the spatiotemporal variation characteristics are used to characterize the changes in electromagnetic properties and electromagnetic scattering of the soil of the typical peatland in the time dimension and the space dimension; A GPR application potential information determination module is used to determine the GPR application potential information of peatlands in different regions according to the spatiotemporal variation characteristics of each typical peatland and the types of mineral deposit genesis of peatlands distributed in different regions; the GPR application potential information is used to characterize the detection capability of ground penetrating radar to detect peatlands in different locations and seasons; the different regions include the target region and other regions except the target region, and the genesis of peat deposits of peatlands in the other regions has a similar relationship with the genesis of peat deposits of the typical peatlands; The model building module is used to build a GPR applicable parameter prediction model based on the GPR application potential information of the peatlands in different regions; the GPR applicable parameter prediction model is used to predict the GPR radar applicable parameters and radar detection season that match the peatlands to be predicted.

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