Method for Inverting Soil Particle Size in Mining Area and Computer Equipment

Abstract

The present application relates to the technical fields of surface ecological environment monitoring in mining areas and computer technology, and discloses a method for inverting the particle size of mining area soil and a computer device. The method includes: obtaining various particle size grades of mining area soil and the effective particle size of each particle size grade, and spectral reflectance curves when respectively at different observation azimuth angles, different observation zenith angles, and a fixed light source zenith angle, obtaining a variety of photometric parameters of mining area soil by using a soil characteristic physical model and the spectral reflectance curves, and calculating an inversion index for the particle size of mining area soil; constructing an inversion regression equation for the particle size of mining area soil based on the inversion index for the particle size of mining area soil and the effective particle size, and inversely obtaining the inverted soil particle size of mining area soil. The bidirectional reflectance spectrum of mining area soil is simulated by using a soil characteristic physical model, and a new inversion index for the particle size of mining area soil is constructed based on the fitted photometric parameters, reducing the influence of soil type on the inversion of the particle size of mining area soil and improving the inversion accuracy of the particle size of mining area soil.

Description

Technical Field

[0001] This application relates to the technical fields of surface ecological environment monitoring in mining areas and computer technology, and particularly to a method for inverting soil particle size in mining areas and a computer device. Background Art

[0002] The particle size is a basic physical property of soil and affects soil properties related to soil structure. The reflectance spectrum can indicate the particle size on the surface of particles (such as soil or sand). As the soil particle size gradually increases, the heterogeneity of the soil surface reflectance spectrum increases. In addition, the reflectance of soil particles is anisotropic with respect to the observation angle and the illumination angle. The bidirectional reflectance distribution function (BRDF) can be used to represent this anisotropic characteristic. Research shows that particle size affects the estimation of soil properties (such as soil organic carbon and total nitrogen). If the bidirectional reflectance characteristics of the soil surface are ignored, it will also affect the estimation accuracy of soil properties.

[0003] Large-scale open-pit mining activities in arid and semi-arid regions will change the soil structure, especially the soil particle size distribution. Compared with natural soil, the mining area soil has a high gravel content and a low organic matter content, showing significant non-Lambertian characteristics. The reflectance spectra in different directions are significantly different, thus affecting the measurement accuracy of particle size. Summary of the Invention

[0004] In view of this, this application provides a method for inverting soil particle size in mining areas and a computer device. The bidirectional reflectance spectrum of mining area soil is simulated by using a physical model of soil characteristics. Based on the fitted photometric parameters, a new index for inverting soil particle size in mining areas is constructed, reducing the influence of soil type on the inversion of soil particle size in mining areas, and thus improving the inversion accuracy of soil particle size in mining areas.

[0005] According to one aspect of this application, a method for inverting soil particle size in mining areas is provided. The method includes:

[0006] Collect mining area soil in different regions of the mining area. For the mining area soil in any region, obtain various particle size grades of the mining area soil and the effective particle size of each particle size grade, where each mining area soil contains at least one particle size grade of soil;

[0007] Select any particle size grade of the soil in any mining area, and obtain the spectral reflectance curves of the selected mining area soil of the selected particle size grade when measured by a multi-angle soil reflectance measurement device at different observation azimuth angles and different observation zenith angles. Among them, each spectral reflectance curve is composed of spectral reflectances of multiple bands. The multi-angle soil reflectance measurement device is provided with multiple observation azimuth angles and multiple observation zenith angles, and the multi-angle soil reflectance measurement device emits light based on a fixed light source zenith angle;

[0008] Use the soil characteristic physical model and the spectral reflectance curve to simulate the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade, and obtain various photometric parameters of the selected mining area soil of the selected particle size grade;

[0009] Among the various photometric parameters, determine the target photometric parameters that are the same as the types of photometric parameters related to the preset particle size inversion. Based on the target photometric parameters and the correlation relationships between the target photometric parameters, calculate the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade;

[0010] For the mining area soil in each region, jointly invert the inverted soil particle sizes of various particle size grades of the soil in the mining area based on the mining area soil particle size inversion index and the effective particle size of each particle size grade of the mining area soil;

[0011] According to another aspect of the present application, a computer device is provided, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the program, the above-mentioned mining area soil particle size inversion method is implemented.

[0012] By means of the above technical solution, a mining area soil particle size inversion method and a computer device provided by the present application use a soil characteristic physical model to simulate the bidirectional reflectance spectrum of mining area soil, and based on the fitted photometric parameters, construct a new mining area soil particle size inversion index, reducing the influence of mining area soil particle size inversion by soil types, and thus improving the accuracy of mining area soil particle size inversion.

[0013] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the description. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically given below. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings:

[0015] Figure 1 The flowchart of a method for inverting the particle size of mine soil provided by an embodiment of the present application is shown;

[0016] Figure 2 The schematic diagram of various particle size grades and effective particle sizes of a mine soil provided by an embodiment of the present application is shown;

[0017] Figure 3 The flowchart of another method for inverting the particle size of mine soil provided by an embodiment of the present application is shown. Detailed implementation manners

[0018] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other.

[0019] In this embodiment, a method for inverting the particle size of mine soil is provided. As Figure 1 shown, the method includes:

[0020] Step 101: Collect the mine soil in different areas in the mine area. For the mine soil in any area, obtain various particle size grades of the mine soil and the effective particle size of each particle size grade, where each mine soil includes at least one particle size grade of soil.

[0021] Currently, the research on inverting the particle size of mine soil using the reflectance spectrum is mostly based on the vertical observation, ignoring the bidirectional reflectance characteristics of the mine soil surface. At the same time, based on the empirical relationship that the soil reflectance is negatively correlated with the particle size, a variety of empirical methods have been used to estimate the soil particle size. However, these empirical models are highly dependent on specific datasets, are greatly affected by different soil types, and lack a direct connection with the physical and chemical properties of the soil, resulting in insufficient model interpretability. In this case, for the inversion of the mine soil particle size, it is mainly based on the vertical observation spectrum, ignoring the non-Lambertian characteristics of the mine soil surface, and the bidirectional reflectance characteristics of the mine soil are still unclear. In addition, the traditional empirical models are greatly affected by the soil type, and it is still unclear how to use the photometric parameters of the physical model and integrate the photometric parameters to improve the accuracy of the mine soil particle size inversion. At the same time, although the physical model of soil characteristics can explain the relationship between the reflectance and the soil particle size through parameters such as the single-scattering albedo, refractive index, and absorption rate. However, whether the physical model can better fit the bidirectional reflectance of the mine soil remains to be verified. Affected by the complex internal components of the soil, a single photometric parameter is difficult to estimate the particle size of different types of soil. It is crucial to integrate multiple photometric parameters to eliminate the influence of the soil type on the particle size estimation and improve the accuracy of the mine soil particle size inversion.

[0022] In the above embodiments of the present application, a physical model of soil properties can be used to simulate the bidirectional reflectance spectrum of mine soil, and a new mine soil particle size inversion index can be constructed based on the fitted photometric parameters, reducing the influence of soil type on the inversion of mine soil particle size, and thus improving the accuracy of mine soil particle size inversion.

[0023] Specifically, mine soil in different regions of the mining area is collected. In particular, mine soil in different types of regions can be collected to enrich the "sample characteristics". For the mine soil in any region, various particle size grades of the mine soil are obtained, as well as the effective particle size of each particle size grade. Among them, each mine soil contains at least one particle size grade of soil, preparing for subsequent particle size inversion. Regarding the collection process, soil can be collected on the surface of the waste dump in a typical open-pit mine in arid and semi-arid regions and dried for subsequent measurement preparation.

[0024] Optionally, for the mine soil in any region, the mine soil of different particle size grades is obtained by screening based on soil sieves of different particle size grades. During the soil screening process, the screening order of the soil sieves is in descending order of particle size grade. The soil screened by any soil sieve of a particle size grade corresponds to a particle size interval. In step 101, for obtaining the effective particle size of each particle size grade, it specifically includes:

[0025] Step 1011, for any particle size grade of the mine soil, based on the effective particle size calculation formula, calculate the effective particle size of the particle size grade in the mine soil, where the effective particle size calculation formula is:

[0026] , ,

[0027] is the effective particle size of the i-th particle size grade in the mine soil, D i is the average value of the particle size interval corresponding to the i-th particle size grade, n is the total number of particle size grades, σ is the soil particle density in the mine soil screened by the particle size interval corresponding to the soil sieve of the i-th particle size grade, △Mi is the soil weight in the mine soil screened by the particle size interval corresponding to the soil sieve of the i-th particle size grade, △Di is the difference of the particle size interval corresponding to the i-th particle size grade, in is the number of soil particles remaining on the soil sieve of the i-th particle size grade, in is the difference between the soil sieve of the i-th particle size grade and the next larger soil sieve.

[0028] In the above embodiments of the present application, for example, there are currently 6 sieves (soil sieves), namely: sieves of 2000, 1000, 500, 250, 100, and 50 μm. On this basis, the interpretations of various particle size grades screened by each soil sieve are as follows: for example, through the 2000-μm sieve, the soil with a particle size greater than or equal to 2000 is screened out, that is, the particle size grade is greater than or equal to 2000. Therefore, there are a total of 7 particle size ranges. The overall process of soil screening is from the largest sieve size to the smallest, that is, starting with the 2000-μm sieve to screen out the soil with a particle size greater than or equal to 2000 μm, and then among the remaining soil with a particle size less than 2000 μm, the 1000-μm sieve is selected to screen out the soil with a particle size greater than or equal to 1000 μm and less than 2000 μm, and so on. Finally, the soil with a particle size less than 50 μm is obtained, and there are a total of 7 particle size grades, for example Figure 2 As shown specifically:

[0029] In the formula,

[0030] i represents the i-th particle size grade being calculated. That is, there are currently 7 particle size grades, namely: greater than or equal to 2000 (the 1st), greater than or equal to 1000 and less than 2000 μm (the 2nd), greater than or equal to 500 and less than 1000 μm (the 3rd), greater than or equal to 250 and less than 500 μm (the 4th), greater than or equal to 100 and less than 250 μm (the 5th), greater than or equal to 50 and less than 100 μm (the 6th), less than 50 μm (the 7th). That is, in the above formula, n represents the total number of particle size grades, which is 7.

[0031] For D i , for example, when i is 2, corresponding to the range of "greater than or equal to 1000 and less than 2000", then the average value is (1000 + 2000) / 2 = 1500. Next, regarding the calculation process of:

[0032] σ is the density of soil particles in the particle size grade of greater than or equal to 1000 and less than 2000, △Mi is the weight of the soil in the particle size grade of greater than or equal to 1000 and less than 2000, and △D i is 1000.

[0033] Specifically, ΔN represents the number of soil particles remaining on the sieve of the i-th particle size grade. This parameter reflects the distribution of soil particles within a certain particle size range and is of great significance for understanding the composition of soil particles. ΔD refers to the difference between the sieve of the i-th particle size grade and the next larger sieve. This parameter represents the size range of the sieve particle size and is an important factor to be considered when calculating the effective particle size. σ represents the density of soil particles. Density is one of the important factors affecting the physical properties of soil particles. In the calculation of the effective particle size, it is treated as a constant or known quantity and is used to convert the soil weight into the number or volume of soil particles.

[0034] Step 102: Select any particle size grade of the soil in any mining area, and obtain the spectral reflectance curves of the selected mining area soil of the selected particle size grade when it is measured by the multi-angle soil reflectance measurement device at different observation azimuth angles and different observation zenith angles. Among them, each spectral reflectance curve is composed of spectral reflectances of multiple bands. The multi-angle soil reflectance measurement device is provided with multiple observation azimuth angles and multiple observation zenith angles, and the multi-angle soil reflectance measurement device emits light based on a fixed light source zenith angle.

[0035] Next, select any particle size grade of the soil in any mining area, and obtain the spectral reflectance curves of the selected mining area soil of the selected particle size grade when it is measured by the multi-angle soil reflectance measurement device at different observation azimuth angles and different observation zenith angles. Each spectral reflectance curve is composed of spectral reflectances of multiple bands, and the band range is determined by the range of the multi-angle soil reflectance measurement device. In the above embodiment of the present application, the band range can be 350 to 2500 nm. The multi-angle soil reflectance measurement device is provided with multiple observation azimuth angles and multiple observation zenith angles, and the multi-angle soil reflectance measurement device emits light based on a fixed light source zenith angle. Specifically, when the structural column where the light source of the multi-angle soil reflectance measurement device faces the soil directly, it is the starting 0 degree.

[0036] Optionally, in step 102, the observation azimuth angles are the angles divided at preset angle intervals between 0 degrees and 360 degrees, and the observation zenith angles are the angles divided at preset angle intervals between 0 degrees and 60 degrees, and the fixed light source zenith angle is 50 degrees.

[0037] In the above embodiment of the present application, the observation azimuth angles can be, for example, 0 degrees, 30 degrees, 60 degrees, 90 degrees, 120 degrees, 150 degrees, 180 degrees, 210 degrees, 240 degrees, 270 degrees, 300 degrees, 330 degrees respectively, and the observation zenith angles can be 0 degrees, 10 degrees, 20 degrees, 30 degrees, 40 degrees, 50 degrees, 60 degrees respectively. When obtaining the spectral reflectance curve, 10 curves can be obtained at each angle, and the average is taken as the final spectral reflectance data (spectral reflectance curve) at this angle.

[0038] Step 103: Using the physical model of soil properties and the spectral reflectance curve, simulate the bidirectional reflectance spectrum of the selected mining area soil with the selected particle size grade to obtain various photometric parameters of the selected mining area soil with the selected particle size grade.

[0039] Next, use the physical model of soil properties and the spectral reflectance curve to simulate the bidirectional reflectance spectrum of the selected mining area soil with the selected particle size grade to obtain various photometric parameters of the selected mining area soil with the selected particle size grade.

[0040] Optionally, in Step 103, the physical model of soil properties is specifically as follows:

[0041] },

[0042] ,

[0043] B(g) = ,

[0044] ,

[0045] ,

[0046] ，

[0047] is the spectral reflectance curve of the selected mining area soil with the selected particle size grade, which is composed of spectral reflectances of multiple bands, is the average single scattering albedo of the surface particles of the selected mining area soil with the selected particle size grade, is the fixed light source zenith angle, is the observation zenith angle, is the observation azimuth angle, P( ) is the scattering phase function is the angle between the incident direction and the outgoing direction of the light emitted by the light source, B(g) is the backscattering function, h is the roughness parameter, is the contribution of the light emitted by the light source after multiple scattering, is the H function used to calculate the multiple scattering of the light emitted by the light source among the particles of the selected mining area soil with the selected particle size grade, x is or , is a function to explain the backward and forward scattering of the smooth surface of the selected mining area soil with the selected particle size grade, is the angle between the specular surface and the outgoing light, The first scattering phase function parameter and the second scattering phase function parameter respectively reflect the influence of the void situation between particles of the soil in the selected mining area of the selected particle size grade on the soil scattering characteristics. The third scattering phase function parameter and the fourth scattering phase function parameter respectively reflect the influence of the average distance between particles of the soil in the selected mining area of the selected particle size grade on the soil scattering characteristics. ω, h, b, b’, c and c’ are photometric parameters to be solved.

[0048] In the above embodiments of the present application, specifically, the spectral reflectance model of the soil, that is, the physical model of soil characteristics, can be constructed by using the determined soil characteristic parameters and the selected spectral reflectance curve. The physical model of soil characteristics is based on physical principles and can describe the spectral reflectance characteristics of the soil. Then, the constructed physical model of soil characteristics is run to simulate the bidirectional reflectance spectrum of the soil in the selected mining area of the selected particle size grade. The simulation process will generate a spectral reflectance curve, and various photometric parameters, such as scattering phase function parameters, average single-scattering albedo, etc., can be further extracted. In particular, the spectral reflectance data obtained by simulation can be compared with the data measured experimentally to verify the accuracy of the simulation results. If there are differences, it may be necessary to adjust the soil characteristic parameters or the spectral reflectance curve and re-run the simulation. Therefore, the physical model of soil characteristics and the spectral reflectance curve can be effectively used to simulate the bidirectional reflectance spectrum of the soil in the selected mining area of the selected particle size grade and obtain various photometric parameters, providing strong support for soil science research and related applications.

[0049] Using the physical model of soil characteristics to simulate the bidirectional reflectance spectrum can obtain the reflection characteristics of the soil at different wavelengths, different incident angles and observation angles, so as to more deeply understand the optical behavior of the soil, and further help to reveal the internal relationship between the physical characteristics such as soil particle size, composition and structure and its optical characteristics. At the same time, the photometric parameters obtained by simulation can provide important references and bases for remote sensing monitoring and soil parameter inversion. By comparing the simulation results with the actual remote sensing data, the remote sensing inversion algorithm can be verified and optimized, and the inversion accuracy of soil parameters can be improved. And soils of different particle size grades have different optical characteristics. The photometric parameters obtained by simulation can be used as important bases for soil attribute parameter inversion and mapping. Simulating the bidirectional reflectance spectrum and obtaining photometric parameters can also provide new perspectives and methods for soil science research, thus helping to reveal the change laws of the soil in the natural environment. By simulating and analyzing the optical characteristics and physical mechanisms of the soil, a scientific basis is provided for soil treatment and restoration, which helps to formulate more effective treatment plans and measures.

[0050] To this end, the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade is simulated using the physical model of soil properties and the spectral reflectance curve. The beneficial effects of various photometric parameters are manifold, including in-depth understanding of soil optical properties, optimization of remote sensing monitoring and inversion, support for inversion and mapping of soil attribute parameters, promotion of soil science research, and guidance for soil treatment and remediation, etc.

[0051] Step 104, among the various photometric parameters, determine the target photometric parameters that are of the same type as the photometric parameters related to the preset particle size inversion. Based on the target photometric parameters and the correlation relationships among the target photometric parameters, calculate the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade.

[0052] Next, among the various photometric parameters, determine the target photometric parameters that are of the same type as the photometric parameters related to the preset particle size inversion. Based on the target photometric parameters and the correlation relationships among the target photometric parameters, calculate the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade. By constructing a new mining area soil particle size inversion index, the influence of soil type on the mining area soil particle size inversion can be reduced, thereby improving the accuracy of the mining area soil particle size inversion.

[0053] Optionally, the photometric parameters related to the preset particle size inversion include the first scattering phase function parameter reflecting the influence of the void situation between particles of the selected mining area soil of the selected particle size grade on the soil scattering characteristics, as well as the second scattering phase function parameter, the roughness parameter, and the average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size grade. In step 104, for calculating the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade based on the target photometric parameters and the correlation relationships among the target photometric parameters, it specifically includes:

[0054] Step 1041, based on the correlation relationships among the target photometric parameters, construct a calculation formula for the mining area soil particle size inversion index. Based on the constructed calculation formula for the mining area soil particle size inversion index and the target photometric parameters, calculate the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade, where the calculation formula for the mining area soil particle size inversion index is:

[0055] ,

[0056] is the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade, are respectively the first scattering phase function parameter reflecting the influence of the void situation between particles of the selected mining area soil of the selected particle size grade on the soil scattering characteristics and the second scattering phase function parameter, is the roughness parameter, is the average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size grade.

[0057] Through the constructed calculation formula for the inversion index of the particle size of mine soil, the correlation relationship among the four photometric parameters is fully reflected, making the inversion of the particle size of mine soil more accurate. Specifically, when determining the correlation relationship among the target photometric parameters, the target photometric parameters required for calculating the inversion index of the particle size of the selected mine soil can be determined. These parameters include the first scattering phase function parameter reflecting the influence of the void situation between the particles of the selected mine soil of the selected particle size grade on the soil scattering characteristics, as well as the second scattering phase function parameter, the roughness parameter, and the average single-scattering albedo of the surface particles of the selected mine soil of the selected particle size grade. Then, determine the mutual influence among the parameters. For example, the scattering phase function parameter reflects the void situation between the soil particles, which affects the scattering characteristics of light; the roughness parameter is related to the soil surface porosity, soil particle composition, and soil compactness varying with depth; while the average single-scattering albedo reflects the absorption and scattering ability of the soil particles to light. Based on the above-determined content, construct the calculation formula for the inversion index of the particle size of mine soil. This formula needs to comprehensively consider all the target photometric parameters and their relationships with each other. For example, the formula may include the product of the parameters reflecting the scattering characteristics, the function value reflecting the multiple-scattering characteristics, and the coefficient reflecting the scattering albedo, etc. In particular, the initially constructed calculation formula can also be verified. By comparing the calculation results with the actual data, the accuracy and reliability of the formula can be evaluated. If there are differences, the formula needs to be adjusted and optimized to more accurately reflect the correlation relationship among the target photometric parameters.

[0058] Step 105, for the mine soil in each region, based on the inversion index of the particle size of the mine soil and the effective particle size of each particle size grade of the mine soil in each mining area, jointly invert the particle size of the soil after inversion of various particle size grades in the mining area.

[0059] Next, for the mine soil in each region, based on the inversion index of the particle size of the mine soil and the effective particle size of each particle size grade of the mine soil in each mining area, jointly invert the particle size of the soil after inversion of various particle size grades in the mining area. Through the inversion technology, the particle size distribution of various particle size grades in the mining area can be accurately obtained, providing accurate basic data for soil resource investigation, land use planning, etc. It helps to more comprehensively understand the physical properties of the mine soil and provides a scientific basis for subsequent soil management and utilization.

[0060] Therefore, jointly inverting the particle size of the soil after inversion of various particle size grades in the mining area based on the inversion index of the particle size of the mine soil and the effective particle size of each particle size grade of the mine soil in each mining area has multiple beneficial effects such as accurately obtaining the soil particle size distribution, improving the soil monitoring efficiency, supporting the ecological restoration of the mining area, optimizing the soil management decision-making, and promoting soil scientific research.

[0061] Optionally, in step 105, for the mining area soil particle size inversion index and effective particle size of each particle size grade based on the soil of each mining area, the inverted soil particle sizes of various particle size grades in the mining area are jointly inverted, specifically including:

[0062] Step 1051, based on the effective particle size corresponding to any one particle size grade of the soil in any mining area and the mining area soil particle size inversion index, determine a set of soil particle size inversion data groups.

[0063] Step 1052, based on the soil particle size inversion data groups corresponding to each particle size grade of the soil in each mining area, perform linear regression fitting to solve for the first regression parameter and the second regression parameter.

[0064] Step 1053, based on the mining area soil particle size inversion regression equation and the obtained first regression parameter and second regression parameter, obtain the inverted soil particle sizes of various particle size grades in the mining area, where the mining area soil particle size inversion regression equation is:

[0065] +B,i ,

[0066] is the inverted soil particle size of the soil of the i-th particle size grade, and B are the first regression parameter and the second regression parameter respectively, is the mining area soil particle size inversion index corresponding to the i-th particle size grade, and n is the total number of each particle size grade of the mining area soil in each region. The mining area soils in different regions may have the same or different particle size grades.

[0067] In the above embodiments of the present application, after performing linear regression fitting on the soil particle size inversion data groups corresponding to each particle size grade of the soil in each mining area to solve for the first regression parameter and the second regression parameter, the mining area soil particle size inversion regression equations in some band ranges are as follows, for example:

[0068] ,(600 - 700nm);

[0069] ,(1250 - 13500nm);

[0070] ,(2000 - 2400nm);

[0071] is the mining area soil particle size inversion regression equation in the 600 - 700nm band range, is the mining area soil particle size inversion regression equation in the 1250 - 13500nm band range, Regression equation for inverting the particle size of mine soil in the wavelength range of 2000 to 2400 nm Is the inversion index of the particle size of the mine soil

[0072] Optionally, in step 104, before determining the target photometric parameter with the same type of photometric parameter related to the preset particle size inversion among multiple photometric parameters, refer to Figure 3 As shown, it further includes

[0073] Step 106, determine the type of photometric parameter related to particle size inversion among multiple photometric parameters according to the correlation between the photometric parameter and the effective particle size, and the determination coefficient between the inversion index of the mine soil particle size and the effective particle size

[0074] Among them, step 106 further includes the following steps

[0075] Step 1061, for any particle size grade of any mine soil, among the multiple photometric parameters, calculate the correlation between each photometric parameter and the effective particle size respectively based on the correlation formula, where the correlation formula is

[0076] ,

[0077] r j Is the correlation of the j-th photometric parameter, x j Is the j-th photometric parameter, y is the effective particle size of the particle size grade, Is the mean value of the photometric parameter Is the mean value of the effective particle size

[0078] Step 1062, for any particle size grade of any mine soil, calculate the determination coefficient between the inversion index of the mine soil particle size of the particle size grade and the effective particle size based on the determination coefficient formula, where the determination coefficient formula is

[0079] ,

[0080] Is the determination coefficient of the inversion index of the mine soil particle size of the k-th particle size grade, m is the total number of inversion indexes of the mine soil particle size Is the effective particle size of the particle size grade Is the mean value of the inversion index of the mine soil particle size Is the inversion index of the mine soil particle size of the k-th particle size grade

[0081] In the above embodiments of the present application, in order to determine the types of photometric parameters related to particle size inversion, the types of photometric parameters related to particle size inversion can be determined according to the correlation between the photometric parameters and the effective particle size, as well as the determination coefficient between the particle size inversion index of the mining area soil and the effective particle size, so as to construct the calculation formula of the particle size inversion index of the mining area soil subsequently. Specifically:

[0082] Regarding the correlation, statistical methods (such as Pearson correlation coefficient) can be used to calculate the correlation between each photometric parameter and the effective particle size. The value range of the correlation is [-1, 1]. The closer the value is to 1 or -1, the stronger the linear relationship between the two; the closer the value is to 0, the weaker the linear relationship between the two.

[0083] Regarding the determination coefficient, statistical methods (such as the determination coefficient, also known as the coefficient of determination ) can be used to calculate the determination coefficient between the particle size inversion index of the mining area soil and the effective particle size. The value range of the determination coefficient is [0, 1]. The closer the value is to 1, the higher the fitting degree of the model to the data, that is, the higher the correlation between the inversion index and the effective particle size.

[0084] Finally, a comprehensive evaluation is carried out. For example, the correlation between the photometric parameter and the effective particle size, as well as the determination coefficient between the particle size inversion index of the mining area soil and the effective particle size, are comprehensively evaluated to evaluate the importance of each photometric parameter in particle size inversion. Set the target photometric parameter, and select the photometric parameter with a high correlation with the effective particle size and a high determination coefficient in the inversion model as the target photometric parameter. These parameters will be more helpful for accurately inverting the particle size distribution of the mining area soil.

[0085] By selecting the target photometric parameter, a more accurate soil particle size inversion model can be constructed to improve the inversion accuracy. Based on the target photometric parameter, a more optimized monitoring scheme for the particle size of the mining area soil can be formulated to reduce unnecessary monitoring costs and time. The accurate relationship between the photometric parameter and the soil particle size can provide a scientific basis for the management and utilization of the mining area soil and support scientific decision-making.

[0086] In a specific embodiment, it is assumed that during the measurement of the mining area soil, the relationship between other photometric parameters (such as transmittance, absorption coefficient, and roughness, etc.) and the soil particle size can be further explored to discover more types of photometric parameters that are helpful for particle size inversion.

[0087] In particular, the Sobal index can also be used to perform sensitivity analysis on the photometric parameters of the model. This index is the most efficient method for quantitatively identifying the sensitivity of different parameters. This method decomposes the total variance of the model into the effects of individual parameters and the combination of each parameter, and can obtain the sensitivity of individual parameters and the interaction between parameters:

[0088] ,

[0089] In the formula, is called the first-order sensitivity, is the second-order sensitivity, and so on. n is the total number of parameters. The total sensitivity S of the i-th parameter Tj is defined as:

[0090] .

[0091] The Sobol index is a global sensitivity analysis method. Based on the principle of variance decomposition, it decomposes the total variance of the model output into the contributions of individual parameters and their combinations. By calculating the variance contributions of each parameter and its combinations to the model output, the sensitivities of individual parameters and their interactions can be quantified. When performing sensitivity analysis using the Sobol index, the specific steps can include the following:

[0092] 1. Define the model:

[0093] Specify the input parameters (luminosity parameters in this example) and output parameters (such as soil particle size or other relevant physical quantities) of the model. Build the model to ensure that it can accurately reflect the relationship between the luminosity parameters and the output parameters.

[0094] 2. Generate samples:

[0095] Use the Sobol sequence or other efficient sampling methods to generate a sample set of the input parameters. These sample sets will be used to evaluate the output of the model under different input combinations.

[0096] 3. Run the model:

[0097] Input the generated sample set into the model to obtain the corresponding output values.

[0098] 4. Calculate the Sobol index:

[0099] Based on the model output, calculate the Sobol index for each luminosity parameter, including the first-order index (measuring the impact of an individual parameter on the output) and the higher-order index (measuring the impact of parameter combinations on the output). The calculation of the Sobol index usually involves complex mathematical derivations and numerical computations, and specialized software tools (such as the SALib library) can be used to assist in the completion.

[0100] 5. Analyze the results:

[0101] According to the calculated Sobol index, evaluate the sensitivity of each luminosity parameter to the model output. Identify the key parameters that have a greater impact on the model output and the interactions between parameters. The advantages of the Sobol index include:

[0102] Global nature: The Sobol index can consider the variations across the entire parameter space, rather than just local variations.

[0103] Decomposability: It can decompose the total variance of the model output into the contributions of individual parameters and parameter combinations, providing detailed sensitivity analysis.

[0104] Quantitativeness: By calculating specific numerical values (Sobol indices), it can quantify the sensitivity of each parameter and parameter combination.

[0105] By applying the technical solution of this embodiment, a physical model of soil properties is used to simulate the bidirectional reflectance spectrum of mine soil. Based on the fitted photometric parameters, a new inversion index of mine soil particle size is constructed, reducing the influence of soil type on the inversion of mine soil particle size, and thus improving the accuracy of mine soil particle size inversion.

[0106] Based on the above as Figure 1 and Figure 3 shown method, to achieve the above object, the embodiment of the present application also provides a computer device, specifically it can be a personal computer, a server, a network device, etc. This computer device includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to implement the above as Figure 1 and Figure 3 shown method for inverting the particle size of mine soil.

[0107] Optionally, this computer device may further include a user interface, a network interface, a camera, a radio frequency (RF) circuit, sensors, an audio circuit, a WI-FI module, etc. The user interface may include a display screen (Display), an input unit such as a keyboard (Keyboard), etc. Optionally, the user interface may further include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a Bluetooth interface, a WI-FI interface), etc.

[0108] Those skilled in the art can understand that the structure of a computer device provided in this embodiment does not constitute a limitation on this computer device, and it may include more or fewer components, or combine certain components, or have different component arrangements.

[0109] The storage medium may further include an operating system and a network communication module. The operating system is a program for managing and storing the hardware and software resources of the computer device, supporting the information processing program and the operation of other software and / or programs. The network communication module is used to implement the communication between the components inside the storage medium, as well as the communication between this entity device and other hardware and software.

[0110] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform, or can be implemented by hardware. The bidirectional reflectance spectrum of the mine area soil is simulated using the physical model of soil characteristics, and a new mine area soil particle size inversion index is constructed based on the fitted photometric parameters, reducing the influence of the mine area soil particle size inversion by the soil type, and thus improving the accuracy of the mine area soil particle size inversion.

[0111] Those skilled in the art can understand that the drawings are only schematic diagrams of a preferred implementation scenario, and the processes in the drawings are not necessarily essential for implementing the present application.

[0112] The above serial numbers of the present application are only for description and do not represent the advantages or disadvantages of the implementation scenarios. The above disclosure only shows several specific implementation scenarios of the present application. However, the present application is not limited thereto, and any changes made by those skilled in the art should fall within the protection scope of the present application.

Claims

1. A method for inverting the particle size of mine area soil, characterized in that, The method includes: Collecting mining area soils in different areas of the mining area. For the mining area soil in any area, obtaining various particle size grades of the mining area soil and the effective particle size of each particle size grade, where each mining area soil contains at least one particle size grade of soil; Selecting any particle size grade of any mining area soil, and obtaining the spectral reflectance curves of the selected mining area soil of the selected particle size grade when it is measured by a multi-angle soil reflectance measuring device at different observation azimuth angles and different observation zenith angles respectively. Each of the spectral reflectance curves is composed of spectral reflectances of multiple bands. The multi-angle soil reflectance measuring device is provided with multiple observation azimuth angles and multiple observation zenith angles, and the multi-angle soil reflectance measuring device emits light based on a fixed light source zenith angle; Using a soil characteristic physical model and the spectral reflectance curve to simulate the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade, and obtaining multiple photometric parameters of the selected mining area soil of the selected particle size grade; Among the multiple photometric parameters, determining target photometric parameters that are of the same type as the photometric parameters related to the preset particle size inversion. The photometric parameters related to the preset particle size inversion include a first scattering phase function parameter reflecting the influence of the void situation between particles of the selected mining area soil of the selected particle size grade on the soil scattering characteristics, a second scattering phase function parameter, a roughness parameter, and the average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size grade; Based on the correlation relationship between the target photometric parameters, constructing a calculation formula for the mining area soil particle size inversion index. Based on the constructed calculation formula for the mining area soil particle size inversion index and the target photometric parameters, calculating the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade. The calculation formula for the mining area soil particle size inversion index is: ， The particle size inversion index of the mining area soil for the selected mining area soil of the selected particle size grade, and The first scattering phase function parameter and the second scattering phase function parameter respectively reflecting the influence of the void situation between particles of the selected mining area soil of the selected particle size grade on the soil scattering characteristics, is the roughness parameter, is the average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size grade; For the mining area soils in each area, based on the mining area soil particle size inversion index and the effective particle size of each particle size grade of each mining area soil, jointly inversely calculating the inversed soil particle sizes of various particle size grades of soil in the mining area; 2. The method according to claim 1, characterized in that, The soil characteristic physical model is: }， ， B(g)= , ， ， ， The spectral reflectance curve of the soil in the selected mining area for the selected particle size grade, which is composed of the spectral reflectances of multiple bands, is the average single scattering albedo of the surface particles of the soil in the selected mining area for the selected particle size grade, is the fixed light source zenith angle, is the observation zenith angle, is the observation azimuth angle, P( ) is the scattering phase function is the angle between the incident direction and the outgoing direction of the light ray emitted by the light source, B(g) is the backscattering function, and h is the roughness parameter, is the contribution of the light ray emitted by the light source after multiple scattering, is the H function used to calculate the multiple scattering of the light ray emitted by the light source among the particles of the soil in the selected mining area for the selected particle size grade, and x is or , is a function to explain the backward and forward scattering of the smooth surface of the soil in the selected mining area for the selected particle size grade, is the angle between the specular surface and the outgoing light ray, are respectively the first scattering phase function parameter and the second scattering phase function parameter reflecting the influence of the void situation among the particles of the soil in the selected mining area for the selected particle size grade on the soil scattering characteristics, are respectively the third scattering phase function parameter and the fourth scattering phase function parameter reflecting the influence of the average distance between the particles of the soil in the selected mining area for the selected particle size grade on the soil scattering characteristics. ω, h, b, b’, c and c’ are the photometric parameters to be solved.

3. The method according to claim 1, wherein The jointly inversely calculating the inversed soil particle sizes of various particle size grades of soil in the mining area based on the mining area soil particle size inversion index and the effective particle size of each particle size grade of each mining area soil includes: Based on the effective particle size corresponding to any particle size grade of any mining area soil and the mining area soil particle size inversion index, determining a set of soil particle size inversion data groups; Based on the soil particle size inversion data groups corresponding to various particle size grades of each mining area soil, performing linear regression fitting to solve for the first regression parameter and the second regression parameter; Based on the mining area soil particle size inversion regression equation and the obtained first regression parameter and the second regression parameter, obtaining the inversed soil particle sizes of various particle size grades of soil in the mining area. The mining area soil particle size inversion regression equation is: +B, i , is the soil particle size after inversion for the i-th soil particle size grade, and B are the first regression parameter and the second regression parameter respectively, is the mining area soil particle size inversion index corresponding to the i-th soil particle size grade, n is the total number of each particle size grade of the mining area soil in each region, and the mining area soils in different regions contain the same or different particle size grades.

4. The method according to claim 1, wherein Before determining the target photometric parameters that are of the same type as the photometric parameters related to the preset particle size inversion among the multiple photometric parameters, the method further includes: Determine the types of photometric parameters related to particle size inversion based on the correlation between photometric parameters and effective particle size, and the determination coefficient between the particle size inversion index of mine area soil and effective particle size. Among various photometric parameters, determine the types of photometric parameters related to particle size inversion.

5. The method according to claim 4, wherein For any particle size grade of any mine area soil, among the various photometric parameters, based on the correlation calculation formula, calculate the correlation between each photometric parameter and the effective particle size respectively. The correlation calculation formula is: ， r j is the relevance of the j-th photometric parameter, x j is the j-th photometric parameter, y is the effective particle size of the particle size grade, is the mean value of the photometric parameter, is the mean value of the effective particle size.

6. The method according to claim 4, wherein For any particle size grade of any mine area soil, calculate the determination coefficient between the particle size inversion index of the mine area soil of the particle size grade and the effective particle size based on the determination coefficient calculation formula. The determination coefficient calculation formula is: ， is the coefficient of determination of the particle size inversion index of the mining area soil for the k-th particle size grade, m is the total number of particle size inversion indices of the mining area soil, is the effective particle size of the said particle size grade, is the average value of the particle size inversion index of the mining area soil, is the particle size inversion index of the mining area soil for the k-th particle size grade.

7. The method according to any one of claims 1 to 6, characterized in that, For the mine area soil in any region, different particle size grades of the mine area soil are obtained by screening based on different soil sieves of different particle size grades. During the soil screening process, the screening order of the soil sieves is in descending order of particle size grade. The soil screened by any soil sieve of a particle size grade corresponds to a particle size interval. Obtaining the effective particle size of each particle size grade includes: For any particle size grade of the mine area soil, calculate the effective particle size of the particle size grade in the mine area soil based on the effective particle size calculation formula. The effective particle size calculation formula is: ， ， is the effective particle size of the i-th particle size grade in the soil of the mining area, D i is the average value of the particle size range corresponding to the i-th particle size grade, n is the total number of particle size grades, σ is the soil particle density in the soil of the mining area screened out from the particle size range corresponding to the soil sieve of the i-th particle size grade, △Mi is the soil weight in the soil of the mining area screened out from the particle size range corresponding to the soil sieve of the i-th particle size grade, and △Di is the difference of the particle size range corresponding to the i-th particle size grade. in is the number of soil particles remaining on the soil sieve of the i-th particle size grade. in is the difference between the soil sieve of the i-th particle size grade and the next larger soil sieve.

8. The method according to claim 7, characterized in that The observation azimuth angles are angles divided at preset angle intervals between 0 degrees and 360 degrees, and the observation zenith angles are angles divided at preset angle intervals between 0 degrees and 60 degrees. The fixed light source zenith angle is 50 degrees.

9. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein, When the processor executes the computer program, it implements the method for inverting the particle size of mine area soil according to any one of claims 1 to 8.

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