Mining area soil particle size inversion method and computer equipment

Abstract

The invention relates to the technical field of mining area surface ecological environment monitoring and the technical field of computers, and discloses a mining area soil particle size inversion method and computer equipment, and the method comprises the steps: obtaining various particle size grades of mining area soil and the effective particle size of each particle size grade; obtaining a plurality of luminosity parameters of the soil in the mining area by using the soil characteristic physical model and the spectral reflectivity curve, and calculating a particle size inversion index of the soil in the mining area; and constructing a mining area soil particle size inversion regression equation based on the mining area soil particle size inversion index and the effective particle size, and performing inversion to obtain the inverted soil particle size of the mining area soil. A soil characteristic physical model is utilized to simulate a mining area soil bidirectional reflectivity spectrum, and a novel mining area soil particle size inversion index is constructed based on fitted luminosity parameters, so that the influence of soil types on mining area soil particle size inversion is reduced, and the mining area soil particle size inversion precision is improved.

Description

Technical Field

[0001] The present application relates to the fields of mining area surface ecological environment monitoring technology and computer technology, and in particular to a mining area soil particle size inversion method and computer equipment. Background Art

[0002] Particle size is a basic physical property of soil, which affects soil properties related to soil structure. Reflectance spectra can indicate the particle size of the particle surface (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 particle size is anisotropic with respect to the observation angle and illumination angle. The bidirectional reflectance distribution function (BRDF) can be used to represent this anisotropic characteristic. Studies have shown 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, the estimation accuracy of soil properties will also be affected.

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

[0004] In view of this, the present application provides a method and computer equipment for inversion of soil particle size in a mining area, which utilizes a physical model of soil characteristics to simulate the bidirectional reflectance spectrum of soil in a mining area, and constructs a new type of soil particle size inversion index for a mining area based on the fitted photometric parameters, thereby reducing the influence of soil type on the inversion of soil particle size in a mining area, thereby improving the accuracy of soil particle size inversion in a mining area.

[0005] According to one aspect of the present application, a method for inversion of soil particle size in a mining area is provided, the method comprising: Collecting mining soil from different areas within the mining area, and obtaining various particle size grades of the mining soil and the effective particle size of each particle size grade for the mining soil in any area, wherein each mining soil includes soil of at least one particle size grade; Select any particle size grade of any mining area soil, and obtain the spectral reflectance curves of the selected mining area soil of the selected particle size grade at different observation azimuths and different observation zenith angles when measured based on a multi-angle soil reflectance measuring device, wherein each spectral reflectance curve is composed of spectral reflectances of multiple bands, and the multi-angle soil reflectance measuring device is provided with multiple observation azimuths and multiple observation zenith angles, and the multi-angle soil reflectance measuring device emits light based on the zenith angle of a fixed light source; Using the soil property physical model and the spectral reflectance curve, the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade is simulated to obtain multiple photometric parameters of the selected mining area soil of the selected particle size grade; Determine a target photometric parameter of the same type as the preset particle size inversion-related photometric parameter among the plurality of photometric parameters, and calculate a mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade based on the target photometric parameter and the correlation between the target photometric parameters; For the mining area soil in each region, based on the mining area soil particle size inversion index and effective particle size of each particle size grade of each mining area soil, the inverted soil particle size of various particle size grades in the mining area is obtained through joint inversion.

[0006] 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, wherein the processor implements the above-mentioned mining area soil particle size inversion method when executing the program.

[0007] Through the above-mentioned technical scheme, the present application provides a method and computer equipment for inversion of soil particle size in a mining area, which utilizes a physical model of soil characteristics to simulate the bidirectional reflectance spectrum of soil in the mining area, and constructs a new type of soil particle size inversion index in the mining area based on the fitted photometric parameters, thereby reducing the influence of soil type on the inversion of soil particle size in the mining area, thereby improving the accuracy of soil particle size inversion in the mining area.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A schematic diagram of a process flow of a method for inverting soil particle size in a mining area provided in an embodiment of the present application is shown; Figure 2 A schematic diagram showing various particle size grades and effective particle sizes of a mining area soil provided in an embodiment of the present application is shown; Figure 3 A schematic flow chart of another method for inverting soil particle size in a mining area provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0010] 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 the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0011] In this embodiment, a method for inverting the particle size of soil in a mining area is provided. Figure 1 As shown, the method includes: Step 101, collecting mining soil from different areas in the mining area, and obtaining various particle size grades of the mining soil and the effective particle size of each particle size grade for the mining soil in any area, wherein each mining soil contains soil of at least one particle size grade.

[0012] At present, the research on the inversion of soil particle size in mining areas using reflectance spectra is mostly based on vertical observations, ignoring the bidirectional reflectance characteristics of the soil surface in mining areas. At the same time, based on the empirical relationship that soil reflectance is negatively correlated with particle size, a variety of empirical methods have been used to estimate soil particle size. However, these empirical models are highly dependent on specific data sets, greatly affected by different soil types, and lack direct connection with soil physical and chemical properties, resulting in insufficient model explanatory power. In this case, the inversion of soil particle size in mining areas is mainly based on vertical observation spectra, ignoring the non-Lambertian characteristics of the soil surface in mining areas, and the bidirectional reflectance characteristics of soil in mining areas are still unclear. In addition, the traditional empirical model is greatly affected by 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 soil particle size inversion in mining areas. At the same time, although the physical model of soil properties can explain the relationship between reflectance and soil particle size through parameters such as single scattering albedo, refractive index, and absorptivity. However, whether the physical model can better fit the bidirectional reflectance of soil in mining areas remains to be verified. Due to the influence of the complex internal components of the soil, it is difficult to estimate the particle size of different types of soil with a single photometric parameter. It is crucial to integrate multiple photometric parameters to eliminate the impact of soil type on particle size estimation and improve the accuracy of soil particle size inversion in mining areas.

[0013] In the above embodiments of the present application, the soil property physical model can be used to simulate the bidirectional reflectance spectrum of the mining area soil, and based on the fitted photometric parameters, a new type of mining area soil particle size inversion index is constructed, which reduces the influence of soil type on the mining area soil particle size inversion, thereby improving the mining area soil particle size inversion accuracy.

[0014] Specifically, the mining soil in different areas of the mining area is collected. In particular, the mining soil in different types of areas can be collected to enrich the "sample characteristics". For the mining soil in any area, various particle size grades of the mining soil and the effective particle size of each particle size grade are obtained, wherein each mining soil contains at least one particle size grade of soil, in preparation for the subsequent particle size inversion. Regarding the collection process, soil can be collected on the surface of the dump of a typical open-pit mine in arid and semi-arid areas and dried to prepare for subsequent measurements.

[0015] Optionally, for the mining soil in any region, the mining soil of different particle size grades are screened based on soil sieves of different particle size grades. In the soil screening process, the screening order of the soil sieves is from large to small in particle size grade. The soil screened by the soil sieve of any particle size grade corresponds to a particle size interval. In step 101, obtaining the effective particle size of each particle size grade specifically includes: Step 1011, for any particle size grade of the soil in the mining area, based on the effective particle size calculation formula, calculate the effective particle size of the particle size grade in the soil in the mining area, wherein the effective particle size calculation formula is: , , is the effective particle size of the i-th particle size class in the mining area 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 mining area soil screened out by the particle size interval corresponding to the soil sieve of the i-th particle size grade, △Mi is the soil weight in the mining area soil screened out by the particle size interval corresponding to the soil sieve of the i-th particle size grade, △Di is the difference in 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.

[0016] In the above embodiment of the present application, for example, there are currently 6 sieves (soil sieves), which are as follows: 2000, 1000, 500, 250, 100 and 50 μm sieves. On this basis, the interpretation of the various particle size grades screened out by each soil sieve is as follows: for example, through a 2000 μm sieve, 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. For this reason, it is equivalent to a total of 7 particle size intervals. The overall process of soil screening is from large to small according to the sieve size, that is, at the beginning, a 2000 μm sieve is used to screen out soil greater than or equal to 2000 μm, and then in the remaining soil less than 2000 μm, a 1000 μm sieve is selected to screen out soil greater than or equal to 1000 μm and less than 2000 μm, and so on. Finally, soil less than 50 μm is obtained. Finally, there are 7 particle size grades, for example Figure 2 As shown, in particular: exist In the formula, 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 first grade), greater than or equal to 1000 and less than 2000μm (the second grade), greater than or equal to 500 and less than 1000μm (the third grade), greater than or equal to 250 and less than 500μm (the fourth grade), greater than or equal to 100 and less than 250μm (the fifth grade), greater than or equal to 50 and less than 100μm (the sixth grade), and less than 50μm (the seventh grade). That is, in the above formula, n represents the total number of particle size grades, which is 7.

[0017] For D i For example, when i is 2, it corresponds to the range of "greater than or equal to 1000 and less than 2000", then the average value is (1000+2000) / 2=1500. Next, about The calculation process: σ is the density of soil particles with a particle size of 1000 or more and less than 2000, △Mi is the weight of soil with a particle size of 1000 or more and less than 2000, △D i It is 1000.

[0018] In particular, 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 important 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 range of sieve particle sizes and is an important factor to consider 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 to convert soil weight into the number or volume of soil particles.

[0019] Step 102, select any particle size grade of any mining area soil, and obtain the spectral reflectance curves of the selected mining area soil of the selected particle size grade at different observation azimuths and different observation zenith angles when measured based on a multi-angle soil reflectance measuring device, wherein each spectral reflectance curve is composed of spectral reflectances of multiple bands, and the multi-angle soil reflectance measuring device is provided with multiple observation azimuths and multiple observation zenith angles, and the multi-angle soil reflectance measuring device emits light based on the zenith angle of a fixed light source.

[0020] Next, select any particle size grade of any mining area soil, and obtain the spectral reflectance curves of the selected mining area soil of the selected particle size grade at different observation azimuths and different observation zenith angles when measured based on the multi-angle soil reflectance measuring device. 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 measuring device. In the above embodiment of the present application, the band range can be 350 to 2500nm. The multi-angle soil reflectance measuring device is provided with a plurality of observation azimuths and a plurality of observation zenith angles. The multi-angle soil reflectance measuring device emits light based on the zenith angle of a fixed light source. In particular, when the structural column where the light source of the multi-angle soil reflectance measuring device is located is directly opposite to the soil, it is the starting 0 degrees.

[0021] Optionally, in step 102, the observation azimuth angles are angles divided at preset angle intervals between 0 degrees and 360 degrees, the observation zenith angles are angles divided at preset angle intervals between 0 degrees and 60 degrees, and the fixed light source zenith angle is 50 degrees.

[0022] In the above embodiments 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, and 330 degrees, respectively, and the observation zenith angles can be 0 degrees, 10 degrees, 20 degrees, 30 degrees, 40 degrees, 50 degrees, and 60 degrees, respectively. When obtaining the spectral reflectance curve, 10 lines can be obtained for each angle and the average is taken as the final spectral reflectance data (spectral reflectance curve) of the angle.

[0023] Step 103, using the soil property physical model and the spectral reflectance curve, simulate the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade to obtain multiple photometric parameters of the selected mining area soil of the selected particle size grade.

[0024] Then, the soil property physical model and the spectral reflectance curve are used to simulate the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade, and various photometric parameters of the selected mining area soil of the selected particle size grade are obtained.

[0025] Optionally, in step 103, the soil property physical model is specifically as follows: }, , B(g)= , , , ， It is the spectral reflectance curve of the selected mining area soil of the selected particle size class, which is composed of the spectral reflectance of multiple bands. is the average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size class, To fix the zenith angle of the light source, To observe the zenith angle, is the observation azimuth, 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 light emitted by the light source when it is scattered multiple times between particles of the selected mining area soil of the selected particle size grade, and x is or , As a function of the backscattering and forward scattering of a smooth surface of a selected mining soil of a selected particle size class, is the angle between the mirror surface and the outgoing light, are respectively the first scattering phase function parameter and the second scattering phase function parameter, which reflect the influence of the inter-particle gap between the selected mining area soil of the selected particle size grade on the soil scattering characteristics. They are respectively the third scattering phase function parameter and the fourth scattering phase function parameter which reflect the influence of the average distance between particles of the selected mining area soil of the selected particle size grade on the soil scattering characteristics, and ω, h, b, b', c and c' are the photometric parameters that need to be solved.

[0026] In the above embodiment of the present application, specifically, the spectral reflectance model of the soil, i.e., the soil characteristic physical model, can be constructed using the determined soil characteristic parameters and the selected spectral reflectance curve. The soil characteristic physical model is based on physical principles and can describe the spectral reflectance characteristics of the soil. Then, the constructed soil characteristic physical model is run to simulate the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade. The simulation process will generate a spectral reflectance curve, and a variety of 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 also be compared with the experimentally measured data to verify the accuracy of the simulation results. If there is a difference, it may be necessary to adjust the soil characteristic parameters or the spectral reflectance curve and re-simulate. To this end, the soil characteristic physical model and the spectral reflectance curve can be effectively used to simulate the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade, and obtain a variety of photometric parameters, providing strong support for soil science research and related applications.

[0027] Using the physical model of soil properties to simulate the bidirectional reflectance spectrum can obtain the reflectance characteristics of soil at different wavelengths, different incident angles and observation angles, so as to have a deeper understanding of the optical behavior of soil, which in turn helps to reveal the intrinsic relationship between the physical properties of soil such as particle size, composition, structure and its optical properties. At the same time, the simulated photometric parameters can provide an important reference and basis 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 to improve the inversion accuracy of soil parameters. As well as soils of different particle size grades have different optical properties, the simulated photometric parameters can be used as an important basis 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, which helps to reveal the laws of soil changes in the natural environment. By simulating and analyzing the optical properties and physical mechanisms of soil, a scientific basis is provided for soil governance and restoration, which helps to formulate more effective governance plans and measures.

[0028] To this end, the physical model of soil properties and the spectral reflectance curves were used to simulate the bidirectional reflectance spectra of the selected mining soils of the selected particle size grades to obtain a variety of photometric parameters. The beneficial effects are multifaceted, including an in-depth understanding of soil optical properties, optimization of remote sensing monitoring and inversion, support for soil attribute parameter inversion and mapping, promotion of soil science research, and guidance for soil management and restoration.

[0029] Step 104, determining a target photometric parameter of the same type as the preset particle size inversion-related photometric parameter among a plurality of photometric parameters, and calculating a mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade based on the target photometric parameter and the correlation between the target photometric parameters.

[0030] Then, among the multiple photometric parameters, the target photometric parameters of the same type as the preset particle size inversion related photometric parameters are determined, and based on the target photometric parameters and the correlation between the target photometric parameters, the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade is calculated. By constructing a new mining area soil particle size inversion index, the influence of soil type on mining area soil particle size inversion can be reduced, thereby improving the mining area soil particle size inversion accuracy.

[0031] Optionally, the preset particle size inversion related photometric parameters include a first scattering phase function parameter reflecting the influence of the inter-particle gap of the selected mining area soil of the selected particle size grade on the soil scattering characteristics, and a second scattering phase function parameter, a roughness parameter, and an average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size grade. In step 104, based on the target photometric parameters and the correlation between the target photometric parameters, a mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade is calculated, specifically including: Step 1041, based on the correlation between each target photometric parameter, construct a mining area soil particle size inversion index calculation formula, and calculate the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade based on the constructed mining area soil particle size inversion index calculation formula and the target photometric parameter, wherein the mining area soil particle size inversion index calculation formula is: , is the mining soil particle size inversion index of the selected mining soil of the selected particle size class, are respectively the first scattering phase function parameter and the second scattering phase function parameter, which reflect the influence of the inter-particle gap between the selected mining area soil of the selected particle size grade on the soil scattering characteristics. is the roughness parameter, Average single scattering albedo of surface particles of selected mining soils of selected particle size classes.

[0032] The calculation formula of the inversion index of the soil particle size in the mining area is constructed to fully reflect the correlation between the four photometric parameters, making the inversion of the soil particle size in the mining area more accurate. Specifically, when determining the correlation between the target photometric parameters, the target photometric parameters required for the calculation of the particle size inversion index of the selected mining area soil can be clarified. These parameters include the first scattering phase function parameter that reflects the influence of the interstices between the 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. Next, the mutual influence between the parameters is determined. For example, the scattering phase function parameter reflects the interstices between the soil particles, which will affect the scattering characteristics of the light; the roughness parameter is related to the porosity of the soil surface, the composition of the soil particles and the soil compactness that varies with depth; and the average single scattering albedo reflects the absorption and scattering ability of the soil particles to the light. Based on the above-mentioned contents, the calculation formula of the inversion index of the soil particle size in the mining area is constructed. This formula needs to comprehensively consider all the target photometric parameters and their relationships with each other. For example, the formula may contain parameter products reflecting scattering characteristics, function values ​​reflecting multiple scattering characteristics, and coefficients reflecting scattering albedo. In particular, the calculation formula initially constructed 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 between the target photometric parameters.

[0033] Step 105, for the mining area soil in each region, based on the mining area soil particle size inversion index and effective particle size of each particle size grade of each mining area soil, jointly invert to obtain the inverted soil particle size of soils of various particle size grades in the mining area.

[0034] Next, for the mining soil in each region, based on the mining soil particle size inversion index and effective particle size of each particle size grade of each mining soil, the inverted soil particle size of various particle size grades in the mining area is jointly inverted. Through the inversion technology, the soil particle size distribution of various particle size grades in the mining area can be accurately obtained, providing accurate basic data for soil resource surveys, land use planning, etc. It helps to have a more comprehensive understanding of the physical properties of mining soil and provide a scientific basis for subsequent soil management and utilization.

[0035] To this end, based on the mining area soil particle size inversion index and effective particle size of each particle size grade of the soil in each mining area, the inverted soil particle size of various particle size grades in the mining area is jointly inverted to obtain the inverted soil particle size of soils of various particle size grades in the mining area, which has multiple beneficial effects such as accurately obtaining soil particle size distribution, improving soil monitoring efficiency, supporting ecological restoration of mining areas, optimizing soil management decisions, and promoting soil science research.

[0036] Optionally, in step 105, based on the mining area soil particle size inversion index and the effective particle size of each particle size grade of the soil in each mining area, the inverted soil particle size of each particle size grade in the mining area is jointly inverted to obtain the inverted soil particle size of the soil in various particle size grades in the mining area, specifically including: Step 1051, 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, determine a set of soil particle size inversion data groups.

[0037] Step 1052, based on the soil particle size inversion data set corresponding to each particle size grade of the soil in each mining area, linear regression fitting is performed to solve the first regression parameter and the second regression parameter.

[0038] Step 1053, based on the inversion regression equation of soil particle size in the mining area, and the first regression parameter and the second regression parameter obtained by solving, the inverted soil particle size of soils of various particle size grades in the mining area is obtained, wherein the inversion regression equation of soil particle size in the mining area is: +B,i , is the inverted soil particle size of the i-th particle size grade soil, and B are the first and second regression parameters respectively, is the mining area soil particle size inversion index corresponding to the i-th 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 soil in different regions contains the same or different particle size grades.

[0039] In the above embodiment of the present application, based on the soil particle size inversion data group corresponding to each particle size grade of the soil in each mining area, linear regression fitting is performed to solve the first regression parameter and the second regression parameter. The inversion regression equation of the soil particle size in the mining area within a partial band range is, for example, as follows: ,(600-700nm); ,(1250-13500nm); ,(2000-2400nm); is the inversion regression equation of soil particle size in the mining area in the 600 to 700 nm band. The inversion regression equation for the soil particle size in the mining area in the 1250 to 13500 nm band is: The inversion regression equation for the soil particle size in the mining area in the 2000 to 2400 nm band is: It is the inversion index of soil particle size in mining area.

[0040] Optionally, in step 104, before determining a target photometric parameter of the same type as the preset particle size inversion-related photometric parameter among the multiple photometric parameters, refer to Figure 3 As shown, it also includes: Step 106, according to the correlation between the photometric parameter and the effective particle size, and the determination coefficient between the mining area soil particle size inversion index and the effective particle size, determine the type of particle size inversion-related photometric parameter among a plurality of photometric parameters.

[0041] Wherein, step 106 further includes the following steps: Step 1061, for any particle size grade of soil in any mining area, among the multiple photometric parameters, based on the correlation calculation formula, respectively calculate the correlation between various photometric parameters and the effective particle size, wherein the correlation calculation formula is: , r j is the correlation of the jth photometric parameter, x j is the jth photometric parameter, y is the effective particle size of the particle size grade, is the mean value of the photometric parameters, is the mean effective particle size.

[0042] Step 1062, for any particle size grade of any mining area soil, the determination coefficient between the mining area soil particle size inversion index and the effective particle size of the particle size grade is calculated based on the determination coefficient calculation formula, wherein the determination coefficient calculation formula is: , is the determination coefficient of the k-th particle size grade of the mining area soil particle size inversion index, m is the total number of mining area soil particle size inversion indexes, is the effective particle size of the particle size grade, is the mean value of the inversion index of soil particle size in the mining area, It is the inversion index of the mining area soil particle size of the kth particle size grade.

[0043] In the above embodiment of the present application, in order to determine the type of photometric parameters related to particle size inversion, the type of photometric parameters related to particle size inversion can be determined based on the correlation between the photometric parameters and the effective particle size, and the determination coefficient between the mining area soil particle size inversion index and the effective particle size, so as to subsequently construct the calculation formula for the mining area soil particle size inversion index, specifically: For 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 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.

[0044] For the coefficient of determination, statistical methods can be used (such as the coefficient of determination, also known as the coefficient of determination ) Calculate the coefficient of determination between the inversion index of soil particle size in the mining area and the effective particle size. The range of the coefficient of determination is [0,1]. The closer the value is to 1, the higher the degree of fit of the model to the data, that is, the higher the correlation between the inversion index and the effective particle size.

[0045] Finally, a comprehensive evaluation is conducted, such as the correlation between the comprehensive photometric parameters and the effective particle size, and the determination coefficient between the mining area soil particle size inversion index and the effective particle size, to evaluate the importance of each photometric parameter in the particle size inversion. The target photometric parameters are set, and the photometric parameters with high correlation with the effective particle size and high determination coefficient in the inversion model are selected as the target photometric parameters. These parameters will be more helpful in accurately inverting the particle size distribution of the mining area soil.

[0046] By selecting the target photometric parameters, a more accurate soil particle size inversion model can be constructed to improve the inversion accuracy. Based on the target photometric parameters, a more optimized mining area soil particle size monitoring plan can be formulated to reduce unnecessary monitoring costs and time. The accurate relationship between photometric parameters and soil particle size can provide a scientific basis for mining area soil management and utilization and support scientific decision-making.

[0047] In a specific embodiment, assuming that during the soil measurement process in a mining area, the relationship between other photometric parameters (such as transmittance, absorption coefficient, roughness, etc.) and soil particle size can be further explored to discover more types of photometric parameters that are helpful for particle size inversion.

[0048] In particular, the Sobal index can also be used to perform sensitivity analysis on the model photometric parameters. 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 influence of a single parameter and the combination of each parameter, and can obtain the sensitivity of a single parameter and the interaction between parameters: , In the formula, It is called 1st sensitivity. is the second sensitivity, and so on, n is the total number of parameters, and the total sensitivity of the i-th parameter is S Tj Defined as: .

[0049] The Sobol index is a global sensitivity analysis method. It is based on the principle of variance decomposition and decomposes the total variance of the model output into the contribution of individual parameters and the combination of parameters. By calculating the variance contribution of each parameter and its combination to the model output, the sensitivity of individual parameters and the interaction between parameters can be quantified. When using the Sobol index for sensitivity analysis, the specific steps can include the following: 1. Define the model: Identify the model's input parameters (photometric parameters in this case) and output parameters (such as soil particle size or other relevant physical quantities). Build the model to ensure that it accurately reflects the relationship between the photometric parameters and the output parameters.

[0050] 2. Generate samples: Use the Sobol sequence or other efficient sampling methods to generate sample sets of input parameters. These sample sets will be used to evaluate the output of the model under different input combinations.

[0051] 3. Run the model: Input the generated sample set into the model to obtain the corresponding output value.

[0052] 4. Calculate the Sobol index: Based on the model output, the Sobol index of each photometric parameter is calculated, including the first-order index (which measures the effect of a single parameter on the output) and the higher-order index (which measures the effect of a combination of parameters on the output). The calculation of the Sobol index usually involves complex mathematical derivations and numerical calculations, which can be assisted by specialized software tools (such as the SALib library).

[0053] 5. Analysis results: The calculated Sobol index is used to evaluate the sensitivity of each photometric parameter to the model output. The key parameters that have a greater impact on the model output, as well as the interactions between the parameters, are identified. The advantages of the Sobol index include: Globality: The Sobol index is able to take into account changes in the entire parameter space, not just local changes.

[0054] Decomposition: Ability to decompose the total variance of the model output into the contributions of individual parameters and parameter combinations, providing detailed sensitivity analysis.

[0055] Quantitative: By calculating specific values ​​(Sobol index), the sensitivity of each parameter and parameter combination can be quantified.

[0056] By applying the technical solution of this embodiment, the soil property physical model is used to simulate the bidirectional reflectance spectrum of the mining area soil. Based on the fitted photometric parameters, a new type of mining area soil particle size inversion index is constructed, which reduces the influence of soil type on the mining area soil particle size inversion, thereby improving the mining area soil particle size inversion accuracy.

[0057] Based on the above Figure 1 and Figure 3 In order to achieve the above-mentioned purpose, the embodiment of the present application also provides a computer device, which can be a personal computer, a server, a network device, etc. The 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 achieve the above-mentioned Figure 1 and Figure 3 The soil particle size inversion method for the mining area is shown.

[0058] Optionally, the computer device may also include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, etc. The user interface may include a display, an input unit such as a keyboard, etc., and the optional user interface may also 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.

[0059] Those skilled in the art will appreciate that the computer device structure provided in this embodiment does not limit the computer device, and may include more or fewer components, or a combination of certain components, or different component arrangements.

[0060] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages and saves the hardware and software resources of the computer device, and supports the operation of information processing programs and other software and / or programs. The network communication module is used to realize communication between the components inside the storage medium, and communication with other hardware and software in the physical device.

[0061] Through the description of the above implementation methods, technicians in this field can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform, and can also be implemented by hardware using the physical model of soil characteristics to simulate the bidirectional reflectance spectrum of mining area soil, and based on the fitted photometric parameters, a new type of mining area soil particle size inversion index is constructed, which reduces the influence of soil type on mining area soil particle size inversion, thereby improving the accuracy of mining area soil particle size inversion.

[0062] Those skilled in the art will appreciate that the accompanying drawing is only a schematic diagram of a preferred implementation scenario, and the process in the accompanying drawing is not necessarily required for implementing the present application.

[0063] The above serial numbers of this application are only for description and do not represent the advantages and disadvantages of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of this application, but this application is not limited to them, and any changes that can be made by technicians in this field should fall within the scope of protection of this application.

Claims

1. A method for inverting soil particle size in a mining area, characterized in that: The method comprises: Collecting mining soil from different areas within the mining area, and obtaining various particle size grades of the mining soil and the effective particle size of each particle size grade for the mining soil in any area, wherein each mining soil includes soil of at least one particle size grade; Select any particle size grade of any mining area soil, and obtain the spectral reflectance curves of the selected mining area soil of the selected particle size grade at different observation azimuths and different observation zenith angles when measured based on a multi-angle soil reflectance measuring device, wherein each spectral reflectance curve is composed of spectral reflectances of multiple bands, and the multi-angle soil reflectance measuring device is provided with multiple observation azimuths and multiple observation zenith angles, and the multi-angle soil reflectance measuring device emits light based on the zenith angle of a fixed light source; Using the soil property physical model and the spectral reflectance curve, the bidirectional reflectance spectrum of the selected mining area soil of the selected particle size grade is simulated to obtain multiple photometric parameters of the selected mining area soil of the selected particle size grade; Determine a target photometric parameter of the same type as the preset particle size inversion-related photometric parameter among the plurality of photometric parameters, and calculate a mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade based on the target photometric parameter and the correlation between the target photometric parameters; For the mining area soil in each region, based on the mining area soil particle size inversion index and effective particle size of each particle size grade of each mining area soil, the inverted soil particle size of various particle size grades in the mining area is obtained through joint inversion.

2. The method according to claim 1, characterized in that: The soil property physical model is: }， ， B(g)= , ， ， ， It is the spectral reflectance curve of the selected mining area soil of the selected particle size class, which is composed of the spectral reflectance of multiple bands. is the average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size class, To fix the zenith angle of the light source, To observe the zenith angle, is the observation azimuth, 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 light emitted by the light source when it is scattered multiple times between particles of the selected mining area soil of the selected particle size grade, and x is or , As a function of the backscattering and forward scattering of a smooth surface of a selected mining soil of a selected particle size class, is the angle between the mirror surface and the outgoing light, are respectively the first scattering phase function parameter and the second scattering phase function parameter, which reflect the influence of the inter-particle gap between the selected mining area soil of the selected particle size grade on the soil scattering characteristics. They are respectively the third scattering phase function parameter and the fourth scattering phase function parameter which reflect the influence of the average distance between particles of the selected mining area soil of the selected particle size grade on the soil scattering characteristics, and ω, h, b, b', c and c' are the photometric parameters that need to be solved.

3. The method according to claim 2, characterized in that The preset particle size inversion related photometric parameters include a first scattering phase function parameter reflecting the influence of the inter-particle gap of the selected mining area soil of the selected particle size grade on the soil scattering characteristics, and a second scattering phase function parameter, a roughness parameter, and an average single scattering albedo of the surface particles of the selected mining area soil of the selected particle size grade. The calculation of 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 between the target photometric parameters includes: Based on the correlation between each target photometric parameter, a calculation formula for the inversion index of the mining area soil particle size is constructed. Based on the constructed calculation formula for the inversion index of the mining area soil particle size and the target photometric parameter, the mining area soil particle size inversion index of the selected mining area soil of the selected particle size grade is calculated, wherein the calculation formula for the inversion index of the mining area soil particle size is: ， is the mining soil particle size inversion index of the selected mining soil of the selected particle size class, and are respectively the first scattering phase function parameter and the second scattering phase function parameter, which reflect the influence of the inter-particle gap between 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 class.

4. The method according to claim 1, characterized in that The inversion index of the soil particle size of each particle size grade of each mining area soil and the effective particle size are jointly inverted to obtain the inverted soil particle size of each particle size grade of soil in the mining area, including: 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, a set of soil particle size inversion data groups is determined; Based on the soil particle size inversion data group corresponding to each particle size grade of the soil in each mining area, linear regression fitting is performed to solve the first regression parameter and the second regression parameter; Based on the inversion regression equation of soil particle size in the mining area, and the first regression parameter and the second regression parameter obtained by solving, the inverted soil particle size of soils of various particle size grades in the mining area is obtained, wherein the inversion regression equation of soil particle size in the mining area is: +B,i , is the inverted soil particle size of the i-th particle size grade soil, and B are the first and second regression parameters respectively, is the mining area soil particle size inversion index corresponding to the i-th 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 soil in different regions contains the same or different particle size grades.

5. The method according to claim 1, characterized in that: Before determining, among the plurality of photometric parameters, a target photometric parameter of the same type as the preset particle size inversion-related photometric parameter, the method further comprises: According to the correlation between photometric parameters and effective particle size, as well as the determination coefficient between the inversion index of soil particle size in mining areas and the effective particle size, the types of photometric parameters related to particle size inversion are determined among a variety of photometric parameters.

6. The method according to claim 5, characterized in that For any particle size grade of any mining area soil, among the multiple photometric parameters, the correlation between various photometric parameters and the effective particle size is calculated based on the correlation calculation formula, wherein the correlation calculation formula is: ， r j is the correlation of the jth photometric parameter, x j is the jth photometric parameter, y is the effective particle size of the particle size grade, is the mean value of the photometric parameters, is the mean effective particle size.

7. The method according to claim 5, characterized in that For any particle size grade of any mining area soil, the determination coefficient between the mining area soil particle size inversion index and the effective particle size of the particle size grade is calculated based on the determination coefficient calculation formula, wherein the determination coefficient calculation formula is: ， is the determination coefficient of the k-th particle size grade of the mining area soil particle size inversion index, m is the total number of mining area soil particle size inversion indexes, is the effective particle size of the particle size grade, is the mean value of the inversion index of soil particle size in the mining area, It is the inversion index of the mining area soil particle size of the kth particle size grade.

8. The method according to any one of claims 1 to 7, characterized in that For the mining soil in any area, the mining soil of different particle size grades is obtained by screening based on soil sieves of different particle size grades. In the soil screening process, the screening order of the soil sieve is from large to small in the order of particle size grades. The soil screened by the soil sieve of any particle size grade corresponds to a particle size interval, and the effective particle size of each particle size grade is obtained, including: For any particle size grade of the soil in the mining area, the effective particle size of the particle size grade in the soil in the mining area is calculated based on the effective particle size calculation formula, wherein the effective particle size calculation formula is: ， ， is the effective particle size of the i-th particle size class in the mining area 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 mining area soil screened out by the particle size interval corresponding to the soil sieve of the i-th particle size grade, △Mi is the soil weight in the mining area soil screened out by the particle size interval corresponding to the soil sieve of the i-th particle size grade, △Di is the difference in 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.

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

10. A computer device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that: When the processor executes the computer program, the method for inverting the soil particle size in a mining area as described in any one of claims 1 to 9 is implemented.

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