Highway engineering post-ecological restoration method and system based on data analysis

Abstract

The invention provides a highway engineering post-ecological restoration method and system based on data analysis, and belongs to the technical field of ecological engineering. The method comprises the following steps: acquiring a soil sample before highway engineering construction, analyzing the soil sample by using XRF, and establishing a mapping relation between the soil sample and the concentration of each nutrient in soil; sampling a soil sample on the site after construction, and analyzing the soil sample on the site after construction by using XRF to obtain a second XRF soil data sample; and finally, carrying out nutrient analysis on the second XRF soil data sample based on the mapping relation so as to generate the highway engineering post-ecological restoration method. According to the invention, the defect of lack of research on post-ecological restoration of highway engineering in the prior art is overcome; a soil nutrient concentration analysis process is simplified by establishing a mapping relation between a soil sample and each nutrient concentration in soil; and the main component number variable in the improved plsr algorithm is associated with the incidence matrix characteristic value of the soil sample on the site before highway engineering construction, so that the analysis accuracy is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of ecological engineering, and in particular relates to a method and system for post-highway engineering ecological restoration based on data analysis. Background Art

[0002] During the construction of highway projects, it is inevitable that the soil structure and vegetation around the project will be damaged, which will lead to adverse consequences such as soil erosion, destruction of ecological balance, and potential landslides. Ecological restoration after highway projects, especially soil restoration, will help restore the micro-ecological chain in the damaged area, improve soil fixation and nutrients, and to a certain extent prevent the occurrence of geological disasters. The technology in Patent No. 2025102653439 collects soil condition data for each section of the highway construction project. The data is then analyzed to determine a sampling frequency adjustment coefficient for each sampling point. The preset sampling frequency of the current sampling point is adjusted based on the sampling frequency adjustment coefficient, and each sampling point is sampled and monitored based on the adjusted sampling frequency. The technology in Patent No. 2024113183184 first selects multiple healthy soil sampling points and calculates average healthy nutrient data. Multiple problematic sampling points are then selected and nutrient data is obtained for each of the actual sampling points. Nutrient data for multiple extended sampling points is then calculated, and average problematic nutrient data for multiple problematic planting areas is calculated based on a specific distance model. Finally, diagnostic comparison results are obtained and fertilization adjustment planning is performed. Existing technologies, such as those described above, lack direct analysis of post-construction ecological restoration methods for highway projects and typically require the development of custom models or custom parameters for soil nutrient analysis. This complex analysis process is also prone to introducing empirical biases, which can affect the analysis results. Summary of the Invention

[0003] In order to solve the above problems existing in the prior art, the present invention proposes a method and system for post-highway engineering ecological restoration based on data analysis.

[0004] To achieve the above-mentioned objectives, the present invention adopts the following technical solution: a method for post-highway engineering ecological restoration based on data analysis, comprising the following steps: step S1: obtaining soil samples from the site before highway engineering construction and performing pretreatment; step S2: using XRF (X-ray Fluorescence, X-ray fluorescence spectrometer) to analyze the soil samples from the site before highway engineering construction to obtain a first XRF soil data sample S1; step S3: establishing a mapping relationship between the first XRF soil data sample S1 and the nutrient concentration C in the soil; step S4: sampling soil samples from the site after highway engineering construction, analyzing the soil samples from the site after highway engineering construction using XRF to obtain a second XRF soil data sample S2, performing nutrient analysis on the second XRF soil data sample S2 based on the mapping relationship, and generating a post-highway engineering ecological restoration method based on the nutrient analysis results.

[0005] Furthermore, the pretreatment in step S1 includes preparing soil samples from the site before the highway construction into multiple groups of uniform powders or multiple pressed tablets.

[0006] Furthermore, the dimension of the first XRF soil data sample S1 in step S2 is the number of soil samples to be analyzed multiplied by the number of XRF energy channels.

[0007] Furthermore, the step S3 establishes a mapping relationship between the first XRF soil data sample S1 and the nutrient concentrations C in the soil, including: step S31: defining the nutrient concentrations in the soil as C in matrix form; step S32: establishing a mapping relationship C=S1×A between the first XRF soil data sample S1 and the nutrient concentrations C in the soil; wherein A represents the mapping coefficient; step S33: calculating the mean and mean square deviation of S1 and C respectively, and standardizing S1 and C based on the mean and mean square deviation to obtain S1' and C'; step S34: calculating the mapping coefficient based on S1' and C', and using the mapping coefficient as the mapping relationship.

[0008] Furthermore, the step S34 specifically includes the following sub-steps: Step S341: Construct an association matrix M of S1' and C', where M=[S1' C'] T ×[S1' C']; Step S342: Calculate the eigenvalues ​​of the association matrix M using the eig function; Step S343: Calculate the number of principal components n based on the eigenvalues ​​of the association matrix M; Step S344: Use S1', C', and n as input variables of the plsr (partial least-square regression) function, calculate the mapping coefficient A, and then use the mapping coefficient A as the mapping relationship.

[0009] Furthermore, the step S343 specifically includes the following sub-steps: step S343-1: find the eigenvalues ​​greater than 1 in the eigenvalues ​​of the association matrix M, and sum the eigenvalues ​​greater than 1 to obtain the first principal component number n1; step S343-2: construct the eigenvalue matrix DIAG of the association matrix M, calculate the first-order difference DIFF matrix of the DIAG matrix, and calculate the second principal component number n2 based on the first-order difference DIFF matrix: n2=k×(max[D1. / D2]+1), where D1 is the matrix constructed after selecting the first element to the second to last element in the first-order difference DIFF matrix, D2 is the matrix constructed after selecting the second element to the last element in the first-order difference DIFF matrix, . / represents element-by-element division, and k represents the empirical coefficient; step S343-3: take the maximum value of the first principal component number n1 and the second principal component number n2 as the principal component number n.

[0010] Furthermore, the step S344 specifically includes first inputting the variables S1′, C′ and n into the plsr function to obtain a return value BETA, and then using BETA as the mapping coefficient A.

[0011] Furthermore, in step S4, nutrient analysis is performed on the second XRF soil data sample S2 based on the mapping relationship, and a post-highway engineering ecological restoration method is generated based on the nutrient analysis results, specifically including: constructing a second XRF soil data sample S2 containing XRF energy channels and the number of soil samples to be analyzed in a matrix form, then multiplying S2 by the mapping coefficient A, and calculating the nutrient concentrations of the second XRF soil data sample S2 according to the multiplication result; and determining whether a soil conditioner needs to be added according to the relationship between the nutrient concentrations and the corresponding concentration thresholds.

[0012] The present invention also proposes a post-highway engineering ecological restoration system based on data analysis, which is used to execute the above-mentioned ecological restoration method, including a data acquisition unit, a data analysis unit and a restoration method generation unit. The data acquisition unit is connected to the data analysis unit, and the data analysis unit is connected to the restoration method generation unit. The data acquisition unit is used to obtain soil samples, the data analysis unit is used to perform nutrient analysis of soil samples on site after highway engineering construction, and the restoration method generation unit is used to generate a soil restoration method based on the results of the data analysis unit.

[0013] The beneficial technical effects of the present invention compared with the prior art are: (1) A post-highway construction ecological restoration method is proposed, which takes soil nutrients after highway construction as the analysis object, making up for the lack of research on post-highway construction ecological restoration in the existing technology; and the present invention can use portable XRF to obtain soil data samples, thereby executing the post-highway construction ecological restoration method and realizing on-site detection of soil nutrients; (2) By establishing a mapping relationship between XRF soil data samples and the concentrations of various nutrients in the soil, the concentrations of various nutrients in the soil can be intuitively associated with the soil sample data, reducing the construction, setting and use of intermediate variables or intermediate algorithm models in the soil nutrient concentration analysis process, and simplifying the soil nutrient concentration analysis process; (3) Using the improved PLSR algorithm, the principal component variables in the improved PLSR algorithm are associated with the eigenvalues ​​of the correlation matrix of the soil samples at the site before the highway construction, ensuring a balance between the retention of soil information at the site before the highway construction and the introduction of empirical bias. This allows for more accurate analysis of the soil conditions after the highway construction based on the soil properties such as structure, pH, and water content of the soil samples at the site before the highway construction, thereby improving the accuracy of the analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other implementation drawings based on the provided drawings without inventive effort.

[0015] Figure 1 This is a flow chart of a method for post-highway engineering ecological restoration based on data analysis according to the present invention; Figure 2 A flowchart for establishing a mapping relationship between a first XRF soil data sample and the concentration of each nutrient in the soil in the present invention; Figure 3 This is a flow chart of the method for calculating the mapping relationship in the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] The following first describes the concepts involved in this application with reference to the accompanying drawings. It should be noted that the following description of each concept is intended only to make the content of this application easier to understand and does not limit the scope of protection of this application. At the same time, the embodiments and features in the embodiments of this application can be combined with each other unless there is a conflict. The following detailed description of this application will be made with reference to the accompanying drawings and in conjunction with the embodiments.

[0018] In conjunction with the instructions Figure 1 The present invention proposes a post-construction ecological restoration method for highway projects based on data analysis, comprising the following steps: Step S1: obtaining soil samples from the site before the highway project construction and performing pretreatment; the source of the soil samples from the site before the highway project construction includes the soil from the temporary occupied site and the slope site before the highway project construction; the pretreatment comprises the steps of coarse grinding, fine grinding, and flattening the soil samples from the site before the highway project construction to prepare them into multiple groups of uniform powders or multiple tablets.

[0019] Step S2: Use XRF to analyze soil samples from the site before the highway project construction to obtain a first XRF soil data sample S1; the dimension of the first XRF soil data sample S1 is the number of soil samples to be analyzed multiplied by the number of XRF energy channels, and the data of the first XRF soil data sample S1 is the relative intensity of the XRF energy spectrum.

[0020] Step S3: Establish a mapping relationship between the first XRF soil data sample S1 and the nutrient concentration C in the soil; Step S4: Sampling soil samples from the site after the highway project construction, using XRF to analyze the soil samples from the site after the highway project construction to obtain a second XRF soil data sample S2, performing nutrient analysis on the second XRF soil data sample S2 based on the mapping relationship, and generating a post-highway project ecological restoration method based on the nutrient analysis results.

[0021] In conjunction with the instructions Figure 2 In step S3, a mapping relationship between the first XRF soil data sample S1 and the nutrient concentrations C in the soil is established, including: step S31: defining the nutrient concentrations in the soil as C in a matrix form, where the dimension of C can be the number of soil samples to be analyzed multiplied by the number of nutrients in the sample to be analyzed (for example, when iron and zinc need to be analyzed, the nutrient number is 2), and the data of C is the pre-determined concentration of each nutrient; step S32: establishing a mapping relationship C=S1×A between the first XRF soil data sample S1 and the nutrient concentrations C in the soil; wherein A represents a mapping coefficient, and the mapping coefficient A is a mapping coefficient matrix; step S33: calculating the mean and mean square deviation of S1 and C respectively, and standardizing S1 and C based on the mean and mean square deviation to obtain S1' and C'; wherein S1' can be equal to the mean of each element in S1 minus S1 divided by the mean square deviation, and C' can be equal to the mean of each element in C minus C divided by the mean square deviation. Step S34: Calculate mapping coefficients based on S1' and C', and use the mapping coefficients as the mapping relationship.

[0022] In conjunction with the instructions Figure 3 , the step S34 specifically includes the following sub-steps: Step S341: Construct the incidence matrix M of S1' and C', where M=[S1' C'] T×[S1' C'], the above-mentioned correlation matrix M is used to describe the cross covariance of the characteristic matrix constructed by S1' and C', which can reflect the linear correlation between S1' and C' and provide a decomposition basis for the plsr function; step S342: use the eig function to calculate the eigenvalues ​​of the correlation matrix M; it can be understood that the above-mentioned eig function is a function for calculating the eigenvalues ​​and eigenvectors of the matrix, and T represents the transpose of the matrix.

[0023] Step S343: Calculate the number of principal components n based on the eigenvalues ​​of the association matrix M; Step S344: Use S1', C' and n as input variables of the plsr function, calculate the mapping coefficient A, and then use the mapping coefficient A as the mapping relationship.

[0024] The step S343 specifically includes the following sub-steps: step S343-1: find the eigenvalues ​​greater than 1 in the eigenvalues ​​of the correlation matrix M, and sum the eigenvalues ​​greater than 1 to obtain the first principal component number n1; step S343-2: construct the eigenvalue matrix DIAG of the correlation matrix M, calculate the first-order difference DIFF matrix of the DIAG matrix, and calculate the second principal component number n2 based on the first-order difference DIFF matrix: n2=k×(max[D1. / D2]+1), where D1 is the first-order difference DIFF matrix selected. The matrix D2 is constructed from the first to the second-to-last element in the first-order difference DIFF matrix. . / represents element-by-element division, and k represents an empirical coefficient. Step S343-3: Take the maximum of the first principal component number n1 and the second principal component number n2 as the principal component number n. Step S344 specifically involves first inputting the variables S1', C', and n into the plsr function to obtain the return value BETA, which is then used as the mapping coefficient A. The first and second principal components represent different degrees of variance deviation, respectively. By comparing the first and second principal components and taking the larger value, a balance can be achieved between retaining soil information on-site before highway construction and introducing empirical bias, thereby improving the accuracy of soil nutrient analysis.

[0025] In step S4, nutrient analysis is performed on the second XRF soil data sample S2 based on the mapping relationship, and a post-highway engineering ecological restoration method is generated based on the nutrient analysis results. Specifically, the method includes: constructing the second XRF soil data sample S2 including the XRF energy channel and the number of soil samples to be analyzed in a matrix form, then multiplying S2 by the mapping coefficient A, and calculating the nutrient concentrations of the second XRF soil data sample S2 according to the multiplication result.

[0026] The above-mentioned method determines whether it is necessary to add soil conditioners based on the relationship between each nutrient concentration and the corresponding concentration threshold. Specifically, when all nutrient concentrations among the nutrient concentrations are less than the corresponding concentration threshold, a first amount of soil conditioners is added to the soil after the highway project; when one or more nutrient concentrations among the nutrient concentrations are less than the concentration threshold, a second amount of soil conditioners is added to the soil after the highway project; when all nutrient concentrations among the nutrient concentrations are greater than the corresponding concentration threshold, no soil conditioners are added to the soil after the highway project.

[0027] The present invention also proposes a post-highway engineering ecological restoration system based on data analysis, which is used to execute the above-mentioned ecological restoration method, including a data acquisition unit, a data analysis unit and a restoration method generation unit. The data acquisition unit is connected to the data analysis unit, and the data analysis unit is connected to the restoration method generation unit. The data acquisition unit is used to obtain soil samples, the data analysis unit is used to perform nutrient analysis of soil samples on site after highway engineering construction, and the restoration method generation unit is used to generate a soil restoration method based on the results of the data analysis unit.

[0028] The embodiments and / or implementation methods described above are only used to illustrate the preferred embodiments and / or implementation methods for realizing the technology of the present invention, and do not impose any form of limitation on the implementation methods of the technology of the present invention. Any person skilled in the art may make slight changes or modifications to other equivalent embodiments without departing from the scope of the technical means disclosed in the content of the present invention, but they should still be regarded as technologies or embodiments that are essentially the same as the present invention.

[0029] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. The above is only the preferred implementation method of this application. It should be pointed out that due to the limitations of textual expression, there are objectively infinite specific structures. For ordinary technicians in this technical field, without departing from the principles of this application, they can also make several improvements, modifications or changes, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes or combinations, or the direct application of the inventive concept and technical solution to other occasions without improvement, should be regarded as the scope of protection of this application.

Claims

1. A post-project ecological restoration method for highway engineering based on data analysis, characterized in that: The steps include: Step S1: obtaining soil samples from the site before highway construction and performing pretreatment; Step S2: using XRF to analyze soil samples at the site before the highway project construction to obtain a first XRF soil data sample S1; Step S3: establishing a mapping relationship between the first XRF soil data sample S1 and the nutrient concentration C in the soil; Step S4: Sampling soil samples from the site after the highway project construction, analyzing the soil samples from the site after the highway project construction using XRF to obtain a second XRF soil data sample S2, performing nutrient analysis on the second XRF soil data sample S2 based on the mapping relationship, and generating a post-highway project ecological restoration method based on the nutrient analysis results.

2. A method for post-highway engineering ecological restoration based on data analysis according to claim 1, characterized in that: The pretreatment in step S1 includes preparing soil samples from the site before the highway construction into multiple groups of uniform powders or multiple pressed tablets.

3. A method for post-highway engineering ecological restoration based on data analysis according to claim 1, characterized in that: The dimension of the first XRF soil data sample S1 in step S2 is the number of soil samples to be analyzed multiplied by the number of XRF energy channels.

4. A method for post-highway engineering ecological restoration based on data analysis according to claim 3, characterized in that: The step S3 of establishing a mapping relationship between the first XRF soil data sample S1 and the nutrient concentrations C in the soil includes: Step S31: defining the concentration of each nutrient in the soil as C in a matrix form; Step S32: establishing a mapping relationship C=S1×A between the first XRF soil data sample S1 and the nutrient concentration C in the soil; wherein A represents a mapping coefficient; Step S33: Calculate the mean and mean square error of S1 and C respectively, and standardize S1 and C based on the mean and mean square error to obtain S1' and C'; Step S34: Calculate mapping coefficients based on S1' and C', and use the mapping coefficients as the mapping relationship.

5. A method for post-highway engineering ecological restoration based on data analysis according to claim 4, characterized in that: The step S34 specifically includes the following sub-steps: Step S341: Construct the incidence matrix M of S1' and C', where M=[S1' C'] T ×[S1' C']; Step S342: Calculate the eigenvalues ​​of the incidence matrix M using the eig function; Step S343: Calculate the number of principal components n based on the eigenvalues ​​of the correlation matrix M; Step S344: Use S1', C' and n as input variables of the plsr function, calculate the mapping coefficient A, and then use the mapping coefficient A as the mapping relationship.

6. A method for post-highway engineering ecological restoration based on data analysis according to claim 5, characterized in that: The step S343 specifically includes the following sub-steps: Step S343-1: Find the eigenvalues ​​of the correlation matrix M that are greater than 1, and sum the eigenvalues ​​that are greater than 1 to obtain the first principal component number n1; Step S343-2: Construct the eigenvalue matrix DIAG of the correlation matrix M, calculate the first-order difference DIFF matrix of the DIAG matrix, and calculate the second principal component number n2 based on the first-order difference DIFF matrix: n2=k×(max[D1. / D2]+1), where D1 is the matrix constructed by selecting the first element to the second-to-last element in the first-order difference DIFF matrix, D2 is the matrix constructed by selecting the second element to the last element in the first-order difference DIFF matrix, . / represents element-by-element division, and k represents the empirical coefficient; Step S343 - 3 : Take the maximum value of the first principal component number n1 and the second principal component number n2 as the principal component number n.

7. The method for post-highway engineering ecological restoration based on data analysis according to claim 5 is characterized in that: The step S344 specifically includes first inputting the variables S1′, C′ and n into the plsr function to obtain the return value BETA, and then using BETA as the mapping coefficient A.

8. The method for post-highway engineering ecological restoration based on data analysis according to claim 5 is characterized in that: In step S4, nutrient analysis is performed on the second XRF soil data sample S2 based on the mapping relationship, and a post-highway engineering ecological restoration method is generated based on the nutrient analysis results. Specifically, the method includes: constructing the second XRF soil data sample S2 including the XRF energy channel and the number of soil samples to be analyzed in a matrix form, then multiplying S2 by the mapping coefficient A, and calculating the nutrient concentrations of the second XRF soil data sample S2 according to the multiplication result; and determining whether a soil conditioner needs to be added based on the relationship between the nutrient concentrations and the corresponding concentration thresholds.

9. A post-road engineering ecological restoration system based on data analysis, used to execute the ecological restoration method according to any one of claims 1 to 8, comprising a data acquisition unit, a data analysis unit, and a restoration method generation unit, wherein the data acquisition unit is connected to the data analysis unit, and the data analysis unit is connected to the restoration method generation unit, characterized in that: The data acquisition unit is used to acquire soil samples, the data analysis unit is used to perform nutrient analysis on soil samples at the site after highway construction, and the remediation method generation unit is used to generate a soil remediation method based on the results of the data analysis unit.

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