A soil environment monitoring data audit method and system

Abstract

The present invention relates to the field of environmental data analysis, and in particular to a soil environment monitoring data audit method and system, the method comprising the following steps: constructing a soil environment monitoring data set for a target area; conducting a pre-audit on the soil environment monitoring data set to obtain a preliminary audit result of the soil environment monitoring data set; conducting a verification audit on the soil environment monitoring data set based on the preliminary audit result to obtain a data verification audit result; and conducting a comprehensive audit on the soil environment monitoring data set in combination with the preliminary audit result and the data verification audit result to complete the soil environment monitoring data audit. The present invention constructs a soil environment monitoring data set, deeply analyzes the accuracy and consistency of the soil environment monitoring data through pre-audit and verification audit, and conducts a comprehensive audit to improve the accuracy and credibility of the audit results, thereby providing solid technical support for the scientific audit of soil environment monitoring data and soil environmental governance.

Description

Technical Field

[0001] The present invention relates to the field of environmental data analysis, and in particular to a soil environment monitoring data auditing method and system. Background Art

[0002] With the accelerated advancement of industrialization and urbanization, soil pollution is becoming increasingly serious, posing a serious threat to the ecological environment and human health. In order to effectively monitor and evaluate soil environmental quality, a soil environmental monitoring system should be established. Through regular or irregular monitoring activities, a large amount of soil environmental monitoring data should be collected. The accuracy and reliability of the data are directly related to subsequent environmental protection decisions and soil governance. Therefore, it is particularly important to strictly review the soil environmental monitoring data.

[0003] Traditional soil environmental monitoring data review methods mainly rely on manual review, which requires a lot of time and human resource costs and is easily affected by human factors, making it difficult to ensure the accuracy and fairness of soil environmental monitoring data review results. With the rapid development of modern information technology, big data, cloud computing and artificial intelligence technologies have gradually been widely used, providing new technical means and solutions for soil environmental monitoring data review.

[0004] The soil environmental monitoring data audit method and system based on modern information technology achieves preliminary audit and quality assessment of soil environmental monitoring data by constructing an intelligent data quality assessment model; further verifies and audits the soil monitoring data to achieve data verification and assessment; and constructs an audit knowledge base to conduct a comprehensive audit of soil monitoring data; thereby ensuring the accuracy and reliability of soil monitoring data, providing scientific data support for soil environmental protection decision-making, and promoting the widespread application and development of modern information technology in the field of environmental data analysis. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a soil environment monitoring data audit method and system.

[0006] In order to achieve the above-mentioned purpose, in the first aspect, the present invention provides a method for reviewing soil environment monitoring data, which includes the following steps: constructing a soil environment monitoring data set for a target area; conducting a pre-review of the soil environment monitoring data set to obtain a preliminary review result of the soil environment monitoring data set; conducting a verification review of the soil environment monitoring data set based on the preliminary review result to obtain a data verification review result; conducting a comprehensive review of the soil environment monitoring data set in combination with the preliminary review result and the data verification review result, thereby completing the review of the soil environment monitoring data. The present invention constructs a soil environment monitoring data set to provide data support for soil environmental protection and governance; verifies the reliability of the soil environment monitoring data set through a pre-review; conducts a verification review of the monitoring data based on the preliminary review result, deeply examines the accuracy and consistency of the data, and effectively reduces the risk of data errors; conducts a comprehensive review in combination with the preliminary review and the data verification review, thereby improving the accuracy and credibility of the soil environment monitoring data and providing an effective data basis for scientific assessment, reasonable planning, and effective governance of the soil environment.

[0007] Optionally, constructing the soil environment monitoring data set for the target area includes: obtaining soil environment monitoring data for the target area; performing data preprocessing on the soil environment monitoring data to obtain standard soil environment monitoring data for the target area; and performing data fusion on the standard soil environment monitoring data to obtain the soil environment monitoring data set for the target area. The present invention obtains soil environment monitoring data for the target area and converts it into standard data through data preprocessing, thereby improving the comparability and accuracy of the data; utilizes data fusion to integrate multi-dimensional soil environment monitoring data to obtain a comprehensive and integrated soil environment monitoring data set; and enhances the representativeness and integrity of the monitoring data, providing data support for subsequent data analysis and review of soil environment monitoring data, and providing comprehensive data support for soil environment protection decision-making.

[0008] Optionally, obtaining soil environmental monitoring data for the target area includes: constructing a soil sampling and monitoring plan for the target area, the soil sampling and monitoring plan including sampling locations, sampling depth, and sampling frequency; and sampling and monitoring the target area based on the soil sampling and monitoring plan to obtain the soil environmental monitoring data. The present invention rationally constructs a soil sampling and monitoring plan to ensure that sampling locations are comprehensive, sampling depths, and sampling frequencies are appropriately set, effectively improving the representativeness and accuracy of soil environmental monitoring data. The soil environmental monitoring data obtained based on the soil sampling and monitoring plan covers soil physical property data, soil chemical property data, and soil biological property data for the target area, providing detailed data support for a comprehensive review of soil environmental monitoring data. This helps to promptly identify soil environmental problems and provides a reference basis for formulating targeted soil protection measures.

[0009] Optionally, the pre-auditing of the soil environment monitoring data set to obtain a preliminary audit result of the soil environment monitoring data set includes: constructing a data quality assessment model for the soil environment monitoring data set; and performing a data quality assessment on the soil environment monitoring data set based on the data quality assessment model to obtain a preliminary audit result. The present invention constructs a data quality assessment model to provide a systematic quality assessment model for soil environment monitoring data. Performing data quality assessment based on the data quality assessment model can comprehensively identify anomalies in the data and obtain preliminary audit results. This ensures the accuracy and reliability of subsequent audits of the soil environment monitoring data and improves the efficiency of the audit of the soil environment monitoring data.

[0010] Optionally, constructing the data quality assessment model for the soil environment monitoring dataset includes: establishing audit and assessment content for the data quality assessment, wherein the audit and assessment content includes data integrity, data accuracy, and data standardization; constructing the data quality assessment model based on the audit and assessment content and in combination with the soil environment monitoring dataset, wherein the data quality assessment model includes:

[0011]

[0012] in, is the data quality assessment indicator, Represents function modeling, To fuse data, is the weight coefficient of the data integrity score, is the data integrity score, is the weight coefficient of the data accuracy score, is the data accuracy score, is the weight coefficient of the data standardization score, The data standardization score. By defining data integrity, data accuracy, and data standardization as audit and evaluation criteria, this paper provides clear standards and a basis for constructing a data quality assessment model. This model can comprehensively and accurately measure the quality of soil environmental monitoring datasets. This enhances the systematic and scientific nature of data quality assessments, improves the reliability of data processing, and provides an important guarantee for the effective use of soil environmental monitoring data.

[0013] Optionally, the verification and audit of the soil environment monitoring data set based on the preliminary audit result to obtain a data verification and audit result includes: performing a cross-temporal and spatial consistency verification and audit on the soil environment monitoring data set to obtain a consistency verification and audit result; performing a multi-indicator correlation verification and audit on the soil environment monitoring data set to obtain a correlation verification and audit result; and constructing a data verification and audit result by combining the consistency verification and audit result with the correlation verification and audit result. By performing a cross-temporal and spatial consistency verification and a multi-indicator correlation verification on the soil environment monitoring data set, the present invention can deeply discover potential problems in the data, thereby ensuring the consistency and rationality of the data, constructing a data verification and audit result, and providing an effective reference basis for the comprehensive audit of soil environment monitoring data; it not only improves the comprehensiveness and accuracy of data verification, but also helps to timely discover and correct data errors, providing strong support for the audit of soil environment monitoring data.

[0014] Optionally, performing a multi-indicator correlation verification audit on the soil environment monitoring dataset to obtain a correlation verification audit result includes: performing feature analysis on the soil environment monitoring dataset to obtain key soil environment monitoring indicators; and constructing a multi-indicator correlation verification model based on the key soil environment monitoring indicators and in combination with the soil environment monitoring dataset, wherein the multi-indicator correlation verification model includes:

[0015]

[0016] in, is the correlation verification indicator, and These are the data values of two key indicators of soil environmental monitoring. Indicates taking the minimum difference of key indicators of soil environment monitoring, is the correlation resolution coefficient, Indicates taking the maximum difference of key indicators of soil environment monitoring, is the weight control coefficient, and is the data mean of two key soil environment monitoring indicators; and according to the multi-indicator correlation verification model, the correlation verification audit result is obtained based on the soil environment monitoring data set. The present invention accurately identifies key indicators by performing feature analysis on the soil environment monitoring data set, providing an important basis for constructing a multi-indicator correlation verification model. The multi-indicator correlation verification model can deeply reveal the inherent connections between various indicators, thereby effectively verifying the logical consistency and rationality of the data; it enhances the pertinence and effectiveness of data verification, improves the scientific nature and accuracy of data quality assessment, and provides strong technical support for the audit of soil environment monitoring data.

[0017] Optionally, the soil environment monitoring data set is comprehensively audited in combination with the preliminary audit results and the data verification audit results to complete the soil environment monitoring data audit, including: constructing a soil environment monitoring data audit knowledge base; combining the preliminary audit results and the data verification audit results, and conducting a comprehensive audit of the soil environment monitoring data set based on the soil environment monitoring data audit knowledge base. The present invention constructs a soil environment monitoring data audit knowledge base, provides comprehensive and systematic support for the soil environment monitoring data audit, combines the preliminary audit results and the data verification audit results, and conducts a comprehensive audit of the soil environment monitoring data based on the knowledge base, which can ensure the comprehensiveness and accuracy of the data audit, improve the efficiency and scientific nature of the soil environment monitoring data audit, help to timely discover potential problems in the soil monitoring data, provide important guarantees for the audit of the soil environment monitoring data, and enhance the reliability of the soil environment monitoring data.

[0018] Optionally, the construction of the soil environment monitoring data audit knowledge base includes: establishing comprehensive audit standards for the soil environment monitoring data set; and constructing the soil environment monitoring data audit knowledge base based on the comprehensive audit standards in combination with the soil environment monitoring data set. The present invention establishes comprehensive audit standards for the soil environment monitoring data set, providing clear and unified guiding principles for data audit work, and constructs a data audit knowledge base in combination with the data set, which not only systematically organizes audit-related professional knowledge, but also ensures the consistency and standardization of the audit process; improves the efficiency and accuracy of data audit, provides a solid foundation for the audit of soil environment monitoring data, and helps to ensure the reliability and application value of the data.

[0019] In a second aspect, the present invention provides a soil environment monitoring data audit system that implements the soil environment monitoring data audit method provided by the present invention. The system includes an input device, an output device, a processor, and a memory. The advantages of the system are that the hardware facilities integrated by the present invention have excellent performance, the input device, the output device, the processor, and the memory are interconnected, and information is smoothly transmitted between the various components. Through the interaction of multiple hardware facilities, an efficient information processing system is constructed. The soil environment monitoring data audit system provided by the present invention constructs an efficient information processing platform by integrating high-performance hardware facilities. The system not only improves the speed and efficiency of data auditing, but also enhances the stability and reliability of data processing. The various hardware facilities work together to make the entire audit method process smoother, providing strong hardware facility support for the accurate audit of soil environment monitoring data. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of a soil environment monitoring data audit method according to an embodiment of the present invention;

[0021] Figure 2 This is a framework diagram of a soil environment monitoring data audit system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] Specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the present invention. In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that these specific details are not necessarily required to practice the present invention. In other instances, well-known circuits, software, or methods are not specifically described to avoid obscuring the present invention.

[0023] Throughout this specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present invention. Therefore, appearances of the phrases "in one embodiment," "in an embodiment," "an example," or "an example" in various places throughout this specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics may be combined in any suitable combinations and / or subcombinations in one or more embodiments or examples. Furthermore, those of ordinary skill in the art will appreciate that the figures provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0024] See Figure 1 An embodiment of the present invention provides a soil environment monitoring data audit method and system, the method comprising the following steps:

[0025] S1. Construct a soil environmental monitoring dataset for the target area.

[0026] Among them, S1 specifically includes the following steps:

[0027] S11. Acquire soil environment monitoring data of the target area.

[0028] S11 specifically includes the following steps:

[0029] S111 , constructing a soil sampling and monitoring plan for the target area, wherein the soil sampling and monitoring plan includes sampling locations, sampling depths, and sampling frequencies.

[0030] Specifically, the sampling locations are determined. First, a detailed survey of the target area is conducted to understand the soil type, topography, and land use, so that representative sampling locations can be selected. Next, the number of sampling locations is determined based on the size of the plot, the degree of soil variability, and the monitoring objectives. This ensures that the sampling locations are evenly distributed and can fully reflect the soil characteristics. When arranging the sampling locations, human interference and the influence of special terrain must be avoided to improve the representativeness of the samples. Finally, the number of each sampling location and the surrounding environmental information must be clearly defined to provide accurate guidance for subsequent sampling work. This ensures that the sampling locations are scientific, reasonable, and practical.

[0031] Specifically, the sampling depth is determined; first, the soil characteristics of the target area are clarified, including the distribution of crop roots and soil profile layers; then, a reasonable sampling depth range is preliminarily set according to monitoring needs; then, through field investigations and soil profile analysis, a comprehensive analysis of soil pollution or variation is conducted, and the sampling depth is further verified and adjusted, and it is evaluated whether the background point sampling depth meets the technical requirements of the occurrence layer sampling to ensure the pertinence and accuracy of the sampling depth, so that it can cover key soil layers and reflect the true status of soil quality.

[0032] Specifically, the sampling frequency is determined; first, the monitoring objectives are clarified; then, the sampling frequency is preliminarily set by comprehensively considering changes in environmental conditions, soil self-purification capacity, and seasonal climate changes; then, through historical data analysis and on-site inspections, adjustments are made based on actual conditions; at the same time, the monitoring cycle and timeliness factors are considered to ensure that the sampling frequency meets the monitoring requirements while being economical and operational, and finally the sampling frequency is determined.

[0033] It should be noted that when sampling is not possible on site or the sampling site cannot be reached, it is determined whether offset sampling or postponed sampling is needed; in addition, when there are obvious problems with the standardization of the sampling operation, which affects the quality of soil monitoring data, the sampling is deemed invalid; including but not limited to incorrect sampling depth, sampling location within the quality control range but in the wrong area such as near a highway or enterprise, or sampling on agricultural land shortly after fertilization and pesticide spraying; in addition, the sampling location adjustment complies with relevant requirements, the sampling operation is standardized, and the sampling is deemed valid; if there are special weather influences such as rainfall, typhoons, floods, etc. during the sampling period, which cannot be avoided within the prescribed sampling period, and the sampling operation is standardized, the sampling is deemed valid.

[0034] S112: Sampling and monitoring the target area based on the soil sampling and monitoring plan to obtain the soil environment monitoring data.

[0035] In this embodiment, according to the soil sampling monitoring plan, soil sampling equipment is used to sample the target area to obtain soil samples, and impurities in the soil samples are removed to facilitate physical, chemical and biological analysis of the soil samples.

[0036] Specifically, the physical properties data of the soil are obtained through physical analysis methods, and the natural moisture content and maximum water absorption capacity of the soil samples are determined using the drying method; the bulk density and density of the soil samples are also determined; and the particle composition and content of the soil samples are determined using the screening method.

[0037] Specifically, the chemical properties of the soil are obtained through chemical analysis methods, and the pH of the soil samples is determined using electrochemical analysis methods; the organic matter composition and content of the soil samples are determined through spectral analysis methods, and the pollutant composition and content in the soil samples are analyzed.

[0038] Specifically, biological property data of the soil are obtained through bioanalysis methods, the composition of the microbial community in the soil samples is analyzed using molecular biology techniques, and the enzyme activity in the soil samples is measured to evaluate the biological quality of the soil.

[0039] It should be noted that relevant test analysis must be carried out within the effective storage period of the soil sample to ensure the stability and accuracy of the test results. When the soil sample does not meet the analysis requirements, resampling is required.

[0040] S12. Preprocess the soil environment monitoring data to obtain soil environment monitoring standard data for the target area.

[0041] In this embodiment, anomaly detection is performed on the soil environment monitoring data, outliers that are obviously beyond the normal range are eliminated, the median of non-outlier values is used to fill the missing values, and normalization is performed. The normalization satisfies the following relationship:

[0042]

[0043] in, is the normalized standard data, For soil environmental monitoring data, is the minimum value of soil environmental monitoring data, It is the maximum value of soil environment monitoring data.

[0044] S13. Performing data fusion on the soil environment monitoring standard data to obtain a soil environment monitoring data set for the target area.

[0045] In an optional embodiment, based on the weighted average method, the normalized standard data is subjected to reliability assessment to obtain a weight coefficient, and the soil environment monitoring standard data is fused using the weight coefficient to construct a soil environment monitoring data set. The data fusion satisfies the following relationship:

[0046]

[0047] in, To fuse data, is the total amount of data, is the traversal counting flag, is the weight coefficient of the data, is the normalized standard data.

[0048] S2. Preliminary review of the soil environment monitoring dataset is performed to obtain a preliminary review result of the soil environment monitoring dataset.

[0049] Among them, S2 specifically includes the following steps:

[0050] S21. Construct a data quality assessment model for the soil environment monitoring dataset.

[0051] Among them, S21 specifically includes the following steps:

[0052] S211. Establish the audit and evaluation content of the data quality assessment, and the audit and evaluation content includes data integrity, data accuracy and data standardization.

[0053] Specifically, the audit and assessment content of data quality assessment is established, mainly including three aspects: data integrity, data accuracy and data standardization. It covers checking the filling status of all required fields to ensure that there are no omissions, comparing data with historical records or industry standards to verify accuracy, using statistical methods to detect and handle outliers, verifying the consistency of data formats and standards, and checking data synchronization, providing guidance support for the preliminary assessment and audit of data quality.

[0054] S212: Based on the audit and evaluation content, the data quality assessment model is constructed in combination with the soil environment monitoring dataset.

[0055] Specifically, according to the audit and evaluation content combined with the weight coefficient, a data quality assessment model is obtained by performing function modeling based on the fusion data of soil monitoring data. The function modeling satisfies the following relationship:

[0056]

[0057] in, is the data quality assessment indicator, Represents function modeling, To fuse data, is the weight coefficient of the data integrity score, is the data integrity score, is the weight coefficient of the data accuracy score, is the data accuracy score, is the weight coefficient of the data standardization score, is the data normalization score.

[0058] S22. Perform a data quality assessment on the soil environment monitoring dataset based on the data quality assessment model to obtain a preliminary review result.

[0059] In this embodiment, the soil environment monitoring dataset is used as the model input of the data quality assessment model, and the data integrity, data accuracy and data standardization are detected by the built-in algorithm of the data quality assessment model to obtain the audit content assessment result, thereby obtaining the data quality assessment index as the model output of the data quality assessment model.

[0060] Furthermore, preliminary audit results of soil environmental monitoring data are obtained by combining the audit content assessment results and data quality assessment indicators; the preliminary audit results include but are not limited to missing values, outliers and format errors, and corresponding improvement measures are generated, providing important reference basis for subsequent data processing, analysis and decision-making.

[0061] S3. Based on the preliminary audit result, the soil environment monitoring data set is verified and audited to obtain a data verification and audit result.

[0062] S3 specifically includes the following steps:

[0063] S31. Perform a cross-temporal and spatial consistency check on the soil environment monitoring dataset to obtain a consistency check result.

[0064] In this embodiment, the soil environment monitoring dataset is firstly temporally and spatially matched to ensure the comparability of the data in time and space. Then, a cross-temporal and spatial consistency check function is constructed to perform consistency check on the soil environment monitoring dataset to obtain a consistency check audit result. The cross-temporal and spatial consistency check function satisfies the following relationship:

[0065]

[0066] in, is an indicator of consistency across time and space, is the total amount of time consistency verification data, is the traversal counting flag, is the time consistency weight coefficient, For in time The data value on For in time The data value on is the total amount of spatial consistency check data, is the traversal counting flag, is the spatial consistency weight coefficient, For the location The data value on For the location The data value on .

[0067] S32. Perform multi-indicator correlation verification and audit on the soil environment monitoring data set to obtain a correlation verification and audit result.

[0068] Wherein, S32 specifically includes the following steps:

[0069] S321. Perform feature analysis on the soil environment monitoring data set to obtain key indicators for soil environment monitoring.

[0070] In this embodiment, statistical feature extraction is performed on a soil environment monitoring data set, and the temporal trend characteristics and spatial distribution characteristics of the soil environment monitoring data are analyzed. Then, the correlation coefficients between the various features are calculated using an algorithm embedded in the processor to obtain strongly correlated data features in the soil environment monitoring indicators. The importance of each feature is evaluated using a machine learning algorithm to obtain an importance evaluation index. The importance evaluation indexes are then sorted to obtain a sorting result. Based on the sorting result, key soil environment monitoring indicators are obtained. The key soil environment monitoring indicators include soil bulk density, organic matter composition and content, and pollutant composition and content.

[0071] S322: Based on the soil environment monitoring key indicators and in combination with the soil environment monitoring data set, a multi-indicator correlation verification model is constructed.

[0072] Specifically, the key indicators of soil environmental monitoring are used as the model input of the multi-indicator correlation verification model, and the correlation degree of the key indicators of soil environmental monitoring is used as the model output. The multi-indicator correlation verification model is constructed using the correlation verification analysis method, and the multi-indicator correlation verification model is trained using historical data to improve the accuracy and generalization ability of the model. Cross-validation is used to prevent the model from overfitting. The multi-indicator correlation verification model satisfies the following relationship:

[0073]

[0074] in, is the correlation verification indicator, and These are the data values of two key indicators of soil environmental monitoring. Indicates taking the minimum difference of key indicators of soil environment monitoring, is the correlation resolution coefficient, Indicates taking the maximum difference of key indicators of soil environment monitoring, is the weight control coefficient, and It is the data mean of two key indicators of soil environment monitoring.

[0075] S323. According to the multi-index correlation verification model, obtain the correlation verification review result based on the soil environment monitoring data set.

[0076] In this embodiment, first, the soil environment monitoring data set is input into the multi-indicator correlation verification model; then, the multi-indicator correlation verification model calculates and analyzes the correlation between each indicator according to a preset algorithm and formula, revealing the potential correlation between the key indicators of soil environment monitoring; finally, the multi-indicator correlation verification model outputs the correlation verification indicator, and then obtains the correlation verification audit result. The correlation verification audit result includes the correlation matrix, correlation coefficient or classification label between the indicators, which is used to evaluate the intrinsic correlation of the soil environment monitoring data set and provides technical support for in-depth analysis of the correlation of soil environment monitoring data.

[0077] S33. Construct a data verification and audit result by combining the consistency verification and audit result and the relevance verification and audit result.

[0078] In this embodiment, first, a comprehensive analysis is performed on the consistency check audit results and the correlation check audit results, and the temporal and spatial stability of the data revealed by the consistency check is compared with the intrinsic correlation between the indicators shown by the correlation check, so as to ensure the coherence of the data in the temporal and spatial dimensions and the logical consistency between the indicators; secondly, a weight distribution method is used to assign corresponding weights to each verification result according to its importance in the data quality assessment, so that the overall quality status of the data can be accurately reflected in the comprehensive analysis; finally, a comprehensive evaluation is performed based on the weighted sum algorithm, and the consistency check audit results and the correlation check audit results are integrated into a unified data verification audit result, which comprehensively reflects the quality status of the soil environment monitoring data set and provides a scientific basis for subsequent data use and management.

[0079] S4. Conduct a comprehensive review of the soil environment monitoring data set based on the preliminary review results and the data verification review results to complete the soil environment monitoring data review.

[0080] Among them, S4 specifically includes the following steps:

[0081] S41. Build a knowledge base for soil environmental monitoring data review.

[0082] Wherein, S41 specifically includes the following steps:

[0083] S411. Establish comprehensive review standards for the soil environment monitoring dataset.

[0084] In an optional embodiment, the authority and applicability of the comprehensive audit standards are ensured based on the industry standards and technical specifications for the audit of soil environmental monitoring data. Specific comprehensive audit standards are established based on the characteristics and requirements of soil environmental monitoring data, and the comprehensive audit standards include data range checking, outlier identification, logical consistency verification, and data rationality verification. Then, through actual operation verification and guidance from professional industry experience, the comprehensive audit standards are further revised and improved to ensure the scientific nature and operability of the comprehensive audit standards, providing comprehensive and systematic reference support for the audit work of soil environmental monitoring data sets.

[0085] S412: Combine the soil environment monitoring data set and construct the soil environment monitoring data audit knowledge base according to the comprehensive audit standard.

[0086] In this embodiment, first, according to the comprehensive audit standards, the laws and regulations, industry standards, technical specifications and audit methods related to soil environmental monitoring are sorted and classified to form a systematic knowledge framework; second, for each audit standard, its definition, calculation formula, judgment basis, common problems and solutions are recorded in detail to form specific audit knowledge points; then, using database technology, the audit knowledge points are digitally stored and structured to facilitate rapid retrieval and intelligent application; at the same time, a knowledge base update mechanism is established to regularly collect and analyze new soil environmental monitoring data audit cases, research results and technological progress, dynamically supplement and optimize the knowledge base, and provide strong knowledge base support for soil environmental monitoring data audit work.

[0087] Specifically, the soil environment monitoring data review knowledge base includes a reference range for physical and chemical project monitoring data, a reference range for heavy metal pollutant monitoring data, and a reference range for organic pollutant monitoring data.

[0088] Furthermore, physical and chemical items include pH value, organic matter and cation exchange capacity. Their reference ranges and key audit scopes are shown in Table 1:

[0089] Table 1: Reference range of physical and chemical project monitoring data

[0090]

[0091] Furthermore, referring to the Soil Environmental Quality Agricultural Land Soil Pollution Risk Control Standard (GB15618-2018), heavy metal pollutants include 8 heavy metal pollutants in GB15618: cadmium, mercury, arsenic, lead, chromium, copper, zinc, and nickel. Their reference ranges and key audit scopes are shown in Table 2:

[0092] Table 2: Reference range of heavy metal pollutant monitoring data

[0093]

[0094] Furthermore, organic pollutants refer to the total amount of BHC, DDT and benzo[a]pyrene in GB15618. Their reference ranges and key audit scopes are shown in Table 3:

[0095] Table 3: Reference range of organic pollutant monitoring data

[0096]

[0097] S42: Combine the preliminary review result and the data verification review result, and conduct a comprehensive review of the soil environment monitoring data set based on the soil environment monitoring data review knowledge base.

[0098] In this embodiment, first, the abnormal data points identified in the preliminary review are compared and analyzed with the potential errors found in the data verification review to confirm the authenticity and scope of the problem; then, based on the relevant standards and methods in the soil environment monitoring data review knowledge base, the problem data is deeply evaluated to determine whether it meets the data quality requirements; on this basis, the data with confirmed problems are corrected or eliminated according to the solutions or suggestions provided in the knowledge base; at the same time, the key information and processing decisions during the review process are recorded to form an audit report; finally, the data set that has undergone comprehensive review is organized and archived to ensure the accuracy and reliability of the soil environment monitoring data review.

[0099] Furthermore, the soil environmental monitoring data that have passed the review will be finally confirmed and integrated into the database, and the data will be managed. In addition, the sampling locations of the invalid data determined by the review in each link will be included in the re-test points, and monitoring and review work will need to be carried out again.

[0100] See Figure 2 In an optional embodiment, in order to efficiently execute the soil environment monitoring data audit method provided by the present invention, the present invention provides a soil environment monitoring data audit system, the system comprising an input device, an output device, a processor, and a memory, wherein the hardware facilities are interconnected, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to call the program instructions to execute the specific steps of the relevant embodiments of the soil environment monitoring data audit method provided by the present invention. The soil environment monitoring data audit system provided by the present invention has a complete structure, objective stability, and enhances the overall applicability and practical application capabilities of the present invention.

[0101] In summary, the method and system for reviewing soil environmental monitoring data provided by the present invention construct a comprehensive and accurate soil environmental monitoring data set, providing solid data support for the review of soil environmental monitoring data and subsequent soil environmental protection and governance work; a pre-review link is introduced to ensure the reliability of the data base by conducting preliminary verification of the soil environmental monitoring data set; subsequently, based on the preliminary review results, the monitoring data is further verified and reviewed to deeply test the accuracy and consistency of the data, thereby reducing the risk of data errors; finally, the results of the preliminary review and the data verification review are combined to conduct a comprehensive review, thereby improving the accuracy and credibility of the soil environmental monitoring data. The method of the present invention is easy to understand, simple to calculate, has a small workload, is convenient for engineering application, and provides a theoretical basis and technical support for the further development of the field of environmental data analysis.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A soil environment monitoring data audit method, characterized in that: The steps include: Construct soil environmental monitoring datasets for target areas; Preliminary review of the soil environment monitoring dataset is performed to obtain a preliminary review result of the soil environment monitoring dataset; The soil environment monitoring dataset was subjected to a cross-temporal and spatial consistency check and audit to obtain the consistency check and audit results: Performing spatiotemporal matching on the soil environment monitoring dataset, constructing a cross-spatiotemporal consistency check function to perform consistency check on the soil environment monitoring dataset to obtain the consistency check audit result, wherein the cross-spatiotemporal consistency check function includes: ； in, is an indicator of consistency across time and space, is the total amount of time consistency verification data, is the traversal counting flag, is the time consistency weight coefficient, For in time The data value on For in time The data value on is the total amount of spatial consistency check data, is the traversal counting flag, is the spatial consistency weight coefficient, For the location The data value on For the location The data value on ; The soil environment monitoring data set is subjected to a multi-index correlation verification and audit to obtain the correlation verification and audit results: Performing feature analysis on the soil environment monitoring data set to obtain key indicators of soil environment monitoring; Based on the soil environment monitoring key indicators and in combination with the soil environment monitoring data set, a multi-indicator correlation verification model is constructed, and the multi-indicator correlation verification model includes: ； in, is the correlation verification indicator, and are the data values of two key indicators of soil environmental monitoring, Indicates taking the minimum difference of key indicators of soil environment monitoring, is the correlation resolution coefficient, Indicates taking the maximum difference of key indicators of soil environment monitoring, is the weight control coefficient, and It is the mean value of the two key indicators of soil environmental monitoring; Obtaining the correlation verification review result based on the soil environment monitoring data set according to the multi-indicator correlation verification model; Combining the consistency check audit result and the relevance check audit result to construct a data check audit result; Combine the preliminary review results and the data verification review results to conduct a comprehensive review of the soil environment monitoring data set to complete the soil environment monitoring data review.

2. The soil environment monitoring data audit method according to claim 1, characterized in that: The step of constructing a soil environment monitoring dataset for a target area includes: Acquiring soil environmental monitoring data of the target area; Performing data preprocessing on the soil environment monitoring data to obtain soil environment monitoring standard data for the target area; The soil environment monitoring standard data is fused to obtain a soil environment monitoring data set for the target area.

3. The soil environment monitoring data auditing method according to claim 2, characterized in that: The obtaining of soil environment monitoring data of the target area includes: Constructing a soil sampling and monitoring plan for the target area, wherein the soil sampling and monitoring plan includes sampling locations, sampling depths, and sampling frequencies; Sampling and monitoring are performed on the target area based on the soil sampling and monitoring plan to obtain the soil environment monitoring data.

4. The soil environment monitoring data auditing method according to claim 1, characterized in that: The preliminary review of the soil environment monitoring dataset to obtain a preliminary review result of the soil environment monitoring dataset includes: Constructing a data quality assessment model for the soil environment monitoring dataset; The soil environment monitoring dataset is evaluated for data quality based on the data quality assessment model to obtain preliminary review results.

5. The soil environment monitoring data auditing method according to claim 4, characterized in that: The step of constructing a data quality assessment model for the soil environment monitoring dataset includes: Establishing the audit and assessment content of the data quality assessment, wherein the audit and assessment content includes data integrity, data accuracy and data standardization; Based on the audit and evaluation content, the data quality assessment model is constructed in combination with the soil environment monitoring data set. The data quality assessment model includes: ； in, is the data quality assessment indicator, Represents function modeling, To fuse data, is the weight coefficient of the data integrity score, is the data integrity score, is the weight coefficient of the data accuracy score, is the data accuracy score, is the weight coefficient of the data standardization score, is the data normalization score.

6. The soil environment monitoring data auditing method according to claim 1, characterized in that: The soil environment monitoring data set is comprehensively reviewed in combination with the preliminary review results and the data verification review results to complete the soil environment monitoring data review, including: Build a soil environmental monitoring data review knowledge base; Combined with the preliminary audit results and the data verification audit results, a comprehensive audit of the soil environment monitoring data set is performed based on the soil environment monitoring data audit knowledge base.

7. The soil environment monitoring data auditing method according to claim 6, characterized in that: The construction of the soil environment monitoring data review knowledge base includes: Establish comprehensive review standards for the soil environmental monitoring datasets; In combination with the soil environment monitoring data set, the soil environment monitoring data audit knowledge base is constructed according to the comprehensive audit standard.

8. A soil environment monitoring data audit system, characterized in that: The system includes an input device, an output device, a processor, and a memory, wherein the input device, the output device, the processor, and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the soil environment monitoring data review method according to any one of claims 1 to 7.

Images