Land parcel vector boundary-oriented automatic auditing and normalizing method

Abstract

The invention discloses a parcel vector boundary-oriented automatic auditing and normalizing method, which comprises the following steps of: S1, creating a data checking root directory and two sub-directories of data and logs, and storing parcel data to be audited in a data folder; s2, developing a checking gadget based on ArcPython, reading the land block boundary data path in the S1, establishing a unified review standard library, performing automatic analysis, error identification and problem list sorting, and outputting a standardized log file; and S3, manually checking the log file corresponding to the land parcel, returning and revising data with problems, and submitting and auditing for the second time. The beneficial effects of efficient and accurate auditing, flow optimization standardization, labor cost reduction and the like are realized.

Description

Technical Field

[0001] The present invention relates to the field of land parcel boundary review, and in particular to an automated review and standardization method for land parcel vector boundaries. Background Art

[0002] In the process of soil pollution prevention and control, accurate and standardized spatial information data management of polluted plots (suspected polluted plots) is crucial. With the in-depth development of environmental protection work, although a large amount of data has been accumulated, there are many problems with the existing data. On the one hand, the spatial information of most plots is missing, and even if there is some information, it is far from meeting the actual needs in terms of accuracy, completeness and standardization. For example, when sharing information on (suspected) polluted plots between departments, information transmission is blocked due to inconsistent data formats, missing or incorrect key information; in the process of calculating the safe utilization rate of polluted plots, the calculation results are relatively biased due to insufficient data accuracy and incomplete attribute fields; when drawing the spatial distribution map required for "one map" management, it is often impossible to accurately present the actual situation of the plot due to data problems, which seriously affects the efficient promotion and scientific decision-making of soil pollution prevention and control work.

[0003] Traditional spatial vector data processing relies on manual operations, and staff need to check a large amount of land data one by one according to complex standards, such as checking whether the coordinate system (CGCS2000 coordinate system and Beijing local coordinate system) is accurate, whether the map projection and zoning (Gauss-Kruger projection, standard 3-degree zoning, Beijing uses 39-degree zoning) are compliant, whether the attribute fields (such as land name, code, area, etc.) are complete and in accordance with the prescribed format, etc. This process is not only huge in workload and time-consuming, but also manual review is easily affected by subjective factors, resulting in frequent errors, and data accuracy and standardization are difficult to guarantee, which seriously hinders the information management and sharing process in soil pollution prevention and control work, and cannot meet the growing demand for environmental protection data management and the urgent work time limit requirements, becoming a key bottleneck in the data management link of soil pollution prevention and control work.

[0004] The existing manual review of the content of plot boundary data files, coordinate systems, field information, calculation of center coordinates and area errors has many processes, low work efficiency, easy omissions, inaccurate calculation of center coordinates and area errors due to the existence of multiple map spots, and a large workload for recording erroneous information. Summary of the invention

[0005] In view of the above problems, the present invention is proposed to provide an automated review and normalization method for land parcel vector boundaries that overcomes the above problems or at least partially solves the above problems.

[0006] According to one aspect of the present invention, a method for automatic review and normalization of land parcel vector boundaries is provided, the method comprising: Step S1: Create a data check root directory and two subdirectories, data and log, and store the plot data to be reviewed in the data folder; Step S2: Develop a verification tool based on ArcPython to read the data path of the land parcel boundary in S1, establish a unified review standard library, perform automatic analysis, identify errors, sort out the problem list and output a standardized log file; Step S3: Manually check the log files corresponding to the plots, modify the problematic data and submit them for review again.

[0007] Optionally, the automatic analysis specifically includes: automatically analyzing the data from five aspects: folder, coordinate system, attribute table, center point coordinates, and plot area.

[0008] Optionally, the step S1: creating a data check root directory and two subdirectories, data and log, and storing the land parcel data to be reviewed in the data folder specifically includes: Create a root directory named Audit tool and two sub-directories named Audit_data and Audit_logs on the computer's C drive. The Audit_data directory is used to store the audit plot data, and Audit_logs is used to store dynamically generated audit log files.

[0009] Optionally, the development of a verification tool based on ArcPython, reading the data path of the land parcel boundary in S1, establishing a unified review standard library, performing automatic analysis, identifying errors, sorting out the problem list and outputting a standardized log file specifically includes: Step S201: Read the land parcel data file in the specified path; Step S202: review the file name and content; Step S203: reviewing the coordinate information of the land parcel boundary data; Step S204: reviewing the attribute field information of the land parcel boundary data; Step S205: Simplify the geographic entities of the land parcel boundary data that have passed the inspection and eliminate the multi-spot data; Step S206, calculating and verifying the center point coordinates of the land parcel boundary data; Step S207, calculating the area error of the plot boundary data; Step S208: output the log file of each audited plot boundary.

[0010] Optionally, the step S203: reviewing the coordinate information of the land parcel boundary data specifically includes: Read the coordinate system information of spatial data, and prompt the data that does not meet the verification requirements of specific coordinate system, specific map projection and zoning rules; And by calculating the polar coordinate values ​​of the plot boundary data, it is determined whether it is located within the urban area of ​​Beijing.

[0011] Optionally, the step S204 of reviewing the attribute field information of the land parcel boundary data specifically includes: Review the attribute field information of the plot boundary data, perform data integrity verification, and conduct format standardization checks on the fields, including field name, code, length, and number of decimal places. At the same time, compare the plot names and codes in the national contaminated land soil environmental management system, and prompt for erroneous field information.

[0012] Optionally, the step S205: unifying the geographic entities of the checked land parcel boundary data to eliminate the multi-spot data specifically includes: Identify the number of patches and attribute information of the land parcel boundary data, and determine the consistency between the number of patches and the row data of the attribute table; If it is detected that a plot corresponds to multiple boundary data, the plot is simplified so that its boundary data is consistent with the number of rows in the attribute table.

[0013] Optionally, the step S207 of calculating the area error of the plot boundary data specifically includes: Automatically calculate the area A of the map, read the reported area B in the national polluted land soil environmental management system, and the area C in the attribute table, and calculate the relative error (AB / AC / BC) between them. If any error is greater than 5%, an error message will be given; .

[0014] Optionally, the step S208: outputting the log file of each audited plot boundary specifically includes: The problem information identified after the review is generated into a standardized TXT text file and output to the log file directory.

[0015] The present invention provides an automatic review and standardization method for plot vector boundaries, which includes: step S1: creating a data check root directory and two subdirectories, data and log, and storing the plot data to be reviewed in the data folder; step S2: developing a verification tool based on ArcPython, reading the plot boundary data path in S1, establishing a unified review standard library, performing automatic analysis, identifying errors, sorting out the problem list and outputting a standardized log file; step S3: manually checking the log file corresponding to the plot, revising the problematic data and submitting it for review for the second time. The method achieves the beneficial effects of efficient and accurate review, standardized process optimization, and reduced labor costs.

[0016] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 A flowchart of a method for automated review and normalization of vector boundaries of plots provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0020] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0021] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0022] like Figure 1 As shown, a method for automatic review and normalization of land parcel vector boundaries includes: Step S1, create a data check root directory and two subdirectories, data and log, and store the plot data to be reviewed in the data folder; Create a root directory named Audit tool and two sub-directories named Audit_data and Audit_logs on the computer's C drive. The Audit_data directory is used to store the audit plot data, and Audit_logs is used to store dynamically generated audit log files.

[0023] Step S2: Develop a verification tool based on ArcPython, read the data path of the plot boundary in S1, establish a unified review standard library, automatically analyze the data from five aspects: folder, coordinate system, attribute table, center point coordinates, and plot area, identify errors, sort out the problem list and output a standardized log file.

[0024] Step S201: Read the plot data file in the specified path Automatically read the parcel data file in C:\Audit tool\Audit_data.

[0025] Step S202: Review file name and content Automatically check whether the folder name complies with the specifications (naming standard: current stage + (scheme number) + plot code), check whether the number of folder files meets the requirements (the number is 3 files), check whether the vector file complies with the specifications (naming standard: current stage + (scheme number) + plot code.shp), and check whether the picture complies with the specifications (naming standard: current stage + (scheme number) + plot code.jpg / png).

[0026] Step S203: Review the coordinate information of the land parcel boundary data It automatically reads the coordinate system information of spatial data, and prompts the data that does not meet the verification requirements of specific coordinate systems (CGCS2000 coordinate system and Beijing local coordinate system), specific map projections and zoning rules (Gauss-Krüger projection 3-degree zoning and Beijing 39-degree zoning); and determines whether the land boundary data is located within the urban area of ​​Beijing by calculating the pole coordinate values ​​of the land boundary data.

[0027] Step S204: Review the attribute field information of the land parcel boundary data Automatically review the attribute field information of the plot boundary data, perform data integrity verification, and perform format standardization checks on the 9 fields in Table 1 below, including field name, code, length, number of decimal places, etc. At the same time, compare the plot names and codes in the national contaminated plot soil environment management system, and prompt for incorrect field information.

[0028] Table 1

[0029] Step S205: Simplify the geographic entities of the checked land parcel boundary data and eliminate multi-spot data.

[0030] Automatically identify the number of patches and attribute information of the land parcel boundary data, and determine the consistency between the number of patches and the row data in the attribute table. If it is detected that a land parcel corresponds to multiple boundary data, the land parcel needs to be simplified so that its boundary data is consistent with the number of rows in the attribute table.

[0031] Step S206: Calculate and review the center point coordinates of the land parcel boundary data By converting the surface data of the plot boundary into point data, the longitude and latitude coordinates are automatically calculated through computational geometry, and then reviewed with the reported center point coordinate values ​​to determine whether it is within the map area.

[0032] Step S207: Calculate the area error of the plot boundary data First, the area of ​​the map (A) is automatically calculated, and the area reported in the national polluted land soil environmental management system (B) and the area filled in the attribute table (C) are read, and the relative errors between them (AB / AC / BC) are calculated respectively. If any error is greater than 5%, an error prompt will be given.

[0033]

[0034] Step S208: output the log file of each audited plot boundary.

[0035] The problem information identified after the review is generated into a standardized TXT text file and output to the log file directory.

[0036] In step S3, the log files corresponding to the plots are manually checked, and the problematic data are corrected and submitted for review again.

[0037] The staff opens the C:\Audit tool\Audit_logs file, finds the log file for the corresponding plot audit, and corrects the problems one by one. After the corrections are correct, the data file is stored again in the Audit_data directory for re-audit until it is correct.

[0038] Beneficial effects: The present invention proposes a method for automatic rapid review and standardization of plot vector boundaries and develops an audit tool based on ArcPython, which achieves the beneficial effects of efficient and accurate review, standardized process optimization, and reduced labor costs. First, the software can quickly and automatically process vector data, which greatly shortens the time compared to manual review, and can complete a large number of plot data checks in a short time. For example, for thousands of historical survey plot data, manual review may take several months, while the software can complete preliminary screening and problem sorting within a few days, and implement it according to strict standards, effectively reducing human negligence and errors, ensuring that data accuracy and standardization meet national and local standards, and providing a reliable data basis for soil pollution prevention and control. Secondly, the software has a built-in standardized processing flow to ensure that the vector boundary processing of each plot follows a unified specification, so that data from different sources are highly consistent in format and content. This helps to break down data barriers and improve the efficiency of information flow and coordination between departments and between practitioners. For example, in the regional soil pollution joint control project, data from all parties can be quickly integrated and analyzed, accelerating decision-making and implementation of measures, and promoting the efficient implementation of soil pollution prevention and control. Finally, automated processing significantly reduces reliance on professional manual review. Enterprises or management departments do not need to invest a large amount of manpower in tedious data verification work, and can reallocate human resources to more valuable environmental research and governance links. In long-term large-scale data management, it greatly reduces manpower, time and financial costs, and improves the economic benefits and sustainability of environmental protection work.

[0039] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for automatic review and normalization of plot vector boundaries, characterized in that: The audit and formalization methods include: Step S1: Create a data check root directory and two subdirectories, data and log, and store the plot data to be reviewed in the data folder; Step S2: Develop a verification tool based on ArcPython to read the data path of the land parcel boundary in S1, establish a unified review standard library, perform automatic analysis, identify errors, sort out the problem list and output a standardized log file; Step S3: Manually check the log files corresponding to the plots, modify the problematic data and submit them for review again.

2. The method for automatic review and normalization of plot vector boundaries according to claim 1, characterized in that: The automatic analysis specifically includes: automatically analyzing the data from five aspects: folder, coordinate system, attribute table, center point coordinates, and plot area.

3. The method for automatic review and normalization of land parcel vector boundaries according to claim 1, characterized in that: The step S1: creating a data check root directory and two subdirectories, data and log, and storing the land parcel data to be reviewed in the data folder specifically includes: Create a root directory named Audit tool and two sub-directories named Audit_data and Audit_logs on the computer's C drive. The Audit_data directory is used to store the audit plot data, and Audit_logs is used to store dynamically generated audit log files.

4. The method for automatic review and normalization of plot vector boundaries according to claim 1, characterized in that: The development of the verification tool based on ArcPython, reading the data path of the land parcel boundary in S1, establishing a unified review standard library, performing automatic analysis, identifying errors, sorting out the problem list and outputting a standardized log file specifically includes: Step S201: Read the land parcel data file in the specified path; Step S202: review the file name and content; Step S203: reviewing the coordinate information of the land parcel boundary data; Step S204: reviewing the attribute field information of the land parcel boundary data; Step S205: Simplify the geographic entities of the land parcel boundary data that have passed the inspection and eliminate the multi-spot data; Step S206: Calculate and review the center point coordinates of the land parcel boundary data; Step S207: Calculate the area error of the plot boundary data; Step S208: Output the log file of each audited plot boundary.

5. The method for automatic review and normalization of land parcel vector boundaries according to claim 4, characterized in that: The step S203: reviewing the coordinate information of the land parcel boundary data specifically includes: Read the coordinate system information of spatial data, and prompt the data that does not meet the verification requirements of specific coordinate system, specific map projection and zoning rules; And by calculating the polar coordinate values ​​of the plot boundary data, it is determined whether it is located within the urban area of ​​Beijing.

6. The method for automatic review and normalization of land parcel vector boundaries according to claim 4, characterized in that: The step S204 of reviewing the attribute field information of the land parcel boundary data specifically includes: Review the attribute field information of the plot boundary data, perform data integrity verification, and conduct format compliance checks on the fields, including field name, code, length, and number of decimal places. At the same time, compare the plot names and codes in the national contaminated land soil environmental management system, and provide prompts for erroneous field information.

7. The method for automatic review and normalization of land parcel vector boundaries according to claim 4, characterized in that: The step S205: unifying the geographic entities of the checked land parcel boundary data and eliminating the multi-spot data specifically includes: Identify the number of patches and attribute information of the land parcel boundary data, and determine the consistency between the number of patches and the row data of the attribute table; If it is detected that a plot corresponds to multiple boundary data, the plot is simplified so that its boundary data is consistent with the number of rows in the attribute table.

8. The method for automatic review and normalization of land parcel vector boundaries according to claim 4, characterized in that: The step S207 of calculating the area error of the plot boundary data specifically includes: First, the area A of the map is automatically calculated, and the area B reported in the national polluted land soil environmental management system and the area C filled in the attribute table are read. The relative errors between AB, AC, and BC are calculated respectively. If any error is greater than 5%, an error prompt will be given. 。 9. The method for automatic review and standardization of land parcel vector boundaries according to claim 4, characterized in that: The step S208: outputting the log file of each audited plot boundary specifically includes: The problem information identified after the review is generated into a standardized TXT text file and output to the log file directory.

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