A method for fast matching calculation of point accuracy

Abstract

This invention discloses a rapid point accuracy matching calculation method, comprising the following steps: ① Selecting a study area and conducting field measurements on the boundary lines of various land features within the study area to obtain phased surveying results and checkpoint data collected according to quality inspection requirements; ② Preprocessing the phased surveying results and checkpoints; ③ Based on the checkpoint data, setting the allowable range for accuracy tolerance and generating a point matching retrieval range; ④ Based on the retrieval range, performing point matching and generating an association record table; ⑤ Based on the association record table, automatically selecting matched point pairs to calculate point accuracy error; ⑥ Based on the point accuracy error calculation results, obtaining the accuracy calculation result file. This method, based on GIS spatial analysis technology, automates the cumbersome data processing and point matching process, reduces the impact of the skill level of calculation personnel on quality inspection projects, and improves quality inspection efficiency and accuracy.

Description

Technical Field

[0001] This invention belongs to the field of surveying and mapping information quality inspection technology, and specifically relates to a method for rapid matching and calculation of point accuracy. Background Technology

[0002] In urban and rural construction, land resource utilization, and environmental protection, land surveying and mapping are essential for planning and management. In geological exploration, mineral development, water conservancy, and transportation construction, control surveying, mine surveying, route surveying, and topographic mapping are necessary for geological surveys and the design and construction of various buildings. The state has formulated the standards "Quality Inspection and Acceptance of Surveying and Mapping Results" (GB / T24356-2009) and "Quality Inspection and Acceptance of Digital Surveying and Mapping Results" (GB / T18316-2008) to supervise and regulate the inspection and acceptance of surveying and mapping results.

[0003] Point accuracy is a crucial indicator of the quality of surveying and mapping results, and its calculation is a vital task in the quality inspection of these results. With the development of the national economy, the scope of geographic information is expanding, the granularity of spatial entities is becoming increasingly finer, and data volume is growing exponentially. Traditional point accuracy calculation methods typically rely on manual matching, which is time-consuming and labor-intensive. The efficiency and accuracy of these calculations are significantly affected by the skill level of the personnel performing the calculations, resulting in highly unstable reliability and a low degree of automation. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a method for rapid matching and calculation of point accuracy, which enables automated calculation of point accuracy, improves quality inspection efficiency, and lowers the barrier to entry for users.

[0005] The present invention is achieved through the following technical solutions.

[0006] This invention provides a method for rapid matching and calculation of point accuracy, comprising the following steps:

[0007] Step 1: Select the study area, conduct field measurements on the boundaries of various land features within the study area, obtain interim surveying results and checkpoint data collected according to quality inspection requirements;

[0008] Step 2: Perform data preprocessing on the phased survey results and checkpoints;

[0009] Step 3: Based on the checkpoint data, set the accuracy tolerance range and generate the point matching retrieval range;

[0010] Step 4: Based on the search range, perform location matching and generate a related record table;

[0011] Step 5: Based on the associated record table, automatically select matching point pairs to calculate the point accuracy error;

[0012] Step 6: Based on the point accuracy error calculation results, obtain the accuracy calculation result file. In Step 1, the inspection points collected according to quality inspection requirements should be evenly distributed and clearly positioned, for each image... Figure 1 Generally, 20-50 are selected from each.

[0013] In step 1, the phased surveying and mapping results data is a DWG format file, which mainly includes marker features, point features, line features, area features and polyhedral features. The marker features include unique identifiers for ground features. The checkpoint data is an EXCEL file generated by copying a DAT file.

[0014] In step 2, the preprocessing steps for the phased surveying and mapping results data are as follows: converting the phased surveying and mapping results DWG format file into a geographic database GDB, and then obtaining line feature vertex data from the database; the preprocessing steps for the checkpoint data are as follows: vectorizing the checkpoint EXCEL file into point features, and then exporting it to generate a new SHP file.

[0015] In step 3, the accuracy tolerance range is set according to relevant national and provincial technical standards. The point matching retrieval range generation step is as follows: based on the set value of the accuracy tolerance range, with the check point as the center and the set value of the accuracy tolerance range as the limit radius, the point matching retrieval range of each check point is generated.

[0016] In step 4, the specific steps of point matching are as follows: First, based on the point matching retrieval range of each checkpoint, determine whether the line feature vertices in the phased surveying results are within the point matching retrieval range of the checkpoints. If the distance between the line feature vertices in the phased surveying results and the checkpoints is less than or equal to the limit radius, then the line feature vertices are associated with the checkpoints and written into the association record table; otherwise, they are not included in the association record table. Second, based on the unique identifiers of ground features in the phased surveying results, determine whether the associated line feature vertices have the same unique identifiers as the checkpoints. If the associated line feature vertices have the same unique identifiers as the checkpoints, then the point is retained in the association record table; otherwise, the point is deleted from the association record table.

[0017] In step 5, the position accuracy error is calculated according to the following formula:

[0018]

[0019] In the formula: x1 and y1 are the coordinates of the check point, x2 and y2 are the coordinates of the inflection points of the line elements in the phased surveying results associated with the check point, and Δ is the positional accuracy error of the matching point pair.

[0020] In step 6, unnecessary fields in the associated information table are deleted, and only the checkpoint identifier and its coordinates, the inflection point identifier and its coordinates of the line elements in the associated phased surveying results, the error and accuracy error of the two points in the X and Y directions are retained, and exported as an EXCEL file.

[0021] The beneficial effects of this invention are as follows:

[0022] 1. It automatically converts data formats, eliminating the need for quality inspectors to manually process data, resulting in a high degree of automation;

[0023] 2. Automatic point matching avoids errors caused by manual matching, improving calculation efficiency and accuracy;

[0024] 3. It has good compatibility and can be used to calculate the positional accuracy of surveying products with corresponding relationships between various types of point pairs. Attached Figure Description

[0025] Figure 1 This is a flowchart of the method proposed in this invention. Detailed Implementation

[0026] The present invention will be further described in detail below through embodiments, but it should not be construed as limiting the scope of the subject matter of the present invention to the following embodiments. Any modifications, substitutions and changes made based on ordinary technical knowledge and common practices in the art without departing from the above technical concept of the present invention are included within the scope of the present invention without substantially changing the technical content.

[0027] This embodiment takes the phased surveying and mapping results quality inspection of a real estate integrated project as an example, using a village cadastral map and inspection points collected according to quality inspection requirements as input data to calculate the accuracy of the points.

[0028] This invention includes the following steps:

[0029] Step 1: Select the study area and conduct field measurements of the boundaries of various land features within the study area to obtain a cadastral map of a village and checkpoint data collected according to quality inspection requirements. The checkpoints collected according to quality inspection requirements should be evenly distributed, clearly located, and each map should contain data from checkpoints. Figure 1 Generally, 20-50 checkpoints are selected from each. The cadastral map is a DWG format file, mainly including marker features, point features, line features, polygon features, and polyhedral features. The marker features include parcel codes or building numbers. The checkpoint data is acquired using surveying instruments and copied from the DAT file to generate an EXCEL file.

[0030] Step 2: Preprocess the cadastral map and checkpoints. The cadastral map data preprocessing steps are as follows: convert the cadastral map DWG format file to a geographic database (GDB), then obtain line feature vertex data from the database. According to database requirements, two parcels sharing a boundary must maintain independent boundary points; boundary points are obtained based on line turning points. In this embodiment, the cadastral map data generated a total of 55,855 boundary points after conversion. The checkpoint data preprocessing steps are as follows: vectorize the checkpoint EXCEL file into point features, then export it to generate a new SHP file.

[0031] Step 3: Based on the checkpoint data, set the allowable range for accuracy tolerance and generate the point matching retrieval range. The allowable range for accuracy tolerance is set by quality inspectors according to relevant national and provincial technical standards such as the "Land Survey Regulations" (TD / T 1001-2012), the "Real Estate Surveying Standard" (GB / T17986-2000), and the "Technical Scheme for Real Estate Ownership Survey (Trial)". The steps for generating the point matching retrieval range are as follows: Based on the set value of the allowable range for accuracy tolerance, with the checkpoint as the center and the set value of the allowable range for accuracy tolerance as the limit radius, generate the point matching retrieval range for each checkpoint. In this embodiment, the point matching retrieval range is set to 0.4m;

[0032] Step 4: Based on the search range, perform point matching and generate an association record table. The specific steps of point matching are as follows: First, based on the point matching search range of each checkpoint, determine whether the boundary point on the cadastral map is within the point matching search range of the checkpoint. If the distance between the boundary point and the checkpoint on the cadastral map is less than or equal to the limit radius, then the boundary point is associated with the checkpoint and written into the association record table; otherwise, it is not included in the association record table. Second, based on the unique identifier of the land feature on the cadastral map, determine whether the associated boundary point has the same land parcel code or building number as the checkpoint. If the associated boundary point has the same land parcel code or building number as the checkpoint, then the point is retained in the association record table; otherwise, the point is deleted from the association record table. The association record table records the checkpoint identifier code, checkpoint coordinates, boundary point identifier code, boundary point coordinates, and the land parcel code or building number of the checkpoint and boundary point. The checkpoint identifier code and the boundary point identifier code have a one-to-many relationship.

[0033] Step 5: Based on the associated record table, automatically select matching point pairs to calculate the point accuracy error. The formula for calculating the point accuracy error is:

[0034]

[0035] In the formula: x1 and y1 are the coordinates of the check point, x2 and y2 are the coordinates of the boundary point associated with the check point, and Δ is the point position accuracy error of the matching point pair;

[0036] Step 6: Based on the point accuracy error calculation results, obtain the accuracy calculation result file. Delete unnecessary fields from the associated information table, retaining only the checkpoint identifier and its coordinates, the associated boundary point identifier and its coordinates, the errors and accuracy errors of the two points in the X and Y directions, and export it as an EXCEL file.

Claims

1. A method for rapid matching and calculation of point accuracy, characterized in that: Includes the following steps: Step 1: Select the study area, conduct field measurements on the boundaries of various land features within the study area, obtain phased surveying results and checkpoint data collected according to quality inspection requirements. The checkpoints collected according to quality inspection requirements are evenly distributed and clearly located. Step 2: Perform data preprocessing on the phased survey results and checkpoints; Step 3: Based on the checkpoint data, set the accuracy tolerance allowable range and generate the point matching retrieval range. The point matching retrieval range generation step is as follows: Based on the set value of the accuracy tolerance allowable range, take the checkpoint as the center and the set value of the accuracy tolerance allowable range as the limit radius to generate the point matching retrieval range for each checkpoint. Step 4: Based on the search range, perform point matching and generate an association record table. The specific steps of point matching are as follows: First, based on the point matching search range of each checkpoint, determine whether the line feature vertices in the phased surveying results are within the point matching search range of the checkpoints. If the distance between the line feature vertices in the phased surveying results and the checkpoints is less than or equal to the limit radius, then the line feature vertices are associated with the checkpoints and written into the association record table; otherwise, they are not included in the association record table. Second, based on the unique identifiers of ground features in the phased surveying results, determine whether the associated line feature vertices have the same unique identifiers as the checkpoints. If the associated line feature vertices have the same unique identifiers as the checkpoints, then the point is retained in the association record table; otherwise, the point is deleted from the association record table. Step 5: Based on the associated record table, automatically select matching point pairs to calculate the point accuracy error; Step 6: Based on the point accuracy error calculation results, generate an accuracy calculation result file.

2. The method for rapid matching and calculation of point accuracy according to claim 1, characterized in that: In step 1, at least twenty inspection points are selected for each image, in accordance with the quality inspection requirements.

3. The method for rapid matching and calculation of point accuracy according to claim 1, characterized in that: In step 1, the phased surveying and mapping results data is a DWG format file, which mainly includes marker features, point features, line features, area features and polyhedral features. The marker features include unique identifiers for ground features. The checkpoint data is an EXCEL file generated by copying a DAT file.

4. The method for rapid matching and calculation of point accuracy according to claim 1, characterized in that: In step 2, the preprocessing steps for the phased surveying and mapping results data are as follows: converting the phased surveying and mapping results DWG format file into a geographic database GDB, and then obtaining line feature vertex data from the database; the preprocessing steps for the checkpoint data are as follows: vectorizing the checkpoint EXCEL file into point features, and then exporting it to generate a new SHP file.

5. The method for rapid matching and calculation of point accuracy according to claim 1, characterized in that: In step 3, the allowable range of accuracy tolerance is set according to relevant national and provincial technical standards.

6. The method for rapid matching and calculation of point accuracy according to claim 1, characterized in that: In step 5, the position accuracy error is calculated according to the following formula: In the formula: , The coordinates of the checkpoint, , The coordinates of the inflection points of the centerline features in the phased survey results associated with this checkpoint. This represents the positional accuracy error of the matched point pair.

7. The method for rapid matching and calculation of point accuracy according to claim 1, characterized in that: In step 6, unnecessary fields in the associated information table are deleted, and only the checkpoint identifier and its coordinates, the inflection point identifier and its coordinates of the line elements in the associated phased surveying results, the error and accuracy error of the two points in the X and Y directions are retained, and exported as an EXCEL file.

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