Large-scale topographic map detection point data acquisition and database building method

Abstract

The invention discloses a large-scale topographic map detection point data acquisition and database building method, and relates to the technical field of large-scale topographic map detection point data database building, and the method comprises the following steps: respectively acquiring a plurality of detection point data, the detection point data comprising a detection point coordinate file, an acquisition registration form, a field photo and an image screenshot marked with a detection point; sorting the plurality of detection point coordinate files according to a set standard; establishing a detection point database, and arranging and importing data of a plurality of detection points into the detection point database. According to the method, the blank of large-scale topographic map position precision detection point acquisition and database building standardization such as 1: 500, 1: 1000 and 1: 2000 is filled up, a detection point database technical standard meeting the actual requirements of inspection work is established, the detection point data standard, the acquisition method standard and the database building standard are mainly researched, the technical standard of large-scale topographic map detection point acquisition and database building is established, and the technical standard of large-scale topographic map position precision detection point acquisition and database building is established. And the detection work efficiency and the detection point result reuse level are improved.

Description

Technical Field

[0001] The invention relates to the technical field of building a database of detection point data of a large-scale topographic map, and in particular to a method for collecting and building a database of detection point data of a large-scale topographic map. Background Art

[0002] Check points are the ground features and geomorphic features collected for topographic map position accuracy detection, including plane check points, elevation check points, and flat-high check points;

[0003] Plane detection points are feature points of land objects collected to detect the plane position accuracy of topographic maps; elevation detection points are feature points of land objects and landforms collected to detect the elevation accuracy of topographic maps; plane-elevation detection points are collected to detect the plane position and elevation accuracy of topographic maps, and can also be used as feature points of plane detection points and elevation detection points.

[0004] In recent years, with the continuous advancement of the construction of a new basic surveying and mapping system and the construction of a real 3D China, there is an increasing demand for the rapid acquisition and efficient management of topographic map detection points at 1:500, 1:1000, and 1:2000. The current quality inspection standards for topographic maps have made clear provisions for the number, distribution, and mathematical accuracy statistical methods of detection points, which has important guiding significance in ensuring the position accuracy of topographic maps.

[0005] At the same time, with the advent of the era of intelligent surveying and mapping, surveying and mapping quality inspection agencies, enterprises and institutions have also carried out research in the standardization of inspection points, automated measurement, and the construction of knowledge bases.

[0006] The research on the construction and application of surveying and mapping quality inspection knowledge base conducted by Huang Changdi and others made public the surveying and mapping quality inspection resource library, knowledge base construction and application research, proposed a surveying and mapping quality inspection knowledge base framework, and used the inspection points, topography, house roofs, etc. of previous years as the data sources of the mathematical precision knowledge base.

[0007] The research on the rapid detection solution of DOM for geographic national conditions monitoring disclosed the standardized arrangement of DOM detection point data, the construction and application exploration of management system by Hu Ruisheng and others, and realized the rapid detection of DOM for geographic national conditions monitoring. Building a knowledge base of surveying and mapping detection points and conducting research on automated quality inspection technology can improve the application rate of reference data, the convenience of query, the standardization of inspection processes, and the consistency of problem statements, and further improve the efficiency of quality inspection.

[0008] However, due to the variety of ways of acquiring testing points, the formats of the collected testing points are diverse. There are problems such as insufficient number of testing points, lack of image screenshot references, and incomplete information records. There are certain limitations on the scope of application of the inspection, and further standardization is needed.

[0009] Practice has proved that by building a database of test point data, establishing the organizational relationship between the original coordinate file of the test point, collecting basic information, precision information, and collecting instrument information, and by using unified numbering, the uniqueness and traceability of the test point data can be ensured, providing guarantee for the reusability of the test point results. The idea of ​​integrating test point collection, sorting, and database building has reached a consensus in the industry, but there is a lack of standards for building databases for test point data. It is urgent to formulate relevant standards to achieve the effect of technology and data sharing. Summary of the invention

[0010] In order to solve the technical problems of detection point data collection and database construction, the present invention provides a method for large-scale topographic map detection point data collection and database construction. The following technical solutions are adopted:

[0011] The method for collecting and building a database of detection point data for a large-scale topographic map includes the following steps:

[0012] Step 1: Collect data of multiple detection points respectively, the detection point data includes detection point coordinate files, collection registration forms, field photos and image screenshots with detection points marked;

[0013] Step 2, sorting out multiple detection point coordinate files according to set standards;

[0014] Step 3, establish a detection point database, and sort and import the data of multiple detection points into the detection point database;

[0015] Step 4: After data format conversion and attribute assignment, a standard detection point database is formed.

[0016] By adopting the above technical solutions, in order to adapt to the development of surveying and mapping results quality inspection technology and actual application needs, fill the gap in the standardization of 1:500, 1:1000, and 1:2000 topographic map position accuracy detection point collection and database construction, and combine the practical experience of detection point reuse, analyze and organize the existing detection point data collection indicators and technical methods, as well as similar database construction requirements, establish detection point database technical standards that meet the actual needs of inspection work, and focus on the research of detection point data standards, collection method standards, and database construction standards.

[0017] Through standard research and application, technical standards for the collection and database construction of large-scale topographic map inspection points were established, which improved the efficiency of inspection work and the level of reuse of inspection point results.

[0018] Optionally, in step 2, organizing the detection point coordinate file includes the following methods:

[0019] When using a measuring instrument to collect the coordinates of the detection points, the coordinate file is directly exported from the measuring instrument and organized into the corresponding detection point coordinate file based on the detection instrument;

[0020] If the coordinate data in the detection point coordinate file only includes plane coordinates and elevation, the plane coordinates and elevation are converted to obtain longitude and latitude coordinates. The detection point coordinate file record format is: detection point number, detection point type, latitude, longitude, geodetic height, north coordinate, east coordinate, elevation, collection date; if the local coordinate system is used, it is converted to the 2000 National Geodetic Coordinate System coordinates;

[0021] The naming format of the detection point coordinate file is: instrument number, acquisition method, central meridian, acquisition date.

[0022] When the measuring instrument is RTK, calculate the Gaussian plane coordinates, convert the longitude and latitude coordinates into Gaussian plane coordinates according to the given projection band, calculate the normal height, and convert the normal height in the HBCORS system based on the original longitude and latitude, geodetic height and instrument height;

[0023] The method of converting and obtaining normal height in the HBCORS system is to extract the detection point number, longitude and latitude, geodetic height, and instrument height of the detection point from the original detection point file, organize them into a text format that meets the online conversion requirements of the HBCORS system, upload them to the HBCORS online location service system for self-service conversion, obtain the Gaussian plane coordinates, elevation, and belt number of the detection point, and obtain the central meridian of the detection point, the Gaussian plane coordinates without belt number, and the 1985 elevation through string batch processing, and add them to the detection point coordinate file;

[0024] When the measuring instrument is a total station, the DLG detection points collected by the polar coordinate method only have plane coordinates but no longitude and latitude coordinates. The detection point number, x north coordinate, y east coordinate and elevation are extracted from the original file to form a text file, which is submitted to the HBCORS online location service system for self-service conversion to obtain the longitude and latitude coordinates and geoid height under the specified central meridian.

[0025] By adopting the above technical solution, when using a measuring instrument to collect detection points, the coordinate file should be directly exported from the measuring instrument, and organized into a detection point coordinate file with the detection instrument as the unit; when using existing results to collect detection points, the detection points collected within the scope of the existing results should be organized into a detection point coordinate file; the original data only collected plane coordinates and elevations, and coordinate conversion should be performed to obtain longitude and latitude coordinates. The detection point record format is: detection point number, detection point type, latitude, longitude, geodetic height, north coordinate, east coordinate, elevation, collection date; detection point coordinates and longitude and latitude, the unit is "degree", and the value is taken to 9 decimal places; plane coordinates, geodetic height, elevation, the unit is "meter", the value is taken to 3 decimal places, and when using the local coordinate system, it needs to be converted to the 2000 national geodetic coordinate system coordinates; the detection point coordinate file can be named in the form of "instrument number + collection method + central meridian + collection date"; the detection point coordinate file related information should be registered in the collection registration form;

[0026] Optionally, use low-altitude UAV aerial photogrammetry to collect field photos of the detection points. When collecting the field photos of the detection points, the main ground object points photographed are placed in the center of the drawing. There are position reference objects in the field photos. The shooting distance is 5m to 20m, and the resolution is not less than 1 million pixels.

[0027] Optionally, the image screenshot with the detection point marked is cropped from reference data, which includes a topographic map and a satellite image. The detection point position is marked with a clear mark, with the detection point position as the center point, and the image is cropped to a set length and width pixel size.

[0028] By adopting the above technical solution, field photos and image screenshots are organized. Field photos and image screenshots with marked detection points are stored as picture files, and folders are created by category to store pictures of different categories; the picture file name should be unique, the file name should be consistent with the detection point number, and an identification code and picture sequence number are attached. The naming rule is: "Identification code + detection point number + picture sequence number", where the field photo identification code is replaced by the letters "ZP" and the image screenshot is replaced by "YX"; the picture sequence number is serially numbered according to the number of field photos (or image screenshots) contained in each detection point, and the picture sequence number retains 2 digits, and a "0" is added in front of less than two digits.

[0029] The readability of the inspection points can be enhanced by adding field photos and image screenshots, providing accurate basis for reusing the inspection points.

[0030] Optionally, step 3 includes the following sub-steps:

[0031] Step 31, create a library, allocate physical space for each type of data, and create a detection point data table;

[0032] Step 32, data preparation, performing consistency conversion on the detection point coordinate file sorted in step 2 according to the requirements of data organization, and the consistency conversion includes code conversion, format conversion, coordinate transformation and projection conversion;

[0033] Step 33, storing the detection point spatial data and attributes in the database according to the data organization method;

[0034] Step 34, detection point file storage, the detection point file is stored in the form of a file, the folder is named according to the project name, and the detection point coordinate file, collection registration form, field photo directory and image screenshot directory are stored in sequence.

[0035] By adopting the above technical solution, the library is created. According to the requirements of database organization, physical space is allocated to each type of data, relevant parameters are set, and data tables are created. The scalability of the database should be considered when allocating physical space. The organized detection point coordinate files are converted for consistency according to the requirements of data organization, mainly including code conversion, format conversion, coordinate transformation, projection conversion, etc.

[0036] The spatial data and attributes of the detection points are stored in the database according to the data organization method. Data can be stored manually or in batches by program.

[0037] The detection point files are stored in the form of files. The folders are named according to the project name, and the detection point coordinate files, collection registration forms, field photo directories, and image screenshot directories are stored in sequence.

[0038] The data at the inspection points should be updated as needed to keep the data realistic.

[0039] Database security protection, confidentiality, and database backup and recovery should comply with the requirements of GB / T 33453.

[0040] The quality requirements of the database should meet the requirements of GB / T 33453, and at the same time meet the requirements of integrity, logical consistency, conceptual consistency, value range consistency, format consistency, attribute accuracy, etc.

[0041] Optionally, step 33 includes the following sub-steps:

[0042] Step 331, input the path information of the attachment of the detection point data, which includes the path corresponding to the screenshot and photo of the detection point, and indicates the detailed location of the detection point, using specific direction terms to describe the position relationship, and the specific direction terms are east, west, south, north, inside, outside, up, down, up and down;

[0043] The position relationship description is consistent with the position relationship between the detection point and the ground object in the photo;

[0044] Step 332, input the detection point source information;

[0045] Step 333, input the accuracy information, fill in the actual detection result scale according to the accuracy of the detection point corresponding to the surveying and mapping results, and fill in the corresponding level for the level control point;

[0046] Step 334, enter the detection point type. The detection point type is divided into detection type and detection result type. The detection type is determined according to the source and purpose of the detection point, and is marked with letter codes in the detection point record string in the detection point file, such as P for plane detection, G for elevation detection, and PG for flat-elevation detection. The detection result type is determined according to the detection type used for detection at the detection point, and the detection result type is reflected in the naming of the detection point file.

[0047] By adopting the above technical solution, the attachment path of the detection point is entered, and the detection point data is accompanied by actual photos and image screenshots. When entering the detection point, it is also necessary to enter the detection point image screenshot, the corresponding path of the photo, and indicate the detailed location of the detection point in the location description. Use words that can specifically and accurately express the position relationship, such as east, south, west, north, inside, outside, up, down, and on and off the ridge, to describe the location, which should be consistent with the location relationship between the detection point and the ground object in the photo, such as "the southwest corner of the flower bed is the landing point".

[0048] Enter the source information of the detection points. The source information of the detection points includes information such as the collection date, which can be extracted from the collection registration form; the project number is based on the station's annual inspection and acceptance project number, and is supplemented and entered during the database construction process. Projects with report numbers are numbered according to the 4-digit year + 3-digit report sequence number, and projects without project report numbers are numbered in sequence with the 4-digit year + 900 / 901 / 902, etc.

[0049] According to the accuracy of the surveying and mapping results corresponding to the detection point, fill in the actual detection result scale; fill in the level of the grade control point, such as GPS control point A, B, C, etc.; fill in the image resolution of the image control point. The accuracy information represents the position accuracy of the detection point that can achieve this type of result at this scale.

[0050] The detection point types are divided into "detection type" and "detection result" types. The "detection type" is determined according to the source and purpose of the detection point, and is marked with letter codes in the detection point record string in the detection point file, such as P for plane detection, G for elevation detection, PG for flat-elevation detection, etc. The detection result type is determined according to the detection type used for detection at the detection point, which has been reflected in the naming of the detection point file.

[0051] Optionally, step 4 includes the following sub-steps:

[0052] Step 41, input the unified number of the inspection point;

[0053] Step 42, data format conversion and attribute assignment, after entering all the inspection points in the Excel entry template, add auxiliary information decimal precision and decimal latitude, batch convert degrees, minutes and seconds into decimal degrees through Excel formulas, edit the conversion formula in Excel, and perform batch conversion;

[0054] Step 43, spatial processing, adds xy data in ArcGIS and converts the detection points into a geographic database in decimal degree format.

[0055] By adopting the above technical solution, the test points are uniformly numbered, and all the test points are entered into the data table in batches. The test point numbering rules stipulate the numbering components and rules, including the acquisition method, the administrative division code, the collection date and the serial number, to ensure that the test point numbers in the whole database are not repeated. At the same time, the newly collected test points can be numbered independently without affecting the numbers of the test points that have been stored in the database.

[0056] After entering all the inspection points in the Excel entry template, add the auxiliary information decimal precision and decimal latitude, and convert the degrees, minutes and seconds into decimal degrees in batches through Excel formulas. This work involves editing the conversion formula in Excel and performing the conversion in batches.

[0057] Optionally, in step 4, if there is a detection point that exceeds the administrative area boundary, the location information of the detection point is mapped to the nearest administrative area.

[0058] By adopting the above technical solution, the detection points are spatially superimposed with the county-level administrative area surface elements, and the names of the county-level administrative areas to which they belong are attached; the detection points are spatially superimposed with the city-level administrative area surface elements, and the names of the city-level administrative areas to which they belong are attached. Some detection points exceed the provincial boundaries. These points are mainly satellite image ground control points and encryption points. The processing method is to correspond these points to adjacent administrative areas to avoid the detection stations where these satellite image ground control points and encryption points are located being unable to be normally stored and processed in the database.

[0059] In summary, the present invention includes at least one of the following beneficial technical effects:

[0060] The present invention can provide a method for collecting and building a database of detection point data on large-scale topographic maps, filling the gap in the standardization of detection point collection and database construction for position accuracy detection points on large-scale topographic maps such as 1:500, 1:1000, and 1:2000. Combined with the practical experience of repeated use of detection points, the present invention analyzes and organizes the existing detection point data collection indicators and technical methods, as well as similar database construction requirements, establishes detection point database technical standards that meet the actual needs of inspection work, and focuses on the research of detection point data standards, collection method standards, and database construction standards.

[0061] Through standard research and application, technical standards for the collection and database construction of large-scale topographic map inspection points were established, which improved the efficiency of inspection work and the level of reuse of inspection point results. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a schematic diagram of the process of data collection and database building of large-scale topographic map detection points of the present invention; DETAILED DESCRIPTION

[0063] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0064] The embodiment of the present invention discloses a method for collecting and building a database of detection point data of a large-scale topographic map.

[0065] Reference Figure 1 , Embodiment 1, a method for collecting and building a database of detection point data of a large-scale topographic map, comprising the following steps:

[0066] Step 1: Collect data of multiple detection points respectively, the detection point data includes detection point coordinate files, collection registration forms, field photos and image screenshots with detection points marked;

[0067] Step 2, sorting out multiple detection point coordinate files according to set standards;

[0068] Step 3, establish a detection point database, and sort and import the data of multiple detection points into the detection point database;

[0069] Step 4: After data format conversion and attribute assignment, a standard detection point database is formed.

[0070] In order to adapt to the development of surveying and mapping results quality inspection technology and actual application needs, fill the gap in the standardization of 1:500, 1:1000, and 1:2000 topographic map position accuracy detection point collection and database construction, and combine the practical experience of detection point reuse, analyze and organize the existing detection point data collection indicators and technical methods, as well as similar database construction requirements, establish detection point database technical standards that meet the actual needs of inspection work, and focus on the research of detection point data standards, collection method standards, and database construction standards.

[0071] Through standard research and application, technical standards for the collection and database construction of large-scale topographic map inspection points were established, which improved the efficiency of inspection work and the level of reuse of inspection point results.

[0072] In embodiment 2, in step 2, arranging the detection point coordinate file includes the following method:

[0073] When using a measuring instrument to collect the coordinates of the detection points, the coordinate file is directly exported from the measuring instrument and organized into the corresponding detection point coordinate file based on the detection instrument;

[0074] If the coordinate data in the detection point coordinate file only includes plane coordinates and elevation, the plane coordinates and elevation are converted to obtain longitude and latitude coordinates. The detection point coordinate file record format is: detection point number, detection point type, latitude, longitude, geodetic height, north coordinate, east coordinate, elevation, collection date; if the local coordinate system is used, it is converted to the 2000 National Geodetic Coordinate System coordinates;

[0075] The naming format of the detection point coordinate file is: instrument number, acquisition method, central meridian, acquisition date.

[0076] When the measuring instrument is RTK, calculate the Gaussian plane coordinates, convert the longitude and latitude coordinates into Gaussian plane coordinates according to the given projection band, calculate the normal height, and convert the normal height in the HBCORS system based on the original longitude and latitude, geodetic height and instrument height;

[0077] The method of converting and obtaining normal height in the HBCORS system is to extract the detection point number, longitude and latitude, geodetic height, and instrument height of the detection point from the original detection point file, organize them into a text format that meets the online conversion requirements of the HBCORS system, upload them to the HBCORS online location service system for self-service conversion, obtain the Gaussian plane coordinates, elevation, and belt number of the detection point, and obtain the central meridian of the detection point, the Gaussian plane coordinates without belt number, and the 1985 elevation through string batch processing, and add them to the detection point coordinate file;

[0078] When the measuring instrument is a total station, the DLG detection points collected by the polar coordinate method only have plane coordinates but no longitude and latitude coordinates. The detection point number, x north coordinate, y east coordinate and elevation are extracted from the original file to form a text file, which is submitted to the HBCORS online location service system for self-service conversion to obtain the longitude and latitude coordinates and geoid height under the specified central meridian.

[0079] When using a measuring instrument to collect detection points, the coordinate file should be directly exported from the measuring instrument, and organized into a detection point coordinate file with the detection instrument as the unit; when using existing results to collect detection points, the detection points collected within the scope of the existing results should be organized into a detection point coordinate file; the original data only collected plane coordinates and elevations, and coordinate conversion should be performed to obtain longitude and latitude coordinates. The detection point record format is: detection point number, detection point type, latitude, longitude, geodetic height, north coordinate, east coordinate, elevation, collection date; detection point coordinates and longitude and latitude, the unit is "degree", and the value is taken to 9 decimal places; plane coordinates, geodetic height, elevation, the unit is "meter", the value is taken to 3 decimal places, and when using the local coordinate system, it needs to be converted to the 2000 national geodetic coordinate system coordinates; the detection point coordinate file can be named in the form of "instrument number + collection method + central meridian + collection date"; the detection point coordinate file related information should be registered in the collection registration form;

[0080] Example 3, using low-altitude drone aerial photogrammetry method to collect field photos of detection points, the main ground object points photographed when collecting the field photos of the detection points are placed in the middle of the drawing, there are position reference objects in the field photos, the shooting distance is 5m to 20m, and the resolution is not less than 1 million pixels.

[0081] Example 4: An image screenshot with detection points marked is cropped from reference data, which includes a topographic map and a satellite image. The detection point position is marked with a clear mark with the detection point position as the center point, and the image is cropped to a set length and width pixel size.

[0082] Field photos and image screenshots are organized. Field photos and image screenshots with marked detection points are stored as image files, and folders are created by category to store images of different categories; the image file name should be unique, the file name should be consistent with the detection point number, and an identification code and image serial number should be attached. The naming rule is: "Identification code + detection point number + image serial number", where the field photo identification code is replaced by the letters "ZP" and the image screenshot is replaced by "YX"; the image serial number is serially numbered according to the number of field photos (or image screenshots) contained in each detection point, and the image serial number retains 2 digits, and a "0" is added in front of less than two digits.

[0083] The readability of the inspection points can be enhanced by adding field photos and image screenshots, providing accurate basis for reusing the inspection points.

[0084] In embodiment 5, step 3 comprises the following sub-steps:

[0085] Step 31, create a library, allocate physical space for each type of data, and create a detection point data table;

[0086] Step 32, data preparation, performing consistency conversion on the detection point coordinate file sorted in step 2 according to the requirements of data organization, and the consistency conversion includes code conversion, format conversion, coordinate transformation and projection conversion;

[0087] Step 33, storing the detection point spatial data and attributes in the database according to the data organization method;

[0088] Step 34, detection point file storage, the detection point file is stored in the form of a file, the folder is named according to the project name, and the detection point coordinate file, collection registration form, field photo directory and image screenshot directory are stored in sequence.

[0089] Database creation. According to the requirements of database organization, physical space is allocated to each type of data, relevant parameters are set, data tables are created, etc. The scalability of the database should be considered when allocating physical space. The organized detection point coordinate files are converted for consistency according to the requirements of data organization, mainly including code conversion, format conversion, coordinate transformation, projection conversion, etc.

[0090] The spatial data and attributes of the detection points are stored in the database according to the data organization method. Data can be stored manually or in batches by program.

[0091] The detection point files are stored in the form of files. The folders are named according to the project name, and the detection point coordinate files, collection registration forms, field photo directories, and image screenshot directories are stored in sequence.

[0092] The data at the inspection points should be updated as needed to keep the data realistic.

[0093] Database security protection, confidentiality, and database backup and recovery should comply with the requirements of GB / T 33453.

[0094] The quality requirements of the database should meet the requirements of GB / T 33453, and at the same time meet the requirements of integrity, logical consistency, conceptual consistency, value range consistency, format consistency, attribute accuracy, etc.

[0095] The test point data are shown in the table below:

[0096] Test point data table

[0097]

[0098] In Example 6, step 33 includes the following sub-steps:

[0099] Step 331, input the path information of the attachment of the detection point data, which includes the path corresponding to the screenshot and photo of the detection point, and indicates the detailed location of the detection point, using specific direction terms to describe the position relationship, and the specific direction terms are east, west, south, north, inside, outside, up, down, up and down;

[0100] The position relationship description is consistent with the position relationship between the detection point and the ground object in the photo;

[0101] Step 332, input the detection point source information;

[0102] Step 333, input the accuracy information, fill in the actual detection result scale according to the accuracy of the detection point corresponding to the surveying and mapping results, and fill in the corresponding level for the level control point;

[0103] Step 334, enter the detection point type. The detection point type is divided into detection type and detection result type. The detection type is determined according to the source and purpose of the detection point, and is marked with letter codes in the detection point record string in the detection point file, such as P for plane detection, G for elevation detection, and PG for flat-elevation detection. The detection result type is determined according to the detection type used for detection at the detection point, and the detection result type is reflected in the naming of the detection point file.

[0104] Enter the attached path of the detection point. The detection point data will be accompanied by on-site photos and image screenshots. When entering the detection point, it is necessary to enter the detection point image screenshots and the corresponding path of the photos at the same time, and indicate the detailed location of the detection point in the location description. Use words that can specifically and accurately express the position relationship, such as east, south, west, north, inside, outside, up, down, and on and off the ridge, etc., which should be consistent with the position relationship between the detection point and the ground object in the photo, such as "the southwest corner of the flower bed is the landing point".

[0105] Example 7, enter the source information of the detection point, the source information of the detection point includes information such as the collection date, which can be extracted from the collection registration form; the project number is supplemented and entered during the database construction process based on the station's annual inspection and acceptance project number. Projects with report numbers are numbered according to the 4-digit year + 3-digit report sequence number, and projects without project report numbers are numbered in sequence with the 4-digit year + 900 / 901 / 902, etc.

[0106] According to the accuracy of the surveying and mapping results corresponding to the detection point, fill in the actual detection result scale; fill in the level of the grade control point, such as GPS control point A, B, C, etc.; fill in the image resolution of the image control point. The accuracy information represents the position accuracy of the detection point that can achieve this type of result at this scale.

[0107] The detection point types are divided into "detection type" and "detection result" types. The "detection type" is determined according to the source and purpose of the detection point, and is marked with letter codes in the detection point record string in the detection point file, such as P for plane detection, G for elevation detection, PG for flat-elevation detection, etc. The detection result type is determined according to the detection type used for detection at the detection point, which has been reflected in the naming of the detection point file.

[0108] In Example 8, step 4 includes the following sub-steps:

[0109] Step 41, input the unified number of the inspection point;

[0110] Step 42, data format conversion and attribute assignment, after entering all the inspection points in the Excel entry template, add auxiliary information decimal precision and decimal latitude, batch convert degrees, minutes and seconds into decimal degrees through Excel formulas, edit the conversion formula in Excel, and perform batch conversion;

[0111] Step 43, spatial processing, adds xy data in ArcGIS and converts the detection points into a geographic database in decimal degree format.

[0112] The test points are uniformly numbered, and all the test points are entered into the data table in batches. The test point numbering rules specify the numbering components and rules, including the acquisition method, the administrative division code, the collection date and the serial number, to ensure that the test point numbers in the entire database are not repeated. At the same time, the newly collected test points can be numbered independently without affecting the numbers of the test points that have been stored;

[0113] After entering all the inspection points in the Excel entry template, add the auxiliary information decimal precision and decimal latitude, and convert the degrees, minutes and seconds into decimal degrees in batches through Excel formulas. This work involves editing the conversion formula in Excel and performing the conversion in batches.

[0114] In Example 9, in step 4, if there is a detection point that exceeds the administrative area boundary, the location information of the detection point is mapped to the nearest administrative area.

[0115] The detection points are spatially superimposed with the county-level administrative area surface elements, and the names of the county-level administrative areas to which they belong are attached; the detection points are spatially superimposed with the city-level administrative area surface elements, and the names of the city-level administrative areas to which they belong are attached. Some detection points are beyond the provincial boundaries. These points are mainly satellite image ground control points and encryption points. The processing method is to correspond these points to adjacent administrative areas to avoid the detection stations where these satellite image ground control points and encryption points are located being unable to be normally stored and processed in the database.

[0116] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for collecting and building a database of detection point data for a large-scale topographic map, characterized in that: The following steps are involved: Step 1: Collect data of multiple detection points respectively, the detection point data includes detection point coordinate files, collection registration forms, field photos and image screenshots with detection points marked; Step 2, sorting out multiple detection point coordinate files according to set standards; Step 3, establish a detection point database, and sort and import the data of multiple detection points into the detection point database; Step 4: After data format conversion and attribute assignment, a standard detection point database is formed.

2. The method for collecting and building a database of detection point data of a large-scale topographic map according to claim 1 is characterized in that: In step 2, the detection point coordinate file is sorted out by the following methods: When using a measuring instrument to collect the coordinates of the detection points, the coordinate file is directly exported from the measuring instrument and organized into the corresponding detection point coordinate file based on the detection instrument; If the coordinate data in the detection point coordinate file only includes plane coordinates and elevation, the plane coordinates and elevation are converted to obtain longitude and latitude coordinates. The detection point coordinate file record format is: detection point number, detection point type, latitude, longitude, geodetic height, north coordinate, east coordinate, elevation, collection date; if the local coordinate system is used, it is converted to the 2000 National Geodetic Coordinate System coordinates; The naming format of the detection point coordinate file is: instrument number, acquisition method, central meridian, acquisition date.

3. The method for collecting and building a database of detection point data of a large-scale topographic map according to claim 2 is characterized in that: When the measuring instrument is RTK, calculate the Gaussian plane coordinates, convert the longitude and latitude coordinates into Gaussian plane coordinates according to the given projection band, calculate the normal height, and convert the normal height in the HBCORS system based on the original longitude and latitude, geodetic height and instrument height; The method of converting and obtaining normal height in the HBCORS system is to extract the detection point number, longitude and latitude, geodetic height, and instrument height of the detection point from the original detection point file, organize them into a text format that meets the online conversion requirements of the HBCORS system, upload them to the HBCORS online location service system for self-service conversion, obtain the Gaussian plane coordinates, elevation, and belt number of the detection point, and obtain the central meridian of the detection point, the Gaussian plane coordinates without belt number, and the 1985 elevation through string batch processing, and add them to the detection point coordinate file; When the measuring instrument is a total station, the DLG detection points collected by the polar coordinate method only have plane coordinates but no longitude and latitude coordinates. The detection point number, x north coordinate, y east coordinate and elevation are extracted from the original file to form a text file, which is submitted to the HBCORS online location service system for self-service conversion to obtain the longitude and latitude coordinates and geoid height under the specified central meridian.

4. The method for collecting and building a database of detection point data of a large-scale topographic map according to claim 1 is characterized in that: Use low-altitude UAV aerial photogrammetry to collect field photos of the detection points. When collecting the field photos of the detection points, the main ground object points photographed are placed in the middle of the drawing. There are position reference objects in the field photos. The shooting distance is 5m to 20m, and the resolution is not less than 1 million pixels.

5. The method for collecting and building a database of detection point data of a large-scale topographic map according to claim 1 is characterized in that: The image screenshots with the detection points marked are cropped from the reference data, which includes topographic maps and satellite images. The detection point positions are marked with obvious marks with the detection point positions as the center points, and the images with set length and width pixel sizes are cropped.

6. The method for collecting and building a database of detection point data of a large-scale topographic map according to claim 1 is characterized in that: Step 3 includes the following sub-steps: Step 31, create a library, allocate physical space for each type of data, and create a detection point data table; Step 32, data preparation, performing consistency conversion on the detection point coordinate file sorted in step 2 according to the requirements of data organization, and the consistency conversion includes code conversion, format conversion, coordinate transformation and projection conversion; Step 33, storing the detection point spatial data and attributes in the database according to the data organization method; Step 34, detection point file storage, the detection point file is stored in the form of a file, the folder is named according to the project name, and the detection point coordinate file, collection registration form, field photo directory and image screenshot directory are stored in sequence.

7. The method for collecting and building a database of detection point data of a large-scale topographic map according to claim 1 is characterized in that: Step 33 includes the following sub-steps: Step 331, input the path information of the attachment of the detection point data, which includes the path corresponding to the screenshot and photo of the detection point, and indicates the detailed location of the detection point, using specific direction terms to describe the position relationship, and the specific direction terms are east, west, south, north, inside, outside, up, down, up and down; The position relationship description is consistent with the position relationship between the detection point and the ground object in the photo; Step 332, input the detection point source information; Step 333, input the accuracy information, fill in the actual detection result scale according to the accuracy of the detection point corresponding to the surveying and mapping results, and fill in the corresponding level for the level control point; Step 334, enter the detection point type. The detection point type is divided into detection type and detection result type. The detection type is determined according to the source and purpose of the detection point, and is marked with letter codes in the detection point record string in the detection point file, such as P for plane detection, G for elevation detection, and PG for flat-elevation detection. The detection result type is determined according to the detection type used for detection at the detection point, and the detection result type is reflected in the naming of the detection point file.

8. The method for collecting and building a database of detection point data for a large-scale topographic map according to claim 1 is characterized in that: Step 4 includes the following sub-steps: Step 41, input the unified number of the inspection point; Step 42, data format conversion and attribute assignment, after entering all the inspection points in the Excel entry template, add auxiliary information decimal precision and decimal latitude, batch convert degrees, minutes and seconds into decimal degrees through Excel formulas, edit the conversion formula in Excel, and perform batch conversion; Step 43, spatial processing, adds xy data in ArcGIS and converts the detection points into a geographic database in decimal degree format.

9. The method for collecting and building a database of detection point data of a large-scale topographic map according to claim 8, characterized in that: In step 4, if there is a detection point that exceeds the administrative area boundary, the location information of the detection point is mapped to the nearest administrative area.

Images