A method for standardizing attribute structure of spatial vector data and storage medium

Abstract

The present invention relates to the field of GIS vector data processing methods, and specifically to a spatial vector data attribute structure standardization method and storage medium. The method comprises the following steps: obtaining a standard attribute structure table required by planning, building and encapsulating a standardized attribute list based on the standard attribute structure table; establishing an existing attribute list based on the obtained target vector data attribute table; adding a standard attribute field to the target vector data attribute table according to whether the field code item of each attribute value in the standardized attribute list already exists in the existing attribute list; obtaining attribute transfer preset information, and transferring the attribute values ​​in the existing attribute list to the standardized attribute list according to the attribute transfer preset information; traversing each attribute value in the target vector data attribute table, and comparing them with the attribute values ​​in the standardized attribute list, and deleting redundant attribute fields in the target vector data attribute table according to the comparison result. The present invention improves data entry efficiency and accuracy.

Description

Technical Field

[0001] The present invention relates to the field of GIS vector data processing methods, and in particular to a spatial vector data attribute structure standardization method and a storage medium. Background Art

[0002] Vector data structures represent specific features on the Earth's surface and assign attributes to those features. Vectors are composed of discrete geometric locations (x, y) called vertices, which define the shape of spatial objects. The organization of the vertices determines the type of vector used: point, line, or polygon. ArcMap is the map processing software in ArcGIS, and ArcMap is one of the foundational modules of ArcGIS. When establishing a standard geographic database, the existing data includes many fields, while the database entry standard requires only one or a few specific fields. Therefore, the vector data structure needs to be standardized.

[0003] ArcMap's method for standardizing vector data attribute structures is:

[0004] 1. Manually add fields one by one according to the attribute structure table and enter field attribute information such as field name, field code, field type, field length, number of decimal places, etc.

[0005] 2. Manually judge and transfer existing field attribute values ​​to newly created standardized fields one by one;

[0006] 3. Manually judge and delete non-standardized redundant fields one by one;

[0007] 4. If the vector data needs to be modified or updated, the above manual operation process needs to be repeated.

[0008] The existing vector data attribute structure standardization methods have the following problems:

[0009] 1. Low work efficiency: In the daily spatial vector data management process, many layers are involved, and each layer attribute table has multiple different attribute structure fields. Each attribute structure field has different field name, alias, type, length, precision (number of decimal places), value range, constraints and remarks. Manually creating and entering this information is very inefficient.

[0010] 2. High error rate: Spatial data involves various complex and intertwined attribute information. Manual data entry is subject to human uncertainty factors and is prone to data entry errors. The error rate of data results is high and accuracy cannot be guaranteed.

[0011] 3. Inconvenience in repeated modifications: Because spatial data governance is a dynamic work, even the same data is often updated and modified regularly or irregularly. Updates and modifications are usually accompanied by re-standardization of attribute structures, which will generate a large amount of high-frequency repetitive work. These repetitive tasks are not suitable for manual completion. Summary of the Invention

[0012] The present invention aims to provide a method for standardizing the attribute structure of spatial vector data to solve the problems of low working efficiency, high error probability and inconvenience in repeated modification of existing methods.

[0013] The spatial vector data attribute structure standardization method in this solution includes:

[0014] Step 1: Obtain the standard attribute structure table of planning requirements, and build and encapsulate the standardized attribute list based on the standard attribute structure table;

[0015] Step 2: Establish an existing attribute list based on the acquired target vector data attribute table;

[0016] Step 3: Add standard attribute fields to the target vector data attribute table based on whether the field code items of each attribute value in the standardized attribute list already exist in the existing attribute list;

[0017] Step 4: Obtain attribute transfer preset information, and transfer attribute values ​​in the existing attribute list to the standardized attribute list according to the attribute transfer preset information;

[0018] Step 5: traverse each attribute value in the target vector data attribute table, compare them with the attribute values ​​in the standardized attribute list, and delete redundant attribute fields in the target vector data attribute table according to the comparison result.

[0019] Preferably, in order to avoid missing attribute fields and perform standardization accurately, in step 2, an existing attribute table is established by traversing the target vector data attribute table to obtain existing attribute fields.

[0020] Preferably, in order to improve the standardization speed of the fields in the target vector data attribute table, in step 3, the field code items of each attribute value in the standardized attribute list are traversed and compared with the attributes in the existing attribute list;

[0021] If the field code item in the standardized attribute list does not exist in the existing attribute list, the field code item will be created in the target vector data attribute table according to the structure attributes of the standardized attribute list.

[0022] More preferably, in order to avoid omission of field attributes and accurately standardize the fields in the target vector data attribute table, in step 3, if the field code item in the standardized attribute list is in the existing attribute list, the standard attribute field is added according to the following process:

[0023] First, create a conversion field in the target vector data attribute table, and transfer the value of the field code item in the target vector data attribute table to the conversion field, and delete the field code in the target vector data attribute table;

[0024] Then, the field code is recreated in the feature column of the target vector data attribute table according to the structural attributes in the standardized attribute table, and the value of the conversion field is transferred to the recreated field code, and then the conversion field is deleted.

[0025] Preferably, in order to improve the efficiency of field attribute transfer, in step 4, the attribute transfer preset information is empty by default. When the attribute transfer preset information is empty, the transfer operation is skipped. When the attribute transfer information is not empty, the transfer operation is performed.

[0026] Preferably, in order to quickly deduplicate non-standard fields in the target vector data attribute table, in step 5, after comparison, if the attribute value in the target vector data attribute table is in the standardized attribute list, the deletion operation is skipped; if the attribute value in the target vector data attribute table is not in the standardized attribute list, the attribute value in the target vector data attribute table is deleted.

[0027] A storage medium stores one or more computer executable programs, wherein the one or more computer executable programs can be executed by one or more processors to perform the steps of the above-mentioned spatial vector data attribute structure standardization method.

[0028] Compared with the existing technology, the beneficial effects of this solution are:

[0029] The standard attribute structure table is converted into a built-in list of the program for encapsulation. After execution, standardized fields are automatically added according to the field attribute information such as field name, alias, type, length, number of decimal places, etc. in the list. The attribute structure table can be automatically entered in batches, which improves the entry efficiency and avoids the inefficiency and error-prone manual entry. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flowchart of an embodiment of a method for standardizing the attribute structure of spatial vector data according to the present invention;

[0031] Figure 2 This is a principle block diagram of an embodiment of a method for standardizing a spatial vector data attribute structure according to the present invention;

[0032] Figure 3This is a block diagram of the principles of the existing standardization method;

[0033] Figure 4 It is a diagram of encapsulation parameters configuration in an embodiment of the method for standardizing the attribute structure of spatial vector data of the present invention;

[0034] Figure 5 This is a schematic diagram of a space vector data attribute structure standardization script tool encapsulated in an embodiment of the space vector data attribute structure standardization method of the present invention. DETAILED DESCRIPTION

[0035] The following is further explained in detail through specific implementation methods.

[0036] Example

[0037] Spatial vector data attribute structure standardization method, such as Figure 1 Shown, including:

[0038] Step 1: Obtain the standard attribute structure table of national land space planning requirements, build and encapsulate the standardized attribute list based on the standard attribute structure table. Taking the standard attribute list of land and sea use in national land space planning as an example, as shown in Table 1, the standardized attribute list is represented as List_std.

[0039] Table 1 Standard attribute structure table builds and encapsulates standardized attributes

[0040] Serial number Field Name Field Code Field Type Field length Decimal places range Constraints Remark 1 Identification code BSM TEXT 18 M 2 Feature Code YSDM TEXT 10 M 3 Administrative region code XZQDM TEXT 12 M 4 Administrative district name XZQM TEXT 100 M 5 Land use category YDLB TEXT 50 M 6 Land and sea use classification code YDYHFLDM TEXT 10 M 7 Land and sea use classification name YDYHFLMC TEXT 50 M 8 Patch area TBMJ Float 15 2 ＞0 M Unit: square meters 9 Deduction coefficient KCXS Float 15 2 ＞0 M Unit: square meters 10 Deduction area KCMJ Float 15 2 ＞0 M Unit: square meters 11 Planned land area GHDLMJ Flot 15 2 ＞0 M Unit: square meters 12 Planning Status GHZT TEXT 2 M 13 Remark BZ TEXT 255 0

[0041] The establishment method based on Table 1 is:

[0042] List_std=[

[0043] ["BSM","ID code","TEXT",18",""],

[0044] ["YSDM","element code","TEXT",10",""],

[0045] [″XZQDM″,″Administrative region code″,″TEXT″,12,″″],

[0046] [″XZQMC″,″Administrative district name″,″TEXT″,100,″″],

[0047] ["YDLB","Land Use Category","TEXT",100,""],

[0048] ["GHYDFLDM","Planning land classification code","TEXT",50,""],

[0049] ["GHYDFLMC","Planned land classification name","TEXT",50,""],

[0050] ["TBMJ","Block Area","Float",15,2],

[0051] ["KCXS","Deduction Coefficient","Float",15,2],

[0052] ["KCMJ","Subtracted Area","Float",15,2],

[0053] ["GHDLMJ","Planned Land Area","Float",15,2],

[0054] ["GHZT","Planning Status","TEXT",100,""],

[0055] ["BZ","Note","TEXT",255,""]

[0056] ].

[0057] Step 2: Establish an existing attribute list based on the acquired target vector data attribute table. Establish an existing attribute table by traversing the target vector data attribute table to obtain the existing attribute fields. The target vector data is represented as DATA_IN, the target vector data attribute table is represented as ListFields, and the existing attribute table is represented as List_in. The existing attribute table is shown in Table 2.

[0058] Table 2 Existing attribute table

[0059]

[0060]

[0061] The method to create Table 2 is: List_in = [f.name for f in arcpy.ListFields(DATA_IN)].

[0062] By converting the standard attribute structure table into a built-in list for encapsulation, the program will automatically add standardized fields based on the field name, alias, type, length, decimal places and other field attribute information in the list after execution, avoiding the inefficient and error-prone manual entry problem.

[0063] Step 3: Add standard attribute fields to the target vector data attribute table ListFields according to whether the field code items List_std[N][0] of each attribute value in the standardized attribute list List_std already exist in the existing attribute list List_in. Specifically, traverse the field code items List_std[N][0] of each attribute value in the standardized attribute list List_std and compare them with the attributes in the existing attribute list List_in.

[0064] If the field code item List_std[N][0] in the standardized attribute list List_std is not in the existing attribute list List_in, the field code item List_std[N][0] is created in the target vector data attribute table ListFields according to the structural attributes of the standardized attribute list List_std.

[0065] If the field code item List_std[N][0] in the standardized attribute list List_std exists in the existing attribute list List_in, the standard attribute field is added as follows:

[0066] First, create a conversion field List_std[N][0]_Alt in the target vector data attribute table ListFields, and transfer the value of the field code item List_std[N][0] in the target vector data attribute table ListFields to the conversion field List_std[N][0]_Alt, and delete the field code List_std[N][0] in the target vector data attribute table ListFields;

[0067] Then, according to the structural attributes in the standardized attribute table List_std, the field code List_std[N][0] is recreated in the feature column Feature Table of the target vector data attribute table ListFields, and the value of the conversion field List_std[N][0]_Alt is passed to the recreated field code List_std[N][0], and then the conversion field List_std[N][0]_Alt is deleted. When the field code item in the standardized attribute list List_std is located in the existing attribute list List_in, the above operation can avoid the situation in step 3 where all the field names in the target vector data and the field names in the standardized attribute table List_std are the same, but other attributes (such as field type, field length) are different, resulting in attribute omission. Therefore, if there are fields with the same name, a new conversion field is added, its field value is passed to the conversion field, the corresponding original field is deleted, and a new field with the same name is added according to the standardization.

[0068] The establishment process of Step 3 is as follows:

[0069] for N in range(0,len(List_std)):

[0070] if List_std[N][0]in List_in:

[0071] arcpy.AddField_management(DATA_IN, field_name = List_std[N][0]+"_Alt", field_alias = List_std[N][0]+"_Alt", field_type = List_std[N][2], field_length = List_std[N][3], field_scale = List_std[N][4])

[0072] arcpy.CalculateField_management(DATA_IN, List_std[N][0]+"_Alt", "!"+List_std[N][0]+"!", "PYTHON_9.3")

[0073] arcpy.DeleteField_management(DATA_IN, List_std[N][0])

[0074] field_list.remove(List_std[N][0])

[0075] arcpy.AddField_management(DATA_IN, field_name = List_std[N][0], field_alias = List_std[N][1], field_type = List_std[N][2], field_length = List_std[N][3], field_scale = List_std[N][4])

[0076] arcpy.CalculateField_management(DATA_IN, List_std[N][0], "!"+List_std[N][0]+"_Alt!", "PYTHON_9.3")

[0077] arcpy.DeleteField_management(DATA_IN, List_std[N][0]+"_Alt") It should be noted that there is a syntax error in the original text in line 10: "field_name=List_std[N][0]+"_Alt" should be "field_name = List_std[N][0]+"_Alt". The same correction is made in the translation for correct representation.

[0078] elif List_std[N][0]not in List_in:

[0079] arcpy.AddField_management(DATA_IN, field_name=List_std[N][0], field_alias=List_std[N][1], field_type=List_std[N][2], field_length=List_std[N][3], field_scale=List_std[N][4]).

[0080] By traversing the existing attribute fields of spatial data and comparing them with the standardized field list, the existing non-standardized fields are deleted, thereby detecting and automatically deleting non-standardized redundant fields. This improves the inefficiency of the existing technology of manually judging and deleting redundant fields one by one.

[0081] Step 4, obtain the attribute transfer preset information, and transfer the attribute value List_in[N] in the existing attribute list List_in to the standardized attribute list List_std according to the attribute transfer preset information. The attribute transfer preset information is empty by default. When the attribute transfer preset information is empty, skip the transfer operation. When the attribute transfer information is not empty, perform the transfer operation.

[0082] The attribute transfer preset information is obtained by setting the transfer interface and establishing the parameter set Dict_in of the attribute transfer preset information for the transfer interface. The default value of the transfer interface is empty. The establishment method is:

[0083] Dict_in={

[0084] 'DATA_IN':arcpy.GetParameterAsText(0),

[0085] 'BSM_IN':arcpy.GetParameterAsText(1),

[0086] 'YSDM_IN':arcpy.GetParameterAsText(2),

[0087] 'XZQDM_IN':arcpy.GetParameterAsText(3),

[0088] 'XZQMC_IN':arcpy.GetParameterAsText(4),

[0089] 'YDLB_IN':arcpy.GetParameterAsText(5),

[0090] 'GHYDFLDM_IN':arcpy.GetParameterAsText(6),

[0091] 'GHYDFLMC_IN':arcpy.GetParameterAsText(7),

[0092] 'TBMJ_IN':arcpy.GetParameterAsText(8),

[0093] 'KCXS_IN':arcpy.GetParameterAsText(9),

[0094] 'KCMJ_IN':arcpy.GetParameterAsText(10),

[0095] 'MJ_IN':arcpy.GetParameterAsText(11),

[0096] 'GHZT_IN':arcpy.GetParameterAsText(12),

[0097] 'BZ_IN':arcpy.GetParameterAsText(13),

[0098] }.

[0099] The process of determining the preset information for the attribute transfer interface is as follows:

[0100] for k in List_std:

[0101] if len(dict_in[k[0]+'_IN'])===0:

[0102] pass

[0103] else:

[0104] arcpy.CalculateField_management(DATA_IN,k[0],"!"+dict_in[k[0]+'_IN']+"!","PYTHON_9.3").

[0105] By providing a preset interface for attribute transfer, users can directly select the fields to be transferred. After the program runs, the selected field values ​​will be automatically transferred to the corresponding standardized fields. This improves the inefficient shortcomings of the existing technology of manual judgment and manual attribute transfer one by one.

[0106] Step 5, traverse each attribute value in the target vector data attribute table ListFields, and compare them with the attribute values ​​in the standardized attribute list List_std, and delete the redundant attribute fields in the target vector data attribute table ListFields according to the comparison results. Specifically, after comparison, if the attribute value in the target vector data attribute table ListFields is in the standardized attribute list, skip the deletion operation; if the attribute value in the target vector data attribute table ListFields is not in the standardized attribute list List_std, delete the attribute value in the target vector data attribute table ListFields.

[0107] The specific process is:

[0108] Get the input data type and judge it, and create a list List_C according to different data types:

[0109] dataType=arcpy.Describe(DATA_IN).dataType

[0110] if dataType=='FeatureClass':

[0111] List_C=['OBJECTID_1','OBJECTID','Objectid','objectid','Shape','SHAPE','shape','Shape_Len gth','Shape_Area','SHAPE_Length','SHAPE_Area','SHAPE_LENGTH','SHAPE_AREA']

[0112] else:

[0113] List_C=['FID','fid','Fid','SHAPE','Shape','shape','ID','Id','id'].

[0114] Traverse each element in the list List_std and append the field code name of each element to the list List_C:

[0115] for j in List_std:

[0116] List_C.append j[0].

[0117] Traverse the target data field values ​​and generate the list Field_list:

[0118] Field_list=[f.name for f in arcpy.ListFields(DATA_IN)].

[0119] Traverse each element Field_list[i] in the list Field_list and compare it with List_C. If Field_list[i] is in List_C, keep the Field_list[i] field and skip the operation; if Field_list[i] is not in List_C, delete the Field_list[i] field:

[0120] for iin range(0,len(Field_list)):

[0121] if Field_list[i]in List_C:

[0122] pass

[0123] else:

[0124] arcpy.DeleteField_management(data_out, Field_list[i]).

[0125] Based on the above method, the code is packaged by ArcGIS script packaging tool and Figure 4 Configure the package parameters to get Figure 5 The script tool for standardizing the attribute structure of spatial vector data shown in the figure takes the data in Table 3 as an example. After standardization, the results in Table 4 are obtained.

[0126] Table 3 Data table before standardization

[0127] Serial number Shape Deduction of land type Town and village land use types Classification of planned land and sea use Shape_Length Shape_Area temporary situation CS TEST 1 noodle 0.1139 paddy field 393.109224 3448.566672 Three-tone 1 23 200 2 noodle 0 Rural road land 231.492256 462.51756 Three-tone 2 23 200 3 noodle 0.1599 dry land 383.807517 3780.044735 Three-tone 3 23 200 4 noodle 0.1348 dry land 123.805486 710.426315 Three-tone 4 23 200 5 noodle 0 Rural road land 110.69866 139.732416 Three-tone 5 23 200 6 noodle 0 Arbor woodland 18.618398 5.513679 Three-tone 6 23 200 7 noodle 0 Arbor woodland 19.881523 0.001206 Three-tone 7 23 200 8 noodle 0 Arbor woodland 27.706087 0.001515 Three-tone 8 23 200 9 noodle 0.1348 dry land 997.435998 13739.206303 Three-tone 9 23 100 10 noodle 0 bamboo forest 119.265777 273.967774 Three-tone 10 23 200 11 noodle 0 bamboo forest 42.284188 45.403838 Three-tone 11 23 200 12 noodle 0 bamboo forest 37.456846 85.786022 Three-tone 12 23 200 13 noodle 0 Rural road land 128.903775 354.136648 Three-tone 13 23 200 14 noodle 0 Rural road land 64.518525 99.656679 Three-tone 14 23 200 15 noodle 0.1599 dry land 196.345605 1901.168823 Three-tone 15 23 200 16 noodle 0.1599 dry land 23.442417 14.203785 Three-tone 16 23 200 17 noodle 0 Rural road land 458.129908 690.256703 Three-tone 17 23 200 18 noodle 0 Other areas 656.593814 1198.330556 Three-tone 18 23 200 19 noodle 0 dry land 283.662162 4057.728638 Three-tone 19 23 200 20 noodle 0 Highway land 528.203503 1692.269804 Three-tone 20 23 200 21 noodle 0 paddy field 431.222403 2268.972612 Three-tone 21 23 200 22 noodle 0 paddy field 495.733679 14031.53251 Three-tone 22 23 100 23 noodle 0.1348 dry land 49.961898 87.481062 Control Plan 23 23 200 24 noodle 0.1348 dry land 311.207199 1605.695227 Control Plan 24 23 200 25 noodle 0 bamboo forest 33.187559 67.695028 Control Plan 25 23 200 26 noodle 0 bamboo forest 126.079291 278.393843 Control Plan 26 23 200 27 noodle 0.1599 dry land 375.398992 3235.162354 Control Plan 27 23 200

[0128] Table 4 Standardized data table

[0129]

[0130] The storage medium stores one or more computer executable programs, and the one or more computer executable programs can be executed by one or more processors to perform the steps of the above-mentioned spatial vector data attribute structure standardization method.

[0131] Before obtaining spatial vector data for subsequent planning operations, the spatial vector data is large in volume and has many types, and the standardization of each type of data is different. Therefore, its standardization is performed manually. This embodiment converts the standard attribute structure table into a built-in list of the program for encapsulation. After the program is executed, it automatically adds standardized fields based on the field attribute information such as the field name, alias, type, length, and number of decimal places in the list, and automatically transfers attributes by traversing each field code. It also compares tables and automatically deletes redundant fields based on the comparison results. Furthermore, it automatically transfers attribute value modifications and updates based on the settings of preset attributes. The overall operation of the standardization operation is simple and can be reused, which greatly reduces the probability of errors in the standardization process and improves the efficiency of the standardization operation.

[0132] like Figure 3 As shown, due to repeated revisions in the process of compiling the national land space planning scheme, the database construction also needs to be updated repeatedly. Each update requires standardization of the relevant planning data. Therefore, the efficiency improvement of the scheme design of this embodiment is not only reflected in the data standardization itself, but also extends to the overall dynamic update and maintenance of the national land space planning scheme, reflecting the system dynamic linkage from scheme compilation to data update, and improving the overall system efficiency of planning compilation and data update, ensuring real-time synchronization of planning schemes and databases, and while automatically and quickly compiling and updating data, preventing the problem of missing other attributes of the same field code items.

[0133] The above is only an embodiment of the present invention, and the common knowledge such as the specific structure and characteristics of the scheme is not described in detail here. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for standardizing the attribute structure of spatial vector data, characterized in that: include: Step 1: Obtain the standard attribute structure table of planning requirements, and build and encapsulate the standardized attribute list based on the standard attribute structure table; Step 2: establishing an existing attribute list based on the acquired target vector data attribute table, and establishing an existing attribute table by traversing the target vector data attribute table to obtain the existing attribute fields; Step 3: Add the standard attribute field to the target vector data attribute table according to whether the field code item of each attribute value in the standardized attribute list already exists in the existing attribute list, and traverse the field code items of each attribute value in the standardized attribute list and compare them with the attributes in the existing attribute list; If the field code item in the standardized attribute list does not exist in the existing attribute list, then create the field code item in the target vector data attribute table according to the structure attributes of the standardized attribute list; If the field code item in the standardized attribute list is in the existing attribute list, add the standard attribute field as follows: First, create a conversion field in the target vector data attribute table, and transfer the value of the field code item in the target vector data attribute table to the conversion field, and delete the field code in the target vector data attribute table; Then, the field code is recreated in the feature column of the target vector data attribute table according to the structural attributes in the standardized attribute table, and the value of the conversion field is transferred to the recreated field code, and then the conversion field is deleted; Step 4: Obtain attribute transfer preset information, and transfer the attribute values ​​in the existing attribute list to the standardized attribute list according to the attribute transfer preset information. The attribute transfer preset information is empty by default. When the attribute transfer preset information is empty, the transfer operation is skipped. When the attribute transfer preset information is not empty, the transfer operation is performed. Step 5: traverse each attribute value in the target vector data attribute table, compare them with the attribute values ​​in the standardized attribute list, and delete redundant attribute fields in the target vector data attribute table according to the comparison result.

2. A method for standardizing the attribute structure of spatial vector data according to claim 1, characterized in that: In step 5, after comparison, if the attribute value in the target vector data attribute table is in the standardized attribute list, the deletion operation is skipped; if the attribute value in the target vector data attribute table is not in the standardized attribute list, the attribute value in the target vector data attribute table is deleted.

3. A storage medium storing one or more computer executable programs, characterized in that: The one or more computer executable programs can be executed by one or more processors to perform the steps of the method for standardizing the attribute structure of spatial vector data according to any one of claims 1-2.

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