Geographic information data warehouse-in and warehouse-out processing method and device

Abstract

The invention discloses a geographic information data in-out storage processing method and device. The problem that geographic information database ground feature data cannot be locally downloaded and stored freely is solved. The geographic information data warehouse-in and warehouse-out processing method comprises the following steps: acquiring a first data cluster of a target ground object in a database; and in response to an instruction of the GUI, segmenting the first data cluster along a certain range line to generate at least one original sub-data cluster. Obtaining an achievement sub-data cluster; and merging the achievement sub-data cluster with the remaining part of data clusters of the first data cluster except the original sub-data cluster to obtain a second data cluster, and recovering the second data cluster to replace the first data cluster in the database. According to the method, incremental updating and storage of the data are realized according to the downloading range line after repairing and testing, and physical edge matching of ground feature elements can be realized.

Description

Technical Field

[0001] The present application relates to the technical field of computer data processing and geographic information database, and in particular to a method and device for processing geographic information data in and out of a database. Background Art

[0002] In the field of surveying and mapping geographic information, data entry and data connection are widely recognized and used. Data entry can be divided into initial entry and incremental update entry in order. With the development of surveying and mapping technology and the emergence of the "multi-survey integration" system, basic surveying and mapping work has become more flexible. It is no longer updated and repaired regularly according to annual requirements, nor is it required to be produced according to the concept of map sheets. Instead, it is repaired and measured at any time according to the project. Then, according to the specific project, the scope is flexibly drawn and downloaded from the database, and the data within the project scope is repaired and measured in the field, and then updated back to the original database in an incremental manner. How to reduce manual operations to realize the cutting and downloading of project area data according to the specified range, update the data into the warehouse after repair and measurement, and then physically merge the land features with the data outside the range, so as to reduce or avoid the problem of large manual processing workload caused by conflicts between land features when entering the warehouse, has become a technology that urgently needs to be solved. Summary of the invention

[0003] The present application proposes a method and device for processing geographic information data in and out of the database. The computer automatically cuts and downloads the project area data according to the specified range, updates the data into the database after measurement and revision, and then merges the land features with the data outside the range, thereby solving the problem that the land feature data in the geographic information database of the prior art cannot be freely downloaded locally and restored.

[0004] In a first aspect, an embodiment of the present application provides a method for processing geographic information data in and out of a database, comprising the steps of: Obtain the first data cluster of the target object in the database; In response to the instruction of the GUI, the first data cluster is segmented along a certain range line to generate at least one original sub-data cluster, and the association relationship between the original sub-data cluster and the first data cluster is determined; and a result sub-data cluster is obtained; The resultant sub-data is combined with the remaining data clusters of the first data cluster excluding the original sub-data cluster to obtain a second data cluster, which is stored back to replace the first data cluster in the database.

[0005] Preferably, after the first data cluster is split along a certain range line and before the second data cluster is restored, the method further comprises the following steps: An intermediate data set is generated; the intermediate data set includes data representing the association relationship between the first data cluster and the original sub-data cluster.

[0006] In one embodiment, the intermediate data set includes the remaining data cluster and data indicating an association relationship between the remaining data cluster and the original sub-data cluster.

[0007] In some embodiments, the resultant data cluster is merged with the remaining data cluster, including any of the following situations: There is no feature point at the breakpoint where the first data cluster is divided by the range line, the original sub-data cluster generates a feature point at the breakpoint, and the feature point at the breakpoint in the second data cluster is deleted; There are feature points at the breakpoints where the first data cluster is divided by the range line, and the feature point attributes of the resultant sub-data cluster and the first data cluster at the breakpoints are merged in the second data cluster.

[0008] In some embodiments, at least one of the following is also included: The feature code of the result data cluster is set to be the same as the feature code of the first data cluster; At least a part of the attributes of the graphic elements of the resultant data cluster and the remaining data cluster are set to be the same.

[0009] In one embodiment, the method further comprises the steps of: Merging the remaining data clusters with the feature point set of the resultant data cluster; The position features, display features and / or primitive combinations of the combined feature point set are determined to generate a symbolic code of the second data cluster.

[0010] In one of the embodiments, data contents or time stamps of the original sub-data cluster and the resultant sub-data cluster are compared to determine whether the data contents or time stamps have changed.

[0011] In the second aspect, the embodiments of the present application also provide a geographic information data in-and-out storage processing device, which is used to implement the geographic information data in-and-out storage processing method described in any one of the embodiments of the first aspect, and includes: an acquisition module, which is used to acquire the first data cluster of the target object in the database, and is also used to acquire the result sub-data cluster. A generation module, which is used to split the first data cluster along a certain range line in response to the instructions of the GUI to generate at least one original sub-data cluster. A determination module, which is used to determine the association relationship between the original sub-data cluster and the first data cluster. A merging module, which is used to merge the result sub-data cluster with the remaining data cluster of the first data cluster excluding the original sub-data cluster, to obtain a second data cluster and store it back to replace the first data cluster in the database.

[0012] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any one of the embodiments of the first aspect.

[0013] In a fourth aspect, an embodiment of the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any one of the embodiments of the first aspect when executing the computer program.

[0014] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects: The present application uses computer software technology to realize the downloading of data by cutting the database according to the range line, and after the survey and repair, the data is incrementally updated and stored according to the download range line, which can achieve the complete integration of land features. For example, the elements after physical connection are stored as a new land feature, rather than a simple data set merging process. The elements after physical connection form a new land feature element data cluster, realizing the overall storage and overall symbolic representation of land feature elements, rather than storing land feature information and driving land feature graphic display separately according to multiple elements before physical connection. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A flowchart of a geographic information data storage and retrieval processing method provided in an embodiment of the present application; Figure 2-1 A schematic diagram of a range line drawn in a database feature symbol style provided in an embodiment of the present application; Figure 2-2 A schematic diagram of the change of the symbol style segmentation of the database feature elements provided in the embodiment of the present application; Figure 2-3 A schematic diagram of changes in elements after segmentation of database features provided in an embodiment of the present application; Figure 2-4 A schematic diagram of the original data clusters replaced by changes in elements after segmentation of database features provided in an embodiment of the present application; Figure 3 A characteristic point set and flow chart of the geographic information data in and out processing method provided in the embodiment of the present application; Figure 4 This is a structural diagram of a geographic information data storage and retrieval processing device according to an embodiment of the present application; Figure 5 Schematic diagram of the commercial server system for the application scenario of this application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0017] The present application discloses a method and device for processing geographic information data in and out of the warehouse. The technology mainly realizes that basic geographic information data can be automatically cut and downloaded according to the specified range line and the update information and graphic information can be recorded separately. The downloaded repair and measurement data can be updated and stored in the warehouse in an incremental mode according to the recorded update information. The downloaded repair and measurement data can be losslessly physically connected according to the recorded graphic information and the symbol effect can be correctly displayed. The conflict problem of multiple people or multiple projects entering and exiting the warehouse can be automatically processed. A geographic entity element can be updated and stored in the warehouse after being split and downloaded to form a new complete geographic entity element.

[0018] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0019] Figure 1 This is a flow chart of a geographic information data input and output processing method according to an embodiment of the present application, including steps 110 to 140.

[0020] Step 110: Obtain the first data cluster of the target object in the database.

[0021] For example, the first data cluster is read from the database and stored in the SourceData field of the project file.

[0022] In one embodiment of the present application, the data structure and attribute data of the target feature in the database are obtained as the first data cluster, which may include the location coordinates, range, name or feature type of the target feature.

[0023] For example, the data structure of the first data cluster includes: feature codes, attribute values, primitives or primitive groups, and symbolic codes.

[0024] The above-mentioned feature code refers to an identifier indicating the type or name of the feature; The attribute values ​​include the common attributes and primitive attributes of the feature. The common attributes include the overall description information of the feature, and the primitive attributes include the features of each primitive constituting the feature graph, such as feature point location information, primitive type, and display features.

[0025] The symbolized code specifically includes an algorithm for generating a display graphic of a feature using at least a portion of feature point location information, display features and / or primitive combination information of the feature in the first data cluster. In one embodiment, the symbolized code includes executable code for implementing primitive combination and display. In another embodiment, the symbolized code includes editable input information for triggering a graphic display program.

[0026] The display characteristics of the features refer to the visual manifestation of the features (such as buildings, roads, rivers, vegetation, etc.), which are represented by attribute values.

[0027] The primitive combination information refers to the combination of basic primitives (such as points, lines, and surfaces) of the features according to certain rules and logic to represent the structure of complex features. Furthermore, in order to record primitive features, the first data includes multiple feature point data, and the data of each feature point is represented by position information. These feature points include, for example, the endpoints of line primitives, the contour points of surface primitives, and multiple inflection points of primitives, etc. At least one of the feature points can be used to locate the entire primitive, primitive group, or the entire feature, and at least a portion of the feature point data is used as an input parameter of the symbolized code.

[0028] Step 120: In response to the instruction of the GUI, the first data cluster is segmented along a certain range line to generate at least one original sub-data cluster, and the association relationship between the original sub-data cluster and the first data cluster is determined.

[0029] In the embodiment of the application, preferably, according to any engineering requirement, the range line is generated in response to a GUI instruction, for example, by inputting the position coordinates of the range line through the GUI, or by capturing the position information of the manual operation track through the GUI to generate the range line.

[0030] The first data cluster is cut along a certain range line to form a new data cluster, which includes at least one original sub-data cluster. The original sub-data cluster refers to the small piece of feature elements after the target feature represented by the first data cluster of the target area is divided by the range line. The original sub-data cluster inherits the data structure of the first data cluster and can be used to display part of the graphics of the target area. In the data structure, information related to the target area can also be added, such as location coordinates or the first data cluster identifier. A parent-child relationship between the original sub-data cluster and the first data cluster is constructed to form an association relationship. For example, the first data cluster identifier can be used as data representing the association relationship between the original sub-data cluster and the first data cluster, and recorded in the original sub-data cluster or other intermediate files.

[0031] The range line can divide the target area into several parts, and the data structure of each regional feature unit can also contain its own contour range.

[0032] For example, the first data cluster D is split along a certain range line to generate at least one sub-data cluster D1 and D2. When the original sub-data cluster D2 is generated, the feature code of the original sub-data cluster is generated. The attribute value of the original sub-data cluster is inherited from the first data cluster. The feature points within the range line are taken out (if there are no feature points on the boundary where the range line and the feature intersect, one or more new feature points with the attribute information of the intersection boundary position can be generated in the original sub-data cluster). The symbolization code includes executable code, for example, how to implement the algorithm of primitive combination and display. It should be noted that when a sub-data D2 in the first data cluster is read, the sub-data D2 is generated for engineering update, but it is not necessary to generate a remaining data cluster D1. The first data cluster D is still retained in the original geographic information database.

[0033] When operations are performed on each part of the first data cluster separately, multiple sub-data clusters need to be generated. Figure 2-1 As shown, the display graph of the parent feature (data is the first data cluster) before the database feature data is downloaded, Item A and Item B represent 2 ranges, that is, the first data cluster is divided into two original sub-data clusters, which are updated by different teams respectively. The box point 210 and the arrow point 220 in the figure represent feature information points (i.e., feature points), where the arrow point is a closed point, that is, the point where the first and last points are connected.

[0034] Preferably, in step 120, after the first data cluster is segmented along a certain range line, step 120A and / or step 120B is further included.

[0035] Step 120A, generating an intermediate data set; the intermediate data set includes data indicating the association relationship between the first data cluster and the original sub-data cluster; In one embodiment, the first data cluster is cut according to the range line, and the cut result is stored in the engineering file as the base map data of the job, that is, the job data set includes the original sub-data cluster.

[0036] In one embodiment, the first data cluster and the original sub-data cluster and the data representing the association relationship are stored in the project file. For example, the identification mapping table representing the association relationship is stored in the DataMapTable public field of the project file.

[0037] The intermediate data set includes an original sub-data cluster that is consistent with the feature code of the first data cluster, and there is a correlation between the attribute values ​​of the two. For example, the attribute value of the first data cluster of a line feature includes length. The length attribute of the original sub-data cluster can be the length attribute value of the original first data cluster, or it can be the length attribute of the first data cluster minus the length attribute of the remaining part after the first data cluster is divided by a certain range line.

[0038] The intermediate data set stores data representing the association relationship. This has the advantage that when the result sub-data cluster is restored to replace the original sub-data cluster, it is easy to determine the first data cluster corresponding to the result sub-data cluster based on the association relationship.

[0039] In one embodiment, the intermediate data set may further include the remaining data cluster, and the association relationship between the remaining data cluster and the result sub-data cluster is determined by the feature codes or feature points of the remaining data cluster and the result sub-data cluster. In addition, the intermediate data set includes data indicating the association relationship between the remaining data cluster and the original sub-data cluster.

[0040] The advantage of the intermediate data set including the remaining data clusters is that when the result sub-data cluster is stored back, it is convenient to combine the result sub-data cluster with the remaining sub-data clusters, avoiding the temporary calculation of the difference between the first data cluster and the original sub-data cluster.

[0041] Step 120B: processing the original sub-data cluster segmentation points and changing the symbolic code.

[0042] It can be understood that the line primitives in the ground feature are divided by the segmentation line to form breakpoints. When there is no feature point at the breakpoint, the feature point should be added at the breakpoint in the original sub-data cluster to avoid losing the graphic features between the breakpoint and the nearest feature point when the symbolization code is executed.

[0043] Preferably, in response to the range line indication of the GUI, the feature point closest to the range line indication information is found, and the generated range line passes through the feature point. In this way, the original feature point information is included at the breakpoint in the original sub-data cluster to avoid losing the graphic features between the breakpoint and the nearest feature point when the symbolized code is executed.

[0044] In one embodiment, preferably, when generating the original sub-data clusters, in the parameters of the symbolized code, the feature point information outside the range line is removed. It can be understood that if the feature point information outside the range line is retained in the parameters of the symbolized code of each original sub-data cluster, the cut sub-data cluster will be too large, so the symbolized code at least changes the feature point set used as the input parameter.

[0045] like Figure 2-2As shown, the symbol styles of the two project ranges formed by cutting and downloading according to the range line have not been updated and produced, but the symbols are inherited within their respective ranges. The child feature elements (represented as the original child data cluster) after the parent feature element of the database is split and downloaded, establish a parent-child relationship and store it, but still inherit the symbol style and feature point information of the parent feature element. However, in order to ensure the correct display of the symbol style, the child feature element must also be supplemented with data. Therefore, there are changes in the original child data cluster during the segmentation process. For example, the project A area adds a box point 210, and the project B area adds an arrow point 220, that is, the closing point must also exist. In this way, the node trend sequence of the child feature element and the parent feature element are the same, and the display graphic style is consistent.

[0046] Step 130: Obtain the result data cluster.

[0047] The original sub-data clusters within a project are tested and repaired to determine the result sub-data clusters. For example, the new data clusters are loaded into the memory and tested and repaired by production operations to form the result sub-data clusters.

[0048] The achievement sub-data cluster is stored in an achievement graph data file, and an association relationship between the achievement sub-data cluster and the first data cluster is established.

[0049] The result sub-data cluster may be an adaptation made based on the original sub-data cluster. For example, after the target area is divided by the range line, the divided original sub-data cluster is stored in the data file of the operation and measurement. As the operation and measurement of the features represented by the original sub-data cluster are carried out, the modified content enters the original sub-data cluster, and finally forms the result sub-data cluster.

[0050] It should be noted that the present application does not care about how to edit the original sub-data cluster to generate the result sub-data cluster. The method or device of the present application is to use the result sub-data cluster as a trigger condition, for example, to obtain the result sub-data cluster in the project file through a dedicated data interface or in response to a restore instruction, such as Figure 5 Achievement graph dataset 550 is shown.

[0051] Preferably, step 130 also includes step 130A.

[0052] Step 130A, after obtaining the achievement sub-data cluster, compare the achievement sub-data cluster with at least one of the feature codes, attribute values ​​and symbolic codes of the original sub-data cluster in the intermediate data set to determine the association relationship between the first data cluster and the achievement sub-data cluster.

[0053] The original sub-data cluster is updated by the result sub-data cluster operation data set to obtain the result sub-data cluster, and the result sub-data cluster is compared with the original sub-data cluster stored in the intermediate data set to determine the first data cluster associated with the result sub-data cluster.

[0054] Step 140: merge the resultant sub-data cluster with the remaining data cluster of the first data cluster excluding the original sub-data cluster to obtain a second data cluster and store it back to replace the first data cluster in the database.

[0055] Take out the elements that are not related to the scope line from the newly added and modified feature sets, directly update the database, and remove the elements from the corresponding feature sets. For the remaining elements in the database data feature set, add them to the pending feature set according to whether they intersect with the scope line. The pending feature set contains multiple result sub-data clusters.

[0056] For example, the resultant sub-data cluster D2' covers the portion of the original sub-data cluster D2, and is added to the feature point difference set of the first data cluster D and the original sub-data cluster D2 to obtain the second data cluster D' and store it back to replace the first data cluster in the database.

[0057] Furthermore, when displaying, the data and graphics of the same land feature in the first data cluster and the result sub-data cluster outside the scope of a certain project are merged and processed.

[0058] Before data merging, the original sub-data cluster and the result sub-data cluster can be searched and checked by position relationship without relying on the intermediate data set. For example, if the position difference between the result sub-data cluster and the original sub-data cluster is less than the set threshold, the result sub-data cluster is considered to be the original sub-data cluster after the update operation.

[0059] For example, determining that the elements in the first data cluster and the result sub-data cluster belong to the same geographical feature specifically comprises the steps of: classifying the geographical elements of the first data cluster and the result sub-data cluster according to the coding; The latest data cluster of the library is obtained from the database, and the achievement sub-data cluster and the latest data cluster of the library are classified according to the element code to form an element set. It should be noted that the latest data cluster refers to the first data cluster before the first data cluster is split, or when the first data cluster is not modified according to the achievement sub-database. After the first data cluster is modified according to the achievement sub-data cluster, the second data cluster obtained is the latest data cluster of the library, and so on. That is, the parent data cluster in the database is updated to be the latest data cluster of the library according to different operations. It can be understood that when multiple original sub-data clusters split from the first data cluster each generate achievement sub-data clusters, they can be merged and stored back to the original database one after another.

[0060] The parameters of the classified results are compared to determine whether the elements belong to the same feature; the compared parameters include spatial information and attribute information. The classified results are compared spatially and attributively, and then the inconsistent elements are physically connected along the project scope.

[0061] Based on the production achievement element set, search element by element to see if there are similar elements in the same spatial position in the library element set. If there are similar elements, compare the two elements according to the spatial point list and information and attribute information. Otherwise, compare the next element. An initial threshold can be set for the position. The initial threshold, for example, determines the distance between elements that can be automatically joined, that is, if it is a line, the distance between the end points of the line can be determined to be the same element. After it can be determined to be the same element, it is determined whether the attributes are the same. If they are the same, they can be automatically joined and merged.

[0062] Preferably, in step 140, after determining the association relationship between the first data cluster / the remaining data cluster and the result sub-data cluster, it is necessary to determine whether the result sub-data cluster has changed compared with the original sub-data cluster.

[0063] In the optimized embodiment of the present application, in response to the change between the result sub-data cluster and the original sub-data cluster, the data merging and restoring of step 140 is performed, otherwise the feature data is not merged and restored. The original sub-data cluster and the result sub-data cluster can be determined to be different based on the change of the data content or timestamp.

[0064] In one of the embodiments, it is determined whether the result sub-data cluster and the original sub-data cluster have changed, and the data contents of the original sub-data cluster and the result sub-data cluster are compared to see whether they are the same.

[0065] The data content includes feature codes, attribute values ​​or symbolic codes; usually, the feature codes of the original sub-data cluster and the result sub-data cluster do not change, but there are cases where the feature codes are changed due to operations. Therefore, if the feature codes are changed, it is considered that the result sub-data cluster and the original sub-data cluster are changed.

[0066] For example, two elements are compared according to feature points, spatial information and attribute information: If the spatial information and attribute information are consistent, the feature is considered unchanged and no update is performed.

[0067] If the spatial information is consistent but the attribute information is different, then the feature (result sub-data cluster) is added to the modified feature set, the corresponding parent feature (first data cluster) is added to the modified feature set, and the modified feature is taken out from the database feature set or intermediate data set. If the spatial information is inconsistent, then the feature is added to the parent feature corresponding to the newly added feature set.

[0068] For example, Figure 2-3 As shown, Figure 2-3It is a new data cluster formed after the update and production, which is used to replace the original data cluster. After the sub-features are downloaded and updated, the changed features are found through the parent-child relationship. By comparison, it is found that the sub-features in project A have not changed, while the features in project B have changed. In this case, the two sub-features need to be merged to replace the parent feature. If it is judged as an associated feature, it will automatically be connected to form a new feature (i.e., the second data cluster) that replaces the original parent feature, and still inherits the characteristic points of the sub-features, maintaining the main rules of the symbol effect unchanged.

[0069] For example, a feature change includes changes in spatial information (a) and attribute information (b). The main ways of feature change are unchanged, modified, added, and deleted. The parent-child relationship is recorded when splitting and downloading. Which type of change it belongs to needs to be determined through comparison. For example, if no relationship is found for a feature element after the update, it is defined as added and can be directly updated to the original database. For another example, if a feature element is deleted or modified and a relationship is found, the spatial information is compared first. If the spatial information is consistent, it is defined as modified, because modification can also be understood as deleting the original information and adding a new one. Therefore, as long as the spatial information changes, it is treated as deletion and addition. The combination of the two (according to a and b) has four types of changes: ① a and b both change, ② a and b do not change, ③ a changes but b does not change, ④ b changes but a does not change. Among them, ② does not need to be updated and the library element remains unchanged, that is, the parent feature element before being split does not need to be updated and only needs to be maintained as it is.

[0070] ④ If the spatial information remains unchanged but the attribute information has changed, it can be directly defined as the modified element. That is, the actual location and range of the feature have not changed, but only one of the attribute information has changed, such as the name field. Extract the parent feature in the database, directly modify this attribute and then replace it back; In both ① and ③, the spatial information has changed, so the updated features (represented as the second data cluster) are directly treated as newly added features, that is, the association is found, so the parent feature of the changed child feature (represented as the first data cluster) is found, the parent feature is deleted, and the corresponding newly added feature is used as a new feature to replace the parent feature to achieve update; In one embodiment, it is determined whether the timestamp in the result sub-data cluster has changed. Because after the data cluster is modified, the attribute value of the feature element or the attribute value of the primitive containing the creation and update time is generated, it can be determined that the result sub-data cluster has changed compared with the original sub-data cluster by the change of the timestamp.

[0071] It should be noted that after the intermediate data set is generated, the intermediate data set can be read for comparison, which can avoid reading information from the database for comparison and improve data security. The intermediate data set here can be cached data or a stored project file.

[0072] like Figure 2-4 As shown in the figure, after being judged as an associated element, it will automatically "join" to form a new element that replaces the original parent feature element, still inheriting the characteristic points of the child feature element, and maintaining the main rules of the symbol effect unchanged.

[0073] Data joints are generally divided into geometric joints (to solve the problem of geometric cracks, which means that the two parts of a feature separated by the boundary of the data file cannot be accurately connected), logical joints (to solve the problem of logical cracks, which means that the same feature has different codes or different attribute information, such as the width of the road, the elevation of the contour line, etc.) and physical joints (to achieve physical seamlessness, to ensure that each geographic element is not only geometrically seamless and logically seamless, but also truly merged into the same geographic element with the same attributes).

[0074] Furthermore, in step 140, the merging processing method of the remaining data clusters in the first data cluster outside the scope of a certain project and the same ground feature graphic in the result sub-data cluster includes any one of the following: Step 140A: perform geometric edge joining along the range line.

[0075] The feature point set of the result data cluster is combined with the feature point set of the remaining data cluster, and the position information of the feature points generated by segmentation of a certain range line in the feature point set of the result data cluster is adjusted to make it coincide with the position information of the feature points generated by segmentation of a certain range line in the remaining data cluster, so as to form the feature point set of the second data cluster.

[0076] The original sub-data cluster is updated to the result sub-data cluster through the operation, which may cause misalignment with the remaining data clusters in display.

[0077] The reason for the misalignment is, for example, when the first data cluster D is decomposed into the remaining data cluster D1 and the original sub-data cluster D2, the boundary point must generate a feature point, and the position attribute of the feature point may change when the original sub-data cluster is edited.

[0078] Therefore, it is necessary to geometrically join the feature point set of the resultant data cluster D2' with the feature point set of the remaining data clusters to form the feature point set of the second data cluster D'.

[0079] The physical edge connection needs to merge the breakpoints of the first data cluster divided by the range line. There are two situations for breakpoint merging: there are feature points at the original segmentation breakpoints, or there are no feature points at the original segmentation breakpoints.

[0080] There is no feature point at the breakpoint where the first data cluster is divided by the range line, and the original sub-data cluster generates a feature point at the breakpoint, then during the merging process, the feature point at the breakpoint of the second data cluster is deleted; There is a feature point at the breakpoint where the first data cluster is divided by the range line, and in the second data cluster, the feature points of the result sub-data cluster and the first data cluster at the breakpoint are merged into one feature point.

[0081] After the feature points at the breakpoints are segmented, the data represented by one feature point becomes two feature points, that is, the positions of the feature points in the original sub-data cluster and the feature points in the first data cluster are the same. Due to the operation, the data of the two feature points are different, so the two feature points need to be merged into one feature point to make the two feature points have the same attributes. You can take only one feature point (for example, the point in the result sub-data cluster) as the merged feature point, or you can take the average value of the two positions to merge the two feature points into one point.

[0082] Step 140B: perform attribute edge joining along the range line.

[0083] The attribute edges include logical edges and physical edges.

[0084] The logical connection refers to the formation of different feature codes when editing the result sub-data cluster, and setting the feature code of the result sub-data cluster to be the same as the feature code of the first data cluster when merging.

[0085] The logical edge connection, for example, in response to the fact that the graphic positions on both sides of the range line do not correspond and belong to the same land feature, physically connects the elements. The public attribute information of the result data cluster and the remaining data cluster is set to be the same, and at least a part of the primitive attribute expression data is set to be the same.

[0086] In this way, the complete graphic of the geographical feature element is used to replace the spliced ​​graphic of the geographical feature element in the first data cluster and the result sub-data cluster.

[0087] Figure 3 The symbolic reshaping flowchart provided for the embodiment of the present application further includes steps 250 to 260 based on steps 110 to 140 (i.e., steps 210 to 240 shown in the figure), to generate a symbolic code of the second data cluster to replace the symbolic code of the first data cluster.

[0088] Step 250: Combine the remaining data clusters and at least a portion of the feature points of the resultant data cluster into a symbolic code input data set.

[0089] The feature type can be determined by feature coding, and each feature has a corresponding attribute value. The symbolization algorithm combines the feature point set of the remaining data cluster with the feature point set of the result sub-data cluster, and determines the position features, display features and / or primitive combinations of the merged feature point set, thereby generating a symbolic code for the second data cluster. The merged feature point set contains all or at least part of the feature points of the remaining data cluster and the result sub-data cluster before the merger. These feature points are the feature points that play a role in generating the feature graphics, and contain the data used by the symbolization code.

[0090] The characteristic points generally include the first and last points of the features, that is, the closing points of the contours of the maximum range; and the internal empty islands that form the closing points of the inner ring of the torus; if there are multiple empty islands, there are multiple closing points of the inner ring; it also includes characteristic point identification information for special display effects on the symbolization effect, such as vanishing points, turning points, virtual-real dividing points, etc. It uses its own symbolization algorithm to read and inherit the original characteristic points, and combines the new coordinate data cluster to redisplay the symbol information. For individual places where the redisplay is very different from the original image, dynamic adjustments are made within a certain threshold so that the part overlapping with the original symbol is maximized to be close to the original value without adjusting the range.

[0091] It should also be noted that different types of features have different graphic representations, so different symbolization algorithms can be determined according to the feature code. It should be noted that the symbolization algorithm for each type of feature is preset, which can identify all feature points that constitute the feature elements, select attribute data that are useful for constructing the feature graphic symbol, select or generate the primitives or primitive combinations that constitute the feature graphic symbol, and determine the display characteristics of the primitives that constitute the feature graphic symbol, such as color, line type, hidden, position distribution, etc.

[0092] Step 260: Determine the position features, display features and / or primitive combinations of the merged feature point set, and generate a symbolic code for the second data cluster.

[0093] In step 260, after the newly added feature set and the undetermined feature set are physically connected along the range line, the symbol effect of the successfully merged feature is restored: For example, after the feature data is merged, the symbolic information is merged, which specifically includes the following steps: Step 260A: Obtain symbolic information of the feature elements of the result data cluster.

[0094] The symbolic information includes a symbolic code, an input data set that triggers the code, and a true value of the symbolic effect.

[0095] Obtain the associated feature elements corresponding to the adjacent feature elements, and the symbolization effect of the same spatial position, and use it as the true value of the symbolization effect; the associated feature elements can be two sub-feature elements that have a mutual connection relationship, that is, the sub-feature elements on both sides of the range line, and one sub-feature element is the associated element of the other sub-feature element, thereby determining the result sub-data cluster and the first data cluster and / or remaining data cluster associated therewith.

[0096] The symbolized effect true value is an output value representing the combination of primitives, display characteristics, and location characteristics, and then the symbolized effect of the child feature element is used to eventually replace the effect of the parent feature element. Since it is confirmed that the symbolized effect of the parent feature element has changed and cannot be used anymore, it is necessary to merge the child feature element to replace the parent feature element. Therefore, the symbolized effect of the child feature element can replace the effect of the parent feature element through the symbolized effect true value.

[0097] Step 260B: fuse the symbolized information to form a true value of the symbolized effect of the second data cluster.

[0098] The symbolic information of the part of the feature elements in the database outside the scope of the reserved project (i.e. the remaining data cluster) is obtained and merged with the symbolic information of the feature elements in the result sub-data cluster.

[0099] For example, the closed points of the elements after the edges are connected are restored according to the spatial positions. Another example is to restore the island information and merge the islands. The island information is applicable to surface features, that is, the holes in the surface features. A surface can draw two closed loops through continuous lines. If a range line just cuts the closed loop in half, the island information must be restored when merging. For another example, the framework information of the feature is restored according to the spatial position, and the threshold is dynamically adjusted to select and cancel the symbol effect whose hidden symbolization effect is closest to the true value to retain the feature framework information of its node; for another example, the hidden, dotted line, feature and other information of the feature is restored; and the cross-symbol effects of special nodes are processed, etc., which are not enumerated here one by one.

[0100] The information (software level) of the correct display of the ground feature elements according to the schematic symbols and the requirements of the topographic map, according to the closure information, point sequence, framework information, ground feature information, hidden information, dotted line information, etc., can be further adjusted according to the given threshold to form a new symbol effect, and the true value of the symbol effect is scored. The optimal symbolization scheme is obtained, and the symbolization information of the element is reset.

[0101] It should be noted that the above configuration process is automatically completed through a symbolization algorithm. For each type of land feature, according to the description of the feature points of the land feature, the feature points and primitives in the land feature element data cluster are selected and processed by a symbolization algorithm dedicated to the land feature to generate the display graphics of the land feature. In combination with the symbolization information of the first data cluster, the result sub-data cluster and / or the second data cluster library, the correct display information of the land feature element symbol is determined. Preferably, the present application may choose to use a set of symbolization codes to process the graphics of the second data cluster, rather than using two sets of symbolization codes to process the graphics of the result data cluster and the remaining data cluster respectively; further, the present application may choose to use the primitive attributes of the display effect in the symbolization code of the result data cluster to replace the primitive attributes of the display effect in the symbolization code of the first data cluster, and generate the symbolization code of the second data cluster. Then, the attribute information related to the display is adjusted according to the set threshold to determine the new symbol effect.

[0102] In surveying and mapping production, many still use a production method in which graphics and databases are separated, which results in low work efficiency and inability to obtain sufficiently up-to-date data in combination with their own funding costs. However, the actual annual changes in a city are limited, especially in areas with a high degree of urbanization. Therefore, the method and device of the present application fully consider the actual production situation, and integrate outbound downloading, updating warehousing, automatic edge connection, and symbolized graphics into one process, so as to achieve real-time updates of a city according to its specific update scope, such as according to the completed area, thereby truly reducing unnecessary production inputs to ensure that the data in this area is sufficiently up-to-date, and making the data have a higher use value to meet other application needs.

[0103] Figure 4 This is a structural diagram of a geographic information data in-and-out processing device according to an embodiment of the present application, which is used to implement the geographic information data in-and-out processing method according to any embodiment of the present application, including: The acquisition module 410 is used to acquire the first data cluster of the target feature in the database; and is also used to acquire the result sub-data cluster.

[0104] The generating module 420 is used to split the first data cluster along a certain range line in response to the instruction of the GUI to generate at least one original sub-data cluster.

[0105] The determination module 430 is configured to determine an association relationship between the original sub-data cluster and the first data cluster.

[0106] The merging module 440 is used to merge the resultant sub-data cluster with the remaining data cluster of the first data cluster excluding the original sub-data cluster, obtain the second data cluster and store it back to replace the first data cluster in the database.

[0107] In one of the embodiments, the acquisition module further includes a first acquisition unit, which is used to acquire a first data cluster of the target object in the database.

[0108] In one of the embodiments, the generation module further includes a first generation unit, which is used to split the first data cluster along a certain range line in response to an instruction of the GUI to generate at least one original sub-data cluster.

[0109] In one of the embodiments, the acquisition module further comprises a second acquisition unit for acquiring a result sub-data cluster.

[0110] In one of the embodiments, the determination module further includes a first determination unit, configured to determine an association relationship between the original sub-data cluster and the first data cluster.

[0111] In one embodiment, the generation module further comprises a second generation unit for merging the result sub-data cluster with the remaining data cluster of the first data cluster excluding the original sub-data cluster to obtain a second data cluster and store it back to replace the first data cluster in the database.

[0112] In one of the embodiments, the generation module further includes a third generation unit for generating an intermediate data set.

[0113] Specifically, it is used to realize any function of determining the intermediate data set in steps 120 to 140.

[0114] In one embodiment, the generation module further includes a fourth generation unit, which is used to merge the resultant data cluster with the remaining data cluster, including any of the following situations: There is no feature point at the breakpoint where the first data cluster is divided by the range line, the original sub-data cluster generates a feature point at the breakpoint, and the feature point at the breakpoint in the second data cluster is deleted; There are feature points at the breakpoints where the first data cluster is divided by the range line, and the feature point attributes of the resultant sub-data cluster and the first data cluster at the breakpoints are merged in the second data cluster.

[0115] Specifically used to implement any function in step 140A.

[0116] In one of the embodiments, the generation module further comprises a fifth generation unit, which sets the feature code of the resultant data cluster to be the same as the feature code of the first data cluster.

[0117] The public attribute information of the result data cluster and the remaining data clusters are set to be the same, and the primitive attribute expressions are set to be the same.

[0118] Specifically used to implement any function in step 140B.

[0119] In one of the embodiments, the generation module further comprises a sixth generation unit, which is used to merge the remaining data clusters with all feature point sets of the resultant data clusters.

[0120] The determination module further includes a second determination unit, which is used to determine the position features, display features and / or primitive combinations of the merged feature point set, and generate a symbolic code of the second data cluster.

[0121] Specifically used to implement any function in steps 250~260.

[0122] In one embodiment, the determination module further includes a third determination unit, which is used to determine the association relationship between the remaining data cluster and the result sub-data cluster by comparing the feature codes or feature points of the remaining data cluster and the result sub-data cluster when the intermediate data set also includes the remaining data cluster.

[0123] Specifically, it is used to realize any function of determining in steps 120 to 140 that the intermediate data set also includes the remaining data cluster.

[0124] In one embodiment, the determination module further includes a fourth determination unit for comparing data content or timestamps of the original sub-data cluster and the result sub-data cluster; determining that the data content has changed, or the timestamp has changed, and the original sub-data cluster and the result sub-data cluster are different.

[0125] Specifically, it is used to implement any function of determining whether the result sub-data cluster and the original sub-data cluster are changed in steps 120 to 140.

[0126] The determination module further includes a fifth determination unit for determining a merging method, wherein the merging method includes physically connecting edges along the range line; and replacing the spliced ​​graph of the feature element in the first data cluster and the result data cluster with the complete graph of the feature element.

[0127] Specifically, it is used to implement any function of the same land feature graphic merging processing method in step 140B.

[0128] In one embodiment, the determination module further comprises a sixth determination unit, which is used to classify the geographic elements of the first data cluster and the result data cluster according to the coding, and is also used to compare the spatial and attribute parameters of the two.

[0129] Specifically, it is used to implement any function of determining in step 140 that the elements in the first data cluster and the result data cluster belong to the same land feature.

[0130] Furthermore, the fifth determination unit and the sixth determination unit are also used to compare the spatial and attribute parameters of the geographic elements of the first data cluster and the resultant data cluster to determine the physical edge connection mode, which is specifically used to realize any function of the physical edge connection mode.

[0131] In one embodiment, the determination module further comprises a seventh determination unit for determining the second data cluster; the generation module further comprises a seventh generation unit for merging the first data cluster and the result data cluster. Specifically, it is used to realize any function of comparing two elements according to spatial point sequence and information and attribute information.

[0132] In one embodiment, the generating module further comprises an eighth generating unit for merging symbolic information, specifically for implementing any function described in step 260 .

[0133] In one embodiment, a geographic information database 450 is further included, and the geographic information database is used to store the ground feature data in the target area before and after the update.

[0134] Figure 5 The present application also provides a system for processing geographic information data, which is used to implement the method described in any one of the embodiments of the present application, including: a geographic information database 510, a data processor 520, a GUI operation interface 530, an application terminal 540, and at least one result map data set 550.

[0135] The geographic information database is used to store target geographic information data.

[0136] The GUI operation interface and / or application terminal is used to input setting conditions and trigger the data processor to run the acquisition module, determination module, generation module or merging module. The data processor, in response to the instruction of the GUI, obtains the target area project range attribute data and determines the range line through the project range attribute data; the geographic information database is used to store the relevant data of the target land feature, including the first data cluster and the second data cluster.

[0137] It should be understood that the above-mentioned specific related contents are only used for illustrative purposes and should not impose any limitation on the present application.

[0138] The specific method for implementing the functions of the above modules is as described in the various method embodiments of the present application and will not be repeated here.

[0139] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. For example, in Figure 5 The application system shown loads the computer program product of the method of the present application. The computer program product includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the method described in any embodiment of the present application is implemented.

[0140] Therefore, the present application also proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present application is implemented.

[0141] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0142] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0143] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0144] Furthermore, the present application also proposes an electronic device (or computing device), comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present application when executing the computer program.

[0145] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory. Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium. Computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device. According to the definition in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0146] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0147] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for processing geographic information data in and out of a database, characterized in that: Contains steps: Obtain the first data cluster of the target object in the database; In response to an instruction of the GUI, the first data cluster is segmented along a certain range line to generate at least one original sub-data cluster, and an association relationship between the original sub-data cluster and the first data cluster is determined; Get the result data cluster; The resultant sub-data cluster is merged with the remaining data cluster of the first data cluster excluding the original sub-data cluster to obtain a second data cluster, which is stored back to replace the first data cluster in the database.

2. According to claim 1, the method for processing geographic information data in and out of the database is characterized in that: After the first data cluster is split along a certain range line and before the second data cluster is restored, the method further comprises the following steps: An intermediate data set is generated; the intermediate data set includes data representing the association relationship between the first data cluster and the original sub-data cluster.

3. The method for processing geographic information data in and out of a database according to claim 1, characterized in that: The method further comprises the steps of: generating an intermediate data set; wherein the intermediate data set comprises the remaining data clusters and data indicating the association relationship between the remaining data clusters and the original sub-data clusters.

4. The geographic information data storage and retrieval processing method according to claim 1, characterized in that: The result data cluster is merged with the remaining data clusters, including any of the following situations: There is no feature point at the breakpoint where the first data cluster is divided by the range line, the original sub-data cluster generates a feature point at the breakpoint, and the feature point at the breakpoint in the second data cluster is deleted; There are feature points at the breakpoints where the first data cluster is divided by the range line, and the feature point attributes of the resultant sub-data cluster and the first data cluster at the breakpoints are merged in the second data cluster.

5. The geographic information data storage and retrieval processing method according to claim 1, characterized in that: Also includes at least one of the following: The feature code of the result data cluster is set to be the same as the feature code of the first data cluster; At least a part of the attributes of the graphic elements of the resultant data cluster and the remaining data cluster are set to be the same.

6. The geographic information data storage and retrieval processing method according to claim 1, characterized in that: Also includes the steps: Merging the remaining data clusters with the feature point set of the resultant data cluster; The position feature, display feature or graphic element combination of the merged feature point set is determined to generate a symbolic code of the second data cluster.

7. The geographic information data storage and retrieval processing method according to claim 1, characterized in that: The data contents or timestamps of the original sub-data cluster and the resultant sub-data cluster are compared to determine whether the data contents or timestamps have changed.

8. A geographic information data storage and retrieval processing device, characterized in that: The method for processing geographic information data in and out of a database according to any one of claims 1 to 7 comprises: An acquisition module is used to acquire the first data cluster of the target object in the database; and is also used to acquire the result sub-data cluster; A generating module, configured to split the first data cluster along a certain range line in response to an instruction of the GUI, and generate at least one original sub-data cluster; A determination module, used to determine the association relationship between the original sub-data cluster and the first data cluster; The merging module is used to merge the result sub-data cluster with the remaining data cluster of the first data cluster excluding the original sub-data cluster, obtain the second data cluster and store it back to replace the first data cluster in the database.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

Images