A method and system for generating a surveying and mapping graph

Abstract

The present invention relates to a method and system for generating a surveying and mapping graph. The method for generating a surveying and mapping graph includes, after obtaining the input graph node data set, parsing the graph node data set, and splitting the graph node data set into several sub-data sets based on the original sequential relationship; selectively loading or not loading each node data in several sub-data sets in the graph node data set according to the current scale; connecting the loaded node data in the order relationship in the graph node data set to generate a closed surveying and mapping graph. It can reduce the amount of data loaded at one time when generating a surveying and mapping graph, and effectively improve the generation efficiency of the surveying and mapping graph.

Description

Technical Field

[0001] The present invention relates to the field of surveying and mapping, and particularly to a method and system for generating surveying and mapping graphics. Background Art

[0002] Through the integration of immovable property cadastral data, the efficient progress of immovable property registration work can be achieved. During the investigation process of immovable property cadastre, it includes stages such as ownership investigation, immovable property measurement, and result warehousing. And in many stages, it involves data viewing or graphic production. A large amount of immovable property cadastral data is integrated into the same system. Although it provides convenience for information verification and analysis, in practical applications, it also faces problems such as a large amount of data loading and low viewing efficiency. Summary of the Invention

[0003] The purpose of this application is to propose a method and system for generating surveying and mapping graphics to solve the problem of low data loading and viewing efficiency after a large amount of immovable property cadastral data is integrated into the same system.

[0004] The surveying and mapping graphics generation method of this application includes:

[0005] After obtaining the input graphic node data set, parse the graphic node data set, and divide the graphic node data set into several sub-data sets on the basis of the original sequential relationship. The graphic node data set includes several node data recorded in sequence, and the node data corresponds to the inflection points of the surveying and mapping graphics;

[0006] After receiving the graphic generation instruction, obtain the current scale;

[0007] Load the node data of the graphic node data set. Among them, according to the current scale, selectively load or not load each of the node data in several sub-data sets of the graphic node data set;

[0008] Connect the loaded node data in the sequential relationship in the graphic node data set to generate a closed surveying and mapping graphic.

[0009] Optionally, the step of parsing the graphic node data set and dividing the graphic node data set into several sub-data sets on the basis of the original sequential relationship includes:

[0010] Perform a morphological influence degree analysis on each node data recorded in the graphic node data set;

[0011] Divide several consecutive node data into sub-data sets according to the results of the morphological influence degree analysis.

[0012] Optionally, the step of dividing a number of consecutive pieces of the node data into subsets according to the result of the morphological influence degree analysis includes:

[0013] Determine subsets at different levels according to different morphological influence degree situations.

[0014] Optionally, the step of selectively loading each piece of the node data in a number of subsets in the graphic node dataset according to the current scale includes:

[0015] Determine the morphological influence degree level corresponding to the current scale, load the subset at the smallest level within the subset corresponding to the current morphological influence degree level, and skip subsets at smaller levels.

[0016] Optionally, after connecting each piece of the loaded node data in sequence in the graphic node dataset to generate a closed surveying and mapping graphic, the following steps are further included:

[0017] After receiving an instruction for scale change, obtain the updated scale;

[0018] In the case of scale reduction, directly adjust the scale based on the currently loaded data;

[0019] In the case of scale enlargement, determine whether the morphological influence degree level corresponding to the scale changes; when the morphological influence degree level corresponding to the scale changes, based on the part still displayed on the screen, supplement and load the subset at the smallest level within the subset corresponding to the current morphological influence degree level; regenerate a closed surveying and mapping graphic based on the supplemented and loaded node data.

[0020] Optionally, the step of dividing the graphic node dataset into a number of subsets on the basis of the original sequence relationship includes:

[0021] Insert a subset identifier into the graphic node dataset. The subset identifier is inserted before the first piece of node data in the subset, and the subset identifier records the number of data in the subset.

[0022] Optionally, during the process of loading the node data in the graphic node dataset, if the subset identifier is encountered, determine whether to load the node data in the corresponding subset;

[0023] If not, directly skip the corresponding subset according to the number of data in the subset recorded by the subset identifier.

[0024] Optionally, the step of performing a morphological influence degree analysis on each piece of node data recorded in the graphic node dataset includes:

[0025] Traverse the node data, and define each node data whose turning angle of the connection line compared with the previous two node data is greater than a set angle as a large turning node;

[0026] Determine the connection lines between each of the large turning nodes and other large turning nodes;

[0027] Determine the maximum distance between several pieces of the node data between the connection lines and the connection lines as the value of the shape influence degree corresponding to the connection lines.

[0028] Optionally, the dividing several consecutive pieces of the node data into subsets according to the result of the shape influence degree analysis includes:

[0029] Divide each of the node data between the connection lines with the shape influence degree within a set range into the same subset as much as possible.

[0030] On the other hand, the present invention further provides a mapping graph generation system, including:

[0031] A node data analysis module, configured to, after obtaining an input graph node data set, parse the graph node data set, and divide the graph node data set into several subsets on the basis of the original sequential relationship, where the graph node data set includes several pieces of node data recorded in sequence, and the node data corresponds to the inflection points of the mapping graph;

[0032] An instruction acquisition module, configured to acquire a graph generation instruction, and after receiving the graph generation instruction, acquire the current scale;

[0033] A data loading module, configured to load the node data of the graph node data set, where, according to the current scale, selectively load or not load each of the node data in several subsets of the graph node data set;

[0034] A graph generation module, configured to connect the loaded node data in the order relationship in the graph node data set to generate a closed mapping graph.

[0035] The mapping graph generation method provided by the present invention parses the graph node dataset, divides the graph node dataset into several sub-datasets on the basis of the original sequential relationship, and selectively loads or does not load each of the node data in several of the sub-datasets in the graph node dataset according to the current scale; thereby generating a mapping graph. Since the sequential relationship of the node data remains unchanged all the time, therefore, although some data is not loaded, the mapping graph formed by connection will be able to be basically within the original range, and based on the data selected during loading, the general shape of the mapping graph can be effectively reflected in some implementation processes. It is possible to reduce the amount of data loaded at one time when generating the mapping graph, and effectively improve the generation efficiency of the mapping graph. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a schematic diagram of the basic process of the mapping graph generation method of this embodiment;

[0037] Figure 2 is a schematic diagram of the detailed process of the mapping graph generation method of this embodiment Figure 1 ;

[0038] Figure 3 is a schematic diagram of the node data division of the mapping graph generation method of this embodiment Figure 1 ;

[0039] Figure 4 is a schematic diagram of the node data division of the mapping graph generation method of this embodiment Figure 2 ;

[0040] Figure 5 is a schematic diagram of the detailed process of the mapping graph generation method of this embodiment Figure 2 ;

[0041] Figure 6 is a complete schematic diagram of the mapping graph of the example provided by the mapping graph generation method of this embodiment;

[0042] Figure 7 is Figure 6 a schematic diagram of a large turning point node;

[0043] Figure 8 is Figure 7 a partial connection schematic diagram of a large turning point node;

[0044] Figure 9 is a mapping graph result generated based on the mapping graph data at a certain scale Figure 6 ;

[0045] Figure 10 is a mapping graph result generated based on the mapping graph data at another scale Figure 6 ;

[0046] Figure 11 This is a schematic structural diagram of the mapping graphic generation system of this embodiment. Specific implementation manners

[0047] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0048] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0049] Embodiment 1:

[0050] This embodiment provides a mapping graphic generation method. As shown in Figure 1 the following, this method includes but is not limited to the following steps:

[0051] S101. After obtaining the input graphic node dataset, parse the graphic node dataset and split the graphic node dataset into several sub-datasets on the basis of the original sequential relationship;

[0052] The graphic node dataset is usually coordinate data on the boundary of real estate information, such as the coordinate data of a land parcel graphic. In this application, it is referred to as node data, which corresponds to the inflection points of the mapping graphic. When relevant personnel view the land parcel graphic, the corresponding land parcel graphic data is read and converted into a vector graphic for display according to these coordinate data.

[0053] The graphic node dataset includes several node data, and these node data are recorded in sequence. The coordinates corresponding to adjacent node data are connected to present an accurate mapping graphic.

[0054] S102. After receiving a graphic generation instruction, obtain the current scale;

[0055] The graphic generation instruction can be that the system interface is opened or the user selectively retrieves the surveying and mapping data within a certain range. This system is usually a GIS (Geographic Information System) system, and in practical applications, it can also be any other system that needs to call surveying and mapping data. This embodiment does not limit.

[0056] When it is necessary to retrieve the surveying and mapping data, usually, an appropriate scale will be determined for display according to the range to be displayed. In the traditional process of generating surveying and mapping graphics, the graphic node data set of all the surveying and mapping graphics to be generated within the range will be retrieved, all the node data therein will be loaded, and the surveying and mapping graphics will be generated accordingly. Since a large amount of data is integrated in the GIS system and the displayed range is large when the scale is too large, the loading of these data will affect the display speed of the surveying and mapping graphics and the viewing efficiency.

[0057] S103. Load the node data of the graphic node data set, where, according to the current scale, selectively load or not load the node data in several sub-data sets in the graphic node data set;

[0058] In this embodiment, when loading the node data of the graphic node data set, it is possible to selectively load some of the node data based on the scale situation, thereby reducing the amount of data loaded during a single graphic generation and effectively accelerating the efficiency during graphic generation.

[0059] S104. Connect the loaded node data in the order relationship in the graphic node data set to generate a closed surveying and mapping graphic;

[0060] Since the order relationship of the node data always remains unchanged, therefore, although some data is not loaded, the surveying and mapping graphic formed by connecting accordingly will be able to be basically within the original range, and based on the data selected during loading, in some implementation processes, it can effectively reflect the general shape of the surveying and mapping graphic. It can be seen that the above surveying and mapping graphic generation method can reduce the amount of data loaded each time when generating the surveying and mapping graphic and effectively improve the generation efficiency of the surveying and mapping graphic.

[0061] In order to make the surveying and mapping graphic generated by the above solution have better quality and reduce the serious distortion caused by omitting node data, optimization can also be achieved by analyzing the node data.

[0062] See Figure 2 As shown, the steps of parsing the graphic node data set and splitting the graphic node data set into several sub-data sets on the basis of the original order relationship may specifically include:

[0063] S201. Analyze the morphological influence degree of each node data recorded in the graphic node dataset;

[0064] S202. Divide several consecutive node data into subsets according to the results of the morphological influence degree analysis;

[0065] It should be noted that the morphological influence degree referred to in this application is actually the influence degree of the connection line between node data on the overall shape. For example, if the connection line has a large angular change compared with the adjacent continua at both ends, its morphological influence degree may be large. Of course, in practical applications, this morphological influence degree is also related to the length of the connection line. For example, a short connection line with a large angle turn, when viewed on the scale of the overall graphic, actually has a small influence on the overall shape.

[0066] Therefore, based on the morphological influence degree for subset division, the node data therein can be stratified based on the influence on the overall shape.

[0067] In practical applications, the number of subsets that can be divided from a single graphic node dataset can be more than 1, and its specific number is not limited. According to the balance requirements of different performances and precisions, under different settings, the number of subsets divided from a single graphic node dataset may also be different.

[0068] In addition, when two or more subsets are divided from a single graphic node dataset, these subsets can be in a parallel relationship. As Figure 3 shown, the graphic node dataset therein includes node data 1 to node data 20. Among them, according to the results of the morphological influence degree analysis, node data 7 - 15 are divided into the first subset, and node data 19 is divided into the second subset. There is no overlap in the node data between the first subset and the second subset, and the two are in a parallel relationship. In the process of generating some mapping graphics, the first subset and the second subset may be ignored, thereby reducing the amount of data read.

[0069] The subsets can also be nested multi-level subsets. That is, within a subset, smaller subsets can also be divided. Figure 4 The graphic node dataset shown includes node data 1 to node data 20. Among them, according to the results of the morphological influence degree analysis, node data 7 - 15 are divided into the first subset, and node data 10 - 13 are divided into the second subset. The node data of the second subset are also all the node data in the first subset, that is, the second subset is a subset of the first subset.

[0070] In practical applications, sub-datasets at different levels are divided based on different morphological influence degrees. Generally speaking, the morphological influence degree of the outermost sub-dataset is greater than that of the innermost sub-dataset (also referred to as a smaller level in this application).

[0071] Therefore, in some embodiments, the step of dividing a number of consecutive node data into sub-datasets according to the result of morphological influence degree analysis includes: determining different levels of sub-datasets according to different morphological influence degrees.

[0072] When the sub-dataset has several levels, different levels of sub-datasets can be selected for loading corresponding to different scales. Among them, the step of selectively loading each node data in several sub-datasets in the graphic node dataset according to the current scale includes: determining the morphological influence degree level corresponding to the current scale, loading the sub-dataset at the smallest level within the sub-dataset corresponding to the current morphological influence degree level, and skipping sub-datasets at smaller levels.

[0073] Taking Figure 4 the graphic node dataset shown as an example, assuming that the smallest level corresponding to the morphological influence degree level corresponding to the current scale is the first sub-dataset, then the node data in the first sub-dataset is loaded; but the node data in the second sub-dataset at a smaller level within the first sub-dataset is skipped. That is, the result of the load is the part of the first sub-dataset minus the second sub-dataset. In practical applications, the morphological influence degree level corresponding to the current scale may not correspond to a sub-dataset, and only the node data outside the sub-dataset is loaded, that is Figure 4 node data 1-6 and node data 16-20.

[0074] Similarly, taking Figure 4 the graphic node dataset shown as an example, assuming that the smallest level corresponding to the morphological influence degree level corresponding to the current scale is the second sub-dataset, then all the node data in the first sub-dataset and the second sub-dataset will be loaded. If the second sub-dataset also includes a third sub-dataset at a smaller level, the node data in the third sub-dataset will be skipped.

[0075] Based on the above embodiments, different numbers of node data can be retrieved at different scales, thereby improving the accuracy of the generated surveying and mapping images in the user's visual perception.

[0076] In some embodiments, after connecting the loaded node data in the order relationship in the graphic node dataset to generate a closed surveying and mapping graphic, the following steps are further included: after receiving an instruction for scale change, obtaining the updated scale; in the case of scale reduction, directly adjusting the scale based on the currently loaded data. In the case of scale enlargement, determining whether the form influence degree level corresponding to the scale changes; when the form influence degree level corresponding to the scale changes, based on the part still displayed on the screen, supplementarily loading the sub-dataset with the smallest level in the sub-dataset corresponding to the current form influence degree level; and regenerating a closed surveying and mapping graphic based on the supplemented loaded node data.

[0077] The above steps can dynamically supplement the node data. When the user enlarges the graphic to a certain extent, the surveying and mapping graphic is regenerated, so that a more accurate surveying and mapping graphic can be presented to the user. It can be understood that based on the size of the graphic scale, the node data of some surveying and mapping graphics may be all loaded. Of course, due to the change of the scale, the number of surveying and mapping graphics that may need to be loaded on the screen may decrease. Therefore, the amount of data of the loaded node data is also relatively small. The node data of other surveying and mapping graphics excluded from the screen due to scale enlargement can still be omitted.

[0078] For the convenience of the system for subsequent identification, a division identifier of the sub-dataset can be directly added on the basis of the original graphic node dataset, so that the system can directly distinguish the situation of the sub-dataset during the data reading process without additionally reading the relevant data of the sub-dataset from other places. At the same time, during subsequent retrieval, the user can also intuitively view the division situation of the sub-dataset.

[0079] In some embodiments, the step of dividing the graphic node dataset into several sub-datasets on the basis of the original order relationship includes: inserting a sub-dataset identifier in the graphic node dataset, the sub-dataset identifier is inserted before the first node data of the sub-dataset, and the sub-dataset identifier records the number of data in the sub-dataset.

[0080] During the process of loading the node data of the graphic node dataset, if a sub-dataset identifier is encountered, it is determined whether to load the node data in the corresponding sub-dataset;

[0081] If not, directly skip the corresponding sub-dataset according to the number of data in the sub-dataset recorded by the sub-dataset identifier.

[0082] The following describes a method for form influence degree analysis provided in this embodiment with reference to the accompanying drawings. It can be understood that in actual work, more complex form influence degree analysis can also be directly performed using deep learning or other methods. See Figure 5As shown, the steps of morphological influence analysis may include:

[0083] S301. Traverse the node data, and define each node data with a turning angle of the connection line compared to the previous two node data greater than a set angle as a large turning node;

[0084] See Figure 6 As shown, there are 11 pieces of node data, which are represented by numbers 1 to 11 in the figure, corresponding to node data 1 to node data 11 respectively. It can be understood that since the surveyed graph is a closed graph, the last piece of node data will be connected to the first piece of node data to form a closed loop. Taking the connection line between node data 11 and node data 1 as an example, the turning angle there is α, that is, the connection line between node data 11 and node data 1 is deflected by an angle α compared to the previous connection line (the connection line between node data 10 and node data 11).

[0085] In practical applications, the specific set angle can be set to 30°, 45° or other reasonable angles, and can be selected based on actual needs.

[0086] As Figure 7 shown, in the example of this embodiment, node data 1, node data 2, node data 3, node data 4, node data 5, node data 6 and node data 10 are defined as large turning nodes. Figure 7 These large turning nodes are circled in the figure for easy understanding.

[0087] S302. Determine the connection lines between each large turning node and all other large turning nodes;

[0088] As Figure 8 shown, taking node data 1 as an example, connect it to other large turning nodes. Of course, node data 2 is connected to node data 1 in sequence, and can be directly ignored in actual calculation.

[0089] S303. Determine the maximum distance between several node data between the connection lines and the connection line as the value of the morphological influence degree corresponding to the connection line;

[0090] Taking the connection line between node data 1 and node data 10 as an example, the corresponding value of the morphological influence degree is the distance d1 from node data 11 to the connection line between node data 1 and node data 10.

[0091] Taking the connection line between node data 1 and node data 6 as an example, the node data between the two connection lines includes node data 7 to node data 11. The distance d2 from node data 10 to the connection line between node data 1 and node data 6 is the maximum distance among them. Therefore, take d2 as the corresponding value of the morphological influence degree.

[0092] In this embodiment, dividing several consecutive node data into subsets according to the results of morphological influence degree analysis includes:

[0093] As much as possible, divide each node data between the connections with morphological influence degrees within the set range into the same subset.

[0094] Assume that the set range is 0 - d3, where d3 is greater than d1 but less than d2. Then, in the above example, node data 11 is divided into a subset.

[0095] In addition, there can be multiple set ranges. Different set ranges correspond to different morphological influence degree levels, and can form hierarchical subsets. The subset corresponding to the narrowest set range is a smaller - level (more inner - layer) subset, and the subset corresponding to the widest set range is a larger - level (more outer - layer) subset.

[0096] In practical applications, the calculation of the value of morphological influence degree can start from the first major turning point node and be completed in sequence. After the relevant data of the first major turning point node is calculated, then calculate the connections between the second major turning point node and subsequent major turning point nodes until all major turning point nodes are traversed.

[0097] In addition, in this embodiment, as much as possible, more node data is divided into the same subset, so as to minimize the amount of data that needs to be loaded to the greatest extent.

[0098] For example, the connection between node data 4 and node data 10, and the connection between node data 6 and node data 10. The values of morphological influence degrees corresponding to the above two connections are about the same. In practical applications, it is very likely that both meet the requirements of a certain set range. Then, at this time, taking the connection with the largest span can minimize the amount of data that needs to be loaded as much as possible. That is, divide the node data from node data 5 to node data 9 between node data 4 and node data 10 into the same subset corresponding to the corresponding set range.

[0099] In this embodiment, assume that node data 11 is divided into a first subset, node data 5 to node data 9 are divided into a second subset, and node data 7, node data 8, and node data 9 are divided into a third subset. Among them, the first subset and the second subset are in a parallel relationship, and the node data of both will be loaded simultaneously or not loaded simultaneously. The second subset and the third subset are subsets of different levels.

[0100] Such as Figure 9As shown, assume that the morphological influence level corresponding to the scale at this time does not correspond to any sub-dataset, then only the remaining node data is loaded; the generated mapping graph reflects the general form of the actual mapping graph, where part of the node data is omitted and loaded, and it can be generated quickly.

[0101] When loading the node data in the second sub-dataset, part of the third sub-dataset may not be loaded. As Figure 10 shown, assume that the scale is enlarged to a set degree. At this time, the node data in the first sub-dataset and the second sub-dataset are loaded, and a mapping graph is regenerated based on the node data at this time. When the scale continues to be enlarged, all the node data in the mapping graph may be fully loaded, and then the most accurate mapping graph will be generated.

[0102] It should be understood that for the convenience of understanding, the amount of node data in the examples of this embodiment is small. In actual applications, especially for more complex mapping graphs, there will be a large amount of node data, so the effect of effectively improving the graph generation efficiency can be achieved.

[0103] This embodiment also provides a mapping graph generation system 100, as Figure 11 shown, which includes a node data analysis module 101, used to parse the graph node dataset after obtaining the input graph node dataset, and divide the graph node dataset into several sub-datasets on the basis of the original sequence relationship. The graph node dataset includes several node data recorded in sequence, and the node data corresponds to the inflection points of the mapping graph;

[0104] An instruction acquisition module 102, used to acquire a graph generation instruction and acquire the current scale after receiving the graph generation instruction;

[0105] A data loading module 103, used to load the node data of the graph node dataset. Among them, according to the current scale, some of the node data in several sub-datasets in the graph node dataset are selectively loaded or not loaded;

[0106] A graph generation module 104, used to connect the loaded node data in sequence in the graph node dataset to generate a closed mapping graph.

[0107] In addition, for the specific steps that the above modules of the mapping graph generation system in this embodiment can execute, reference can also be made to the mapping graph generation method provided in this embodiment, which will not be elaborated in this embodiment.

[0108] Moreover, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present disclosure that have equivalents, modifications, omissions, combinations (e.g., schemes that cross various embodiments), adaptations, or alterations. It is not limited to the examples described in this specification or during the implementation of this application, and the examples will be construed as non-exclusive.

[0109] The above description is intended to be illustrative and not restrictive. For example, the above examples (or one or more of their aspects) can be used in combination with each other. For example, other embodiments can be used by those of ordinary skill in the art upon reading the above description.

[0110] The foregoing are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, various changes and modifications can be made to the embodiments of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for generating surveying and mapping graphics, characterized in that: include: After obtaining the input graphic node data set, the graphic node data set is parsed, and the graphic node data set is divided into a plurality of sub-data sets based on the original sequence relationship, wherein the graphic node data set includes a plurality of node data recorded in sequence, and the node data corresponds to the inflection point of the surveying and mapping graphics; After receiving the graphics generation instruction, obtain the current scale; Loading node data of a graphic node data set, wherein, according to a current scale, selectively loading or not loading each of the node data in a plurality of sub-data sets in the graphic node data set; Connecting the loaded node data according to the sequence relationship in the graphic node data set to generate a closed surveying and mapping graphic; The step of parsing the graphic node data set and dividing the graphic node data set into a plurality of sub-data sets based on the original sequence relationship includes: Performing a morphological influence analysis on each node data recorded in the graphic node data set, where the morphological influence is the degree of influence of the connection between the node data on the overall shape; Dividing a plurality of continuous node data into sub-data sets according to the result of the morphological influence analysis; The step of dividing a plurality of continuous node data into sub-data sets according to the result of the morphological influence analysis comprises: According to different morphological influences, sub-data sets at different levels are determined; The step of performing morphological influence analysis on each node data recorded in the graphic node data set comprises: Traversing the node data, defining each node data whose turning angle of the line connecting the first two node data is greater than the set angle as a large turning node; Determine the connection between each major turning point and other major turning points; The maximum distance between a plurality of the node data and the link is determined as the value of the morphological influence corresponding to the link.

2. The method for generating surveying and mapping graphics according to claim 1, characterized in that: The step of selectively loading each of the node data in a plurality of sub-data sets in the graphic node data set according to the current scale includes: The morphological influence level corresponding to the current scale is determined, and the sub-dataset of the smallest level in the sub-dataset corresponding to the current morphological influence level is loaded, and the sub-datasets of smaller levels are skipped.

3. The method for generating surveying and mapping graphics according to claim 1, characterized in that: After connecting the loaded node data according to the sequence relationship in the graphic node data set to generate a closed surveying and mapping graphic, the method further includes: After receiving the scale change instruction, obtain the updated scale; When the scale is reduced, the scale is adjusted directly based on the currently loaded data; When the scale is enlarged, determine whether the morphological influence level corresponding to the scale has changed; when the morphological influence level corresponding to the scale has changed, based on the part still displayed on the screen, supplement the loading of the sub-dataset of the minimum level within the sub-dataset corresponding to the current morphological influence level; and regenerate a closed mapping graphic based on the supplemented node data.

4. The method for generating surveying and mapping graphics according to claim 1, characterized in that: The step of dividing the graph node data set into a plurality of sub-data sets based on the original sequence relationship includes: A sub-dataset identifier is inserted into the graph node dataset, the sub-dataset identifier is inserted before the first node data of the sub-dataset, and the sub-dataset identifier records the number of data in the sub-dataset.

5. The method for generating surveying and mapping graphics according to claim 4, characterized in that: In the process of loading the node data of the graphic node data set, if the sub-data set identifier is encountered, determining whether to load the node data in the corresponding sub-data set; If not, the corresponding sub-dataset is directly skipped according to the sub-dataset identifier recording the number of data in the sub-dataset.

6. The method for generating surveying and mapping graphics according to claim 1, characterized in that: The dividing of a plurality of continuous node data into sub-data sets according to the result of the morphological influence analysis comprises: The node data between the links whose morphological influence is within a set range are divided into the same sub-data set as much as possible.

7. A surveying and mapping graphics generation system, characterized in that: include: A node data analysis module is used to parse the graphic node data set after obtaining the input graphic node data set, and divide the graphic node data set into a plurality of sub-data sets based on the original sequence relationship, wherein the graphic node data set includes a plurality of node data recorded in sequence, and the node data corresponds to the inflection point of the surveying and mapping graphics; The instruction acquisition module is used to acquire the graphic generation instruction and acquire the current scale after receiving the graphic generation instruction; A data loading module, used for loading node data of a graphic node data set, wherein, according to a current scale, each of the node data in a plurality of sub-data sets in the graphic node data set is selectively loaded or not loaded; A graphics generation module, used for connecting the loaded node data according to the sequence relationship in the graphic node data set to generate a closed surveying and mapping graphic; The step of parsing the graphic node data set and dividing the graphic node data set into a plurality of sub-data sets based on the original sequence relationship includes: Performing a morphological influence analysis on each node data recorded in the graphic node data set, where the morphological influence is the degree of influence of the connection between the node data on the overall shape; Dividing a plurality of continuous node data into sub-data sets according to the result of the morphological influence analysis; The step of dividing a plurality of continuous node data into sub-data sets according to the result of the morphological influence analysis comprises: According to different morphological influences, sub-data sets at different levels are determined; The step of performing morphological influence analysis on each node data recorded in the graphic node data set comprises: Traversing the node data, defining each node data whose turning angle of the line connecting the first two node data is greater than the set angle as a large turning node; Determine the connection between each major turning point and other major turning points; The maximum distance between a plurality of the node data and the link is determined as the value of the morphological influence corresponding to the link.

Images