KR101763413B1 - THE Method for GENERALIZING DigitalMap - Google Patents

Abstract

The present invention relates to a method for generalizing a digital map to select and simply express an object with respect to the scale and purpose of use for digital map. According to an embodiment of the present invention, a method for generalizing a digital map in a web (Server-Client) environment comprises the following steps: retrieving map data from a server; receiving generalization sets to generalize the map data from a user; generalizing the map data based on the generalization sets transmitted to the server; and adding the generalization results on a screen without loss of a current editing map through asynchronous communications.

Description

{The Method for GENERALIZING DigitalMap}

The present invention relates to a digital map generalization method.

A digital map is a basic spatial data of a geographic information system, a process of reducing the details of a spatial shape in a digital map. Often performed when scaling down the map scale, it involves generalization of the numerical map, such as reduction of detail, resampling of larger intervals, or reduction of the number of points in the line. Traditionally, this has been handled manually by cartographers, but in particular with semi-automated and automated methods, in combination with the Geographic Information System (GIS). Therefore, there is a need for a method that can generalize the digital map efficiently according to the user's needs.

Unlike existing commercial GIS software which generalizes a digital map according to a predetermined value, the present invention provides a generalization method of a digital map capable of setting a generalization criterion according to a user's purpose, I want to express it briefly.

A method for generalizing a digital map in a server-client environment according to an embodiment of the present invention includes: loading map data from a server; Receiving a generalization setting for generalizing the map data from a user; Transmitting generalization settings to a server and performing generalization on the map data based on the generalization settings; And adding the generalization result to the screen without loss of the current editing map through asynchronous communication.

In one embodiment, the step of loading map data from the server comprises the steps of: the user uploading data in the form of a file to a GeoServer; Receiving vector data as character string data in the form of GeoJSON using the WFS service provided by the geo server; Analyzing the Geo-Jason-style character string provided in the Open Layer 3 and converting it into graphic data through the Canvas function of HTML5; And creating a new layer on the map with the coordinates of the feature according to the determined coordinate system.

In one embodiment, the step of receiving the generalization setting includes receiving a reference value for performing a simplification function or an elimination function, respectively, from a user, and in the case of simplification, The length of the object (length) (km) when the line string and the multi-line string data are input, and the length (km) of the object when the multi-line string data is input. (M2) indicating the width of the object when polygon data and polygon data are input.

In one embodiment, the step of inputting the generalization setting includes displaying a user's setting of a reference value according to a generalized item on a screen.

In one embodiment, the step of receiving the generalization settings comprises: storing the settings of the generalized items in a JavaScript as a JSON object, and storing the stored generalized objects in an open layer 3 (Openlayers 3) And transmitting the layer information including the feature information of the converted layer to the server.

In one embodiment, the step of performing generalization on the map data may include a step of, in a Geotools object transformation module, performing a generalization on the map data using a GeoTools object's SimpleFeatureCollection, And if the attribute of the input data exists, it is converted into a simple feature collection object having x, y coordinate values and attributes, and if the attribute does not exist, into a simple feature collection object having only x, y coordinate values .

In one embodiment, the step of generalizing the map data may include generating a value corresponding to the generalization option from the received JSON data as a generalization option object in the generalization option object creation module If the geometry type of the input data is a polygon or a polygon, the width reference value input by the user is stored in the generalization option. If the geometry type of the input data is a line string or a multi-line string, The distance reference value and the length reference value inputted by the user are stored in the generalization option.

In one embodiment, the step of performing generalization on the map data includes a step of performing a generalization object generation module, a simple collection object generated in the geoid tool object conversion module and the generalization option object generation module, And creating a generalization object with the generalization option object.

In one embodiment, performing the generalization on the map data further comprises, in the Topology Build module, configuring a topology network of coordinate values of the simple feature collection of the generalized object do.

In one embodiment, the step of configuring the topology network may include classifying the simple features as having a dangle point and not having a dangle point among the simple features that constitute the simple feature collection, Wherein the spatial data having two dangling points (first point, end point) or having only one (first point, one end point) are subjected to a simplification and elimination algorithm , And the spatial data that does not have any dangling points does not apply the elimination algorithm.

In one embodiment, performing the generalization on the map data may include generating a topology table in which a topology network generated by the topology generation module is listed in a list type in a topology table generation module Wherein the topology table further includes an ID of an object connected to a first point or an end point of another object, an ID of an object connected to the first point, an ID of an object connected to the end point, and a distance The information is being stored.

In one embodiment, performing the generalization on the map data may include applying a simplification or elimination algorithm to all simple feature objects of the simple feature collection using the generalized object and the topology table object in the generalization module The method comprising the steps of:

In one embodiment, the step of applying the simplification algorithm includes removing points that are unnecessary for expressing features of a line by selecting points for characteristic, characteristic description, and shape maintenance represented by the original line, The algorithm is either Distance & Angle, DOUGLAS, or LANG algorithm.

In one embodiment, the step of applying the elimination algorithm includes deleting line data of a predetermined length (km) or less or face data of a certain area (m2) or less inputted by the user.

In one embodiment, performing the generalization on the map data may further include generating a simple feature collection object newly generated through the generalization module in the generalization result object creation module, The feature collection object refers to spatial data to be displayed as a generalization result value on the Web.

In one embodiment, performing the generalization on the map data may further include generating a generalized report object for comparing data before and after generalization in a generalization report object generation module, The generalization report stores the number of simple feature objects of the input simple feature collection before generalization, the number of points constituting the object, the number of simple feature objects of the simple feature collection to be returned after generalization, and the number of points constituting the object.

In one embodiment, performing the generalization on the map data comprises converting the simple feature collection returned after performing the simplification and elimination algorithm in the GeoJson object transformation module to a GeoJason object for display on a web browser The method comprising the steps of:

In one embodiment, performing the generalization on the map data comprises: generating generalization result GeoJason objects, generalized report objects, and topology table objects, which are generated through all modules of generalization, in a generalization layer generation module Wherein the generalization result and the topology table object are displayed in a form of a table in a user screen, wherein the generalization report and the topology table object are displayed on a user screen in a table format .

The computer program according to one embodiment combines with hardware to implement each of the steps of the digital map generalization method described above.

According to another embodiment of the present invention, a method of generalizing a digital map can be provided, and an object can be selected and briefly expressed according to the purpose of accumulating and using a digital map. All of the above methods are provided as functions available on a web browser, and unlike conventional commercial GIS software that is based on desktop, it has an advantage that it can be used anywhere in the Internet-enabled environment.

1 is a view showing the structure of GeoJSON.
2 is a diagram showing a generalized module flow chart.
3 is a diagram showing a generalization result before application of topology generation.
4 is a view showing a dangle point.
5 is a diagram showing a result of generalization after application of topology generation.
6 is a diagram showing a simplified step 1.
FIG. 7 is a diagram showing a simplified Step 2. FIG.
Fig. 8 is a diagram showing a result of simplification.
9 is a diagram showing a comparison screen before and after generalization.
10 is a diagram showing a generalization report.
11 is a diagram showing a topology table.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like or similar elements are denoted by the same or similar reference numerals, and redundant description thereof will be omitted. The suffix " module " and " part " for the components used in the following description are given or mixed in consideration of ease of specification, and do not have their own meaning or role. In the following description of the embodiments of the present invention, a detailed description of related arts will be omitted when it is determined that the gist of the embodiments disclosed herein may be blurred. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. , ≪ / RTI > equivalents, and alternatives.

Generalization according to one embodiment of the present disclosure provides two functions. The first function is a simplification function. When the data type is a line string or a multi-line string, the DOUGLAS algorithm is applied to simplify spatial data by using a predetermined reference value inputted by the user. The second function is the elimination of data with a length or area less than a certain threshold value entered by the user with the elimination, and can be used when the data type is a line string, a multi-line string, a polygon, or a polygon. The steps of generalization are: 1. Importing map data, 2. Setting generalization, 3. Transferring data to inspection server, and 4. Adding generalization result. The detailed steps are as follows.

1. Importing map data

The generalization tool according to one embodiment of the present application was developed in accordance with the ⁽¹⁾ environment of the web-server. Desktop applications such as ArcGIS or QGIS, which is a commercial program, use vector data in the form of files, but web-based generalization tools are not accessible and editable directly on the user's screen (web browser) due to the limitation of web security. Therefore, in order to provide the vector data to be used for generalization in a user-editable form in the web environment, it must be converted into a data format suitable for the web environment, and GeoServer ^{footnote (2)} is used as means for solving this. The web-based generalization tool uses the Web Feature Service (WFS) ^{footnote (3)} provided by the Geo Server to upload the vector data to the geo server as shown in FIG. 1 It is provided as string data in the form of a Jason (GeoJSON) ^{footnote (4)} . A server is a computer that provides services, and because it exists for a large number of clients, it usually has a very large capacity, Web server (IIS, Apache) serves as a server, and the user's web browser (Firefox or Microsoft Internet Explorer) is the client program. / Footnote (2): Geo server GeoServer) is an open source GIS software server developed in Java that enables users to share and edit geospatial data. Because it was developed with interoperability, it is possible to use open standards to serve various spatial data sources. / Footnote (3): Using the HyperText Transfer Protocol (HTTP) to create a set of geographic feature units (4): It is a spatial data exchange format based on JavaScript Object Notation (JSON). Because it adopts the syntax of JavaScript, JavaScript is used frequently in web environment It is advantageous.)

The supplied Geo-Jason-style string analyzes the string data within the OpenLayer3 ^{footnote (5) and} uses the canvas ^{footnote (6)} of the HyperText Markup Language 5 (HTML5) . Then, the coordinates of the feature are created as a new layer on the map according to the defined coordinate system. The user then checks the created layer. (Footnote (5): A JavaScript-based open source library for outputting and editing maps in a web browser.) / Footnote (6): A functional element added to HTML5. Can be used for.

2. Setting generalization

The generalization setting simplifies the setting of the reference value for performing the elimination function, and each reference value must be inputted. In Table 1, for simplification, enter the vertical distance (in km) between the points of the line string (LineString) or the multi-line string (MultiLineString) data. Elemination means the length (km) which means the length of the object when the line string and the multi-line string data are input, the width of the object when the polygon data and the polygon data are input (M 2) to be input.

Generalized Items Feature type Reference value leveling Line strings, multi-line strings Distance (km) Elimination
Line strings, multi-line strings Length (km) Polygon, Multipolygon Width (m²)

Generalization setting As in the structured verification setting, since the reference value according to the generalization item is set in the user screen, it is possible to expand the system in various forms.

The above generalization item settings are saved as JSON ^{footnote (7)} objects inside JavaScript. The stored object includes the feature information of the layer converted into Geo-Jason through Openlayers3 and transmits it to the server. (7): JSON (Javascript Object Notation) is a lightweight data-exchange format that is easy for humans to read and write, It is also easy to analyze and create machines, especially when they are exchanging data on the Internet.

3. Transfer to server

AJAX ^{footnote (8)} sends a generalized object in the form of a string to the server through a request. The server includes 10 modules as shown in Fig. 2 for generalizing the objects. (Footnote (8): Asynchronously sending and receiving information in various formats (JSON, XML, HTML and plain text format) to the server side You can reduce the amount of data you receive and delegate processing to the client.)

3.1 GeoTools object transformation

It is a module that converts GeoJason objects from input JSON data into a simple feature collection of geo-tools that can be used internally. Unlike geometry object transformation of structured verification, if there is an attribute of input data, it is converted into a simple feature collection object with x, y coordinate value and attribute. If attribute does not exist, it is converted into simple feature collection object with only x, y coordinate value .

3.2 Creating Generalization Option Object

It is a module that generates a value corresponding to the generalization option among the input JSON data as a generalization option object. When the geometry type of the input data is polygon or polygon, only the elimination function of deleting data having an area less than a certain reference value can be performed, and the width reference value inputted by the user is stored in the generalization option. If the geometry type of the input data is a line string or a multiline string, both the simplification and the elimination function can be performed, and the distance reference value and the length reference value inputted by the user are stored in the generalization option.

3.3 Generating generalized objects

3.1 Geo Tool Object Conversion Module and 3.2 Generalization Option Generate generalized objects with simple feature collection object and generalization option object created by object creation module respectively.

3.4 Topology Build

Before the generalization algorithm is performed, a topology network of coordinate values of the simple feature collection of generalized objects is constructed by topology generation. If a line object that does not apply topology generation is simplified or eliminated, even if it is a single line, if the distance between a point and a point is short, a line object is cut off as shown in FIG. 3 do.

Therefore, the above problem is solved through topology generation. Topology generation generates simple feature collection and applies algorithms to each of the simple features that make up the simple feature collection, classifying them into two cases, one having a dangle point and the other having no dangling point. As shown in FIG. 4, a dangling point means a last point of spatial data in which no connected object exists. Spatial data with both dangling points (first point and end point) and spatial data with only one (first point, end point) are simplified, and all the elimination algorithms are applied, and no dangling points Since the spatial data means that there are objects connected to both end points, the algorithm is not applied (the object is not unconditionally deleted if the spatial data length is short). FIG. 5 is a diagram showing a result of generalization after applying topology generation .

3.5 Creating a Topology Table

And generates a topology table in which a topology network (Topology Network) generated through a topology generation module is listed in a list type. The table stores the ID of the object connected to the first or end point of another object, the ID of the object connected to the first point, the ID of the object connected to the end point, and the distance information between the connected objects.

3.6 Generalization

Apply the following generalization algorithm to all simple feature objects in a simple feature collection using generalization objects and topology table objects.

- Simplification

Simplification refers to the process of eliminating unnecessary surplus points in expressing the characteristics of a line by selecting the points represented by the original lines and describing the characteristics and shape. The generalization algorithms are typically Distance & Angle, DOUGLAS, LANG. The present invention applies the DOUGLAS algorithm.

Assuming that the SimpleFeatureCollection is a SimpleFeature, the following example is taken as a straight line between the first point p1 and the last point p5 of the coordinate values of the simple features as shown in FIG. 6 Thereby creating a connecting line.

The straight line distance between this line and each point is calculated and a point (p6) at a distance greater than the distance input by the user from the farthest distance is calculated and stored as a simple feature object point . Then, as shown in FIG. 7, a new line connecting p1 and a point p6 stored in the simple feature object as a result of simplification is generated. In the same way, the point (p3), which is farther away from the newly generated line than the distance, is stored in the simplification result simple feature object.

This method is repeated until the point between the straight lines does not exist. Then, the result of the p6 and the last point (p15) stored in the first step are repeated in the same manner as shown in FIG.

Through the above process, newly created simple features are stored and returned to the simple feature collection.

- Elimination

Elimination means deletion of line data less than a certain length (km) inputted by the user or plane data of a certain area (m2) or less. All simple feature objects that constitute the input simple feature collection object are sequentially fetched and checked to see if they satisfy the criteria value entered by the user. If the geometric type of the simple feature is a line string or a multiline string, determine the length of the geometric value of the simple feature and check whether the value is less than the length (km) input by the user. If the geometry type is a polygon or a polygon, determine the area of the geometric value of the corresponding simple feature and check whether the value is equal to or smaller than the area (㎡) input by the user. If the length or width is less than or equal to the reference value, it is not stored in the simple feature collection object to be returned. If the length or width is larger than the reference value, the result is stored in the simple feature collection object.

3.7 Generating generalization result objects

3.6 Refers to a module that creates a newly created simple feature collection object through a generalization module and refers to spatial data to be displayed as a generalization result on the web.

3.8 Generating Generalization Report

Generalized report object generation module generates a generalized report object that compares data before and after generalization. The generalization report stores the number of simple feature objects of the input simple feature collection before generalization, the number of points constituting the object, the number of simple feature objects of the simple feature collection to be returned after generalization, and the number of points constituting the object.

3.9 GeoJSON object conversion

After performing the simplification and elimination algorithms, the returned simple feature collection is transformed into a Geo-Jason object for display on the Web browser.

3.10 Generating a Generalization Layer

The generalization layer generation module is a module that generates a generalization layer object as a generalization result, a generalized report object, and a topology table object, which are generated through generalization modules. Generalization results Geo-Jason objects are added to the viewer as a verification result layer, generalized reporting, and topology table objects are displayed in tabular form on the user's screen.

4. Adding generalization results

The generalization result adds the generalization result to the screen without loss of existing map data through the asynchronous communication ^{footnote (9)} . Since there is no loss of existing data, it is possible to compare data before and after generalization. FIG. 9 is a diagram of a Geo-Jason object added to a screen, which means spatial data in a generalized layer object transmitted from a server, before and after map data is actually generalized. Figure 10 shows a generalized report and Figure 11 shows a topology table. (Footnote (9): When an existing web application fills a form in a browser and submits it to a web server, The Ajax application can only request data from the web server and then process the data in the client.)

The above-described present invention can be implemented as a computer program or an application recorded on a medium. The computer readable medium includes all kinds of recording devices in which data that can be read by a computer system is stored. Examples of the computer readable medium include a hard disk drive (HDD), a solid state disk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, , And may also be implemented in the form of a carrier wave (e.g., transmission over the Internet). Also, the computer may include a control unit of the terminal.

The foregoing detailed description should not be construed in all aspects as limiting and should be considered illustrative. The scope of the present invention should be determined by rational interpretation of the appended claims, and all changes within the scope of equivalents of the present invention are included in the scope of the present invention.

Claims (19)

As a numerical map generalization method in a web (Server-Client) environment,
Loading map data from a server;
Receiving a generalization setting for generalizing the map data from a user;
Transmitting the generalization setting to the server and performing generalization on the map data based on the generalization setting; And
Adding the generalization result to the screen without losing the current editing map through asynchronous communication,
The loading step may include: a step in which a user uploads data in a file format to a GeoServer; Receiving vector data as character string data in the form of GeoJSON using a web feature service (WFS) provided by the geo server; Analyzing the Geo-Jason-style character string provided in the Open Layer 3 and converting it into graphic data through the Canvas function of HTML5; And creating a new layer on the map of the coordinates of the feature according to a predetermined coordinate system,
The receiving step may include receiving a reference value for performing a simplification function or an elimination function from a user, wherein the simplifying step includes receiving a line string or a multi-line string And the length of the object (length) (km) when the line string or the multi-line string data is input, receives the vertical distance (km) between the polygons Polygon) or MultiPolygon data is input, the area (m2) indicating the width of the object is input,
The receiving step may include displaying a reference value according to a generalized item on a screen so that the user can set a reference value,
The receiving step stores the settings of the generalized items in a JavaScript as a JSON object, and stores the stored generalized object as feature information of a layer converted into Geo-Jason through the open layer 3 To the server,
The step of performing the generalization on the map data may include transforming the GeoJason object into a SimpleFeatureCollection of the GeoTool available in the GeoTools object conversion module, Transforming a simple feature collection object having an x, y coordinate value and an attribute, if the attribute of the input data exists, into a simple feature collection object having only x, y coordinate values if the attribute does not exist;
delete delete delete delete delete The method according to claim 1,
Wherein the step of performing generalization on the map data comprises:
Generalization Option In the object creation module,
And generating a value corresponding to the generalization option from the received JSON data as a generalization option object,
If the geometry type of the input data is a polygon or a polygon, the width reference value inputted by the user is stored in the generalization option. If the geometry type of the input data is a line string or a multi-line string, A method of generalizing a digital map, wherein the distance reference value and the length reference value are stored in a generalization option.
8. The method of claim 7,
Wherein the step of performing generalization on the map data comprises:
In the generalized object creation module,
And generating a generalized object using the simple feature collection object and the generalized option object generated by the geoid tool object conversion module and the generalized option object generation module, respectively.
9. The method of claim 8,
Wherein the step of performing generalization on the map data comprises:
In the Topology Build module,
And constructing a topology network of coordinate values of the simple feature collection of the generalization object.
10. The method of claim 9,
Wherein configuring the topology network comprises:
Further comprising the step of classifying the simple features as having a dangle point and not having a dangle point among the simple features constituting the simple feature collection to generate a simple feature collection,
Here, the spatial data having both of the dangling points (the first point and the end point) and the spatial data having only one (one of the first point and the end point) are subjected to the simplification and elimination algorithm, and the dangling points A method of generalizing a digital map, wherein the spatial data does not apply an elimination algorithm.
10. The method of claim 9,
Wherein the step of performing generalization on the map data comprises:
In the topology table generation module,
And generating a topology table in which the topology networks generated through the topology generation module are listed in a list type,
Wherein the topology table stores the ID of the object connected to the first point or the end point of another object, the ID of the object connected to the first point, the ID of the object connected to the end point, Map generalization method.
12. The method of claim 11,
Wherein the step of performing generalization on the map data comprises:
In the generalization module,
Further comprising applying a simplification or elimination algorithm to all simple feature objects of the simple feature collection using the generalized object and the topology table object.
12. The method of claim 11,
Wherein applying the simplification algorithm comprises:
And removing unnecessary surplus points for expressing features of the line by selecting points for characteristic, characteristic description and shape maintenance represented by the original line,
Wherein the simplifying algorithm is one of Distance & Angle, DOUGLAS, and LANG algorithms.
12. The method of claim 11,
Wherein the generating the simple feature collection comprises:
Wherein when the elimination algorithm is applied, line data less than or equal to a certain length (km) input by the user or plane data less than or equal to a certain area (m2) is deleted.
13. The method of claim 12,
Wherein the step of performing generalization on the map data comprises:
In the generalization result object creation module,
And generating a newly created simple feature collection object through the generalization module,
Wherein the generated simple feature collection object is spatial data to be displayed as a generalized result value on the web.
16. The method of claim 15,
Wherein the step of performing generalization on the map data comprises:
Generalization Report In the object creation module,
Generating a generalized report object that compares data before and after generalization,
The generalization report includes a number of simple feature objects before the generalization and a number of points constituting the object, a number of simple feature objects of the simple feature collection to be returned after generalization, and the number of points constituting the object. .
17. The method of claim 16,
Wherein the step of performing generalization on the map data comprises:
In the GeoJSON object transform module,
And converting the simple feature collection returned after performing the simplification and elimination algorithm to a GeoJason object for display on a web browser.
18. The method of claim 17,
Wherein the step of performing generalization on the map data comprises:
In the Generalization Layer generation module,
Generating a generalization result GeoJason object, a generalized report object, and a topology table object as a generalized layer object through all modules of generalization,
Wherein the generalization result GeoJason object is added to a viewer as a verification result layer, and the generalization report and the topology table object are displayed on a user screen in a table format.
18. A computer program stored in a medium for executing each step of a digital map generalization method as claimed in any one of claims 1 to 7 in combination with hardware.

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