JP4047061B2 - Data structure of a map database that stores multiple records in time series - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a data structure of a map database representing a map.
[0002]
[Prior art]
Conventionally, the use of map databases representing maps has been expanding. The map data includes feature data representing features such as roads on the map. The feature data includes shape data representing the shape of the feature and attribute data. For example, road attribute data includes road types such as national roads and prefectural roads. Map data will be revised from time to time. The user can use the revised map through distribution via a medium such as a CD-ROM or the Internet.
[0003]
Here, the electronic map may be used to display events that occur and change in time series in association with features on the map. For example, a case where a place where a traffic accident has occurred is displayed on a map. According to such a map display, the user can analyze the correlation between the road environment at the accident site and the situation. Conventionally, accident histories are managed in individual databases, and by reading position information from this database, the location of the accident site, the number of accidents, and the like are displayed on a map.
[0004]
[Problems to be solved by the invention]
However, in this mode, it may be difficult to take correspondence between the event and the feature. For example, when the name of a feature such as a road is changed, it is difficult to associate the event data before the change name change with the feature after the name change. Also, when the shape of a feature changes due to construction, etc., the event before the shape change and the feature after the shape change are associated with each other, which may hinder accurate analysis of the correlation between the two. It was.
[0005]
Although it is possible to visually grasp changes in the terrain by performing time-series slide display of the map, it has not been possible to flexibly handle it. For example, there is a case where only the feature that has changed is objectively extracted from the features of the map data before and after the revision. Furthermore, it is not easy to analyze the effects of shape changes and the like on various events.
[0006]
The above-described problems are common problems when objectively analyzing the relationship between attributes such as events and features, and temporal transitions of the features or attributes. An object of this invention is to provide the map database which can implement | achieve such objective analysis.
[0007]
[Means for solving the problems and their functions and effects]
In order to solve at least a part of the above problems, the following configuration is applied in the present invention.
The first data structure of the present invention is:
In the data structure of a map database that represents a map,
Feature data prepared for each feature represented on the map;
The gist is to include predetermined time information associated with the feature and associated with the feature data.
[0008]
The second data structure of the present invention is
Attribute data for storing predetermined attributes related to the features represented on the map;
The gist is to include predetermined time information associated with the attribute and associated with the attribute data.
[0009]
By doing in this way, feature data and attribute data can be memorize | stored in time series, and the transition of a feature, an attribute, etc. can be grasped objectively.
[0010]
Here, the map represented by the map database includes various maps. For example, a house map, a city map, a map including a house frame / lifeline, and the like are included. The use of the map database may be local materials. Further, the map may be a two-dimensional map or a three-dimensional map. Further, the map may include an aerial photograph, satellite photograph, bird's-eye view image, and the like.
[0011]
The features include various features appearing on the map such as roads, buildings and other structures, forests, fields, house frames, rivers, lakes, electricity and gas lifelines. A feature representing a part of a building or the like may be used like a feature representing a three-dimensional intersection of a road. Further, it may include an artificially set shape, space, region, position, etc., such as administrative divisions, regions / regions, travel routes, air routes, and ferry routes. In addition, the features may include the summit of a mountain, a survey reference point, the position of a lighthouse, and the like. Further, the features may include contour lines, isobars, typhoon eyes, high pressure / low pressure, and the like.
[0012]
Examples of the predetermined time information related to the feature include a feature construction time, a repair time, and a demolition time. For features built in a phased maintenance plan, time information may be stored in the form of how many maintenance plans were built. The predetermined time information may be information that directly represents time or information that represents a time-series order.
[0013]
Various attributes can be listed as attributes according to the features. For example, feature names, types, and regulations can be included. As the name, the name of the household and the name of the business can be listed for buildings such as houses and stores. Examples of types of roads include types of highways, toll roads, general national / prefectural roads, narrow roads, and the like. The types of intersections may include types such as a three-dimensional intersection and a dead end. In addition, examples of the route type include an air route and a ferry route. Types of structures can include types such as overpasses, bridges, tunnels, caves, and railroad crossings. Furthermore, as the regulation, for example, in the regulation of the road, traffic regulation such as one-way traffic, U-turn prohibition, and speed limitation can be cited.
[0014]
The time information related to the attribute includes, for example, the time and period when the attribute is set, changed, abolished, or confirmed.
[0015]
Here, the map database may or may not include attribute data. When attribute data is included, the attribute data associated with the time information may be included at least in part, or may not be included at all.
[0016]
Here, the predetermined time information may be related only to the feature data, or may be related only to the attribute data. It may be related to both feature data and attribute data.
[0017]
The map database preferably includes shape data representing the shape of a feature or the like. As the shape data, a two-dimensional model or a three-dimensional model may be used. Various models such as a solid model, a surface model, and a wire frame model can be used. Furthermore, a polygon data format, a raster data format, a vector data format, and other various data formats can be used for the shape data. In addition, the shape represented by the shape data preferably includes various shapes such as points, lines, surfaces, solids, and combinations thereof. The shape data may include data representing a planar internal structure such as a floor plan of a house, or data representing a three-dimensional internal structure such as a piping diagram in a building. May be.
[0018]
In the data structure of the present invention,
The attribute may include a predetermined event that has occurred with respect to the feature.
[0019]
The predetermined event refers to a phenomenon that is not explicitly expressed on the map, a phenomenon related to the feature, an event that changes with time, and various events that occur, change, or disappear in relation to the feature. For example, an event includes a phenomenon that continues in time series. However, events such as names, types, traffic regulations, etc., which are artificially set for each feature, and the shape on the map itself are not included in the event.
[0020]
Events are not limited to existing features. For example, in the case where there is consolidation due to a merger of companies, the results of previous companies may be associated with the merged company. Moreover, you may memorize | store the performance of the company which concerns on the demolished building corresponding to the ruins.
[0021]
Events related to roads include the opening of roads, accidents, traffic jams, construction, rainfall and snowfall. Events related to buildings include crime, land prices, and fire. Events also include the performance of companies and sales offices and the number of condominium households.
[0022]
Events include changes in feature attributes. For example, mergers, spin-offs, establishments, relocations, and abolition of companies, schools, etc., forest burnt down due to forest fires, road type changes, railway line acquisitions, electrification, double track, single track, toll road tariff change -Changes in managers, changes in road traffic regulations, changes in administrative division names, changes in population distribution, etc.
[0023]
An event includes a change in the shape of a feature. For example, coastline changes due to revetment work and coastal erosion, contour changes due to landslides, etc., double-tracked / overpassed / underground roads and railway lines, ferry and passenger aircraft route changes, administrative division shape changes / integration・ Including division, expansion, reduction, north of the cherry blossom front, changes in temperature and animal and plant distribution.
[0024]
In the data structure of the present invention,
It is preferable that at least a part of the feature data and attribute data store a plurality of records having different time information for the related features and attributes.
[0025]
By doing in this way, the change of a feature and an attribute can be grasped in time series with a plurality of records.
[0026]
In the data structure of the present invention,
At least a part of the feature data and attribute data stores link data associated with each of the plurality of records,
The link data may be capable of specifying a past record corresponding to the record.
[0027]
By doing in this way, at least the past record corresponding to the record can be easily specified. For example, even a correspondence between features having different names, positions, shapes, and the like can be easily identified. When setting a link so that an old record can be identified from a new record of time information, it is sufficient to generate a link together with the creation of a new record, without providing a new link for an existing old record. Further, a link for specifying a new record from an old record may be provided. The link is preferably provided in a form that can specify the storage location of each record, such as a path or an address.
[0028]
The administrator of the map database may be able to individually set / change / add / delete attribute data, link data, and the like according to actual events. For example, the number of accidents can be added each time an accident occurs, or the situation of the accident can be added. Moreover, it is good also as a map database which sets and changes a memory content according to performance, a traffic phenomenon, and inspection / repair of a lifeline.
[0029]
The map database of the present invention uses feature data associated with time information, attribute data, customer management, traffic planning, crime prevention plan, credit information investigation, safe school route examination, traffic light installation examination, It can be used for applications such as lifeline maintenance. The map database used for customer management may be a map database that stores home renovation information, new customer information, replacement demand customer information, sales area information, and the like.
[0030]
The map output device of the present invention is
A map information output device that outputs map information based on a map database representing a map,
The map database has a plurality of different data in time series at least in part,
The map information output device comprises:
A specification part for specifying an extraction condition for extracting data to be output;
The gist of the present invention is to include an extraction unit that extracts data that meets the extraction condition over the time series, and a map information output unit that outputs the extracted data.
[0031]
By doing so, it is possible to output a plurality of different data in time series. The extraction condition can be specified based on the same / difference / similarity of name / position / shape / attribute.
[0032]
The map database may store a plurality of different versions in time series over the entire map. For example, the map data of each revised version distributed by the CD-ROM may be held together. In such a case, the feature data and attribute data in each version are not necessarily associated with the time information. The feature data and attribute data are grasped in time series according to the time when each version is issued.
[0033]
The map database is
Feature data prepared for each feature represented on the map;
Attribute data storing predetermined attributes related to the feature,
It is desirable that at least one of the feature data and the attribute data is associated with predetermined time information related to the feature and the attribute.
[0034]
In this way, it is possible to output a plurality of feature data and attribute data that are different in time series. In addition, since the feature data and attribute data are associated with time information such as the construction time, the construction time and the like can be accurately analyzed regardless of the revision time of the map data.
[0035]
In the map information output device of the present invention,
At least a part of the data stores link data that specifies time-sequentially different data corresponding to the data,
The extraction unit may perform extraction over the time series based on the identification result.
[0036]
By doing in this way, extraction over time series can be performed easily.
[0037]
In the map information output device of the present invention,
A processing unit that performs predetermined information processing on the data extracted over the time series,
The output may be an output corresponding to the processing.
[0038]
By doing in this way, the data corresponding to a feature can be processed in time series. For example, processing such as sorting, classification, comparison, and summation can be performed.
[0039]
As the output format, visual output such as documents and drawings can be used. At this time, various formats such as a list, a table, and a graph can be used. In addition, an audio output by voice may be used. For example, when a map database is used for a car navigation system, voice synthesis or guidance by a bell may be performed.
[0040]
In the map information output device of the present invention,
The information processing may be statistical processing relating to the extracted data.
[0041]
The statistical process includes, for example, a process of calculating an increase / decrease rate, an increase / decrease number, an average value, etc., and obtaining a maximum value, a minimum value, and a median value for a quantitative event such as an accident or business performance. The feature, time, etc. corresponding to the maximum value, minimum value, and median value may be obtained. Further, the statistical processing is not limited to calculation of numerical values, and may be geographical processing such as obtaining an area where the extracted features are dense.
[0042]
The output may be a difference, difference, or difference output over time series, or may be an output of the same / similar portion over time series examples. For example, it may indicate a road with little traffic change in time series.
[0043]
In the map information output device of the present invention,
The map information output unit outputs the extracted result,
It may be output separately from the map,
It is good also as what outputs with at least one part of the said map.
[0044]
When outputting together with at least a part of the map, the extracted result can be browsed and confirmed while comparing with the map.
[0045]
For example, a graph or a table showing the extracted results may be attached to a map and output. At this time, an extraction result related to the feature may be output by clicking on the feature or icon on the map. Further, each administrative division on the map may be color-coded according to the extraction result, or a plurality of shapes that are different in time series may be superimposed and displayed. Or it is good also as what outputs the difference and difference of a some shape etc. which differ in time series, and an invariable part.
[0046]
In the map information output device of the present invention,
The map information output unit may output the map in a manner corresponding to the extracted result.
[0047]
For example, the feature to be extracted may be highlighted or the color or character size may be changed. Moreover, it is good also as what highlights the road where the reduction rate of the number of accidents is high. Furthermore, it is also possible to identify an administrative division including a road where the number of accidents has decreased in the past several years, and to output a map with blank areas other than the administrative division.
[0048]
The present invention can be configured in various modes such as a map database output method in addition to a map database data structure and a map information output device. Moreover, you may comprise as a signal which can be equated with the computer program itself which implement | achieves these methods with a computer, or this. Furthermore, you may comprise as a recording medium which recorded these computer programs.
[0049]
Here, the storage medium may be a flexible disk, CD-ROM, magneto-optical disk, IC card, ROM cartridge, punch card, printed matter on which a code such as a bar code is printed, an internal storage device of a computer (memory such as RAM or ROM). ) And various types of computer-readable media such as external storage devices.
[0050]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described based on examples of a map information output system.
A. First embodiment: Accident analysis processing:
A1. System and functional block configuration:
A2. Data structure:
A3. processing:
B. Second embodiment: Resident analysis processing:
B1. Data structure:
B2. processing:
B3. Variation:
C. Third embodiment: Bank analysis processing:
C1. Data structure:
C2. processing:
C3. Variation:
D. Fourth embodiment: Land price analysis processing:
D1. Data structure:
D2. processing:
E. Example 5: Traffic analysis processing:
E1. Data structure:
E2. processing:
[0051]
A. First embodiment: Accident analysis processing:
A1. System and functional block configuration:
FIG. 1 is an explanatory diagram showing the system configuration of the map information output system. The map information output system includes a map server 100 and a personal computer 100a connected by a network INT. The map server 100 holds map data representing a map. Note that the network INT may be a wide area network such as the Internet or a limited network such as a local area network.
[0052]
The personal computer 100a acquires desired image data from the map server 100 by sending request data. The map server 100 acquires the request data, and creates image data while referring to the map data. The image data includes map information related to the map represented by the map data. The user can browse the map information by causing the browser executed on the personal computer 100a to process the image data.
[0053]
FIG. 1 also shows the functional block configuration of the map server 100. The functional blocks shown in the figure are configured by software in a control program executed by the map server 100. However, each functional block may be configured in hardware. The map server 100 includes a communication unit 110, an instruction unit 111, an analysis unit 112, an extraction unit 113, a map storage unit 114, and a display unit 115.
[0054]
The communication unit 110 manages communication with the personal computer 100a.
The instruction unit 111 acquires request data representing a request from the personal computer 100a via the communication unit 110. The instruction unit 111 gives an instruction to the analysis unit 112 and the display unit 115 based on the request data.
[0055]
The map storage unit 114 stores a plurality of versions of map data prepared for each year. The map storage unit 114 holds map data representing past maps in addition to map data representing maps of the latest year. In the following description, it is assumed that the 99-year map data and the 98-year map data are held. The 1999 version is the latest version of the data. The map data includes feature data representing features such as buildings and forests. Details of the map data will be described later.
[0056]
The map data is used as the latest version of the map that was revised in the previous year. For example, the map data of the 1999 version is map data created based on surveying / survey in 1998.
[0057]
The analysis unit 112 analyzes the map based on an instruction from the instruction unit 111. The analysis unit 112 performs analysis by referring to the map data stored in the map storage unit 114. The analysis unit 112 passes the analysis result to the display unit 115 to generate image data.
[0058]
The extraction unit 113 extracts the feature data instructed by the analysis unit 112 from the map storage unit 114 over time.
[0059]
The display unit 115 generates image data based on the instruction of the instruction unit 111 while using the analysis result of the analysis unit 112 and the stored content of the map storage unit 114. The display unit 115 sends the generated image data to the personal computer 100a via the communication unit 110.
[0060]
A2. Data structure:
FIG. 2 is an explanatory diagram showing the data structure of the map storage unit 114.
As shown in FIG. 2, the map storage unit 114 stores two sets of map data, a 98-year version and a 99-year version. Each map data includes feature data prepared for each feature represented on the map. In the feature data, the shape and attribute of the feature, an event related to the feature, and the like are stored. In this embodiment, for the sake of convenience of explanation, the case of processing two sets of map data of the 98 version and the 99 version has been shown, but the same applies to the processing of three or more sets of map data. For example, a 97 year edition may be added.
[0061]
FIG. 2 shows the details of the data structure of the feature data together with the feature data 1 of the 1998 version. The feature data includes a name record, a shape record, an attribute record, and an event record.
[0062]
The name record stores the name of the feature. In the case of the feature data 1 in FIG. 2, the name “road 1” is stored. The shape record stores the shape of the feature on the map in a polygon data format. Details of the storage in the polygon data format will be described later. The attribute record stores the attribute of the feature. In the case of road 1, the case where the classification of the feature is “road” and the road type is “national road” is shown.
[0063]
The event record stores events associated with the feature. In the case of the present embodiment, the number of accidents on the road represented by the feature data is stored. In the case of road 1, the number of accidents “10 times” is stored. This is the number of accidents that occurred on the road 1 from the creation of the 1997 edition to the creation of the 1998 edition. That is, an event of 10 accidents is stored in association with a feature called road 1. In addition, it is good also as what memorize | stores an accident according to actual accident occurrence. In such a case, accidents from the creation of the 1998 version to the creation of the 99 version are added to the 1998 version map and sequentially stored. Memorize the accident after the 1999 edition is made on the 99 edition map.
[0064]
Further, FIG. 2 also shows the shape 10 of the road 1 on the 1998 version map ma2. The shape record of the road 1 stores the shape of the road 1 by polygon data including the positions of the six points p1, p2, p3... P6. The map is coordinated in an xy orthogonal coordinate system. The shape record of the road 1 stores six points p1, p2, p3... P6 while using this xy coordinate system. Note that the end points T1 and T2 of the road 1 are also stored in the shape record of the road 1. The end points T1 and T2 will be described later.
[0065]
A3. processing:
FIG. 3 is a flowchart showing the accident analysis output process. The map server 100 acquires the request data by performing the process shown in FIG. 3, performs the process with reference to the stored contents of the map storage unit 114, and sends the image data desired by the user.
[0066]
In step sa1, the instruction unit 111 acquires request data. The request data includes an instruction of the map range to be processed by the analysis unit 112 and the mode of image data output by the display unit 115. The instruction unit 111 gives an instruction to the analysis unit 112 and the display unit 115 based on the request data. Thereafter, in the analysis process of steps Sa2 to Sa4, the analysis unit 112 performs the analysis process.
[0067]
In step sa <b> 2, the analysis unit 112 extracts the feature data whose classification is “road” from the 99-year version map data.
[0068]
In step sa3, the extraction unit 113 identifies the road corresponding to the road extracted in step Sa2 in the 1998 version of the map data. Specifically, a road having the same end point is specified. Here, the position of the end point of the road is stored in the shape record. In order to explain the end points of the road, the map ma2 in FIG. 2 also shows the positions of the end points t1 and T2 of the road 1 together. The extraction unit 113 examines the coincidence / non-coincidence for the end points.
[0069]
In step sa4, the analysis unit 112 compares the stored contents of the shape records to identify roads having a change in shape from the 98 version to the 99 version. That is, by identifying the roads whose end points coincide with each other and whose shape has changed, the roads modified from the 1998 version to the 1999 version are grasped.
[0070]
In step sa5, the analysis unit 112 performs statistical processing of accidents regarding the road identified in step sa4. Specifically, the reduction rate of the number of accidents before and after renovation is calculated.
[0071]
In step sa6, the display unit 115 generates image data based on the accident reduction rate calculated by the analysis unit 112, and sends the image data to the personal computer 100a.
[0072]
FIG. 4 is an explanatory diagram showing an example of accident analysis processing.
The map storage unit 114 stores roads included in the 1998 and 99 version maps as feature data. The 99-year map ma1 has roads a to d. The 1998 version map ma2 has roads 1-4.
[0073]
In the process of step sa2 in FIG. 3, the analysis unit 112 extracts the feature data of the 1999 version of roads a to d. In step sa3, according to the roads a to d extracted in step Sa2, the extraction unit 113 specifies the 1998 version of roads 1 to 4, respectively. This is because the end points of roads a to d and roads 1 to 4 coincide with each other. In step sa4, road a and road 1 and road c and road 3 are specified. This is because the shape changes in the 99 and 98 editions, respectively. Road b and road 2, road d and road 4 are not specified because they have the same shape.
[0074]
In step sa5, the reduction rate of the number of accidents before and after the repair is calculated for the road specified in step sa4. For road 1 and road a, the decrease rate is “(10−8) ÷ 10 × 100 = 20%”. For the road 3 and the road c, the decrease rate is “(10−9) ÷ 10 × 100 = 10%”.
[0075]
FIG. 5 is an explanatory diagram showing an interface for outputting the processing result of the map server 100. The output image data in step Sa6 is displayed by the personal computer 100a.
[0076]
The output image 200 displays a 99-year version map. In the output screen 200, accident reduction rate displays 213 a and 223 a are respectively attached to the road displays 210 a and 220 a of the roads a and c related to the repair. Accident reduction rate displays 213a and 223a are displayed in association with roads that have been repaired. The accident reduction rate displays 213a and 223a are assigned the processing results of step Sa5 in FIG. 3 for roads a and c, respectively.
[0077]
According to the map information output system described above, by storing the road position / shape and the number of accidents in association with each other, it is possible to objectively grasp the transition of the road position / shape and the number of accidents. Further, by outputting the calculation processing result together with the map, the user can sufficiently grasp the processing result while comparing with the map.
[0078]
Here, on the output screen 200 in FIG. 5, the roads a and c related to the repair may be highlighted. In FIG. 5, the highlights 210a and 220a of the roads a and c related to the repair are schematically shown by hatching. By such highlighting, the result of the calculation process can be grasped sufficiently while comparing with the map.
[0079]
In addition, on the output screen 200, the roads 211a and 221a before the repair of the 1998 version roads 1 and 3 may be displayed together. The map display including roads before and after the renovation shows the chronological transition of the road shape, making it easier to analyze the causal relationship with the improvement rate.
[0080]
The road displays 211a and 221a before the repair and the accident reduction rate displays 213a and 223a may be displayed by clicking the road displays 210a and 220a after the repair.
[0081]
In addition, the extraction part 113 demonstrated as what extracts based on the end point and shape of a road. However, it is not limited to such a case. For example, it is good also as what extracts based on a name record. Further, the repair information may be stored in an event record and used for extraction.
[0082]
B. Second embodiment: Resident analysis processing:
The map information output system described below is common to the system of the first embodiment in terms of system configuration and functional block configuration. Further, the data configuration used by the map storage unit 114 and the content of processing are substantially the same as those of the system of the first embodiment. In the following description of the second embodiment, the differences will be mainly described while being compared with the case of the first embodiment.
[0083]
In the second embodiment, the map server 100 uses feature data representing “house”. The house feature data stores the resident. The map server 100 performs a map display for identifying a house having a resident change from the old version. Newspaper sellers use this information to conduct sales activities for subscription contracts.
[0084]
B1. Data structure:
FIG. 6 is an explanatory diagram showing a data structure for storing map data used for the resident analysis process. In the feature data 1 in the figure, it is stored in the attribute record that the feature represents a house. Further, in the feature data 1, it is stored in the event record that the resident of the house is “Suzuki”. Moreover, in the feature data 2 and 3, it is memorize | stored in an attribute record that it is the feature data showing a parking lot and an empty space, respectively. In this embodiment, the administrator of the map server 100 inputs new year map data into the map server 100. The new year's map data reflects changes in tenants.
[0085]
Although omitted in FIG. 6 for the sake of illustration, the map data of this embodiment includes feature data such as roads in addition to houses. In FIG. 6, shape records such as the feature data 1 are also omitted. Hereinafter, parts omitted for the sake of illustration are the same as in the description of the first embodiment. Further, in this embodiment, for convenience of explanation, it is assumed that the map data of the 99 version and the 98 version are the same except for the event record in the feature data. Further, the same name is stored in the corresponding feature data of different years. The extraction unit 113 will be described below as specifying feature data of different years based on the same name.
[0086]
B2. processing:
FIG. 7 is a flowchart showing the resident analysis process. The process shown in FIG. 7 corresponds to the analysis process (steps Sa2 to Sa4 in FIG. 3) in the first embodiment.
[0087]
In step Sb1, house feature data included in the 99 version map data is extracted. In step Sb2, the extraction unit 113 identifies the house corresponding to the house extracted in step Sb1 from the 1998 version map data. As described above, in this embodiment, the identification is performed based on the same name record. In step Sb3, the event records of the feature data extracted in steps Sb1 and Sb2 are compared, and those having differences, that is, those having different old and new residents are selected. In step Sb4, in order to visit the house selected in step Sb3, the feature data of the parking lot closest to this house is searched. At this time, the feature position information stored in the shape record is used. The search for the parking lot may be omitted.
[0088]
FIG. 8 is an explanatory diagram illustrating an example of a resident analysis process.
In step Sb1 in FIG. 7, a 99-year version of the house is extracted. Here, it is assumed that houses of “section 1” and “section 2” are extracted. In step Sb2, the extraction unit 113 identifies the sections 1 and 2 of the 98 version map data based on the same name. In step Sb3, the difference between the tenant and the 98 version is checked. As for section 1, “Tanaka” is stored in the 1998 version, and “Suzuki” is stored in the 99 version. Regarding the section 2, “Harada” is stored in both the 99 version and the 98 version. The analysis unit 112 detects a difference regarding the section 1. In step Sb4, based on the difference, the analysis unit 112 extracts the parking lot in the section 3 that is closest to the house in the section 1.
[0089]
FIG. 9 is an explanatory diagram showing an interface for specifying a house where a resident has been changed and a searched parking lot. This is a display of the processing results for the map shown in FIG.
[0090]
A display 210b indicating the house position is attached to the output screen 200b showing the house extraction result. This is attached corresponding to the display 211b of the house in the section 1 where the resident change is detected in step Sb3 of FIG. The resident name is shown in the display 210b indicating the position of the house. Furthermore, the display 220b which shows the position of a parking lot is attached | subjected to the output screen 200b. This is attached corresponding to the display 221b of the parking lot searched in step Sb4 of FIG.
[0091]
According to the map information output system described above, it is possible to easily grasp a house whose attribute has changed over a plurality of versions. By displaying the map while identifying the house, the user can easily grasp the position and distribution of the desired house.
[0092]
In this embodiment, the newspaper seller may correct the latest version of map data based on the result of actual sales activities. For example, it may be possible to store the fact in the event record for a house that has been successfully subscribed. At this time, by adding an extraction condition in step Sb1 in FIG. 7, a house that has been successfully subscribed can be excluded from the processing targets in step Sb2 and subsequent steps. Similarly, a resident may be subject to correction.
[0093]
B3. Variation:
Here, a case where the map server performs a route search on a map will be described as a modification of the second embodiment.
[0094]
The request data acquired by the instruction unit 111 in this modification includes information on the current position of the user. The analysis unit 112 performs a route search from the current position to the parking lot searched in step Sb4 in FIG. The display unit 115 outputs image data based on the route search result. In the analysis processing shown in FIG. 7, the analysis unit 112 performs a route search after searching for a parking lot in step Sb4.
[0095]
FIG. 10 is an explanatory diagram showing an interface for specifying a route search result to the searched parking lot. The output screen 205b showing the route search result is the same as the output screen 200b of FIG. 9 in that a display 215b showing the position of the house and a display 225b showing the position of the parking lot are attached. The output screen 205b further includes a display 230b indicating the current position and a display 231b of a route from the current position to the parking lot.
[0096]
C. Third embodiment: Bank analysis processing:
In the third embodiment, the map server 100 uses feature data representing “bank”. In this embodiment, the 98 version banks will merge. The merged bank is included in the 1999 map data.
[0097]
In this embodiment, the feature data is different from that in the first embodiment in that it includes a link for specifying a past event record. By using this link, the extraction unit 113 can specify the number of scandals retroactively while responding to the succession relationship before and after the merger. The analysis unit 112 can analyze the number of scandals while grasping the continuation status of bank business before and after the merger.
[0098]
C1. Data structure:
FIG. 11 is an explanatory diagram showing the data structure of map data including links.
The event record of the bank feature data in this embodiment records the number of scandals of the bank. Here, the number of scandals is recorded in association with the link. The link identifies the location of the past number of scandals. In the case of AB Bank, there are two links for the number of scandals. This is because the A and B banks in the 1998 version map merged to create the AB bank. Each link identifies the location of the number of scandals in both the 1998 and A banks. If there is no merger, one link is enough.
[0099]
C2. processing:
FIG. 12 is a flowchart showing a scandal analysis process performed by the analysis unit 112.
In step Sc1, the bank specified by the request data is extracted from the 99-year map data.
[0100]
In step sc2, the content of the number of scandals included in the feature data is extracted. Here, we take out the 1999 version of the bank.
[0101]
In step sc3, it is determined whether or not past map data is to be processed. The range in which data is to be extracted is designated in advance by the request data. If it is necessary to extract past map data, the process proceeds to step Sc3r. In step Sc3r, the extraction unit 113 takes out the link. In the first step Sc3r, a link about the scandal of the 1999 version is taken out. Thereafter, in step Sc2, the number of scandals of the old year version specified by the link extracted in step Sc3r is extracted.
[0102]
In this way, past data is extracted in a chained manner while referring to the link, and when the number of scandals for all the map data in the range specified by the requested data is finished, the process proceeds to step Sc4 according to the determination in step Sc3. Moved. In step Sc4, the total number of scandals taken out is counted for each bank in the 99 version.
[0103]
FIG. 13 is an explanatory diagram showing an example of a map that records the number of scandals. In the 99 version map mc1, AB bank and C bank exist. For AB bank and C bank, the number of scandals 5 times and 2 times are stored respectively. Similarly, in the 1998 version map, banks A to C exist, and the map storage unit 114 stores the number of scandals.
[0104]
In FIG. 13, the number of scandals in the 1998 version map specified by the link for the 1999 version of AB bank and C bank is indicated by a dashed line arrow. The link included in the feature data of the AB bank specifies the number of scandals of the A bank and the B bank in the 1998 map mc2.
[0105]
FIG. 14 is an explanatory diagram showing the contents of the scandal analysis process. This is a scandal analysis process based on the map data shown in FIG. Regarding the 1999 version of the map, the number of scandals of AB Bank and Bank C will be taken out 5 or 2, respectively. In addition, the number of scandals 1, 3 and 2 of Banks A, B and C are taken out of the 1998 version map. These scandals are summed in step Sc4 in FIG. The number of scandals at AB Bank is “5 + 1 + 3 = 9”, and the number of scandals at Bank C is “2 + 0 = 2”.
[0106]
FIG. 15 is an explanatory diagram showing an interface for outputting the number of bank scandals before and after the merger. This shows an output screen 200c based on the processing result shown in FIG. On the screen 200c for outputting the number of scandals, an AB bank scandal count display 212c and a C bank scandal count display 222c are displayed. They are shown attached to the AB bank position display 210c and the C bank position display 220c, respectively. In FIG. 15, the scandal number display 212 c indicates that the former bank from which AB bank was merged is the A and B banks. However, the present invention is not limited to this case.
[0107]
According to the map information output system described above, the number of scandals over a plurality of years can be easily extracted by using links, regardless of merger / name change of features.
[0108]
FIG. 15 also shows that the merger from Bank A and Bank B to Bank AB occurred in February 1998 in the AB Bank scandal count display 212c. The merged month is stored in the event record of AB bank shown in FIG. 11, and the display unit 115 reads this and displays the merged month.
[0109]
C3. Variation:
In the following, various cases will be described with respect to modifications of the third embodiment.
First, various cases can be considered for the mode indicating the number of scandals. For example, by clicking the bank position displays 210c and 220c, the scandal number displays 212c and 222c indicating the total number of scandals over the 98-99 edition may be displayed. In addition, it is possible to confirm the number of scandals of AB and C banks by the 99 version alone by 5, 5 times or the scandals by the 98 version of A, B and C banks by the same mouse operation. Good.
[0110]
Further, by clicking the position display 210c of the AB bank, the building positions of the 1998 version A and B banks which are the merger banks may be confirmed. At this time, as in the case of FIG. 15, the number of scandals of Banks A and B in the 1998 edition may be shown one or three times, or the total number of scandals over multiple years before the 1998 edition is also shown. It is good.
[0111]
Secondly, in this embodiment, the number of scandals of the banks before and after the merger is associated with the link, but the present invention is not limited to this case. For example, when there is a transfer of a bank building, the number of scandals stored in association with the building before the transfer may be associated with the number of scandals stored in association with the building after the transfer. This is the case, for example, when the location of the 1999 version C bank building is different from the location in the 98 version (see FIG. 13). At this time, the map server 100 may show the old and new bank buildings together on the map. According to such a map information output system, the number of scandals over a plurality of years can be easily extracted regardless of the movement of the feature.
[0112]
Third, a modified example of the link will be described. In the above description, it is assumed that the version specification is not included in the link, and all the links specify the event record of the previous year. The link includes designation of a version, and may specify not only one but a plurality of versions of records. Furthermore, in the above embodiment, the link is a link that associates the number of scandals. The links may be associated in units of feature data or event records.
[0113]
Fourth, a case where the map storage unit 114 does not store a plurality of versions over the entire map data will be described. For the sake of convenience, in the above description, the map storage unit 114 holds 99-year map data, 98-year map data, and the like. However, the present invention is not limited to such a case. For example, in the third embodiment, all records such as shape records and attribute records may be stored only for the latest 99 version, and only event records may be stored for the 98 version and earlier. In such a case, the map server 100 can perform analysis based on the event record. According to such a map information output system, the storage capacity can be reduced.
[0114]
Similarly, in cases other than the third embodiment, a plurality of versions may not be stored over the entire map data. For example, in the first embodiment, a plurality of versions may not be stored over the entire map data, and a plurality of versions may be stored for each feature data. In the data structure of FIG. 4, the 99 version data is stored only for the roads a and c related to the repair. At this time, you may memorize | store only about the shape about the roads a and c, and may memorize | store only about the number of accidents about the roads a and c.
[0115]
D. Fourth embodiment: Land price analysis processing:
In the fourth embodiment, the analysis unit 112 compares the old and new maps to check for demolition of the building and other changes. In this embodiment, the map data includes land price information. The analysis unit 112 examines changes in buildings and changes in land prices over time.
[0116]
D1. Data structure:
FIG. 16 is an explanatory diagram showing a data structure for storing map data including land price information. In FIG. 16, the feature data 1 represents “Area A” on the map md. In the event record of the feature data 1, the land price of the area A is stored.
[0117]
On the other hand, the feature data 2 represents “Store A”. Store A exists in area A. The feature data 3 represents “Store B” outside the area A.
[0118]
D2. processing:
FIG. 17 is a flowchart showing the land price analysis process.
In step Sd1, feature data whose classification is “region” is extracted over time.
[0119]
In step Sd2, the land price information extracted in step Sd1 is extracted. In step Sd2, for each area extracted in step Sd1, the in-region features included in the area are extracted. The extraction is performed based on the inclusion relation of polygon data of each feature.
[0120]
In step Sd3, the land price fluctuation is examined for each region. Further, in step Sd3, the increase / decrease in the number of local features is checked for features such as stations and shops. If a local feature that existed in the past no longer exists in the latest map data, it is determined that the feature is demolished and “disappeared”. On the contrary, when the thing corresponding to the local feature in the latest map data does not exist in the past map data, it is determined that it is “newly constructed”.
[0121]
In step Sd4, the land price examined in step Sd3 and the changes in the local features are compared for each region. In step Sd5, the correlation between the change in the feature and the change in the land price is determined based on the comparison result in step Sd4. The processing of steps Sd4 to Sd5 will be described in detail below with a specific example.
[0122]
FIG. 18 is an explanatory diagram showing an example of a map including land price information. Below, the content of the land price analysis process about the map shown in FIG. 18 is demonstrated.
[0123]
First, area A and area B are extracted from the map data of the 1999 version and the 98 version, respectively. In the A and B areas, the land price is 50,000 yen / m for the 1998 map data. ² It is grasped. In addition, the map data of 1998 version is 70,000 yen / m for both regions. ² It is grasped. In addition, in the A and B areas, it is understood that the features include the station A and the shop A in the A area and the shop B in the B area in the 99 version map. It can be seen that the 1998 version of the map does not contain significant features in both A and B areas.
[0124]
About change of land price, A area is 20,000 yen / m ² Rise, B area is 30,000 yen / m ² It is a decline, and the difference between A and B areas is 50,000 yen / m ² Magnification is calculated. Regarding the change in the feature, it is grasped that the station A and the store A are newly constructed in the A area, and the store B is newly constructed in the B area. From the above, it can be understood that the number of stores increases between the A and B areas, and the difference between the A and B areas increases by one for the number of stations.
[0125]
From the above, in step Sd5, it is concluded that the increase or decrease in the store is irrelevant to the change in land prices. It is concluded that the increase in stations has a positive correlation with changes in land prices. The conclusion in step Sd5 is sent to the personal computer 100a by a process corresponding to step Sa6 in FIG. 3 in the first embodiment. The display unit 115 sends image data representing the conclusion content in text.
[0126]
In this embodiment, the conclusion content is output separately from the map. However, it is not limited to such a case. For example, as in the case illustrated in the previous embodiment (see FIGS. 5, 9 to 10, and 15 to 16), it is also conceivable to send image data in which the conclusion content is embedded in a map.
[0127]
According to the map information output system described above, a plurality of extraction results can be compared. Specifically, it is possible to objectively grasp changes in land prices and features and analyze the correlation between changes in land prices and changes in features.
[0128]
Further, in this embodiment, the change of the feature is illustrated by taking a new feature. Feature changes include demolishing, moving, and refurbishing features. Similar processing can be performed in these cases.
[0129]
E. Example 5: Traffic analysis processing:
Finally, the case of analyzing road traffic by recording the date of accident for each road will be described. The events stored in the map server 100 in this embodiment include accidents that occur on the road and new construction of roads due to construction. The user adds memory of the event according to the actual event occurrence. The user can obtain a desired processing result based on the latest stored contents.
[0130]
E1. Data structure:
FIG. 19 is an explanatory diagram showing a data structure for recording the date of an accident for each road.
Roads 1 to 3 exist on the map maE. The event record of the feature data representing the road stores the construction date of the road. For example, for road 2, the date of construction is stored as 10/30. The event record stores an accident on the road. For accidents, the date and location of the accident are stored. For example, in the case of the accident A on the road 1, the date of the accident is 10/10, and the accident position is stored as coordinates (51, 27).
[0131]
The storage of events may be performed by sorting in order of date. Moreover, an accident and road construction may be memorize | stored separately and may be memorize | stored integrally.
[0132]
E2. processing:
FIG. 20 is a flowchart showing traffic analysis processing. The process shown in FIG. 20 corresponds to the analysis process (steps Sa2 to Sa4 in FIG. 3) in the first embodiment.
[0133]
In step Se1, the analysis area designated by the request data is grasped. In the analysis area, the request data designates a rectangular area on the map. FIG. 19 illustrates the analysis area 5e. The user of the personal computer 100a can specify the analysis area by operating the mouse on the map. In step Se2, a road that at least partially overlaps the analysis area is extracted. At this time, the construction date of the road is grasped. In step Se3, accidents in the analysis area are extracted. The extraction need only be performed for the road accident extracted in step Se2. In step Se4, the number of accidents is calculated every month.
[0134]
When the map storage unit 114 has the storage contents shown in FIG. 19 and the user designates the analysis area 5e, the roads 1 and 2 are extracted in step Se2. In step Se3, accidents B, C, and D are extracted. The accident A is not extracted because it is not an accident in the analysis area 5e.
[0135]
FIG. 21 is an explanatory diagram showing an interface for outputting the result of the traffic analysis process. This shows an interface in the case of outputting the processing result for the stored contents shown in FIG. The processing result is shown by a graph 201e. In the graph 201e, the horizontal axis represents the passage of years. The vertical axis represents the number of monthly accidents in the analysis area 5e. A broken line 202e in the graph 201e indicates the number of accidents per month. Further, a display 203e of the new date of the road 2 is also shown.
[0136]
According to the map information output system described above, it is possible to memorize road accidents and road construction dates in a time series. Various information processing can be performed.
[0137]
In the map information output system described above, a link can be used in the same manner as in the previous embodiment. For example, it is possible to use a link that correlates memories of accidents in the analysis area 5e in time series. Conversely, the information processing in the previous embodiment can be realized by the same data configuration as in the present embodiment.
[0138]
Further, in the present embodiment, description has been made by taking a traffic accident and road construction as examples. However, other various events and other attributes can be similarly stored. For example, the traffic regulation on the road and the change date of the road type may be stored. Further, the date of connection 10/30 of the road 2 to the road 1 may be stored in association with the road 1.
[0139]
Here, in the above various explanations, explanations have been made focusing on events, but the same applies to road type and other attributes.
[0140]
As mentioned above, although the various Example of this invention was described, it cannot be overemphasized that this invention is not limited to these Examples, and can take a various structure in the range which does not deviate from the meaning. For example, the above processing may be realized by hardware as well as by software.
[0141]
Here, the user may be able to change one or both of the event record and the attribute record in accordance with an actual event occurrence such as road repair or an accident occurrence. These additions / changes may be performed by directly operating the map server 100 or may be performed from the personal computer 100a via a network.
[0142]
In this case, the event record or the like may be stored in association with the identifier of the user or user group. By doing in this way, the map information according to each user etc. can be provided. For example, the map server 100 may store business records of a plurality of salesmen on a single map, or store business records of a plurality of sales groups on a single map. Each salesperson can view and change his / her business records according to actual business activities by using a mobile terminal or the like.
[0143]
Further, the event record or the like may be added / changed by an unspecified user. For example, like a so-called bulletin board in the WWW, reports and evaluations may be additionally stored from unspecified users in association with sightseeing spots shown on a map.
[0144]
Furthermore, the map server 100 and the personal computer 100a may share and store a map database. For example, the event record or the like may be stored in the personal computer 100a, and the other may be stored in the map server 100. At this time, the shape record etc. which the map server 100 memorize | stores is good also as what is matched with the event record etc. which each personal computer of a some user memorize | stores. For the correspondence between the two, for example, an identifier of a user or a user group can be used. Further, various processes as shown in the flowchart of FIG. 3 may be performed by the map server 100 or the personal computer 100a.
[0145]
The map server 100 may be realized by the personal computer 100a alone. In such a case, for example, a car navigation device mounted on an automobile may store a map database and provide map information to the driver. At this time, the personal computer 100a and the car navigation device may acquire new shape data or the like via a network such as a wireless network or a storage medium such as a CD-ROM. Further, addition / change of an event record or the like may be possible.
[Brief description of the drawings]
FIG. 1 is an explanatory diagram showing a system configuration of a map information output system.
FIG. 2 is an explanatory diagram showing a data configuration of a map storage unit 114;
FIG. 3 is a flowchart showing an accident analysis output process.
FIG. 4 is an explanatory diagram showing an example of accident analysis processing;
FIG. 5 is an explanatory diagram showing an interface for outputting a processing result of the map server 100;
FIG. 6 is an explanatory diagram showing a data configuration for storing map data used for resident analysis processing;
FIG. 7 is a flowchart showing a resident analysis process.
FIG. 8 is an explanatory diagram showing an example of a resident analysis process.
FIG. 9 is an explanatory diagram showing an interface for specifying a house where a resident has been changed and a searched parking lot;
FIG. 10 is an explanatory diagram showing an interface for specifying a route search result to a searched parking lot.
FIG. 11 is an explanatory diagram showing a data configuration for storing map data including a link.
12 is a flowchart showing a scandal analysis process performed by an analysis unit 112. FIG.
FIG. 13 is an explanatory diagram showing an example of a map including banks before and after the merger.
FIG. 14 is an explanatory diagram showing an example of specific contents of a scandal analysis process.
FIG. 15 is an explanatory diagram showing an interface for outputting the number of scandals of the bank before and after the merger.
FIG. 16 is an explanatory diagram showing a data configuration for storing map data including land price information.
FIG. 17 is a flowchart showing land price analysis processing;
FIG. 18 is an explanatory diagram showing an example of a map including land price information.
FIG. 19 is an explanatory diagram showing a data configuration for recording the date of an accident for each road.
FIG. 20 is a flowchart showing traffic analysis processing.
FIG. 21 is an explanatory diagram showing an interface for outputting a result of traffic analysis processing;
[Explanation of symbols]
100 ... Map server
100a ... Personal computer
110: Communication unit
111 ... Indicator
112 ... Analysis Department
113 ... Extraction unit
114 ... Map storage unit
115 ... Display section
ma1 ... 99 version map
ma2 ... 1998 edition map
10. Shape of road 1
p1, p2, p3, p4, p5, p6 ... points on road 1
T1, T2 ... Endpoint
200 ... Output image
210a, 220a ... road display
211a, 221a ... Display of road before renovation
213a, 223a ... Accident reduction rate display
200b ... Output screen showing house extraction results
210b ... Display indicating the position of the house
211b ... Display of extracted house
220b ... Display indicating the position of the parking lot
221b ... Display of searched parking lot
205b ... Output screen showing route search result
215b ... Display indicating the position of the house
215b: Display indicating the position of the parking lot
231b ... Display of route
230b ... Display indicating current position
mc1 ... 99 version map
mc2 ... 98 edition map
212c, 222c ... Number of scandals
210c, 220c ... Bank position display
md ... Map
md1 ... 98 edition map
md2 ... 1999 version map
201e ... graph
202e ... Accident line
203e ... Date of new construction

Claims (5)

A map information output device that outputs map information based on a map database representing a map,
The map database has a plurality of different version map data different in time series at least in part,
The map information output device comprises:
A specification part for specifying extraction conditions;
An extraction unit for extracting data that conforms to the extraction condition over the time series;
A map information output unit for outputting the extracted data;
Each different version map data ,
Feature data prepared for each feature represented on the map;
Attribute data storing predetermined attributes related to the feature,
At least one of the feature data and attribute data is associated with predetermined time information related to the feature and attribute ,
The feature data includes an event record in which events related to the feature are registered,
The event record of each different version map data includes a link that sequentially identifies event records of past different version map data according to a time series,
The said extraction part is a map information output device which extracts the said event record over the said time series based on this specific result . The map information output device according to claim 1,
A processing unit that performs predetermined information processing on the event record extracted over the time series,
The map information output device, wherein the output is an output corresponding to the information processing. The map information output device according to claim 1,
The map information output unit outputs the extracted result together with at least a part of the map. A method for outputting map information based on a map database representing a map,
The map database has a plurality of different version map data different in time series at least in part,
The method
A computer extracting data that conforms to a specified extraction condition over the time series;
The computer comprising the step of outputting the extracted data;
Each different version map data ,
Feature data prepared for each feature represented on the map;
Attribute data storing predetermined attributes related to the feature,
At least one of the feature data and attribute data is associated with predetermined time information related to the feature and attribute ,
The feature data includes an event record in which events related to the feature are registered,
The event record of each different version map data includes a link that sequentially identifies event records of past different version map data according to a time series,
The extracting step includes extracting the event record over the time series based on the specific result . A computer program for causing a computer to output map information based on a map database representing a map,
The map database has a plurality of different version map data different in time series at least in part,
The computer program is
A function for extracting data that meets the specified extraction conditions over the time series;
A computer program for causing the computer to realize the function of outputting the extracted data;
Each different version map data ,
Feature data prepared for each feature represented on the map;
Attribute data storing predetermined attributes related to the feature,
At least one of the feature data and attribute data is associated with predetermined time information related to the feature and attribute ,
The feature data includes an event record in which events related to the feature are registered,
The event record of each different version map data includes a link that sequentially identifies event records of past different version map data according to a time series,
The extraction function is a computer program that extracts the event record over the time series based on the specific result .

Images