JP2013037416A - Mesh data retrieval system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a mesh data retrieval system capable of reducing retrieval time even when the number of meshes is increased by reducing a mesh size to finely describe a target terrain.SOLUTION: The mesh data retrieval system includes tile data, position input means, and retrieval means for retrieving mesh data corresponding to a designated position. The retrieval means detects target tile data on the basis of plane position information on the designated position and a range condition of the tile data, and retrieves target mesh data from among pieces of mesh data in the target tile data on the basis of plane position information of the mesh data and the plane position information on the designated position.

Description

  The present invention relates to a technique for acquiring information on an arbitrary point from a relatively wide range, and more specifically to a mesh data search system for quickly searching for target mesh data from a set of mesh data. It is.

  There is a lot of information related (linked) to the place so that the climate varies from region to region and the population varies from region to region. In addition to information associated with a relatively wide area such as the climate and population, there is also a lot of information associated with medium to small areas such as municipalities, school districts, land prices and rainfall. In particular, the ground height (elevation) differs from point to point, so it can be said that it is information associated with a very small area.

  When information associated with these places (positions) is maintained over a wide range, a large amount of information must be maintained. For example, when the information “elementary school ward” is prepared for all over Japan, it is necessary to prepare information (elementary ward) exceeding 100,000 cases. Therefore, when searching for the target information from the prepared information, the search is performed from 100,000 pieces of information. In general, therefore, information associated with the position information (for example, an elementary school ward) is generally prepared and target information can be acquired by designating the position.

  Progress in research on geographic information led by the Geospatial Information Authority of Japan has contributed greatly to the method of preparing data associated with location information as well as location information. With respect to the search technology, the evolution of software such as Geographic Information System (GIS) has greatly contributed. For this reason, a technique of preparing a large amount of data associated with the position information and performing a data search using software such as GIS has rapidly spread and is now widely used as a general technique.

  On the other hand, terrain measurement methods such as the emergence of aerial laser measurements have become so advanced that large amounts of elevation data can be easily acquired. This aviation laser measurement is performed by flying an aircraft over the terrain to be measured and receiving the reflection of the laser irradiated to the terrain during the flight. That is why you can get it. Elevation data is extremely useful and can be used in a wide variety of ways, such as construction work plans for civil engineering and architecture, and in recent years, used for inundation simulations due to inundation and inundation, inundation due to tsunamis, or for automatic driving of automobiles It is a lot of data.

  As described above, altitude data is also information associated with position information, and it is convenient to maintain it together with position information. However, it is not realistic to use countless point cloud data acquired by aviation laser measurement as it is. This is because innumerable data is stored or retrieved from innumerable data, so that a computer that executes the data becomes special and expensive.

  Therefore, when using countless point cloud data, it is common to model the target terrain. Representative examples of this modeling include DEM (Digital Elevation Model) and DSM (Digital Surface Model). In modeling, as shown in FIG. 1, it is common to divide the target range into a grid and to have representative plane coordinates (X, Y) and elevation values (Z) for each division unit (mesh). Is.

  When modeling the target terrain, of course, the target terrain can be expressed more precisely as the mesh size (mesh size) is reduced. On the other hand, as the mesh size is reduced, the amount of information increases. In other words, the search time is extremely long because a large amount of information is searched. For example, when a mesh as shown in FIG. 1 is configured, as shown in FIG. 9, mesh IDs and predetermined information (coordinates and attributes in the figure) are assigned to records (information corresponding to one line in the figure). ), And one data set (file or database) is constructed by collecting all records (0001 to N in the figure). Then, when searching by specifying a position, the data set of FIG. 9 is read, and the specified position information and each mesh are collated one by one as shown in the search image of FIG. Is extracted as a search result. Thus, the smaller the mesh size, that is, the greater the number of meshes, the longer the search time.

  Therefore, Patent Document 1 proposes a method for improving the search efficiency and reducing the search time, although it is an example of map (graphic) display.

JP-A-8-77328

  Patent Document 1 is characterized in that, conventionally, all layers have the same mesh size (number of divisions), but the number of divisions (mesh size) is changed for each layer according to the characteristics of the layer. Thereby, the search efficiency is improved as compared with the conventional case, that is, the search time is shortened.

  However, Patent Literature 1 is improved by focusing on the relative relationship between layers, and it can be said that the search time is not basically improved. That is, when the road layer illustrated in Patent Document 1 is composed of a large number of meshes, the search time cannot be shortened by the method of Patent Document 1.

The problem of the present invention is to solve the problem of the prior art including Patent Document 1, that is, the problem that the search time becomes long when it is composed of a large number of meshes. Accordingly, it is an object of the present invention to provide a mesh data search system that can reduce the search time even when the mesh size is reduced and the mesh amount is increased.

  The mesh data search system of the present invention is a system for searching for target mesh data from a plurality of mesh data obtained by dividing a predetermined region. In the system for searching for target mesh data, position input means for inputting a specified position, target mesh data And the tile data represents a divided range obtained by dividing the predetermined area into a plurality of pieces, and is composed of two or more mesh data, and the divided range is the range. The mesh data includes plane position information for specifying the mesh, and the search means includes the plane position information of the designated position input by the position input means. And including the designated position from a plurality of the tile data based on the range condition of the tile data. The target tile data is detected, and the search means further includes: The target mesh data corresponding to the designated position is searched.

  In the mesh data search system of the present invention, the range condition for specifying the division range of the tile data is a first condition configured by a maximum value and a minimum value of longitude or X coordinate, and a maximum value and a minimum value of latitude or Y coordinate. The second condition is configured, wherein the search means detects candidate tile data from the plurality of tile data based on the plane position information of the designated position and the first condition, and the search means The target tile data may be detected from the candidate tile data based on the plane position information of the designated position and the second condition.

  In the mesh data search system of the present invention, the range condition for specifying the division range of the tile data is a first condition configured by a maximum value and a minimum value of longitude or X coordinate, and a maximum value and a minimum value of latitude or Y coordinate. The second condition is configured, the search means detects candidate tile data from the plurality of tile data based on the plane position information of the designated position and the second condition, and the search means The target tile data may be detected from the candidate tile data based on the plane position information of the designated position and the first condition.

  The mesh data search system of the present invention has an attribute information extraction function, the mesh data includes attribute information related to the mesh, and the attribute information extraction function is used to search the target mesh data searched by the search means. It is also possible to extract attribute information.

  In the mesh data search system according to the present invention, the attribute information may be an altitude value or / and an inundation depth calculated within the predetermined area.

The mesh data search system of the present invention has the following effects.
(1) Since the information related to the position is acquired simply by specifying the position, the search operation is easy to understand and easy.
(2) Since the corresponding target tile data need only be detected from the tile data obtained by largely dividing the predetermined area and only the mesh data in the target tile data is searched, the predetermined area is covered with a large number of meshes. Even if it is a case, it is not necessary to search all the mesh data in a predetermined area, As a result, search time can be shortened drastically.
(3) A large amount of mesh information is not managed as a single file (or database) as in the prior art, but multiple files (or databases) are managed in units of tile data. be able to. (Even if some abnormality occurs, all mesh information is not destroyed.)

The model figure explaining the concept of the mesh data utilized with the mesh data search system of this invention. The model figure for demonstrating the mesh ID shake | assigned to mesh data. Explanatory drawing which shows the detail of mesh data. The model figure for demonstrating tile ID assigned to tile data. The model figure explaining the range conditions of each division | segmentation range. Explanatory drawing which shows the state which carried out the monitor display of the altitude value and the inundation depth as attribute information. The flowchart which shows an example (first half part) of the flow of the mesh data search system of this invention. The flowchart which shows an example (second half part) of the flow of the mesh data search system of this invention. The model figure which shows the structure of the conventional mesh data. Explanatory drawing which shows the image which searches the conventional mesh data.

  An example of an embodiment of a mesh data search system of the present invention will be described with reference to the drawings.

(Overview)
FIG. 1 is a model diagram for explaining the concept of mesh data used in the mesh data search system of the present invention. The mesh data is data representing one section (hereinafter referred to as “mesh 1”) obtained by subdividing the predetermined area 2 targeted by the mesh data search system into a lattice shape. In other words, a large number of mesh data are constructed so as to cover the entire range of the predetermined region 2. Note that the predetermined region 3 means a range having a planar spread. For example, a region such as a prefecture or a city can be cited as the predetermined region 3. Of course, the present invention is not limited to this, and the predetermined area 3 may be a relatively narrow area such as a facility such as a block or an amusement park, or a wide area such as the Kanto area or the Kyushu area.

  The mesh data is data representing the mesh 1 obtained by subdividing the predetermined area 2 and has representative coordinates and attribute information as will be described later. (Area, figure, etc.) need not be provided (may be provided). Further, in FIG. 1, the predetermined region 2 is divided into a substantially square lattice and the mesh shape is substantially square. However, the present invention is not limited to this, and any mesh shape such as a rectangle, a rhombus, or an oval can be used. Thus, the shape and size of each mesh 1 can be changed.

  As described above, in order to cover the predetermined area 2, a very large number of mesh data is constructed. The mesh data retrieval system of the present invention retrieves target mesh data easily and quickly from among these many mesh data groups. Specifically, when a target position is designated by the position input means, the search means searches for corresponding mesh data based on the position information, and provides the result to the user. A display means for providing the result can also be provided.

  Hereinafter, each element will be described in detail.

(Mesh data)
The mesh data is data representing “mesh 1” obtained by subdividing the predetermined area 2 as described above. If this mesh 1 which is an area smaller than the predetermined region 2 is formed, various methods can be adopted as a method for subdividing. Here, a method using DEM will be described as an example of a mesh data creation method.

  First, DEM will be described. The DEM is a numerical model of the topography, which is the shape of the ground surface, and is generally a lattice model. The DEM is formed as a set of points (so-called point cloud data) having the latitude and longitude of the ground surface or the plane coordinates (X, Y) and the altitude value (Z). Can be reproduced. This point cloud data can be acquired by aviation laser measurement. Of course, in addition to the aerial laser measurement, point cloud data with three-dimensional spatial information may be generated based on stereo aerial photographs and satellite photographs, or the point of having direct three-dimensional spatial information by surveying the site. Group data may be acquired.

  The point cloud data acquired by the aviation laser measurement is merely a set of laser measurement points measured at random, and the DEM is created by the following procedure. That is, a plurality of grids (for example, square lattices) arranged at predetermined intervals (for example, 2 m or 5 m) are placed on the laser measurement points. By being divided by this square lattice, lattice points are generated, and a large number of quadrangles (DEM mesh) are formed. This DEM mesh is provided with one representative point, and the position of the representative point is the center of the DEM mesh, or the grid point at the upper right corner of the DEM mesh, and can be designed as appropriate according to other situations. it can.

  Based on the three-dimensional coordinates (X, Y, Z) of the laser measurement points, the plane coordinates (X, Y) and altitude values (Z) of the DEM mesh representative points are calculated to complete the DEM. This calculation method includes an interpolation method based on TIN (Triangulated Irregular Network) that obtains the height from an irregular triangle network from a laser measurement point, a nearest neighbor method that employs the nearest laser measurement point (Nearest Neibor), and an inverse distance weighting method. Various methods such as (IWD), Kriging method, and average method are adopted.

  Next, a mesh data creation method will be described. Mesh data is created as data representing the mesh 1 constituting the DEM created as described above. FIG. 2 is a model diagram for explaining a mesh ID assigned to mesh data. As shown on the left side of this figure, when a DEM is created for a predetermined area 2, a large number of meshes 1 are arranged so as to cover the entire predetermined area 2. An enlarged view of the “a part” shown on the left side of FIG. 2 is the right side of FIG. 2. As shown in this figure, a “mesh ID” is provided for each mesh. The mesh ID is an arbitrary number as long as it is a unique number (unique and unique) for all mesh data in the predetermined area 2 or a unique number for all mesh data in tile data described later. The number method can be taken.

  When the mesh ID is assigned to the mesh 1, one plane position information is provided. The “plane position information” here is a concept including coordinates (X, Y) and latitude / longitude in a plane rectangular coordinate system, that is, a position specified on a plane by coordinates (X, Y) or latitude / longitude. That is. FIG. 3 is an explanatory diagram showing details of the mesh data. As shown in this figure, one mesh data (one line in the table in the figure) is composed of a mesh ID and plane position information (X and Y coordinates in the figure). In addition, altitude and other subject information can be provided as attribute information. When DEM is used, the plane coordinates (X, Y) of the representative point of the DEM mesh described above can be adopted as plane position information of mesh data. Similarly, when an altitude is provided as mesh data, an altitude value (Z) of a DEM mesh representative point can be employed.

  In this way, mesh data is created, and this is performed for all meshes 1 in the predetermined area 2.

(Tile data)
The created mesh data is not used individually one by one, but rather a file or database that collects a certain number of mesh data (hereinafter collectively referred to as “files”). .) A file or the like in which a bundle of mesh data is collected is tile data.

  FIG. 4 is a model diagram for explaining a tile ID assigned to tile data. 4 is an enlarged view of the “b section” on the left side of FIG. As shown in the figure, the predetermined area 2 is divided into a plurality of ranges (hereinafter, this divided range is referred to as “divided range 3”). Then, tile data is created as representing the division range 3. The divided range 3 has a plurality of meshes 1 within the range, and a plurality of divided ranges 3 are created in the predetermined area 2. In other words, the division range 3 is composed of a plurality of meshes 1, and the entire predetermined region 2 is covered by the plurality of division ranges 3. The shape and size of the division range 3 may all be the same within the predetermined region 2 or may be different as shown in FIG. For example, if the predetermined area 2 has a range of about 50 km × 50 km, the division range 3 can be about 3 km × 4 km.

  A “tile ID” is provided for each of the divided ranges 3 (right side in FIG. 4). As long as the tile ID is a unique number for all tile data in the predetermined area 2, an arbitrary numbering method can be adopted. Then, tile data is a combination of all the mesh data in the division range 3 into one file or the like (FIG. 3). Note that “T001, T105, Tn” shown in FIG. 3 are file IDs.

  FIG. 5 is a model diagram for explaining the range condition of each divided range 3. A range condition is set for the divided range 3. This range condition specifies the range of the divided range 3. For example, if the tile ID shown in FIG. 4 is described in the divided range 3 of T105, the left end X coordinate, the right end X coordinate, and the top end It is set by the Y coordinate and the Y coordinate (or longitude) at the bottom. In other words, if the left end X coordinate is the minimum value, the right side X coordinate is the maximum value, the bottom end Y coordinate is the minimum value, and the upper Y coordinate is the maximum value, the condition is that each is between the minimum value and the maximum value. This division range 3 (T105) can be specified. Of course, it goes without saying that latitude and longitude can be used instead of coordinates.

(Position input means)
When the user of the mesh data search system obtains information regarding a specific position in the predetermined area 2, the specific position is designated. A means for designating this position is a position input means. Although this position designation method can directly input plane position information (coordinates and latitude / longitude), a background map corresponding to the predetermined area 2 is prepared, and a target position is designated on the map (click operation) ) Is easy and easy to operate. When the target position (designated position) is designated by the position input means, the plane position information of the designated position is acquired and stored.

(Search means)
The search means searches for mesh data corresponding to the plane position information of the designated position input by the position input means. At this time, the target mesh data is selected through a two-stage search. For the sake of convenience, the mesh data intended by the user of the mesh data search system, that is, mesh data corresponding to the designated position is referred to as “target mesh data”. This will be specifically described below.

  In the first stage, first, tile data including target mesh data (hereinafter referred to as “target tile data”) is searched. Therefore, the plane position information of the designated position is collated with the range condition of the division range 3. That is, if the plane position information of the designated position meets the range condition of the divided range 3, the designated position exists in the divided range 3. The tile data corresponding to the divided range 3 is the target mesh data. That is, target tile data including

When detecting the target tile data, the plane position information of the designated position is between the X coordinate minimum value (Xmin) and the X coordinate maximum value (Xmax) shown in FIG. 5, and the Y coordinate minimum value (Ymin). And the Y coordinate maximum value (Ymax). That is, if the plane position information of the designated position is (Xt, Yt), the following conditional expression can be shown.
First condition Xmin ≦ Xt ≦ Xmax
Second condition Ymin ≦ Xt ≦ Ymax

  Based on the plane position information (Xt, Yt) of the designated position, the first condition and the second condition are collated for each divided range 3, and the detection is finished when the divided range 3 matching both conditions is found, Tile data corresponding to the division range 3 is extracted as target tile data.

  Alternatively, with reference to Xt in the plane position information of the designated position, first, each division range 3 is collated under the first condition, and tile data corresponding to the division range 3 conforming to the first condition is “candidate tile data”. Will pick up as. At this time, normally, a plurality of “candidate tile data” are picked up. Next, the division range 3 corresponding to the plurality of “candidate tile data” is collated under the second condition with reference to Yt in the plane position information of the designated position, and the division range suitable for this condition When 3 is found, the collation is finished, and tile data corresponding to this division range 3 is extracted as target tile data.

  Of course, contrary to the above, candidate tile data can be picked up under the second condition and the target tile data can be extracted under the first condition.

  In the second stage of the search by the search means, the target mesh data is searched from the mesh data included in the detected target tile data. Here, the search is not performed for all the mesh data in the predetermined area 2, but the mesh data included in the target tile data is searched as a candidate, so that the time required for the search is extremely shortened.

  Specifically, on the basis of the plane position information (Xt, Yt) of the designated position, each mesh data is checked against the plane position information included in the mesh data, and the mesh data determined to be the most suitable is determined. Extract as target mesh data. In this case, mesh data having plane position information closest to the plane position information of the designated position can be extracted as target mesh data. In the proximity determination, a conventionally used method such as determination based on the sum of squared differences between coordinates can be employed.

  In addition, when the plane position information of the mesh data is regular (for example, when both the X and Y coordinates are 2 m apart), the plane position information of the specified position is converted to the nearest neighbor point that matches the rule in advance. In addition, it is possible to collate with the plane position information of each mesh data.

(Display means)
The display means presents the attribute information of the target mesh data to the user who has input the designated position through a monitor or the like. Examples of the attribute information include various information such as an address, land use status, land price, and population in addition to the information on the altitude value Z shown in FIG. Alternatively, a document file related to the location, a graphic for displaying a photo, and a map can be presented as attribute information. All the maintained attribute information can be presented by the display means, but can also be presented after extracting the attribute information to be shown by the attribute information extraction function.

  In FIG. 6, the altitude value Z and the inundation depth h are displayed on the monitor as attribute information. The inundation depth h is obtained by assigning the result of inundation simulation due to inundation / outside water inundation or tsunami in advance to each mesh data. In this way, by preparing attribute information for each mesh data, various information can be presented to the user.

(flow)
An example of a series of flows executed by the mesh data search system of the present invention, from input of a designated position to display of attribute information, will be described with reference to FIGS.

  The user inputs a position where the attribute information is desired by the position input means (S02). At this time, a background map corresponding to the predetermined area 2 is displayed on the monitor, and the target position is clicked with the mouse. When the designated position is input, the plane coordinates (Xt, Yt) of the designated position are acquired and stored.

  Next, the search means repeatedly collates the first condition (X coordinate condition) against all the divided ranges 3 in the predetermined area 2 with reference to Xt of the plane coordinates (Xt, Yt) of the designated position. Go (S03-S04). Tile data corresponding to the divided range 3 that conforms to the first condition is successively stored as “candidate tile data” (S05). When the collation judgment for all the divided ranges 3 is completed (S06), the process proceeds to the next step.

  The divided range 3 corresponding to the detected candidate tile data is collated under the second condition (Y coordinate condition) with reference to Yt of the plane coordinates of the designated position (S07 to S08). The collation is finished when the division range 3 that meets the second condition is found, tile data corresponding to the division range 3 is extracted as target tile data, and the process proceeds to the next step (S09).

  Based on the plane coordinates (Xt, Yt) of the designated position, the mesh data included in the target tile data is collated with the plane coordinates (Xn, Yn) of the mesh data. Specifically, the difference (sum of squares of coordinate difference) between the plane coordinates (Xt, Yt) of the designated position and the plane coordinates (Xn, Yn) of the mesh data is calculated (S10), and this is used as the target tile data. It performs with respect to all the mesh data contained (S11). Then, the one with the smallest coordinate difference is extracted as target mesh data (S12) and determined (S13).

  Finally, the attribute information of the target mesh data to be indicated by the attribute information extraction function is extracted (S14), and this attribute information is displayed on the monitor by the display means (S15).

  The mesh data search system of the present invention is not limited to extracting altitude and inundation depth, but can be used when extracting all information associated with position information. Note that the predetermined area is not necessarily divided into a lattice shape or the like, and any structure can be used as long as it is a set of mesh data including plane position information. Further, the mesh data search system of the present invention does not necessarily require a background map or GIS, and can use original or general-purpose software.

1 Mesh 2 Predetermined area 3 Dividing range h Inundation depth Z Elevation value

Claims (5)

In a system for searching for target mesh data from a plurality of mesh data obtained by dividing a predetermined area,
Tile data, a position input means for inputting a designated position, and a search means for searching for target mesh data,
The tile data represents a divided range obtained by dividing the predetermined area into a plurality of pieces, and is composed of two or more mesh data, and the divided range is set with a range condition for specifying the range,
The mesh data includes plane position information for specifying the mesh,
The search means includes the designated position from among the plurality of tile data based on the plane position information of the designated position input by the position input means and the range condition included in the tile data. Detect target tile data,
Further, the search means includes a target corresponding to the specified position from the mesh data constituting the target tile data based on the plane position information specifying the mesh data and the plane position information of the specified position. A mesh data search system characterized by searching mesh data. The range condition for specifying the division range of the tile data includes a first condition composed of a maximum value and a minimum value of longitude or X coordinates, and a second condition composed of a maximum value and a minimum value of latitude or Y coordinates. Consists of
The search means detects candidate tile data from the plurality of tile data based on the plane position information of the designated position and the first condition,
The mesh data search according to claim 1, wherein the search means detects target tile data from the candidate tile data based on the plane position information of the designated position and the second condition. system. The range condition for specifying the division range of the tile data includes a first condition composed of a maximum value and a minimum value of longitude or X coordinates, and a second condition composed of a maximum value and a minimum value of latitude or Y coordinates. Consists of
The search means detects candidate tile data from the plurality of tile data based on the plane position information of the designated position and the second condition,
The mesh data search according to claim 1, wherein the search means detects target tile data from the candidate tile data based on the plane position information of the designated position and the first condition. system. In addition to having an attribute information extraction function, the mesh data includes attribute information related to the mesh,
4. The mesh data search system according to claim 1, wherein the attribute information extraction function extracts attribute information of the target mesh data searched by the search unit. 5.   The mesh data search system according to any one of claims 1 to 4, wherein the attribute information is an altitude value or / and an inundation depth calculated within the predetermined area.

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