TWI786874B - Method of the digital grid model and system thereof - Google Patents

Abstract

A method of the digital grid model and system thereof are provided. The system received a plurality of grid data, to combine these data and eliminate duplicate areas, and then divided them into several area data of the same specification, and not only obtain the required area data but adjacent out-of-boundary data during value-added calculations such as slope calculation or openness calculation.

Description

Method and System of Numerical Grid Model

The present invention relates to a method and system of a numerical grid model, in particular to a method and system for numerical grid model establishment, when accessing divided numerical grid data, taking data outside the corresponding boundary and indexing the divided numerical grid Data to facilitate the method and system of value-added operations of numerical grid models.

According to the high-precision and high-resolution numerical terrain model measurement specification (technical report) announced by the Ministry of the Interior on November 30, 2002, the numerical grid model is constructed with grid point data, for example: Numerical terrain Digital Terrain Model (DTM for short), which represents the spatial distribution of actual terrain features in digital form. The numerical terrain model includes: the digital elevation model (Digital Elevation Model, referred to as DEM) and the numerical coverage model (Digital Surface Model, referred to as DSM) of the uppermost surface covering (including artificial buildings and vegetation).

The numerical elevation model is a numerical grid model of the natural landform fluctuations on the earth's surface when each grid point records the plane coordinates and elevation data of the point, and it does not contain surface vegetation and artificial structures. composed of points. In order to facilitate data management and subsequent application, here we define discrete points as grid points at equal intervals.

The numerical coverage model represents the numerical grid model of the uppermost surface of the earth's surface that cannot be penetrated by visible light. It differs from the numerical elevation model in that it represents the uppermost surface of buildings and perennial vegetation. This model is also based on the rule It is composed of pixel discrete points. Here we also define discrete points as grid points with equal intervals. The grid points of the above two models are constructed in pixel data format.

Generally speaking, the size of the distance between the grid points of the numerical grid model is called resolution. It determines how subtle the terrain model can represent changes in surface relief.

Considering that the use of numerical grid model data has its facility environment and technical thresholds, in order to give full play to the application of numerical grid models in land planning and geographic information systems, and expect to be able to conduct online query demonstrations and provide various Interconnection and use of the agency platform to expand the application field of numerical grid data, strengthen the surveying and mapping information circulation mechanism, and provide value-added application services such as: weighted analysis, search radius analysis, etc.

Among them, the weighted analysis refers to the algorithm provided on the ArcGIS website, which is used to calculate the rate of change between each pixel and the direction of adjacent pixels, and calculates the elevation Z value of the central pixel and the surrounding 3x3 pixels. The smaller the slope value, the flatter the terrain; otherwise, the steeper it is. The calculation unit can use degree (degree) and percentage (percentage). The slope algorithm depends on the amount of change in the horizontal and vertical directions.

Terrain openness: Yokoyama et al. (2002) proposed the concept of terrain openness, which can reflect the degree of concave and convex terrain in the analysis window. The main analysis method is to set the red point (A) as the center of the circle, and equidistant ( L) Average the zenith angles (Ø𝐿D) and nadir angles (ΨLD) of all eight azimuths, and finally subtract and average again to obtain the terrain openness ( I ).

However, when performing value-added calculation services such as weighted analysis or search radius analysis based on the current numerical grid model, the calculation of the slope of a point by the four-neighborhood method requires elevation data adjacent to the point, east-west, north-south, and eight-neighborhood Calculating the slope of a certain point requires the elevation data of eight azimuths adjacent to the point. When calculating the slope at the boundary of each block of data, it will appear because the range of data acquisition does not include the data outside the boundary, and Distort the calculation result of the slope of the boundary. For example, when calculating the slope of a 5000*5000 pixel elevation data, due to the lack of adjacent data, the slope at the position of the outermost week cannot be obtained. In the past, it was impossible to solve the problem In the case of generating slope data of 5000*5000 pixels, usually in the process of calculating this data, it is still necessary to introduce other data adjacent to the data to calculate the boundary, which hinders the utilization of computing resources and storage space.

Therefore, the present invention provides a method for calculating a numerical grid model, which establishes a numerical grid and divides it into multiple pieces of data. When performing value-added calculation services such as weighted analysis or search radius analysis, each piece of data after division is used and taken together. Use the out-of-boundary data of the data, the out-of-boundary data can be one or a few grid pixels wide around the data, compared with directly accessing other data adjacent to the data, this method takes more data However, it can ensure the correctness of the boundary data after the value-added calculation of each data after division, and optimize the use of computing resources and storage space.

Another problem is that when performing value-added calculation services such as weighted analysis or search radius analysis, since the database of numerical grid data is very large, if all data are directly used for value-added calculations, the calculation efficiency will be very low. Since the numerical grid data is usually created by many numerical grid data, the previous practice is to store the data corresponding to each numerical grid data one by one, and use the required data or multiple data when calculating, but the value The size and shape of the grid data are often inconsistent, which will lead to difficulties in judging the range when obtaining the required data.

Therefore, the present invention provides a method for normalizing the numerical grid model. The numerical grid model is divided into rectangular data of a fixed size, and each data is indexed. When adding value calculations, only the calculation range can be quickly obtained. Need data, improve calculation efficiency.

The main purpose of the present invention is to provide a method and system for calculating the numerical grid model, by capturing the data of the pixels to be calculated and the surrounding pixels outside the boundary when calculating the slope, to assist in the calculation of the slope, it can be used when using Under the condition of minimum computing resources, the data at the boundary is guaranteed to be correct.

Another object of the present invention is to provide a method and system for calculating a numerical grid model, by capturing the data of the pixels to be calculated and the surrounding pixels outside the boundary when calculating the terrain openness, to assist in the calculation of the terrain openness When , the data at the boundary can be guaranteed to be correct under the condition of using the least computing resources.

Another object of the present invention is to provide a method and system for accessing a numerical grid model. By indexing the divided numerical grid model, it is convenient for value-added calculations, such as: slope, terrain openness, etc., can be Quickly obtain corresponding information according to the index.

In order to achieve the above-mentioned purpose and effect, the present invention provides a method for calculating a numerical grid model, the steps of which include: providing a plurality of numerical grid data, each numerical grid data includes a spatial coordinate information, which represents the numerical network The position of the grid data, each grid point of each numerical grid data has a height value, which represents the topography of the grid point; according to the spatial coordinate information, the numerical grid data is arranged at a 2D coordinate to generate an initial Grid data, the arrangement here refers to putting each numerical grid data into the corresponding position according to the spatial coordinate information; eliminating at least one repeated area of the initial grid data to generate a reconstructed grid data, here at least one repeated Area refers to the overlapping area when the numerical grid data is arranged in the previous step; the reconstructed grid data is divided into a plurality of area grid data according to a resolution value, and a plurality of neighbors corresponding to each area grid data are obtained Grid point data, because it is convenient to use the reconstructed grid data that needs to be divided into a huge amount of data; and according to a weighted analysis method, the height value and one of the regional grid data and the corresponding adjacent grid point data Calculate one of the terrain slope values of the regional grid data. Here, the terrain slope data will be calculated based on the terrain height data.

The present invention provides an embodiment, wherein the resolution value of each regional grid data is K*K, and K is a natural number.

The present invention provides an embodiment, wherein the resolution value of each regional grid data is K+1*K+1 after combining a plurality of adjacent grid point data corresponding to each regional grid data, and K is a natural number .

The present invention provides an embodiment, wherein the resolution value of the terrain slope value is K*K, and K is a natural number.

The present invention provides an embodiment, wherein the spatial coordinate information is the shooting spatial coordinate of each numerical grid data.

The present invention provides an embodiment, wherein, in the step of eliminating at least one overlapping region of the initial grid data to generate a reconstructed grid data, at least a repeating region.

The present invention provides an embodiment, wherein, according to a resolution value, the reconstructed grid data is divided into a plurality of regional grid data and a plurality of adjacent grid point data adjacent to each corresponding regional grid data are obtained In the step, a plurality of regional grid data are sequentially divided according to the spatial coordinate information.

The present invention provides an embodiment, wherein the weighted analysis methods are, for example, the four-neighborhood method, the weighted eight-neighborhood method, and the equal-weight eight-neighborhood method.

In order to achieve the above-mentioned purpose and effect, the present invention provides another method for calculating a numerical grid model, the steps of which include: providing a plurality of numerical grid data, each numerical grid data including a spatial coordinate information, which represents a numerical value The position of the grid data, each grid point of each numerical grid data has a height value, which represents the topography of the grid point; according to the spatial coordinate information, the numerical grid data is arranged in a 2D coordinate to generate a Arranging the initial grid data here refers to putting each numerical grid data into the corresponding position according to the spatial coordinate information; eliminating at least one repeated area of the initial grid data to generate a reconstructed grid data, here at least one Repeated area refers to the area that overlaps each other when the numerical grid data is arranged in the previous step; the reconstructed grid data is divided into multiple regional grid data according to a resolution value, and the corresponding multiple adjacent adjacent grid data of each area is obtained. Neighboring grid point data, here, for the convenience of use, the reconstructed grid data with a large amount of data needs to be divided; and according to a search radius analysis method, the height value and one of the regional grid data and the corresponding adjacent grid Calculate the topographic openness value of one of the regional grid data from the point data. This method can calculate the topographic openness data based on the terrain height data.

The present invention further provides an embodiment, wherein the search radius analysis method is, for example, a cover window radius search method.

In order to achieve the above-mentioned purpose and effect, the present invention also provides a method for accessing a numerical grid model, the steps of which include: providing a plurality of numerical grid data, each numerical grid data includes a spatial coordinate information, which represents The position of the numerical grid data; arrange the numerical grid data at a 2D coordinate according to the spatial coordinate information to generate an initial grid data, and arrange here refers to placing each numerical grid data into the corresponding Position; eliminate at least one overlapping area of the initial grid data to generate a reconstructed grid data, where at least one overlapping area refers to the overlapping area when the numerical grid data is arranged in the previous step; the reconstruction is divided according to a resolution value The grid data is a plurality of regional grid data. Here, for the convenience of use, it is necessary to divide the reconstruction grid data with a huge amount of data; and to index each regional grid data. Here, for the convenience of use, it is necessary to index a large amount of data in the regional network grid data.

The present invention also provides an embodiment, wherein, after the step of indexing each regional grid data, further comprising: storing the regional grid data in a map database;

The present invention also provides an embodiment, wherein, after the step of indexing each area grid data, it further includes: calculating at least one serial number required according to a value-added service event; extracting one of the area grid data according to the serial number One for one to retrieve data; and calculate a calculation result according to the retrieved data.

The present invention also provides an embodiment, wherein the spatial coordinate information is the shooting spatial coordinate of each numerical grid data.

The present invention also provides an embodiment, wherein, in the step of eliminating at least one overlapping region of the initial grid data to generate a reconstructed grid data, the elimination is performed according to the shooting time of each numerical grid data or a display layer at least one repeat region.

The present invention also provides an embodiment, wherein, in the step of dividing the reconstructed grid data into a plurality of regional grid data according to a resolution value, the plurality of regional grid data are sequentially divided according to the spatial coordinate information.

The present invention also provides an embodiment, wherein the resolution value of each regional grid data is K*K, and K is a natural number.

The present invention also provides an embodiment, the value-added service event such as: weight analysis or search radius analysis.

In order to achieve the above-mentioned purpose and effect, the present invention also provides a numerical grid model system, which includes: a host computer, which is equipped with a numerical grid model building module to convert a plurality of numerical grid data according to a spatial coordinate information Arranging to generate an initial grid data, eliminating at least one overlapping region of the initial grid data to generate a reconstructed grid data, dividing the reconstructed grid data into a plurality of regional grid data and obtaining each corresponding region A plurality of adjacent grid point data of the grid data is calculated based on at least part of the regional grid data and a plurality of adjacent grid point data corresponding to at least part of the regional grid data.

The present invention further provides an embodiment, wherein the host computer further includes: a grid processing unit, which arranges a plurality of numerical grid data according to the spatial coordinate information to generate initial grid data, and eliminates at least overlapping areas of the initial grid data , to generate reconstructed grid data; an operation processing unit, which divides the reconstructed grid data into a plurality of regional grid data and obtains a plurality of adjacent grid point data corresponding to each regional grid data, and indexes each A regional grid data for calculating regional grid data; a map database for storing indexed regional grid data; a calculation module for calculating based on a value-added service event.

In order to enable your review committee members to have a further understanding and understanding of the characteristics of the present invention and the achieved effects, the following examples and accompanying descriptions are hereby provided:

Hereinafter, the present invention will be described in detail by illustrating various embodiments of the present invention by means of the accompanying drawings. Inventive concepts may, however, be embodied in many different forms and should not be construed as limited to the illustrative embodiments set forth herein.

In view of the existing process of calculating the numerical grid model, for example, in the process of weighted analysis, the calculation of the boundary value of the grid data is distorted, and accordingly, the present invention proposes a method for calculating the numerical grid model , in order to ensure the correctness of the calculation of the boundary value, the data of the adjacent boundary is obtained at the same time when the grid data is divided.

First of all, please refer to FIG. 1 , which is a flow chart of a method of an embodiment of the present invention. As shown in the figure, in the present invention, its steps include:

Step S10: providing a plurality of numerical grid data, each numerical grid data includes a spatial coordinate information, and each grid point of each numerical grid data has a height value;

Step S20: Arranging the numerical grid data on a 2D coordinate according to the spatial coordinate information to generate an initial grid data;

Step S30: Eliminate at least one overlapping region of the initial grid data to generate a reconstructed grid data;

Step S40: Divide the reconstructed grid data into a plurality of regional grid data according to a resolution value and obtain a plurality of adjacent grid point data corresponding to each regional grid data; and

Step S50: According to a weighted analysis method, the height value and one of the regional grid data and the corresponding adjacent grid point data are used to calculate a topographic slope value of one of the regional grid data.

Then explain the system required for the method for the calculation numerical grid model of the present embodiment, please refer to the 2nd figure, it is a block diagram of an embodiment of the present invention, as shown in the 2nd figure; The calculated value of the present invention The grid model system includes a host computer 10 provided with a numerical grid model building module 20, and the numerical grid model building module 20 includes a grid processing unit 30 and an operation processing unit 40; in this embodiment, the host computer 10 It can be a computer host or a server host, and the numerical grid model building module 20 is an application program, but not limited thereto.

As shown in step S10, the grid processing unit 30 of the host computer is provided with the numerical grid data 32. The numerical grid data 32 usually comes from an airborne LiDAR (Light Detection And Ranging, LiDAR), and its accuracy can even reach a decimeter. Since the image grid produced by airborne LiDAR is a known technology, its imaging principle will not be described in detail here. It is only necessary to understand that the numerical grid data 32 generated by it is usually presented as two-dimensional elevation data; each numerical grid data 32 is also presented. Including spatial coordinate information 322, each grid point 324 record of each numerical grid data 32 has a height value 326, for example: there should be 9 grid points 324 in the data of 3*3 size, and the corresponding record has The height value of 9 pens is 326; the spatial coordinate information 322 refers to the spatial coordinates of the shooting location, which is represented by a positive value for the east longitude and a negative value for the west longitude. Positive value, south latitude is negative value, its range is -90 degrees to +90 degrees, the grid point 324 is determined by the accuracy of the airborne lidar, which represents the degree of resolution of the ground, and the height value 326 can be the altitude ( altitude), that is, the height relative to sea level.

Next, as shown in step S20 , the grid processing unit 30 arranges the numerical grid data 32 at the 2D coordinates 34 according to the spatial coordinate information 322 of each numerical grid data 32 to generate the initial grid data 342 .

Then, as shown in step S30, and referring to FIG. 3, there is a repeated area 344 in the initial grid data 342, because each numerical grid data 32 will partially overlap other numerical grid data 32, so the grid processing unit 30 will eliminate repeated regions 344 according to a shooting time 328 or a display layer 36 of each numerical grid data 32 to generate a reconstructed grid data 38; When the shooting time is reached, the display layer 36 refers to the order in which each numerical grid data 32 is arranged at the 2D coordinates 34. For example, if the shooting time 328 is used to eliminate the repeated area 344, then the shooting time in the repeated area 344 can be retained 328 newer, remove the older ones of shooting time 328; if the repeated area 344 is eliminated with the display layer 36 as a benchmark, then the numerical grid data 32 put in later in the repeated area 344 can be kept, and the earlier put in is removed Numerical grid data 32, but not limited thereto.

Then, as shown in step S40, and referring to FIG. 4, the arithmetic processing unit 40 divides the reconstructed grid data 38 into regional grid data 42, which is divided according to the resolution value 422, for example: the resolution value 422 is K* K, then the division and reconstruction grid data 38 is a rectangular area grid data 42 with a side length of K grid points (K is a user-defined natural number, such as: 5000, then the data is 5000*5000 size), but not Limited to this; the calculation processing unit 40 also divides the regional grid data 42 sequentially according to the spatial coordinate information 322, for example, from the lower left corner of the spatial coordinate, that is, the lower left corner of the 2D coordinate 34 to the right online; the resolution value 422 can be set by the host computer 10, but is not limited thereto; referring to Fig. 5, the operation processing unit 40 obtains the corresponding adjacent grid point data 424 adjacent to each area grid data 42, for example, adjacent can refer to the area The data in the outer circle of the grid data 42, but not limited thereto.

Finally, as shown in step S50, and referring to FIG. 5, the calculation processing unit 40 calculates the area according to the weighted analysis method 44 using the height value 326 and one of the area grid data 42 and the corresponding adjacent grid point data 424. The terrain slope value 442 of one of the grid data 42, the weighted analysis method 44 is for example: the weighted eight-neighborhood method, if it has a grid point A0 to be calculated, then it uses eight grid points around the pixel A0 to be calculated The height value 326 of B1~B8 is used to calculate the terrain slope value 442 of the pixel A0 to be calculated. Therefore, to calculate the grid point A0 to be calculated at the edge of each area grid data 42, it is necessary to use the adjacent adjacent The grid points B1, B4, B6, B7, B8 of the grid point data 424; the weighted analysis method 44 can also be a four-neighborhood method, then it uses four grid points B2, B4 around the grid point A0 to be calculated , B5, B7 to calculate the terrain slope value 442 of the grid point A0 to be calculated, therefore, to calculate the grid point A0 to be calculated at the edge of each area grid data 42, it is necessary to use adjacent adjacent grids The grid points B4 and B7 of the point data 424; the weighted analysis method 44 can also be an equal-weight eight-neighborhood method, which uses eight grid points B1~B8 around the grid point A0 to calculate the grid to be calculated The terrain slope value 442 of point A0, therefore, to calculate the grid point A0 to be calculated at the edge of each regional grid data 42, it is necessary to use the grid points B1 and B4 of the adjacent adjacent grid point data 424 , B6, B7, B8, but not limited to. The four-neighborhood method, the equal-weight eight-neighborhood method or the weighted eight-neighborhood method are known techniques.

，式(一)。 Four-neighborhood method:

, Formula (1).

Formula (1) where S is the terrain slope value 442 of the grid point A0 to be calculated, B2, B4, B5, and B7 correspond to the height value 326 of the eight pixels B1~B8 around the pixel A0 to be calculated, and d is the grid point The actual length corresponding to the side length of 324.

，式(二)。 Equal-weight eight-neighborhood method:

, formula (2).

Formula (2) S is the terrain slope value 442 of the grid point A0 to be calculated, B1~B8 corresponds to the height value 326 of the eight grid points B1~B8 around the grid point A0 to be calculated, d is the height value of the grid point 324 The actual length corresponding to the side length.

，式(三)。 Weighted eight-neighborhood method:

, formula (3).

Formula (3) where S is the terrain slope value 442 of the grid point A0 to be calculated, B1~B8 correspond to the height value 326 of the eight grid points B1~B8 around the grid point A0 to be calculated, and d is the grid point The actual length corresponding to the side length of 324.

Since in this example, the numerical grid data is established by creating a numerical grid model and then divided, the divided data and the corresponding adjacent data are used when calculating the slope value, and all grid points, especially the outermost circumference of each data, can be accurately calculated. Compared with the adjacent data, the border grid points do not need to use other data with a larger amount of data, so as to achieve the purpose of improving calculation efficiency and saving storage space. Therefore, the method for calculating the numerical grid model of the present invention has the advantages of saving computing resources and storage space, and is very helpful for establishing a numerical grid model and providing value-added computing services.

In this example, the numerical grid model building module 20 starts the processing procedure from the numerical grid data 32 captured by the airborne lidar, but the feature of the present invention is when the value-added calculation such as the weighted eight-neighborhood method is used to calculate the terrain slope value 442 and when needing to use the divided regional grid data 42, for each regional grid data 42, its adjacent adjacent grid point data 424 can be obtained, so that it is not necessary to use other regional grid data 42 The terrain slope value 442 at the boundary of each regional grid data 42 can be calculated, so in another embodiment, it can also be used to calculate other added values such as: terrain openness.

The flow of the method for calculating the numerical grid model of another embodiment of the present invention will be described below. Please refer to FIG. 6. The steps of this embodiment include the following:

Step S110: Provide numerical grid data, each numerical grid data includes spatial coordinate information, and each grid point of each numerical grid data has a height value;

Step S120: Arranging the numerical grid data on 2D coordinates according to the spatial coordinate information to generate initial grid data;

Step S130: Eliminate overlapping regions of the initial grid data to generate reconstructed grid data;

Step S140: Divide the reconstructed grid data into regional grid data according to the resolution value and obtain adjacent grid point data adjacent to each corresponding regional grid data; and

Step S150: According to a search radius analysis method, the height value and one of the regional grid data and the corresponding adjacent grid point data are used to calculate a terrain openness value of one of the regional grid data.

Then explain the system required for the method for the calculation numerical grid model of the present embodiment, please refer to the 2nd figure, it is a block diagram of an embodiment of the present invention, as shown in the 2nd figure; The calculated value of the present invention The grid model system includes a host computer 10 provided with a numerical grid model building module 20, and the numerical grid model building module 20 includes a grid processing unit 30 and an operation processing unit 40; in this embodiment, the host computer 10 can be a computer The host or server host, the numerical grid model building module 20 is an application program, but not limited thereto.

As shown in step S110, the grid processing unit 30 of the host computer is provided with the numerical grid data 32. The numerical grid data 32 usually comes from an airborne LiDAR (Light Detection And Ranging, LiDAR), and its precision can even reach a decimeter. Since the use of airborne lidar to draw measurement grids is a known technique, its imaging principle will not be described in detail here. It is only necessary to understand that the numerical grid data 32 generated by it is usually presented as two-dimensional elevation data; each numerical grid data 32 It also includes spatial coordinate information 322, and each grid point 324 of each numerical grid data 32 records a height value 326, for example: there should be 9 grid points 324 in the data of 3*3 size, corresponding A total of 9 records have a height value of 326.

Among them, the spatial coordinate information 322 spatial coordinate information 322 records the spatial coordinates of the shooting location, and its expression method is that the longitude is represented by the positive value of the east longitude and the negative value of the west longitude. The range is -180 degrees to +180 degrees, and the latitude is represented by the north latitude. Positive value, south latitude is negative value, its range is -90 degrees to +90 degrees, the grid point 324 is determined by the accuracy of the airborne lidar, which represents the degree of resolution of the ground, and the height value 326 can be the altitude ( altitude), that is, the height relative to sea level.

Next, as shown in step S120 , the grid processing unit 30 arranges the numerical grid data 32 at the 2D coordinates 34 according to the spatial coordinate information 322 of each numerical grid data 32 to generate the initial grid data 142 .

Then, as shown in step S130, and referring to FIG. 3 , there is a repeated area 344 in the initial grid data 142, because each numerical grid data 32 will partially overlap other numerical grid data 32, so the grid processing unit 30 will eliminate the repeated area 344 according to the shooting time 328 or display layer 36 of each numerical grid data 32 to generate the reconstructed grid data 38; For the shooting time, the display layer 36 refers to the order in which each numerical grid data 32 is arranged at the 2D coordinates 34. For example, if the shooting time 328 is used to eliminate the repeated area 344, then the shooting time 328 in the repeated area 344 can be kept. For the new one, remove the older one of the shooting time 328; if the repeated area 344 is eliminated based on the display layer 36, then the numerical grid data 32 put in later in the repeated area 344 can be kept, and the numerical grid data 32 put in earlier can be removed. grid data 32, but not limited thereto.

Then, as shown in step S140, and referring to FIG. 4, the arithmetic processing unit 40 divides the reconstructed grid data 38 into regional grid data 42, which is divided according to the resolution value 422, for example: the resolution value 422 is K *K, then divide the reconstructed grid data 38 into a rectangular area grid data 42 with a side length of K grid points (K is a user-defined natural number, such as: 5000, the data is 5000*5000 in size), but Not limited to this; the calculation processing unit 40 also divides the regional grid data 42 sequentially according to the spatial coordinate information 322, for example, from the lower left corner of the 2D coordinate 34 to the right online; resolution The value 184 can be set by the host computer 10, but is not limited thereto; referring to FIG. 5, the operation processing unit 40 obtains the corresponding adjacent grid point data 424 adjacent to each area grid data 42.

Finally, as shown in step S150, the calculation processing unit 40 calculates the height value 326 and one of the regional grid data 42 and the corresponding adjacent grid point data 424 according to the search radius analysis method 46 to calculate the value of the regional grid data 42. One of them is the topography openness value 462, the search radius analysis method 46 is the cover window radius search method such as: the average method or the eight-direction method, the openness is mainly to explore two characteristics that exist simultaneously on the terrain: convexity (convexity) and concave (concavity) How to present the amount of change through analysis. The openness combines the concept of sight and calculates the value-added results formed by taking the average of the zenith angle or nadir angle of the eight directions within the range formed by the radius length. It is necessary to set a center point 464 and a cover window radius 466 during the calculation of the openness. According to the height value 326 in the center point 464 and the cover window radius 466, one of the regional grid data 42 and the corresponding adjacent grid point data are taken. 424 to calculate the terrain openness value 462, for example, referring to the 7th figure, there are 4 regional grid data 42 in the cover window radius 466, after the central point 464 and the cover window radius 466 are input by the host computer 10, the calculation processing unit The 40 obtains these regional grid data 42 and the corresponding adjacent grid point data 424 accordingly.

，N個方位，式(四)。 Negative Opennsess=

，N個方位，式(五)。 Average method (N directions): Positive Openness=

, N directions, formula (4). Negative Opennessess=

, N orientations, formula (5).

Here Openness is the terrain openness value 462, ∆H is the difference between the center point 464 and the height value 326 of each point of the cover window radius 466, ∆D is the cover window radius 466, N is the data number of each point on the cover window radius 466.

，N=8，式(六)。 Negative Opennsess=

，N=8，式(七)。 Octave method: Positive Openness=

, N=8, formula (6). Negative Opennessess=

, N=8, formula (7).

Here, the eight orientations refer to north, northeast, east, southeast, south, southwest, west, and northwest. Openness is the terrain openness value 462, ∆H is the center point 464 and the height value of each point on the cover window radius 466 of the eight orientations is 326 The difference, ∆D is the radius of the cover window 466.

Since in this example, the numerical grid data is established as a numerical grid model and then divided, the divided data and the corresponding adjacent data are used when calculating the terrain openness value, so that all grid points, especially each data, can be accurately calculated The boundary grid points on the outermost periphery do not need to use other data with a large amount of data compared with the adjacent data, so as to achieve the purpose of improving calculation efficiency and saving storage space. Therefore, the method for calculating the numerical grid model of the present invention has the advantages of saving computing resources and storage space, and is very helpful for establishing a numerical grid model and providing value-added computing services.

The present invention also provides a method for accessing the numerical grid model. In view of the fact that the access data will be divided during the process of generating the numerical grid model, the present invention further provides a method for indexing the access data, so that the value-added calculation can be performed Quickly retrieve the required information.

The flow of the method for accessing the numerical grid model of another embodiment of the present invention will be described below. Please refer to FIG. 8. The steps of this embodiment include the following:

Step S210: providing numerical grid data, each numerical grid data includes spatial coordinate information;

Step S220: Arranging the numerical grid data on 2D coordinates according to the spatial coordinate information to generate initial grid data;

Step S230: Eliminate overlapping regions of the initial grid data to generate reconstructed grid data;

Step S240: dividing the reconstructed grid data into regional grid data according to the resolution value; and

Step S250: Index each regional grid data.

Then explain the system required for the method for the calculation numerical grid model of the present embodiment, please refer to the 2nd figure, it is a block diagram of an embodiment of the present invention, as shown in the 2nd figure; The calculated value of the present invention The grid model system includes a host computer 10 provided with a numerical grid model building module 20, and the numerical grid model building module 20 includes a grid processing unit 30 and an operation processing unit 40; in this embodiment, the host computer 10 can be a computer The host or server host, the numerical grid model building module 20 is an application program, but not limited thereto.

As shown in step S210, the grid processing unit 30 of the host computer is provided with the numerical grid data 32. The numerical grid data 32 usually comes from an airborne LiDAR (Light Detection And Ranging, LiDAR), and its accuracy can even reach a decimeter. Since the image grid produced by airborne LiDAR is a known technology, its imaging principle will not be described in detail here. It is only necessary to understand that the numerical grid data 32 generated by it is usually presented as two-dimensional elevation data; each numerical grid data 32 is also presented. Contains the shooting location information, that is, the spatial coordinate information 322; the spatial coordinate information 322 refers to the shooting spatial coordinates, and its expression method is that the longitude is represented by a positive value for the east longitude, and a negative value for the west longitude, and its range is -180 degrees to +180 degrees, and the latitude is represented by The north latitude is a positive value, and the south latitude is a negative value, and its range is -90 degrees to +90 degrees.

Next, as shown in step S220 , the grid processing unit 30 arranges the numerical grid data 32 at the 2D coordinates 34 according to the spatial coordinate information 322 of each numerical grid data 32 to generate the initial grid data 342 .

Then, as shown in step S230, and referring to FIG. 3 , there is a repeated area 344 in the initial grid data 342, because each numerical grid data 32 will partially overlap other numerical grid data 32, so the grid processing unit 30 will eliminate the repeated area 344 according to the shooting time 328 or display layer 36 of each numerical grid data 32 to generate the reconstructed grid data 38; For the shooting time, the display layer 36 refers to the order in which each numerical grid data 32 is arranged at the 2D coordinates 34. For example, if the shooting time 328 is used to eliminate the repeated area 344, then the shooting time 328 in the repeated area 344 can be kept. For the new one, remove the older one of the shooting time 328; if the repeated area 344 is eliminated based on the display layer 36, then the numerical grid data 32 put in later in the repeated area 344 can be kept, and the numerical grid data 32 put in earlier can be removed. grid data 32, but not limited thereto.

Then, as shown in step S240, and referring to FIG. 4, the arithmetic processing unit 40 divides the reconstructed grid data 38 into regional grid data 42, which is divided according to the resolution value 422, for example: the resolution value 422 is K *K, then divide the reconstructed grid data 38 into a rectangular area grid data 42 with a side length of K grid points (K is a user-defined natural number, such as: 5000, the data is 5000*5000 in size), but Not limited to this; the calculation processing unit 40 also divides the regional grid data 42 sequentially according to the spatial coordinate information 322, for example, from the lower left corner of the 2D coordinate 34 to the right online; resolution The value 422 can be set by the host 10, but is not limited thereto.

Finally, as shown in step S250, the calculation processing unit 40 indexes each regional grid data 42 according to the spatial coordinate information 322. For example, one of the regional grid data 42 has a longitude of 120.93310546875~120.958129882812 and a latitude of 24.8233032226562~24.8483276367187. The number is 95818483 to facilitate the search, but not limited to this.

Referring to Fig. 9, step S250 further includes:

Step S252: Store the regional grid data in a map database.

Then, as shown in step S252, and referring to FIG. 2, the numerical grid model building module 20 also includes a map database 50. The map database 50 can be a hard disk or cloud space, but is not limited thereto. The calculation processing unit 40 The area grid data 42 indexed in step S250 can be stored in the map database 50 .

Please refer to Fig. 10, step S250 further comprises:

Step S260: Calculate at least one serial number required according to a value-added service event.

Step S270: one of the retrieved regional grid data according to the serial number is a retrieved data; and

Step S280: Calculate a calculation result according to the captured data.

As shown in step S260, and referring to FIG. 2, the numerical grid model building module 20 also includes a calculation module 60, and the calculation module 60 can calculate the required number according to the value-added service event 62. The value-added service event 62 is for example : weighted analysis or search radius analysis, as described in step S50 or step S150, weighted analysis or search radius analysis can obtain the regional grid data 42 according to its calculation process, and the calculation module 60 can obtain the corresponding grid data 42 according to each area No. 64.

Then, as shown in step S270, the calculation module 60 retrieves one of the regional grid data 42 according to the number 64 as the retrieved data 66. If the regional grid data 42 has been stored in the map database 50 in step S252, then The calculation module 60 retrieves one of the regional grid data 42 from the map database 50 according to the number 64 as the retrieved data 66 .

Finally, as shown in step S280, the calculation module 60 uses the calculation processing unit 40 to perform value-added service events 62 such as: weight analysis or search radius analysis according to the captured data 66, and obtain a calculation result 68, such as: terrain slope A value of 442 or a terrain openness value of 462, but not limited to.

The regional grid data divided and indexed in this embodiment, so that when the calculation module performs value-added services, it can directly obtain the number according to the spatial coordinate range, and then obtain the data required for calculation according to the number, without the need to first retrieve All the data, and then find the required data from all the data, and then retrieve the required data, especially the numerical grid model has a huge amount of data, the time difference between only obtaining the required data and obtaining all the data is more obvious , the present invention can make the value-added calculation process more efficient and save memory, which is not only beneficial to reduce the user's hardware cost, but also improves the applicability and competitiveness of the present invention in the market.

To sum up, the present invention is a numerical grid model method and its system. By dividing the numerical grid data to calculate the boundary value, additional adjacent data are obtained to achieve the effect of correctly calculating the boundary value and saving storage space. , and then use the numerical grid data divided by the index to achieve the effect of fast utilization according to the number and saving storage space.

Therefore, the present invention is novel, progressive and can be used in industry. It should meet the patent application requirements of my country's patent law. I file an invention patent application in accordance with the law. I pray that the bureau will grant the patent as soon as possible. I sincerely pray.

However, the above-mentioned ones are only preferred embodiments of the present invention, and are not used to limit the scope of the present invention. For example, all equal changes and modifications are made according to the shape, structure, characteristics and spirit described in the scope of the patent application of the present invention. , should be included in the patent application scope of the present invention.

10: Host 20: Numerical grid model building module 30: grid processing unit 32: Numerical grid data 322: Spatial coordinate information 324: grid point 326: height value 328: Shooting time 34: 2D coordinates 342:Initial grid data 344: Repeat area 36:Display layers 38:Reconstruct grid data 40: Operation processing unit 42: Regional grid data 422: Resolution value 424: Adjacent grid point data 44: Weighted Analysis Method 442: terrain slope value 46: Search Radius Analysis 462: terrain openness value 464: center point 466: Radius of cover window 50:Map database 60: Calculation module 62: Value-added service event 64: number 66: Retrieve data 68: Calculation result A0: Grid points to be calculated B1~B8: Eight grid points around A0 S10 to S280: Steps

Figure 1: It is a flow chart of the method of one embodiment of the present invention; Fig. 2: it is a block diagram of an embodiment of the present invention; Figure 3: It is a schematic diagram of the repeating region of an embodiment of the present invention; Figure 4: It is a schematic diagram of grid points to be calculated and adjacent grid points according to an embodiment of the present invention; Figure 5: It is a schematic diagram of regional grid data and adjacent grid point data according to an embodiment of the present invention; Fig. 6: It is a method flow chart of another embodiment of the present invention; Figure 7: It is a schematic diagram of the center point and the radius of the cover window in another embodiment of the present invention; Fig. 8: It is the flow chart of the method of another embodiment of the present invention; Fig. 9: it is a method flow chart of another embodiment of the present invention; and Fig. 10: It is a method flow chart of another embodiment of the present invention.

S10 to S50: Steps

Claims (28)

A method for calculating a numerical grid model, which includes: receiving a plurality of numerical grid data by a host computer, each of the numerical grid data includes a spatial coordinate information, and each network of each of the plurality of grid format data The grid point has a height value; the host arranges the numerical grid data at a 2D coordinate according to the spatial coordinate information to generate an initial grid data; the host eliminates at least one overlapping area of the initial grid data , to generate a reconstructed grid data; the host computer divides the reconstructed grid data into a plurality of regional grid data according to a resolution value and obtains a plurality of corresponding adjacent ones of the regional grid data adjacent grid point data; and the host computer calculates the height value of the regional grid data according to a weighted analysis method and takes one of the regional grid data and the corresponding adjacent pixel data One of the terrain slope values. The method for calculating a numerical grid model as described in Claim 1, wherein the resolution value of each of the regional grid data is K*K, and K is a natural number. The method for calculating a numerical grid model as described in claim 2, wherein the resolution of each of the regional grid data combined with a plurality of adjacent grid point data corresponding to each of the regional grid data The value is K+1*K+1, K is a natural number. The method for calculating a numerical grid model as described in Claim 1, wherein the resolution value of the terrain slope value is K*K, and K is a natural number. The method for calculating a numerical grid model as described in Claim 1, wherein the spatial coordinate information is the shooting range of each of the numerical grid data. The method for calculating a numerical grid model as described in claim 1, wherein in the step of eliminating at least one overlapping region of the initial grid data to generate a reconstructed grid data, according to each of the numerical grids A shooting time of data or a display layer eliminates at least one repeated region. The method for calculating a numerical grid model as described in claim 1, wherein the reconstructed grid data is divided into a plurality of regional grid data according to a resolution value and each of the corresponding regional grid data is obtained In the step of adjoining a plurality of adjacent grid point data, the plurality of regional grid data are sequentially divided according to the spatial coordinate information. The method for calculating a numerical grid model as described in Claim 1, wherein the weighted analysis method is, for example, a four-neighborhood method, a weighted eight-neighborhood method, and an equal-weight eight-neighborhood method. A method for calculating a numerical grid model, which includes: receiving a plurality of numerical grid data by a host computer, each of the numerical grid data includes a spatial coordinate information, each of the numerical grid data The grid point has a height value; the host arranges the numerical grid data at a 2D coordinate according to the spatial coordinate information to generate an initial grid data; the host eliminates at least one repetition of the initial grid data region to generate a reconstructed grid data; the host computer divides the reconstructed grid data into a plurality of regional grid data according to a resolution value and obtains a plurality of corresponding adjacent ones of the regional grid data Adjacent grid point data; and the host calculates the areas based on a search radius analysis method, the height value and one of the area grid data and the corresponding adjacent grid point data One of the grid data one of the terrain openness value. The method for calculating a numerical grid model as described in Claim 9, wherein the resolution value of each of the regional grid data is K*K, and K is a natural number. The method for calculating a numerical grid model as described in claim 10, wherein each of the regional grid data is combined with a plurality of adjacent grid point data corresponding to each of the regional grid data. The value is K+1*K+1, K is a natural number. The method for calculating a numerical grid model as described in Claim 10, wherein the resolution value of the terrain slope value is K*K, and K is a natural number. The method for calculating a numerical grid model as described in Claim 10, wherein the spatial coordinate information is the shooting spatial coordinate of each of the numerical grid data. The method for calculating a numerical grid model as described in claim 10, wherein in the step of eliminating at least one overlapping region of the initial grid data to generate a reconstructed grid data, according to each of the numerical grids A shooting time of data or a display layer eliminates at least one repeated region. The method for calculating a numerical grid model as described in claim 10, wherein the reconstructed grid data is divided into a plurality of regional grid data according to a resolution value and corresponding to each of these regional grid data is obtained In the step of adjoining a plurality of adjacent grid point data, the plurality of regional grid data are sequentially divided according to the spatial coordinate information. The method for calculating a numerical grid model as described in Claim 10, wherein the search radius analysis method is a cover window radius search method. A method for accessing a numerical grid model, which includes: receiving a plurality of numerical grid data by a host, each of the numerical grid data includes a spatial coordinate information; the numerical grid data is arranged at a 2D coordinate to generate an initial grid data; the host eliminates at least one overlapping region of the initial grid data to generate a reconstructed grid data; The host divides the reconstructed grid data into a plurality of regional grid data according to a resolution value; and the host indexes each of the plurality of regional grid data. The method for accessing a numerical grid model according to claim 17, further comprising: storing the regional grid data in a map database after the step of indexing each of the regional grid data. The method for accessing a numerical grid model as described in claim 17, wherein after the step of indexing each of the regional grid data, it further includes: calculating at least one number required according to a value-added service event; according to One of the numbered grid data of the retrieved area is a retrieved data; and a calculation result is calculated according to the retrieved data. The method for accessing a numerical grid model as described in claim 17, wherein the spatial coordinate information is the shooting spatial coordinate of each of the numerical grid data. The method for accessing a numerical grid model as described in claim 17, wherein in the step of eliminating at least one overlapping region of the initial grid data to generate a reconstructed grid data, according to each of the numerical grids One of the shooting time of the grid data or a display layer eliminates at least one repeated region. The method for accessing a numerical grid model as described in claim item 17, wherein in the step of dividing the reconstructed grid data into a plurality of regional grid data according to a resolution value, the spatial coordinate information is sequentially divided according to the spatial coordinate information A plurality of area grid data. The method for accessing a numerical grid model as described in claim 17, wherein the resolution value of each of the regional grid data is K*K, and K is a natural number. The method for accessing a numerical grid model as described in claim 17, wherein each of the regional grid data is indexed according to the spatial coordinate information. In the method for accessing a numerical grid model according to claim 19, the value-added service event is weight analysis or search radius analysis. A system for accessing a numerical grid model, which includes: a host computer, which sets a numerical grid model building module to arrange a plurality of numerical grid data according to a spatial coordinate information to generate an initial grid data, eliminating The initial grid data repeats at least one region to generate a reconstructed grid data, divides the reconstructed grid data into a plurality of regional grid data and obtains a plurality of corresponding ones of the plurality of regional grid data Neighboring grid point data is calculated based on at least part of the regional grid data and a plurality of adjacent grid point data corresponding to at least part of the regional grid data. In the system for accessing a numerical grid model as described in claim 26, the host computer further includes: a grid processing unit that arranges a plurality of numerical grid data according to the spatial coordinate information to generate the initial grid data , eliminating at least the overlapping area of the initial grid data to generate the reconstructed grid data; an operation processing unit, which divides the reconstructed grid data into a plurality of regional grid data and obtains each of the corresponding grid data A plurality of adjacent grid point data of the regional grid data, index each of the regional grid data, and calculate the regional grid data; a map database, which stores the indexed regional grid data data; and a calculation module, which calculates according to a value-added service event. In the system for accessing a numerical grid model as described in claim 27, the value-added service event is weight analysis or search radius analysis.

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