KR101089256B1 - Geographic Information analysis method using of programing Invisible Depth Analysis - Google Patents

Abstract

The present invention relates to a method for analyzing geographic information using invisible depth analysis, comprising: (a) selecting a viewing target point; (b) calculating depth data of an invisible region based on a line of sight at an observation point using a view analysis algorithm; And (C) calculating a video image using the calculated data.
By providing the present invention, it is possible to increase the computational speed and eliminate the possibility of initial error, and to correct the error due to the earth curvature radius and the light refraction error for the global analysis, for the range of 11 km or more considered as a plane in surveying. It can be analyzed and developed in the form of a convenient user tool using this reconstructed algorithm, which can be used for convenience and popularity.
In addition, it is possible to analyze the high-resolution wide area that was not possible by the existing manual work, and can be used for landscape management such as height limit of buildings.

Description

Geographic Information analysis method using of programing Invisible Depth Analysis}

The present invention relates to a method for analyzing geographic information, and more particularly, to a method for analyzing geographic information quickly and accurately using an automated invisibility program model rather than a manual method.

In the process of rapid industrialization, he experienced hard development and damage to the surrounding natural landscape due to economic growth logic and development-oriented approach, which led to the recognition of the interest and importance of landscape.

In addition, the enactment of the Landscape Act, which has the basic legal characteristics related to urban landscape, enacted the legal basis for landscape management in each municipality, and is concentrating on landscape management.

However, the policies and experiences of urban landscapes in Korea are still in the early stages, and there are not many in-depth studies on landscapes, and they often rely on qualitative judgments of experts in architecture or urban design. There is a lack of planning.

Therefore, quantitative analysis research is required to secure objectivity of landscape management, and the most representative one is called viewshed analysis, which is an analysis based on visual and physical relations.

Visibility analysis is a technique that analyzes the visible area through which a viewing object is observed through computer simulation. It is used in various fields such as industry, landscape, tourism, military, and space, and it is especially performed in landscape field of environmental impact assessment. It is widely used in analysis to be regarded as an analysis.

However, since the visibility analysis is judged only by the presence of visibility, it is insufficient to judge the quality of the landscape which is more important to the landscape, and various methods are being developed to compensate for this, and the concept of invisibility depth analysis, incident angle analysis, and surface curve analysis, etc. That is it.

Among them, invisible depth analysis is a concept that can be used as a valid tool in landscape management such as depth that can hide development impact or maximum allowable height of facilities, but commercial programs have not been provided yet. Is the reality.

Invisible depth analysis is an analysis that calculates the depth from the collimation line formed by the obstacle between the observation point and the measurement point to the indicator of the measurement point based on the digital terrain information (DTM) (see FIG. 1).

This means the depth of the area that is invisible to the terrain when the landscape is viewed from the main point of view, and when determining the constructionable height of the artificial structure which is considered to be a landscape deterioration factor, or the height of the shortwave antenna erected in the invisible region, It can be used in a variety of ways, for example, when concealing concealed military bases for military purposes.

This concept of invisibility was first mentioned in Higuchi's 1983 book The visual and spatial structure of landscape. In his study of the visual and spatial structure of the landscape, he introduced the concept of invisibility, which seems to reconstruct what had previously been used in ideas rather than his first definition.

Subsequently, Lim Seung-bin et al. (1994) set the minimum preservation height of Namsan Skyline through a study on the urban skyline conservation management technique, and then set the height that can be constructed by the height difference between the elevation angle and the ground surface. 1997), in the study on the visibility information analysis method using GIS, studied the height of building regulation that does not obstruct the view on the main roads of the Sanbangsan area in terms of depth of invisible area.

In addition, Cho Dong-beom (2001) presented the formula of invisible depth through landscape informatization study of skyline and invisible depth in the landscape landscape evaluation. There are a number of studies, including the specific process of quantification.

However, despite these studies, the development of invisibility analysis tools has not been developed even with existing GIS programs or application programs for research purposes. This may be due to low availability in terms of utilization, but it also could not be used because the tools were not developed. This is conceptually established, but is equivalent to many concepts that have been abandoned due to programming technology limitations.

1 is a view showing a conceptual diagram of an invisible depth analysis method, Figure 2 is a view showing a process of calculating the invisibility through the conventional manual work. As shown in Fig. 1 and 2, it means the depth of the area not visible to the terrain when viewed from the viewpoint, it is possible to manually work as shown in Figure 2 through the drawing of the terrain cross section. FIG. 2 shows a manual process used by landscape workers in (a) and draws a grid of appropriate resolution on a map with contours of the target site, and lines between target points (TP) to be obtained from the viewing point (VP). Draw. In (b), the water line is drawn according to the contour height between the view point and the target point, and the terrain cross section and the LOS (Line of Sight) are constructed. The depth of invisibility can be obtained by measuring the depth between the topographical section and the LOS constructed as described above, and (c) repeats the steps (a) and (b) to measure the invisibility of all grid points, and the coloring corresponding to each value. Visualization through.

This invisibility analysis by hand requires a lot of time and effort, and also has a problem of inaccuracy because the grid spacing can be set only within the drawing range. For this reason, there is a problem in the field that some grid areas are not analyzed, or the analysis is abandoned.

An object of the present invention for solving the above problems is to increase the computational speed, eliminate the possibility of initial error, wide area analysis, convenient user tools, and an analysis method with ease of use and popularity To provide.

A first aspect of the present invention for solving the above-mentioned problem is (a) selecting a viewing target point; (b) calculating depth data of an invisible region based on a line of sight at an observation point using a view analysis algorithm; And (C) calculating a video image using the calculated data.

Here, the visibility analysis algorithm of step (b) preferably uses a digital elevation model (DEM), and the algorithm of the viewshed analysis is based on a reference plane method. In addition, it is preferable to use a point-to-point method in combination with a viewpoint close to the viewpoint point.

In addition, preferably, the data on the viewing target point may be using the observer viewpoint height, the viewing target height, the observation azimuth angle, the observation vertical angle and the observation radius data, (a) selecting a viewing target point; (b) calculating depth data of an invisible region based on a line of sight at an observation point using a view analysis algorithm; (c) first correcting an error due to an earth curvature radius in the data; (d) second correcting the error due to the refraction of light in the first corrected data; And (e) calculating a video image using the calculated data.

Here, the step of calculating the digitized data of the step (b) is preferably using a digital elevation model (DEM), the algorithm of the viewshed analysis (Viewshed analysis) is a reference plane method (reference plane method) ), And it is preferable to use a point-to-point method in combination with the viewpoint close to the viewpoint point.

In addition, preferably, the data on the viewing target point may be to use the observer viewpoint height, the viewing target height, observation azimuth angle, observation vertical angle and observation radius data.

By providing the present invention, it is possible to increase the computational speed and eliminate the possibility of initial error, and to correct the error due to the earth curvature radius and the light refraction error for the global analysis, for the range of 11 km or more considered as a plane in surveying. It can be analyzed and developed in the form of a convenient user tool using this reconstructed algorithm, which can be used for convenience and popularity.

In addition, it is possible to analyze the high-resolution wide area that was not possible by the existing manual work, and can be used for landscape management such as height limit of buildings.

1 is a view showing a conceptual diagram of an invisible depth analysis method,
2 is a view showing a process of calculating the invisibility through the conventional manual work,
3 is a flowchart illustrating a method for analyzing geographic information using an invisible depth analysis according to the present invention;
4 is a view showing an invisibility calculation formula and a conceptual diagram thereof;
5 is a diagram showing a conceptual diagram of interpretation of the visibility analysis;
FIG. 6 is a flowchart illustrating a method for analyzing geographic information using invisible depth analysis as another embodiment according to the present invention; FIG.
7 illustrates a point-to-point algorithm and linear interpolation;
8 is a diagram illustrating a scheme of a reference plate algorithm;
9 is a diagram illustrating a conceptual diagram of a mixing algorithm of a reference plate method and a point-to-point method applied in the present invention;
10 is a view showing a relationship diagram of the Geoprocessing Tool applied in the present invention,
11 is a diagram illustrating a procedure for registering an invisible depth analysis DLL implemented in the present invention;
12 is a view showing a user interface of the invisible depth analysis implemented in the present invention,
13 is a view showing the results of geographic information analysis using the invisible depth analysis according to the present invention.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

3 is a diagram illustrating a flow chart of a method for analyzing geographic information using invisible depth analysis according to the present invention. As shown in Figure 3, the present invention (a) selecting the viewing target point (S100); (b) calculating depth data of an invisible region based on a line of sight at the viewing target point using a line of sight analysis algorithm (S110); And (C) calculating a video image using the calculated data (S120).

That is, the present invention provides a method that can calculate the depth (invisibility) of the invisible region on the basis of the collimation line, unlike the conventional invisible depth analysis method, which is made by hand. By providing analysis tools that apply the program technique, it is possible to provide geographic information through invisibility analysis more quickly, accurately and easily.

Hereinafter, the invisibility analysis applied in the present invention will be described in detail.

The calculation of invisibility by programming requires a logical equation, which has already been suggested by the researchers. 4 is a diagram illustrating an invisibility calculation formula and a conceptual diagram thereof. As shown in FIG. 4, the difference between the height corresponding to the target point Pt coordinate of the line of sight (LOS) formed by the viewing point Pv and the terrain obstacle Pb and the elevation of Pt, that is, Hta + Htb is calculated as an invisibility. Hta can be interpreted as (the obstacle height at the height of the eyes (Hb)) × (distance from the viewing point to the target point) ÷ (distance from the viewing point to the blind) by the proportional expression of the LOS angle between the viewing point and the obstacle. It is possible to obtain Htb by arithmetic operations of the elevation of the viewpoint, the eye level of the observer, and the elevation of the target point.

This formula is similar to the formula in the field of view analysis in that it is basically calculated by LOS (Line of Sight). 5 is a diagram illustrating a conceptual diagram of interpretation of the visibility analysis. As shown in FIG. 5, the analysis of the visibility analysis determines the invisible region when the height of the LOS is higher than the target point elevation (Example Pt1), and determines the visible region when the LOS height is lower than the target point elevation (Example Pt2). The target point Pt at this time is interpreted as acting as a visual obstacle Pb of the new LOS.

This means that the algorithm of invisible depth analysis is the same as the algorithm of visibility analysis, and many algorithms have already been studied and published. In the present invention, the invisible depth analysis implementation algorithm employs an existing visibility analysis algorithm.

The observer viewpoint data used here considers the observer viewpoint height, viewing object height, observation start and end azimuth angle, observation vertical angle, and observation radius as shown in [Table 1], and uses the ArcGIS method of inputting as attribute data. It was.

FIG. 6 is a flowchart illustrating a method for analyzing geographic information using invisible depth analysis according to another embodiment of the present invention. As shown in Figure 6, the present invention (a) selecting the viewing target point (S200); (b) calculating depth data of an invisible region based on a line of sight at the viewing target point using a line of sight analysis algorithm (S210); (c) first correcting an error due to an earth curvature radius in the data (S220); (d) second correcting the error due to the refraction of light in the first corrected data (S230); And (e) calculating a video image using the calculated data (S240).

That is, the embodiment according to the present invention is an invention configured to enable more precise analysis by adding an error correction step due to the curvature radius and an error correction step due to the refraction of light to the invention illustrated in FIG. 3.

First, considering the error correction by the radius of curvature of the earth, there are a few more things to consider in the analysis of invisibility by the above-described equation, one of which is that the earth is round. The error caused by the earth's curvature is also known as the difference, and it is the difference in height caused by the earth's curvature.

The error due to the earth curvature radius can be calculated as shown in [Equation 1].

[Δh1: Gradient, S: Distance between two stations, R: Earth radius]

The correction of the error is corrected by subtracting the error from the calculation obtained by the basic equation.

Secondly, in the error correction caused by the refraction of light, another error caused by the rounding of the earth is the error of refraction of light caused by the atmosphere. This causes the level line drawn horizontally from the earth's surface away from the earth and eventually extends into space, where the level line is refracted through the atmospheric layer with a change in density. This is also called an error of refraction of light by the atmosphere or a train, and can be calculated as shown in [Equation 2].

[Δh2: train, K: refractive index (0.12-0.14), S: distance between two points, R: earth radius]

In this case, the refraction coefficient K is applied differently according to the region. In Korea, 0.14 is mainly used. The correction for the error due to the radius of curvature or the refraction of light is proportional to the square of the distance S between the two points, so it can be ignored when the area of the analysis site is not wide, but it must be considered when the area is wide. desirable.

In addition, the viewshed algorithm includes the point-to-point method (Huss and Pumar, 1997), the vector-analysis method (Sorensen and Lanter, 1993), and the reference plane method. , Wang et al., 2000), etc. have already been established, and the characteristics thereof are shown in [Table 2].

Looking at the algorithms of visible visibility analysis, there are advantages and disadvantages in computation time and accuracy. The following describes the point-to-point and reference plate algorithms.

7 illustrates a point-to-point algorithm and linear interpolation. As shown in FIG. 7, the point-to-point algorithm calculates the LOS for all points (points 1-8 on the drawing) that intersect from the viewpoint VP to the target point TP and calculates an invisibility depth based on the point-to-point algorithm. . This method can further increase the accuracy by using a linear interpolation method as shown in (b).

Such a point-to-point algorithm has the advantage that the performance result is very reliable, but the computation time is very long when the target area is large because the calculation is repeated for all grid points between the viewpoint and the target point.

8 is a diagram illustrating a scheme of a reference plate algorithm. As shown in FIG. 8, in the reference plate algorithm, the plane formed by the viewpoint S and the three points of the reference points r _{m -1, n + 1} , r _{m , n + 1} has a relationship with the measurement target terrain height d _{m , n} ( As shown in a), when the height of the reference plate is higher, it becomes an invisible region, and the difference becomes an invisible depth. Also, as in (b), if the terrain height is larger, it is determined as the visible area, and the terrain height d _{m , n} is stored as the reference value r _{m , n} and used as the reference value of the next target point. And the speed is relatively fast. However, since the operation result is used as a reference value of the next point, there is a possibility that an initial error at a point close to the point of time accumulates.

In order to implement the reference plate algorithm, solutions of plane equations are required. Plane equations are represented by Equation 3,

In order to solve the equation, three coordinate points of the plane are required.If the coordinates of the three points constituting the reference plate, that is, the two reference points and the viewing point are set to, the equation coefficients A, B, C, and D of the plane are It can be solved by a matrix as shown in [Equation 4].

Solving this matrix is equal to [Equation 5],

If the x and y coordinates of the target point to be obtained can be known, the height of the reference plate can be obtained by Equation 6.

As discussed above, it is difficult to find an algorithm that satisfies both computation speed and accuracy. Therefore, in the present invention, the point-to-point method is used in combination with the reference plane method in consideration of the computation speed. A diagram illustrating a conceptual diagram of a mixed algorithm of a reference plate method and a point-to-point method applied in the present invention.

Hereinafter, the programming applied to the geographic information analysis method using the invisible depth analysis according to the present invention will be described, and the analysis result will be described.

ArcObject Using Invisible Depth Analysis  avatar

Developing a new program using a given algorithm is very complicated and difficult. Therefore, in the present invention, only the main part is programmed, and the user interface and data format are customized by using an ESRIR ^R ArcObject ^TM product, and implemented in the form of a tool of ArcToolbox in consideration of user convenience and popularity.

ArcGIS ^TM provides 4 types of Geoprocessing customization tools, GPModelTool that directly implements custom buttons, etc. in the product as shown in the Geoprocessing Tool relationship diagram of FIG. 10, and GPScriptTool that can perform simple commands in scripting languages. There are GPCustomTool, which can be implemented and distributed in the form of extension pack mainly used in 3rd party, and GPFunctionTool, which is used to create custom tool of ArcToolbox. In this study, GPFunctionTool which is easy to distribute users and has a wide range of customization using ArcObject is used.

GPFunctionTool is basically implemented by GPFunction object and GPFunctionFactory object. GPFucctionFactory is an object that acts as a container for GPFuctions, and GPFuction is an object that can implement each function to implement.

The implementation programming language of each interface uses VB6.0 (Visual Basic 6.0), and the result is made in the form of a dynamic link library (DLL) and can be registered and executed in ArcToobox of ArcGIS ^TM .

11 is a diagram illustrating a procedure for registering an invisible depth analysis DLL implemented in the present invention. FIG. 11 (a) registers a DLL to the GPFucctionFactory by Category Manager, FIG. 11 (b) adds tools registered in ArcToolbox, and FIG. 11 (c) shows registration tools in ArcToolbox.

1. I / O data

Inputs for invisible depth analysis include viewpoint data and terrain data. For the viewpoint data, ESRI ^R SHAPEFILE was used. The information to be included in the viewpoint data includes the viewpoint coordinate information and the coordinate system. In addition, as shown in [Table 3], the observer viewpoint height, the observation target height, the observation start azimuth angle, the observation azimuth angle, the observation vertical angle, and the observation radius are shown. In addition, ArcGIS ^TM 's viewshed analysis method is inputted as attribute data. It is entered in the form of a table of SHAPEFILE, and if there is no data of the corresponding field, it is treated as the default value.

Terrain data was read into RasterDataset by OpenRasterDataset (in Name: String) method using GRID format, implementing IWorkspaceFactory, IRasterWorkspace. The output data also uses the GRID format, and implements IRasterBandCollection, IRasterBand, and IRawPixels to read (in tlc: IPnt, in pxls: IPixelBlock) and Write (in tlc: IPnt, in pxls: IPixelBlock) methods. Was controlled.

However, since the area range of PixelBlock does not support more than 7000 × 7000 cells, it was necessary to program sector by sector in order to analyze all the areas, but in case of resolution of 1m × 1m, 7km × 7km and resolution of 5m × 5m In the case of a relatively large area of 35km × 35km can be analyzed, there is no separate sectorization programming.

2. User Interface

FIG. 12 is a diagram illustrating a user interface of invisible depth analysis implemented in the present invention. The topographical data and analysis results of ① use the ESRI ^R GRID format, and the observer viewpoint data of the viewing point uses the ESRI ^R SHAPEFILE format. ② is an option to correct the error caused by the curvature of the earth, that is, the difference between the height of the horizontal line and the level line due to the curvature of the earth, and ③ is used to correct the error that the light is refracted by the change in refractive index caused by the density difference of the atmospheric layer. Is optional.

Application of point-to-point algorithm in ④ The point-to-point algorithm was used for the measurement point close to the viewpoint to compensate for the shortcomings of the reference point algorithm as mentioned in the algorithm selection. to be.

3. Application result

The target area was set at a radius of about 10km around Buseoksa Temple. Buseoksa Temple is not only famous for its long history but also for its outstanding landscape resources. These landscape resources are valuable resources to be preserved, and are local resources targeted for regional development projects, and are exposed to indiscriminate development in the context of preservation and development.

Therefore, preservation of traditional landscapes and rational regional development require landscape management to define areas that can be developed and areas that need to be regulated, and in-depth analysis is meaningful as a quantitative basic data for landscape management.

13 is a view showing the results of geographic information analysis using the invisible depth analysis according to the present invention. The view point was held next to Anyang-ru in the front yard of the municipal faucet, and the gaze height was set to 1.6m, the analysis start radius was set to 20m (RADIUS1 = 20), and the resolution was set to 5m × 5m for high resolution analysis. In addition, the result ranged from 0m to 5,368m with a very wide range of values, so that more values within 250m were treated as the same value to increase visibility.

As a result, it was confirmed that not only the results of the visible analysis but also the invisible depth, that is, the invisibility, can be accurately measured when viewed from Buseoksa Temple. It was confirmed that this can be used for the height limit data of the building, which is judged to be a landscape obstacle factor when viewed from Buseoksa Temple.

As such, when a method of analyzing geographic information using an invisible depth analysis according to the present invention is provided, a point-to-point method is located near a viewpoint based on a reference plane method in consideration of a calculation speed. ) Can be used in combination to exclude the possibility of initial error.

Also, for wide area analysis, the error due to the radius of curvature and the refraction error of light are corrected so that it can be analyzed over the range of 11km that is considered as a plane in surveying.In the form of ArcToolbox tool that can be distributed and used by using the reconstructed algorithm Developed and easy to use and popular.

And, as a result of applying this to the site, it was possible to analyze high-resolution wide area which could not be done by the existing manual work, and it can be clearly seen that it can be used for landscape management such as building height limitation.

While the invention has been shown and described with respect to the specific embodiments thereof, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. Anyone with it will know easily.

Claims (8)

(a) selecting a viewing target point;
(b) calculating depth data of an invisible region based on a line of sight at an observation point using a view analysis algorithm; And
(C) a method of analyzing geographic information using an invisible depth analysis, comprising calculating a video image using the calculated data.
The method of claim 1,
In the (b) step, the visibility analysis algorithm is a geographic information analysis method using invisible depth analysis, characterized in that using the Digital Terrain Model (DTM).
The method of claim 1,
The algorithm of the viewshed analysis is based on a reference plane method, and a point-to-point method is used in combination with a viewpoint close to the viewpoint point. Geographic information analysis method using invisibility analysis.


delete (a) selecting a viewing target point;
(b) calculating depth data of an invisible region based on a line of sight at an observation point using a view analysis algorithm;
(c) first correcting an error due to an earth curvature radius in the data;
(d) second correcting the error due to the refraction of light in the first corrected data; And
(e) calculating a video image using the calculated data;
Geographic information analysis method using an invisible depth analysis comprising a.
The method of claim 5,
Computing the data of the step (b) is a geographic information analysis method using the visible frequency analysis, characterized in that using the Digital Terrain Model (DTM).
The method of claim 5,
The algorithm of the viewshed analysis is based on a reference plane method, and a point-to-point method is used in combination with a viewpoint close to the viewpoint point. Geographic information analysis using visual frequency analysis.


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