KR100450631B1 - Method for making a DEM using a interpolation - Google Patents

Abstract

Elevation point layer extraction step, which extracts a layer with information about elevation values from the digital map of the DXF (DXF) file format and converts it into an internal file format, the elevation point extracted in the elevation point layer extraction step A TIN generation step of generating data of a triangular irregular triangular network structure (TIN) using the following procedure; And

(a) extracting the elevation point in the elevation point layer extraction step, selecting a starting point, (b) selecting two points other than the starting point, and calculating the outer core of the triangle by forming a triangle using three points, and (c) (DT; Delaunay Triangulation) If the triangle is satisfied and the generated triangle does not already exist, the triangular shape is determined, if the Diti condition is not satisfied, if the generated triangle exists, returning to the step of selecting two points other than the starting point, (d) outputting the internal format file after determining the triangle;

Nearest Neighbor Interpolation, Inverse Weighted Distance Interpolation, Inverse Square Distance Weighted Interpolation Method using the elevation point output in the form of an internal format file in the TIN generation step A lattice using interpolation, comprising generating a digital elevation modeling (DEM) by one method selected from the group consisting of Inverse Square Distance Weighted Interpolation and Bilinear Interpolation Disclosed is a method for generating a die DM.

According to the present invention, a lattice type DM can be obtained which is used in many fields such as spatial analysis, three-dimensional modeling, mathematical analysis, etc. using a pre-established national numerical map.

Description

Method for making a lattice type DM using interpolation {Method for making a DEM using a interpolation}

The present invention relates to a method for generating digital emulation modeling (DEM) using interpolation, and in particular, many fields such as spatial analysis, three-dimensional modeling, and mathematical analysis using triangular networks and interpolation methods on irregular elevations extracted by digital maps. The present invention relates to a method for generating a lattice type diem used in the present invention. The interpolation method is used to know the altitude value of a specific point in a certain area that already knows the attribute value, that is, the altitude value. The method of the present invention uses this interpolation method to provide useful data in various fields. How to create it.

As a topographic map digital mapping project that is part of the National Geographic Information System (NGIS) project currently being promoted by the government, the 1 / 5,000 digital map has already been produced for the whole country, and the existing national numerical map can be used in various fields. One of the important ones is to generate lattice type DM data (hereinafter abbreviated as DM) which is used in many fields such as spatial analysis, 3D modeling, and mathematical analysis.

Commercially developed DM generators are DXF2DEM (Intersys, Korea) in Korea, and ER-Mapper 6.0 (ER Mapper, Australia) and MGE (Intergraph, USA).

Overseas, KYPIPE and EPANET are used.

DXF2DEM is a software of pure domestic technology that makes DEM data in a short time without going through a separate conversion step by selecting a three-dimensional specific layer such as contours from digital map de-X (DXF) data.

ER Mapper is one of the world's most widely used image processing software. The Surface Gridding wizard in ER Mapper 6.0 is software for creating multiband grid images from multi-input data.

MGE Terrain Modeler is a 3D terrain analysis software using DM and other surface data. It is used for flood prevention, location of dams and communication facilities, modeling of terrain information, error search and analysis.

Since these commercial DM programs are independent executable DM generating programs, they require expensive program costs, and when only DM generation is required, a program including other functions must be purchased. In addition, foreign products may not be suitable for digital maps established by the National Geographic Information System, and very complicated usage methods are required.

An object of the present invention is to use a national numerical map, which is an established method, and extracts an elevation point with an altitude value using a national numerical map and applies interpolation to apply grid-type DM data for spatial analysis, three-dimensional modeling, and mathematical analysis. To provide a way to produce.

National figures map basically includes layers with contours, reference points, etc., which have elevation values. Therefore, in the present invention, as a method of generating a lattice type DM, the present invention intends to propose a method of extracting an elevation point having an altitude value using a pre-established national numerical map and generating it as a lattice type DM.

The present invention proposes a method for generating a lattice type DM using triangular networks and interpolation at irregular elevations extracted by a digital map. Hereinafter, the present invention will be described in detail.

The present invention proposes a method for extracting an elevation point having an altitude value using a national numerical map in the form of a DXF (DXF) and generating a DM using the same.

Types of interpolation used in the present invention include Nearest Neighbor Interpolation, Inverse Weighted Distance Interpolation, Inverse Square Distance Weighted Interpolation, and Bilinear Interpolation Interpolation and Linear Interpolation.

The method of the present invention can be divided into three stages as follows.

First, the elevation layer extraction step of extracting the layer with the information about the altitude value from the digital map of the dex F file format and converting it into the internal file format

Secondly, TIN generation step of generating data of irregular triangular network structure (TIN) using extracted elevation point

Third, a lattice-shaped DEM is generated by interpolation using the extracted elevation points.

Hereinafter, a case where the present invention is actually applied to a specific region will be described as an example. Hereinafter, each step will be described by noting the module (elevation layer layer extraction module, TIN generation module, DEM generation module) responsible for such a function.

Target area

The sample target area of the present invention is as follows.

1) Target area: Sinmyeon-ri, Immam-myeon, Jeongeup-si

2) Target Area: 6.31 sq km

3) Digital Map File Name (1: 5000, 1'13 "* 1'13"): 35612002.dxf

Module Diagram

The module of the present invention includes an elevation layer extraction module, a lattice type DEM generation module, a TIN generation module, and the like.

The DEM generation module using interpolation can be largely divided into three modules. Firstly, there is an elevation layer extraction module that extracts layers containing elevation information from the DXF format digital map and converts them into an internal file format. Secondly, there is a TIN generation module that serves to generate a TIN using the extracted elevation points. Third, there is a lattice type DEM manufacturing module that serves to generate a lattice type DEM by interpolation using the extracted elevation points.

-Elevation layer extraction module (Elevation layer extraction step)

In the extraction of the elevation point layer, extraction of the elevation point for the fabrication of the lattice type DEM involves the following tasks.

1) Elevation point rare extraction module is a preliminary step for the production of lattice DEM, and extracts the layer with elevation information from DXF format digital map and converts it into internal file format.

2) Elevation point layer is a layer containing information about elevation point, and means the layer with code number 71XX (contour line), 7217 (elevation point), and 73XX (reference point) of the national digital map standard topographic code.

3) The method of extracting these layers directly reads a DXF file and extracts only those layers whose layer code corresponds to 71XX (contour line), 7217 (elevation point), and 73XX (reference point) to convert to internal file format.

4) The internal file format here is an ASCII file that holds x, y, z information about elevation points extracted from the elevation point layer.

-TIN generation module (TIN generation step)

The TIN generation module includes the following work flow.

1) The TIN generation module converts the data into an irregular triangular network structure using x, y, and z information about the elevation points extracted by the elevation layer extraction module.

2) Delaunay triangles are created using randomly distributed elevation points.

3) The conditions for the creation of this Delaunay triangle shall not include any other points in the inscribed circle for the three points constituting the triangle.

4) The output TIN is saved in internal file format.

5) The internal file format here is an ASCII file that holds information about the nodes, edges, and triangles that make up the TIN.

-Grid DEM Fabrication Module (Grid DEM Generation)

Fabrication of lattice DEM involves the following process.

1) The lattice type DEM manufacturing module plays a role of generating lattice type DEM by interpolation using extracted elevation points.

2) The interpolation method is used to know the property value of a specific point in a certain area that already knows the property value. In the present invention, the interpolation method for the four methods of Nearest Neighbor, Inverse weighted distance, Inverse square distance weighted interpolation, and Bilinear Interpolation is compared and analyzed.

3) In manufacturing lattice DEM using extracted elevation points, Nearnest Neighbor, Inverse weighted distance, Inverse square distance weighted interpolation, and Bilinear interpolation are used.

4) The lattice type DEM to be output has information about the ground coordinates of the origin, the size of the pixel, and the number of rows and columns.

5) The grid DEM file format is ArcView's ASCII Raster file format.

-Detailed workflow of the DEM creation stage

The DEM generation process using interpolation can be divided into the elevation layer extraction process and the TIN generation lattice DEM generation step. The flow chart of the whole work process is shown in the table below.

-Detailed process of extracting the elevation point layer

The elevation point layer extraction module forms a triangle network and converts elevation points for generating a DEM using an interpolation method from the digital topographic map in DXF format into an internal format. The method of extracting such a layer directly reads a DXF file, and extracts only layers corresponding to contour lines 71XX, elevations 7217, and reference points 73XX, and converts them into an internal file format. At this time, the internal file format stored is an ASCII file, and represents x, y, and z information about elevation points extracted from an elevation point layer.

Detailed process of TIN generation

-Detailed process of lattice DEM production

This step is to create a grid-type DEM using the elevation data inside the extracted point in the elevation point layer extraction step as input data. In this step, the resolution of the DEM to be generated is decided and the type of interpolation method is selected to manufacture the DEM. Below is a flow chart of this lattice DEM fabrication process.

-Application formula and technical analysis of invention

-Application formula and technical analysis related to the elevation point extraction module

-DXF file description and main group codes

The input data of the present invention is a country value map in DXF file format, and the DXF file is a file exchange format for AutoCAD by AutoCAD, which is developed to enable data compatibility internally with AutoCAD (file format DWG) or with other 3D programs. With the widespread use of AutoCAD in the industry, the DXF data format has become the de facto common format for 3D data. The characteristic of DXF data is that the file structure is composed of ASCII characters, so that the contents can be checked and modified by a general text editor, but the size of the file is quite large.

DXF files enable the exchange of AutoCAD with other programs. DXF files can be in ASCII or binary format. All AutoCAD executables accept the ASCII DXF format. But the opposite is not guaranteed. ASCII DXF files can be easily converted to other CAD system formats and applied well to the special analysis of other programs. Since ASCII DXF files are more common than binary formats, this chapter uses DXF files to represent ASCII DXF files, and binary DXF files to represent binary formats.

Both ASCII and binary DXF files contain a complete description of AutoCAD drawing. Most AutoCAd drawing data does not have equivalent object types in other programs, so the DXB file format is given. This creates a simple geometric depiction of the drawing.

DXF files are organized as pairs of values associated with code. Code known as group code indicates the type of associated value. By using group code and value pairs, DXF files are organized as parts. It consists of records consisting of group code and data items. Each group code and value is on its own line in the DXF file.

Each part starts with group code 0 followed by the string SECTION. This is followed by group code 2 and the string giving the name of the section (eg HEADER). Each section consists of a group code and a value defining its elements. At the end of each section is a string ENDSEC 0.

The overall organization of the DXF file is as follows.

HEADER section This section contains general information. It consists of the version number of AutoCAD and the number of variables in the system. Each parameter contains the name of the variable and its associated value.

-BLOCKS section: Contains information about defined applied class. An example of this is the database of BLOCKS, ENTITIES and other OBJECTS sections. The definition of a class is permanently fixed in the class hierarchy.

TABLES section This section contains the definition of the symbol table.

APPID: application identification table

-DIMSTYLE: Dimension Shape Table

-LAYER: Layer Table

-LTYPE: Line Type Table

-STYLE: text type table

UCS: user coordinate system table

VIEW: view table

VPORT: viewport configuration table

-BLOCK_RECORD

BLOCKS section contains a block definition and a drawing object that makes each block reference to a drawing.

ENTITIES section: This section contains graphic objects (entities) and block references in the drawing.

OBJECTS section contains non-graphical objects of the drawing. All objects that are not entities or in symbol table records or symbol tables are stored in this section. Examples of entries in the OBJECTS section are dictionaries containing mline styles and groups.

-Analysis of applied formula and technology related to TIN generation module

The triangular network TIN generated in the present invention satisfies the conditions of the Delaunay triangle as follows.

Delaunay triangle

Delaunay triangles are triangles that do not contain any other points in the circumscribed circle of the three points that make up the triangle. In order to check whether the condition of the Delaunay triangle is satisfied, the outer core of the triangle and the radius of the circumscribed circle must be found.

-The outer core of the triangle

The outer core of the triangle means the center point of the circumscribed circle of the triangle and has the following properties. This property can be used to calculate the outer core.

The outer core of the triangle is equidistant from each vertex. Therefore, if each vertex of the triangle is A (x1, y1), B (x2, y2), C (x3, y3), and the outer core is O (x, y), the following equation is established.

-Radius of circumscribed circle

-Deluanay triangular condition check

To determine if the triangle created using the three points is a Deluanay triangle, we construct a circle circumference using the outer core and the radius of the circumscribed circle, and then check whether any point other than the three points constituting the triangle is inside the circumference. Just do it.

The method of checking whether an arbitrary point is in the circumscribed circle is determined using the equation of the circumscribed circle as follows.

If the outer core is O (x, y) and the radius of the circumscribed circle is r, the equation of the circumscribed circle is as follows.

(x-Ox) ² + (y-Oy) ² = r ²

To check if any point is in the circumscribed circle, compare the left and right side values by substituting any point P (x, y) into the equation of the circumscribed circle.

If the value on the left side is greater than the value on the right side r ² , any point P is outside the circumscribed circle.

On the contrary, if the value on the left side is smaller than the value on the right side r ² , it cannot be a Delaunay triangle because there is a point other than the vertex of the triangle in the circumscribed circle.

-Interpolation method using TIN

The process of converting TIN to DEM is to take the z-values of the three points of the triangle and use interpolation to find the altitude value (z-value) for any lattice inside the triangle.

For example, use the interpolation method to find the altitude value of the p 'point for the z value of the (i, j) th grid at the three points p1, p2, and p3 of the given triangle as shown below.

The three points are called p1 (x1, y1, z1), p2 (x2, y2, z2), p3 (x3, y3, z3), respectively, and any point to find is p '(x', y ', z Let's say

Compute x 'and y' from the position of the p (i, j) lattice.

Apply linear interpolation to find z '

Let's assume the linear equation z = ax + by + c.

The constants a, b and c are obtained by substituting the three points p1, p2 and p3 of the triangle.

-Z 'is obtained by substituting (x', y ') of p' into a linear equation.

The altitude value of the p (i, j) grid is z '.

(You can find the altitude value of any point inside the triangle.)

-Application formula and technical analysis related to lattice type DEM manufacturing module

Interpolation applied in the lattice-shaped DEM fabrication module of the present invention is four types: Nearest Neighbor Interpolation, Inverse weighted distance Interpolation, Inverse square distance weighted interpolation, and Bilinear Interpolation. Details are as follows.

Nearnest Neighbor Interpolation

The simplest interpolation is to find the nearest point around and take a value. The first point to be found in the above-described manner is the closest point, so the altitude value of the found point is taken.

In the search order described above, the closest point is found in the sixth. In other words, since the altitude value of the nearest point in x is 100, this value is taken as x.

Inverse weighted distance Interpolation

Inverse weighted distance interpolation calculates the distance from the unknown point to the point where the altitude value is already known, and weights the inverse of the distance value so that the closer to the unknown point, the greater the weight. You can get the altitude value of.

This interpolation method is calculated as follows.

Inverse square distance weighted interpolation

Inverse square distance weighted interpolation calculates the distance from the unknown point to the point where the altitude value is already known, and estimates the value by weighting it as the inverse of the square of the distance value so that the closer to the unknown point, the greater the weight. do.

This interpolation method is calculated as follows.

Number of points to search = 3

Grid size = 10

If three elevation points adjacent to x were found: 112, 70, and 100,

Calculate x by weighting the distance inversely.

dsum = 1/800 + 1/800 + 1/200 = 0.0075

zsum = 112/800 + 70/800 + 100/200 = 0.7275

As a result, x is

x = zsum / dsum = 97

Bilinear Interpolation

Bilinear Interpolation is a method of estimating unknown values using surrounding values. This is a method of assigning a value to a point you want to know by weighting the area according to the distance from one point to another point, rather than weighting the distance from point to point.

This interpolation method is calculated as follows.

Number of points to search = 3

Grid size = 10

If three elevation points adjacent to x were found: 112, 70, and 100,

x-112 Area = 400

x-70 Area = 400

x-100 Area = 100

Calculate x by weighting the distance inversely.

dsum = 1/400 + 1/400 + 1/100 = 0.015

zsum = 112/400 + 70/400 + 100/100 = 1.455

As a result, x is

x = zsum / dsum = 97

Output file format structure

-Extracted elevation point file format structure

Elevation Point Extraction The internal file format structure of elevation points extracted from the layer module is as an ASCII file. The ID and x, y and z values for the elevation point are repeated sequentially.

TIN internal file format structure

The structure of the TIN consists of a triangle constituting a triangle network, three points constituting each triangle, and three edges. In storing the triangles generated as a result of the triangle network formation, the points constituting each triangle have x, y, and z values, and the edges are indexes of two points forming each edge. The triangle stores the index values of the three edges forming the triangle. The most important point in storing with this structure is to prevent duplicate points and edges from being saved. This also enables more efficient retrieval of objects and objects in the TIN.

The above three tables show the result after duplicate storage after TIN is completed. For 10 TIN triangles, the number of points is 12, the number of edges is 21 and the triangle is stored 10. Each point has a coordinate value and an altitude value. The edges are stored as indexes of both ends of the points, and triangles as indexes of edges forming a triangle.

Grid DEM internal file format structure

In the present invention, the DEM generated by the lattice-type DEM fabrication module is stored in an ASCII internal file format. This format is compatible with Arcview's Import Raster Data Type. The detailed file structure is shown below.

-Design of DEM Generation Module Using Interpolation

Class design

1) class content

In the present invention, it is basically based on the CGISPoint class and the CGISGrid class. The member functions and member variables of the class are as shown below.

CGISPoint is designed to represent Point objects in the elevation layer extraction stage.

Class. The CGISPoint class will contain information about the x, y, and z values of the Point object.

CGISGrid is a class for representing grid DEMs created by interpolation using extracted elevation points. The CGISGrid class includes header information required for the grid-type DEM and information on altitude values for each grid.

The CGISElev class corresponds to the elevation layer extraction module. Elevation points with altitude values are extracted from the digital map and stored in an internal file format.

The CGISDem class corresponds to the lattice DEM production module. A lattice DEM is generated through various interpolation methods using an internal file format that contains information about elevation points extracted from the CGISElev class.

The CGISTri class uses the extracted elevation points to create a DT (Delaunay Triangle) and store it in an internal file format.

2) Detailed class description

Application algorithm

Elevation layer extraction module algorithm

The role of the elevation layer extraction module is to derive elevation points from objects with elevation values from the DXF format file. Among the layer codes of the national figures map, the codes of the layer having the high value correspond to codes starting with 71, 72, and 73 in the middle classification. If you list in detail:

1) contour layer code

-7110, 7111, 7112, 7113, 7114, 7120, 7121, 7122, 7123, 7124, 7130, 7131,7132, 7133, 7134

2) Elevation Layer Layer Code

-7217

3) Base Point Layer Code

-7310, 7311, 7312, 7320, 7321, 7322, 7323

The extraction of the elevation point layer code can be easily solved because the digital map data is a Dxf file and an ASCII file format. That is, the algorithm design is solved as follows.

The algorithm applied in the present invention has only three types of objects having a high value, such as POLYLINE, INSERT, and VERTEX. Therefore, if the object has a high value, the z value must be included in the Group Code 30. Extracting the elevation point with z through

Elevation layer extraction algorithm

File Open-> "Dxf File"

While (End of File)

Layer Value <-Scan 1 Line in Dxf File

IF Layer Value = POLYLINE, INSERT, VERTEX Then

IF Scan Value = 10 Then X <-Scan Next Line in Dxf File

IF Scan Value = 20 Then Y <-Scan Next Line in Dxf File

IF Scan Value = 30 Then Z <-Scan Next Line in Dxf File

IF Layer Value = $ EXTMAX, $ EXTMIN Then

Boundary Value <-Scan Next Line in Dxf File

End of while

TIN generation module algorithm

The TIN generation module plays a role in generating a TIN using the elevation point extracted from the elevation point layer extraction module. The generated TIN is stored in an internal file format. This includes information on the points, edges, and triangles that make up the TIN.

The algorithm for generating a TIN is:

// form a Delaunay triangle for all elevations

for (i = 0; i <n; i ++) {

pi = point [i];

for (j = i + 1; j <n; j ++) {

pj = point [j];

for (k = i + 1; k <n; k ++) {

// If j == k, triangle is not formed so skip

if (j == k) continue;

pk = point [k];

if (! newTri.Create (pi, pj, pk))

continue; // if triangle configuration is not possible

// check if the triangle created already exists

flag = 0;

for (m = 0; m <count; m ++) {

// compare center of circumference to see if two triangles are equal

If (newTri.hashCode == cc [m]) flag ++;

if (flag> 0) break;

}

if (flag> 0) continue;

// DT condition check of generated triangle

flag = 0;

for (l = 0; l <n; l ++) {

// Check DT condition by assigning another random point

flag + = newTri.CheckDT (point [l]);

if (flag> 0) break;

}

// if DT condition is satisfied

if (flag == 0) {

cc [count ++] = newTri.hashCode;

Add_point (pi, pj, pk);

}

} // end for k

} // end for j

} // end for i

-Grid DEM Fabrication Module Algorithm

For grid-like DEM generation, it is possible only through interpolation using extracted elevation points. There are various methods for such interpolation, and the present invention is applied to four methods such as Nearest Neighbor, Inversed weighted distance, Inversed square distance weighted distance Interpolation, and Bilinear Interpolation.

Interpolation is a method used to know the altitude value of a specific point in a region that already knows the attribute value, that is, the altitude value.

In the present invention, the following method was used to find a point having an altitude of the surroundings.

Fix the column among the grids at the x position and the surrounding position, search 135, 246 first, and then search 78.

If the search results fall short of the number desired by the user, the size of the window is increased and the same search method is searched.

Peripheral Grid Search Algorithm

inc = 0; // increment for window size

while (found <= searchPoints) {

for (k = (i-inc); k <= (i + inc); k ++) {

l = j-inc;

...

l = j + inc;

...

} // end for k

for (l = (j-inc + 1); l <= (j + inc-1); l ++) {

k = i-inc;

...

k = i + inc;

...

} // end for l

} // end while

1) Nearest Neighbor Interpolation Algorithm

The simplest interpolation is to find the nearest point around and take a value. The first point to be found in the above-described manner is the closest point, so the altitude value of the found point is taken.

Therefore, if a close point is found in the search algorithm described above, the altitude value may be taken. In this case, searchPoints would of course be 1.

Nearest Neighbor Interpolation Algorithm

inc = 0; // increment for window size

searchPoints = 1; // just find the closest point

while (found <= searchPoints) {

for (k = (i-inc); k <= (i + inc); k ++) {

l = j-inc;

if (Check == True) {

zsum + = grid.z [k] [l];

found ++;

}

l = j + inc;

if (Check == True) {

zsum + = grid.z [k] [l];

found ++;

}

} // end for k

for (l = (j-inc + 1); l <= (j + inc-1); l ++) {

k = i-inc;

if (Check == True) {

zsum + = grid.z [k] [l];

found ++;

}

k = i + inc;

if (Check == True) {

zsum + = grid.z [k] [l];

found ++;

}

} // end for l

} // end while

2) Inverse weighted distance Interpolation algorithm design

Inverse weighted distance interpolation calculates the distance from the unknown point to the point where the altitude value is already known, and weights the inverse of the distance value so that the closer the point is, the greater the weight is. You can get the altitude value of.

Therefore, if a close point is found in the search algorithm described above, the altitude value may be taken. In this case, searchPoints are determined arbitrarily by the user. However, if serachPoint is 1, it is the same as Nearest neigbhor Interpolation. Therefore, serchPoint must take at least two values.

Inversed weighted distance Interpolation algorithm

inc = 0; // increment for window size

searchPoints = 5; // search for 5 nearest points

dd = 0; // distance from unknown

dsum = 0; // sum of inverse weights of distances

zsum = 0; // sum of altitude values by weight

while (found <= searchPoints) {

for (k = (i-inc); k <= (i + inc); k ++) {

l = j-inc;

if (Check == True) {

dd = double ((i-k) * (i-k) + (j-l) * (j-l));

dsum + = double (1.0 / dd);

zsum + = grid.z [k] [l] / dd;

found ++;

}

l = j + inc;

if (Check == True) {

If (Check == True) above

Same as contents

}

} // end for k

...

} // end while

3) Inverse square distance weighted distance Interpolation algorithm design

Inverse square distance weighted distance Interpolation calculates the distance from the unknown point to the point where the altitude value is already known, and weights the inverse of the square of the distance value so that the closer to the unknown point, the greater the weight.

As with Inverse weighted interpolation, the number of searchPoints allows the user to set any value greater than one.

Inversed square distance weighted distance Interpolation algorithm

inc = 0; // increment for window size

searchPoints = 5; // search for 5 nearest points

dd = 0; // distance from unknown

dsum = 0; // sum of inverse weights of distances

zsum = 0; // sum of altitude values by weight

while (found <= searchPoints) {

for (k = (i-inc); k <= (i + inc); k ++) {

l = j-inc;

if (Check == True) {

dd = float (((i-k) * (i-k) + (j-l) * (j-l)) * ((i-k) * (i-k) + (j-l) * (j-l)));

dsum + = float (1.0 / dd);

zsum + = grid.z [k] [l] / dd;

found ++;

}

l = j + inc;

if (Check == True) {

Same as if (Check == True) above

}

} // end for k

...

} // end while

4) Bilinear Interpolation Algorithm Design

Bilinear Interpolation calculates the distance from the unknown point to the point where the altitude value is known in a certain area within a certain range, and weights the inverse of the width value corresponding to the distance so that the closer to the unknown point, the larger the weight is. to be.

If a point found within a certain range of the unknown point lies on a parallel line with the unknown point, it does not form a rectangle. In this case, the weight of the unknown point is given by weighting the square of the distance without giving weight as the width of the rectangle. Will be estimated.

-How to use DEM generation module using interpolation

Elevation layer extraction

After declaring the CGISDemInterpolation class as shown below, call the ExtractElevFromDxf member function.

CGISDem Interpolation demCD;

demCD.ExtractElevFromDxf ("35612002.dxf");

Extracted elevation points are stored in ASCII internal file format.

-DEM generation by Nearest Neighbor Interpolation

Following the elevation extraction, the DEM is created by calling the NearestInterpolation member function as shown below.

demCD. Nearest Interpolation (10);

The generated grid DEM is stored as nearest.asc ".

-Generation of DEM by Inverse weighted distance Interpolation

After extracting the elevation point, call the InverseDistanceInterpolation member function as shown below to create the DEM. The parameter value is the number of points to search.

demCD. Inverse Distance Interpolation (10, 3);

The resulting grid DEM is stored as weight.asc ".

-DEM generation by inverse square distance weighted interpolation

After extracting the elevation, InverseSquareDistanceWeighting-

Calling the Interpolation member function generates a DEM. The parameter value is the number of points to search.

demCD.InverseSquareDistanceWeightingInterpolation (10,3);

The resulting grid DEM is stored as square.asc ".

-DEM generation by Bilinear Interpolation

After extracting the elevation point, call the BilinearInterpolation member function as shown below to generate the DEM.

demCD.Bilinear Interpolation (10);

The resulting grid DEM is stored as "bilinear.asc".

-DEM generation by Tin-Linear Interpolation

After extracting the elevation point, call the TinLinearInterpolation function as shown below to generate the DEM.

demCD.TinLinearInterpolation (10);

The resulting grid DEM is stored as "tin.asc".

As described above, according to the method of the present invention, there is provided a method of generating a lattice type DM used in many fields such as spatial analysis, 3D modeling, mathematical analysis, and the like by using an already constructed national numerical map.

Claims (4)

Elevation point layer extraction step of extracting a layer with information about elevation value from the digital map of DXF (DXF) file format and converting it into an internal file format. TIN generation step of generating a triangular Irregular Network (TIN) of irregular triangular network structure by using the elevation point extracted in the elevation point layer extraction step; And (a) selecting a starting point after extracting an elevation point in the elevation point layer extraction step, (b) selecting two points other than the starting point and forming a triangle using three points to calculate the outer core of the triangle; (c) determining the triangular shape if the triangle satisfying the Delaunay Triangulation (DT) condition and the generated triangle does not already exist; and selecting two points other than the starting point if the generated triangle is not satisfied. Back step, (d) outputting the internal format file after determining the triangle; Nearest Neighbor Interpolation, Inverse Weighted Distance Interpolation, Inverse Square Distance Weighted Interpolation Method Generating a digital Elevation Modeling (DEM) in one method selected from the group consisting of Inverse Square Distance Weighted Interpolation, Bilinear Interpolation, and Linear Interpolation. Grid-based DM generation method using the interpolation method characterized in that. delete delete delete