JP2009251250A - Numerical map data processing method, numerical map data processing program, and numerical map data processing apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a numerical map data processing method for expressing a landform in topographic indices composed of a plurality of elements on the basis of a numerical map so as to create a map with excellent visibility. <P>SOLUTION: An altitude value k at each lattice point E is read from numerical map data 50. A range constituted of a plurality of lattice points E surrounding the central lattice point is set to be a nearby range NA. Out of the altitude values k of all the lattice points E in the nearby range NA, a peak contact altitude value k<SB>max</SB>and a valley contact altitude value k<SB>min</SB>are read and, from the expression R=(k-k<SB>min</SB>)/(k<SB>max</SB>-k<SB>min</SB>), a ratio altitude value R is calculated. Next, on the basis of the altitude value k of each lattice point E, the tilt angle θ of the slope of each lattice point E is calculated. Then, for every lattice point E, a topographic index T is calculated from the expression T=log(k×tanθ×R). Then, color image data are calculated from the topographic index T for every lattice point E and, by making the color image data correspond to lattice point by an operation such as pasting the color image data to each lattice point E, a topographic map is created, displayed on a display section 5 and outputted by an output section 6. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

The present invention relates to a numerical map data processing method, a numerical map data processing program, and a numerical map data processing apparatus for expressing a landform numerically based on numerical map data and creating a map with excellent visibility based on the numerical value About.

Many attempts have been made to visualize and represent the terrain on a two-dimensional map. Generally, maps that represent the terrain include contour maps, shade maps, elevation maps, and slope distribution maps. . The contour map is a method of expressing the topography by connecting the same elevation points with lines. The shadow map is a method of expressing the terrain three-dimensionally by simulating light irradiation from a specific direction. The altitude map is a method for expressing the topography by displaying the altitude in different colors. The slope distribution map is a method of expressing the terrain by associating the slope amount of the terrain with brightness, saturation, and the like. Many of these maps are created on the basis of numerical map data obtained by converting the terrain into data by associating the altitude with a mesh formed by dividing the terrain into the longitude and latitude directions.

The numerical map data is processed by comparing the altitude data of adjacent meshes to make the reference mesh the altitude data associated with the least error due to truncation of the altitude data of the numerical map. By setting the mesh elevation data as the reference elevation data, connecting the same reference elevation data from the coordinate values of the reference mesh and the reference elevation data, drawing high-precision contour lines with few errors, and expressing the inclined surface with high accuracy There is a numerical map data processing method capable of performing (Patent Document 1). Moreover, as a method for displaying the terrain, a so-called red three-dimensional map is created by three-dimensionally expressing the height and inclination of the uneven portions of the terrain by intuitively visualizing the vector field including the three-dimensional attributes. There is a visualization processing system (Patent Document 2).
JP 2003-208094 A Japanese Patent No. 3670274

However, the contour map creates contour lines at constant elevation intervals, so the contour interval becomes too dense at points with steep slopes, and the contour interval becomes too wide at points with gentle slopes. There is a problem that it is difficult to express the topography visually. In particular, the cliff part cannot be expressed because there are no gaps between the contour lines, and there is a problem that a complicated work of replacing with a cliff symbol is required.

  The shadow map expresses the undulation of the terrain by shining light from above diagonally, so that the slope in a specific direction is emphasized, and the shadowed area becomes dark and difficult to see. Furthermore, since the topography with small unevenness cannot be expressed, it is not possible to express a flat plain with few undulations. There is also a problem that the unevenness is reversed and the appearance is different depending on the direction of light.

There are altitude map and contour map as elevation maps, but all of them are densely expressed in high altitude areas, but in low altitude areas, the change in altitude is scarce and the expression is sparse, and the topography can be expressed in detail. I can't. In addition, it is difficult to distinguish whether the slope is an ascending slope or a descending slope, and there is a risk of mistaking the ridges and valleys, so a certain level of skill is required to accurately interpret the topography. Furthermore, it cannot be said that the terrain is represented three-dimensionally as a whole map, and there is a problem that it is difficult to visually grasp the terrain.

In the slope distribution map, the same slope location is expressed in the same way.For example, if the slope is zero slope in both the ridge and valley, it becomes the same expression, and the distinction between the plain and the mountain is unclear and the distinction between the ridge and the valley cannot be made. . In addition, the unevenness of the slope is also unclear. And since the slope map expresses the terrain based on the slope angle, it is impossible to express a plain portion with little undulation and little slope. As described above, it is difficult to express on the two-dimensional plane so that the features of the terrain can be intuitively understood only by individual data such as altitude and inclination.

On the other hand, since the map created by the numerical map data processing method of Patent Document 1 described above is a single representation of only elevation data, it does not fall under the category of the conventional terrain representation method, and is always excellent in visibility. However, there is a difficulty in clearly expressing low flat areas with flat and low undulations. The so-called red three-dimensional map created by the above-described visualization processing system of Patent Document 2 is a map configured to display red as the amount of inclination increases, brighter as the altitude is higher, and darker as the altitude is lower. It is excellent for expressing mountains with high altitude and lots of unevenness, but it cannot express terrain with low altitude and low unevenness in detail, and is unsuitable for expressing plains and urban areas. Furthermore, since it is not a simple gradation display, there is a problem that it is difficult to superimpose with other maps.

  The present invention has been made in view of the above-described drawbacks of the prior art. By representing the terrain with numerical values composed of a plurality of elements based on numerical map data, various numerical analyzes of the terrain are possible, and further based on the numerical values. It is an object of the present invention to provide a numerical map data processing method, a numerical map data processing program, and a numerical map data processing apparatus for creating a map with excellent visibility.

The means of the present invention configured to solve the above-described problem is configured by dividing the ground surface by a plurality of meshes arranged along two-dimensional coordinates, and by the altitude values at each lattice point of the mesh. The step of obtaining the altitude value k of each grid point from the numerical map data, and a range composed of a plurality of grid points surrounding the grid point for each grid point is set as the neighborhood range of the grid point, and the neighborhood range A maximum altitude value k _max and a minimum altitude value _kmin from the altitude values k of a plurality of grid points, and based on the acquired maximum altitude value k _max , the minimum altitude value _kmin and the altitude value k, There is a step of calculating a specific elevation R for each lattice point by an equation of R = (k−k _min ) / (k _max −k _min ).

  And obtaining the elevation values k of a plurality of grid points surrounding the grid points for each of the grid points, and calculating the inclination angle θ of the slope at the grid points based on the plurality of elevation values k; Based on the altitude value k, the specific altitude R, and the inclination angle θ, it is preferable to further include a step of calculating the geological index T for each grid point by the equation T = log (k × R × tan θ).

  Further, color image data is calculated for each grid point based on the relative elevation R, and a specific elevation map is created by associating the color image data with the corresponding grid point, and is displayed on the display unit or output to the output unit. It is good to further have the step to do.

  Further, the step of creating the relative elevation map and displaying it on the display unit or outputting it to the output unit calculates color image data corresponding to the shade based on the relative elevation R, and corresponds the color image data to the corresponding grid point. By doing so, a gradation ratio elevation map may be created and displayed on the display unit or output to the output unit.

  Further, color image data is calculated for each grid point based on the topographic index T, and a topographic map is created by associating the color image data with the corresponding grid point, and displayed on the display unit or output to the output unit. A step may be further provided.

  The step of creating the topographical map and displaying it on the display unit or outputting it to the output unit calculates color image data corresponding to the shade based on the topographic index T, and associates the color image data with the corresponding grid points. Thus, it is preferable to create a gradation feature map and display it on the display unit or output it to the output unit.

  Further, the step of creating the topographical map calculates color image data that corresponds to the hue based on the topographical index T, creates a multi-level topographical map by correlating the color image data to the corresponding grid points, and displays It is good to display to a part or to output to an output part.

Further, the means constituting the present invention according to claim 8 divides the ground surface by a plurality of meshes arranged along two-dimensional coordinates, and is a numerical map composed of elevation values at each lattice point of the mesh. From the data, a process of obtaining the elevation value k of each grid point, and a range composed of a plurality of grid points surrounding each grid point for each grid point is defined as a neighborhood range of the grid point, Based on the processing for obtaining the highest elevation value k _max and the lowest elevation value _kmin from the elevation values k of the plurality of grid points, and the obtained highest elevation value k _max , the lowest elevation value _kmin and the elevation value k, R = The process of calculating the relative elevation R for each grid point by the formula of (k−k _min ) / (k _max −k _min ), and the elevation values of a plurality of grid points surrounding the grid point for each grid point k to obtain these multiple elevation values k Next, based on the process of calculating the slope angle θ of the slope at the grid point and the elevation value k, specific elevation R and slope angle θ, T = log (k × R × tan θ) is used for each grid point. A process of calculating the feature index T, calculating color image data for each grid point based on the feature index T, creating a feature map by associating the color image data with the corresponding grid point, and displaying it on the display unit The function is to cause the computer to execute processing to be output to the display or output unit.

According to a ninth aspect of the present invention, there is provided a computer-readable storage medium storing the program according to the eighth aspect.

The means constituting the present invention according to claim 10 divides the ground surface with a plurality of meshes arranged along two-dimensional coordinates, and is a numerical map composed of elevation values at each lattice point of the mesh. A range composed of a plurality of grid points surrounding each grid point and means for obtaining the altitude value k of each grid point from the data is defined as a neighborhood range of the grid point, Based on the means for obtaining the highest elevation value k _max and the lowest elevation value _kmin from the elevation values k of the plurality of grid points, and based on the obtained highest elevation value k _max , the lowest elevation value _kmin and the elevation value k, R = Means for calculating the relative elevation R for each grid point by the equation of (k−k _min ) / (k _max −k _min ), and the altitude values of a plurality of grid points surrounding the grid point for each grid point k respectively, and the plurality of elevation values k Based on the altitude value k, the specific altitude R, and the inclination angle θ, T = log (k × R × tan θ) A means for calculating a feature index T, color image data is calculated for each grid point based on the feature index T, and a feature map is created by associating the color image data with the corresponding grid point. Means is provided with means for outputting to a display or output unit.

The present invention has the following effects by adopting the above-described configuration.
(1) Define a specific altitude value indicating where the ground surface is located between the erosion surface representing the terrain before erosion and the lower erosion surface, and create a map based on that value to represent the terrain This makes it possible to accurately grasp the fine undulations on the ground surface formed by erosion and the generation process and distribution of rivers formed by erosion.
(2) Since the terrain is expressed by logarithmically transformed values and a map is created based on the values, it is possible to greatly emphasize and express areas with low elevation and low undulations. It is possible to express in detail the low-lying areas, urban areas, hills, etc., which are difficult to do and have low undulations.
(3) By representing the topography as a product of logarithmic transformation of the product of elevation, tangent of slope, and specific elevation, locations with high elevation, steep slopes and higher ridges, lower elevations and gentle slopes Can be expressed in lower detail, so that the features of the terrain can be emphasized and expressed in detail.
(4) Since the map created based on the geological index can express the terrain three-dimensionally, it has better visibility than conventional maps, and terrain interpretation can be performed easily and accurately.
(5) By representing the map with a single color gradation display, it is possible to superimpose with other maps while representing the terrain three-dimensionally. Expression and data analysis can be easily performed.
(6) Maps created based on the geological index can represent flood damage areas, flood damage areas, volcanic disaster areas, earthquake disaster areas, etc. It can be applied to systems and the like.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 shows a schematic block diagram of an embodiment of a numerical map data processing apparatus. The numerical map data processing apparatus includes a control unit 1 that is a central processing unit (CPU) that performs various calculations and processes, and a first memory such as a ROM that stores programs read into the control unit 1, an operating system, and the like. A unit 2, a second storage unit 3 such as a RAM for storing information processed by the control unit 1 and information written from the control unit 1, and various information necessary for numerical map data processing such as settings and instructions An input unit 4 including a keyboard, mouse, touch panel, etc., a display unit 5 such as a display for displaying information output from the control unit 1, and printing out information output from the control unit 1 And an output unit 6 including a printer or the like. The first storage unit 2 stores a numerical map data processing program 100.

The second storage unit 3 stores numerical map data 50 to be processed by the numerical map data processing program 100. In this embodiment, the numerical map data 50 is a numerical map 50m issued by the Geographical Survey Institute. "Mesh" is used. The numerical map 50m mesh is a digital elevation model (measured by contour map drawn on the 15,000th topographic map published by the Geospatial Information Authority of Japan. DEM: Digital
Elevation Model). The altitude of each grid point formed by dividing the 15,000 scale topographic map into 200 equal parts in the longitude and latitude directions is converted into data, and the actual distance between the grid points is about 50 m × 50 m It is.

The numerical map data 50 is not limited to the “numerical map 50 m mesh” issued by the Geospatial Information Authority of Japan, but the “numerical map 25 m mesh” created by aerial photogrammetry, the numerical map 1 m mesh and SRTM ( Shuttle
A numerical map created by measuring the earth's topography with a radar mounted on the space shuttle by Radar Topography Mission) can be used regardless of the scale.

FIG. 2 shows a flowchart of numerical map data processing according to the first embodiment. First, the control unit 1 obtains the grid points E ₁ , E ₂ ,... From the numerical map data 50 stored in the second storage unit 3 by arranging the ground surface along X and Y coordinates orthogonal to each other. ... Elevation value k in E _n (hereinafter collectively referred to as E in some cases) is read (step 1).

Next, the control unit 1 calculates a specific elevation R for each grid point E based on the elevation value k of each grid point E acquired in step 1. When trying to calculate the ratio altitude R for lattice points E _1, as shown in FIG. 3, first, constituted by a plurality of grid points E surrounding grid points E ₁ as the center grid point the lattice points E ₁ The range is set as the neighborhood range NA ₁ of the grid point E ₁ , and the maximum elevation value k _max and the minimum elevation value _kmin are read from the elevation values k of all the grid points E existing in the neighborhood range NA ₁ , and the maximum elevation is obtained. The value k _max is set as the tangential elevation value k _max of the lattice point E ₁ located at the center of the neighborhood range NA ₁ , and the minimum elevation value _kmin is also set as the tangential elevation value _kmin of the lattice point E ₁ . Store in the storage unit 3 (step 2). In this embodiment, as shown in FIG. 3, the grid points are indicated by a total of 120 round dots of 11 rows in the X coordinate direction and 11 columns in the Y coordinate direction surrounding the grid point E ₁ as the center. and a neighborhood area NA ₁ ranges that. However, the neighborhood range is not limited to 120 grid points, and may be appropriately changed based on the size of the map.

Next, based on the read altitude value k, close peak altitude value k _max, and close valley altitude value _kmin , a value calculated by the following formula is used as a relative altitude R to correspond to each grid point E, and the second storage unit 3 (step 3). This process is performed along the grid point in the X coordinate direction, and when the grid point in the X coordinate direction is completed, the same process is performed along the Y coordinate direction, so that the neighborhood range is set for all the grid points E, and the ratio The elevation R can be calculated.

FIG. 4 is a side view showing the relationship between the close peak elevation value k _max , the close valley elevation value k _min , and the elevation value k in each adjacent neighborhood range. The adjacent neighborhood ranges are represented by NA ₁ , NA ₁₁ , NA ₂₁ , NA _31, and the central lattice points of each neighboring range are represented by long lines as E ₁ , E ₁₁ , E ₂₁ , and E ₃₁ , respectively. Further, the close peak elevation value k _max of each neighboring range is indicated by Δ, the close contact elevation value km _min is indicated by ×, the elevation value k is indicated by ○, and the lattice points are indicated by short lines L. As shown in FIG. 4, replacing the altitude tangent peak elevation values k _max the center grid point in a neighborhood range, Sehho surface plane created by connecting the respective contact peak elevation values k _max in the vicinity of the range adjacent , It can be considered that the ridge surface approximately represents the topography before erosion began. Similarly, replacing the Settani elevation values k _min of the near neighbor range elevation of the center grid point, defining a surface which is created by connecting the respective Settani elevation values k _min of the neighborhood area adjacent the Settani surface The tangent plane can be regarded as representing the lower limit plane of erosion. The specific elevation R calculated in step 3 indicates where the elevation value k of the central lattice point in the vicinity range is located between the erosion original surface representing the topography before erosion and the erosion lower limit surface. It can be said that it represents the terrain undulation characteristics in a wide range. Further, when the erosion degree is defined as erosion degree = 1−specific elevation R, the specific elevation R can be regarded as the erosion remaining degree.

Next, after calculating the relative elevation R for each lattice point E in step 3, the control unit 1 sets all the lattice points using the following formula, with the maximum value of the relative elevation R being 1 and the minimum value being 0. Color image data is calculated for E, and the color image data is stored in the second storage unit 3 in correspondence with each grid point (step 4).

Next, the control unit 1 reads the color image data corresponding to each grid point E from the second storage unit 3 and creates a map by corresponding the color image data by pasting the color image data to each grid point E or the like ( Step 5). The color image data corresponds to each color of the RGB color model. In this embodiment, the values of R and B are fixed at 0, and when the specific altitude R = 1, green = 255 and the color image data is green. When the specific elevation R = 0, the color image data becomes black when green = 0, and the terrain is represented as a green gradation specific elevation map in which the gradation changes from black to bright green as the relative elevation R increases. Represents.

The created gradation ratio elevation map is displayed on the display of the display unit 5 and / or simultaneously printed out by the printer of the output unit 6 or the like (step 6). FIG. 5 shows a gradation specific elevation map of the entire Kanto region created using this embodiment. In addition, when expressing the specific altitude as a map, it is not limited to gradation display, and the color is not limited to green, and can be expressed on the map using various expression methods and colors.

In the gradation ratio elevation map, rivers and lakes are close to the lower limit of erosion, so they are expressed in black or dark tones. On the other hand, plateaus are expressed in light tones because of low erosion. Furthermore, in the plateau, a slight difference in the degree of erosion is expressed as a fine terrain, thereby expressing a fine change in the undulation of the plateau. In this way, from the gradation ratio elevation map, it is possible to read the distribution status of rivers and plateaus, the pattern of structural regulation according to the live structure, and the like, so that the generation process and development status of the river can be grasped in detail.

FIG. 6 shows a flowchart of numerical map data processing according to the second embodiment of the present invention. In the present embodiment and other embodiments described later, the same components as those in the first embodiment are denoted by the same reference numerals, and the description thereof is omitted.

The control unit 1 calculates the slope angle θ of the slope of each grid point E based on the elevation value k of each grid point E acquired in step 1, and associates the slope angle θ with each grid point E to obtain the second angle. Store in the storage unit 3 (step 11). This process is also performed for all grid points E. As shown in FIG. 7, when the inclination angle θ is to be obtained for the lattice point E ₁ (the elevation value of the lattice point E ₁ is e), the inclination angle θ is set to the lattice point E ₁ in the X coordinate direction. , And can be calculated using the elevation values (b, h, d, f) of four lattice points E (near 4) adjacent in the Y coordinate direction. The formula to calculate is shown below.

W is the distance between lattice points. The inclination angle θ is not a elevation values 4 near elevation values of the eight grid points around 8 azimuth surrounding grid points E ₁ E (8 near) (a, b, c, d, f, g, Using h, i), the following equation can be used.

And the control part 1 is the following about all the grid points E based on the altitude value k of each grid point E, the specific altitude R, and inclination | tilt angle (theta) read or calculated by the process of said step 1 thru | or step 3 and step 11, respectively. The value calculated using the equation is stored in the second storage unit 3 as a feature index T in correspondence with each grid point E (step 12).

Next, the control unit 1 calculates color image data for all grid points E using the following formula, with the maximum value of the landscape index T being 5 and the minimum value being −2, and the color image data is calculated for each grid point. Store in the second storage unit 3 in correspondence with the point E (step 13). The color image data corresponds to each color of the RGB color model. When the feature index T = 5, the color image data is black when gray = 0, and when T = −2, the color image data is gray = 255. Becomes white, and gradation changes from white to gray and black as the geological index T increases.

Next, the control unit 1 reads the color image data corresponding to each grid point E from the second storage unit 3 and creates a map by corresponding the color image data by pasting the color image data to each grid point E or the like ( Step 14). As a result, terrain with a low terrain index T is displayed in white, terrain with a high terrestrial index T is displayed in black, and gray-colored gradation terrain that changes from white to gray and black as the terrain index T increases. A diagram can be created. Then, the created gradation map is displayed on the display of the display unit 5 and / or simultaneously printed out by the printer of the output unit 6 or the like (step 15). FIG. 8 shows a gradation feature map of the entire Kanto region created using this embodiment.

In the conventional representation method, the terrain is usually expressed by a single element such as the altitude and the inclination angle. However, the topographic index T calculated by the above-described processing is the altitude of the grid points which are three elements regarding the terrain. Since the product of the value k, the tangent of the inclination angle θ, and the specific elevation R is logarithmically converted, the elevation is high, the slope is steep, and the value close to the ridge is larger, the elevation is low, and the slope is It is gentle and has a lower value at a point close to the valley, and can be said to be a value representing a pseudo elevation that emphasizes the features of the terrain. Further, the product of these three elements can be regarded as a value that emphasizes the degree of resistance to erosion. Furthermore, since the geological index T is a logarithmically transformed product of the above three elements, the product of the elevation value k, the tangent of the inclination angle θ, and the relative elevation R is small, the elevation is low, and the slope is gentle. The shape of the low land is large and expressed in detail, and the slight undulations of the low ground can be accurately grasped.

In place of or simultaneously with the display and output of the gradation feature map, the feature index T calculated for each grid point E is displayed as numerical data on the display of the display unit 5 or printed out by a printer of the output unit 6 or the like. May be output. The appearance index T displayed and output as numerical data is not a single element but a numerical representation of the topography using three elements, so various numerical analyzes such as statistical analysis, and the appearance index T are simulated. It can be used for various purposes such as topographic numerical analysis by considering it as altitude value, complexity analysis such as gray system and fuzzy system analysis and simulation, etc. It is considered useful for disaster prevention planning, regional planning, etc.

FIG. 9 shows a flowchart of numerical map data processing according to the third embodiment of the present invention. The controller 1 calculates the inclination angle θ for each grid point E in step 11, calculates the feature index T for each grid point E in step 12, and then sets the maximum value of the feature index T to 4.0 and the minimum value. Color image data is calculated for each feature index T according to an RGB value file in which the feature index T and RGB values are associated with each other at 0.2 intervals between 0 and 4.0 as 0 (step 21). As shown in FIG. 10, the RGB value file corresponds to the feature index T and the RGB value, and is stored in the first storage unit 2. Then, the color image data is made to correspond by pasting the color image data to each grid point E or the like, thereby creating a stepped-color feature map (step 22). In the present embodiment, the region having the largest feature index T is the brown color, the region having the next largest feature index is the green color, the region having the smallest feature index T is the light blue color, and the feature index. Areas where T is small are expressed in gray color, and areas where surface index T is 0 are expressed in white.

Then, the created stage-saturated map is displayed on the display of the display unit 5 and / or simultaneously printed out by the printer of the output unit 6 or the like (step 23). It is also possible to display and output the color chart in a format corresponding to the geological index at the same time when displaying and outputting the stepped-color feature map. Further, as in the second embodiment, the feature index T may be displayed and output as numerical data instead of or simultaneously with the display and output of the tiered feature map. FIG. 11 shows a dansai map of the Kanto region created using this embodiment.

FIGS. 12, 13, and 14 show a shadow map, an elevation map, and a slope distribution map of the entire Kanto region, respectively, created by a conventional expression method. These three maps are also created using “Numerical Map 50m Mesh” published by the Geospatial Information Authority of Japan, as well as gradation terrain maps and dansai terrain maps. Then, the map created by the conventional expression method is compared with the gradation feature map shown in FIG. 8 and the tiered feature map shown in FIG.

First, in the shade map of FIG. 12, the mountainous areas with high altitudes such as Mount Tsukuba, Yachizo Mountains located on the northeast side 12A, Ashio Mountains located on the northwest side 12B, and Chichibu Mountains located on the west side 12C are undulated. It is expressed in three dimensions. However, the area 12D sandwiched between the Yamizo and Ashio Mountains, the area 12E sandwiched between the Ashio and Chichibu Mountains, plain areas with little elevation in Tokyo and Saitama Prefecture, and urban areas are mostly dark. Therefore, it is difficult to say that the features of the terrain are difficult to understand. Next, the altitude stage chroma chart of FIG. 13 is densely expressed in high altitude mountainous areas such as the Ashio Mountains located on the northwest side 13A, but the other region 13B sandwiched between the Yachimi Mountains and the Ashio Mountains, The mid-altitude area such as 13C between the Ashio Mountains and the Chichibu Mountains, the plains and urban areas around Tokyo where changes in elevation are scarce, and the terrain cannot be expressed in detail. Furthermore, since the map has no three-dimensional effect and it is difficult to discriminate between high and low elevations, it is difficult to visually grasp the features of the topography. And the slope distribution map of FIG. 14 has less topographic relief such as Tokyo, Saitama Prefecture, the area 14A sandwiched between the Yachimi Mountains and the Ashio Mountains, and the area 14B sandwiched between the Ashio Mountains and the Chichibu Mountains. Areas with few slopes are hardly expressed. Moreover, since the same inclination value becomes the same expression, when the inclination is the same in the ridge and the valley, the expression is the same, and the visual expression is poor.

On the other hand, the gradation topographic map shown in FIG. 8 emphasizes the features of the terrain by expressing the terrain with the product of three elements of the elevation value k, the inclination angle θ, and the relative elevation R, and further logarithmically converts it. This is a map created based on the geological index. Therefore, the high altitude and steep mountainous area are all expressed in detail, and further, the area 8A sandwiched between Mt. Tsukuba, Hachizo Mountains and Ashio Mountains, the area 8B sandwiched between Ashio Mountains and Chichibu Mountains, Tokyo In addition, the terrain that was difficult to express in the shading maps of plains and cities, etc. with low elevations and low elevations around Saitama Prefecture is also clearly expressed in detail, but there are few undulations and their series It is possible to accurately grasp the direction of the terrain uplift. The distribution of alluvial lowlands, the shape of the topography, and the river topography are also expressed in detail. In addition, the linear structure of the topography including the valley line and ridge line is also expressed in detail. Further, since the three-dimensional representation is performed as compared with the conventional representation method, the characteristics of the terrain can be visually grasped.

As with the gradation topographical map, the terrain topographical map shown in FIG. 11 is not only high in altitude, but has a steep slope, as well as the 11A region between the Tsukuba, Yachizo Mountains and the Ashio Mountains, the Ashio Mountains and the Chichibu Mountains. Areas 11B, Tokyo, and Saitama Prefecture are surrounded by plains and urban areas with low elevation and low undulation. In general, mountain areas with high altitudes have a visually green image due to overgrown trees, and ridges and peaks with high altitudes and steep slopes have a visually brown image due to the color of the exposed mountain surface. In addition, urban areas and plains with low altitude, gentle slopes and little unevenness, have visually white and gray images depending on roads and buildings. Therefore, the region with the highest feature index T is expressed in brown color, the region with the second highest feature index is expressed in green color, and the region with the smallest feature index T is expressed in white and gray color. Thus, while maintaining the feature of the terrain expression by the terrain index T, the terrain can be expressed in a more visually superior state by adding a natural sense to it.

In this way, the map created based on the geological index T is a distinction between high and low mountains that were difficult with the conventional terrain expression method, the distribution of plains, hills, alluvial areas, etc. in low altitude areas and rivers. Therefore, it is possible to accurately and visually grasp the characteristics of the entire terrain including not only high altitude areas but also low altitude areas. Therefore, it is also effective for the analysis of urban areas where most of them are located on low ground. In addition, compared to conventional maps, the terrain can be expressed more three-dimensionally, so it can be said that the map is excellent in expressive power that makes it easy to visually grasp the terrain.

  Maps created based on the geological index T, especially gray gradation topographical maps, can be overlaid with other maps while representing the topography three-dimensionally compared to conventional maps. Multifaceted and complex expressions can be performed. FIG. 15 shows a map in which a gray gradation topographic map and an inclination distribution map of the Daisetsuzan system in Hokkaido are superimposed. By superimposing the gradient topographic map and the slope distribution map, it is possible to clearly express the topography of mountain areas with high elevations, especially the change in slope, and if the maps of the volcanic area are overlaid, the lava flow It is possible to accurately grasp the situation and the distribution of pyroclastic flow. Note that the overlaying of maps is not limited to topographic maps and slope distribution maps, but can be applied to other maps such as shadow maps and 15,000th map information from the Geospatial Information Authority of Japan. Superposition with photographs, satellite images, etc. is also possible, thereby obtaining a new terrain expression.

  FIG. 16 is a diagram in which a gradation topographic map and a flood damage map of the Hokkaido Ishikari side basin are superimposed. Inundated by flooded water is distributed like low spots in low-altitude areas. As can be seen from FIG. 16, the flooded area coincides with the low area represented by the gradation topographic map, and in particular, most coincides in the downstream area. Therefore, it is also possible to express flooded areas due to floods such as floods and tsunamis by using topographic maps. Therefore, it can be applied to hazard maps for disaster countermeasures such as flood inundation risk area maps and inundation expected area maps. It is also possible to forecast flooding of rivers and flooded areas due to flooding.

It is a block diagram of a numerical map data processing device. It is a flowchart which shows the procedure which calculates a specific elevation from numerical map data, and produces a specific elevation map. It is explanatory drawing of the vicinity range in calculation of a specific altitude. It is explanatory drawing of a ridge face and a tang face. It is a gradation specific elevation map. FIGS. 6 to 8 relate to the second embodiment of the present invention, and FIG. 6 is a flowchart showing a procedure for calculating a feature index from numerical map data and creating a gradation feature map. It is explanatory drawing of the lattice point used for calculation of the inclination-angle of each lattice point. It is a gradation feature map of the whole Kanto region. FIGS. 9 to 11 relate to the third embodiment of the present invention, and FIG. 9 is a flowchart showing a procedure for calculating a feature index from numerical map data and creating a multi-level feature map. It is an RGB value table | surface which shows a geological index and the RGB value corresponding to it. It is a terrain map of the Kanto region. It is a shade map of the Kanto region. This is an elevation map of the Kanto region. It is a slope distribution map of the Kanto region. It is the figure which overlaid the gradation topographic map and slope distribution map of the Daisetsuzan system of Hokkaido. It is the figure which superimposed the gradation topographical map and flood damage figure of Hokkaido Ishikari side basin.

Explanation of symbols

5 Display unit 6 Output unit 50 Digital map data 100 Digital map data processing program E Grid point k Elevation value NA Neighborhood range R Specific elevation T Terrain index θ Inclination angle

Claims (10)

Partitioning the ground surface with a plurality of meshes arranged along two-dimensional coordinates, and obtaining the altitude value k of each grid point from the numerical map data constituted by the altitude values at each grid point of the mesh; , A range composed of a plurality of grid points surrounding each grid point for each grid point is set as a neighborhood range of the grid point, and the highest elevation value k is selected from the elevation values k of the plurality of grid points in the neighborhood range. R = (k−k _min ) / (k _max −k _min ) based on the step of acquiring _max and the minimum altitude value _kmin , and the acquired maximum altitude value k _max , the minimum altitude value _kmin and the altitude value k A numerical map data processing method comprising a step of calculating a relative elevation R for each grid point by an equation.   Obtaining elevation values k of a plurality of grid points surrounding the grid points for each grid point, calculating an inclination angle θ of the slope at the grid points based on the plurality of elevation values k, and elevation values 2. The method according to claim 1, further comprising a step of calculating a geological index T for each grid point based on k, a specific elevation R, and an inclination angle θ by an equation of T = log (k × R × tan θ). Numerical map data processing method.   Calculating color image data for each grid point based on the relative elevation R, creating a specific elevation map by associating the color image data with the corresponding grid points, and outputting the map to the display unit or outputting to the output unit The numerical map data processing method according to claim 1, further comprising:   The step of creating the specific elevation map and displaying it on the display unit or outputting it to the output unit calculates color image data corresponding to the shade based on the specific elevation R, and associates the color image data with the corresponding grid points. 4. The numerical map data processing method according to claim 3, wherein a gradation ratio elevation map is created by the step and displayed on the display unit or output to the output unit.   Calculating color image data for each grid point based on the topographic index T, creating a topographical map by associating the color image data with the corresponding grid point, and outputting to the display unit or outputting to the output unit; The numerical map data processing method according to claim 2, further comprising:   The step of creating the topographic map and displaying it on the display unit or outputting it to the output unit calculates color image data that corresponds to the shade based on the topographic index T, and associates the color image data with the corresponding grid points. 6. The numerical map data processing method according to claim 5, wherein a gradation feature map is created and displayed on the display unit or output to the output unit.   The step of creating the topographical map calculates color image data that corresponds to the hue based on the topographical index T, creates a stepped-colored topographical map by correlating the color image data to the corresponding grid points, and displays it on the display unit. 6. The numerical map data processing method according to claim 5, wherein the numerical map data is output to a display or output unit. Processing of dividing the ground surface with a plurality of meshes arranged along two-dimensional coordinates, and obtaining the elevation value k of each grid point from the numerical map data composed of the elevation values at each grid point of the mesh; , A range composed of a plurality of grid points surrounding each grid point for each grid point is set as a neighborhood range of the grid point, and the highest elevation value k is selected from the elevation values k of the plurality of grid points in the neighborhood range. R = (k−k _min ) / (k _max −k _min ) based on the process of acquiring _max and the minimum altitude value _kmin and the acquired maximum altitude value k _max , the minimum altitude value _kmin and the altitude value k The process of calculating the relative elevation R for each grid point by the equation, and the elevation values k of a plurality of grid points surrounding the grid point for each grid point are obtained, and based on the plurality of elevation values k, Calculate slope angle θ of slope at grid point A process, a process of calculating a feature index T for each grid point based on the elevation value k, the specific elevation R, and the inclination angle θ, by the formula T = log (k × R × tan θ), and the feature index T Based on the above, color image data is calculated for each grid point, a topographic map is created by associating the color image data with the corresponding grid point, and the computer executes a process of displaying on the display unit or outputting to the output unit Numerical map data processing program characterized by functioning as possible. A computer-readable storage medium on which the program according to claim 8 is recorded. Means for dividing the ground surface with a plurality of meshes arranged along two-dimensional coordinates, and obtaining the elevation value k of each grid point from the numerical map data constituted by the elevation values at each grid point of the mesh; , A range composed of a plurality of grid points surrounding each grid point for each grid point is set as a neighborhood range of the grid point, and the highest elevation value k is selected from the elevation values k of the plurality of grid points in the neighborhood range. R = (k−k _min ) / (k _max −k _min ) based on the means for acquiring _max and the minimum altitude value _kmin , and the acquired maximum altitude value _kmax , the minimum altitude value _kmin and the altitude value k According to the formula, the means for calculating the relative elevation R for each grid point, and the elevation values k of a plurality of grid points surrounding the grid point for each grid point are obtained, and based on the plurality of elevation values k, Calculate slope angle θ of slope at grid point Means, a means for calculating a feature index T for each lattice point according to an equation of T = log (k × R × tan θ) based on the elevation value k, the specific elevation R, and the inclination angle θ; A color image data is calculated for each grid point on the basis of the above, and a feature map is created by associating the color image data with the corresponding grid point, and is displayed on the display unit or output to the output unit. Numerical map data processing device.

Images