JP2013054660A - Vegetation map creation device and vegetation map creation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a vegetation map creation device and a vegetation map creation program for creating a vegetation map useful for a tree kind segment investigation of a forest, etc. using only aerial laser surveying data, without using an orthophoto image.SOLUTION: In a vegetation map creation device, an input section 11 takes in DEM data 21, DSM data 22 and reflection intensity data 23. A DHM data creation section 12 and an on-ground opening calculation section 13 create DHM data 24 and DHM on-ground opening data 25. A reflection intensity graduated coloring section 14, a tree height graduated coloring section 15, and an on-ground opening graduated coloring section 16 create reflection intensity image data 31, tree height image data 32, and tree crown solid image data 33 using a reflection intensity color table 26, a tree height color table 27, and an on-ground opening color table 28, respectively. A map composition section 17 creates an image from each image data and displays a composite vegetation map 34 on a terminal 19.

Description

  The present invention relates to a technical field of analyzing land cover status using data obtained by remote sensing. More specifically, the present invention relates to a vegetation map creation apparatus and a vegetation map creation program for creating a vegetation map that can be used for forest tree species classification survey and the like by using only aerial laser survey data without using an orthophoto image.

  Advanced remote sensing technology has been developed to acquire data used for topographic interpretation and land cover classification in mapping and scientific surveys.

  Of the data obtained by remote sensing, the orthophoto image is a planar color photographic image obtained by geometrically transforming a surface photograph taken with an aircraft into an orthographic projection map, and visually shows trees, buildings, roads, ground, grassland, etc. Easily decipherable. Furthermore, since orthophoto images are actual local images, they have a high visual appeal and have been used in various systems in recent years.

  On the other hand, there is aviation laser survey data as other data obtained by remote sensing. An example is distance data to the ground measured by a time difference from a reflected wave from the ground by irradiating laser light from the laser distance measurement mounted on the aircraft toward the ground.

  Further, as disclosed in Patent Document 1, it has become possible to measure the reflection intensity of reflected waves from the ground as aviation laser survey data at the same time as measuring distance data.

  In Non-Patent Document 1, “In recent years, an on-board laser scanner that directly measures the three-dimensional coordinates of ground points (points on the surface of the ground, buildings, trees, etc.) has been put into practical use, and the laser beam used for ranging ( A device that can measure the reflection intensity of near-infrared rays has also appeared, which is the intensity of the first reflected pulse with respect to the emitted pulsed light, not only the reflectance of the near-infrared light but also the state of the surface of the object ( This is a new type of data that also reflects (roughness and transmittance) (for example, the reflection intensity of plants with high near-infrared light reflectance is not necessarily strong) and is not affected by the shade because it is an active sensor. Therefore, it is expected to be used. "

  In Patent Document 1, since the wavelength of the laser beam to be irradiated is in the near infrared region, the reflection intensity is related to the activity of the plant, and it is known that the hardwood has a higher reflectance than the conifer. Then, it is disclosed that a tree species can be discriminated and a pseudo image of vegetation information can be created.

  Furthermore, in Patent Document 2, the analysis using the reflection intensity is an analysis using a black and white image. In order to solve the problem that the researcher feels uncomfortable and difficult to understand, the reflection intensity data is usually In view of the RGB information, applying the point that the reflection intensity information corresponds to the RGB B wavelength band, and combining the reflection intensity wavelength band information with the B wavelength band in the normal RGB information, pseudo near red A method for creating external data is disclosed.

Japanese Patent No. 3515678 Japanese Patent No. 4521858

“Research on the possibility of acquiring geographic information using the reflection intensity of laser light” Ministry of Land, Infrastructure, Transport and Tourism Geographical Survey Institute website [searched on August 5, 2011], Internet <URL: http: // www. gsi. go. jp / REPORT / HYOKA / 14-1-hyoka14-1-4. html>

  Orthophoto images have excellent visual effects, but have the following drawbacks.

  (1) Since orthophoto images are taken from above, shadows are generated due to topography and features, so there are places that cannot be seen.

  (2) Since orthophoto images are a plurality of images taken in order within a certain area within the target area, when joining adjacent images, the joints may be displaced or invisible places may occur. . In addition, since the image is captured while conditions such as brightness at the time of capturing each image change from time to time, there is a difference in color tone between the images, and an error may occur in analysis by color.

  (3) In the orthophoto image, depending on the shooting direction with respect to the feature, a position shift or an invisible place occurs due to the fall of the feature.

  (4) Since an orthophoto image is a planar color photograph, when a river or valley in a mountainous area is covered with trees, the river or valley cannot be easily determined. Also, the mountain ridge cannot be easily determined to be a ridge if most of the trees growing on the ridge are of a similar color (for example, green). That is, a planar color photographic image lacks a stereoscopic effect and cannot easily grasp the surface layer.

  On the other hand, if color information is not added to the aviation laser survey data by any method, the created image is a black and white image like the image published in Non-Patent Document 1, and the visual analysis efficiency is poor.

  The present invention has been made to solve the above-described problems. A vegetation map that can grasp the distribution of trees at a glance only from aerial laser survey data without using an orthophoto image having the above-described drawbacks. An object is to obtain a vegetation drawing creation device and a vegetation drawing creation program.

  The vegetation map creation apparatus of the present invention is a vegetation map creation apparatus that creates a vegetation map using only aerial laser survey data in which a grid with a desired interval is set in the entire measurement area.

DEM data consisting of XY coordinate values and ground elevation values of the grid generated from aerial laser survey data, DSM data consisting of XY coordinate values and surface elevation values, and reflection intensity data consisting of XY coordinate values and reflection intensity values, An input unit that captures data from an external storage medium into storage means;
The ground elevation value and surface elevation value related to the same XY coordinate value are read from the DEM data and DSM data stored in the storage means, and the tree elevation value obtained by subtracting the ground elevation value from the surface elevation value is stored as DHM data together with the XY coordinate value. A DHM data creation unit stored in the means;
Arbitrary grids of DHM data are set as sample grids, and the maximum tilt angles are obtained from the distances between the grids from the sample grids to the target grids within the search range and the tree height difference in each direction, and the maximum tilt angles are averaged. The above-mentioned ground opening value is stored in the storage means as DHM ground opening data together with the XY coordinate value of the sample grid,
The reflection intensity value is read from the reflection intensity data stored in the storage means, the reflection intensity color table stored in advance in the storage means is searched by the reflection intensity value, and the first set for the reflection intensity value is obtained. A reflection intensity stage portion that obtains a display color component and stores it in the storage means as reflection intensity image data together with XY coordinate values;
The tree height value is read from the DHM data, the tree height color table stored in the storage means in advance is searched with the tree height value, the second display color component set for the tree height value is acquired, and the XY coordinate value is obtained. Along with the tree height image data to be stored in the storage means as tree height image data,
The ground opening value is read from the DHM ground opening data, the ground opening color table stored in the storage means in advance is searched with the ground opening value, and the third value set for the ground opening value is set. Obtaining a display color component and storing it in a storage means as a crown three-dimensional image data together with XY coordinate values;
The gist of the present invention is to include a map composition unit that generates an image from each image data stored in the storage unit and superimposes and displays the image as a vegetation map on the terminal.

Furthermore, the vegetation map creating apparatus of the present invention is
The reflection intensity value is read from the reflection intensity data stored in the storage means, the reflection intensity value conversion table stored in advance in the storage means is searched with the reflection intensity value, and the a * component set for the reflection intensity value Converted to a value,
Read the tree height value from the DHM data, search the tree height value conversion table stored in the storage means in advance, and convert it to the b * component value set for the tree height value,
L * component set for the ground opening value by reading the ground opening value from the DHM ground opening data, searching the ground opening value conversion table previously stored in the storage means, and searching for the ground opening value. Converted to a value,
The gist of the present invention is to include a Lab color stage portion that stores the a * component value, b * component value, and L * component value together with the XY coordinate values in the storage means as Lab color vegetation image data.

  The vegetation map creation program of the present invention is a vegetation map creation program that creates a vegetation map using only aerial laser survey data in which a grid with a desired interval is set in the entire measurement area.

On the computer,
DEM data consisting of XY coordinate values and ground elevation values of the grid generated from aerial laser survey data, DSM data consisting of XY coordinate values and surface elevation values, and reflection intensity data consisting of XY coordinate values and reflection intensity values, Input means for loading from an external storage medium into the storage means;
The ground elevation value and surface elevation value related to the same XY coordinate value are read from the DEM data and DSM data stored in the storage means, and the tree elevation value obtained by subtracting the ground elevation value from the surface elevation value is stored as DHM data together with the XY coordinate value. Means for creating DHM data to be stored in the means;
Arbitrary grids of DHM data are set as sample grids, and the maximum tilt angles are obtained from the distances between the grids from the sample grids to the target grids within the search range and the tree height difference in each direction, and the maximum tilt angles are averaged. A ground opening calculation means for storing the above-mentioned ground opening value in the storage means as DHM ground opening data together with the XY coordinate value of the sample grid,
The reflection intensity value is read from the reflection intensity data stored in the storage means, the reflection intensity color table stored in advance in the storage means is searched by the reflection intensity value, and the first set for the reflection intensity value is obtained. A reflection intensity gradation unit that obtains a display color component and stores it in a storage unit as reflection intensity image data together with XY coordinate values;
The tree height value is read from the DHM data, the tree height color table stored in the storage means in advance is searched with the tree height value, the second display color component set for the tree height value is acquired, and the XY coordinate value is obtained. Along with the tree height image data to be stored in the storage means as tree height image data,
The ground opening value is read from the DHM ground opening data, the ground opening color table stored in the storage means in advance is searched with the ground opening value, and the third value set for the ground opening value is set. A ground opening stage stage coloring means for acquiring a display color component and storing it in a storage means as a canopy stereoscopic image data together with XY coordinate values;
The gist of the present invention is to generate an image from each image data stored in the storage means and execute a function as a map synthesis means for superimposing and displaying the image as a vegetation map on the terminal.

Furthermore, the vegetation map creation program of the present invention is a vegetation map creation program that creates a vegetation map using only aerial laser survey data in which a grid with a desired interval is set in the entire measurement area. The computer reads the reflection intensity value from the reflection intensity data stored in the storage means, searches the reflection intensity value conversion table stored in advance in the storage means, and sets the reflection intensity value. a * component value,
Read the tree height value from the DHM data, search the tree height value conversion table stored in the storage means in advance, and convert it to the b * component value set for the tree height value,
L * component set for the ground opening value by reading the ground opening value from the DHM ground opening data, searching the ground opening value conversion table previously stored in the storage means, and searching for the ground opening value. Converted to a value,
The gist of the present invention is to further execute a function as a Lab color gradation unit that stores the a * component value, the b * component value, and the L * component value together with the XY coordinate values as Lab color vegetation image data in the storage unit.

  In the present invention, since an orthophoto image having the above-mentioned drawbacks is not used, a clear vegetation map can be created without causing the influence of shadows, displacement of joints, difference in color tone between areas, and collapse of features. Can do.

  Furthermore, it is possible to read vegetation color tone, crown shape, and tree height information at a glance by creating a three-dimensional vegetation map that can be stepped based on aerial laser survey data and grasp the distribution of trees.

  In addition, the vegetation map can be mechanically drawn by color-coding the vegetation area according to the tree type, and the visual interpretation of the forest facies using conventional orthophoto images can be performed efficiently and more accurately. be able to.

Configuration diagram of first vegetation map creating apparatus according to Embodiment 1 (A) DEM data configuration diagram, (b) DSM data configuration diagram, (c) reflection intensity data configuration diagram (A) DHM data configuration diagram, (b) DHM ground opening data configuration diagram (A) Reflection intensity color table configuration diagram, (b) Tree height color table configuration diagram, (c) Ground opening color table configuration diagram Image data configuration diagram DHM data creation unit flowchart Ground opening calculation unit flowchart (A) Explanatory diagram of grid position on XY plane, (b) Explanatory diagram of lattice position in XYZ space Reflection intensity stage flowchart Map composition flowchart Composite image adjustment unit flowchart (A) reflection intensity image, (b) tree height image, (c) canopy stereo image, (d) composite vegetation map of 3 images, (e) orthophoto image (A) Lab color color space conceptual diagram, (b) Lab color color space definition of the present invention Configuration diagram of second vegetation map creating apparatus of embodiment 2 (A) Reflection intensity value conversion table configuration diagram, (b) Tree height value conversion table configuration diagram, (c) Ground opening value conversion table configuration diagram Lab color vegetation image data configuration diagram Lab color stage flowchart (part 1) Lab color stage flowchart (part 2) (A) Lab color vegetation image, (b) Mizunara image, (c) Sawagurumi image (A) Lab color vegetation map, (b) Forest fauna map

  An object of the present invention is to provide an apparatus for creating a three-dimensional vegetation map in which the distribution of trees can be grasped only from aerial laser survey data 20 without using an orthophoto image as illustrated in FIG. .

  Therefore, tree height obtained from the aviation laser survey data 20, that is, tree height, crown shape, and leaf composition were selected as indices for identifying the tree species.

  Depending on the type of tree, the height of the tree differs depending on whether it is a shrub or a tree, and the crown shape varies depending on how the branches and leaves grow. Furthermore, the shape and color of the leaves differ depending on the tree species.

  Therefore, these characteristics are digitized from the aviation laser survey data 20 and represented on a map, and by superimposing them, a vegetation map that can identify the tree species can be created.

  First, input data used in the present invention is defined with reference to the data structure shown in FIG.

  Aviation laser survey data 20 is the distance to the ground determined from the time difference from the laser reflected pulse from the ground by irradiating the laser from the laser rangefinder mounted on the aircraft to the ground using the aircraft laser survey system. This is data obtained by measuring the intensity of the laser reflected pulse together with the position of the measurement point.

  Digital elevation model data (hereinafter referred to as DEM data 21) is a aviation laser survey that sets a grid structure with a desired grid spacing d (for example, 0.2 m or 0.5 m) in the entire measurement area. Among the data 20, filtering is performed to remove buildings and trees other than the ground surface from the elevation data measured by the last returned pulse (last pulse) of the laser reflected pulses, and the elevation interpolation method is used. Is the grid-like elevation data of the ground obtained by the above, and as shown in FIG. 2 (a), the center of each grid given the grid number i (i = 1, 2,..., N). It is composed of the X coordinate (longitude Xi), Y coordinate (latitude Yi), and Z coordinate (ground elevation value Zgi) of the point.

  As an example of elevation interpolation method, create a contour map connecting the same elevation values of the aviation laser survey data 20, create an irregular triangle network (TIN) for this contour map, restore the ground, There is a method for obtaining the height of the intersection of TIN and each grid.

  The digital surface model data (hereinafter referred to as DSM data 22) is a building measured by the first reflected pulse (first pulse) of the laser reflected pulse in the aerial laser survey data 20 Is the altitude data of the surface layer including trees and trees, etc., and the center point of each grid given the grid number i of the same grid structure as the DEM data set for the entire measurement area as illustrated in FIG. X coordinate (longitude Xi), Y coordinate (latitude Yi), and Z coordinate (surface elevation value Zsi).

  The reflection intensity data 23 is obtained by measuring the intensity of the laser reflected pulse with respect to the irradiated laser pulse. As illustrated in FIG. 2C, the data structure is the same as the DEM data set for the entire measurement area. The X coordinate (longitude Xi), the Y coordinate (latitude Yi), and the reflection intensity value Fi of the center point of each lattice assigned with the lattice number i.

  From the DEM data 21, DSM data 22, and reflection intensity data 23 described above, the XY coordinate value, ground elevation value Zgi, surface elevation value Zsi, and reflection intensity value Fi of each grid in the entire measurement area can be obtained.

  How to digitize an index for identifying a tree species from the obtained data and create a vegetation map from the digitized index will be described below with reference to specific examples.

  Note that the grid is a section whose length of one side is the grid interval d, but in the following description, the various values of the grid are the coordinate values of the center point of the grid set as the grid data and various values. Value shall be indicated.

<Embodiment 1>
As shown in FIG. 1, in the first vegetation map creating apparatus 10 according to the first embodiment of the present invention, as a data processing unit, an input unit 11, a DHM data creating unit 12, a ground opening calculation unit 13, , A reflection intensity stage color part 14, a tree height stage color part 15, a ground opening degree stage color part 16, a map composition part 17, and a composite image adjustment part 18 are included.

  Further, the storage means (not shown) of the first vegetation map creating apparatus 10 includes DEM data 21, DSM data 22, reflection intensity data 23, and digital height model data (hereinafter referred to as DHM). Data 24), DHM ground opening data 25, reflection intensity color table 26, tree height color table 27, ground opening color table 28, and image selection table 29 are stored.

  Further, the storage means of the first vegetation map creating apparatus 10 stores reflection intensity image data 31, tree height image data 32, and canopy stereoscopic image data 33 generated for displaying the vegetation map 34 on the terminal 19. Is done.

  The input unit 11 receives the DEM data 21, DSM data 22, and reflection intensity data 23, which are input data obtained from the aviation laser survey data 20 whose definition is described above, from the external storage medium, in the first vegetation map creating apparatus 10. A process of taking in the storage means is performed.

  The input unit 11 may be means for reading data from an external storage medium such as a CD-ROM or a USB memory, or may be stored in an external device connected to the first vegetation map creating apparatus 10 via a communication network. It may be a means for downloading from a medium via a communication network.

  The DHM data creation unit 12 reads the ground elevation value Zgi and the surface elevation value Zsi of each grid from the DEM data 21 and the DSM data 22 stored in the storage means by the input unit 11, and the ground elevation value from the surface elevation value Zsi. As illustrated in FIG. 3A, the altitude value obtained by subtracting Zgi is stored in the storage unit as the DHM data 24 together with the XY coordinate values of each lattice.

  In the present invention, since trees are targeted, the altitude value obtained by subtracting the ground elevation value Zgi from the surface elevation value Zsi becomes the tree height value Zhi of each tree, and the DHM data 24 is also called tree height data.

  The ground opening calculation unit 13 calculates the ground opening value θi of each grid from the DHM data 24 stored in the storage unit by the DHM data creation unit 12, and as illustrated in FIG. Are stored in the storage means as DHM ground opening data 25.

  Here, the opening is one of the methods for extracting the terrain feature line. It is used to express the terrain three-dimensionally by quantifying the extent to which a certain point protrudes from the ground and the extent of biting underground. Is done.

  There are two types of opening: ground opening and underground opening. The ground opening is a numerical value of how wide the sky looks when viewed from a certain point, and the underground opening is how much the underground space is expanded when viewed from a certain point. Is a numerical value.

  In the present invention, the ground opening is used as an index indicating the inclination of the crown of each tree. For example, a tree species such as a conifer with little spread to the side of the branch has a steep crown and a small opening on the ground. On the other hand, a tree species such as a broad-leaved tree that spreads its branches sideways has a gentle inclination of the crown and a large ground opening.

  Details of the ground opening calculation will be described later.

  The reflection intensity stage 14 reads the reflection intensity value Fi of each grating from the reflection intensity data 23 stored in the storage means by the input section 11, and stores the reflection intensity color table 26 (FIG. According to the correspondence between the reflection intensity value Fi and the display color component Ci set in a)), the gradation of each grid is performed, and the reflection intensity image data 31 of the measurement area is generated and stored in the storage means.

  The tree height stage chromatic part 15 reads the tree height value Zhi of each lattice from the DHM data 24 stored in the storage means by the DHM data creation part 12, and stores the tree height color table 27 (FIG. 4B) previously stored in the storage means. In accordance with the correspondence relationship between the tree height value Zhi and the display color component Ci set in the reference), the gradation of each grid is performed, and the tree height image data 32 of the measurement area is generated and stored in the storage means.

  The ground opening stage saturation unit 16 reads the ground opening value θi of each grid from the DHM ground opening data 25 stored in the storage unit by the ground opening calculation unit 13 and stores the ground opening previously stored in the storage unit. In accordance with the correspondence between the ground opening value θi and the display color component Ci set in the color table 28 (see FIG. 4C), each grid is staged to generate the crown three-dimensional image data 33 of the measurement area. And stored in the storage means.

  The reflection intensity image data 31, the tree height image data 32, and the canopy stereoscopic image data 33 stored in the storage unit are configured by XY coordinate values and display color components Ci of the respective grids as illustrated in FIG.

  The data of the display color component Ci is data defined in each color table and may be three elements such as RGB values or one element only of gray scale values.

  The map synthesizing unit 17 calculates each grid from the reflection intensity image data 31, tree height image data 32, and tree crown three-dimensional image data 33 stored in the storage means by the reflection intensity gradation unit 14, the tree height gradation unit 15, and the ground opening degree gradation unit 16, respectively. The XY coordinate value and the display color component Ci are read out, and each image is generated and displayed superimposed on the terminal 19 to create a vegetation map 34.

  Although not shown, the map composition unit 17 outputs and prints the data of the vegetation map 34 in which the reflection intensity image data 31, the tree height image data 32, and the canopy stereoscopic image data 33 are superimposed on the connected printer. You can also

  The composite image adjustment unit 18 includes a reflection intensity color table 26, a tree height color table 27, and a ground opening color table 26 used when the reflection intensity gradation unit 14, the tree height gradation unit 15, and the ground opening degree gradation unit 16 perform gradation of each grid. The degree color table 28 is stored in the storage means by input from the terminal 19 and is changed as necessary.

  Further, the composite image adjustment unit 18 causes the terminal 19 to select only the image data that the user wants to display among the reflection intensity image data 31, the tree height image data 32, and the canopy stereoscopic image data 33 for creating the vegetation map 34. The image selection table 29 is stored in the storage means. The map composition unit 17 refers to the image selection table 29 and displays only the selected image on the terminal 19.

  Next, the configuration of the color table illustrated in FIGS. 4A to 4C will be described.

  In the example of the color table 26 for reflection intensity shown in FIG. 4A, the reflection intensity value Fi is divided from the weakest value to the strongest value at regular intervals, and what kind of component configuration is used as the display color component Ci. The component mode M (RGB in this example) indicating which color is assigned to each value is set by each RGB value.

  For example, in the first embodiment, the color scale on the side of the color table 26 for the reflection intensity is in the range from the weakest value to the strongest value of the reflection intensity value Fi so that the stronger the reflection intensity value Fi, the darker blue. Each RGB value is set for each reflection intensity value Fi in the table so that a white to blue gradation is assigned.

  In the example of the tree height color table 27 shown in FIG. 4B, the minimum value to the maximum value of the tree height value Zhi are divided at regular intervals, and the component indicating the component configuration as the display color component Ci. The mode M (RGB in this example) and which color is assigned to each value are set by each RGB value.

  For example, in the first embodiment, white to green expressed on the color scale next to the tree height color table 27 in the range from the lowest value to the highest value of the tree height value Zhi so that the darker the green the higher the tree height. Each value of RGB is set for each tree height value Zhi in the table so that the gradation is assigned.

  In the example of the ground opening color table 28 shown in FIG. 4C, in order to display the canopy stereoscopic image data 33 in gray scale, the minimum and maximum values of the ground opening value θi are displayed at regular intervals. A component mode M (in this example, gray scale) indicating what kind of component configuration is divided as the display color component Ci, and how much gray is set for each value is set by the gray scale value. ing.

  For example, in the first embodiment, the color scale next to the ground opening color table 28 is set in the range from the minimum value to the maximum value of the ground opening value θi so that the gray level becomes darker as the ground opening becomes larger. A gray scale value is set for each ground opening value θi in the table so that a color gradation of white to black is assigned.

  In the first embodiment, blue, green, and grayscale display color components Ci are specified by RGB and grayscale. However, display color components Ci are used according to the purpose of use and the state of the area measured by the aviation laser. Can be changed to combinations other than blue, green, and grayscale.

  Next, the flow of processing of the first vegetation map creating apparatus 10 according to Embodiment 1 of the present invention will be described with reference to FIGS.

(Processing of DHM data creation unit 12)
When the storage of the input data in the storage unit by the input unit 11 is completed, the DHM data creation unit 12 creates the DHM data 24 according to the procedure shown in FIG.

  First, the DEM data 21 stored in the storage means is read (step S12-1).

  Further, the DSM data 22 stored in the storage means is read (step S12-2).

  Next, the XY coordinate values (X1, Y1) and the ground elevation value Zg1 of the first grid (lattice number i = 1) are acquired from the DEM data 21 (step S12-3).

  Using the acquired XY coordinate values (X1, Y1) as key information, a lattice having the same XY coordinate values (X1, Y1) is searched from the DSM data 22, and the surface elevation value Zs1 is acquired (step S12-4).

  Subsequently, the ground elevation value Zg1 is subtracted from the acquired surface elevation value Zs1 to calculate a tree height value Zh1 (step S12-5).

  Finally, the calculated tree height value Zh1 is stored in the storage means as the DHM data 24 together with the XY coordinate values (X1, Y1) of the first lattice (step S12-6).

  Here, it is determined whether the processed grid is the last grid in the DEM data 21. For example, as shown in FIG. 2A, the total number of lattices (maximum lattice number i = n) is set in the DEM data 21 together with the data of each lattice, and the lattice number i of the processed lattice is n. If it is determined that it is equal to n, the processing is completed for all the lattices, and the processing is terminated (step S12-7).

  On the other hand, when the lattice number i of the processed lattice is smaller than n, the next lattice is designated by adding 1 to the lattice number i, and the processing from step S12-3 is repeated (step S12-8).

  By repeating the processing from step S12-3 to step S12-6, tree height values Zh2, Zh3,..., Zhn of lattice numbers i = 2, 3,. The completed DHM data 24 is completed.

(Processing of the ground opening calculation unit 13)
In the present invention, as shown in FIG. 8, the ground opening value θi used as an index indicating the inclination of the crown of each tree is represented by a lattice with a lattice number i (hereinafter referred to as a sample lattice in the processing of the ground opening calculation unit 13). Pi) and an inclination angle formed between each grid existing within a line-of-sight distance from the point of the sample grid Pi (hereinafter referred to as a target grid Qm in the processing of the ground opening calculation unit 13). .

  Here, the line-of-sight distance is represented by a radius R of a circle centered on the sample lattice Pi, and the search range is within the circle.

  If the radius R is too longer than the tree interval, the lattice of the adjacent tree vertex is included in the search range, and the maximum inclination angle is formed with respect to the vertex of the adjacent tree. On the other hand, if the radius R is too short with respect to the tree interval, the shape of the valleys and valleys in the tree crown is detected, and a plurality of tree vertices may be extracted for one tree crown. For this reason, the radius R is preferably set to be less than a typical tree interval in the measurement area.

  The ground opening value θi of the sample grid Pi is searched for the target grid Qm existing in 8 directions from the sample grid Pi, and the maximum in each direction from the angle θm from the zenith formed with each target grid Qm. The average inclination angle is calculated by extracting the inclination angle θmax and dividing the total by the number of directions.

  As shown in the grid position diagram on the XY plane in FIG. 8A, D0, D45, D90, D135, D180, D225, D270, D315 To do.

  The mark ♦ shown in FIG. 8A is the sample grid Pi, the mark ● is the target grid Qm positioned on each direction line, and the mark ◯ shows a non-target grid. Even if it is located on each direction line, the grid existing outside the search range is excluded.

  When the DHM data creation unit 12 completes the creation of the DHM data 24, the ground opening calculation unit 13 creates the DHM ground opening data 25. Refer to the diagram of the grid positions in the XYZ space in FIG. 8B. The processing will be described according to the flowchart shown in FIG.

  First, the ground opening calculation unit 13 reads the DHM data 24 stored in the storage unit (step S13-1).

  Next, as described above, in order to designate a search range, a radius R that is less than a representative tree interval in the measurement area is set (step S13-2).

  From the read DHM data 24, the sample lattice Pi of the lattice number i for calculating the ground opening value θi is set by the minimum value of the lattice number i, for example (step S13-3).

  From the XY coordinate values (Xi, Yi) of the sample lattice Pi and the lattice interval d, the XY coordinate values (Xm, Ym) of the first target lattice Qm in one direction are set as follows according to the search direction (step S13). -4).

In the direction D0: (Xm, Ym) = (Xi + d, Yi)
For direction D45: (Xm, Ym) = (Xi + d, Yi + d)
For direction D90: (Xm, Ym) = (Xi, Yi + d)
In the case of the direction D135: (Xm, Ym) = (Xi−d, Yi + d)
In the direction D180: (Xm, Ym) = (Xi−d, Yi)
In the direction D225: (Xm, Ym) = (Xi-d, Yi-d)
For direction D270: (Xm, Ym) = (Xi, Yi-d)
For direction D315: (Xm, Ym) = (Xi + d, Yi−d)
The DHM data 24 is searched using the XY coordinate values (Xm, Ym) set in step S13-4 as a key, and it is determined whether or not the corresponding target lattice Qm exists in the DHM data 24 (step S13-5).

  When the target lattice Qm exists, the inter-lattice distance Lm on the XY plane from the sample lattice Pi to the target lattice Qm is calculated by Equation 1 (step S13-6).

Lm = {(Xm−Xi) ² + (Ym−Yi) ² } ^1/2 Equation 1
Next, in order to determine whether the target lattice Qm is within the search range, the calculated inter-grid distance Lm is compared with a radius R or less (step S13-7).

  If the target lattice Qm is within the search range, the tree height difference ΔZhm between the sample lattice Pi and the target lattice Qm is calculated by Equation 2 (step S13-8).

ΔZhm = Zhm−Zhi Equation 2
The aspect ratio Km between the sample lattice Pi and the target lattice Qm is calculated from the calculated inter-lattice distance Lm and the tree height difference ΔZhm by Equation 3, and is temporarily stored in the storage means (step S13-9).

Km = ΔZhm / Lm Equation 3
When the processing for one target lattice Qm is completed, the XY coordinate values (Xm, Ym) of the target lattice Qm are updated as follows according to the search direction, and the process returns to step S13-5 to return to the next target lattice Qm. The process is repeated for (Step S13-10).

For direction D0: (Xm, Ym) = (Xm + d, Ym)
For direction D45: (Xm, Ym) = (Xm + d, Ym + d)
For direction D90: (Xm, Ym) = (Xm, Ym + d)
In the case of the direction D135: (Xm, Ym) = (Xm−d, Ym + d)
For direction D180: (Xm, Ym) = (Xm−d, Ym)
In the direction D225: (Xm, Ym) = (Xm−d, Ym−d)
For direction D270: (Xm, Ym) = (Xm, Ym−d)
For direction D315: (Xm, Ym) = (Xm + d, Ym-d)
In the middle of the processing, if the target lattice Qm corresponding to the direction in which the search is performed no longer exists in the determinations in step S13-5 and step S13-7, whether the processing has been completed in all directions with respect to the sample lattice Pi. For example, it is determined by comparing whether the direction is D315 (step S13-11).

  If there is still a direction to be searched, the next search direction is set, the process returns to step S13-4, and the process is repeated (step S13-12).

  When the processing is completed for all directions with respect to the sample lattice Pi, the maximum value Kmax in each direction is extracted from all the aspect ratios Km stored in step S13-9, and the maximum inclination angle in each direction is expressed by Expression 4 and Expression 5. θmax is calculated, and the average value obtained by dividing the sum of the maximum inclination angles θmax in each direction by the number of directions in which the target grid Qm exists is defined as the ground opening value θi, and the DHM ground opening data together with the XY coordinate values of the sample grid Pi 25 is stored in the storage means (step S13-13).

Max_angle = tan ⁻¹ (Kmax) (4)
Maximum inclination angle θmax = 90−Max_angle Expression 5
Here, the number of directions in which the target grid Qm exists differs depending on the position in the measurement area where the sample grid Pi exists, and when the sample grid Pi exists inside the measurement area, all the 8 directions shown in FIG. Become.

  On the other hand, when the sample grid Pi exists at the edge of the measurement area, there are no other grids beyond the edge of the measurement area, so the number of directions in which the target grid Qm exists is three directions indicating the outside of the measurement area. When the sample grid Pi is present at four corners of the measurement area, there are only three directions excluding the five directions indicating the outside of the measurement area.

  The number of directions in which the target grid Qm exists is determined, for example, in step S13-5 by determining whether the target grid Qm exists in the DHM data 24, and is counted when it exists.

  Finally, it is determined whether or not the ground opening value θi has been calculated for all the grids in the DHM data 24, for example, whether the grid number i of the sample grid Pi is the maximum value. Step S13-14).

  If there is a lattice to be further processed, 1 is added to the lattice number i to update to the next sample lattice Pi, and the processing is repeated from step S13-4 (step S13-15).

  Next, the reflection intensity data 23 stored in the storage means by the input unit 11, the DHM data 24 created by the DHM data creation unit 12, and the DHM ground opening data 25 created by the ground opening calculation unit 13, respectively. A procedure for creating various image data will be described.

  In describing the flow of various image data creation procedures, FIG. 9 shows a flowchart of the processing of the reflection intensity gradation unit 14. The processing of the tree stage stage section 15 and the ground opening stage stage section 16 is basically the same as the flowchart of FIG. 9 except that the data to be referred to is different as shown in FIG.

(Processing of the reflection intensity stage 14)
As shown in FIG. 9, the reflection intensity gradation unit 14 reads the reflection intensity data 23 stored in the storage means by the input unit 11 (step S14-1).

  For example, the grid having the smallest grid number i is designated from the read reflection intensity data 23, and the XY coordinate value and the reflection intensity value Fi of the corresponding grid are acquired (step S14-2).

  Next, the reflection intensity color table 26 is searched using the acquired reflection intensity value Fi as a key, and the display color component Ci corresponding to the acquired reflection intensity value Fi is acquired (step S14-3).

  The acquired display color component Ci is stored in the storage unit as the reflection intensity image data 31 together with the XY coordinate values of the lattice acquired in step S14-2 (step S14-4).

  Finally, it is determined whether the processed grid is the last grid included in the reflection intensity data 23, for example, whether the grid number i is less than the maximum value (step S14-5).

  If it is not the last grating, the grating number i is incremented by 1, the next grating of the reflection intensity data 23 is designated, the process returns to step S14-2, and the processes up to step S14-5 are repeated (step S14-6). .

  In the case of the last lattice, the component mode M indicating the component configuration of the display color component Ci set in the reflection intensity color table 26 illustrated in FIG. 4A is illustrated in FIG. As described above, the process is completed by adding to the reflection intensity data 23 (step S14-7).

(Processing of the tree height stage section 15 and the ground opening stage stage section 16)
As described above, the processing flow of the tree height stage chromatic part 15 and the ground opening degree chromatic part 16 is the same as the process flow of the reflection intensity stage chromatic part 14.

  In the processing corresponding to step S14-1, in place of the reflection intensity data 23, the tree height stage saturation unit 15 creates the DHM data 24 created by the DHM data creation unit 12, and the ground opening stage stage saturation unit 16 creates the ground opening degree saturation unit 16 by the ground opening degree calculation unit 13. The DHM ground opening data 25 is read.

  In the process corresponding to step S14-2, the tree height stage chromatic part 15 obtains the tree height value Zhi and the ground opening degree stage chromatic part 16 obtains the ground opening degree value θi together with the XY coordinate value of the lattice, instead of the reflection intensity value Fi.

  In the process corresponding to step S14-3, the tree height stage chromatic part 15 searches the tree height color table 27 using the acquired tree height value Zhi as a key, and acquires the display color component Ci corresponding to the acquired tree height value Zhi.

  Further, the ground opening stage color section 16 searches the ground opening color table 28 using the acquired ground opening value θi as a key, and acquires the display color component Ci corresponding to the acquired ground opening value θi.

  In the process corresponding to step S14-4, the acquired display color component Ci is stored as the tree height image data 32, and the ground opening stage color portion 16 is stored as the canopy stereoscopic image data 33 together with the XY coordinate values of the acquired grid. Save to means.

  Similarly to the reflection intensity stage color part 14, the tree height stage color part 15 and the ground opening degree color stage part 16 repeat the above processes up to the last lattice.

  As shown in FIG. 5, the tree height stage section 15 and the ground opening stage stage section 16, as illustrated in FIG. 5, have a component mode M that indicates what component configuration the display color component Ci illustrated in FIGS. 4B and 4C has. These are added to the tree height image data 32 and the canopy stereoscopic image data 33, respectively.

(Processing of the map composition unit 17)
Next, the processing of the map synthesis unit 17 that displays the image data created by each stage coloring unit on the user terminal 19 will be described with reference to the flowchart of FIG.

  The map synthesizing unit 17 reads the reflection intensity image data 31, the tree height image data 32, and the tree canopy stereoscopic image data 33 respectively created by each stage color unit from the storage unit (step S17-1).

  Further, the map composition unit 17 reads the image selection table 29 set in the storage means (step S17-2).

  The map synthesizing unit 17 generates an image from the image data selected by the user from the reflection intensity image data 31, the tree height image data 32, and the crown stereo image data 33 to be displayed by the image selection table 29, and the vegetation map 34. Is displayed on the terminal 19 (step S17-3).

  When the map composition unit 17 displays an image on the terminal 19, the map composition unit 17 determines the meaning of each value of the display color component Ci based on the component mode M set in the image data. Conversion from the color system to the color system of the terminal 19 is performed.

  When there are a plurality of selected image data, the map composition unit 17 superimposes these images and displays them on the terminal 19.

  Further, an image generated from the selected image data is output to the printer at the request of the user (step S17-4).

(Processing of the composite image adjustment unit 18)
The composite image adjustment unit 18 is a means for changing the settings of the image selection table 29 and each color table so that the user can change the image displayed on the terminal 19 and adjust the color tone of the image. 11 shows a flowchart of the process.

  The composite image adjustment unit 18 reads each color table and the image selection table 29 stored in the storage unit (step S18-1).

  The composite image adjustment unit 18 displays the read data on either the left or right or top and bottom of the vegetation map 34 displayed on the terminal 19 by the map composition unit 17 (step S18-2).

  The composite image adjustment unit 18 receives the setting data when the user sets an image selection change in the image selection table 29 or a color tone change in each color table based on the vegetation map 34 displayed on the terminal 19. (Step S18-3).

  To change the color tone of each color table, in addition to inputting the value of each display color component Ci of the color table one by one, the color scale shown in FIG. 4 is displayed next to the color table, and the colors at both ends thereof are displayed. It is possible to divide evenly within the range of the color table simply by designating, and automatically set the value of each display color component Ci in the color table.

  The composite image adjustment unit 18 updates each color table and the image selection table 29 stored in the storage unit with the received setting data (step S18-4).

  When each color table and the image selection table 29 are updated by the composite image adjustment unit 18, each stage coloring unit is activated, image data is re-created according to the updated color table, and the map composition unit 17 performs the image selection table 29. Thus, the newly selected image is displayed on the terminal 19.

  In the first embodiment, the reflection intensity image 31a shown in FIG. 12 (a) is converted into a blue gradation from the reflection intensity image data 31, as shown in FIG. The tree height image 32a shown in FIG. 12B is displayed with a green gradation from the tree height image data 32, and the tree crown image 33a shown in FIG. Is displayed.

  If the image selection table 29 is selected to display all the images, the map synthesis unit 17 displays a vegetation map 34 in which all the images are superimposed and the three images shown in FIG. To do.

  For comparison with the vegetation map 34 shown in FIG. 12 (d), an orthophoto image of the same region is shown in FIG. 12 (e). A similar forest image can be generated without using any orthophoto image.

  Furthermore, in the vegetation map 34 shown in FIG. 12 (d), there is no shaded and dark portion like an orthophoto image, and the trees are clearly displayed to the extent that they can be distinguished.

  Also, the tree photographed in the same green color in the orthophoto image is displayed in a different color tone reflecting the tree species in the vegetation map 34 shown in FIG.

<Embodiment 2>
In the first embodiment described above, the display color component Ci is assigned to each of the three indices of reflection intensity, tree height, and ground opening, and then each image is generated. it's shown.

  On the other hand, in the second embodiment of the present invention, one display color component Ci is determined by three indices of reflection intensity, tree height, and ground opening, and a vegetation map 34 of one image is directly created.

  Therefore, in the second embodiment, the vegetation map 34 is created using the L * a * b * color system specified by the International Lighting Commission CIE (Commission International de I'Eclariage).

  As shown in FIG. 13A, the color space of the L * a * b * color system (hereinafter referred to as Lab color) is defined by the L * axis, the a * axis, and the b * axis. Represents lightness, and chromaticity indicating hue and saturation is represented by a * and b *. a * and b * indicate the color directions, + a * indicates red, -a * indicates green, + b * indicates yellow, and -b * indicates blue.

  In the second embodiment, a Lab color color space as illustrated in FIG. 13B is defined. That is, the L * axis from L * = 0 (black) to L * = 255 (white), the a * axis from a * = 0 (green) to a * = 255 (red), and b * = 0 The Lab color space is defined by the b * axis from (blue) to b * = 255 (yellow).

  Here, by assigning the ground opening to the L * axis, the reflection intensity to the a * axis, and the tree height to the b * axis, one display color is determined by the three indexes.

  FIG. 14 shows a configuration necessary for the following description, unlike the first vegetation map creation device 10 shown in FIG. 1, among the configurations of the second vegetation map creation device 10 a according to the second embodiment of the present invention. The other components that are the same as those of the first vegetation map creating apparatus 10 are omitted.

  The second vegetation map creating apparatus 10a includes a Lab color stage coloring unit 40. The storage means includes a reflection intensity value conversion table 41, a tree height value conversion table 42, a ground opening value conversion table 43, and a Lab color. Lab color vegetation image data 44 generated by the gradation unit 40 is stored.

  The Lab color stage unit 40 reads the reflection intensity value Fi of each grating from the reflection intensity data 23 stored in the storage unit by the input unit 11, and stores the reflection intensity value conversion table 41 (FIG. 15 (FIG. 15) stored in the storage unit in advance. The reflection intensity value Fi is converted into an a * component value using a).

  Further, the Lab color gradation unit 40 reads the tree height value Zhi of each lattice from the DHM data 24 stored in the storage means by the DHM data creation section 12, and stores the tree value conversion table 42 (FIG. 15) stored in the storage means in advance. (B)) is used to convert the tree height value Zhi into a b * component value.

  Further, the Lab color stage saturation unit 40 reads the ground opening value θi of each grid from the DHM ground opening data 25 stored in the storage unit by the ground opening calculation unit 13 and stores the ground opening value previously stored in the storage unit. Using the degree value conversion table 43 (see FIG. 15C), the ground opening degree value θi is converted into an L * component value.

  The Lab color stage section 40 stores the a * component value, b * component value, and L * component value obtained by the conversion in the storage unit as Lab color vegetation image data 44 together with the XY coordinate values of each grid.

  Next, the configuration of the conversion table illustrated in FIGS. 15A to 15C will be described.

  In the example of the reflection intensity value conversion table 41 shown in FIG. 15A, the weakest value of the reflection intensity value Fi is 0 as the a * component value, the strongest value is 255 as the a * component value, and the reflection intensity value Fi The range is evenly assigned to the range of a * = 0 to 255.

  In the example of the tree height value conversion table 42 shown in FIG. 15B, the minimum value of the tree height value Zhi is 0 as the b * component value, the maximum value is 255 as the b * component value, and the range of the tree height value Zhi is a *. = 0 to 255.

  In the example of the ground opening value conversion table 43 shown in FIG. 15C, the minimum value of the ground opening value θi is 0 as the L * component value and the maximum value is 255 as the L * component value. The range of θi is equally assigned to the range of L * = 0 to 255.

  As shown in FIG. 16, the configuration of the Lab color vegetation image data 44 generated by the Lab color grading unit 40 is set such that L * a * b * is set as the component mode M, and the XY coordinate value of each grid and the L * component Value, a * component value, and b * component value.

  Next, the flow of processing of the Lab color gradation unit 40 will be described with reference to FIGS. 17 and 18.

(Processing of Lab color stage section 40)
As illustrated in FIG. 17, the Lab color gradation unit 40 reads the reflection intensity data 23 stored in the storage unit by the input unit 11 and starts the reflection intensity value conversion process. (Step S40-1).

  For example, the grid having the smallest grid number i is designated from the read reflection intensity data 23, and the XY coordinate value and the reflection intensity value Fi of the corresponding grid are acquired (step S40-2).

  Next, the reflection intensity value conversion table 41 is searched using the acquired reflection intensity value Fi as a key, and an a * component value corresponding to the acquired reflection intensity value Fi is acquired (step S40-3).

  The acquired a * component value is stored in the storage unit as Lab color vegetation image data 44 together with the XY coordinate value of the grid acquired in step S40-2 (step S40-4).

  Finally, it is determined whether the processed grid is the last grid included in the reflection intensity data 23, for example, whether the grid number i is less than the maximum value (step S40-5).

  If it is not the last grating, the grating number i is incremented by 1, the next grating of the reflection intensity data 23 is designated, the process returns to step S40-2, and the processes up to step S40-5 are repeated (step S40-6). .

  If it is the last lattice, the process proceeds to tree height conversion processing.

  As illustrated in FIG. 17, the Lab color gradation unit 40 reads the DHM data 24 created by the DHM data creation unit 12 (step S40-7).

  For example, the grid having the smallest grid number i is designated from the read DHM data 24, and the XY coordinate value and tree height value Zhi of the corresponding grid are acquired (step S40-8).

  Next, the tree height value conversion table 42 is searched using the acquired tree height value Zhi as a key, and the b * component value corresponding to the acquired tree height value Zhi is acquired (step S40-9).

  The acquired b * component value is added to the grid data of the same XY coordinates in the Lab color vegetation image data 44 already stored in the storage means (step S40-10).

  Finally, it is determined whether the processed grid is the last grid included in the DHM data 24, for example, whether the grid number i is less than the maximum value (step S40-11).

  If it is not the last lattice, the lattice number i is incremented by 1, the next lattice of the DHM data 24 is designated, the processing returns to step S40-8, and the processing up to step S40-11 is repeated (step S40-12).

  If it is the last grid, the process proceeds to the ground opening value conversion process.

  As illustrated in FIG. 18, the Lab color stage coloring unit 40 reads the DHM ground opening data 25 created by the ground opening calculation unit 13 (step S40-13).

  For example, the grid having the smallest grid number i is designated from the read DHM ground opening data 25, and the XY coordinate value and the ground opening value θi of the corresponding grid are acquired (step S40-14).

  Next, the ground opening value conversion table 43 is searched using the acquired ground opening value θi as a key, and the L * component value corresponding to the acquired ground opening value θi is acquired (step S40-15).

  The acquired L * component value is added to the grid data of the same XY coordinates in the Lab color vegetation image data 44 already stored in the storage means (step S40-16).

  Finally, it is determined whether the processed grid is the last grid included in the DHM ground opening data 25, for example, whether the grid number i is less than the maximum value (step S40-17).

  If it is not the last lattice, the lattice number i is incremented by 1, the next lattice of the DHM data 24 is designated, the process returns to step S40-14, and the processing up to step S40-17 is repeated (step S40-18).

  If it is the last grid, the process ends.

  The map synthesizing unit 17 reads the Lab color vegetation image data 44 created by the Lab color grading unit 40 together with the reflection intensity image data 31, the tree height image data 32, and the canopy stereoscopic image data 33 shown in the first embodiment from the storage unit. Then, an image is generated from the image data selected by the user to be displayed by the image selection table 29 and displayed on the terminal 19 as the vegetation map 34.

  As shown in FIG. 19A, the map composition unit 17 displays a Lab color vegetation image 44a from the Lab color vegetation image data 44 on the terminal 19 as a vegetation map 34.

  Compared with the vegetation map 34 shown in FIG. 12D of the first embodiment, the difference in display color of each tree is further clarified.

  In an actual field survey, a circle displayed on the Lab color vegetation image 44a in FIG. 19A shows a red tree because of its high tree height and strong reflection intensity, as shown in FIG. 19B. Mushrooms with lots of leaves were clustered, and Sawagurumi with sparse leaves as shown in FIG. 19 (c) was clustered at locations displayed in green because of the high tree height but low reflection intensity.

  Furthermore, the place displayed in blue is a place where the tree height is extremely low, that is, the ground appears, and can be clearly distinguished from the tree.

  For example, as shown in FIG. 20A, the Lab color vegetation image 44a and the three-dimensional terrain image are superimposed and displayed on the terminal 19 as a vegetation map 34, thereby further visually recognizing the vegetation of the tree species three-dimensionally. It becomes easy.

  As the three-dimensional landform image, an image created by the method using the three-dimensional image creation device disclosed in Japanese Patent No. 4272146 can be used.

  That is, the first and second vegetation map creation devices 10 and 10a are provided with a three-dimensional topographic image creation unit, and the DEM ground opening is determined from the DEM data 21 stored in the storage means by the same processing as the ground opening calculation unit 13. The value is obtained, and further, the DEM underground opening value is obtained from the inverted DEM data 21 in which the solid with the air layer pressed against the DEM data 21 is turned over, the difference between the two is displayed in gray scale, and the slope is displayed in red gradation Create the displayed pseudo-color image.

  In the created pseudo color image, the ridge and the summit portion are whitish, the valley and the depression are expressed in black, and the steeper portion is expressed in red so that even one image has a three-dimensional effect and is also called a red three-dimensional image.

  Further, there may be provided means for directly reading the 3D terrain image created by the external 3D image creation device into the first and second vegetation map creation devices 10 and 10a.

  In the present invention, a 3D terrain image is added to the selection item of the image selection table 29, and if the 3D terrain image has been selected, the map composition unit 17 superimposes the 3D terrain image on another selected image to the terminal 19. indicate.

  At this time, in consideration of overlapping with other images, adjustments such as displaying the stereoscopic terrain image with reduced saturation and lightness are appropriately performed.

  Although FIG. 20 (a) is grayscale, it is difficult to understand, but in an actual image, each tree is displayed in green in the upper left part indicated by a circle, the red part is displayed in the central part, and the lower right part is displayed in the lower right part. A mixture of red and green is displayed. When field surveys are conducted, the tree species in each area are different.

  Based on FIG. 20A, when the outline of the range of similar colors is drawn, a forest phase division diagram as shown in FIG. 20B can be obtained.

  As described above, in the first embodiment, the vegetation map 34 is displayed in a hue similar to natural green like the orthophoto image, and can be used as an alternative to the orthophoto image. In the second embodiment, the tree species is used. Trees are displayed in various colors such as red, blue, and yellow other than natural tree colors (mainly green) using the L * a * b * color system so that they can be more clearly distinguished. doing.

  Thus, according to the present invention, the distribution of the tree species can be easily visually recognized, and the local vegetation survey can be performed efficiently.

  The embodiment described above exemplifies an apparatus and a processing procedure for embodying the technical idea of the present invention, and does not limit the arrangement of components or the order of processing. The technical idea of the present invention can be variously modified within the technical scope described in the claims. It should be noted that the drawings are schematic and the configuration of the apparatus is different from the actual one.

DESCRIPTION OF SYMBOLS 10 1st vegetation map creation apparatus 10a 2nd vegetation map creation apparatus 11 Input part 12 DHM data creation part 13 Ground opening degree calculation part 14 Reflection intensity stage color part 15 Tree height stage color part 16 Ground degree opening stage color part 17 Map composition part 18 Composite image adjustment Unit 19 Terminal 20 Aviation laser survey data 21 DEM data 22 DSM data 23 Reflection intensity data 24 DHM data 25 DHM ground opening data 26 Reflection intensity color table 27 Tree height color table 28 Ground opening color table 29 Image selection table 31 Reflection intensity image data 31a Reflection intensity image 32 Tree height image data 32a Tree height image 33 Tree crown three-dimensional image data 33a Tree crown three-dimensional image 34 Vegetation map 40 Lab color stage portion 41 Reflection intensity value conversion table 42 Tree height value conversion table 43 Ground opening value conversion table 44 Lab color vegetation image data 44a Lab color vegetation image

Claims (10)

A vegetation map creation device that creates a vegetation map using only aerial laser survey data in which a grid of desired intervals is set for the entire measurement area,
DEM data consisting of XY coordinate values and ground elevation values of the grid generated from the aerial laser survey data, DSM data consisting of the XY coordinate values and surface elevation values, and a reflection consisting of the XY coordinate values and reflection intensity values An input unit for importing intensity data from an external storage medium into a storage means;
From the DEM data and the DSM data stored in the storage means, the ground elevation value and the surface elevation value related to the same XY coordinate value are read, and the tree elevation value obtained by subtracting the ground elevation value from the surface elevation value, A DHM data creation unit that stores the XY coordinate values in the storage means as DHM data;
An arbitrary lattice of the DHM data is set as a sample lattice, and a maximum inclination angle is obtained from an inter-grid distance and a tree height difference from the sample lattice to a target lattice existing in a search range in a plurality of directions, and the maximum inclination angle A ground opening degree calculation unit for storing the ground opening value averaged as DHM ground opening degree data together with the XY coordinate values of the sample grid,
The reflection intensity value is read from the reflection intensity data stored in the storage means, and a color table for reflection intensity stored in the storage means in advance is searched with the reflection intensity value. A reflection intensity gradation unit that acquires the set first display color component and stores it in the storage means as reflection intensity image data together with the XY coordinate values;
The tree height value is read from the DHM data, a tree height color table stored in the storage means in advance is searched with the tree height value, and a second display color component set for the tree height value is acquired. A tree height stage chromatic part to be stored in the storage means as tree height image data together with the XY coordinate values;
The ground opening value is read from the DHM ground opening data, a color table for the ground opening previously stored in the storage means is searched with the ground opening value, and set for the ground opening value. A third display color component that is obtained and stored in the storage means as canopy stereoscopic image data together with the XY coordinate values;
A vegetation map creating apparatus, comprising: a map composition unit that generates an image from each image data stored in the storage unit and superimposes and displays the image on a terminal as a vegetation map.   The vegetation map creating apparatus according to claim 1, further comprising a composite image adjusting unit that changes the reflection intensity color table, the tree height color table, and the ground opening color table by an input from the terminal. The composite image adjustment unit stores, in a storage unit, an image selection table in which the type of image that the user wants to display is set from the terminal,
The vegetation map creating apparatus according to claim 2, wherein the map composition unit refers to the image selection table and displays only the selected image on the terminal. The reflection intensity value is read from the reflection intensity data stored in the storage means, a reflection intensity value conversion table stored in advance in the storage means is searched with the reflection intensity value, and the reflection intensity value is Convert to the set a * component value,
Reading the tree height value from the DHM data, searching the tree height value conversion table stored in the storage means in advance with the tree height value, converting it to a b * component value set for the tree height value,
The ground opening value is read from the DHM ground opening data, a ground opening value conversion table stored in the storage means in advance is searched with the ground opening value, and set for the ground opening value. Converted to L * component value,
The Lab color chromatic part which further stores the a * component value, the b * component value, and the L * component value together with the XY coordinate values as Lab color vegetation image data in the storage unit. The vegetation map creation device described in the paragraph. A vegetation map creation device that creates a vegetation map using only aerial laser survey data in which a grid of desired intervals is set for the entire measurement area,
DEM data consisting of XY coordinate values and ground elevation values of the grid generated from the aerial laser survey data, DSM data consisting of the XY coordinate values and surface elevation values, and a reflection consisting of the XY coordinate values and reflection intensity values An input unit for importing intensity data from an external storage medium into a storage means;
From the DEM data and the DSM data stored in the storage means, the ground elevation value and the surface elevation value related to the same XY coordinate value are read, and the tree elevation value obtained by subtracting the ground elevation value from the surface elevation value, A DHM data creation unit that stores the XY coordinate values in the storage means as DHM data;
An arbitrary lattice of the DHM data is set as a sample lattice, and a maximum inclination angle is obtained from an inter-grid distance and a tree height difference from the sample lattice to a target lattice existing in a search range in a plurality of directions, and the maximum inclination angle A ground opening degree calculation unit for storing the ground opening value averaged as DHM ground opening degree data together with the XY coordinate values of the sample grid,
The reflection intensity value is read from the reflection intensity data stored in the storage means, a reflection intensity value conversion table stored in advance in the storage means is searched with the reflection intensity value, and the reflection intensity value is Convert to the set a * component value,
Reading the tree height value from the DHM data, searching the tree height value conversion table stored in the storage means in advance with the tree height value, converting it to a b * component value set for the tree height value,
The ground opening value is read from the DHM ground opening data, a ground opening value conversion table stored in the storage means in advance is searched with the ground opening value, and set for the ground opening value. Converted to L * component value,
A Lab color chromatic part that stores the a * component value, the b * component value, and the L * component value together with the XY coordinate values as Lab color vegetation image data in the storage means;
A vegetation map creating apparatus comprising: a map synthesis unit that generates an image from the Lab color vegetation image data and displays the image as a vegetation map on a terminal. A vegetation map creation program for creating a vegetation map using only aerial laser survey data in which a grid of desired intervals is set for the entire measurement area,
On the computer,
DEM data consisting of XY coordinate values and ground elevation values of the grid generated from the aerial laser survey data, DSM data consisting of the XY coordinate values and surface elevation values, and a reflection consisting of the XY coordinate values and reflection intensity values Input means for importing intensity data from an external storage medium into the storage means;
From the DEM data and the DSM data stored in the storage means, the ground elevation value and the surface elevation value related to the same XY coordinate value are read, and the tree elevation value obtained by subtracting the ground elevation value from the surface elevation value, DHM data creating means for storing in the storage means as DHM data together with XY coordinate values;
An arbitrary lattice of the DHM data is set as a sample lattice, and a maximum inclination angle is obtained from an inter-grid distance and a tree height difference from the sample lattice to a target lattice existing in a search range in a plurality of directions, and the maximum inclination angle The ground opening degree calculation means for storing the ground opening value averaged in the storage means as the DHM ground opening data together with the XY coordinate values of the sample grid,
The reflection intensity value is read from the reflection intensity data stored in the storage means, and a color table for reflection intensity stored in the storage means in advance is searched with the reflection intensity value. A reflection intensity gradation unit that acquires the set first display color component and stores it in the storage unit as reflection intensity image data together with the XY coordinate values;
The tree height value is read from the DHM data, a tree height color table stored in the storage means in advance is searched with the tree height value, and a second display color component set for the tree height value is acquired. A tree height stage coloring means for storing in the storage means as tree height image data together with the XY coordinate values;
The ground opening value is read from the DHM ground opening data, a color table for the ground opening previously stored in the storage means is searched with the ground opening value, and set for the ground opening value. A third display color component that has been obtained and stored in the storage means as a canopy stereoscopic image data together with the XY coordinate values;
A vegetation map creation program for executing a function as a map synthesis unit that generates an image from each image data stored in the storage unit and superimposes and displays the image on a terminal as a vegetation map. In the computer,
The vegetation map according to claim 6, further executing a function as a composite image adjusting unit that changes the color table for reflection intensity, the color table for tree height, and the color table for ground opening by input from the terminal. Creation program. In the composite image adjusting means, an image selection table in which the type of image that the user wants to display is set from the terminal is stored in the storage means,
The vegetation map creation program according to claim 7, wherein the map composition unit is configured to execute the display of only the selected image on the terminal with reference to the image selection table. In the computer,
The reflection intensity value is read from the reflection intensity data stored in the storage means, a reflection intensity value conversion table stored in advance in the storage means is searched with the reflection intensity value, and the reflection intensity value is Convert to the set a * component value,
Reading the tree height value from the DHM data, searching the tree height value conversion table stored in the storage means in advance with the tree height value, converting it to a b * component value set for the tree height value,
The ground opening value is read from the DHM ground opening data, a ground opening value conversion table stored in the storage means in advance is searched with the ground opening value, and set for the ground opening value. Converted to L * component value,
A function for further executing a function as a Lab color gradation unit that stores the a * component value, the b * component value, and the L * component value together with the XY coordinate values as Lab color vegetation image data in the storage unit. The vegetation map creation program according to any one of claims 6 to 8. A vegetation map creation program for creating a vegetation map using only aerial laser survey data in which a grid of desired intervals is set for the entire measurement area,
On the computer,
DEM data consisting of XY coordinate values and ground elevation values of the grid generated from the aerial laser survey data, DSM data consisting of the XY coordinate values and surface elevation values, and a reflection consisting of the XY coordinate values and reflection intensity values Input means for importing intensity data from an external storage medium into the storage means;
From the DEM data and the DSM data stored in the storage means, the ground elevation value and the surface elevation value related to the same XY coordinate value are read, and the tree elevation value obtained by subtracting the ground elevation value from the surface elevation value, DHM data creating means for storing in the storage means as DHM data together with XY coordinate values;
An arbitrary lattice of the DHM data is set as a sample lattice, and a maximum inclination angle is obtained from an inter-grid distance and a tree height difference from the sample lattice to a target lattice existing in a search range in a plurality of directions, and the maximum inclination angle The ground opening degree calculation means for storing the ground opening value averaged in the storage means as the DHM ground opening data together with the XY coordinate values of the sample grid,
The reflection intensity value is read from the reflection intensity data stored in the storage means, a reflection intensity value conversion table stored in advance in the storage means is searched with the reflection intensity value, and the reflection intensity value is Convert to the set a * component value,
Reading the tree height value from the DHM data, searching the tree height value conversion table stored in the storage means in advance with the tree height value, converting it to a b * component value set for the tree height value,
The ground opening value is read from the DHM ground opening data, a ground opening value conversion table stored in the storage means in advance is searched with the ground opening value, and set for the ground opening value. Converted to L * component value,
Lab color gradation means for storing the a * component value, the b * component value, and the L * component value together with the XY coordinate values as Lab color vegetation image data in the storage means,
A vegetation map creation program for generating an image from the Lab color vegetation image data and executing a function as map synthesis means for displaying the image on a terminal as a vegetation map.