JP7123366B2 - Evaluation method for standing trees in a forest area and boundary survey method suitable for identifying the evaluation target area in this evaluation method - Google Patents

Description

TECHNICAL FIELD The present invention relates to a method for evaluating the number of standing trees and volume of wood in a forest area, and particularly to a boundary line survey method for surveying forest boundaries.

The use of image information and laser measurement information has been proposed as a method of evaluating the number of standing trees and volume of wood in forest areas.
Patent Literature 1 proposes a forest information processing system that automatically measures the volume of trees in a forest area based on forest photography image information and tree height information acquired from above the forest area.
In Patent Document 1, from forest image information acquired by high-resolution satellites or aircraft, the number of standing trees is measured by extracting the tree crown shape by an area division method called the Watershed algorithm, and GPS / IMU and distance measurement sensors is used to obtain the tree height.
Patent Document 2 calculates DSM data indicating the three-dimensional position of trees on the ground and DTM data indicating the three-dimensional position of the ground from aerial survey data, extracts treetops from the DSM data, and extracts treetops from the treetops. It proposes extracting the tops, calculating the height of the tops from the tops and DTM data, and extracting the crown for each top from the tops and the DSM data.
In Patent Document 2, the aerial survey data includes data measured by a laser ranging device (distance and irradiation angle, distinction between first and last), attitude of a helicopter measured by a gyro, and three-dimensional position data of a helicopter obtained by a GPS receiver. , DTM data is generated from the measured value of the last pulse, and DSM data is generated from the measured value of the first pulse.
Moreover, in Patent Document 2, DSM mesh data is used for extracting the tips of the treetops. That is, the target area is divided into square tiles, and the top of the treetop with the highest altitude is extracted for each tile. Here, in order to deal with errors that depend on the tile separation position and multiple tree species with different sizes, we tested with multiple tile sizes and stored the data detected at each tile size.
Patent document 3 proposes a tree position detection device that detects the positions of trees using three-dimensional point cloud data of a forest obtained by aerial laser measurement that sweeps a laser pulse from the sky and measures the reflected signal waveform. is doing.
In Patent Document 3, a normalization means that converts the height represented by the point cloud data into a real height from the ground surface to generate normalized point cloud data, and the tree crown area of the forest and the lower branch area below it. Based on the difference in the distribution of the normalized point cloud data, the branch lower layer setting means that sets a constant height range in the forest as the lower branch layer, and the normalized point cloud data belonging to the lower branch layer are extracted and displayed on the ground surface. a plane projection means for obtaining a two-dimensional frequency distribution by projecting onto a plane along the tree, and a position detection means for detecting locations where normalized point cloud data gather in the two-dimensional frequency distribution based on a predetermined standard and setting them as tree positions. It has
On the other hand, in general, a total station is used for topographical data surveying, such as for creating maps.
Surveying using a total station is highly accurate, but requires skill and has the problem of low productivity.
A compass surveying device is a surveying device that does not require skill and is highly productive, but the compass surveying device has lower surveying accuracy than a total station, and errors are cumulatively affected especially when there are few reference points. There is a problem that
Patent Document 4 and Patent Document 5 disclose a surveying method using a compass surveying instrument.
Further, Patent Documents 6 and 7 disclose a method of determining coordinate data of reference points on the ground by photographing from an aircraft.
Further, Patent Document 8 discloses a surveying method for creating map information by integrating the results of both ground surveying and aerial surveying.

Japanese Patent Application Laid-Open No. 2003-344048 Japanese Patent Application Laid-Open No. 2007-198760 JP 2012-098247 A JP 2010-085217 A JP 2015-143625 A JP 2011-169658 A JP 2006-027331 A JP 2016-017931 A

The standing tree evaluation methods proposed in Patent Documents 1 to 3 process data using only the data obtained by photographing or measuring, and therefore tend to depend on the accuracy of the obtained data. Patent Literature 1 to Patent Literature 3 do not disclose the use of the number of actual standing trees obtained by actually measuring standing trees in the representative area.
On the other hand, as for the boundary line surveying method, Patent Documents 4 to 8 describe a combination of compass surveying and surveying based on photographed data. Supplementing with is not disclosed.

An object of the present invention is to provide a method for evaluating standing trees in a forest area, which can extract standing tree vertices using a grid with a reference value suitable for the evaluation target area and can calculate the number of standing trees with little error. .
In addition, the present invention measures an accurate reference point by surveying using photographed data, and uses this reference point to perform compass surveying of most of the boundaries. It is an object of the present invention to provide a boundary line survey method that can be performed with high accuracy.

A method for evaluating standing trees in a forest area according to claim 1 of the present invention is a method for evaluating standing trees in a forest area using photographed data photographed from above, wherein a server converts the photographed data into point cloud data a point cloud data generation step of generating 60d, dividing a representative area which is a part of the evaluation target area into a grid with a reference value, and extracting the highest position data from the point cloud data 60d in the divided grid into vertices a representative area vertex extraction step of extracting as a tree vertex extraction step in the representative area, a representative area tree vertex determination step of determining whether or not the vertex extracted in the representative area vertex extraction step is a tree vertex, and the representative area tree vertex determination step a step of calculating the number of standing tree vertices in the representative area for calculating the number of standing tree vertices in the representative area determined to be the tree vertices in the above; a standing tree number comparison step of comparing with the number of actual standing trees in the representative area; a reference value changing step of changing the reference value so that the difference between the number of inner tree vertices and the number of actual standing trees is within the threshold; and the evaluation target area using the changed reference value changed in the reference value changing step. are divided into the grids, and extracted in the evaluation target area vertex extraction step of extracting the highest position data as the vertices from the point group data 60d in the divided grids, and the evaluation target area vertex extraction step a standing tree vertex determination step for determining whether or not the vertex is the tree vertex; and a step of determining the number of trees to be calculated.
According to a second aspect of the present invention, in the method for evaluating standing trees in a forest area according to claim 1, the server performs a terrain data correspondence step of aligning terrain data 60c of the evaluation target area different from the point cloud data 60d with the point cloud data 60d; a tree vertex calculation step of calculating the height of the tree vertex based on the landform data 60c; and a timber volume calculation step.
The boundary survey method of the present invention according to claim 3 is a boundary survey method suitable for specifying the evaluation target area in the evaluation method for standing trees in a forest area according to claim 1 or claim 2, wherein: A reference point setting step of setting a reference point 1 at a position that can be photographed from the sky, a flight route determination step of determining a flight route along the boundary, and the flight route a flight step of flying the unmanned aerial vehicle 10 along the flight path determined in the determination step; a photographing information measuring step of measuring photographing position data and photographing direction data of the photographing device 11 at the time of photographing in the photographing step; a photographing data storing step of storing position data and the photographing direction data; and coordinate data of the reference point 1 using the photographing data, the photographing position data, and the photographing direction data stored in the photographing data storing step. and a compass surveying step of obtaining survey data of the boundary and the reference point 1, wherein the coordinate data of the reference point 1 determined in the reference point coordinate determination step; A boundary line is determined from the survey data acquired in the compass survey step.
According to a fourth aspect of the present invention, in the boundary survey method according to the third aspect, in the reference point setting step, a global navigation satellite system receiver 12 is used to measure the coordinate data of the reference point 1, and the In the flight route determination step, the flight route is determined using the measured coordinate data of the reference point 1 .
The present invention according to claim 5 is the boundary survey method according to claim 3 or claim 4, wherein the compass surveying step is performed together with the reference point setting step, and the survey data obtained in the compass surveying step is 3. The boundary line is determined by recalculation using the coordinate data of the reference point 1 determined in the reference point coordinate determining step.

According to the evaluation method for standing trees in a forest area of the present invention, the number of standing tree vertices in the representative area is calculated in advance in the representative area, and the calculated number of standing tree vertices in the representative area matches the actual number of standing trees in the representative area. By comparing whether or not it is, and changing the reference value so that the number of tree vertices in the representative area and the actual number of trees match, it is possible to extract the tree vertices using a grid with a reference value suitable for the evaluation target area. , the number of standing trees can be calculated with little error.
Further, according to the boundary line surveying method of the present invention, a reference point is set at a position that can be photographed from the sky, and accurate coordinate data for this reference point is obtained using photographing data acquired by an unmanned aerial vehicle. By determining the boundary line from the coordinate data and the survey data, it is possible to survey the boundary line particularly in a forest area with high efficiency and high accuracy.

Flowchart showing a processing flow of a standing tree evaluation method in a forest area according to an embodiment of the present invention Photographed data extracted in the photographed data extraction step of the evaluation method for standing trees in the same forest area Point cloud data generated in the point cloud data generation step of the evaluation method for standing trees in the same forest area Image diagram of the step of extracting vertices in a representative area of the evaluation method for standing trees in the same forest area Conceptual diagram of the step corresponding to topographical data in the evaluation method for standing trees in the forest area Image diagram of the vertex extraction step within the evaluation target area of the evaluation method for standing trees in the same forest area 1 is a block diagram showing an apparatus for implementing a boundary survey method according to an embodiment of the present invention; FIG. Flowchart showing the processing flow of the boundary line survey method Explanatory drawing showing the boundary and reference points in the same boundary survey method Flowchart showing the processing flow of the boundary survey method according to another embodiment of the present invention

A method for evaluating standing trees in a forest area according to the first embodiment of the present invention includes a point cloud data generation step in which a server generates point cloud data from photographed data; A representative area vertex extraction step of dividing an area into a grid based on a reference value and extracting the highest position data as a vertex from the point cloud data in the divided grid, and the vertex extracted in the representative area vertex extraction step is used as a tree vertex. a standing tree vertex determination step in the representative area for determining whether or not a standing tree vertex number in the representative area is calculated; A tree number comparison step of comparing the number of standing tree vertices in the representative area calculated in the step of calculating the number of standing tree vertices with the number of actual standing trees in the representative area, and the number of standing tree vertices in the representative area and the actual standing trees compared in the standing tree number comparison step. If the difference between the number of vertices exceeds the threshold, the reference value is changed so that the difference between the number of standing tree vertices in the representative area and the number of actual standing trees is within the threshold, and the reference value changing step. an evaluation area vertex extraction step of dividing the evaluation target area into grids using the change reference value and extracting the highest position data as a vertex from the point cloud data in the divided grid; and an evaluation target area vertex extraction step An evaluation target area tree vertex determination step for determining whether or not an extracted vertex is a tree vertex, and the evaluation target area tree vertex number determined as a tree vertex in the evaluation target area tree vertex determination step is used as the number of trees to be calculated. and a step of determining the number of standing trees to be determined. According to the present embodiment, the number of standing tree vertices in the representative area is calculated in advance in the representative area, and it is compared whether or not the calculated number of standing tree vertices in the representative area matches the actual number of standing trees in the representative area, By changing the reference value so that the number of tree vertices in the representative area and the actual number of trees match, it is possible to extract the tree vertices using a grid with reference values suitable for the evaluation target area. can be calculated.

According to a second embodiment of the present invention, in the method for evaluating standing trees in a forest area according to the first embodiment, the server performs point cloud The terrain data of the evaluation target area, which is different from the data, is aligned with the point cloud data. It has a tree vertex calculation step of calculating the height of the vertex, and a lumber volume calculation step of calculating the lumber volume using the height of the tree vertex calculated in the tree vertex calculation step. According to the present embodiment, the height of standing trees from the ground surface can be calculated by using the terrain data of the evaluation target area that is different from the point cloud data, and the volume of trees can be calculated using the height of standing trees. be able to.

A third embodiment of the present invention is a boundary survey method suitable for specifying an evaluation target area in the method for evaluating standing trees in a forest area according to the first or second embodiment, in which the boundary or A reference point setting step of setting a reference point near the boundary and at a position that can be photographed from the sky, a flight route determination step of determining a flight route along the boundary, and a flight route determined in the flight route determination step. a flight step of flying an unmanned aerial vehicle along a path; a photographing step of photographing an area including a reference point with a photographing device mounted on the unmanned aerial vehicle in the flight step; a shooting data storing step of storing shooting position data and shooting direction data measured in the shooting information measuring step together with the shooting data shot in the shooting step; and a shooting data storing step storing the shooting data. a reference point coordinate determination step of determining the coordinate data of the reference point using the obtained photographing data, photographing position data, and photographing direction data; and a compass surveying step of obtaining survey data of the boundary and the reference point. The boundary line is determined from the coordinate data of the reference points determined in the point coordinate determination step and the survey data obtained in the compass survey step. According to this embodiment, a reference point is set at a position that can be photographed from the sky, accurate coordinate data is obtained for this reference point using photographing data acquired by an unmanned aerial vehicle, and the coordinate data of the reference point and the survey By determining the boundary line from the data, it is possible to survey the boundary line, especially in the forest area, with high efficiency and high accuracy.

According to a fourth embodiment of the present invention, in the boundary survey method according to the third embodiment, in the reference point installation step, the coordinate data of the reference points are measured using a global navigation satellite system receiver, and the flight path In the determination step, the flight path is determined using the measured coordinate data of the reference points. According to this embodiment, a flight path at a lower altitude can be determined along the reference point.

According to a fifth embodiment of the present invention, in the boundary survey method according to the third or fourth embodiment, the compass surveying step is performed together with the reference point setting step, and the survey data acquired in the compass surveying step is used as a reference point. The boundary line is determined by recalculation using the coordinate data of the reference points determined in the point coordinate determination step. According to this embodiment, since the survey is performed when the reference point is installed, there is no need to enter the survey location twice, which improves workability.

Embodiments of the present invention will be described below with reference to the drawings.
FIG. 1 is a flow chart showing the processing flow of a standing tree evaluation method in a forest area according to this embodiment;
FIG. 2 is the image data extracted in the image data extraction step, FIG. 3 is the point cloud data generated in the point cloud data generation step, FIG. 4 is an image diagram of the representative area vertex extraction step, and FIG. 5 is an image diagram of the terrain data correspondence step. FIG. 6 is an image diagram of the step of extracting vertices in the evaluation target area.

The server extracts photographic data of, for example, an evaluation target area enclosed by a boundary line from the photographic data photographed from above (step 51). If the photographed data is still image data, a plurality of pieces of photographed data photographed from different positions are extracted.
FIG. 2 shows the photographic data extracted in the photographic data extraction step 51 .

The server generates point cloud data from the photographed data extracted in the photographed data extraction step 51 (step 52). The point cloud data generated in the point cloud data generating step 52 is three-dimensional data.
FIG. 3 shows the point cloud data generated in the point cloud data generation step 52. As shown in FIG.
A part of the area to be evaluated is specified as a representative area. For the representative area, an area that is easy to count is specified in order to count the actual number of standing trees on site. Also, the representative area specifies an area with a standard standing tree situation in the evaluation target area.
The representative area can be specified by the server, for example, on the condition that it faces a road or vacant land, or is located in the vicinity of the evaluation target area.
Also, whether the area is standard or not can be determined by the server based on the features extracted from the image data.

The server divides the representative area into grids based on the reference value (step 53), and extracts the highest position data as vertices from the point cloud data in the divided grid (step 54).
FIG. 4 is an image diagram of the representative area vertex extraction step 54 . FIG. 4(a) is an image diagram of specifying the representative area, FIG. 4(b) is an image diagram of dividing the representative area into a grid with reference values in step 53, and FIG. 4(c) is the highest position data in step 54 specified as the vertex. It is an image figure.

The server determines whether or not the vertex extracted in the representative area vertex extraction step 54 is a tree vertex (step 55).
In step 55 for judging the vertices of standing trees in the representative area, for example, trees whose height data values of the highest position data are clearly judged not to be the height of the standing trees are excluded.
The server calculates the number of tree vertices in the representative area determined to be tree vertices in the representative area tree vertex determination step 55 (step 56).
The server compares the number of standing tree vertices in the representative area calculated in the step 56 for calculating the number of standing tree vertices in the representative area with the number of actual standing trees in the representative area (step 57).
Here, the actual number of standing trees in the representative area to be compared in the standing tree number comparison step 57 is counted by investigation at the site and stored in the server. Note that the number of actual standing trees in the representative area may be counted visually based on image data instead of on-site investigation.
When the difference between the number of standing tree vertices in the representative area and the number of actual standing trees compared in the standing tree number comparison step 57 exceeds the threshold, the server determines that the difference between the number of standing tree vertices in the representative area and the number of actual standing trees is within the threshold. (step 58).
In the reference value changing step 58, for example, if the number of actual standing trees is 20 and 10% of the number of actual standing trees is set as a threshold, the threshold is ±2. Do not change the value. When the number of tree vertices in the representative area is 14, that is, when the number of tree vertices in the representative area is less than the actual number of trees, the reference value is changed to a smaller value. Also, when the number of tree vertices in the representative area is 25, that is, when the number of tree vertices in the representative area is greater than the number of actual trees, the reference value is changed to a larger value.
In the reference value change step 58, after changing the reference value, the steps from the representative area vertex extraction step 54 to the tree number comparison step 57 are repeated until the difference between the number of vertices of trees in the area and the number of actual trees falls within the threshold. .

The server aligns the terrain data of the evaluation target area, which is different from the point cloud data, with the point cloud data based on the reference point where the terrain was photographed from the point cloud data extracted in the photographing data extraction step 51. (Step 60).
For the terrain data used in the terrain data correspondence step 60, for example, board map information (digital elevation model) provided by the Geospatial Information Authority of Japan can be used.
FIG. 5 is an image diagram of step 60 corresponding to terrain data.
As shown in FIG. 5, the terrain data 60c is aligned with the point cloud data 60d based on the reference points 60a and 60b where the terrain was photographed. For alignment, a reference area of a predetermined range may be used instead of the reference points 60a and 60b.

The server divides the evaluation target area into grids using the changed reference value changed in the reference value change step 58 (step 61), and extracts the highest position data as vertices from the point cloud data 60c in the divided grid ( step 62).
FIG. 6 is an image diagram of the evaluation target area vertex extraction step 62 .
The server determines whether or not the vertex extracted in the evaluation target area vertex extraction step 62 is a tree vertex (step 63). The determination in the evaluation target area standing tree vertex determination step 63 is the same as in the representative area standing tree vertex determination step 55 .
The server calculates the height of the tree apex based on the landform data 60c for the apex determined to be the tree apex in the evaluation target area tree apex determination step 63 (step 64).
The server determines the number of standing tree vertices in the evaluation target area determined to be standing tree vertices in the evaluation target area tree vertex determination step 63 as the calculated number of standing trees (step 65).
The server can calculate the timber volume by calculating the height of each tree from the ground surface in the tree vertex calculation step 64 (step 66).
In this way, the number of standing trees is calculated in the calculated number of standing trees determination step 65, and the volume of wood is calculated in the volume of wood volume calculation step 66, so that standing trees in the forest area can be evaluated.
Conical conifers such as Japanese cedar and Japanese cypress are suitable for standing trees to be evaluated in this embodiment.

FIG. 7 is a block diagram showing an apparatus for implementing the boundary survey method according to this embodiment.
As shown in FIG. 7, an unmanned aerial vehicle 10, a compass surveying device 20, and a processing device 30 are used in the boundary surveying method of the present embodiment.

An unmanned aerial vehicle 10 is equipped with an imaging device 11 , a global navigation satellite system receiver 12 , an imaging position measuring device 13 , and an imaging direction measuring device 14 .
The unmanned aerial vehicle 10 is an aircraft also called a drone, and a multicopter type helicopter having a plurality of rotor blades is suitable for the unmanned aerial vehicle 10 .
The image capturing device 11 may be one that captures a still image or one that captures a moving image. The photographing device 11 photographs an area including the reference point 1 . A plurality of still images are acquired from different flight positions with respect to one reference point 1 .
The global navigation satellite system receiver 12 measures the current position and flight height of the unmanned aerial vehicle 10 using GNSS such as GPS, GLONASS, and Galileo. Use the data to fly on a preset flight route.
The shooting position measuring device 13 measures the shooting position of the shooting device 11 . The earth navigation satellite system receiver 12 can be used for the photographing position measuring device 13 .
The shooting direction measuring device 14 measures the optical axis direction of the lens center of the shooting device 11 . The shooting direction measuring device 14 measures the optical axis direction with respect to the unmanned aerial vehicle 10 with an angle sensor or the like, and the flight direction of the unmanned aerial vehicle 10 can be measured using measurement data from the earth navigation satellite system receiving device 12 or a gyro sensor. The photographing direction of the photographing device 11 can be measured from the flight direction of the unmanned aerial vehicle 10 and the optical axis direction with respect to the unmanned aerial vehicle 10 .

The compass surveying device 20 is a device for measuring azimuth and elevation angle, preferably a digital compass using a digital compass, and preferably a device further equipped with a laser rangefinder. The compass surveying device 20 surveys a reference pile serving as a reference point 1 and a boundary pile 2 installed along the boundary.

The processing device 30 has a flight route determination unit 31 , a photographed data storage unit 32 , a reference point coordinate data calculation unit 33 , a survey data storage unit 34 and a boundary line calculation unit 35 .
The flight path determination unit 31 determines the flight path of the unmanned aerial vehicle 10 . A flight path is determined such that the unmanned aerial vehicle 10 flies along a boundary or along a reference point 1 .
The photographing data storage unit 32 stores the photographing data obtained by the photographing device 11, the photographing position data measured by the photographing position measuring device 13, and the photographing direction data measured by the photographing direction measuring device 14. Remember. Therefore, each photographing data is stored together with the photographing position data at the time of photographing and the photographing direction data at the time of photographing.
The reference point coordinate data calculator 33 calculates the coordinate data of the reference point 1 using the photographing data, the photographing position data, and the photographing direction data stored in the photographing data storage unit 32 .
The survey data storage unit 34 stores the survey data of the reference point 1 and the boundary pile 2 acquired by the compass survey device 20 .
The boundary line calculation unit 35 calculates the boundary line from the coordinate data of the reference point 1 calculated by the reference point coordinate data calculation unit 33 and the survey data stored in the survey data storage unit 34 .

FIG. 8 is a flow chart showing the processing flow of the boundary survey method.
In the reference point installation step 1, a reference point 1 is installed at a boundary to be surveyed or in the vicinity of the boundary and at a position that can be photographed from the sky.
When setting the reference point 1 in the reference point setting step 1, it is preferable to measure the coordinate data of the reference point 1 (step 2). The coordinate data of the reference point 1 can be measured by a global navigation satellite system receiver 12 using GNSS such as GPS, GLONASS, and Galileo.
The coordinate data of the reference point 1 measured in step 2 is stored in the storage unit (step 3), and the coordinate data of the reference point 1 can be used to determine the flight path in the flight path determination step 4.

Flight path determination step 4 determines a flight path along boundaries or reference points 1 .
The unmanned aerial vehicle 10 flies along the flight path determined in flight path determination step 4 (flight step 5).
The photographing step 6 is performed while the unmanned aerial vehicle 10 is in flight. In the photographing step 6, an area including the reference point 1 is photographed by the photographing device 11 mounted on the unmanned aerial vehicle 10. FIG. In photographing, a plurality of pieces of photographing data are acquired from a plurality of positions with respect to one reference point 1 .
At the time of photographing in the photographing step 6, the photographing position data and the photographing direction data of the photographing device 11 are measured (photographing information measurement step 7).
In the photographing data storage step 8, together with the photographing data photographed in the photographing step 6, photographing position data and photographing direction data measured in the photographing information measuring step 7 are stored. The photographing data, the photographing position data, and the photographing direction data stored in the photographing data storage step 8 may be transferred to the photographing data storage section 32 of the processing device 30 after the flight of the unmanned aerial vehicle 10 is completed.

In the reference point coordinate determining step 9, the coordinate data of the reference point 1 is calculated and determined by the reference point coordinate data calculation unit 33 using the photographing data, the photographing position data, and the photographing direction data stored in the photographing data storage step 8. do.
The determined coordinate data of the reference point 1 is stored (step 10) and used for surveying in step 11 of compass surveying.

In the compass surveying step 11, the determined coordinate data of the reference point 1 is used to obtain the survey data of the reference point 1 and the boundary pile 2. FIG.
As in this embodiment, when the coordinate data of the reference point 1 is determined in advance and the compass survey is performed using the coordinate data of the reference point 1, the boundary line can be determined by the compass survey step 11 ( step 12).

FIG. 9 is an explanatory diagram showing boundaries and reference points in the same boundary survey method.
As shown in FIG. 9, the boundary stake 2 is installed along the boundary, and the reference point 1 is installed near the boundary at a position where there are no obstacles such as trees and can be photographed from above. The reference point 1 is preferably set at the boundary where there are no obstacles such as trees.
By setting as many reference points 1 as possible on or near the boundary, it is possible to reduce deterioration in accuracy due to compass surveying.

As described above, according to this embodiment, the reference point 1 is set at a position that can be photographed from the sky. By determining the boundary line from the coordinate data of the reference point 1 and the survey data, it is possible to survey the boundary line particularly in a forest area with high efficiency and high accuracy.
Further, according to this embodiment, in the reference point installation step 1, the coordinate data of the reference point 1 is measured using the earth navigation satellite system receiver 12, and in the flight path determination step 4, the measured coordinates of the reference point 1 By determining the flight path using the data, it is possible to determine a flight path at a lower altitude along the reference point 1 .

FIG. 10 is a flow chart showing the processing flow of the boundary survey method according to another embodiment. Note that the same processing as in FIG. 8 is given the same reference numerals, and the description thereof is omitted.
In this embodiment, when the reference point 1 is installed in the reference point installation step 1, the boundary stake 2 is installed (step 21), and the survey data of the reference point 1 and the boundary stake 2 is acquired (compass survey step 11).
The survey data of the reference point 1 and the boundary stakes 2 acquired in the compass survey step 11 are temporarily stored (step 22), and after the coordinate data of the reference point 1 are determined in the reference point coordinate determination step 9, the survey data are recalculated. (step 23), and the boundary line is determined (step 12).

As in this embodiment, the compass survey step 11 is performed together with the reference point installation step 1, and the survey data acquired in the compass survey step 11 is used with the coordinate data of the reference point 1 determined in the reference point coordinate determination step 9. By recalculating and fixing the boundary line, since the survey is performed when the reference point 1 is installed, there is no need to enter the survey location twice, and workability is improved.

The present invention is suitable for surveying in forests with large slopes and undulations and many obstacles such as trees.

REFERENCE SIGNS LIST 1 reference point 2 boundary stake 10 unmanned aerial vehicle 11 imaging device 12 earth navigation satellite system receiver 13 imaging position measurement device 14 imaging direction measurement device 20 compass surveying device 30 processing device 31 flight path determination unit 32 imaging data storage unit 33 reference point coordinates Data calculation unit 34 Survey data storage unit 35 Boundary line calculation unit 60a, 60b Reference point 60c Terrain data 60d Point cloud data

Claims (5)

A method for evaluating standing trees in a forest area using photographed data photographed from above,
the server
a point cloud data generation step of generating point cloud data from the imaging data;
a representative area vertex extracting step of dividing a representative area, which is a part of the evaluation target area, into a grid with a reference value, and extracting the highest position data as a vertex from the point cloud data in the divided grid;
a representative area tree vertex determination step of determining whether or not the vertex extracted in the representative area vertex extraction step is a tree vertex;
a representative area standing tree vertex count calculating step for calculating the number of standing tree vertices in the representative area determined to be the standing tree vertices in the standing tree vertex determining step;
a standing tree number comparison step of comparing the number of standing tree vertices in the representative area calculated in the step of calculating the number of standing tree vertices in the representative area with the number of actual standing trees in the representative area;
When the difference between the number of standing tree vertices in the representative area and the actual number of standing trees compared in the standing tree number comparison step exceeds a threshold, the difference between the number of standing tree vertices in the representative area and the actual number of standing trees is within the threshold. a reference value changing step of changing the reference value such that
The area to be evaluated is divided into the grid using the changed reference value changed in the step of changing the reference value, and the highest position data is extracted as the vertex from the point cloud data in the divided grid. an interior vertex extraction step;
an evaluation target area tree vertex determination step of determining whether or not the vertex extracted in the evaluation target area vertex extraction step is the tree vertex;
and a calculated standing tree number determining step of determining the number of standing tree vertices in the evaluation target area determined to be the standing tree vertices in the evaluation target area standing tree vertex determining step as the calculated standing tree number. Evaluation method. the server
a terrain data corresponding step of aligning the terrain data of the evaluation target area, which is different from the point cloud data, with the point cloud data based on the reference point from which the terrain was captured from the point cloud data;
a tree vertex calculation step of calculating the height of the tree vertex determined as the tree vertex in the evaluation target area tree vertex determination step based on the terrain data;
2. The method for evaluating standing trees in a forest area according to claim 1, further comprising a timber volume calculation step of calculating a timber volume using the height of the tree apex calculated in the standing tree apex calculation step. . In the boundary survey method suitable for specifying the evaluation target area in the method for evaluating standing trees in a forest area according to claim 1 or claim 2,
a reference point setting step of setting a reference point at a position that can be photographed from the sky on a boundary to be surveyed or in the vicinity of the boundary;
a flight path determination step of determining a flight path along the boundary;
a flight step of flying the unmanned aerial vehicle along the flight path determined in the flight path determination step;
a photographing step of photographing an area including the reference point with a photographing device mounted on the unmanned aerial vehicle in the flying step;
a shooting information measuring step of measuring shooting position data and shooting direction data of the shooting device at the time of shooting in the shooting step;
a photographing data storage step of storing the photographing position data and the photographing direction data measured in the photographing information measuring step together with the photographing data photographed in the photographing step;
a reference point coordinate determination step of determining the coordinate data of the reference point using the imaging data, the imaging position data, and the imaging direction data stored in the imaging data storage step;
a compass survey step of acquiring survey data of the boundary and the reference point;
A boundary line surveying method, wherein a boundary line is determined from the coordinate data of the reference point determined in the reference point coordinate determining step and the survey data obtained in the compass surveying step. In the reference point installation step, coordinate data of the reference point is measured using a global navigation satellite system receiver;
4. The boundary survey method according to claim 3, wherein, in the flight route determination step, the flight route is determined using the coordinate data of the measured reference points. performing the compass surveying step together with the reference point setting step;
4. The boundary line is determined by recalculating the survey data acquired in the compass survey step using the coordinate data of the reference point determined in the reference point coordinate determination step. The boundary survey method according to claim 4.

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