CN108564583B

CN108564583B - Sample plot monitoring method, device and system

Info

Publication number: CN108564583B
Application number: CN201810372096.2A
Authority: CN
Inventors: 汤欣; 梁东成
Original assignee: Guangdong Yunlin Information Engineering Technology Co ltd
Current assignee: Guangdong Yunlin Information Engineering Technology Co., Ltd.
Priority date: 2018-04-23
Filing date: 2018-04-23
Publication date: 2020-12-01
Anticipated expiration: 2038-04-23
Also published as: CN108564583A

Abstract

The invention provides a sample plot monitoring method, a device and a system, wherein the sample plot comprises a plurality of unit sample plots with equal areas, the method is applied to a monitoring platform, the monitoring platform is in wireless communication with an unmanned aerial vehicle carrying an image acquisition device, and the method comprises the following steps: for each unit sample plot, sending longitude and latitude range information of a preset unit sample plot and longitude and latitude position information preset by each tree to be detected positioned in the unit sample plot; receiving a unit sample plot image which is sent by an unmanned aerial vehicle and corresponds to longitude and latitude range information and is acquired by an image acquisition device, and tree height information and a tree image which respectively correspond to longitude and latitude position information; according to the unit sample plot image, the tree height information, the tree image and the preset species characteristic information, the under-forest vegetation factor in the sample plot and the breast height factor and the crown width factor of each tree to be detected are determined, the technical problem that the monitoring process in the prior art is low in efficiency is solved, and the technical effect of improving the monitoring process efficiency is achieved.

Description

Sample plot monitoring method, device and system

Technical Field

The present invention relates to the field of sample plot monitoring technologies, and in particular, to a sample plot monitoring method, device, and system.

Background

The plot refers to a region of limited range for vegetation survey sampling. By monitoring the sample plot, the composition structure, species diversity and the like of a typical colony in the sample plot can be known.

In practical applications, technicians need to enter the sample plot themselves and monitor the vegetation in the sample plot by sample plot monitoring factors (breast diameter, tree height, crown width, etc.). Because the monitoring is carried out manually, a large amount of time is consumed to complete the monitoring process of the sample plot in the monitoring process, and the problem of low efficiency of the monitoring process is caused.

Disclosure of Invention

In view of the above, the present invention provides a sample plot monitoring method, device and system to alleviate the technical problem of low efficiency of the monitoring process in the prior art.

In a first aspect, an embodiment of the present invention provides a sample plot monitoring method, where the sample plot includes a plurality of unit sample plots with equal areas, the method is applied to a monitoring platform, and the monitoring platform wirelessly communicates with an unmanned aerial vehicle carrying an image acquisition device, and the method includes:

for each unit sample plot, sending preset longitude and latitude range information of the unit sample plot and preset longitude and latitude position information of each tree to be detected positioned in the unit sample plot;

receiving a unit sample plot image which is sent by the unmanned aerial vehicle and corresponds to the longitude and latitude range information and is acquired by the image acquisition device, and tree height information and a tree image which respectively correspond to the longitude and latitude position information;

and determining the under-forest vegetation factor in the sample plot and the breast-height factor and crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information.

With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where determining the understory vegetation factor in the sample plot according to the unit sample plot image and the species characteristic information includes:

for each frame of image in the unit sample plot image, performing image segmentation on each frame of image by using a preset image segmentation algorithm to obtain a binary image;

filtering the binary image by using a preset filtering algorithm to obtain a filtered binary image;

extracting the contour of the filtering binary image by using a preset contour extraction operator to obtain a contour binary image;

and in the species characteristic information, determining that the species corresponding to the contour consistent with the contour binary image is the under-forest vegetation factor.

With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the filtering algorithm includes: a mean filtering algorithm and a median filtering algorithm.

With reference to the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the tree height information includes: height of the whole tree and height under the branches.

With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the tree image includes: the tree breast height diameter image acquired by the image acquisition device at a preset vertical acquisition distance and a preset horizontal acquisition distance is used for determining the breast height diameter factor of each tree to be detected according to the tree image, and the method comprises the following steps:

determining the vertical side edge simulation length of the tree breast-height diameter image according to the horizontal acquisition distance and a preset monitoring angle of the image acquisition device;

carrying out image segmentation on the tree breast-height diameter image by using the image segmentation algorithm to obtain a breast-height diameter binary image;

filtering the two-value image of the chest diameter by using the filtering algorithm to obtain a filtered two-value image of the chest diameter;

extracting the contour of the filtering chest diameter binary image by using the contour extraction operator to obtain a chest diameter contour binary image;

adding a horizontal line passing through a central point on the thoracic diameter contour binary image, wherein the horizontal line is intersected with the thoracic diameter contour to obtain a first intersection point and a second intersection point;

determining a first pixel length between the first intersection point and the second intersection point according to the pixel coordinates of the first intersection point and the pixel coordinates of the second intersection point;

determining a second pixel length of the vertical side according to the pixel coordinates of two end points of the vertical side of the chest diameter contour binary image;

and determining the chest diameter factor according to the vertical side edge simulation length, the first pixel length and the second pixel length.

With reference to the first aspect, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where the determining, according to the horizontal acquisition distance and a preset monitoring angle of the image acquisition device, a vertical side simulated length of the tree breast diameter image includes:

dividing the monitoring angle by two to obtain a half monitoring angle;

calculating the tangent value of the half monitoring angle, and multiplying the obtained result by the horizontal acquisition distance to obtain a half vertical side simulation length;

and multiplying the half vertical side simulation length by two to obtain the vertical side simulation length by calculation.

With reference to the first aspect, an embodiment of the present invention provides a sixth possible implementation manner of the first aspect, where the tree image further includes: the tree crown width image that image acquisition device gathered, tree height information still includes: determining the crown width factor of each tree to be detected according to the tree height information and the tree image, wherein the height from the crown of the tree to be detected to the ground and the highest height when the tree crown width image is obtained comprise:

subtracting the height of the crown from the ground by using the highest height, and calculating to obtain the height of the crown from the machine;

calculating the tangent value of the half monitoring angle, and multiplying the obtained result by the height of the crown from the machine to obtain a half side simulation length;

carrying out image segmentation on the tree crown image by using the image segmentation algorithm to obtain a crown binary image;

filtering the crown binary image by using the filtering algorithm to obtain a filtered crown binary image;

extracting the contour of the filtering coronal binary image by using the contour extraction operator to obtain a coronal contour binary image;

drawing a line vertical to the side edge from the central point of the coronal outline binary image, wherein the intersection point of the vertical line and the side edge is a third intersection point;

determining a third pixel length between the central point and the third intersection point according to the pixel coordinate of the central point and the pixel coordinate of the third intersection point;

connecting line segments between any two points on the crown width outline to obtain a plurality of connecting line segments;

determining two end points of the line segment with the longest length as a fourth intersection point and a fifth intersection point respectively in the plurality of connecting line segments;

determining a fourth pixel length between the fourth intersection point and the fifth intersection point according to the pixel coordinate of the fourth intersection point and the pixel coordinate of the fifth intersection point;

and determining the crown factor according to the third pixel length, the fourth pixel length and the half-side simulation length.

In a second aspect, an embodiment of the present invention further provides a sample plot monitoring apparatus, including: the device comprises a sending module, a receiving module and a determining module;

the sending module is used for sending the preset longitude and latitude range information of the unit sample plot and the preset longitude and latitude position information of each tree to be detected positioned in the unit sample plot for each unit sample plot;

the receiving module is used for receiving the unit sample plot image which is sent by the unmanned aerial vehicle and corresponds to the longitude and latitude range information and is acquired by the image acquisition device, and the tree height information and the tree image which respectively correspond to the longitude and latitude position information;

the determining module is used for determining the under-forest vegetation factor in the sample plot and the breast-height factor and crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information.

In a third aspect, an embodiment of the present invention further provides a sample plot monitoring system, including: a plurality of drones carrying image acquisition devices and a monitoring platform applying the method according to any one of the first aspect.

In a fourth aspect, the present invention also provides a computer-readable medium having non-volatile program code executable by a processor, where the program code causes the processor to execute the method according to any one of the first aspect.

The embodiment of the invention has the following beneficial effects: the embodiment of the invention provides a sample plot monitoring method, wherein the sample plot comprises a plurality of unit sample plots with equal areas, the method is applied to a monitoring platform, the monitoring platform is in wireless communication with an unmanned aerial vehicle carrying an image acquisition device, and the method comprises the following steps: for each unit sample plot, sending preset longitude and latitude range information of the unit sample plot and preset longitude and latitude position information of each tree to be detected positioned in the unit sample plot; receiving a unit sample plot image which is sent by the unmanned aerial vehicle and corresponds to the longitude and latitude range information and is acquired by the image acquisition device, and tree height information and a tree image which respectively correspond to the longitude and latitude position information; and determining the under-forest vegetation factor in the sample plot and the breast-height factor and crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information.

Therefore, when sample plots are to be monitored, for each unit sample plot, the monitoring platform sends preset longitude and latitude range information of the unit sample plot and preset longitude and latitude position information of each tree to be detected positioned in the unit sample plot; receiving a unit sample plot image which is sent by the unmanned aerial vehicle and corresponds to the longitude and latitude range information and is acquired by the image acquisition device, and tree height information and a tree image which respectively correspond to the longitude and latitude position information; determining under-forest vegetation factors in the sample plot and the breast-height factor and crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information, therefore, technicians can determine the under-forest vegetation factor in the sample plot and the breast-height factor and crown factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and the preset species characteristic information received by the monitoring platform without entering the sample plot in person, so that the problem that the monitoring process of the sample plot can be completed only by consuming a large amount of time due to manual monitoring is avoided, therefore, the technical problem of low efficiency of the monitoring process in the prior art is solved, and the technical effect of improving the efficiency of the monitoring process is achieved.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a first flowchart of a sample plot monitoring method according to an embodiment of the present invention;

FIG. 2 is a second flowchart of a sample plot monitoring method according to an embodiment of the present invention;

FIG. 3 is a third flowchart of a sample-monitoring method according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a sample-chamber monitoring system according to an embodiment of the present invention.

Detailed Description

To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Currently, a plot refers to a region of limited range for vegetation survey sampling. By monitoring the sample plot, the composition structure, species diversity and the like of a typical colony in the sample plot can be known.

In practical applications, technicians need to enter the sample plot themselves and monitor the vegetation in the sample plot by sample plot monitoring factors (breast diameter, tree height, crown width, etc.). Because all the monitoring is carried out manually, in the monitoring process, a large amount of time is consumed to complete the sample plot monitoring process, so that the problem of low efficiency of the monitoring process is caused.

In order to facilitate understanding of the embodiment, a sample plot monitoring method disclosed in the embodiment of the present invention is first described in detail, where the sample plot includes a plurality of unit sample plots with equal areas, and the method is applied to a monitoring platform, where the monitoring platform wirelessly communicates with an unmanned aerial vehicle carrying an image capturing device, as shown in fig. 1, and the sample plot monitoring method may include the following steps.

For example, the pattern may include a plurality of unit patterns having equal areas, and the pattern is described as including four unit patterns. The method comprises the following steps: unit pattern 1, unit pattern 2, unit pattern 3, and unit pattern 4. The areas of the unit pattern 1, the unit pattern 2, the unit pattern 3, and the unit pattern 4 are equal. The position information of the sample plot and the unit sample plot is set at the time of initial monitoring.

Step S101, for each unit sample plot, sending preset longitude and latitude range information of the unit sample plot and preset longitude and latitude position information of each tree to be detected in the unit sample plot.

For example, when the longitude range of the sample plot is (a1, a3) and the latitude range is (b1, b3), the longitude and latitude range information may be as shown in table 1.

TABLE 1

Number of unit sample	Longitude range	Latitude range
			1	(a1,a2)	(b2,b3)
2	(a2,a3)	(b2,b3)
			3	(a1,a2)	(b1,b2)
4	(a2,a3)	(b1,b2)

Wherein the content of the first and second substances,

illustratively, each of the unit plots may include a plurality of trees to be detected. For each unit sample plot, the example that the unit sample plot 1 includes five trees to be detected is described, and the longitude and latitude position information may be as shown in table 2.

TABLE 2

Tree numbering	Latitude and longitude position
		1	(m1,n1)
2	(m2,n2)
		3	(m3,n3)
4	(m4,n4)
		5	(m5,n5)

The longitude positions in table 2 are all within a longitude range (a1, a2), and the latitude positions are all within a latitude range (b2, b 3).

And step S102, receiving a unit sample plot image which is sent by the unmanned aerial vehicle and corresponds to the longitude and latitude range information and is acquired by the image acquisition device, and tree height information and a tree image which respectively correspond to the longitude and latitude position information.

For example, the tree height information may include: height of the whole tree and height under the branches.

And S103, determining an under-forest vegetation factor in the sample plot and a breast-height factor and a crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information.

For example, as shown in fig. 2, determining the under-forest vegetation factor in the plot according to the unit plot image and the species characteristic information may include the following steps.

In step S201, for each frame of image in the unit sample area image, a preset image segmentation algorithm is used to perform image segmentation on each frame of image, so as to obtain a binary image.

Illustratively, the image segmentation algorithm may be a histogram segmentation algorithm, an optimal thresholding algorithm, or an Otsu thresholding algorithm.

And S202, performing filtering processing on the binary image by using a preset filtering algorithm to obtain a filtered binary image.

Illustratively, the filtering algorithm may include: a mean filtering algorithm and a median filtering algorithm.

And step S203, extracting the contour of the filtering binary image by using a preset contour extraction operator to obtain a contour binary image.

Illustratively, the contour extraction operator may be a Roberts operator, a Sobel operator, a Prewitt operator, or a Laplacian operator.

And step S204, determining the species corresponding to the contour consistent with the contour binary image as the under-forest vegetation factor in the species characteristic information.

Illustratively, the species characteristic information includes N species for example. The species characteristic information may be as shown in table 3.

TABLE 3

Illustratively, there is a one-to-one correspondence between profiles and species.

For example, image segmentation may be performed based on flower features to obtain a flower binary image, then the flower binary image is filtered and contour extraction is performed to obtain a flower contour binary image, and in the species feature information, a species corresponding to a flower contour consistent with the flower contour binary image is determined to be the under-forest vegetation factor. The species characteristic information may be as shown in table 4.

TABLE 4

For example, image segmentation may be performed based on leaf features to obtain a leaf binary image, then the leaf binary image is filtered and contour extraction is performed to obtain a leaf contour binary image, and in the species feature information, it is determined that a species corresponding to a leaf contour consistent with the leaf contour binary image is the under-forest vegetation factor. The species characteristic information may be as shown in table 5.

TABLE 5

Illustratively, the tree image includes: the tree breast height diameter image acquired by the image acquisition device at the preset vertical acquisition distance and the preset horizontal acquisition distance, as shown in fig. 3, may include the following steps of determining the breast height diameter factor of each tree to be detected according to the tree image.

And S301, determining the vertical side edge simulation length of the tree breast diameter image according to the horizontal acquisition distance and a preset monitoring angle of the image acquisition device.

Illustratively, the vertical acquisition distance may be set to 1.3 meters.

For example, the determining the simulated vertical side length of the tree breast diameter image according to the horizontal collecting distance and the preset monitoring angle of the image collecting device may include the following steps.

And dividing the monitoring angle by two to obtain a half monitoring angle.

For example, the monitoring angle is known, and the monitoring angle is described as α. Dividing the monitoring angle alpha by two to obtain a half monitoring angle

And calculating the tangent value of the half monitoring angle, and multiplying the obtained result by the horizontal acquisition distance to obtain the half vertical side simulation length.

For example, the horizontal acquisition distance may be set to a meter, and then a simulated length of half of the vertical side may be obtained

Illustratively, when one half of the vertical side is modeled as having a length of

Then, the vertical side simulation length can be calculated as

And S302, carrying out image segmentation on the tree breast-height diameter image by using the image segmentation algorithm to obtain a breast-height diameter binary image.

And step S303, carrying out filtering processing on the chest diameter binary image by using the filtering algorithm to obtain a filtered chest diameter binary image.

And S304, extracting the contour of the filtering chest diameter binary image by using the contour extraction operator to obtain a chest diameter contour binary image.

And S305, adding a horizontal line passing through the central point on the thoracic diameter contour binary image, and intersecting the horizontal line and the thoracic diameter contour to obtain a first intersection point and a second intersection point.

Step S306, determining a first pixel length between the first intersection point and the second intersection point according to the pixel coordinate of the first intersection point and the pixel coordinate of the second intersection point.

Step S307, determining a second pixel length of the vertical side according to the pixel coordinates of the two end points of the vertical side of the chest diameter contour binary image.

Step S308, determining the chest diameter factor according to the vertical side edge simulation length, the first pixel length and the second pixel length.

Illustratively, when the vertical side simulates a length of

When the length of the first pixel is p and the length of the second pixel is q, determining the chest diameter factor as

And (4) rice.

Illustratively, the tree image further includes: the tree crown width image that image acquisition device gathered, tree height information still includes: the method comprises the following steps of determining the height of the crown of the tree to be detected from the ground and the highest height when the crown width image of the tree is obtained, and determining the crown width factor of each tree to be detected according to the height information of the tree and the tree image.

And subtracting the height of the crown from the ground by using the highest height, and calculating to obtain the height of the crown from the machine.

For example, when the maximum height of the image of the crown of the tree is 6 meters and the height of the crown from the ground is 4 meters, the height of the crown from the machine can be calculated to be 2 meters.

And calculating the tangent value of the half monitoring angle, and multiplying the obtained result by the height of the crown from the machine to obtain the half side simulation length.

Illustratively, when the crown is d meters from the machine height, the simulated length of one half side is

And carrying out image segmentation on the tree crown image by using the image segmentation algorithm to obtain a crown binary image.

And carrying out filtering processing on the crown binary image by using the filtering algorithm to obtain a filtering crown binary image.

And extracting the contour of the filtering crown binary image by using the contour extraction operator to obtain a crown contour binary image.

And drawing a line vertical to the side edge from the central point of the coronal outline binary image, wherein the intersection point of the vertical line and the side edge is a third intersection point.

And determining a third pixel length between the central point and the third intersection point according to the pixel coordinate of the central point and the pixel coordinate of the third intersection point.

And connecting the line segments between any two points on the crown width outline to obtain a plurality of connecting line segments.

And determining two end points of the line segment with the longest length as a fourth intersection point and a fifth intersection point respectively in the plurality of connecting line segments.

And determining a fourth pixel length between the fourth intersection point and the fifth intersection point according to the pixel coordinate of the fourth intersection point and the pixel coordinate of the fifth intersection point.

Illustratively, when half the side is modeled as having a length of

When the length of the third pixel is e and the length of the fourth pixel is f, determining the crown factor as

And (4) rice.

In an embodiment of the present invention, an embodiment of the present invention provides a sample plot monitoring method, where the sample plot includes a plurality of unit sample plots with equal areas, the method is applied to a monitoring platform, the monitoring platform wirelessly communicates with an unmanned aerial vehicle carrying an image acquisition device, and the method includes: for each unit sample plot, sending preset longitude and latitude range information of the unit sample plot and preset longitude and latitude position information of each tree to be detected positioned in the unit sample plot; receiving a unit sample plot image which is sent by the unmanned aerial vehicle and corresponds to the longitude and latitude range information and is acquired by the image acquisition device, and tree height information and a tree image which respectively correspond to the longitude and latitude position information; and determining the under-forest vegetation factor in the sample plot and the breast-height factor and crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information.

In another embodiment of the present invention, a sample pattern monitoring apparatus disclosed in the embodiment of the present invention is described in detail, including: the device comprises a sending module, a receiving module and a determining module;

In another embodiment of the present invention, a sample monitoring system disclosed in the embodiment of the present invention is described in detail, including: a plurality of unmanned aerial vehicles carrying image acquisition devices and a monitoring platform applying the method according to any of the above embodiments.

For example, the sample plot monitoring system includes four drones carrying image capturing devices. As shown in fig. 4, the system for monitoring the sample may include: four unmanned aerial vehicles carrying image acquisition devices and a monitoring platform 41. Four unmanned aerial vehicles that carry image acquisition device do respectively: drone 42, drone 43, drone 44 and drone 45. The monitoring platform 41 is in wireless communication with the drone 42, the drone 43, the drone 44 and the drone 45, respectively.

In a further embodiment of the present invention, a computer-readable medium having a non-volatile program code executable by a processor and causing the processor to perform any one of the methods of the above embodiments is disclosed.

Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present invention.

The device provided by the embodiment of the present invention has the same implementation principle and technical effect as the method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the method embodiments without reference to the device embodiments.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In all examples shown and described herein, any particular value should be construed as merely exemplary, and not as a limitation, and thus other examples of example embodiments may have different values.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.

In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

The computer program product for performing the sample-area monitoring method provided in the embodiment of the present invention includes a computer-readable storage medium storing a nonvolatile program code executable by a processor, where instructions included in the program code may be used to execute the method described in the foregoing method embodiment, and specific implementation may refer to the method embodiment, which is not described herein again.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. The sample plot monitoring method is characterized in that the sample plot comprises a plurality of unit sample plots with equal areas, the method is applied to a monitoring platform, the monitoring platform is in wireless communication with an unmanned aerial vehicle carrying an image acquisition device, and the method comprises the following steps:

determining an under-forest vegetation factor in the sample plot and a breast-height factor and a crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information;

determining the understory vegetation factor within the plot from the unit plot image and the species characteristic information, comprising:

determining species corresponding to the contour consistent with the contour binary image as the under-forest vegetation factor in the species characteristic information;

the tree image includes: the tree breast height diameter image acquired by the image acquisition device at a preset vertical acquisition distance and a preset horizontal acquisition distance is used for determining the breast height diameter factor of each tree to be detected according to the tree image, and the method comprises the following steps:

2. The method of claim 1, wherein the filtering algorithm comprises: a mean filtering algorithm and a median filtering algorithm.

3. The method of claim 2, wherein the tree height information comprises: height of the whole tree and height under the branches.

4. The sample plot monitoring method of claim 1, wherein determining the vertical side simulated length of the tree breast path image according to the horizontal acquisition distance and a preset monitoring angle of the image acquisition device comprises:

dividing the monitoring angle by two to obtain a half monitoring angle;

multiplying the half of the vertical side simulation length by two to obtain the vertical side simulation length by calculation;

the tree image further includes: the tree crown width image that image acquisition device gathered, tree height information still includes: determining the crown width factor of each tree to be detected according to the tree height information and the tree image, wherein the height from the crown of the tree to be detected to the ground and the highest height when the tree crown width image is obtained comprise:

5. A sample plot monitoring device, comprising: the device comprises a sending module, a receiving module and a determining module;

the determining module is used for determining the under-forest vegetation factor in the sample plot and the breast-height factor and crown width factor of each tree to be detected according to the unit sample plot image, the tree height information, the tree image and preset species characteristic information;

the determination module is further to:

the tree image includes: the image acquisition device acquires tree breast diameter images at a preset vertical acquisition distance and a preset horizontal acquisition distance; the determining module comprises:

the length determining unit is used for determining the vertical side edge simulation length of the tree breast diameter image according to the horizontal acquisition distance and a preset monitoring angle of the image acquisition device;

the binary image determining unit is used for carrying out image segmentation on the tree breast diameter image by using the image segmentation algorithm to obtain a breast diameter binary image; filtering the two-value image of the chest diameter by using the filtering algorithm to obtain a filtered two-value image of the chest diameter; extracting the contour of the filtering chest diameter binary image by using the contour extraction operator to obtain a chest diameter contour binary image;

the intersection point determining unit is used for adding a horizontal line passing through a central point on the thoracic diameter contour binary image, and the horizontal line is intersected with the thoracic diameter contour to obtain a first intersection point and a second intersection point;

a pixel length determination unit, configured to determine a first pixel length between the first intersection point and the second intersection point according to the pixel coordinate of the first intersection point and the pixel coordinate of the second intersection point; determining a second pixel length of the vertical side according to the pixel coordinates of two end points of the vertical side of the chest diameter contour binary image;

and the breast diameter factor determining unit is used for determining the breast diameter factor according to the vertical side edge simulation length, the first pixel length and the second pixel length.

6. A sample plot monitoring system, comprising: a plurality of drones carrying image acquisition devices and a monitoring platform applying the method according to any one of claims 1 to 4.

7. A computer-readable medium having non-volatile program code executable by a processor, wherein the program code causes the processor to perform the method of any of claims 1-4.