CN113640232A - Identification method for grassland toxic and harmful grass - Google Patents
Identification method for grassland toxic and harmful grass Download PDFInfo
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- CN113640232A CN113640232A CN202110765507.6A CN202110765507A CN113640232A CN 113640232 A CN113640232 A CN 113640232A CN 202110765507 A CN202110765507 A CN 202110765507A CN 113640232 A CN113640232 A CN 113640232A
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- 231100000331 toxic Toxicity 0.000 title claims abstract description 40
- 230000002588 toxic effect Effects 0.000 title claims abstract description 40
- 238000000034 method Methods 0.000 title claims abstract description 24
- 244000025254 Cannabis sativa Species 0.000 title claims description 34
- 230000003595 spectral effect Effects 0.000 claims abstract description 82
- 230000007246 mechanism Effects 0.000 claims abstract description 36
- 241000209504 Poaceae Species 0.000 claims abstract description 30
- 238000012545 processing Methods 0.000 claims abstract description 18
- 238000007781 pre-processing Methods 0.000 claims abstract description 17
- 238000001228 spectrum Methods 0.000 claims description 15
- 241000196324 Embryophyta Species 0.000 claims description 10
- 230000001473 noxious effect Effects 0.000 claims description 9
- 231100000252 nontoxic Toxicity 0.000 claims description 8
- 230000003000 nontoxic effect Effects 0.000 claims description 8
- 231100000572 poisoning Toxicity 0.000 claims description 5
- 230000000607 poisoning effect Effects 0.000 claims description 5
- 241000607479 Yersinia pestis Species 0.000 claims 2
- 231100000611 venom Toxicity 0.000 claims 2
- 241001148683 Zostera marina Species 0.000 claims 1
- 239000002574 poison Substances 0.000 description 6
- 231100000614 poison Toxicity 0.000 description 6
- 230000004308 accommodation Effects 0.000 description 4
- 239000000463 material Substances 0.000 description 3
- 231100000419 toxicity Toxicity 0.000 description 3
- 230000001988 toxicity Effects 0.000 description 3
- 240000007651 Rubus glaucus Species 0.000 description 2
- 235000011034 Rubus glaucus Nutrition 0.000 description 2
- 235000009122 Rubus idaeus Nutrition 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000006866 deterioration Effects 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012876 topography Methods 0.000 description 2
- 241001671653 Aconitum carmichaelii Species 0.000 description 1
- 241001113925 Buddleja Species 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013144 data compression Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000008034 disappearance Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000013277 forecasting method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 241000894007 species Species 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N2021/1765—Method using an image detector and processing of image signal
- G01N2021/177—Detector of the video camera type
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
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- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The application provides a method for identifying toxic and harmful grasses in grassland, which comprises the following steps: acquiring spectral information in a preset area of a field grassland by using an aircraft carrying a hyperspectral camera; preprocessing the spectral information by using a processing mechanism carried by an aircraft to obtain target information; and storing the target information by utilizing a storage mechanism carried by the aircraft. After the aircraft is retracted, the target information can be analyzed in a laboratory, so that the growth and distribution of the toxic grasses on the field grasslands can be further accurately analyzed.
Description
Technical Field
The application relates to the field of toxic and harmful grass identification, in particular to a method for identifying toxic and harmful grass in grassland.
Background
The natural grassland poison grass is one of important characteristics of grassland deterioration, is a main factor causing the grassland deterioration, has great influence on animal husbandry in pastoral areas, and particularly, the poison grass such as radix euphorbiae lantu, buddleia and aconitum carmichaeli is a green killer of the natural grassland, so that the sustainable development of the animal husbandry of the natural grassland is restricted. Therefore, species identification, area estimation and space-time dynamic monitoring are carried out aiming at the natural grassland noxious grasses, which are important contents for the research of the grassland noxious grasses. However, the current natural grassland toxicity disaster monitoring and forecasting methods mainly comprise manual field investigation, field sampling and the like. Common survey methods include "sample methods," which are time consuming and labor intensive, increasing labor intensity and cost. The investigation of toxic and harmful grasses is difficult due to the complex topography and inconvenient traffic of natural grasslands in some remote areas.
Disclosure of Invention
The application aims to provide a method for identifying toxic and harmful grasses in grassland, which can solve the technical problem of difficulty in identifying the toxic grasses in the prior art.
The embodiment of the application is realized as follows:
a method for identifying toxic and harmful grasses in grassland comprises the following steps:
acquiring spectral information in a preset area of a field grassland by using an aircraft carrying a hyperspectral camera;
preprocessing the spectral information by using a processing mechanism carried by an aircraft to obtain target information;
and storing the target information by utilizing a storage mechanism carried by the aircraft.
Further, still include:
and constructing a spectrum information base according to the target information.
Further, the spectral information includes:
spectral information of noxious grasses within a predetermined area of the field grassland.
Further, the spectral information further includes:
location information of noxious grasses within a predetermined area of the field grassland.
Further, preprocessing the spectral information comprises:
checking whether the spectral information is complete.
Further, preprocessing the spectral information further comprises:
and comparing the difference between the spectral information of the toxic weeds in the preset area and the spectral information of the non-toxic weeds in the preset area.
Further, preprocessing the spectral information further comprises:
and comparing the difference of the spectral information of different toxic and harmful grasses in the preset area.
Further, constructing a spectral information base according to the target information comprises:
acquiring spectral information with the largest difference among different toxic and harmful grasses in a preset area;
obtaining the spectral information with the maximum difference between the toxic and harmful grass in the preset area and the non-toxic and harmful grass in the preset area.
Further, the aircraft is an unmanned aerial vehicle.
The beneficial effects of the embodiment of the application are that: the identification method for the grassland toxic weeds comprises the following steps: acquiring spectral information in a preset area of a field grassland by using an aircraft carrying a hyperspectral camera; the hyperspectral camera carried by the aircraft can be used for conveniently acquiring the spectral information in the preset area, so that manpower and material resources can be effectively saved, and the spectral information can be used for analyzing the conditions such as the quantity and distribution of toxic and harmful grasses in the preset area, so that the growth condition of the toxic and harmful grasses on the grassland can be obtained; preprocessing the spectral information by using a processing mechanism carried by an aircraft to obtain target information; the spectrum information is not collected, and the like, and the hyperspectral camera can be carried by the aircraft again to collect the spectrum information in the missing area, so that the working efficiency can be effectively improved; storing the target information by using a storage mechanism carried by the aircraft; after the aircraft is retracted, the target information can be analyzed in a laboratory, so that the growth and distribution of the toxic grasses on the field grasslands can be further accurately analyzed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is a flow chart of a grass poisoning identification method provided in an embodiment of the present application;
fig. 2 is a structural diagram of a grassland poisoning grass identification terminal according to an embodiment of the present application.
Icon:
100-grassland toxic and harmful grass identification terminal; 110-an aircraft; 111-an antenna; 112-a foot rest; 120-a hyperspectral camera; 130-processing mechanism.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element.
It will be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like, as used herein, refer to an orientation or positional relationship indicated in the drawings that is solely for the purpose of facilitating the description and simplifying the description, and 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 considered as limiting the present application.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "plurality" means two or more unless specifically limited otherwise
Now, the identification method for grass toxicity and grassland toxicity identification terminal provided by the embodiment of the application are explained.
As shown in fig. 1, the identification method for grass poisoning provided by the present application includes:
and S1, acquiring the spectrum information in the preset area of the field grassland by using the hyperspectral camera carried by the aircraft.
In particular, the aircraft may be a drone, for example: the model is an unmanned aerial vehicle of Dajiang-longitude and latitude M600 PRO, which can carry a load of 6 KG. The hyperspectral camera may be of the type: gaiasky-mini2-VN, its weight is 1.5KG, can be carried by above-mentioned unmanned aerial vehicle. Because the high spectrum camera has unmanned aerial vehicle to carry, the user only need control unmanned aerial vehicle and fly the position that can control the high spectrum camera, in the region that the topography is complicated, inconvenient traffic, need not the user and walk to the region of predetermineeing on the spot in the field, only need control unmanned aerial vehicle and fly to this predetermine the region and can utilize the spectral information of high spectrum camera in to predetermineeing the region to gather.
Specifically, the spectral information may include: spectral information of noxious grasses within a predetermined area of the field grassland. The growth and distribution conditions of the toxic and harmful grasses in the preset area of the field grassland can be analyzed by utilizing the spectral information, so that the health condition of the field grassland is obtained.
Specifically, the spectral information may further include: location information of noxious grasses within a predetermined area of the field grassland. The specific position distribution condition of the field noxious grass can be analyzed by utilizing the position information, so that the health condition of the grassland in different areas of the field grassland can be obtained. This positional information can be confirmed by the positioner on the aircraft, for example, can be with the camera lens orientation of high spectrum camera under to the positional information that the poison grass that high spectrum camera obtained is the positional information of unmanned aerial vehicle this moment.
And S2, preprocessing the spectral information by using a processing mechanism carried by the aircraft to obtain target information.
Specifically, the processing mechanism may be a processor, which may specifically be: the model is as follows: raspberry Pi (4b) and the operating system is: the Linux operating system adopts the following models: the CPU and model number of the quad-core Cortex-A72(ARM v8)64-bit 1.5GHz are as follows: broadcom VideoCore VI (500MHz) GPU.
Specifically, the preprocessing the spectral information may include: the spectral information is checked for completeness. For example, the staff expects to acquire the spectral information in a plurality of preset areas, and the spectral information only includes the spectral information in one or some of the preset areas, so that the spectral information of other preset areas is not complete due to the absence. Under this condition, can remind the staff through signals such as light to make the staff in time discover, and then utilize the aircraft to carry the high spectrum camera and fly to other preset regions, with the spectral information of other preset regions of collection disappearance. So that the finally obtained target information is complete.
Specifically, the preprocessing the spectral information may further include: and comparing the difference between the spectral information of the toxic weeds in the preset area and the spectral information of the non-toxic weeds in the preset area. By comparing the spectral information of the toxic and harmful grass in the preset area with the spectral information of the non-toxic and harmful grass in the preset area, the spectral information with the largest difference between the toxic and harmful grass in the preset area and the non-toxic and harmful grass in the preset area can be obtained, and therefore, a spectral information base can be constructed.
Specifically, the preprocessing the spectral information may further include: and comparing the difference of the spectral information of different toxic and harmful grasses in the preset area. By comparing the spectral information of different toxic and harmful grasses in the preset area, the spectral information with the largest difference among the different toxic and harmful grasses in the preset area can be obtained, thereby being beneficial to constructing a spectral information base.
And S3, storing the target information by using a storage mechanism carried by the aircraft.
Specifically, the storage mechanism may be of the type: SanDisk, 512G or 1T capacity memory card.
And S4, establishing a spectrum information base according to the target information.
Specifically, constructing the spectrum information base may include: acquiring spectral information with the largest difference among different toxic and harmful grasses in a preset area; acquiring spectral information with the largest difference between toxic and harmful grass in a preset area and non-toxic and harmful grass in the preset area; carrying out format conversion and data compression aiming at the screened spectral information; the spectral information of the grass poison is uploaded to a data processing control center, namely a data storage position of a Raspberry Pi (4b) operating system.
The identification method for the grassland toxic weeds comprises the following steps: acquiring spectral information in a preset area of a field grassland by using an aircraft carrying a hyperspectral camera; the hyperspectral camera carried by the aircraft can be used for conveniently acquiring the spectral information in the preset area, so that manpower and material resources can be effectively saved, and the spectral information can be used for analyzing the conditions such as the quantity and distribution of toxic and harmful grasses in the preset area, so that the growth condition of the toxic and harmful grasses on the grassland can be obtained; preprocessing the spectral information by using a processing mechanism carried by an aircraft to obtain target information; the spectrum information is not collected, and the like, and the hyperspectral camera can be carried by the aircraft again to collect the spectrum information in the missing area, so that the working efficiency can be effectively improved; storing the target information by using a storage mechanism carried by the aircraft; after the aircraft is retracted, the target information can be analyzed in a laboratory, so that the growth and distribution of the toxic grasses on the field grasslands can be further accurately analyzed.
As shown in fig. 2, the present application provides a grass poison grass identification terminal 100 including: a hyperspectral camera 120, a processing mechanism 130, a storage mechanism, and an aircraft 110.
The hyperspectral camera 120 is used for acquiring spectral information of a preset area. The processing mechanism 130 is electrically connected to the hyperspectral camera 120 and is configured to pre-process the spectral information to obtain target information; the storage mechanism is electrically connected to the processing mechanism 130 and is used for storing the target information; the aircraft 110 is connected to the hyperspectral camera 120 and is used for flying to a preset area with the hyperspectral camera 120. The aircraft 110 may be a drone. In particular, the aircraft 110 may be a drone, for example: the model is an unmanned aerial vehicle of Dajiang-longitude and latitude M600 PRO, which can carry a load of 6 KG. The hyperspectral camera 120 model may be: gaiasky-mini2-VN, its weight is 1.5KG, can be carried by above-mentioned unmanned aerial vehicle. Specifically, the processing mechanism 130 may be a processor, which specifically may be: the model is as follows: raspberry Pi (4b) and the operating system is: the Linux operating system adopts the following models: the CPU and model number of the quad-core Cortex-A72(ARM v8)64-bit 1.5GHz are as follows: broadcom VideoCore VI (500MHz) GPU. Specifically, the storage mechanism may be of the type: SanDisk, 512G or 1T capacity memory card.
The present application provides a grassland poison and weed identification terminal 100 including: the hyperspectral camera 120, the processing mechanism 130, the storage mechanism and the aircraft 110, wherein the hyperspectral camera 120 is used for acquiring spectral information of a preset area; the processing mechanism 130 is electrically connected to the hyperspectral camera 120, and is configured to pre-process the spectral information to obtain target information; the storage mechanism is electrically connected to the processing mechanism 130 and is used for storing the target information; the aircraft 110 is connected to the hyperspectral camera 120 and is used for carrying the hyperspectral camera 120 to fly to the preset area. The hyperspectral camera 120 carried by the aircraft 110 can be used for conveniently acquiring spectral information in the preset area, so that manpower and material resources can be effectively saved, and the conditions such as the quantity and distribution of toxic and harmful grass in the preset area can be analyzed by using the spectral information, so that the growth condition of the grassland toxic and harmful grass can be obtained; preprocessing the spectral information by using a processing mechanism 130 carried by the aircraft 110 to obtain target information; through preprocessing, whether the spectral information is complete or not can be preliminarily analyzed, and when the spectral information is incomplete, for example, the spectral information of a part of regions is not acquired, the hyperspectral camera 120 carried by the aircraft 110 can be used for acquiring the spectral information in the missing regions again, so that the working efficiency can be effectively improved; storing the target information using a storage mechanism carried by the aircraft 110; after the aircraft 110 is retracted, the target information can be analyzed in a laboratory, so that the growth and distribution of the toxic grass on the grassland in the field can be further accurately analyzed.
In some embodiments of the present application, the grassy weed identification terminal 100 may further include: and a control mechanism. The control mechanism is signally connected to the aircraft 110 for sending flight instructions to the aircraft 110 to control the flight of the aircraft 110. Specifically, this control structure can be for controlling the above-mentioned unmanned aerial vehicle's remote control mechanism to the realization is controlled the flight of aircraft 110.
In some embodiments of the present application, the aircraft 110 includes: antenna 111 and flight body, antenna 111 signal connection is in control mechanism for receive the flight instruction, and fly the body flight according to flight instruction control.
In some embodiments of the present application, the aircraft 110 may further include: the foot rest 112, form accommodation space between foot rest 112 and the flight body, hyperspectral camera 120 sets up in accommodation space. The accommodation space can protect the foot rest 112, and when the aircraft 110 lands on the ground, because the hyperspectral camera 120 is arranged in the accommodation space, the foot rest 112 firstly contacts the ground, so that the damage to the hyperspectral camera 120 caused by the hyperspectral camera 120 firstly contacting the ground can be effectively prevented.
In some embodiments of the present application, the plurality of foot rests 112 are disposed in a plurality, the plurality of foot rests 112 are spaced apart from each other, and the plurality of foot rests 112 are annularly disposed around the hyperspectral camera 120. The plurality of foot rests 112 may be more stable for landing the aircraft 110.
In some embodiments of the present application, the lens of the hyperspectral camera 120 faces away from the direction of the flying body. In this case, the spectral information acquired by the hyperspectral camera 120 is the spectral information at the position where the aircraft 110 is located at the moment.
In some embodiments of the present application, the processing mechanism 130 is fixedly mounted to the aircraft 110. The processor may be mounted to the top surface of the aircraft 110 to prevent it from falling.
In some embodiments of the present application, the storage mechanism is fixedly mounted to the aircraft 110. The storage mechanism may be mounted inside the aircraft 110 to ensure its environmental stability.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (9)
1. A method for identifying toxic and harmful grasses in grassland is characterized by comprising the following steps:
acquiring spectral information in a preset area of a field grassland by using an aircraft carrying a hyperspectral camera;
preprocessing the spectral information by using a processing mechanism carried by an aircraft to obtain target information;
and storing the target information by utilizing a storage mechanism carried by the aircraft.
2. The method of identifying grass poisoning of claim 1, further comprising:
and constructing a spectrum information base according to the target information.
3. The method of identifying grass weeds of claim 2 wherein said spectral information includes:
spectral information of noxious grasses within a predetermined area of the field grassland.
4. The method for grass identification of claim 3 wherein the spectral information further comprises:
location information of noxious grasses within a predetermined area of the field grassland.
5. The method of claim 2, wherein preprocessing the spectral information comprises:
checking whether the spectral information is complete.
6. The method of identifying grass venomous pests of claim 5, wherein preprocessing the spectral information further comprises:
and comparing the difference between the spectral information of the toxic weeds in the preset area and the spectral information of the non-toxic weeds in the preset area.
7. The method of identifying grass venomous pests of claim 6, wherein preprocessing the spectral information further comprises:
and comparing the difference of the spectral information of different toxic and harmful grasses in the preset area.
8. The method of claim 7, wherein constructing a spectral library of information based on the target information comprises:
acquiring spectral information with the largest difference among different toxic and harmful grasses in a preset area;
obtaining the spectral information with the maximum difference between the toxic and harmful grass in the preset area and the non-toxic and harmful grass in the preset area.
9. The method of grass poisoning identification of claim 1, wherein the aerial vehicle is an unmanned aerial vehicle.
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| CN202110765507.6A CN113640232A (en) | 2021-07-07 | 2021-07-07 | Identification method for grassland toxic and harmful grass |
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| CN202110765507.6A CN113640232A (en) | 2021-07-07 | 2021-07-07 | Identification method for grassland toxic and harmful grass |
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2021
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| CN102706813A (en) * | 2012-05-31 | 2012-10-03 | 北京林业大学 | Poa pratensis variety identification method based on hyper-spectral image |
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