CN117875571A - Forest vegetation growth condition analysis method and system - Google Patents
Forest vegetation growth condition analysis method and system Download PDFInfo
- Publication number
- CN117875571A CN117875571A CN202410275529.8A CN202410275529A CN117875571A CN 117875571 A CN117875571 A CN 117875571A CN 202410275529 A CN202410275529 A CN 202410275529A CN 117875571 A CN117875571 A CN 117875571A
- Authority
- CN
- China
- Prior art keywords
- pest
- vegetation
- disease
- insect
- pesticide spraying
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 21
- 241000607479 Yersinia pestis Species 0.000 claims abstract description 384
- 201000010099 disease Diseases 0.000 claims abstract description 294
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 294
- 241000238631 Hexapoda Species 0.000 claims abstract description 212
- 239000000575 pesticide Substances 0.000 claims abstract description 180
- 238000010586 diagram Methods 0.000 claims abstract description 67
- 238000003892 spreading Methods 0.000 claims abstract description 67
- 230000007480 spreading Effects 0.000 claims abstract description 67
- 239000007921 spray Substances 0.000 claims abstract description 18
- 238000005507 spraying Methods 0.000 claims description 158
- 238000000034 method Methods 0.000 claims description 24
- 239000000203 mixture Substances 0.000 claims description 21
- 238000009472 formulation Methods 0.000 claims description 19
- 238000009826 distribution Methods 0.000 claims description 17
- 238000010191 image analysis Methods 0.000 claims description 15
- 230000000903 blocking effect Effects 0.000 claims description 14
- 238000002360 preparation method Methods 0.000 claims 2
- 208000031940 Disease Attributes Diseases 0.000 claims 1
- 238000005457 optimization Methods 0.000 abstract description 2
- 241000196324 Embryophyta Species 0.000 description 155
- 238000012545 processing Methods 0.000 description 18
- 238000005516 engineering process Methods 0.000 description 10
- 235000008331 Pinus X rigitaeda Nutrition 0.000 description 8
- 235000011613 Pinus brutia Nutrition 0.000 description 8
- 241000018646 Pinus brutia Species 0.000 description 8
- 241000243771 Bursaphelenchus xylophilus Species 0.000 description 7
- 241001491790 Bupalus piniaria Species 0.000 description 6
- 230000008859 change Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 239000003795 chemical substances by application Substances 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 238000012876 topography Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 238000004590 computer program Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000004660 morphological change Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Landscapes
- Catching Or Destruction (AREA)
Abstract
The invention is applicable to the technical field of forest vegetation disease and pest control, and provides a forest vegetation growth condition analysis method and system, wherein a plurality of punctiform disease and pest vegetation images are obtained and combined to obtain a disease and pest spreading range diagram; and obtaining a target treatment area according to the plant diseases and insect pests spreading range diagram. When the unmanned aerial vehicle kills the forest vegetation that the large tracts of land suffered the plant diseases and insect pests and sprays the pesticide, can make unmanned aerial vehicle kills the insect according to the pest control route flight that the optimization set for, and can also be according to the concrete plant diseases and insect pests condition in the unmanned aerial vehicle of deinsectization place vegetation region, the pesticide of the unmanned aerial vehicle of dynamic adjustment is sprayed quantity and the pesticide sprays the kind for the forest vegetation region that has different plant diseases and insect pests condition can obtain suitable pesticide and spray the kind, and then has improved the plant diseases and insect pests treatment efficiency to the forest vegetation.
Description
Technical Field
The invention belongs to the technical field of forest vegetation disease and pest control, and particularly relates to a forest vegetation growth condition analysis method and system.
Background
In the analysis process of the growth condition of forest vegetation, the method is very important for monitoring and controlling plant diseases and insect pests of the forest vegetation. Forest diseases and insect pests are important biological disasters in forest production, have destructive damage to forests, and seriously threaten the forest production, ecological environment and economic development of disaster-stricken countries. In the prior art, when the occurrence of the disease and insect pest phenomenon in forest vegetation is found, a relatively efficient treatment mode is a mode of spraying pesticides on a large scale for an unmanned aerial vehicle.
When the large-area forest vegetation is subjected to the pest and disease damage phenomenon, different kinds of pest and disease damage of the forest vegetation in different areas can exist, and the damage degree of the vegetation is different. At present, when unmanned aerial vehicle sprays and kills forest vegetation, the pesticide type and the pesticide amount sprayed can not be intelligently changed according to the specific pest and disease conditions of the vegetation in the area, so that the forest vegetation in different areas can not obtain ideal pesticide treatment effect.
Disclosure of Invention
The invention aims to provide a forest vegetation growth condition analysis method and system, and aims to solve the problems in the background technology.
The invention is realized in such a way that a forest vegetation growth status analysis method comprises the following steps:
acquiring a plurality of punctiform plant diseases and insect pests vegetation images, and combining the punctiform plant diseases and insect pests vegetation images to obtain a plant disease and insect pest spreading range diagram;
obtaining a target treatment area according to the plant disease and insect pest spreading range diagram, and making a deinsectization travelling route in the target treatment area;
analyzing all point-like plant diseases and insect pests vegetation images corresponding to the pest control travelling route of the target treatment area in the plant disease and insect pest spreading range diagram, and obtaining a plurality of plant disease and insect pest attribute points;
when the pesticide spraying equipment advances according to the deinsectization advancing route, a deinsectization pesticide spraying dynamic adjustment command is formulated according to the vegetation disease and pest attribute points, and the deinsectization pesticide spraying dynamic adjustment command is output to the pesticide spraying equipment.
By further limiting the technical scheme of the embodiment of the invention, the steps of obtaining a target treatment area according to the plant disease and insect pest spreading range diagram and making a deinsectization travelling route in the target treatment area comprise the following steps:
obtaining a target treatment area according to the plant diseases and insect pests spreading range diagram;
analyzing the plant disease and insect pest spreading range diagram, and determining the plane distribution positions of a plurality of dot plant disease and insect pest vegetation images contained in the plant disease and insect pest spreading range diagram;
and intelligently planning an insect-killing travelling route according to the plane distribution positions of the dot-shaped plant disease and insect pest vegetation images.
As a further limitation of the technical scheme of the embodiment of the invention, the target treatment area comprises a pest and disease killing area and a key blocking area.
As further defined by the technical solution of the embodiment of the present invention, the step of analyzing all dot-like plant diseases and insect pests vegetation images corresponding to the pest control travelling route of the target treatment area in the plant diseases and insect pests spreading range diagram, and obtaining a plurality of plant diseases and insect pests attribute points includes:
analyzing a plurality of point-shaped plant diseases and insect pests vegetation images corresponding to the insect pest spreading range diagram of the insect pest killing travelling route one by one;
determining the plant diseases and insect pests types and severity indexes corresponding to each punctiform plant diseases and insect pests vegetation image;
and binding the plant diseases and insect pests types corresponding to each punctiform plant diseases and insect pests vegetation image and the plant diseases and insect pests severity index to obtain a plurality of plant diseases and insect pests attribute points.
By further limiting the technical scheme of the embodiment of the invention, after a plurality of vegetation disease and pest attribute points are obtained, the positioning electronic fence of each dot disease and pest vegetation image in the pest killing travelling route is obtained, and the positioning electronic fence corresponding to the same dot disease and pest vegetation image is bound with the vegetation disease and pest attribute points.
As a further limitation of the technical scheme of the embodiment of the invention, when the pesticide spraying device travels along the pest killing travelling route, the steps of formulating a dynamic pesticide spraying adjustment command according to the attribute points of plant diseases and insect pests and outputting the dynamic pesticide spraying adjustment command to the pesticide spraying device include:
receiving execution feedback information from the pesticide spraying equipment to determine that the pesticide spraying equipment enters the pest killing travelling route and obtain the real-time position of the pesticide spraying equipment;
analyzing the real-time position of the pesticide spraying equipment, determining a target positioning electronic fence where the real-time position of the pesticide spraying equipment is located, and acquiring vegetation pest attribute points bound by the target positioning electronic fence;
and formulating a dynamic pesticide spraying adjustment command according to the vegetation disease and pest attribute points, and outputting the dynamic pesticide spraying adjustment command to pesticide spraying equipment.
As a further limitation of the technical scheme of the embodiment of the invention, the steps of formulating a dynamic adjustment command of pesticide spraying according to the attribute points of vegetation diseases and insect pests and outputting the dynamic adjustment command of pesticide spraying to pesticide spraying equipment comprise:
acquiring a preset pesticide spraying control model, and determining the type of the required spraying pesticide and the required spraying amount of the vegetation pest attribute points bound by the target positioning electronic fence according to the preset pesticide spraying control model;
according to the type of pesticide to be sprayed and the required spraying quantity, a dynamic adjustment command for spraying the pesticide to be killed is formulated;
and outputting the dynamic pesticide spraying adjustment command to the pesticide spraying equipment.
A forest vegetation growth condition analysis system, the system includes pest and disease spreading range diagram acquisition module, deinsectization travel route formulation module, vegetation pest and disease damage attribute point acquisition module and deinsectization pesticide spraying dynamic adjustment command formulation module, wherein:
the plant disease and insect pest spreading range diagram acquisition module is used for acquiring a plurality of punctiform plant disease and insect pest vegetation images and combining the punctiform plant disease and insect pest vegetation images to obtain a plant disease and insect pest spreading range diagram;
the deinsectization traveling route establishment module is used for obtaining a target treatment area according to the plant disease and insect pest spreading range diagram and establishing an deinsectization traveling route in the target treatment area;
the vegetation disease and pest attribute point acquisition module is used for analyzing all point disease and pest vegetation images corresponding to the pest control travelling route of the target treatment area in the disease and pest spreading range diagram and obtaining a plurality of vegetation disease and pest attribute points;
the pesticide spraying dynamic adjustment command making module is used for making a pesticide spraying dynamic adjustment command according to the attribute points of plant diseases and insect pests when the pesticide spraying equipment advances according to the pesticide spraying travelling route, and outputting the pesticide spraying dynamic adjustment command to the pesticide spraying equipment.
As a further limitation of the technical solution of the embodiment of the present invention, the deinsectization travel route formulation module specifically includes:
the target treatment area acquisition unit is used for acquiring a target treatment area according to the plant disease and insect pest spreading range diagram;
a plane distribution position determining unit for analyzing the plant disease and insect pest spreading range diagram and determining plane distribution positions of a plurality of dot plant disease and insect pest vegetation images contained in the plant disease and insect pest spreading range diagram;
and the deinsectization travel route planning unit is used for intelligently planning an deinsectization travel route according to the plane distribution positions of the dot disease and insect pest vegetation images.
As a further limitation of the technical solution of the embodiment of the present invention, the vegetation disease and pest attribute point obtaining module specifically includes:
the plant disease and insect pest point vegetation image analysis unit is used for analyzing a plurality of plant disease and insect pest point vegetation images corresponding to the insect pest killing travelling route in the plant disease and insect pest spreading range diagram one by one;
the attribute analysis unit is used for determining the plant diseases and insect pests types and severity indexes corresponding to each punctiform plant diseases and insect pests vegetation image;
and the vegetation disease and pest attribute point obtaining unit is used for binding the disease and pest types corresponding to each punctiform disease and pest vegetation image and the disease and pest severity index to obtain a plurality of vegetation disease and pest attribute points.
Compared with the prior art, the method has the advantages that the plant disease and insect pest spreading range diagram is obtained by acquiring a plurality of dot plant disease and insect pest vegetation images and combining the dot plant disease and insect pest vegetation images; obtaining a target treatment area according to the plant disease and insect pest spreading range diagram, and making a deinsectization travelling route in the target treatment area; analyzing all point-like plant diseases and insect pests vegetation images corresponding to the pest control travelling route of the target treatment area in the plant disease and insect pest spreading range diagram, and obtaining a plurality of plant disease and insect pest attribute points; when the pesticide spraying equipment advances according to the deinsectization advancing route, a deinsectization pesticide spraying dynamic adjustment command is formulated according to the vegetation disease and pest attribute points, and the deinsectization pesticide spraying dynamic adjustment command is output to the pesticide spraying equipment. When the unmanned aerial vehicle kills the forest vegetation that the large tracts of land suffered the plant diseases and insect pests and sprays the pesticide, can make unmanned aerial vehicle kills the insect according to the pest control route flight that the optimization set for, and can also be according to the concrete plant diseases and insect pests condition in the unmanned aerial vehicle of deinsectization place vegetation region, the pesticide of the unmanned aerial vehicle of dynamic adjustment is sprayed quantity and the pesticide sprays the kind for the forest vegetation region that has different plant diseases and insect pests condition can obtain suitable pesticide and spray the kind, and then has improved the plant diseases and insect pests treatment efficiency to the forest vegetation.
Drawings
FIG. 1 is a flow chart of a method provided by an embodiment of the present invention;
FIG. 2 is a flow chart of a method for creating a deinsectization travel route according to an embodiment of the present invention;
FIG. 3 is a flowchart of obtaining vegetation disease and pest attribute points in the method provided by the embodiment of the invention;
FIG. 4 is a flow chart of a method for formulating dynamic adjustment commands for pesticide spraying according to an embodiment of the present invention;
FIG. 5 is a flow chart of a method for determining the type of pesticide to be sprayed and the amount of pesticide to be sprayed according to an embodiment of the present invention;
FIG. 6 is an application architecture diagram of a system provided by an embodiment of the present invention;
fig. 7 is a block diagram of a module for setting a pest-killing traveling route in the system according to the embodiment of the present invention;
fig. 8 is a block diagram of a module for obtaining vegetation disease and pest attribute points in the system according to the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Fig. 1 shows a flowchart of a method provided by an embodiment of the present invention.
Specifically, a forest vegetation growth condition analysis method specifically comprises the following steps:
and S100, acquiring a plurality of punctiform plant diseases and insect pests vegetation images, and combining the punctiform plant diseases and insect pests vegetation images to obtain a plant disease and insect pest spreading range diagram.
According to the embodiment of the invention, the intelligent high-definition camera carried by the unmanned aerial vehicle is used for photographing local areas of the forest vegetation areas to be treated, the intelligent high-definition camera is used for uploading the photographed local forest vegetation images to the background processing cloud in real time, the background processing cloud is used for carrying out intelligent image analysis on the local forest vegetation images and judging whether the local forest vegetation images are punctiform disease and insect pest vegetation images according to the existence of the disease and insect pest images in the local forest vegetation images, the intelligent image analysis technology is a mature image analysis technology in the prior art and judging whether the disease and insect pest phenomenon exists in the forest vegetation, and a multispectral technology can be adopted;
when the background processing cloud identifies dot-shaped plant disease and insect pest vegetation images with plant disease and insect pest phenomena, the forest area corresponding to the dot-shaped plant disease and insect pest vegetation images is taken as a central area, the shooting unmanned aerial vehicle is controlled to carry out radiation shooting operation to the periphery of the central area, the background processing cloud carries out intelligent image analysis on the shot partial forest vegetation images one by one, all dot-shaped plant disease and insect pest vegetation images are screened out, and then the background processing cloud carries out image plane combination on the dot-shaped plant disease and insect pest vegetation images according to the specific position to obtain a plant disease and insect pest spreading range diagram.
Further, the forest vegetation growth status analysis method further comprises the following steps:
and step 200, obtaining a target treatment area according to the plant disease and insect pest spreading range diagram, and making a deinsectization travelling route in the target treatment area.
Specifically, fig. 2 shows a flowchart for making a vermin exterminating traveling route.
The method comprises the following steps of obtaining a target treatment area according to a plant disease and insect pest spreading range diagram, and making a deinsectization travelling route in the target treatment area:
step S201, obtaining a target treatment area according to the plant disease and insect pest spreading range diagram;
step S202, analyzing a plant disease and insect pest spreading range diagram, and determining the plane distribution positions of a plurality of dot plant disease and insect pest vegetation images contained in the plant disease and insect pest spreading range diagram;
step S203, intelligently planning an insect-killing travelling route according to the plane distribution positions of the dot-shaped plant disease and insect pest vegetation images.
In the embodiment of the invention, when the background processing cloud plans the deinsectization travelling route according to the plane distribution positions of the dot-shaped plant disease and insect pest vegetation images, the deinsectization unmanned aerial vehicle can be ensured to pass over the partial forest vegetation areas corresponding to the dot-shaped plant disease and insect pest vegetation images;
it is understood that the target treatment area includes a pest killing area and a key blocking area, the pest killing area refers to a local forest vegetation area which has been determined to contain the pest, the key blocking area refers to a surrounding part of the forest vegetation area which contains the pest, and the key blocking area is annular, that is, the key blocking area surrounds the pest killing area.
Further, the forest vegetation growth status analysis method further comprises the following steps:
and S300, analyzing all point-like plant diseases and insect pests vegetation images corresponding to the pest control travelling route of the target treatment area in the plant disease and insect pest spreading range diagram, and obtaining a plurality of vegetation plant disease and insect pest attribute points.
Specifically, fig. 3 shows a flowchart for obtaining vegetation disease and pest attribute points.
The method for analyzing all point-like plant diseases and insect pests vegetation images corresponding to the pest control travelling route of the target treatment area in the plant diseases and insect pests spreading range diagram and obtaining a plurality of vegetation plant diseases and insect pests attribute points specifically comprises the following steps:
step S301, analyzing a plurality of point-shaped plant disease and insect pest vegetation images corresponding to the insect pest spreading range diagram of the insect pest spreading route one by one;
step S302, determining the plant diseases and insect pests types and severity indexes corresponding to each punctiform plant diseases and insect pests vegetation image;
step S303, the plant diseases and insect pests types corresponding to each punctiform plant diseases and insect pests vegetation image and the plant diseases and insect pests severity index are bound to obtain a plurality of plant diseases and insect pests attribute points.
In the embodiment of the invention, when a background processing cloud analyzes a plurality of point-shaped plant disease and insect pest vegetation images corresponding to a pest control travelling route in a plant disease and insect pest spreading range diagram, determining plant disease and insect pest types and plant disease severity indexes of a local forest vegetation area corresponding to each point-shaped plant disease and insect pest vegetation image through an intelligent image analysis technology, and then binding the plant disease and insect pest types and the plant disease severity indexes corresponding to each point-shaped plant disease and insect pest vegetation image to obtain a plurality of plant disease and insect pest attribute points;
for example, in the pine tree sheet area, the background processing cloud determines that a certain point-like plant disease and insect pest vegetation image includes a plant image of 'pine needle wilting with water loss, changing into yellow brown to red brown, and burning', then the plant disease and insect pest type corresponding to the point-like plant disease and insect pest vegetation image can be primarily determined as pine wood nematode disease, then the background processing cloud continues to analyze the point-like plant disease and insect pest vegetation image, and determines the plant disease and insect pest severity of the point-like plant disease and insect pest vegetation image according to the color change degree or the form change degree of the pine needle and pine branch.
Further, the forest vegetation growth status analysis method further comprises the following steps:
after a plurality of vegetation disease and pest attribute points are obtained, a positioning electronic fence of each dot disease and pest vegetation image in the pest killing travelling route is obtained, and the positioning electronic fence corresponding to the same dot disease and pest vegetation image is bound with the vegetation disease and pest attribute points;
step S400, when the pesticide spraying equipment advances according to the deinsectization travelling route, a deinsectization pesticide spraying dynamic adjustment command is formulated according to the vegetation disease and pest attribute points, and the deinsectization pesticide spraying dynamic adjustment command is output to the pesticide spraying equipment.
Specifically, fig. 4 shows a flowchart for formulating dynamic adjustment commands for pesticide spraying.
When the pesticide spraying equipment advances according to the deinsectization advancing route, a deinsectization pesticide spraying dynamic adjustment command is formulated according to the vegetation disease and pest attribute points, and the deinsectization pesticide spraying dynamic adjustment command is output to the pesticide spraying equipment, and the method specifically comprises the following steps of:
step S401, receiving execution feedback information from the pesticide spraying equipment to determine that the pesticide spraying equipment enters a pest killing travelling route and obtain the real-time position of the pesticide spraying equipment;
step S402, analyzing the real-time position of the pesticide spraying equipment, determining a target positioning electronic fence where the real-time position of the pesticide spraying equipment is located, and acquiring vegetation pest attribute points bound by the target positioning electronic fence;
step S403, according to the attribute points of vegetation diseases and insect pests, a dynamic pesticide spraying adjustment command is formulated, and the dynamic pesticide spraying adjustment command is output to pesticide spraying equipment.
Specifically, fig. 5 shows a flowchart for determining the type of pesticide to be sprayed and the amount of spraying required.
Wherein, according to vegetation disease and pest attribute point, formulate the dynamic adjustment command of deinsectization pesticide spraying to the pesticide spraying equipment is sprayed to deinsectization pesticide dynamic adjustment command output, specifically includes following step:
step S4031, a preset pesticide spraying control model is obtained, and the type of the required pesticide spraying and the required spraying amount of the vegetation pest attribute points bound by the target positioning electronic fence are determined according to the preset pesticide spraying control model;
step S4032, a dynamic pesticide spraying adjustment command is formulated according to the type of pesticide to be sprayed and the required spraying quantity;
step S4033, outputting the dynamic adjustment command of pesticide spraying to the pesticide spraying equipment.
In the embodiment of the invention, the pesticide spraying equipment refers to the unmanned aerial vehicle, when the unmanned aerial vehicle executes a pest killing task, the real-time position is sent to the background processing cloud in real time, the background processing cloud analyzes whether the unmanned aerial vehicle enters a positioning electronic fence of any point-shaped plant disease and insect pest vegetation image in real time, once the unmanned aerial vehicle is determined to enter the positioning electronic fence of a point-shaped plant disease and insect pest vegetation image, the background processing cloud can send a formulated pest killing travelling route to the unmanned aerial vehicle, and the unmanned aerial vehicle is controlled to carry out pesticide spraying operation according to the pest killing travelling route;
it can be understood that a preset pesticide spraying control model is pre-stored in a background processing cloud, a plurality of pest types and pesticide types applied by each pest type are stored in the preset pesticide spraying control model, pesticide amounts which are required to be used by different degrees of pest are also stored in the preset pesticide spraying control model, after a target positioning electronic fence where an unmanned aerial vehicle is located is determined, a vegetation pest attribute point bound by the target positioning electronic fence (namely, a vegetation pest attribute point of a forest vegetation area contained by the target positioning electronic fence) can be obtained by the background processing cloud, then the pest types and pest severity indexes contained by the vegetation pest attribute point bound by the target positioning electronic fence are input into the preset pesticide spraying control model, a required pesticide spraying type and a required pesticide spraying amount corresponding to the vegetation pest attribute point bound by the target positioning electronic fence are obtained, a dynamic pesticide spraying adjustment command is formulated according to the required pesticide spraying type and the required pesticide spraying amount, and the dynamic pesticide spraying command is output to pesticide spraying equipment;
for example, the disinfestation unmanned aerial vehicle carries two disinfestation agents, one is aimed at "pine moth" and the other is aimed at "pine wood nematode disease", when the disinfestation unmanned aerial vehicle enters a positioning electronic fence corresponding to the point-like plant disease and insect pest vegetation image A, a background processing cloud obtains a plant disease and insect pest attribute point a corresponding to the positioning electronic fence, the plant disease and insect pest attribute point a is analyzed, the plant disease and insect pest types contained in a local forest vegetation area corresponding to the point-like plant disease and insect pest vegetation image A are "pine moth", the plant disease and insect pest severity is "medium", the background processing cloud generates a disinfestation pesticide spraying dynamic adjustment command X, and controls the disinfestation unmanned aerial vehicle to spray pesticide aimed at "pine moth" and the spraying amount is controlled to be medium dosage;
the unmanned aerial vehicle enters a positioning electronic fence corresponding to a point-like plant disease and insect pest vegetation image B along a pest control travelling route, a background processing cloud obtains relevant information of the position in real time, a plant disease and insect pest attribute point B corresponding to the positioning electronic fence is called, the plant disease and insect pest type contained in a local forest vegetation area corresponding to the point-like plant disease and insect pest vegetation image B is analyzed according to the plant disease and insect pest attribute point B, the plant disease and insect pest type is 'pine wood nematode disease', the plant disease and insect pest severity degree is 'mild', the background processing cloud generates a dynamic pesticide spraying adjustment command Y, the unmanned aerial vehicle is controlled to spray pesticide aiming at the 'pine wood nematode disease', and the spraying amount is controlled to be a small amount;
in practical application, the frequency of changing the pesticide spraying type is generally low (the types of plant diseases and insect pests of the same piece of forest vegetation are often single), and the pesticide spraying amount is frequently changed for different plant disease and insect pest areas (the damage degree of the plant diseases and insect pests of different areas of the same piece of forest vegetation can be greatly different due to the influence factors such as topography, vegetation composition structure and the like);
it can be understood that the pesticide spraying amounts of the key blocking areas are the same, and the spraying types correspond to the plant diseases and insect pests contained in the dot plant disease and insect pest vegetation image, so that when the unmanned deinsectization plane enters the key blocking areas, the pesticide spraying amount is not required to be adjusted, and only a preset amount of pesticide corresponding to the plant diseases and insect pests contained in the dot plant disease and insect pest vegetation image is required to be sprayed;
through the technical scheme, when the unmanned aerial vehicle kills the forest vegetation of the large-area pest and disease damage by spraying pesticides, the unmanned aerial vehicle can fly to kill the pests according to the optimally set pest and disease damage traveling route, and the pesticide spraying amount and the pesticide spraying type of the unmanned aerial vehicle can be dynamically adjusted according to the specific pest and disease damage condition of the vegetation area where the unmanned aerial vehicle kills the pests, so that the forest vegetation area with different pest and disease damage conditions can obtain proper pesticide spraying amount and pesticide spraying type, and further the pest and disease damage treatment efficiency of the forest vegetation is improved.
Further, fig. 6 shows an application architecture diagram of the system provided by the embodiment of the present invention.
In another preferred embodiment of the present invention, a forest vegetation growth analysis system includes:
the plant disease and insect pest spreading range diagram obtaining module 100 is configured to obtain a plurality of dot-shaped plant disease and insect pest vegetation images, and combine the plurality of dot-shaped plant disease and insect pest vegetation images to obtain a plant disease and insect pest spreading range diagram.
In the embodiment of the invention, an intelligent high-definition camera carried by a camera unmanned aerial vehicle is used for photographing a local area of a forest vegetation area to be treated, the intelligent high-definition camera is used for uploading the photographed local forest vegetation images to a disease and pest spreading range image acquisition module 100 in real time, the disease and pest spreading range image acquisition module 100 is used for carrying out intelligent image analysis on the local forest vegetation images and judging whether the local forest vegetation images are punctiform disease and pest vegetation images according to the existence of the disease and pest images in the local forest vegetation images, the intelligent image analysis technology is a mature image analysis technology in the prior art and judging whether the disease and pest phenomena exist in the forest vegetation, and a multispectral technology can be adopted;
when the plant disease and insect pest spreading range diagram acquiring module 100 identifies dot plant disease and insect pest vegetation images with plant disease and insect pest phenomena, the forest area corresponding to the dot plant disease and insect pest vegetation images is taken as a central area, the unmanned aerial vehicle is controlled to perform radiation image shooting operation to the periphery of the central area, the plant disease and insect pest spreading range diagram acquiring module 100 performs intelligent image analysis on the shot partial forest vegetation images one by one, and screens out all dot plant disease and insect pest vegetation images, and then the plant disease and insect pest spreading range diagram acquiring module 100 performs image plane combination on the dot plant disease and insect pest vegetation images based on the specific position to obtain a plant disease and insect pest spreading range diagram.
Further, the forest vegetation growth analysis system further comprises:
the deinsectization travel route formulation module 200 is configured to obtain a target treatment area according to the pest spreading range diagram, and formulate an deinsectization travel route in the target treatment area.
Specifically, fig. 7 shows a block diagram of a configuration of the deinsectization travel route formulation module 200 in the system according to the embodiment of the present invention.
In a preferred embodiment of the present invention, the deinsectization travel route formulation module 200 specifically includes:
a target treatment area obtaining unit 201, configured to obtain a target treatment area according to the pest spreading range diagram;
a plane distribution position determining unit 202 for analyzing the pest spreading range map and determining plane distribution positions of a plurality of dot pest vegetation images included in the pest spreading range map;
and the deinsectization travel route planning unit 203 is configured to intelligently plan an deinsectization travel route according to the planar distribution positions of the plurality of dot pest vegetation images.
In the embodiment of the present invention, when the deinsectization traveling route formulation module 200 plans the deinsectization traveling route according to the plane distribution positions of the plurality of dot pest vegetation images, it should be ensured that the deinsectization unmanned aerial vehicle can pass over the partial forest vegetation areas corresponding to all the dot pest vegetation images;
it is understood that the target treatment area includes a pest killing area and a key blocking area, the pest killing area refers to a local forest vegetation area which has been determined to contain the pest, the key blocking area refers to a surrounding part of the forest vegetation area which contains the pest, and the key blocking area is annular, that is, the key blocking area surrounds the pest killing area.
Further, the forest vegetation growth analysis system further comprises:
the vegetation disease and pest attribute point acquisition module 300 is configured to analyze all point disease and pest vegetation images corresponding to the pest control travelling route of the target treatment area in the disease and pest spreading range diagram, and obtain a plurality of vegetation disease and pest attribute points.
Specifically, fig. 8 shows a block diagram of a vegetation disease and pest attribute point acquisition module 300 in the system according to an embodiment of the present invention.
In a preferred embodiment of the present invention, the vegetation disease and pest attribute point obtaining module 300 specifically includes:
a punctiform pest vegetation image analysis unit 301 for analyzing, one by one, a plurality of punctiform pest vegetation images corresponding to the pest killing traveling route in the pest spreading range diagram;
an attribute analysis unit 302, configured to determine a pest type and a pest severity index corresponding to each dot pest vegetation image;
and a vegetation disease and pest attribute point obtaining unit 303, configured to bind the disease and pest type and the disease and pest severity index corresponding to each dot disease and pest vegetation image, so as to obtain a plurality of vegetation disease and pest attribute points.
In the embodiment of the present invention, when analyzing a plurality of dot-shaped pest vegetation images corresponding to a pest spreading range diagram of a pest killing travelling route, the dot-shaped pest vegetation image analysis unit 301 should determine a pest type and a pest severity index of a local forest vegetation area corresponding to each dot-shaped pest vegetation image through an intelligent image analysis technology, and then bind the pest type and the pest severity index corresponding to each dot-shaped pest vegetation image to obtain a plurality of pest attribute points of the vegetation;
for example, in the pine tree sheet area, when the vegetation disease and pest attribute point acquisition module 300 determines that a certain point disease and pest vegetation image includes a "pine needle wilt with water loss, turns into yellow brown to red brown, and appears as fire" vegetation image by using the intelligent image analysis technology, the vegetation disease and pest attribute point acquisition module 300 can primarily determine that the disease and pest category corresponding to the point disease and pest vegetation image is pine wood nematode disease, and then the vegetation disease and pest attribute point acquisition module 300 continues to analyze the point disease and pest vegetation image, and determines the disease and pest severity of the point disease and pest vegetation image according to the color change degree or the morphological change degree of the pine needle and pine branch.
Further, the forest vegetation growth analysis system further comprises:
the dynamic adjustment command formulation module 400 for spraying pesticide is used for formulating dynamic adjustment command for spraying pesticide according to the attribute points of plant diseases and insect pests when the pesticide spraying device moves along the pesticide spraying route, and outputting the dynamic adjustment command for spraying pesticide to the pesticide spraying device.
In the embodiment of the invention, the pesticide spraying device refers to a disinfestation unmanned aerial vehicle, when the disinfestation unmanned aerial vehicle executes a disinfestation task, the real-time position is sent to the disinfestation pesticide spraying dynamic adjustment command formulation module 400 in real time, the disinfestation pesticide spraying dynamic adjustment command formulation module 400 analyzes whether the disinfestation unmanned aerial vehicle enters a positioning electronic fence of any point-shaped plant disease and insect pest vegetation image in real time, once the disinfestation unmanned aerial vehicle is determined to enter the positioning electronic fence of a point-shaped plant disease and insect pest vegetation image, the disinfestation pesticide spraying dynamic adjustment command formulation module 400 can send the formulated disinfestation travel route to the disinfestation unmanned aerial vehicle, and the disinfestation unmanned aerial vehicle is controlled to carry out pesticide spraying operation according to the disinfestation travel route;
it can be understood that the preset pesticide spraying control model is pre-stored in the pesticide spraying dynamic adjustment command formulation module 400, the preset pesticide spraying control model stores a plurality of pest types and pesticide types applied by each pest type, and also stores pesticide amounts to be used by different degrees of pest, the pesticide spraying dynamic adjustment command formulation module 400 can obtain vegetation pest attribute points bound by the target positioning electronic fence (i.e., vegetation pest attribute points of forest vegetation areas contained by the target positioning electronic fence) after determining the target positioning electronic fence where the pesticide unmanned aerial vehicle is located, then the pesticide spraying dynamic adjustment command formulation module 400 inputs the pest types and the pest severity indexes contained by the vegetation attribute points bound by the target positioning electronic fence into the preset pesticide spraying control model to obtain required spraying pesticide types and required spraying amounts corresponding to the vegetation attribute points bound by the target positioning electronic fence, and then formulates a pesticide spraying dynamic adjustment command according to the required pesticide types and the required spraying amounts, and outputs the pesticide spraying dynamic adjustment command to the pest spraying dynamic device;
for example, the disinfestation unmanned aerial vehicle carries two disinfestation agents, one is aimed at "pine moth" and the other is aimed at "pine wood nematode disease", when the disinfestation unmanned aerial vehicle enters a positioning electronic fence corresponding to the point-like plant disease and insect pest vegetation image a, the disinfestation pesticide spraying dynamic adjustment command formulation module 400 obtains a plant disease and insect pest attribute point a corresponding to the positioning electronic fence, and analyzes according to the plant disease and insect pest attribute point a that the plant disease and insect pest vegetation image a corresponds to a local forest vegetation area contains a plant disease and insect pest species of "pine moth", and the plant disease and insect pest severity is "medium", the disinfestation pesticide spraying dynamic adjustment command formulation module 400 generates a disinfestation pesticide spraying dynamic adjustment command X, and controls the disinfestation unmanned aerial vehicle to spray pesticide aiming at "pine moth pest" and controls the spraying amount to be medium dose;
the unmanned deinsectization plane enters a positioning electronic fence corresponding to the B point-like plant disease and insect pest vegetation image along a deinsectization travelling route, the deinsectization pesticide spraying dynamic adjustment command formulation module 400 acquires the position related information in real time, the plant disease and insect pest attribute point B corresponding to the positioning electronic fence is acquired, the plant disease and insect pest category contained in a local forest vegetation area corresponding to the B point-like plant disease and insect pest vegetation image is analyzed according to the plant disease and insect pest attribute point B, and the plant disease and insect pest severity is mild, the deinsectization pesticide spraying dynamic adjustment command formulation module 400 generates an deinsectization pesticide spraying dynamic adjustment command Y, and the unmanned deinsectization plane is controlled to spray pesticide aiming at the pine wood nematode disease, and the spraying quantity is controlled to be a small quantity;
in practical application, the frequency of changing the pesticide spraying type is generally low (the types of plant diseases and insect pests of the same piece of forest vegetation are often single), and the pesticide spraying amount is frequently changed for different plant disease and insect pest areas (the damage degree of the plant diseases and insect pests of different areas of the same piece of forest vegetation can be greatly different due to the influence factors such as topography, vegetation composition structure and the like);
it can be understood that the pesticide spraying amounts of the key blocking areas are the same, and the spraying types correspond to the plant diseases and insect pests contained in the dot plant disease and insect pest vegetation image, so that when the unmanned deinsectization plane enters the key blocking areas, the pesticide spraying amount is not required to be adjusted, and only the preset amount of pesticide corresponding to the plant diseases and insect pests contained in the dot plant disease and insect pest vegetation image is required to be sprayed.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (10)
1. A method for analyzing forest vegetation growth, the method comprising:
acquiring a plurality of punctiform plant diseases and insect pests vegetation images, and combining the punctiform plant diseases and insect pests vegetation images to obtain a plant disease and insect pest spreading range diagram;
obtaining a target treatment area according to the plant disease and insect pest spreading range diagram, and making a deinsectization travelling route in the target treatment area;
analyzing all point-like plant diseases and insect pests vegetation images corresponding to the pest control travelling route of the target treatment area in the plant disease and insect pest spreading range diagram, and obtaining a plurality of plant disease and insect pest attribute points;
when the pesticide spraying equipment advances according to the deinsectization advancing route, a deinsectization pesticide spraying dynamic adjustment command is formulated according to the vegetation disease and pest attribute points, and the deinsectization pesticide spraying dynamic adjustment command is output to the pesticide spraying equipment.
2. The method for analyzing the growth conditions of forest vegetation according to claim 1, wherein the step of obtaining a target treatment area based on the plant spread map and making a deinsectization travel route in the target treatment area comprises:
obtaining a target treatment area according to the plant diseases and insect pests spreading range diagram;
analyzing the plant disease and insect pest spreading range diagram, and determining the plane distribution positions of a plurality of dot plant disease and insect pest vegetation images contained in the plant disease and insect pest spreading range diagram;
and intelligently planning an insect-killing travelling route according to the plane distribution positions of the dot-shaped plant disease and insect pest vegetation images.
3. The method of claim 2, wherein the target treatment area includes a pest control area and a critical blocking area.
4. The method for analyzing the growth conditions of forest vegetation according to claim 1, wherein the step of analyzing all punctiform pest vegetation images corresponding to the pest control traveling route of the target treatment area in the pest spreading range map and obtaining a plurality of pest control attribute points of the vegetation comprises:
analyzing a plurality of point-shaped plant diseases and insect pests vegetation images corresponding to the insect pest spreading range diagram of the insect pest killing travelling route one by one;
determining the plant diseases and insect pests types and severity indexes corresponding to each punctiform plant diseases and insect pests vegetation image;
and binding the plant diseases and insect pests types corresponding to each punctiform plant diseases and insect pests vegetation image and the plant diseases and insect pests severity index to obtain a plurality of plant diseases and insect pests attribute points.
5. The method according to claim 4, wherein after obtaining a plurality of vegetation disease and pest attribute points, a positioning electronic fence of each dot disease and pest vegetation image in the pest killing travel route is obtained, and the positioning electronic fence corresponding to the same dot disease and pest vegetation image is bound to the vegetation disease and pest attribute points.
6. The method for analyzing the growth of forest vegetation according to claim 5, wherein the steps of formulating a dynamic pesticide spray adjustment command based on the plant disease and pest attribute points while the pesticide spray device travels along the pesticide travel route, and outputting the dynamic pesticide spray adjustment command to the pesticide spray device comprise:
receiving execution feedback information from the pesticide spraying equipment to determine that the pesticide spraying equipment enters the pest killing travelling route and obtain the real-time position of the pesticide spraying equipment;
analyzing the real-time position of the pesticide spraying equipment, determining a target positioning electronic fence where the real-time position of the pesticide spraying equipment is located, and acquiring vegetation pest attribute points bound by the target positioning electronic fence;
and formulating a dynamic pesticide spraying adjustment command according to the vegetation disease and pest attribute points, and outputting the dynamic pesticide spraying adjustment command to pesticide spraying equipment.
7. The method for analyzing the growth conditions of forest vegetation according to claim 6, wherein the step of formulating a dynamic pesticide spray adjustment command based on the vegetation pest attribute points and outputting the dynamic pesticide spray adjustment command to the pesticide spray device comprises:
acquiring a preset pesticide spraying control model, and determining the type of the required spraying pesticide and the required spraying amount of the vegetation pest attribute points bound by the target positioning electronic fence according to the preset pesticide spraying control model;
according to the type of pesticide to be sprayed and the required spraying quantity, a dynamic adjustment command for spraying the pesticide to be killed is formulated;
and outputting the dynamic pesticide spraying adjustment command to the pesticide spraying equipment.
8. The system for analyzing the growth condition of the forest vegetation is characterized by comprising a plant disease and insect pest spreading range diagram acquisition module, a deinsectization traveling route preparation module, a plant disease and insect pest attribute point acquisition module and an deinsectization pesticide spraying dynamic adjustment command preparation module, wherein:
the plant disease and insect pest spreading range diagram acquisition module is used for acquiring a plurality of punctiform plant disease and insect pest vegetation images and combining the punctiform plant disease and insect pest vegetation images to obtain a plant disease and insect pest spreading range diagram;
the deinsectization traveling route establishment module is used for obtaining a target treatment area according to the plant disease and insect pest spreading range diagram and establishing an deinsectization traveling route in the target treatment area;
the vegetation disease and pest attribute point acquisition module is used for analyzing all point disease and pest vegetation images corresponding to the pest control travelling route of the target treatment area in the disease and pest spreading range diagram and obtaining a plurality of vegetation disease and pest attribute points;
the pesticide spraying dynamic adjustment command making module is used for making a pesticide spraying dynamic adjustment command according to the attribute points of plant diseases and insect pests when the pesticide spraying equipment advances according to the pesticide spraying travelling route, and outputting the pesticide spraying dynamic adjustment command to the pesticide spraying equipment.
9. The forest vegetation growth analysis system of claim 8, wherein the deinsectization travel route formulation module specifically comprises:
the target treatment area acquisition unit is used for acquiring a target treatment area according to the plant disease and insect pest spreading range diagram;
a plane distribution position determining unit for analyzing the plant disease and insect pest spreading range diagram and determining plane distribution positions of a plurality of dot plant disease and insect pest vegetation images contained in the plant disease and insect pest spreading range diagram;
and the deinsectization travel route planning unit is used for intelligently planning an deinsectization travel route according to the plane distribution positions of the dot disease and insect pest vegetation images.
10. The forest vegetation growth analysis system of claim 8, wherein the vegetation pest and disease attribute point acquisition module specifically comprises:
the plant disease and insect pest point vegetation image analysis unit is used for analyzing a plurality of plant disease and insect pest point vegetation images corresponding to the insect pest killing travelling route in the plant disease and insect pest spreading range diagram one by one;
the attribute analysis unit is used for determining the plant diseases and insect pests types and severity indexes corresponding to each punctiform plant diseases and insect pests vegetation image;
and the vegetation disease and pest attribute point obtaining unit is used for binding the disease and pest types corresponding to each punctiform disease and pest vegetation image and the disease and pest severity index to obtain a plurality of vegetation disease and pest attribute points.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410275529.8A CN117875571A (en) | 2024-03-12 | 2024-03-12 | Forest vegetation growth condition analysis method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410275529.8A CN117875571A (en) | 2024-03-12 | 2024-03-12 | Forest vegetation growth condition analysis method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117875571A true CN117875571A (en) | 2024-04-12 |
Family
ID=90577700
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410275529.8A Pending CN117875571A (en) | 2024-03-12 | 2024-03-12 | Forest vegetation growth condition analysis method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117875571A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101801746B1 (en) * | 2017-01-03 | 2017-11-27 | (주)세이프어스드론 | Smart Drone for disaster prevention, System and Method using the same |
| KR20170139849A (en) * | 2016-06-10 | 2017-12-20 | 주식회사 비전아이티 | Monitoring system for forest disease and pest using a drone, and operation method thereof |
| KR20200043801A (en) * | 2018-10-18 | 2020-04-28 | 농업회사법인 만나씨이에이 주식회사 | Artificial Intelligence Plant Management System |
| WO2020174645A1 (en) * | 2019-02-28 | 2020-09-03 | 株式会社オプティム | Computer system, pest detection method, program |
| CN113925039A (en) * | 2021-10-12 | 2022-01-14 | 一鼎(福建)生态园林建设有限公司 | Internet of things-based garden pest and disease intelligent protection system and prevention and control method |
| CN116158421A (en) * | 2023-03-01 | 2023-05-26 | 新疆农业大学 | Crop pest control pesticide spraying method, system, storage medium, equipment and application |
-
2024
- 2024-03-12 CN CN202410275529.8A patent/CN117875571A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20170139849A (en) * | 2016-06-10 | 2017-12-20 | 주식회사 비전아이티 | Monitoring system for forest disease and pest using a drone, and operation method thereof |
| KR101801746B1 (en) * | 2017-01-03 | 2017-11-27 | (주)세이프어스드론 | Smart Drone for disaster prevention, System and Method using the same |
| KR20200043801A (en) * | 2018-10-18 | 2020-04-28 | 농업회사법인 만나씨이에이 주식회사 | Artificial Intelligence Plant Management System |
| WO2020174645A1 (en) * | 2019-02-28 | 2020-09-03 | 株式会社オプティム | Computer system, pest detection method, program |
| CN113925039A (en) * | 2021-10-12 | 2022-01-14 | 一鼎(福建)生态园林建设有限公司 | Internet of things-based garden pest and disease intelligent protection system and prevention and control method |
| CN116158421A (en) * | 2023-03-01 | 2023-05-26 | 新疆农业大学 | Crop pest control pesticide spraying method, system, storage medium, equipment and application |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111246735B (en) | Device for plant management | |
| CN104615146B (en) | Unmanned aerial vehicle spraying operation automatic navigation method without need of external navigation signal | |
| CN109197278B (en) | Method and device for determining operation strategy and method for determining drug spraying strategy | |
| US20220167606A1 (en) | Method for plantation treatment of a plantation field | |
| US20220167546A1 (en) | Method for plantation treatment of a plantation field with a variable application rate | |
| US20220167605A1 (en) | Method for plantation treatment of a plantation field | |
| CN108303963A (en) | A kind of Intelligent unattended driving equipment for plant protection earth station system | |
| EP3673425A1 (en) | Yield estimation in the cultivation of crop plants | |
| Taylor et al. | Precision forestry: operational tactics for today and tomorrow | |
| CN117875571A (en) | Forest vegetation growth condition analysis method and system | |
| KR102221603B1 (en) | Distributing system using agricultural drones | |
| CN111818796A (en) | Device for spray management | |
| KR20210008711A (en) | Robot system using artificial intelligence for preventing blight and harmful insects from damaging plants | |
| CN113435728B (en) | Farm insect pest searching and killing method and system | |
| CN207924492U (en) | A kind of Intelligent unattended driving equipment for plant protection earth station system | |
| CN208092546U (en) | A kind of intelligent sound wave pest trapping system | |
| Gabel | New concept of vine grape protection–knowledge-based approach & high tech | |
| Richard Glass et al. | Desarrollo de nuevas tecnologías que impulsan avances en agricultura de precisión para optimizar insumos y reducir la huella ambiental | |
| CN118278593A (en) | Pest control route planning method and system based on plant protection unmanned aerial vehicle | |
| Salam et al. | Optimal management of witches’ broom disease of lime in presence of extreme environmental factors using stochastic dynamic modelling | |
| Oluwagbayide et al. | APPLICATIONS OF DRONE IN ENHANCEMENT OF AGRICULTURAL PRODUCTION | |
| Moorthi et al. | Smart Agriculture System | |
| DE102023132031A1 (en) | INTELLIGENT WEED TREATMENT | |
| CN118313800A (en) | High-standard farmland big data intelligent management platform and method based on Internet of things | |
| Jaynes | Some recent developments in white-pine weevil research in the Northeast |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |