158 results about "Forest pest" patented technology

The invention relates to the technical field of remote sensing monitoring, in particular to an intelligent forest disease and pest monitoring method and system based on unmanned aerial vehicle remote sensing, and the method comprises the following steps: collecting multispectral data by an unmanned aerial vehicle, extracting reflectivity and smoothing the reflectivity, carrying out differential recognition on abnormal pixels, extracting curves and screening significant changes, segmenting scab boundaries, and classifying health states. And generating a pest and disease map layer prediction trend. According to the method, the reflectivity time sequence is constructed, differential processing is carried out, the vegetation change trend is dynamically captured, abnormal areas are identified by combining slope offset and persistence analysis, significant pixels are screened according to main peak wavelength offset, boundary information is extracted, the scab positioning precision is improved, and the recognition resolution of the lesion state is enhanced through reflectivity combined analysis; accurate description of disease spot dynamic changes is realized, static image dependence limitation is broken through, monitoring time continuity and space response capability are enhanced, and disease and insect pest change capture efficiency and state classification accuracy are effectively improved.

The invention provides a division method and system for a forest pest control area, and relates to the technical field of data processing, and the method comprises the steps: building a forest pest control database through collecting pest data and environment data of a control area; and training a pest risk prediction model based on historical data to generate a risk distribution map. And then, in combination with a GIS technology and a deep learning image segmentation algorithm, intelligent division is performed on the target area, and it is ensured that the unmanned aerial vehicle efficiently covers the prevention and control unit. According to the method, the optimal spraying route can be planned by adopting a path optimization algorithm based on the flight capability of the unmanned aerial vehicle, the pesticide carrying capacity and the environmental conditions, spraying parameters are dynamically adjusted by monitoring the wind speed, obstacle information and the like in real time, precise pesticide application is ensured, the pest control efficiency can be improved, repeated spraying and spraying blind areas are reduced, the pesticide use amount is reduced, and the pesticide application cost is reduced. Intelligent and precise forest pest control is achieved, and the method is suitable for large-scale unmanned aerial vehicle autonomous operation scenes.

The invention discloses a forest prevention and control method based on disease and pest monitoring, and belongs to the technical field of forestry prevention and control, and the method comprises the steps: dividing a target forest into regions according to vegetation types, collecting historical multi-source data, filling the missing data, analyzing a time sequence and causal relationship to construct a time sequence causal diagram, and simulating a disease and pest spatio-temporal dynamic state in combination with current data. And determining a prevention and control risk level and a key induction factor of each region, executing a prevention and control strategy according to the level, and updating a causal diagram through reinforcement learning according to forest health response data. According to the method, a closed loop is formed from data processing to model construction, accurate prevention and control are achieved, efficiency and scientificity are improved, forest ecological changes can be dynamically optimized and adapted, and the prevention and control effect is guaranteed.

The invention relates to the technical field of image recognition, and discloses a multispectral image and deep learning-based forest disease and insect pest automatic recognition method, which comprises the following steps of 1, carrying a multispectral camera containing a red edge wave band through an unmanned aerial vehicle to obtain a forest region image; 2, calculating a red edge normalized vegetation index of the image; 3, performing time sequence modeling on the red edge normalized vegetation index data of more than five consecutive periods, and inputting a time sequence convolutional network to generate an early lesion probability graph; 4, detecting a pest and disease damage target by adopting a multi-scale adaptive feature pyramid network; 5, outputting a disease and pest distribution thermodynamic diagram; and 6, driving the unmanned aerial vehicle cluster to execute precise pesticide spraying. According to the method, through the high sensitivity of the red-edge wave band to chlorophyll degradation and in combination with sequential convolutional network dynamic modeling, an initial lesion area can be recognized 7-10 days before disease development, the early disease recognition capability is remarkably improved, the disease discovery period is shortened, and large-scale disease diffusion is effectively avoided.

The invention provides an unmanned aerial vehicle-based accurate spraying system for forest diseases and insect pests, and relates to the technical field of disease and insect pest treatment, and the system comprises a real-time monitoring module which is used for carrying out real-time monitoring on a forest region; the division and identification module is used for carrying out detection and classification, generating a data classification result, carrying out division and identification on the forest region and determining grid parameters of the forest region; the diffusion prediction module is used for performing disease and pest diffusion prediction to obtain a disease and pest diffusion coefficient; the synchronous updating module is used for constructing a pest and disease prediction spreading trend; and the precise spraying module is used for formulating a spraying task, executing and carrying out effect evaluation, carrying out dynamic feedback optimization, generating a spraying optimization task and carrying out precise spraying of diseases and insect pests. The technical problems that in the prior art, small differences between plant diseases and insect pests and healthy plants are often difficult to distinguish accurately, especially when the plant diseases and insect pests are distributed dispersedly or hidden, spraying leakage or spraying non-uniformity exists, and then the spraying effect is insufficient are solved.

The invention discloses a forest pest and disease development trend prediction method and system combined with remote sensing monitoring, and relates to the related field of forestry monitoring data processing, and the method comprises the steps: carrying out the remote sensing monitoring of a target forest, building a remote sensing image data set, calling ground monitoring data, and carrying out the rasterization based on a time step after the interpolation; performing multi-feature joint extraction on the remote sensing image data set, and superposing extraction results to a unified grid to form a multi-layer feature map; constructing a joint feature matrix by using the rasterized data and the multi-layer feature map, and performing pest distribution identification through a classification model; performing pest development trend prediction by taking the pest distribution diagram as a basic feature and taking the combined feature matrix as an additional feature; and according to a development trend prediction result, carrying out pest abnormity early warning. The technical problem of insufficient prediction accuracy caused by insufficient monitoring efficiency and accuracy in existing forest pest development trend prediction is solved, and the technical effects of improving the monitoring efficiency and accuracy and improving the pest prediction accuracy are achieved.

The invention discloses a forest pine nematode disease identification and positioning method based on deep learning, and the method comprises the steps: constructing a multi-modal data set through the fusion of LiDAR point cloud, image data and time sequence information, and employing the advantages of a convolutional neural network (CNN), a graph neural network (GNN) and a long short-term memory network (LSTM) in the method, thereby achieving the recognition and positioning of the forest pine nematode disease. According to the method, high-precision capture and analysis of tree geometric structure information and time change conditions are realized, and a scientific basis can be provided for tracking the origin of pathogens by determining an initial infection source, so that a more effective control strategy is formulated; by generating the infection probability graph and predicting the transmission path of the pine nematode disease, the transmission of the pine nematode disease can be predicted in advance, and the source of the pine nematode disease can be found; compared with the prior art, prevention measures can be taken more quickly, the risk of pine nematode disease diffusion is reduced, and the efficiency and accuracy of forest pine nematode disease monitoring are improved.

The invention relates to the technical field of data analysis, and further relates to a forest pest and disease identification method based on data analysis, and the method comprises the steps: 1, obtaining an aviation orthoimage of a target forest region and a trapping point count in a set time interval, and associating the trapping count to a sample region unit according to the recent affiliation; 2, a composite simplex complex composed of a plaque layer, a sample area layer and a trapping layer is constructed on a forest map grid, counter examples are screened out through a two-stage verifier, and then suspected pest and disease damage triggering units are output; step 3, establishing a disease and insect pest atlas database, and describing typical modes by disease type topological fingerprints; and carrying out similarity judgment on the topological evidence packet and the disease type topological fingerprint to generate a disease type, a range and a credibility level, and carrying out layering labeling on a forest map grid. According to the method, the fine-grained structure change of diseases and insect pests can be captured in an early stage, and the recognition accuracy and interpretability are improved through multi-source evidence synthesis.

The invention relates to the technical field of pest control, and discloses a natural enemy insect release device for forest pest control, which comprises an unmanned aerial vehicle body capable of identifying and detecting the state of a tree, a putting mechanism arranged below the unmanned aerial vehicle body and a feeding pipe arranged in the putting mechanism, and a pull rope is arranged at the upper end of the feeding pipe. A fixing shaft is fixedly installed at the upper end of the pull rope, a plurality of guide vanes are fixedly installed on the outer side of the fixing shaft, a fixing cylinder with an opening formed in one end is fixedly installed on the guide vanes, the opening is located in the end, away from the fixing shaft, of the fixing cylinder, a balance weight bead is movably installed in the fixing cylinder, and a winding wire is connected between the balance weight bead and the cylinder wall of the fixing cylinder; the lower end of the feeding pipe is provided with a blocking piece which enables the feeding pipe to be communicated inside and outside when the feeding pipe is put. The natural enemy insect releaser aims at solving the problems that a feeding pipe of an existing natural enemy insect releaser is put on the ground, so that insects cannot quickly reach target trees, and diseases and pests of the target trees cannot be prevented and controlled.

The invention relates to the technical field of pest control, in particular to a forest pest prediction system based on data analysis, which comprises a data preprocessing module, a dynamic weight distribution module, a pest feature recognition module, a prediction model training module and a prediction result output module. According to the method, the feature weight is dynamically adjusted through error distribution analysis, the influence of each feature on a pest event is accurately quantified, the adaptability of weight distribution is improved, multi-feature correlation analysis is combined, key features highly related to pest and disease damage are screened, interference of irrelevant factors is reduced, the model input quality is enhanced, and the weight error change trend is dynamically calculated. According to the method, time sequence optimal weight configuration is formed, high-precision prediction of the occurrence trend of diseases and insect pests is realized, the risk distribution trend is quantified and risk areas are divided based on comparison of prediction data and actual occurrence data, a scientific space-time evaluation result is provided for prevention and control of diseases and insect pests, and accurate prevention and control resource configuration is facilitated.

The invention discloses a forest pest monitoring system and method based on three-dimensional remote sensing. The method comprises the steps of 1, collecting remote sensing original data; 2, constructing a standardized space structure data set; 3, constructing a standardized spectral feature set; 4, executing trunk state modeling, structure enhancement modeling and spectrum injection modulation through an improved Vision Mama network, and generating a joint feature tensor; step 5, performing disease and pest area detection, grade classification and type identification on the combined feature tensor to generate a disease and pest area detection result set; step 6, obtaining a historical disease and pest region detection result set, extracting time evolution characteristics of diseases and pests through a pre-trained ConvLSTM model, and outputting a trend prediction result set; and 7, uploading the disease and insect pest area detection result set and the trend prediction result set to a visual interface for visual display. According to the method, the space-time modeling capability and the intelligent early warning level of forest pest and disease monitoring are improved.

The utility model discloses a forestry pest control trap lamp which comprises a top frame, a pesticide box is installed on the top plate, the pesticide box is communicated with a pesticide pump, the pesticide pump is communicated with a pipe frame, an installation plate is installed on the pipe frame, a trap lamp is installed on the installation plate, a net frame is installed on the installation plate, and sponge is arranged in the net frame. The mounting plate is provided with a power grid, the power grid is in sliding connection with a brush holder, the bottom end of the power grid is provided with a transverse plate, the transverse plate is fixedly connected with a bottom frame, the bottom frame is in sliding connection with a filter frame, the filter frame is provided with a pull plate, the pull plate is provided with a clamping frame, the clamping frame is in buckle connection with a buckle frame, and a fan is arranged in the bottom frame. The fan is started to drive insect corpses on the power grid to fall into the filter frame to be collected, the brush frame continuously moves up and down to brush the surface of the power grid, and the insect corpses are conveniently cleaned; when the illumination sensor detects that light is strong, the pesticide pump is started to extract the attractant in the pesticide box and convey the attractant into the sponge.

The utility model discloses a prevention and control trap for forest pest and disease damage, including adjusting rod, base, power grid and collecting tray, base is fixedly installed on the top of adjusting rod, power grid is fixedly connected on the top of base, collecting tray is fixedly installed on the bottom of base, both sides of base are provided with baffle ring, the baffle ring is fixed on the baffle ring, and the baffle ring is fixed on the baffle ring. The blocking ring is movably connected to the inner wall of the collecting disc. By arranging the blocking ring, the mounting hole and the positioning assembly, the blocking ring can be effectively mounted and positioned by the positioning assembly through the mounting hole, pests fall into the collecting disc through the blocking ring after being caught by a power grid, and then the pests in the collecting disc can be blocked through the blocking ring; the device solves the problems that the device is lack of a protection structure, a collection box cannot be protected after pests are collected through a collection disc, the pests in the collection box splash all around during wind blowing or raining, and the surrounding environment is affected.

The invention provides a forestry pest and disease damage real-time monitoring method and system, and relates to the technical field of data processing, and the method comprises the steps: selecting a position A of an early warning node, a node position B with the maximum yield per unit time in a past one hour, and a node position C with the maximum spatial distribution dispersion; forming a monitoring unit according to the position A, the node position B and the node position C of the early warning node; calculating the radius of a circumcircle of the measurement unit, and determining the grid division density based on the radius of the circumcircle; according to the grid division density, performing adaptive grid division on the monitoring unit to obtain a plurality of grid units; generating a space risk adjustment value according to the space distribution characteristics of the grid units; constructing a spatial diffusion model according to the regional and spatial risk adjustment values of the collaborative outbreak phenomenon; obtaining an insect condition risk level according to the spatial diffusion model; and generating a comprehensive insect condition early warning according to the insect condition risk level. According to the method, the time sequence mutation can be dynamically sensed, and the spatial diffusion risk can be accurately evaluated.

The invention discloses an artificial mangrove forest pest monitoring and early warning method and system, and belongs to the technical field of ecological environment monitoring, and the method comprises the steps: collecting multi-frequency pest acoustic signals and low-altitude thermal infrared image data, constructing a pest energy density field, and forming a multi-dimensional propagation feature matrix; establishing a pest risk node map based on the matrix, simulating a propagation path and calculating a pest energy coupling strength coefficient; carrying out energy refraction remapping and abnormal superposition region identification, extracting an energy convergence core region, and generating a propagation trend trajectory diagram; constructing a combined prediction model of the microscopic infection characteristics and the macroscopic diffusion situation of the insect pests, outputting an evolution stage risk curve, and identifying secondary outbreak latent points; the method has high adaptability, high accuracy and response preposition, and the intelligent level of mangrove forest pest monitoring and early warning is remarkably improved.

The invention discloses a forestry pest intelligent prevention and early warning method and system based on image recognition, and the method comprises the steps: firstly obtaining a multi-dimensional image comprising different spectral frequency bands and spatial resolutions, carrying out the processing of a texture optimization model of multi-dimensional image fusion, and deeply mining the texture features of pests to form a fusion image; then, a forestry pest population recognition algorithm is combined with various parameters such as body types and antennas to judge population types; establishing a spatial distribution model based on categories and related parameters, and predicting a development trend in combination with a growth cycle and environmental adaptability parameters; and finally, generating prevention and early warning information by integrating the category, distribution and prediction data. The system comprises six units including a multi-dimensional image acquisition unit and an image fusion processing unit, all the units cooperate with one another, the whole process processing from image acquisition to early warning information generation is achieved, and an efficient and accurate technical scheme is provided for forestry pest prevention and control.

The invention discloses a forest pest control infusion device, relates to the technical field of forestry control equipment, and aims to solve the problems that an existing forest infusion device is large in size and loose in structure, needs additional accessories for carrying in complex terrains, increases load and is easy to lose and damage parts; the technical problems that during drilling installation, the hole diameter is difficult to control, liquid medicine leaks easily, an inserting needle is difficult to fix or a tree trunk is damaged secondarily, a guide pipe is blocked due to the fact that wood chips are not cleaned thoroughly, and infusion is forced to be interrupted and drilling is carried out again are solved. The gun drill is adopted for providing power, so that the use size of the device is reduced, the infusion step can be completed by opening the control valve with the other hand after punching is completed, the use difficulty of the device is reduced, meanwhile, a drill bit does not need to be taken out after punching is completed, and an additional infusion device does not need to be adopted; by means of the integrated design, the tedious steps of replacing equipment are omitted, the drill bit does not need to be repeatedly inserted and pulled, and then secondary damage to forest trees is avoided.

The invention provides a forest insect pest prediction method and system and a readable storage medium, and relates to the technical field of forest insect pest prediction.The forest is divided into a plurality of grids, main forest tree types, forest tree characteristics, soil characteristics and meteorological data of each grid are collected, and scientific assessment and management of insect pest risks are achieved. The method mainly comprises the following steps: firstly, carrying out characteristic parameter acquisition on grids, and carrying out similar grid group division based on soil characteristics; secondly, constructing an insect pest prediction model through a random forest algorithm, training by utilizing insect pest data of a sample grid, and predicting insect pest severity levels of other grids; and finally, analyzing the pest severity level change of each grid at the current and historical moments, generating an alarm index, and sending out a corresponding alarm signal according to a preset threshold value. According to the method, the environmental suitability index and the forest vulnerability index are combined, the insect attack grade is determined by adopting the expert scoring method, and the insect attack risk can be effectively monitored and early warned, so that a scientific basis is provided for forest management.

The invention relates to the technical field of image processing, in particular to a forest pest intelligent identification method based on unmanned aerial vehicle remote sensing, which comprises the following steps: analyzing the position distribution condition of pixel points in each suspected pest connected domain in an LAB color space coordinate system, and obtaining the green sensitivity of each suspected pest connected domain; dividing all suspected pest and disease connected domains into high green sensitivity connected domains and low green sensitivity connected domains based on green sensitivity; acquiring an enhancement coefficient of a remote sensing grayscale image of the to-be-detected man-made forest according to a grayscale difference condition of pixel points between the high green sensitivity connected domain and the low green sensitivity connected domain and the edge feature parameters; enhancing the remote sensing grayscale image of the to-be-detected man-made forest according to the enhancement coefficient to obtain an enhanced remote sensing image of the to-be-detected man-made forest; and performing intelligent forest disease and insect pest identification based on the enhanced remote sensing image of the to-be-detected man-made forest. According to the invention, the recognition degree of the forest regions with diseases and pests in the man-made forest is improved.

The utility model belongs to the technical field of forest disease and pest control, and particularly relates to a forest disease and pest control spraying device which comprises a straight pipe, a piston plate is slidably mounted in the straight pipe, a connecting rod is mounted on the top side of the piston plate, a threaded rod is rotatably mounted on the bottom side of a mounting frame, and a worm gear is mounted on the outer side of the bottom end of the threaded rod. A guide rod is mounted on the top side of the mounting frame, and a worm is mounted on the outer side of the rotating shaft; a servo motor is started, a rotating shaft at the output end of the servo motor drives a worm to rotate, rotation of the worm drives a worm gear to rotate, then a threaded rod rotates, a connecting rod vertically ascends and descends along a guide rod, the connecting rod drives a piston plate to synchronously ascend and descend in a straight pipe, if a forest tree is high, the threaded rod drives the piston plate to ascend, the spraying coverage range of a spraying nozzle is enlarged, and the forest tree is short; the piston plate descends, the spraying area is reduced, the spraying height is accurately adjusted, liquid medicine is intensively sprayed to forest tree parts needing prevention and control, and waste of the liquid medicine is reduced.

The application provides a forestry pest damage monitoring device, and relates to the field of forestry pest monitoring. The device comprises a base and an ultraviolet insecticidal lamp. The upper surface of the base is fixedly connected with a monitoring table. The upper surface of the monitoring table is fixedly connected with support columns in a symmetrical manner. The upper surface of the support columns is fixedly connected with mounting plates. The upper surface of the mounting plates is fixedly connected with support plates in a symmetrical manner. The upper surface of the support plates is fixedly installed with a top plate. The ultraviolet insecticidal lamp is fixedly installed on the lower surface of the top plate. The device can attract pests by the ultraviolet insecticidal lamp, and the pests can be knocked off and dropped into the through groove through the guide cylinder and then dropped onto the middle of the upper surface of the monitoring table. When the pests are accumulated on the surface of the monitoring table, the accumulated pests can be swept into the collecting groove by starting the cleaning assembly, and then dropped into the collecting assembly for collection. The device can prevent a large number of pests from being accumulated on the monitoring table and overlapping together, and the long-term non-treatment can affect the monitoring condition of the infrared sensor and the monitoring effect.

The invention relates to the technical field of pest monitoring, in particular to a forest pest intelligent monitoring method based on unmanned aerial vehicle remote sensing. Hyperspectral data and a plurality of forest images of each measuring point of the to-be-measured forest area at different shooting positions are acquired; and determining insect pest characteristic values by using the spectral curve change difference of the hyperspectral data and the wavelength absorbance. Considering that the insect pest area range is gradually expanded and adjacent measuring points have similar characteristics, the mutation of insect pest characteristic values between the measuring points at the same shooting position is analyzed to obtain an insect pest mutation coefficient, and the jitter influence of the unmanned aerial vehicle is represented. And analyzing the number and position features of the edge lines and the ghost lines in the forest image, and determining a shooting jitter feature value. And in combination with the pest mutation coefficient and the shooting jitter characteristic value, the reference value of the pest characteristic value of each measuring point is quantified, the shooting position less affected by the jitter of the unmanned aerial vehicle is screened, and finally monitoring is performed based on the pest characteristic value under the screened shooting position, so that the accuracy is improved.

The utility model relates to the technical field of forestry pest trapping devices, and discloses an easily-detachable forestry pest trapping box which comprises a first transparent shell, a second transparent shell is arranged on the inner bottom wall of the first transparent shell, and a box cover tightly attached to the top of the second transparent shell is arranged on the top of the first transparent shell. A deinsectization assembly is arranged at the bottom of the box cover, and conical inlet pipes with one ends communicating with the inner wall of the second transparent shell are arranged on the left side wall and the right side wall of the first transparent shell correspondingly. According to the forestry pest trapping box easy to disassemble, by arranging the lock catch assembly, when the box cover needs to be disassembled, a worker can pull two lock catches towards the two sides, so that the lock catches are separated from lock catch bases, and at the moment, the box cover can be disassembled from the first transparent shell; and the box cover can be disassembled without rotating the box cover, so that the disassembly is relatively convenient, the practicability of the device is improved, and the device is convenient to use by a worker.

1. Name of the product in this design: Alarm device (forest animal pest control). 2. Purpose of this design: for use in alarm devices. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention belongs to the field of forest control, and provides a tree trunk punching and pesticide injection device for forest pest control, which comprises a vehicle body, an encircling mechanism is mounted at the top of the vehicle body, the encircling mechanism is used for relatively fixing the vehicle body and a tree trunk, a mounting frame is fixedly mounted on the vehicle body, and an adjusting mechanism is mounted on the mounting frame. A medicine injection mechanism is installed at the output end of the adjusting mechanism, and the adjusting mechanism is used for adjusting the horizontal position, the vertical position and the angle of the medicine injection mechanism. The vehicle body is fixed to a tree trunk through the surrounding mechanism, the vehicle body is prevented from being pushed away by the tree trunk during punching, the punching efficiency is improved, punching and pesticide injection are conducted on the tree trunk through the pesticide injection mechanism, manual punching and pesticide injection by workers are avoided, the workers are prevented from squatting to work, the workers only need to push the vehicle body to be close to the tree trunk, and the labor intensity of the workers is lowered. Therefore, automatic punching and medicine injection work can be achieved, and the working efficiency is greatly improved.

The present invention discloses a forest pest early warning model construction system and method, which relates to the technical field of forestry early warning model construction. It outputs an impact factor for each block, and re-corrects the initial monitoring intensity of each block based on the impact factor. After regularly conducting a comprehensive analysis of the real-time data of all blocks, the overall performance index of the monitored forest area is obtained, and the overall performance index is combined with dynamic judgment rules to analyze whether it is necessary to optimize and adjust the current monitoring intensity of all blocks. After dynamically generating a personalized plan for each block based on the analysis results, the personalized plan is mapped to the monitoring forest area early warning model for display. The construction system can dynamically adjust the monitoring intensity according to the actual situation of different blocks, improve the pertinence and accuracy of monitoring, and generate an overall performance index by regularly comprehensively analyzing the real-time data of the blocks and combining it with dynamic judgment rules to dynamically adjust the monitoring strategy, so that the system can adapt to environmental and risk changes.

1. Name of the design product: Forestry insecticidal lamp. 2. Use of the design product: This design product is used for forestry insect control. 3. Design key points of the design product: Lies in the shape. 4. Picture or photograph that best shows the design key points: Stereogram.

This invention relates to the field of data analysis technology, and more specifically, to a method for identifying forest pests and diseases based on data analysis. The method includes: Step 1: acquiring aerial orthophotos of the target forest area and counting trapping points within a set time interval, and associating the trapping counts with the nearest-nearest-assigned sample area units; Step 2: constructing a complex simplex on a forest map grid, consisting of a patch layer, a sample area layer, and a trapping layer, and outputting suspected pest and disease triggering units after filtering out negative examples using a two-stage verifier; Step 3: establishing a pest and disease map database, describing typical patterns using disease type topological fingerprints; performing similarity assessment between the topological evidence package and the disease type topological fingerprints to generate disease type, extent, and confidence level, and labeling the data in layers on the forest map grid. This invention can capture fine-grained structural changes in pests and diseases at an early stage, and improves identification accuracy and interpretability by utilizing multi-source evidence synthesis.

The invention belongs to the technical field of data processing, and provides an unmanned aerial vehicle forest damage monitoring method and system based on time perception attention, and the method specifically comprises the steps: collecting images through an unmanned aerial vehicle, constructing a forest damage image sequence library, constructing a pest perception model based on time perception attention through the forest damage image sequence library, and obtaining a pest related vector; constructing a K-layer perceptron according to the insect pest correlation vector, extracting an image descriptor from the K-layer perceptron, obtaining an insect pest monitoring degree, collecting an insect pest image through the insect pest monitoring degree, marking an insect pest region, continuously obtaining the insect pest monitoring degree for the insect pest region, and calculating a forest pest occurrence track number; and finally, judging a forest damage monitoring result according to the forest damage occurrence track number. Modeling of insect population density fluctuation and control hysteresis effect on a micro scale is realized, so that hierarchical memory of historical intervention response and inflection point sensitivity is enhanced by using time sequence perception, power consumption and computing power are released, storage resources are saved, cruising ability is improved, and signal anxiety in a forest scene is prevented.

The utility model discloses a pesticide spraying device for forestry disease and pest control, and relates to the technical field of pesticide spraying devices. The pesticide spraying device comprises a flat car, a pesticide barrel is arranged on the upper side of the flat car, a pesticide spraying mechanism connected with the pesticide barrel is arranged on the upper side of the flat car, a transmission shaft is rotationally matched in the pesticide barrel, and a first servo motor used for driving the transmission shaft to rotate is arranged on the upper side of the pesticide barrel. The first servo motor is started to drive the transmission shaft to drive the plurality of stirring blades, the filter cartridge and the auger blade to rotate, and the auger blade drives the liquid medicine between the filter cartridge and the medicine barrel to vertically lift, so that the liquid medicine higher than the interior of the filter cartridge between the filter cartridge and the medicine barrel flows back into the filter cartridge through filter holes in the filter cartridge, and the liquid medicine is conveniently and circularly mixed in the vertical direction; when the stirring blades rotate, liquid medicine in the medicine barrel can be horizontally stirred conveniently, the mixing uniformity of the liquid medicine in the medicine barrel can be improved conveniently, meanwhile, the inner wall of the side portion of the medicine barrel can be cleaned conveniently through the stirring blades, and medicine spraying work can be conducted through the medicine spraying mechanism.