8198 results about "Ecology" patented technology

The invention relates to the technical field of information processing, in particular to a water conservancy slope ecological management method and system based on multi-source sensing data. The method comprises the following steps: collecting meteorological monitoring data, soil hydrological monitoring data, vegetation coverage monitoring data, topographic surveying and mapping data and water and soil loss monitoring data as original slope ecological environment data; performing data pre-registration processing on the original slope ecological environment data to obtain standardized slope ecological environment data; performing erosion-runoff coupling process simulation by using the standardized slope ecological environment data to obtain water and soil erosion dynamic parameters; performing water and soil loss trend prediction based on the water and soil erosion kinetic parameters, and generating water and soil loss risk assessment data; and designing an ecological management scheme based on the water and soil loss risk assessment data. By dynamically adjusting and optimizing the ecological management scheme, the ecological state of the slope is monitored in real time, and continuous improvement and self-adaptive optimization of ecological management of the water conservancy slope are achieved.

The invention provides a seedling cultivation growth condition monitoring method, which comprises the steps of performing data processing on a time series data set of hydrological conditions, obtaining a dynamic association rule among different hydrological parameters, constructing an association model of the hydrological parameters, and quantitatively describing mutual influence and restriction relationships among water temperature, dissolved oxygen and salinity parameters by the association model; performing data processing on the time sequence data set of seedling growth, establishing a seedling growth process model, determining key parameters of a seedling growth curve by analyzing growth rate change rules of seedlings in different growth stages, and correcting the model according to initial quality and stocking density factors of the seedlings; a seedling growth prediction model is combined with an intelligent optimization algorithm, key control parameters in the breeding process are dynamically adjusted, and according to the seedling growth trend predicted by the model, hydrological conditions and feeding strategies are adaptively optimized, so that intelligent management of the breeding process is realized.

The invention discloses an amphibious unmanned aerial vehicle riverway sediment concentration real-time monitoring method based on underwater light field imaging and cross-modal fusion, and relates to the technical field of riverway sediment monitoring. Comprising the following steps: acquiring aerial multispectral data and preprocessing the aerial multispectral data; an integrated polarized light field camera is carried on an amphibious unmanned aerial vehicle to capture underwater light field data, and underwater three-dimensional light field information is reconstructed and sediment scattering characteristics are extracted through an optical model and a lightweight deep learning network; the air multispectral data and sediment scattering characteristics are fused through space-time alignment and an attention mechanism, a sediment concentration prediction model is generated, and then a spatial distribution diagram of the river sediment concentration is output; and carrying out real-time monitoring and early warning on the river sediment concentration according to the spatial distribution diagram of the river sediment concentration through edge calculation and cloud collaboration architecture. The method is combined with an advanced deep learning algorithm, high-resolution silt concentration inversion can be realized, and the method has real-time performance and adapts to a complex water body environment.

The invention provides a coast defense monitoring system based on unmanned aerial vehicle group collaboration and an application method thereof, and relates to the technical field of coast defense monitoring, and the coast defense monitoring system integrates air unmanned aerial vehicles, water surface unmanned ships and underwater unmanned ships, constructs a four-dimensional collaborative monitoring network, and combines a frequency domain resonance superposition technology and real-time analysis of marine environment variables. A dynamic three-dimensional environment model is generated, threat prediction of a time dimension is realized, multi-source sensor data can be fused in real time, a complete space contour of a target is formed, threat distribution in several hours in the future is predicted through environment change, for example, unmanned aerial vehicle deployment is adjusted in advance to cope with illegal border crossing behaviors in storms, and the risk of threatening is reduced. Quantum entanglement communication and acousto-optic hybrid communication ensure the stability and security of data transmission, and support millisecond response. According to the effect, the real-time performance and foresight of coast defense monitoring are remarkably improved, so that the system not only can quickly cope with current threats, but also can actively prevent potential risks.

The present disclosure provides water-soluble film packages composed of a water-soluble film, where the packages include: one or more compartment(s) including dehydrated microbes. The disclosure further provides methods of production of the water-soluble film packages, and methods of application thereof. The water-soluble packages of the disclosure enable convenient and accurate application of microbial dry powders to plants, promote uniform dispersion of powdered microbes, enhance microbial shelf life, and enhance the survival of microbes on seed, while being environmentally sustainable.

The invention relates to the field of soil spectrum analysis, in particular to a farmland soil environment detection method and system. The method comprises the following steps: firstly, analyzing fluctuation characteristics of near infrared spectrum curves of a plurality of soil samples in a preset window of a target wavelength to obtain undisturbed degrees of the near infrared spectrum curves in the target wavelength; fitting spectral data points of the near infrared spectral curve, and obtaining feature retention degrees of the extreme points on the fitted curve according to the difference of fitting absorbance of adjacent extreme points on the fitted curve, the absorbance of each wavelength and the difference of the fitting absorbance and the wavelength distribution of the extreme points on each fitted curve; filtering the spectral data points of the target curve based on the non-interference degree and the feature retention degree to obtain a filtering curve; according to the method, the interference information in the near infrared spectrum curve is removed, the existing key information is reserved as much as possible, and the precision of farmland soil environment detection is improved.

The invention discloses a forestry ecological environment real-time monitoring and management method based on big data, and belongs to the technical field of forestry ecological environment management, and the method comprises the following steps: S1, multi-source heterogeneous data collection and sensor network deployment; s2, multi-modal data fusion and intelligent transmission: developing an adaptive communication protocol dynamic switching module, and automatically switching to a satellite communication link in a 4G / 5G network blind area; s3, mass data storage and distributed calculation: constructing a hybrid cloud storage architecture, and storing real-time monitoring data into a Redis cache queue; s4, intelligently extracting ecological environment indexes; s5, dynamically evaluating the ecological bearing capacity; s6, performing multi-level early warning and emergency response; s7, making a precise forestry management decision; and S8, carrying out system self-optimization and closed-loop management. According to the method, the air-space-ground integrated monitoring network is constructed, so that the comprehensiveness and the real-time performance of forestry ecological environment perception are remarkably improved; multi-source data of the unmanned aerial vehicle, the satellite remote sensing and the ground sensor are complementary.

Systems and methods provide collection of telemetry by an Information Handling System (IHS). A policy decision point (PDP) of a zero-trust computing environment controls access to protected resources and receives an indicator of attack related to the IHS. The PDP identifies a telemetry definition specifying telemetry being collected by the IHS and updates the telemetry definition to specify a subsystem telemetry chain for configuring telemetry by hardware subsystems of the IHS that are related to the indicator of attack. The updated telemetry definition is transmitted to the IHS. Upon identifying the subsystem telemetry chain in the updated telemetry definition, the IHS adjusts telemetry generation by one or more of the hardware subsystems of the IHS based on their position in the subsystem telemetry chain.

The invention relates to the technical field of slope protection, in particular to a slope stability assessment method and system applied to mine ecological restoration, and the method comprises the steps: collecting basic geological data and dynamic monitoring data of a slope in an assessment region based on a set data collection frequency; performing space-time division according to a preset time window and a space grid to obtain a plurality of space-time window units, and calculating to obtain a multi-dimensional stability evaluation index according to the basic geological data and the dynamic monitoring data corresponding to each space-time window unit; based on the multi-dimensional stability evaluation indexes corresponding to different space-time window units, constructing a space-time serialized slope stability characteristic matrix; inputting the dynamic stability data into a preset multi-dimensional stability evaluation model to obtain a dynamic stability index; correcting the dynamic stability index by considering the obtained real-time environmental load interference data to obtain a corrected stability index; and a preset slope stability threshold value is utilized to perform early warning judgment.

Systems and methods provide collection of telemetry by an Information Handling System (IHS). A policy decision point (PDP), of a zero-trust computing environment that controls access to a plurality of protected resources, receives an indication of resource piracy related to hardware components of the IHS. The PDP identifies a telemetry definition specifying telemetry being collected by the IHS and updates the telemetry definition to specify an updated telemetry chain for configuring telemetry collection by the hardware components of the IHS. The updated telemetry definition is transmitted to the IHS. Upon identifying the updated telemetry chain in the telemetry definition received from the PDP, the IHS adjusts telemetry generation by one or more of the hardware components of the IHS based on their position in the telemetry chain.

The invention discloses an ecological pontoon device and method for removing heavy metal in a water body, and relates to the technical field of sewage treatment.The ecological pontoon device comprises an overwater moving platform, a power propeller, a self-cruising module assembly, a heavy metal ion removing assembly and a control system, and the power propeller is installed at the bottom of the overwater moving platform; the self-cruising module assembly is mounted on the water mobile platform; the heavy metal ion removal assembly comprises an acrylic square groove formed in the water moving platform, ecological filler filled in the acrylic square groove and a micro diaphragm water pump installed between the acrylic square groove and the water moving platform, and the micro diaphragm water pump is suitable for pumping water from the lake into the acrylic square groove. The water is filtered by the ecological filler and is pumped back to the lake body again; the control system is electrically connected with the power propeller and the self-cruise module assembly. According to the method, heavy metal ions in the water body can be effectively removed, and the efficiency can be remarkably improved while the cost is reduced.

The invention discloses a percolate intelligent remote monitoring and control system and method, and relates to the technical field of percolate monitoring. The percolate intelligent remote monitoring and control method comprises the following steps: S1, acquiring percolate working condition response data, and preprocessing the percolate working condition response data; s2, analyzing joint mutation characteristics of the three-dimensional core mutation parameters, identifying mutation event candidate points, aggregating to form mutation sections, and constructing a mutation section data set; s3, constructing an intervention judgment data set based on the abrupt change section data set, evaluating the intervention triggering strength of the abrupt change section, and judging whether to implement an intervention strategy or not based on an evaluation result; and S4, calling mutation event candidate points in which mutation sections are not formed, calculating trend characteristic parameters of various working conditions, evaluating working condition evolution risks and judging risk levels of abnormal candidate sections. The problem that the blocking risk cannot be recognized in time when the inlet water is mixed with the suspended fibers is solved.

The invention discloses a river water surface two-dimensional flow field reconstruction method based on effective tracer detection and tracking, and the method comprises the steps: carrying out the distortion correction of an original video image sequence, and setting an ROI region according to the water level detection river water surface range; the method comprises the following steps: collecting a multi-scene floating object data set, screening floating objects with high relative brightness and clear outlines in different scenes, and training a YOLO model to detect the floating objects on the surface of a river; using an OCSORT matching tracking method to track adjacent frames of targets to obtain a trajectory, and filtering according to the length, angle and variance of the trajectory to obtain a stable trajectory; according to the method, object information obtained through target detection is utilized, according to the area, the area change rate and the length-width ratio of a floating object on an image, the following performance and stability of the floating object are evaluated, a track fusion weight is calculated, and the influence of unreliable floating objects is reduced; and gridding the river surface area after orthographic correction, and for a grid with a plurality of tracks, calculating the average flow velocity of the grid according to the confidence coefficient of each track to obtain a gridding two-dimensional flow velocity vector field. The method can accurately identify the floating object which meets the requirements of visibility, following performance and stability on the river surface as an effective water flow tracer, and is suitable for measuring the flow velocity of the river surface in complex scenes such as night, storm, flare, shadow and the like.

The invention relates to the technical field of pattern recognition, in particular to an ecological restoration nursery stock quality detection system based on pattern recognition, which comprises an image acquisition module for controlling camera equipment to acquire nursery stock images under target time and illumination conditions to obtain an original image set; and performing format unification and cleaning on the original image set, removing image noise and irrelevant information, and generating a cleaned image set. According to the method, the image pickup equipment is controlled to obtain the original nursery stock image under the target time and illumination condition, the consistency and stability of image data are improved, after unified format and information cleaning are carried out on the original image, image noise and invalid information are eliminated, and the nursery stock feature extraction precision is improved. Based on multi-dimensional feature extraction of colors, textures and shapes and comparative analysis of known quality standards, accurate judgment of seedling growth quality is realized, and scientificity and reliability of seedling screening are improved.

The invention provides a carbon neutralization evaluation method for an ecological park, and the method comprises the steps: obtaining the basic data of various carbon assets in the ecological park, and the basic data comprises the natural ecological system carbon sink capability and human activity carbon emission intensity data; according to the carbon asset basic data, a time sequence analysis method is adopted to carry out modeling on the change trend of the carbon sink capacity and the carbon emission intensity, and a change trend model is obtained; modeling the spatial distribution of the carbon reserves and the carbon flux by utilizing a geographic information system technology and combining a change trend model to obtain a spatial distribution model; key variables are extracted from the spatial distribution model, and the effects of different factors on the carbon assets are quantified by adopting a multiple regression analysis method; acquiring carbon asset monitoring data, evaluating data quality, and if an abnormal value exists, performing correction by adopting a data cleaning algorithm; and according to the corrected carbon asset data, adopting a random forest model to predict the carbon sink capacity and the carbon emission intensity, and generating a dynamic evaluation result.

The invention discloses an acid mine wasteland ecological restoration plant dynamic optimization configuration method, and relates to the field of ecological restoration, and the method comprises the following steps: 1, collecting soil attribute data in a predetermined range of an acid mine wasteland in a dotted manner, and synchronously obtaining growth attribute data of to-be-selected plants and periodic weather data of a target area; step 2, extracting a deterioration feature set having a deterioration effect on plant growth based on the soil attribute data, and analyzing a bioremediation feature set capable of inhibiting the deterioration feature in the plant attribute data to generate a candidate plant set; 3, constructing a dynamic environment simulation model based on a deep learning algorithm, wherein input dimensions comprise weather data time sequence features, soil deterioration feature vectors and a plant bioremediation feature matrix; the method can accurately predict the restoration effects of plants under different climate and soil conditions, simulate the effects of different intervention measures in real time, output the optimal intervention scheme, and ensure the balance between the resource utilization efficiency and the restoration effects.

A river-lake system ecological scheduling method coupled with basin hydrological response belongs to the field of reservoir ecological scheduling, and comprises the following steps: firstly, selecting a research area to represent a hydrological station, and drawing a basin hydrological evolution topological graph; secondly, constructing a watershed hydrological response model step by step, and simulating a response process of lake hydrological situation to upstream reservoir drainage; thirdly, putting forward an ecological evaluation index, and quantifying lake hydrological-ecological response; 4, constructing a multi-objective optimization scheduling model of the river-lake system; 5, optimizing the multi-objective optimization scheduling model of the river-lake system; and finally, based on a fuzzy optimization method, recommending an optimal reservoir scheduling rule conforming to decision preference. According to the method, the beneficial benefits such as power generation and water supply of the reservoir are guaranteed, the adverse effect of concentrated water storage of the upstream reservoir on the ecology of the downstream lake can be weakened to the maximum extent, the reservoir scheduling rule with the maximum comprehensive benefits is recommended, and scientific scheduling basis and decision support are provided for green development of a river-lake system.

The invention relates to the technical field of building materials, in particular to a Yellow River superfine sand aggregate interface reinforcing agent and a preparation and use method thereof.The interface reinforcing agent is prepared from 0.05-0.1 part of graphene oxide powder, 50-100 parts of a silane coupling agent, 50-100 parts of nano-silicon dioxide, 10-30 parts of oxalic acid and 5000-7000 parts of water; graphene oxide powder, a silane coupling agent and nano silicon dioxide are jointly used for preparing an interface modifier for performing interface modification treatment on the Yellow River superfine sand, so that the interface bonding force between the Yellow River superfine sand and a cement hydration product is enhanced.

The invention discloses an ecological carbon sink measurement and estimation data fusion platform for the thermal power industry, and belongs to the technical field of data fusion. The method is realized through five steps of a data acquisition module, a carbon sink measurement and calculation module, a prediction model construction module, a data fusion module and a decision support module. According to the invention, through butt joint with a thermal power enterprise energy management system, production data including generating capacity and coal consumption are acquired in real time, and the timeliness of the data is greatly improved. Ecological environment data and meteorological data around a thermal power enterprise are comprehensively collected by using a satellite remote sensing technology and a ground sensor, and the comprehensiveness and accuracy of the data are ensured. According to the method, a dynamic adjustment mechanism is adopted, and the pre-estimation model is continuously optimized according to real-time data feedback, so that the model can adapt to the change of the environment. And time sequence analysis and regression analysis are combined to form an integrated model, so that the accuracy and reliability of a pre-estimation result are greatly improved.

The invention discloses an aquatic product ultra-low temperature fresh-keeping processing control method, and relates to the technical field of aquatic product fresh-keeping processing, and the method specifically comprises the following steps: evaluating a fat local oxidation risk grade caused by oxygen exposure on the surface of a high-fat aquatic product in each region in a freezing chamber; dividing each area in the freezing chamber into a low risk area, a medium risk area and a high risk area according to an evaluation result; constructing an oxidation risk adjustment mechanism according to the division result of each region in the freezing chamber; in the implementation process of the oxidation risk adjustment mechanism, whether the adjustment effect of the oxidation risk adjustment mechanism on each region can reach the expectation or not is evaluated, and the oxidation risk adjustment mechanism is optimized according to the evaluation result. According to the method, the problem of fat oxidation caused by oxygen exposure on the surface of the high-fat aquatic product in the ultralow-temperature freezing process is solved, and the preservation effect in the freezing process is effectively improved through real-time monitoring and dynamic optimization of an adjustment mechanism.

The invention relates to an ecological landscape type disaster reduction seawall, the section form of the seawall is a gentle slope into-sea multi-stage composite type, and the seawall structurally comprises a seawall foot on the seaside, a first-stage planting platform, a gentle slope, a second-stage planting platform, a waterside platform, a wave wall and a road which are sequentially arranged from sea to land; on the basis of ensuring safety, the seawall is subjected to ecological landscape design, so that the seawall can play roles in intercepting silt and purifying water; the effects of weakening wave energy and reducing marine disaster threats can be achieved; and meanwhile, the hydrophilicity of the seawall can be improved, and a leisure activity space is provided for people. The invention further relates to a design method of the ecological landscape type disaster reduction seawall and a method for determining the crest elevation of the ecological landscape type disaster reduction seawall. The section form of the seawall can be determined according to the wave height and the height difference between the sea level and the road surface, the crest elevation of the seawall can be effectively reduced, the engineering cost is reduced, and the seawall ecological function is increased.

The invention discloses a method for denitrifying wastewater by using a low-temperature-resistant heterotrophic nitrification and aerobic denitrification bacterium, and relates to a method for denitrifying wastewater by using a biological bacterium, the bacterium is Pseudomonas putida, is named as Pseudomonas umsongensis BK17, belongs to Pseudomonas, and is preserved in the China Center for Type Culture Collection (CCTCC), the preservation number is CCTCC M 20242924, and the preservation date is December 27, 2024. The strain is a heterotrophic nitrification-aerobic denitrification bacterium, can efficiently remove inorganic nitrogen pollution in a water body, still has good denitrification performance under low-temperature stress, and is high in low-temperature tolerance. The strain can efficiently treat nitrogen-containing wastewater under the condition of 10 DEG C, and the removal efficiency can reach 99% or above. The method has great potential in the application of inorganic nitrogen pollution treatment of domestic sewage and other water bodies in cold regions in China.

The invention provides a sheep body size measuring method and device based on three-dimensional reconstruction and point cloud segmentation, a medium and a program product, and relates to the technical field of computer vision. The method comprises the following steps: acquiring a sheep image of a to-be-detected sheep, and preprocessing the sheep image to obtain a multi-view sheep target point cloud; performing point cloud registration processing on the multi-view sheep target point cloud to obtain a sheep three-dimensional model; performing point cloud segmentation processing based on the body size measurement key points and the sheep three-dimensional model to obtain key point region point clouds; based on the key point region point cloud, determining a region point cloud projection space, performing attitude normalization on the interval point cloud, and determining an attitude normalized key point region point cloud; and calculating the body size data of the to-be-measured sheep based on the point cloud of the key point region subjected to attitude normalization. According to the embodiment of the invention, through three-dimensional reconstruction of the body surface point cloud of the sheep, non-contact measurement of the body size data of the sheep is realized, and the measurement efficiency and accuracy are improved.

The invention relates to the technical field of edible fungus cultivation and soilless culture, in particular to a preparation method and application of an organic ecological soilless culture substrate for dictyophora rubrovolvata. Auxiliary materials such as perlite, vermiculite, river sand and wood chips are mixed according to the proportion, and the soilless culture substrate is prepared. The matrix is completely used for soil-covered cultivation of dictyophora rubrovolvata, compared with a traditional cultivation mode, dictyophora rubrovolvata hyphae germinate quickly and grow vigorously, the conversion rate of mushroom buds (mushroom eggs) is high, the fruiting amount is large, meanwhile, the content of nutritional ingredients is increased, limited indexes such as heavy metal are obviously reduced, and the quality of dictyophora rubrovolvata products is effectively improved. According to the method, a new mode of soilless culture of edible mushrooms is constructed.

The invention discloses an ecological restoration effect evaluation method and system based on satellite remote sensing, and the method comprises the steps: collecting the satellite remote sensing data and field soil data of a preset region, and taking the remote sensing data of the preset region within a specified time as to-be-analyzed data; calculating a time sequence deviation and a contrast ratio based on the satellite remote sensing data to obtain a grading region; performing deviation correction on the satellite remote sensing data according to the field soil data in the grading region, and inputting the corrected satellite remote sensing data into a space-time ecological development prediction model to obtain ecological development prediction data; performing restoration uncertainty analysis according to the ecological development prediction data and the field soil data to obtain an ecological restoration effect confidence coefficient, and performing elastic capability analysis according to the ecological restoration effect confidence coefficient and the satellite remote sensing data to obtain an ecological elastic index; and constructing a time-varying ecological restoration effect evaluation model according to the ecological elasticity index, and outputting an evaluation result based on the to-be-analyzed data.

According to the method disclosed by the invention, arbuscular mycorrhizal fungi and biochar are added while multiple-leaf goldenrain trees are planted in cadmium-polluted soil. Compared with a traditional remediation mode of independently utilizing plants or microorganisms or biochar, the microorganism-plant-biochar combined remediation has the advantages that the plants, the microorganisms and the biochar are co-cultured to form a symbiotic system, so that the cadmium content in the soil is remarkably reduced, the remediation capacity of the plants is enhanced, and meanwhile, the growth of the plants is remarkably improved. The strategy breaks through the limitation that in the prior art, only improvement of plant resistance is concerned, and the strategy more focuses on the double effects of improving the phytoremediation capacity and promoting the growth effect, so that the maximization of the phytoremediation effect is achieved.

Systems and methods support collection of validated telemetry by an Information Handling System (IHS). A policy decision point (PDP) of a zero-trust computing environment controls access to protected resources The PDP identifies a telemetry stream of the IHS to be validated and identifies a telemetry definition specifying telemetry being collected by the IHS. The PDP updates the telemetry definition to specify adjustments to telemetry streams of the IHS to be authenticated and transmits the updated telemetry definition to the IHS. The IHS identifies telemetry that is ready for transmission and, based on the updated telemetry definition received from the policy decision point, generates a digital signature that authenticates the telemetry that is ready for transmission. The authenticated telemetry is transmitted to one or more destinations specified in the updated telemetry definition.

The invention discloses a hyperspectral technology-based inversion method for SPAD values and nitrogen concentrations of leaves in the whole growth period of rice. The hyperspectral data of the leaves of the rice are obtained by means of an ASD Field Spec4 portable ground object spectrometer in the initial differentiation period (PI), the heading period (HD), the middle filling period (MF) and the mature period (MA) of young ears; measuring the SPAD value of the rice as the chlorophyll content by using an SPAD-502 chlorophyll meter; determining the nitrogen concentration of the rice leaves by adopting a Kjeldahl method; performing correlation analysis on the hyperspectral data of the leaves, the nitrogen concentration and SPAD, and screening sensitive wavebands. According to the method, the hyperspectral characteristic wave band of the rice leaf is extracted through a correlation analysis method, so that the redundancy of full-spectrum data modeling is reduced, data are optimized, an inversion model of the nitrogen concentration and SPAD value of the rice leaf is constructed based on linear regression (LR), random forest (RF), support vector regression (SVR) and gradient boosting (GBRT), and the nitrogen concentration and SPAD value of the rice leaf are obtained. The optimal machine learning algorithm with high precision and good stability is obtained, and a scientific basis can be provided for non-destructive real-time leaf color monitoring and precise fertilization control of indica rice in the South China.

An underwater organism imaging aid system according to an aspect of the present disclosure includes, at least one memory configured to store instructions, and at least one processor configured to execute the instructions to: detect an underwater organism from an image acquired by a camera, determine a positional relationship between the underwater organism detected and the camera, and output auxiliary information for moving the camera in such a way that a side face of the underwater organism and an imaging face of the camera face each other based on the positional relationship.

The invention discloses a pine wood nematode disease tree grading detection method based on unmanned aerial vehicle remote sensing and an improved PWD-YOLOv10n algorithm, and relates to the technical field of forestry harmful diseased tree detection, and the method comprises the steps: (1) diseased tree remote sensing image collection; (2) constructing a data set; (3) network model improvement; (4) selecting evaluation indexes; (5) result evaluation: in the step (3), by designing a PWD-YOLOv10 model with high precision and low leak detection, introducing a CAA attention mechanism module into a backbone network of the YOLOv10n model so as to enhance the feature extraction capability; c2fEMSCP modules are introduced into a backbone part and a neck part respectively, the recognition precision of the model is further improved, the omission ratio is effectively reduced, and rapid and accurate grading detection on the pine wood nematode disease tree in a complex environment is realized by training the high-performance PWD-YOLOv10n model.