40 results about "Nature reserve" patented technology

The invention provides a multi-modal ecological environment monitoring element plug-in integration system and method based on unified objectification modeling. Firstly, an object model and an inheritance system of monitoring equipment, data and an algorithm are constructed; on the basis, a unified logic storage and metadata cataloguing mechanism oriented to heterogeneous databases such as relational databases, non-relational databases and file object databases is designed and realized; the plug-and-play and full-life-cycle management of equipment, data and algorithm models is further realized through a dynamic registration module; common APIs (Application Program Interface) such as object-level addition, deletion, modification and query, space-time association query, concurrent task scheduling and aggregation and the like are externally provided by relying on a unified service bus. And the hybrid storage engine cooperatively manages structured and unstructured data and maintains a topological relation between objects. According to the scheme, object dynamic integration and expansion are completed on the premise that operation is not interrupted, the multi-source heterogeneous data management and cross-modal analysis efficiency is remarkably improved, and the method is suitable for various ecological environment monitoring scenes such as natural reserve, drainage basin pollution supervision and disaster emergency response.

The invention relates to the field of specific calculation models, and discloses a natural regulation type salinized soil desalination simulation and multi-objective optimization configuration method, which comprises the following steps of: 1, data acquisition and earlier stage processing; 2, constructing a water and salt migration model; step 3, simulation analysis and scheme optimization; 4, carrying out substitution model training and multi-objective optimization; the final scheme is directly used for guiding engineering implementation, and specifically comprises the steps of determining the terrain adjustment amplitude, the position and depth of a drainage ditch, the micro-topographic relief scale, the earth filling and digging volume and shallow guide and drainage path configuration. The method has the beneficial effects that the natural drainage capacity of regional underground water can be remarkably improved, the effect that evaporation drives salt to move upwards is weakened, the rainfall infiltration capacity is improved, and the natural leaching effect is enhanced. The method is suitable for areas such as mud flats, salt pans and natural reserves where artificial engineering measures are not suitable to be taken, and has the advantages of low cost, high stability, ecological friendliness and the like.

The invention relates to the field of ecological monitoring, in particular to a space-air-ground integrated monitoring and early warning method and system for a natural reserve and a medium, and the method comprises the steps: collecting multi-source heterogeneous monitoring data of the natural reserve through a satellite remote sensing device, an unmanned aerial vehicle aerial photographing device and a plurality of ground sensors which are integrally deployed; performing structured enhancement on the multi-source heterogeneous monitoring data to construct a unified ecological database; inputting the structured enhanced data into a trained deep learning model based on a convolutional neural network architecture for reasoning so as to identify a monitoring target or an abnormal event of a preset category; and according to a deep learning model output result, generating early warning information and pushing the early warning information to a management terminal. According to the invention, through systematic integration of a deep learning technology, scattered data of the natural reserve is converted into linkage information, artificial low-efficiency processing is upgraded to intelligent active decision making, and the application value of air-space-ground integrated data in protection area management can be fully released.

This invention provides a method and system for assessing the impact of construction disturbance on biodiversity in nature reserves, relating to the field of computer technology. The method includes: acquiring species distribution data, construction disturbance data, and environmental data within the nature reserve; constructing an ecological association network based on the species distribution data to obtain a species interaction network; extracting network structure features from the species interaction network to obtain a set of key species; modeling the disturbance propagation dynamics based on the set of key species and the construction disturbance data to obtain an impact propagation path map; predicting biodiversity responses based on the impact propagation path map and environmental data to obtain trends in changes in biological community composition; and conducting a comprehensive impact assessment based on these trends, outputting an impact level index by comparing the degree of deviation from historical baseline states. This invention effectively improves the overall accuracy and predictive precision of the assessment of the impact of construction disturbance on biodiversity in nature reserves.

The application discloses an ecological environment monitoring device based on big data, which comprises a base, a connecting frame arranged above the base, windward fan blades rotatably connected to the connecting frame, a fourth bevel gear fixedly connected to the windward fan blades, a third bevel gear meshedly connected to the fourth bevel gear, a rotating rod fixedly connected to the bottom of the third bevel gear, the rotating rod being rotatably connected to the connecting frame, and a rotating rod being drivingly connected to the rotating rod. In the application, the technical problem that mosquitoes and insects in a nature reserve lie on the surface of a monitoring device and a multi-angle camera in summer, produce excrement or lay eggs, and corrode the device shell and the lens is effectively solved. The surface of the camera is wiped by a friction plate, the cleaning effect of a cleaning agent spraying ring is utilized, and the airflow generated by the swinging of a sail plate blocks the lying of mosquitoes and insects, so that the lens is prevented from being dirty and the shell is prevented from being corroded, the normal shooting function of the multi-angle camera is ensured, the overall service life of the device is prolonged, and the stable development of the monitoring work of endangered animals is ensured.

The invention discloses a Metarhizium rileyi XBM-z strain and an application of the Metarhizium rileyi XBM-z strain in prevention and treatment of mangrove forest pests. The preservation number of the metarhizium reevesii XBM-z is GDMCC NO: 65954, and the metarhizium reevesii XBM-z is obtained by being separated from metarhizium giganteum female neoplasm moth collected in a mangrove forest natural reserve area in Guangdong province, and has very strong pathogenicity to mangrove forest explosive lepidoptera pests such as the metarhizium giganteum female neoplasm moth and teak camel moth; and the Metarhizium reevesii XBM-z has strong halophilicity, can promote mycelial growth and increase sporulation quantity under the condition that the salt concentration is less than 3%, is suitable for application in a mangrove forest high-salinity environment, is a biocontrol bacterium with good application potential in mangrove forest pest control, and has important significance in mangrove forest pest control.

The application discloses a nature reserve resource three-dimensional right confirmation method, system and equipment, and relates to the technical field of natural resource right confirmation.The application firstly acquires the coordinate point set of each ancient tree in the protection area, then carries out density checking in the protection area, so that the gathering degree and distribution law of the ancient trees in the protection area in space are determined.Meanwhile, the ancient tree environment influence weighted graph is constructed, so that the influence of factors such as the terrain fluctuation between the ancient trees, the ecological connection strength between the trees and the main barriers and the like is comprehensively considered, and the boundary of the right confirmation community candidate area is further optimized.Then, the right confirmation community area of the nature reserve resource is determined, and the ancient tree resource right confirmation graph of the protection area is made, which provides strong support for the effective protection and management of the nature reserve resource, that is, the difficulty in right confirmation of the natural ancient tree famous tree resource and the low precision in the prior art are effectively solved.

The application discloses an intelligent nature reserve electronic boundary post applied to the field of electronic boundary posts, which is composed of a square tube, a stabilizing assembly, a ground-buried assembly and a boundary post assembly, adopts a semicircle ball and a spherical groove to form a self-adaptive leveling structure, cooperates with a bottom counterweight block to form a gravity self-stabilizing system, can automatically correct when the ground subsides slightly or tilts, long-term maintains a vertical posture, guarantees that data collected by devices such as a camera and a weather sensor is accurate and reliable, and realizes quick locking and installation of the ground-buried assembly by means of a large-stress-area ground-buried plate, a fixing rod, a clamping plate and a bolt, does not need to pour a large amount of concrete, significantly reduces construction difficulty and cost, has strong anti-pulling and anti-inclination performance, is suitable for complex soil environments in the wild, realizes data collection, intelligent processing and remote transmission through an electric control board, can be operated unattended all day long, and realizes real-time boundary monitoring, intrusion early warning and remote control.

The invention discloses a data-driven biodiversity monitoring management method based on multi-source fusion, and particularly relates to the technical field of ecological environment monitoring. Multi-source heterogeneous ecological data of remote sensing images, species records, environmental sensors, community science and the like are obtained and subjected to standardization processing to generate a unified data matrix; based on a space grid model and a sliding time window mechanism, space-time sequence features of all grid points are extracted; generating an embedded vector by using a pre-trained multi-modal ecological representation learning model, and predicting a species diversity index of each region in combination with a species inhabiting adaptability model; a spatio-temporal evolution graph is further constructed, an abnormal change area is identified, and unmanned aerial vehicle cruising and high-frequency monitoring tasks are dynamically scheduled; according to the method, the intelligence, the real-time performance and the precision of ecological monitoring can be improved, and the method is suitable for various application scenes such as natural reserves and biodiversity hot spots.

The present application relates to the technical field of ecological monitoring, in particular to a mobile ecological damage intelligent monitoring device for nature reserves, comprising a vehicle body and a collection box, a collection pipe and a collection cover are sequentially installed on the top of the collection box in communication, the collection cover is used for capturing sand and soil particles in wind sand and conveying them to the collection mechanism in the collection box through the collection pipe, sand and soil particles are captured by the collection cover, then conveyed to the inside of the collection box through the collection pipe, and stored through the sample storage tube in the collection mechanism, as the number of sand and soil particles collected in the sample storage tube increases, the sample storage tube will rotate as a whole under the action of gravity in cooperation with the driving mechanism, further storing the collected sand and soil particles in different sample storage tubes, realizing the collection and independent storage of sand and soil particles at different time periods in the wind erosion process.

The present application relates to the technical field of ecological environment protection, and particularly relates to a coastal wetland nature reserve integration optimization method fusing ecological system integrity, authenticity and high-quality development layout, comprising the following steps: S1: acquiring and generating an ecological system integrity and authenticity spatial difference distribution map; S2: acquiring and generating a human activity intensity distribution map; S3: performing spatial superposition analysis to identify a protection and development conflict region; S4: performing spatial comparison to identify an ecological protection vacancy region; S5: calculating an integration optimization coefficient of each region respectively; and S6: dividing into different priority integration optimization types. The present application, by fusing the spatial adjacency relationship of ecological system integrity, authenticity and high-quality development layout, constructs differentiated integration optimization, realizes accurate identification and priority division of key regions in the coastal wetland ecological system, and improves the scientificity and operability of the nature reserve system optimization.

This application discloses an integrated monitoring boundary marker system based on multimodal sensing and redundant transmission, relating to the field of nature reserve monitoring technology. The system includes multiple boundary markers, each containing sensing and imaging equipment, a dual-power management unit, a sound source identification unit, a multi-source data fusion processing unit, and a multi-mode communication unit electrically connected to the system. This system can effectively monitor and accurately transmit monitoring data for protected areas with an average area of ​​82,000 to 83,000 hectares when only 58 to 59 boundary markers are used. It offers high monitoring reliability and reduces data mistransmission.

The invention relates to the field of three-dimensional modeling, in particular to a natural reserve ecological data dynamic fusion method based on a three-dimensional geographic information system. The method comprises the following steps: obtaining an original observation value of an ecological factor, and carrying out standardization processing to obtain a standardized value of the ecological factor; calculating a deviation degree based on the standardized value of the ecological factor; based on the standardized values and the deviation degrees of the ecological factors, an ecological data dynamic fusion algorithm is adopted, and ecological response indexes are obtained through calculation; and based on the ecological response indexes, generating a final color vector through an ecological response color mapping algorithm. The problems that according to a traditional ecological data dynamic fusion method, all monitoring points are regarded as independent individuals, and the propagation characteristics of short-distance high influence and long-distance gradual attenuation are difficult to quantify are solved; the problems that in a three-dimensional scene, abstract ecological stress intensity is difficult to convert into visual and gradually-changing color information, parameterized regulation and control on human eye sensitivity are lacked, and a high-risk area is easy to cover or misjudge are solved.

The application discloses a natural reserve infrared camera monitoring and analyzing system in the technical field of natural reserve research, which comprises a collecting module and an analyzing module. The collecting module comprises a ring-shaped mounting piece fixed on a tree, a mounting frame slidingly mounted on the ring-shaped mounting piece, an infrared camera mounted on the mounting frame, and a driving piece for driving the mounting frame to move on the ring-shaped mounting piece. An inner side wall of the ring-shaped mounting piece is provided with a positioning air bag, and an inner side wall of the positioning air bag is provided with a plurality of groups of vertical positioning strips. The analyzing module comprises a processing device mounted on the mounting frame. In the application, the infrared camera is mounted on the mounting frame, and the mounting frame is slidingly mounted on the ring-shaped mounting piece. The infrared camera can move and monitor the surroundings by the driving piece driving the mounting frame to move on the ring-shaped mounting piece. Therefore, a plurality of infrared cameras do not need to be installed, and the cost is reduced.

The invention relates to a bird voiceprint and vision fusion real-time identification method for an oil exploitation operation area, and belongs to the technical field of oil exploitation operation, and the method comprises the steps: collecting a field twitter signal of a current monitoring area of a set natural reserve in a current time segment, and converting the field twitter signal into a voiceprint time frequency graph; acquiring targeted visual data of each frame of on-site monitoring picture in the current time segment in the current monitoring area; a lightweight neural network corresponding to a set natural reserve is adopted to intelligently identify various different bird data of the current monitoring area in the current time segment; in order to solve the technical problem that bird identification lacks scene adaptability, time integrity and data comprehensiveness, a lightweight neural network with a customized structural design is adopted for a set natural reserve in which an oil exploitation operation area is distributed, and intelligent identification of various different bird data is completed at the same time, so that the technical problem is solved.

The present application relates to the technical field of data processing, and particularly relates to a natural reserve unmanned aerial vehicle inspection optimization method, which solves the technical problem of unreasonable inspection route planning of an unmanned aerial vehicle in inspecting a natural reserve in the prior art. The method comprises the following steps: dividing the natural reserve into a plurality of grids, calculating the static obstacle density of the non-obstacle grids in the plurality of grids based on the point cloud data of the static obstacles of the natural reserve, and calculating the dynamic obstacle density of the non-obstacle grids based on the image data of the dynamic obstacles of the natural reserve; determining the comprehensive obstacle factor of each non-obstacle grid based on the static obstacle density and the dynamic obstacle density; selecting the initial point of the grey wolf algorithm based on the static obstacle density, and performing iterative calculation of the grey wolf algorithm with the minimum weighted value of the inspection path length and the comprehensive obstacle factor of the inspection path as the optimization target to determine the inspection path.

The present application relates to the oil exploitation operation area-oriented bird voiceprint and visual fusion real-time identification method, belongs to the oil exploitation operation technical field, the method includes: collecting the current monitoring area of the set nature reserve in the current time segment in the field bird song signal, and converting into voiceprint time-frequency graph; acquire the pertinence visual data of each frame of field monitoring picture of the current monitoring area in the current time segment; using the corresponding lightweight neural network intelligent identification of the set nature reserve in the current time segment in the current monitoring area of various different bird data; the present application aims at the technical problem that bird identification lacks scene adaptability, time integrity and data comprehensiveness, for the set nature reserve distributed with oil exploitation operation area, using the lightweight neural network of custom structure design, at the same time, the intelligent identification of various different bird data is completed, so that the above technical problems are solved.

The invention discloses an ecological protection red line zoning method based on an ecological important area, and belongs to the technical field of ecological protection red line zoning, and the method comprises the steps: firstly analyzing an ecological service function space-time pattern of a target area through an InVEST physical model, and recognizing a first ecological important area; constructing a positive sample through spatial superposition of the natural reserve and the ecological factors, determining a negative sample in combination with an outlier detection model, and training a machine learning model to recognize a second ecological important region; performing space-time quantization on the two types of ecological important areas, determining a time sequence trend and a spatial pattern, and performing fusion clustering to form an ecological important pattern partition and an ecological change trend partition; and superposing the two types of partitions to obtain an identification result, dividing types and grades, and forming an ecological protection red line zoning scheme. According to the method, a zoning method system fusing a physical model and a machine learning model is established, a multistage red line zoning method coupling ecological importance spatial distribution and a time sequence trend is formed, and a targeted protection strategy is provided.

The invention relates to a natural reserve resource multi-target optimization method and device, a storage medium and equipment, and the method comprises the steps: obtaining multi-source remote sensing data of a target natural reserve, and achieving the prediction of aboveground biomass data and plant crude protein data of the target natural reserve through a pre-trained prediction model; on the basis of a second-generation non-dominated sorting genetic algorithm, the optimal planning information of the target protection area is obtained according to the biological data, the aboveground biomass data, the plant crude protein data, the decision-making target and the constraint conditions of the target protection area; data support is provided for planning of a livestock group structure, the number of wild animals and artificial grassland planting information of a target protection area, the balance problem of multiple targets of human settlement-grassland-wild animal-livestock balance of the natural protection area is solved, and sustainable development of the natural protection area is promoted.

The invention relates to a global natural reserve biodiversity protection effect evaluation method and device, and the method comprises the steps: obtaining multi-source remote sensing and statistical data, constructing a multi-dimensional ecological index system covering forest changes, vegetation vitality, human interference and a landscape structure, carrying out the standardization processing and weight setting, and carrying out the evaluation of the biodiversity protection effect of the global natural reserve. Generating a plurality of standardized index data elements; constructing an equal-area buffer area as a contrast area on the basis of the boundary of each protected area, performing internal and external pairing analysis, and identifying a net ecological effect brought by a protection behavior through methods such as an index difference value, a ratio, a time trend and spatial autocorrelation; and performing weighted synthesis on the normalized and weighted indexes, constructing a comprehensive scoring model, dividing effect levels according to scores, and visually outputting effect distribution results through a GIS (Geographic Information System). Therefore, the problem that the biodiversity protection effect of the global natural reserve cannot be systematically and quantitatively evaluated in a multi-dimensional and multi-level mode in the prior art is solved.

The utility model discloses a protective device for endangered trees in a natural reserve, which belongs to the technical field of tree protection and comprises a pair of protective half shells, fixing blocks are fixedly connected to the outer ends of the sides, close to each other, of the protective half shells, and threaded holes are formed between the fixing blocks. A preset groove is formed in the protection half shell, and a nutrient solution bag and a control liquid bag are fixedly connected to the inner wall of the preset groove; the purposes of extruding a stress plate and pushing an extrusion plate to extrude a nutrient solution bag and a prevention and control liquid bag to supply nutrients to trees and prevent diseases and pests can be achieved through body shape changes of the trees in different growth stages. Meanwhile, under the action of a liquid discharging head and a liquid spraying head, a nutrient solution in a nutrient solution bag and a control solution in a control solution bag can be sprayed to the roots and branches of the trees respectively, and therefore protection and treatment on the endangered trees are effectively improved.

The invention discloses a red-top crane behavior pattern recognition method and system based on an artificial intelligence visual technology, and relates to the technical field of intelligent recognition, and the method comprises the following steps: S1, collecting original video data containing the activity of a red-top crane through a high-resolution camera device arranged in a natural reserve; and S2, preprocessing and labeling the original video data: performing frame splitting according to a fixed time interval, eliminating redundant frames by using a perceptual hash algorithm, and performing bounding box labeling and behavior label labeling on red-crowned crane individuals in key frames. According to the automatic identification method for the behavior pattern of the red-top crane, by integrating advanced artificial intelligence and computer vision technologies, the efficiency and accuracy of behavior monitoring of the red-top crane are remarkably improved, the defects that traditional manual observation is greatly limited by the environment and low in efficiency are overcome, all-weather and all-around automatic monitoring is achieved, and the method is suitable for popularization and application. And the fineness and adaptability of behavior recognition are improved.

This invention discloses a dynamic intelligent patrol device and system for nature reserves in the field of ecological protection technology. The device includes a ground monitoring component, a ground patrol component, and a low-altitude patrol component. The invention utilizes the pole of the ground monitoring component as a docking platform, allowing drones to land on the pole unaffected by the forest canopy. This enables the ground patrol component to reach the bottom of the pole after completing its patrol mission, where it is lifted and retrieved by the hoisting unit. A guide component is used as a channel, allowing the hoisting unit to descend along it and dock with the vehicle body. Furthermore, during hoisting, because the docking mechanism is located above the front of the vehicle body, the guide rope no longer runs vertically downwards along the guide component but instead tilts away from the opening slot, facilitating the lifting of the vehicle body along the pole.

This invention discloses a smart forestry IoT patrol method and system for nature reserves. It acquires abnormal coordinates of patrol personnel when GPS signals are lost, determines the preceding and following positions of these abnormal coordinates, and then precisely corrects the abnormal positions based on the determined preceding and following positions and the patrol personnel's movement speed. The smart forestry IoT patrol method and system for nature reserves provided by this invention effectively solves the problem of GPS location deviation for forest rangers during patrols, ultimately establishing accurate trajectory positions and effectively and accurately protecting the work results of forest rangers. It also helps managers to conduct more precise supervision of forest rangers.

This invention relates to the field of ecological risk assessment technology, and in particular to a method and system for assessing human-wildlife conflict risk in nature reserves. It constructs a list of conflicting species and a standardized distribution dataset by integrating multi-source data. Based on a maximum entropy model, a stacked species distribution model is built to calculate species hazard levels. For three types of conflict—crop damage, livestock predation, and personal injury—arable land, grassland, and population density are matched as exposure indicators, respectively. Based on a "hazard level × exposure level" framework, categorized risk sub-models are constructed, and a comprehensive risk raster map is generated by overlaying these sub-models. Finally, the overall risk assessment value is calculated using nature reserves as units. This invention addresses the problems of existing human-wildlife conflict risk assessment technologies, which fail to effectively integrate multi-species contributions, differentiate conflict types, and adapt to large-scale protected area systems.

The present application relates to the field of aquatic organism identification in nature reserves, and discloses a method for identifying aquatic organisms based on multi-source data of nature reserves, comprising: S1: obtaining multi-source data and preprocessing to obtain preprocessed multi-source data; S2: extracting features based on the preprocessed multi-source data to obtain the shape features, sonar features and voiceprint features of aquatic organisms; S3: constructing an aquatic organism identification target model; and S4: identifying aquatic organisms based on the aquatic organism identification target model, inputting the shape features, sonar features and voiceprint features of aquatic organisms into the aquatic organism identification target model, and outputting the aquatic organism identification result. The present application realizes accurate identification of aquatic organisms through processing and deep fusion of multi-source data, improves the precision and accuracy of aquatic organism identification, and can balance wide-range detection and microscopic identification, adapt to various water body scenes, and provide comprehensive support for aquatic organism protection.

The invention relates to the technical field of non-electrical variable control or regulation systems, and particularly discloses a natural reserve sightseeing vehicle control method and system. The scheme comprises a multi-source mobile monitoring platform collaborative perception module, a global ecological parameter dynamic reconstruction module, a pollution event traceability and diffusion path deduction module and a sightseeing vehicle adaptive scheduling control module. According to the invention, high-resolution seamless perception of the ecological environment of the natural reserve and rapid and accurate traceability and response of pollution events are realized, and the utilization efficiency of patrol resources and the intelligent level of ecological supervision are improved.

The application discloses a kind of for nature reserve green environmental protection road composite material and preparation method and application, and nature reserve green environmental protection road composite material includes mixed soil, sodium lignosulfonate, quicklime, mixed latex and water.Nature reserve green environmental protection road composite material in the application of building road includes the following steps: roadbed shoulder preparation, preparation nature reserve green environmental protection road composite material, mechanical paving, rolling forming, light receiving and compaction maintenance.The application utilizes difficult to recycle waste material to utilize again, reduces the demand of natural resources, and has less influence on environment, while the strength of nature reserve green environmental protection road composite material is higher, meets the requirement of environmental road construction in nature reserve and the like, conforms to the development trend of current green building, and has wide application prospect.

The application discloses a kind of wild animal habitat suitability evaluation method based on geographical weighted random forest classification model, belong to ecological information science, geographic information science, wild animal protection and machine learning technical field.The present application is aimed at the defects that existing global model cannot capture the spatial non-stationarity of environment-species relationship and traditional geographical weighted model is difficult to deal with nonlinear classification problem, constructs a spatial self-adaptive local random forest classification model system, completes the whole process of data library construction, spatial weight definition, optimal bandwidth optimization, global suitability prediction, result grading and driving factor analysis.The application significantly improves the habitat assessment accuracy in large-scale, high-heterogeneous habitat areas, can simultaneously analyze the dominant driving factors of species distribution in different regions, provides accurate scientific basis for wild animal habitat protection and nature reserve planning, and adapts to the evaluation needs of multiple types of wild animals.