79 results about "Biodiversity" patented technology

The invention provides an intelligent analysis and early warning system for biodiversity big data, and relates to the technical field of biodiversity monitoring. The system comprises a multi-source data acquisition module, a heterogeneous data fusion preprocessing module, a biodiversity feature intelligent extraction module, a dynamic evolution analysis module, a risk early warning module, a visual output module and a model adaptive optimization module. An edge-cloud collaborative architecture and a multi-source data acquisition module are adopted to synchronously acquire biological sample, environment, human activity and historical literature data, after fusion preprocessing of an improved depth auto-encoder, a twin neural network is adopted to extract multi-dimensional features of species, an evolution trend is predicted through an improved Bayesian network and LSTM fusion model, and a multi-dimensional feature of the species is obtained. And outputting multi-level early warning in combination with a dynamic early warning threshold library, and finally performing multi-terminal visual display. According to the method, the problems of single traditional monitoring data, low fusion precision, short prediction period, early warning rigidity and the like are solved, and the accuracy and real-time performance of biodiversity analysis and early warning are improved.

The invention discloses an aquatic organism diversity analysis method based on hydropower station construction influence, and is applied to the technical field of biological diversity analysis. Comprising the following steps: dividing a target water body into a plurality of monitoring areas according to a hydropower station construction scheme; hydrological data and biodiversity data are collected in different periods; performing space-time analysis on the hydrological data and the biodiversity data of different monitoring areas, identifying change conditions and calculating quantitative indexes; matching the hydrological data with the biodiversity data, and analyzing the influence capability of different parameters in the hydrological data on the biodiversity data; and evaluating the influence degree of the hydropower station construction on the aquatic organism diversity. Multi-source parameters before hydropower station construction, in the construction process and in the operation process are monitored, the influence of hydropower station construction on aquatic organism diversity of a target water body is analyzed through hydrological data, and data reference is provided for protecting species diversity.

This invention provides a Bayesian-based method and apparatus for spatial trade-off and synergistic optimization of ecosystem services, relating to the fields of ecology and statistics. The invention acquires an ecological spatial database of a target area, uses ArcGIS software's netting and clipping tools to generate a grid layer of a specified size for the target area, obtaining a pixel set. Based on the ecological spatial database and pixel set, the blue carbon storage, biodiversity maintenance capacity, and coastal protection capacity of the target area are calculated, representing three ecosystem services. Furthermore, the coupling coordination degree is obtained to analyze the overall coordination level among ecosystem services. A Bayesian-based ecosystem service synergy prediction model is constructed using Netica software to identify key driving factors and output the probability distribution of corresponding nodes, simulating and analyzing potential synergistic impacts under different scenarios. This invention can accurately identify and clarify the trade-off and synergistic relationships of key ecosystem services such as coastal wetlands, achieving synergistic spatial optimization of ecosystem services.

The invention provides an invasive plant detection method based on fusion of a satellite remote sensing image and a ground observation sample, and relates to the technical field of ecological monitoring. According to the method, a technical route of'satellite remote sensing image-multi-screening feature-model training and detection 'is constructed under an extremely simple data framework of free multispectral satellite image + open biodiversity platform, and invasive plant mapping is completed with extremely low cost. According to the method, the data recorded in the open biodiversity platform is fully utilized, the labor cost required for acquiring the ground data is greatly reduced, and the data is provided with the longitude and latitude and the species label, so that the expensive data purchasing and manual drawing process is effectively avoided, and the low-cost, high-efficiency and replicable detection process is realized. According to the method, only the preset number of core features are selected for model training, the input dimension is controlled, and a model classification task is more stable when facing a small sample task.

The invention discloses a multi-class-group ecological safety operation space determination method and system for a large estuary delta and a storage medium. Relates to the technical field of ecological environment protection and wetland resource management. The method comprises the following steps: acquiring multi-source spatio-temporal data of a target estuary delta, preprocessing, constructing a multi-period inning boundary database, analyzing a distance effect, calculating an inning strength index, determining an optimal hysteresis period through hysteresis analysis, constructing three types of accumulation indexes, fitting a response relation curve of the three types of accumulation indexes and biodiversity, and determining the biodiversity of the target estuary delta. Identifying non-linear inflection points on the curve to determine a threshold position; and constructing a biodiversity response surface according to the analysis result, and further identifying the ecological operation space. According to the method, data of multi-stage remote sensing, multi-class biodiversity monitoring and the like and a multi-model joint calculation framework are combined, the lag response, the cumulative effect and the threshold features of the multi-class biocenosis are quantitatively recognized, an ecological safety operation space recognition system is formed, and support can be provided for ecological planning, management and decision making.

A panel for a seawall has a frame. The frame has a first area and forms front surface which is substantially planar. A typographical member disposed on the frame has a second area, less than the first area. The typographical portion extends in a direction away from the frame and forms an uneven surface, the surface having at least one depression therein having a depth of at least three inches.

The present application belongs to the technical field of river vegetation restoration in water conservancy projects, and particularly relates to a river submerged plant restoration method based on flow velocity zoning, comprising the following steps: determining a fish adaptability threshold to flow velocity in a target river, including a lower limit of unsuitable flow velocity Vu and an upper limit of suitable flow velocity Vs; constructing a rapid flow zone, a transition zone and a slow flow zone in the river according to Vu and Vs, so that the flow velocity of the rapid flow zone is greater than or equal to Vu, the flow velocity of the slow flow zone is less than or equal to Vs, and the flow velocity ratio of the rapid flow zone to the slow flow zone is greater than or equal to 1.5 times; removing fish with a body length greater than or equal to 10 cm in the river so that the density is less than or equal to 0.3 tail / m 2 ; and planting submerged plants that can adapt to a flow velocity greater than or equal to Vs in the rapid flow zone and / or the transition zone. The present application has the advantages that the present application utilizes the adaptability difference of submerged plants and fish to different flow velocities, and creates a rapid flow zone-transition zone-slow flow zone, which not only creates conditions for submerged plant restoration, but also increases habitat diversity, which is conducive to the restoration of ecological and biological diversity of the entire river.

The invention relates to the technical field of coast ecological restoration, in particular to a muddy coast embankment-penetrating biological channel and a construction method. The invention aims to provide the muddy coast embankment-penetrating biological channel and the construction method, the biological channel and the construction method have the function of protecting biological diversity, and the effective ecological protection effect is achieved by fully combining the coast ecology principle and aiming at the geological and ecological characteristics of the muddy coast. According to the technical scheme, the muddy coast embankment penetrating biological channel comprises a seawall, a coastal tidal beach located on the coastal side of the seawall, an embankment rear ecological zone located on the back-to-sea side of the seawall and an embankment body biological channel transversely penetrating through the lower portion of the seawall to communicate the coastal tidal beach with the embankment rear ecological zone. A construction method of a muddy coast embankment penetrating biological channel comprises the steps of coastal tidal beach construction, embankment body biological channel construction and embankment back ecological zone construction.

The present application belongs to the technical field of computer data processing, and provides a biodiversity inversion method based on multi-source remote sensing image fusion, comprising: remote sensing image data acquisition, image preprocessing, image fusion processing, multispectral resolution image data generation, spectral feature extraction, final frequency feature extraction, feature integration and target ecological variable prediction; the present application realizes differentiated fusion of high and low frequency components under different scales through wave base adaptive selection and multi-scale wavelet decomposition, taking into account spectral fidelity and spatial structure preservation, improves the complementarity of multi-source data and the quality of fused images; through spectral resolution refinement processing and multi-bandwidth scale simulation, the limitation of single resolution is broken through, and the ability to capture complex spectral features of vegetation is enhanced; through spatial neighborhood feature fusion, spatial correlation is enhanced; through the ecological variable inversion estimation model, multi-index synchronous prediction is realized, and the generality of the model is improved.

The invention relates to the technical field of ecological assessment, and discloses a coastal wetland ecosystem condition assessment method and device, a medium and a product, different smooth regression functions are obtained through double generalized additive model processing, and the influence of an environmental single factor on vegetation and the cooperative influence of the environment and the vegetation on benthic organisms are accurately quantified. Furthermore, the index value is determined by taking historical data as a reference and combining a nonlinear rule of a smooth function, so that subjective weighting deviation is avoided. Furthermore, the weight is calculated based on the association between the real-time index value and the biological index, so that human subjective intervention is avoided, and the weight is ensured to reflect the actual contribution of the index to the ecological system. Meanwhile, the influence of single data deviation is reduced by using the multi-tree integration characteristic of the random forest model, so that the weight result is more stable. Furthermore, the complex ecosystem condition of the coastal wetland can be comprehensively evaluated in combination with the index value and the weight, the biodiversity is protected, and the stability of the ecosystem is maintained.

The invention relates to a method for constructing a marine organism diversity distribution model, which is used for constructing a marine species distribution prediction model framework with ecological adaptability, prediction accuracy and management guidance by relying on technical paths such as multi-source data fusion, sample optimization generation, adaptive clustering recognition, multi-model fusion prediction, mechanism interpretable analysis and the like. And quantitative tool support is provided for marine ecological red line demarcation, flagship species protection area planning, ecological restoration priority area identification and the like.

The invention provides a bird habitat quality assessment method and device for a large lake watershed, and is applied to the technical field of bird habitat quality assessment, and the method comprises the steps: obtaining land utilization data and bird biodiversity data of a target region, the target region comprising a plurality of different climate regions; based on the bird biodiversity data and the land utilization data, differentially adjusting and optimizing the habitat suitability parameters and the threat factor sensitivity parameters of the large lake basin for different climate regions to obtain a plurality of large lake basin bird habitat quality optimization parameter sets corresponding to the different climate regions; rasterizing the land utilization data and the threat factor data to obtain rasterized data; and inputting the rasterized data and the optimization parameter set into a preset InVEST model to carry out habitat quality evaluation, and obtaining an optimized habitat quality evaluation result. According to the method, the applicability of the model in big lake basin bird habitat quality evaluation can be improved in combination with bird ecological characteristics.

The present application relates to the technical field of ecological restoration of intertidal oyster reef, and discloses an oyster reef component based on an intertidal photovoltaic pile foundation and a manufacturing method thereof, which comprises a sleeving mechanism, the bottom of the sleeving mechanism is provided with an adhering mechanism, and the bottom of the adhering mechanism is provided with a supporting and fixing mechanism; the sleeving mechanism comprises a half sleeve one and a half sleeve two, both ends of the half sleeve one are fixedly connected with plug blocks, both ends of the half sleeve two are provided with plug slots, the plug blocks and the plug slots are mutually inserted, both top ends of the half sleeve two are provided with mounting holes, the top of the two plug blocks is provided with plug holes, bolts are arranged between the mounting holes and the plug holes, and the inner side walls of the half sleeve one and the half sleeve two are provided with anti-skid pieces. The oyster reef component based on the intertidal photovoltaic pile foundation and the manufacturing method thereof can not only provide a suitable habitat for oysters, but also can repair the intertidal habitat of a photovoltaic field area, increase the types and density of benthic organisms, and restore the biodiversity of the photovoltaic field area.

The application discloses a kind of marine biological sound extraction enhancement methods, systems, equipment and medium, belong to intelligent information processing technical field.Method first constructs training dataset by mixed natural background noise, pure biological call and ship noise, uses pre-training model to combine diffusion probability model and carries out iterative optimization, learns the mapping relationship of noise addition and removal.In inference phase, through conditional guidance technology dynamic adjustment model output, accurately separate target biological sound and background noise, and combine verification set and actual collection data to evaluate enhancement effect.The application significantly improves the extraction accuracy and purity of marine biological call in noisy environment, solves the problem of poor adaptability and low efficiency of traditional method, and can be widely used in marine ecological monitoring, species behavior research and underwater acoustic communication engineering, providing efficient and reliable technical support for marine environmental protection and biodiversity research.

The present application relates to the technical field of biodiversity monitoring, and particularly relates to a water biodiversity monitoring system and method based on image recognition. The method comprises the following steps: acquiring an image of a continuous interface zone of a target water body along a solid substrate to a water space, extracting an attachment unit formed by different morphological aquatic organisms, and determining a distribution range of each attachment unit in the interface zone to form attachment unit occupation data; identifying a boundary contour between adjacent attachment units based on the attachment unit occupation data, and determining a mosaic connection relationship between the attachment units according to an extension continuous state and a local turning and gathering state of the boundary contour to form mosaic structure data; and partitioning and deducing the distribution range of the attachment units according to the mosaic structure data. The present application realizes high-precision, continuity and quantifiable monitoring of the ecological structure of the water body by analyzing the spatial structure and diversity evolution of the aquatic organism attachment unit.

The invention discloses a forage grass planting restoration method based on Yellow River basin biodiversity restoration, and the method comprises the following steps: S1, carrying out the region division of a basin, and obtaining the environment data of a to-be-restored region; s2, stress-resistant forage grass combination screening is carried out according to the geographical conditions of the functional areas; s3, planning an ecological planting scheme, and implementing planting restoration; s4, performing dynamic ecological regulation and control including water management, natural enemy management, pollination insect management and growth fertilizer management; and S5, monitoring and feeding back a repairing effect. Compared with the prior art, the forage grass planting restoration method based on Yellow River basin biodiversity restoration and the application of the forage grass planting restoration method have the advantages that variety screening is carried out by considering multi-environment difference, and sustainable ecological restoration is completed.

The present application belongs to the technical field of ecological system or natural environment protection by using big data analysis, further to the technical field of biodiversity monitoring and protection, and specifically relates to a biological species loss risk assessment method and a monitoring and early warning system.The intelligent monitoring and early warning system for monitoring the species loss risk of the present application comprises a data acquisition module, a data transmission module, an analysis module and a model saving module.The intelligent system or method of the present application can intelligently monitor the species loss risk through big data analysis and integration, and is more accurate, fast and convenient than artificial monitoring and evaluation.According to the monitoring result, the person skilled in the art can effectively formulate corresponding protection strategies, and further effectively protect the biodiversity and the natural environment.

The invention discloses a benthic organism sample identification and analysis method and system based on data mining. The method comprises the following steps: firstly, acquiring standard image data of benthic organisms in different growth stages, extracting appearance features and constructing a feature database; establishing an identification model based on the database, collecting target sample and community three-dimensional structure image data by using an underwater robot, and carrying out initial identification; and if the result is not unique, mining an inter-species relationship, constructing a community relationship network in combination with a graph theory algorithm, calculating the credibility of the identification result, and performing secondary identification to obtain a final result. The method improves the identification accuracy and reliability, and is suitable for marine ecological monitoring and biodiversity research.

This invention relates to the field of ecological environment monitoring technology, specifically an intelligent ecological monitoring method. This method constructs a monitoring and early warning system through multi-dimensional perception, intelligent correlation, time-series prediction, and hierarchical early warning. Specifically, it first collects data from ten dimensions, including atmosphere, water quality, soil, biodiversity, and ecological patterns, which can overcome the limitations of traditional monitoring that is often limited to a single or a few types of indicators. Then, it uses a deep learning-based multi-source data fusion algorithm to mine the implicit correlations between different ecological elements. Next, it uses an improved LSTM model for time-series analysis, which can proactively identify abnormal trends. An attention mechanism is introduced to enable the model to focus more on the key time periods and key indicator combinations that lead to anomalies, improving the accuracy of trend analysis. Finally, the early warning level is determined based on the degree of deviation from a preset threshold, realizing the quantification and hierarchical classification of early warning information. This helps to optimize resource allocation and enhances the initiative, scientific nature, and management efficiency of ecological environment protection.

The invention belongs to the technical field of estuary environment biodiversity monitoring, and particularly relates to a method for monitoring estuary environment biodiversity based on eDNA. According to the method, three core strategies of gradient partition point distribution, sediment-dominated collaborative sampling and multi-method parallel verification are creatively integrated, and a set of special eDNA monitoring method for the complex estuary environment is formed. The implementation result proves that the method can systematically, sensitively and non-invasively reveal the spatial pattern of the estuary biocenosis, and effectively solves the key technical problems that the traditional method is large in interference and low in efficiency, and the general eDNA technology is insufficient in pertinence to benthic organisms and poor in representativeness.

The present application relates to the technical field of marine ecological restoration evaluation, and specifically discloses a method for evaluating the ecological effect of island carbon sequestration, comprising: collecting sediment and biological time series data in the target island carbon sequestration area, applying wavelet transform and random forest fusion to multi-scale decomposition of the sediment organic carbon time series signal, identifying hydrodynamic noise and biological carbon sequestration characteristic spectrum, screening disturbance-resistant carbon components and constructing a carbon stability index; based on the carbon stability index, combining partial least squares path modeling and XGBoost, constructing a biological-sediment causal chain, analyzing the differential regulation path of seagrass roots and seaweed attachment devices on benthic biodiversity and sulfide dynamics, and outputting the biological path coefficient; the present application effectively distinguishes hydrodynamic noise and biological carbon sequestration characteristic spectrum by wavelet transform and random forest fusion for multi-scale decomposition of the sediment organic carbon time series signal, screens disturbance-resistant carbon components and constructs a carbon stability index, and realizes quantitative separation of physical disturbance and biological carbon sequestration contribution.

The utility model relates to the technical field of biodiversity observation, in particular to a biodiversity observation device convenient to fix, which comprises a fixed base, a support frame, an adjusting mechanism, an observation module and a fixing assembly. The fixed base is in threaded connection with a ground nail through a ground nail groove to achieve primary fixation, and the anti-overturning capacity of the fixed assembly is enhanced through a telescopic rod and a fixed plate; the adjusting mechanism can flexibly adjust the height and angle of the observation module. Through the design of the drain hole, the protective cover, the sealing ring and the like, the device adapts to complex terrains and underwater environments, and long-term stable deployment is ensured. The device can be quickly fixed and flexibly adjusted, the observation requirements in various scenes are met, and the adaptability and reliability of the device are improved.

The utility model discloses a river bank protection greening module which comprises a supporting column, a reinforcing pile is fixed to one side of the supporting column, one end of the reinforcing pile is fixedly installed in a hardened bank slope, an embedding hole is formed in the inner side of the supporting column, and a loss prevention plate and bearing planting soil are fixed to the inner side of the embedding hole; the supporting columns are symmetrically arranged relative to the center of the anti-loss plate, and a plurality of reinforcing piles are arranged on the supporting columns; the anti-loss plates are arranged at equal intervals along the supporting columns, and the width sizes of the anti-loss plates are increased layer by layer from top to bottom so as to form a slope shape. The ecological restoration system at least has the following beneficial effects that ecological restoration and biodiversity improvement are achieved, planting soil is borne through the anti-loss plate, hygrophytes are planted through the covering soil layer, an inhabiting and breeding place is provided for aquatic and terrestrial organisms, the soil can be fixed through plant root systems, an ecological barrier is formed, the ecological system of the river channel is effectively restored, and the biodiversity is promoted.

The invention discloses a reef-embankment cooperative system based on dredged object resource utilization and a port channel flow slowing, wave dissipating and silt reducing method, and relates to the technical field of port channel engineering. The system comprises a dredge ecological reef body and a composite energy dissipation embankment, the dredge ecological reef body and the composite energy dissipation embankment are cooperatively arranged from an open sea to a shoreline along a channel to form a three-stage hydrodynamic regulation gradient, 50%-70% of dredge is used as a main material of the ecological reef body, cement and a composite additive are matched, and the ecological reef body is put according to hydrodynamic partitions after pretreatment, mixing and forming maintenance; the embankment is divided into a foundation layer (graded riprap), an energy dissipation layer (concrete special-shaped blocks) and a protective layer (containing planting hole precast blocks and planting saline-alkaline tolerant plants). The technical effects that the collaborative wave dissipation rate is 50%-60%, the flow slowing rate is 25%-35%, the silt reduction rate is 40%-50%, the dredged material utilization rate is 50%-70%, and the cost is reduced by 40% or above can be achieved, meanwhile, the biological diversity can be improved, and engineering, resource and ecological values are achieved.

The invention provides a water and sand rhythm self-adaptive ecological water power channel device and a use method thereof, and aims to adjust lakeside wetland sediment deposition, guarantee ecological water use, improve water quality and restore ecology by constructing a channel device adaptive to lake hydrological rhythm and an intelligent management system. The device comprises a water inlet section (including a narrow-deep / shallow-wide section and a water-permeable separation levee), an ecological overflow section (including a shoal habitat area, a surface flow purification area and a deep pool conservation area), a sediment interception system (an assembly type triangular cone and a grit chamber) and an intelligent management unit (a water quality monitoring module, a water level sensing module and an automatic control module). The ecological water level assurance rate of the lakeside wetland can be remarkably increased, sediment deposition is reduced, the self-purification capacity of a water body is enhanced, biological diversity is enriched, and the method is suitable for lake ecological restoration engineering.

The application discloses a cascade hydropower station group intelligent scheduling and compensation benefit optimization method for ecological flow guarantee, and relates to the technical field of hydraulic engineering management. The application can accurately guarantee the ecological flow demand of the key section of the river basin, maintain the integrity of the aquatic habitat and the biodiversity, effectively solve the problem that the ecological flow is squeezed and difficult to quantify in the traditional cascade scheduling, optimize the power generation efficiency of the cascade hydropower station group through intelligent scheduling, balance the ecological protection cost and the hydropower development benefit by using the compensation mechanism, quantify the optimization effect by using the three-dimensional evaluation system, reduce the contradiction and conflict of the stakeholders, realize the win-win of ecological protection and economic development, and ensure that the method is adapted to different river basin characteristics and scheduling scenes through the whole-process simulation and parameter optimization of the typical river basin case in the model verification and iteration module. The system management module guarantees the efficient coordination of the user authority, data security and module interaction, and improves the operability and long-term operation reliability of the method.

The invention provides a terrestrial organism diversity monitoring method and device. A target monitoring area is divided into a plurality of ecological grids; processing the collected monitoring data set to identify species occurrence events and man-made interference events in each ecological grid; determining a dynamic event response increment of each ecological grid according to the number of species newly found in the statistical window and the man-made interference event intensity of each ecological grid; determining a monitoring urgency index of each ecological grid based on the static monitoring priority and the dynamic event response increment of each ecological grid; and making an adaptive monitoring strategy according to the monitoring urgency index of each ecological grid and the resource constraint of the mobile monitoring device, and fusing the monitoring results of all the ecological grids to generate an adaptive terrestrial biodiversity distribution diagram of the target monitoring area. By adopting the scheme of the invention, static value and dynamic threats can be fused, and intelligent monitoring of resources can be adaptively scheduled according to the static value and the dynamic threats.

This application discloses a cloud-based intelligent biodiversity monitoring method and system, relating to the field of intelligent monitoring. Specifically, species images collected by front-end devices are first uploaded to the cloud platform, where a general recognition model performs a preliminary assessment. If the general model's recognition result has high confidence or indicates a non-confusing species, the result is directly output. Crucially, when the general model's recognition result is uncertain or involves predefined easily confused species, the system extracts the species' Region of Interest (ROI) image and feeds it into a specially trained expert attention classifier. This classifier extracts multi-scale spatial salient features and performs deep fusion to accurately capture subtle differences, ultimately providing expert-level prediction results. This recognition strategy effectively overcomes the challenges of species identification in complex environments, significantly improving the accuracy and reliability of biodiversity monitoring.

This invention is applicable to the field of ecological environmental protection, providing a method and system for dynamic assessment of biodiversity in ecologically sensitive areas. The method includes: deploying a dynamic mobile monitoring network around the periphery of the ecologically sensitive area to collect data on human activity infiltration and time-series data of ecological parameters (vegetation canopy fragmentation, soil microbial activity decay rate, and frequency of stress behavior of indicator species); analyzing data fluctuation patterns through a time-series analysis model to identify early warnings of ecological degradation; performing reverse correlation of multi-source data based on satellite imagery, pollutant diffusion paths, and historical violations to determine the location and driving factors of degradation events; and integrating data quarterly to construct a dynamic resilience map and generate customized protection recommendations. This achieves early warning and precise source tracing of ecological degradation, improving the targeting and effectiveness of ecological protection strategies, and is applicable to the dynamic assessment and protection decision-making of biodiversity in ecologically sensitive areas.

The application provides a seawall front vegetation intelligent irrigation control method and system, and relates to the technical field of vegetation watering.The method comprises the following steps: constructing a seawall front irrigation system; acquiring a vegetation image; identifying a vegetation growth stage through a convolutional neural network according to the vegetation image; dividing vegetation regions according to vegetation types and the identified vegetation growth stage; predicting the required unit area water supply of each vegetation region through an artificial neural network according to soil granularity, average air temperature, precipitation, air humidity, a normalized water body index, vegetation types and the vegetation growth stage; and irrigating the vegetation in each vegetation region through the seawall front irrigation system according to the required unit area water supply of each vegetation region.The application can provide the best growth conditions for seawall front vegetation, promote the health and growth of the vegetation, help maintain and improve the stability of the ecosystem in the seawall front region, and support biodiversity.