71 results about "Species distribution" patented technology

The invention discloses an euphausia superba fishery change prediction method based on an ocean circulation-sea ice-species distribution coupling model, and relates to the technical field of ocean science. Euphausia superba fishery historical observation data, satellite remote sensing data and reanalysis data are collected, euphausia superba resources and environmental data are integrated, and the euphausia superba fishery change prediction method based on the ocean circulation-sea ice-species distribution coupling model is obtained. Constructing a polar region resource environment database covering total elements of physics-biology-environment; and based on an FVCOM model, constructing an ocean circulation-sea ice coupling model of a surrounding sea area of the peninsula of the south pole, and simulating and verifying physical environment characteristics of a target sea area. By constructing the ocean circulation-sea ice-species distribution coupling model, integrating multi-source data and analyzing a cooperative driving mechanism of a multi-scale physical process to euphausia superba resource change, compared with a traditional method, the change of an euphausia superba fishery can be simulated and predicted more accurately, and the method has the advantages of being high in practicability and the like. And the problem of inaccurate prediction caused by limited space-time coverage rate of observation data is effectively solved.

The invention discloses a marine fishery resource survey station adaptive optimization method based on a space-time coupling model. According to the method, a space-time continuous species distribution dynamic reference field is constructed by coupling a Bayesian hierarchical species distribution model and a regional ocean model system; performing ecological layering based on time, space and environment dimensions; and when the environment variables change significantly, a habitat suitability index is dynamically reconstructed, and the station layout is optimized again, so that the coverage of a key ecological hot spot area is ensured, and the in-gradient representativeness is maintained. The method has the advantages of fast environmental response, strong spatial representativeness, high adaptability and the like, and is suitable for scenes of resource assessment, ecological protection, biodiversity monitoring and the like.

The invention relates to a species suitable habitat simulation method and device under future climate, and the method comprises the steps: obtaining remote sensing data, foundation observation data and species distribution data in a target region, and carrying out the unified preprocessing of the data, and obtaining processed data; constructing environment characteristic variables based on the processed data, and performing screening to obtain a training data set meeting species suitability modeling input conditions; and constructing a species suitability model under the current climate condition by using the training data set, predicting species suitable habitat distribution under a future climate scene by using the species suitability model, and analyzing a spatial change trend according to the species suitable habitat distribution. Therefore, the problems that remote sensing and foundation observation data are isomerism in the aspects of time, space, scale and the like, an effective data fusion and index conversion mechanism is lacked, registration errors and feature inconsistency are easily caused, and the accuracy and reliability of ecological parameter estimation are affected are solved.

The invention provides a key species population spatial distribution quantification method and system in a complex ecological system, and the method comprises the steps: carrying out the feature extraction of biological and environmental data collected in a target ecological region, and carrying out the fusion of the extracted multi-modal features, and generating a comprehensive feature vector; based on the target large model, analyzing the comprehensive feature vector, identifying species in the target ecological region, and obtaining species identification information of each species; based on the species identification information and the comprehensive feature vector corresponding to the target ecological region, quantifying a species population space distribution condition, and generating species population quantification information at least comprising a population distribution diagram, a population density diagram and a population dynamic change diagram; and based on the species population quantitative information and the collected original data, generating and displaying a quantitative report. According to the method, the species can be intelligently, efficiently and accurately identified based on the large model, the distribution condition and dynamic change of the species can be visually displayed, a quantitative report is provided, and a powerful basis is provided for ecological protection and management.

The invention relates to a regional climate shelter identification method based on climate change and a species distribution model. The method comprises the following steps: S1, species distribution modeling; step S2, biological velocity calculation; s3, calculating the richness of the species; s4, calculating the habitat quality; step S5, climate stability calculation; step S6, calculating a connectivity index and a reachability index; the method has the advantages that dimensions of three information including space, time and ecology can be effectively captured, species richness, habitat quality, climate stability and biological speed are integrated, the defect that a climate speed index neglects species specific diffusion rate and habitat suitability in shelter recognition is made up, and the method has the advantages of being high in adaptability and high in reliability. And the method is limited by a climate matching threshold value, so that the climate refuge can be identified more accurately.

The invention discloses a coastal zone planning method and system based on MaXent and hotspot analysis, and relates to the technical field of coastal zone planning. Comprising the following steps: S1, collecting environment variable data, species distribution data and development intensity data, constructing a unified space-time grid system, and realizing time sequence expression of the data through data preprocessing; s2, constructing a quarterly time sequence maximum entropy model, and performing time sequence evaluation on each grid habitat state to form a habitat evolution type; s3, identifying time sequence significant hot spots and hot spot persistence and intensity features, constructing ecological development relationship comprehensive representation, and identifying ecological development conflict types; and S4, spatially superposing the habitat evolution type and the ecological development conflict type to form a self-adaptive access rule, and generating differentiated planning suggestions according to regions. The problem that planning lacks dynamic adaptability due to the fact that coastal zone habitat suitability and development intensity depend on static time point data for a long time and a time sequence evolution rule cannot be recognized is solved.

The invention relates to the technical field of species ecological niche modeling, and provides a coastal wetland waterfowl ecological corridor construction method and system, and the method comprises the steps: collecting target waterfowl species distribution point data, and obtaining a waterfowl species distribution data set; performing habitat suitability modeling on environmental factor data and the waterfowl species distribution data set through a species distribution model to obtain a coastal wetland ecological source land; habitat suitability prediction modeling is carried out on the environment variables through a random forest algorithm, resistance value assignment is carried out on suitability indexes, and a coastal wetland comprehensive resistance surface is obtained; and carrying out multi-scene corridor path identification on the coastal wetland comprehensive resistance surface and the coastal wetland ecological source land to obtain the coastal wetland waterfowl ecological corridor. According to the method, the functionality of the ecological corridor under different ecological backgrounds can be comprehensively reflected, so that the ecological suitability of the constructed corridor is improved.

The invention relates to the technical field of species distribution analysis, and discloses a dove tree population natural update limitation-based species distribution analysis system, which comprises a habitat factor acquisition module, an update limitation evaluation module, a distribution prediction module, a spatial constraint correction module and an adaptability atlas optimization module. The habitat factor acquisition module acquires data in real time and constructs a multi-layer environment factor topology; the update limit evaluation module evaluates update limit in combination with genetic diversity and seed diffusion constraint; the distribution prediction module generates a distribution strategy through spatial modeling and ecological niche optimization; the spatial constraint correction module corrects a diffusion range and genetic parameters based on terrain and climate factors; and the adaptability graph optimization module feeds back an analysis result to carry out closed-loop optimization on the strategy. The system is provided with a multi-stage obstacle avoidance mechanism and a redundant link, so that the habitat change response capability is improved. According to the method, accurate analysis and dynamic optimization of davidia involucrata distribution are realized, and technical support is provided for species protection.

This invention discloses a method for predicting changes in Antarctic krill fishery grounds based on a coupled ocean circulation-sea ice-species distribution model. This method, which relates to the field of marine science and technology, collects historical observational data on the Antarctic krill fishery, satellite remote sensing data, and reanalysis data, integrates Antarctic krill resource and environmental data, and constructs a polar resource and environmental database covering all physical, biological, and environmental factors. Based on the FVCOM model, a coupled ocean circulation-sea ice model is constructed for the waters surrounding the Antarctic Peninsula to simulate and verify the physical environmental characteristics of the target sea area. By constructing a coupled ocean circulation-sea ice-species distribution model, integrating multi-source data, and analyzing the synergistic driving mechanisms of krill resource changes through multi-scale physical processes, this method can more accurately simulate and predict changes in Antarctic krill fishery grounds than traditional methods, effectively addressing the problem of inaccurate predictions caused by the limited spatiotemporal coverage of observational data.

The invention relates to the technical field of ecological environment protection, in particular to a multi-dimensional evaluation method for a connectivity function of a land directed ecological network, which comprises the following steps: collecting species distribution data and environment variable data of a target area to measure land inhabitation suitability; screening land habitat plaques of the target area according to the land habitat suitability; identifying a species migration corridor according to the land region species migration resistance surface and the land region habitat plaque; establishing a land directed ecological network according to the land habitat plaques and the species migration galleries; an improved multi-centrality algorithm is adopted to measure the directed degree centrality, the directed adjacent centrality and the directed intermediary centrality of the directed ecological network, and then the ecological node comprehensive centrality and the ecological connection edge comprehensive centrality of the land area directed ecological network are evaluated. Therefore, the problem that the importance of each component of the ecological network has an omission risk due to the fact that the existing connectivity assessment based on the undirected ecological network does not consider the interaction demand of the ecological flow is solved.

The invention discloses an intelligent forest wild animal monitoring method and system based on multi-source data fusion, and relates to the field of wild animal monitoring and ecological protection, and the method constructs an integrated monitoring system by arranging a ground infrared camera network and an unmanned aerial vehicle multi-sensor inspection platform and accessing satellite remote sensing data. And the system analyzes infrared data in real time by using the edge computing node and triggers emergency response of the unmanned aerial vehicle, so that quick tracking of key events is realized. Pixel-level space-time alignment and cross-modal feature fusion are performed on multi-source image data, and a target detection model is input, so that species and behaviors can be accurately identified. Meanwhile, after the multispectral data and the geographical environment data are subjected to gridding alignment, the data are input into a habitat analysis model, and a habitat suitability probability graph is generated. And automatically generating protection decision support information through comprehensive correlation analysis of species distribution and habitat quality. According to the invention, all-weather, full-space and intelligent wild animal monitoring and protection response are realized.

The application discloses a coastal zone planning method and system based on MaXent and hotspot analysis, and relates to the technical field of coastal zone planning. The method comprises the following steps: S1, collecting environmental variable data, species distribution data and development intensity data, constructing a unified space-time grid system, and realizing time series expression of the data through data preprocessing; S2, constructing a quarterly time series maximum entropy model, time series evaluating habitat states of each grid, and forming habitat evolution types; S3, identifying time series significant hotspots and hotspot persistence and intensity characteristics, constructing a comprehensive representation of ecological development relationship, and identifying ecological development conflict types; and S4, spatially superimposing the habitat evolution types and the ecological development conflict types, forming adaptive access rules, and generating differentiated planning suggestions according to regions. The problems that the long-term dependence of coastal zone habitat suitability and development intensity on static time point data and the inability to identify time series evolution rules result in the lack of dynamic adaptability of planning are solved.

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 a kind of urban bird species distribution prediction method and system based on deep learning, it is related to the technical field of ecology and landscape architecture, by realizing the unified modeling of environmental characteristics, species co-occurrence relationship and spatial proximity information;Through environmental characteristic intelligent weighting and enhancement mechanism and multi-task joint learning strategy, the expression ability of model to ecological correlation structure is improved;Combined with species richness stratified evaluation and calibration mechanism, the reliability of the prediction result of uninvestigated area is enhanced;Form the automation technical process from data processing, model training to regional species richness output, can provide efficient, systematic technical support for urban biodiversity assessment and ecological planning.

The invention relates to the technical field of natural resource protection and ecological system management, and discloses a method and a system for constructing a three-dimensional dynamic model of forest grass wet and waste areas based on digital twinning, and the method comprises the steps: obtaining multispectral image data and environment readings of forest, grassland, wetland and desert areas; performing feature data primary processing to obtain vegetation coverage information and environment variable data; performing species distribution boundary labeling to obtain a species distribution boundary; performing pattern correlation analysis to obtain a preliminary relation matrix; if the association strength of the water level parameter and the desertification parameter in the preliminary relation matrix is higher than a preset strength threshold value, calculating a correction coefficient of the water level parameter and the desertification parameter; carrying out weight balance to obtain a balance relation matrix; time sequence deviation detection and stability verification are carried out, and an ecological change simulation framework is determined. According to the method, comprehensive analysis of complex ecological systems such as forests, grasslands, wetlands and deserts can be realized, and dynamic monitoring and protection are carried out.

The invention belongs to the technical field of smart cities, and particularly relates to a smart city environment management method and system based on digital twinning, and the method achieves the high-precision collection of species distribution, vegetation coverage, surface temperature and wind speed data in a city region. By constructing a dynamic space model containing a species-environment interaction relationship, the dynamic change of surface thermal radiation absorption and release caused by increase and decrease of different species is successfully simulated; furthermore, by calculating hourly influence coefficients and iteratively deriving a ten-year microclimate evolution trend, a priority ranking scheme for species protection or regulation is finally generated. According to the method, the understanding depth and response speed of urban managers for ecological environment changes are greatly improved, real-time calibration based on latest monitoring data becomes possible, and scientificity and foresight of urban management decisions are ensured.

The invention discloses a method for predicting a future suitable habitat change trend of medicinal plant diversity, relates to the technical field of species distribution prediction, and aims to solve the problem that a habitat of medicinal plants is seriously damaged and under the background that part of the medicinal plants are eradicated or endangered. A future distribution prediction framework is constructed based on a MaxEnt model on the premise that the medicinal plant diversity is urgently required to be protected, and the suitable habitat change trend of the medicinal plant diversity in the future is predicted by using the MaxEnt model, so that species eradication can be effectively avoided, sustainable development of medicinal plant resources is guaranteed, and meanwhile ecological balance is maintained. The MaxEnt model has the characteristics of high accuracy and simplicity and convenience in operation, can accurately predict the suitable habitat of the medicinal plant diversity even when sample distribution points are few, and can provide reference for local governments to cope with international sustainable development and diversity protection policies.

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 application discloses a natural ecosystem authenticity determination method and device, relates to the technical field of ecological evaluation, and comprises the following steps: acquiring land use data of a research area, and calculating an ecological structure authenticity index; identifying a natural reference area based on ecological environment zoning and the ecological structure authenticity index; acquiring ecosystem service data, and calculating an ecological process authenticity index and an ecological function authenticity index based on the natural reference area; acquiring species distribution data, and calculating a biological and indicator species authenticity index; acquiring human activity data, and calculating a human disturbance intensity index; and finally, normalizing and weightedly fusing the indexes to obtain a natural ecosystem authenticity comprehensive index. The application solves the problems of single dimension, neglect of regional natural benchmark differences and lack of a multi-factor comprehensive framework of the existing evaluation method, and significantly improves the scientific nature of natural reserve management.

This invention provides a quantitative prediction method for the spatiotemporal distribution changes of vole populations, belonging to the field of species distribution prediction in the ecological environment. The method includes: determining vole habitats based on their activity range; dividing the study area of ​​the vole habitat into an unstructured grid based on triangular units using a hydrodynamic model and a two-dimensional sediment model; constructing a vole habitat quality assessment model, a vole subpopulation migration model, a vole population size change model, and a vole stored energy change model; coupling these models for calculation, and predicting the distribution changes of the vole population based on the calculation results. This invention, through the coupled calculation of different models, can accurately predict the distribution range of vole based on the calculation results, which is of great significance for effectively controlling vole outbreaks.

The invention relates to the technical field of plant ecological monitoring and computer vision, and discloses a grassland dominant species identification method based on unmanned aerial vehicle remote sensing and deep learning, and the method comprises the steps: carrying out the fusion processing of a to-be-identified unmanned aerial vehicle remote sensing image of a target grassland region, and obtaining a to-be-identified fusion image; inputting the fusion image to be identified into a trained species identification model to obtain a species classification result of the target grassland area; combining the species classification result with the space coordinates of the target grassland area to generate a species distribution diagram of the target grassland area; according to the method, the problem of insufficient species identification precision in a complex grassland environment can be solved, manual investigation cost and subjective deviation are reduced, grassland dominant species identification accuracy and spatial analysis capability are improved, and refined data support is provided for grassland ecological protection.

The invention provides a method and a system for predicting a potential suitable growth area of alien invasive species in the technical field of risk management of invasive species. The method comprises the following steps: S1, acquiring a large amount of environment variable data and species distribution sample data; s2, downscaling the environment variable data through a spatial regression model to construct a high-resolution environment data set, performing spatial refinement on the species distribution sample data through a Moran index to construct a sample data subset, and constructing a data set based on the high-resolution environment data set and the sample data subset; s3, creating a species distribution model based on a maximum entropy model, a random forest, a support vector machine, a generalized linear model, an XGBOOST or a deep learning model, and training the species distribution model through the data set; and S4, predicting the suitable growth area of the alien invasive species through the trained species distribution model. The method has the advantages that the prediction precision and generalization ability of the potential suitable growth area of the alien invasive species are greatly improved.

The invention discloses a biodiversity investigation monitoring method based on satellite remote sensing and environmental DNA sequencing. The method comprises the following steps: S1, acquiring habitat remote sensing data and environmental DNA data; s2, preprocessing the obtained data, and comparing the preprocessed data with a public gene database to obtain species distribution data; s3, performing time and space scale alignment and fusion on the habitat remote sensing data and the environment DNA data to generate a biodiversity feature data set; and S4, constructing and generating a correlation model and a three-dimensional model between the habitat and the species distribution, and visually displaying the dynamic change of the biodiversity. According to the method, the comprehensiveness, accuracy and timeliness of investigation and monitoring are improved, and a scientific basis is provided for biodiversity protection.

The present application relates to the technical field of ecological environment and carbon emission management, and discloses a method, device and equipment for evaluating carbon sink potential of ecological restoration in an open-pit mine area, which comprises the following steps: obtaining basic data of the mine area, and constructing a multi-dimensional remote sensing data cube, an environmental factor database and a species distribution sample database based on the basic data of the mine area; generating a closed pit spatiotemporal distribution database based on the multi-dimensional remote sensing data cube; modeling the habitat suitability probability of species based on the environmental factor database, the species distribution sample database and the closed pit spatiotemporal distribution database, and generating an ecological restoration suitability spatial zoning database; generating a carbon sink potential spatiotemporal distribution map based on the closed pit spatiotemporal distribution database and the ecological restoration suitability spatial zoning database, and evaluating the carbon sink potential of the mine area based on the carbon sink potential spatiotemporal distribution map; the present application can finely depict the spatiotemporal evolution law of the restoration of the mine area, dynamically quantify the carbon fixation potential of different restoration measures and species types, and obtain a scientific carbon sink evaluation method.

The application discloses a biodiversity investigation and monitoring method based on satellite remote sensing and environmental DNA sequencing, comprising the following steps: S1, obtaining habitat remote sensing data and environmental DNA data; S2, preprocessing the obtained data and comparing with a public gene database to obtain species distribution data; S3, aligning and fusing the habitat remote sensing data and the environmental DNA data in time and space scales to generate a biodiversity feature data set; and S4, constructing a correlation model and a three-dimensional model between the habitat and the species distribution, and visually displaying the dynamic change of biodiversity. The application improves the comprehensiveness, accuracy and timeliness of investigation and monitoring, and provides a scientific basis for biodiversity protection.

The invention relates to a method for forming a continuous spatio-temporal data sequence based on a species distribution model and an environmental data supplementary time section, and relates to the technical field of fishery resource investigation and evaluation and ecological system modeling and management. The method comprises the following steps: collecting fixed-point survey data and environmental condition data; establishing a resource-environment relation model; acquiring environment data at a target time point and speculating a fishery resource distribution state based on the model; speculating resource distribution characteristics in the middle time period through interpolation between the two investigation time points; adjusting environmental adaptation feature optimization prediction based on the speculation result; and finally, integrating the speculated data and the measured data to generate a minute-scale, hour-scale or daily-scale continuous three-dimensional resource distribution data set. According to the method, the temporal-spatial resolution and continuity of fishery resource distribution data can be remarkably improved, the ecological mechanism support of prediction is enhanced, and the method is widely applied to fishery resource dynamic monitoring, ecological system evaluation, protection division formulation and fishery management based on an ecological system.

The invention provides a karst rocky desertification side slope ecological restoration method which comprises the following steps: selecting a rocky desertification side slope region, generating a spherical region range based on geographic coordinates, and recording center coordinates of a target side slope; the method comprises the following steps: acquiring vegetation coverage, height and type distribution data based on remote sensing data and field sampling, and acquiring wind speed, wind direction, soil element distribution, precipitation, runoff, vegetation seed bank quantity, seed bank soil humidity, seed particle size distribution and type distribution data at the same time; generating a wind power field function according to the wind speed and wind direction data, analyzing the soil element content, calculating the total rainwater amount and the total runoff amount, and generating the number of effective vegetation seeds; integrating the parameters to construct a carbon sequestration and slow release model, and outputting a carbon cycle model. According to the method, the carbon sequestration capability of the karst rocky desertification slope ecosystem can be accurately evaluated, the dynamic monitoring and optimization of the ecological restoration effect are realized, and the ecological restoration efficiency and the regional ecological stability are improved.

This invention discloses a method for delineating restoration areas based on biodiversity and habitat stress in the field of natural resource management technology. The method includes acquiring species distribution records and environmental variable data for each species in a target spatial area, and then filtering the environmental variable data to obtain filtered environmental variable data. This invention processes the input data using multiple models in an integrated species distribution model to calculate species richness, functional diversity, and phylogenetic diversity as representative indicators. This overcomes the limitations of previous methods that only focused on a single dimension of biodiversity information, providing a more comprehensive representation of biodiversity levels. By constructing a comprehensive biodiversity index and a comprehensive habitat stress index to comprehensively identify priority restoration areas, this method avoids the limitations and shortcomings of previous methods that only focused on a single dimension of biodiversity, and fully considers the dynamic coupling relationship between biodiversity and habitat conditions.

This application relates to a method for identifying avian influenza spillover risk areas at the waterfowl-seabird interface, comprising: acquiring indicator data and environmental data of avian influenza waterfowl-seabird hosts; wherein, the indicator data includes species distribution point data of avian influenza waterfowl-seabird hosts and avian influenza occurrence point data in seabirds; screening species distribution point data monthly; determining whether the species distribution point data is sufficient according to preset conditions; if all species distribution point data is sufficient, calculating the waterfowl-seabird spillover risk index based on activity intensity; otherwise, calculating the waterfowl-seabird spillover risk index based on species richness, thereby identifying avian influenza spillover risk areas between waterfowl and seabirds. By integrating avian influenza waterfowl-seabird host indicator data and environmental data, and using different methods to calculate the waterfowl-seabird spillover risk index pixel by pixel according to different species distribution point distribution situations, the method can accurately identify avian influenza spillover risk areas between waterfowl and seabirds.

The present invention provides a species distribution data aggregation method and system, and a storage medium. The method comprises: obtaining original species distribution data; determining a map grid scale displaying the species distribution, and acquiring the original species distribution data within a range of each grid; and taking each grid as a central grid, and performing data enhancement on the central grid by using original species distribution data of multiple other grids within a set range around each grid, thereby obtaining a species distribution data aggregation result of each grid. The species distribution data aggregation method provided by the invention can enhance the display of the species distribution data, thereby improving the data display effects.