1488 results about "Ecosystem" patented technology

The invention relates to the technical field of forestry informatization, in particular to an ecological public welfare forest monitoring and intelligent management system and method. The method comprises the steps of collecting multi-dimensional ecological data in real time and performing data fusion; based on a data fusion result, establishing an ecological behavior evolution graph and a multi-layer state inversion network by adopting a graph attention mechanism, forming a dynamic ecological twinborn body, and realizing ecological system state prediction, historical disturbance inversion and future behavior simulation; a risk tensor map is constructed in combination with state abnormality, trend instability and intervention ineffectiveness in a three-dimensional mode, a dynamic grading thermodynamic diagram is generated, and a personalized regulation and control strategy is recommended through reinforcement learning; and finally, sensing an actual regulation and control effect through a feedback mechanism, dynamically correcting twin model parameters by using deviation analysis, and constructing a knowledge base based on historical strategies and effects to drive strategy self-optimization. According to the method, a sensing-modeling-regulation-feedback closed loop is formed, and the accuracy and adaptability of ecological management are improved.

The invention aims to provide a mine ecological restoration carbon sequestration rate prediction method for solving the problems of an existing ecological restoration carbon sequestration rate prediction method. The method comprises the following steps: step 1, collecting multiple parameter multi-source data including vegetation growth, earth surface change and soil change of an ecological restoration area; 2, integrating the data, and constructing a dynamic prediction model for the change of the mine ecological restoration carbon sequestration rate; 3, verifying and optimizing the prediction model by using historical data and field observation data; and 4, adopting a machine learning technical means for the optimized prediction model, and establishing a quantitative relationship between the carbon sequestration rate change and ecological restoration means of land utilization, vegetation coverage and soil attributes. The method overcomes the influence of extreme climate events on the carbon sequestration rate of an ecological system, can accurately predict the change trend of the carbon sequestration rate under different ecological restoration strategies in the future, and provides a powerful scientific basis for ecological restoration of a mining area.

The invention relates to the technical field of ecological environment protection, in particular to an ecological protection red line division method applied to ecological basic investigation, which comprises the following steps: evaluating the service function and stability of an ecological unit through ecological basic data collection and processing in combination with an ecological model, and further delimiting an ecological protection red line area. The boundary of the red line area is optimized through space overlay analysis and conflict analysis of the current land utilization situation, and real-time adjustment is carried out based on ecological risk assessment and a dynamic monitoring mechanism. In combination with deep learning and reinforcement learning algorithms, dynamic monitoring and flexible adjustment of the red line area are realized, continuity and safety of an ecological system are guaranteed, intelligent management of the ecological protection red line is realized through a GIS technology and an early warning mechanism, scientificity and effectiveness of the ecological protection red line area are ensured, and the ecological protection red line area management method and system are suitable for popularization and application. And a reliable guarantee is provided for long-term stable development of an ecological system.

The invention relates to the field of water conservancy and hydropower engineering, in particular to a multi-objective optimized hydropower ecological scheduling decision-making system and method, and the system comprises a data collection module, an ecological model module, an intelligent decision-making engine module, a scheduling execution module, an effect evaluation module and a knowledge base module. The data acquisition module collects multi-source data, the ecological model module generates a training data set, the intelligent decision engine carries out ecological process modeling and probability prediction based on a deep learning architecture and spatial-temporal feature extraction, and generates a scheduling decision, the scheduling execution module controls hydropower engineering operation, and the effect evaluation module monitors ecological and economic effects. The knowledge base module stores historical experience and provides optimization suggestions, and the system improves the simulation accuracy of the ecological system, especially when the flow changes suddenly; and through uncertainty quantification, the system reliability and the ecological safety guarantee rate are enhanced, and high efficiency, accuracy and sustainability of ecological scheduling of the hydropower engineering are realized.

The invention relates to the technical field of port planning and construction, and particularly discloses a port planning and construction environment feasibility assessment method and system, and the method comprises the following steps: S1, obtaining planning parameters, real-time environment monitoring data, a historical ecological data set and social economic data of a target port; s2, constructing a dynamic coupling model of environmental bearing-ecological disturbance-pollution diffusion-social economic influence; and S3, based on the dynamic coupling model, adopting multi-scene space-time prediction simulation, and outputting an environmental feasibility comprehensive index, a key constraint factor and a social economic influence evaluation result. A dynamic coupling model of environment bearing, ecological disturbance, pollution diffusion and social economic influence is constructed, the four sub-models interact in real time through bidirectional data flow, full-dimension dynamic coupling evaluation of natural environment, ecological system, pollutant migration and social economic factors is achieved, and compared with traditional single-factor evaluation, the comprehensive evaluation accuracy is improved.

The invention discloses a soil health and microbiological analysis intelligent environment monitoring device, and relates to the technical field of soil monitoring, the device comprises the following components: an outer shell, a sensor assembly, a microflora interaction monitoring sensor group, a data acquisition and transmission module, a power supply module, a microprocessor, a control unit and a data analysis module; signal molecule concentration change data and predatory relationship visual data are combined through the data analysis module, deep analysis is carried out by using bioinformatics and mathematical modeling means, and a multi-dimensional regulation network hidden in a microbial community can be comprehensively revealed; according to the soil health assessment device, the interaction relationship between the soil ecological system and the soil ecological system is analyzed accurately, the influence of the interaction relationship on key ecological functions such as material circulation and energy flow in the soil ecological system is analyzed accurately, the device can generate a detailed soil health assessment report based on the analysis results, agricultural scientific researchers, planting farmers and environmental protection monitoring departments can assess the soil health condition accurately, and the soil health assessment efficiency is improved. And targeted soil management measures are taken.

The invention discloses a sewage denitrification dosing method and system based on machine learning and a storage medium, and belongs to the technical field of sewage treatment.The method includes the steps that data are collected and preprocessed, and variable data influencing biochemical pool carbon source dosing behaviors are obtained; and lagging influence of carbon source input on the denitrification amount index is analyzed, and the duration time range of the drug effect is determined. And adopting the trained prediction model, and based on the denitrification amount index and the prediction variable of the future t + X period, obtaining the dosage of the (t + 1) th period. Through a correlation analysis method, the correlation rule of nitrogen conversion in the future X period after the carbon source is added is analyzed, the duration time of the drug effect is determined, the lag effect is accurately quantified, and the problem of mismatching of regulation and control opportunities is avoided. The hysteresis effect is captured and subjected to multi-factor coupling analysis based on the prediction model, the carbon source adding amount and time are optimized, system load fluctuation caused by excessive carbon sources or incomplete nitrogen removal caused by insufficient carbon sources are avoided, and the stability of an original sewage ecological system is gradually improved.

The invention discloses a plant configuration method for synergistically improving forest ecological products, and relates to the technical field of plant configuration methods. The method comprises the following steps: site condition analysis: selecting a forest region with an area of S hectare in a mountain area as an implementation object, and obtaining site conditions of the implementation object through field exploration; setting an ecological target; screening plant varieties; plant configuration layout planning; calculating ecological influence factors; initial ecological target calculation: calculating an initial ecological target by using an ecological target calculation model based on the obtained ecological influence factors of different plant types and the divided forest region information; and adjusting the forest region based on the determined forest region information and the determined plant type information. According to the method, the actual situation of the region can be accurately grasped, the scientificity of a plant configuration scheme is greatly improved, and it is ensured that a forest ecological system always develops towards a preset ecological target.

The invention discloses an ecological restoration effect evaluation and simulation system after polluted soil restoration, and relates to the technical field of soil restoration, and the system comprises a soil feature generation module which generates an ecological feature data set; the ecological restoration evaluation module is used for establishing a multi-dimensional evaluation model by using an analytic hierarchy process and a fuzzy comprehensive evaluation method based on the ecological characteristic data set, and generating an ecological restoration effect index; the dynamic simulation prediction module is used for constructing an ecological restoration dynamic simulation model and simulating the evolution trend of a soil ecological system under different environment conditions; and the restoration strategy optimization module is used for generating a targeted ecological restoration optimization scheme by combining a preset restoration strategy library according to the ecological restoration effect index and the dynamic simulation prediction result. According to the method, a closed-loop system integrating multi-source data acquisition and processing, multi-dimensional evaluation, dynamic simulation prediction and stepped strategy optimization is constructed, and accurate evaluation of the ecological restoration effect after contaminated soil restoration and scientific optimization of the restoration strategy are achieved.

The invention relates to the technical field of image processing, and discloses a mangrove forest ecological information extraction method and system based on an unmanned aerial vehicle. The method comprises the following steps: acquiring overlooking and side-looking photos through an unmanned aerial vehicle; correcting the overlook picture by using the coordinate information and superposing the overlook picture to the remote sensing image; generating a photographing direction pattern layer based on the side view photo; establishing a mangrove forest species interpretation mark library by using a random forest algorithm; classifying selected samples to generate a species distribution diagram; and finally evaluating the mangrove forest ecological function to form ecological monitoring data. According to the method, multi-angle and multi-level high-precision ecological information extraction of the mangrove forest is realized, so that a more accurate and comprehensive scientific basis is provided for species classification, ecological system function evaluation and protection management of the mangrove forest.

A method for delineating an ecological corridor based on a maximum similarity model determines ecosystem type according to the determined ecological source, and assigns a habitat suitability index; and according to a maximum similarity matrix between different ecosystems, assigns the habitat suitability index to peripheral pixels of the selected ecological source, to obtain a similar value of the habitat suitability index. The habitat suitability index is corrected according to the surface curvature data and population density data, and resistance surface data is calculated according to the corrected value. Based on the resistance surface data, an ecological corridor is delineated comprehensively to find one or more paths corresponding to a minimum cost distance as ecological corridors. The influence of ecological environment on ecological corridor establishment is considered more comprehensively, so that the ecological corridor is delineated more accurately, and applied into practice to maximum extent.

The invention relates to the technical field of data analysis, in particular to a territorial space planning data analysis system for ecological restoration, which comprises an interference parameter acquisition module, an ecological disturbance calculation module, a restoration area identification module, a priority level judgment module and a site selection stability screening module. According to the method, the accuracy and efficiency of ecological restoration are improved by capturing various disturbance factors of an ecological sensitive area and dynamically evaluating ecological degradation, and the signal of ecological degradation can be recognized earlier by comprehensively monitoring the change trend of earth surface coverage and the dynamic state of a water body and quickly responding to the subtle change of an ecological environment; ecological service function indexes are adopted for inter-year comparison, a long-term view angle about the health state of an ecological system is provided, prediction accuracy is improved, ecological restoration work can be implemented in a more targeted mode, and the lasting effect of the ecological restoration work is ensured through continuous monitoring of land utilization changes.

The invention discloses an intelligent fish and rice symbiosis ecological control system and method based on the Internet of Things. The system comprises a fish breeding area, a rice irrigation area and a circulating water channel arranged between the fish breeding area and the rice irrigation area. The central control platform is used for collecting a dissolved oxygen (DO) value and a pH value in a water body in real time through a plurality of water quality sensors configured in the system; the dissolved oxygen DO value and the pH value are water quality data; and analyzing the dissolved oxygen DO value, generating a water quality regulation and control instruction, and regulating the oxygenation equipment according to the water quality regulation and control instruction. The automatic buffering agent adding device is used for automatically adding a buffering agent according to an instruction sent by the central control platform; the oxygenation equipment comprises an aeration device and is used for adjusting the content of dissolved oxygen in the water body. According to the intelligent fish and rice symbiosis ecological control system based on the Internet of Things, the fish culture area, the rice irrigation area and the circulating water channel are integrated, effective management and control of the fish and rice symbiosis ecological system are achieved, the water body environment is optimized, and the symbiosis benefits of fishes and rice are improved.

The invention provides a seaweed farm ecosystem prediction method, system, device and medium, and belongs to the technical field of seaweed farms, and the method specifically comprises the steps: collecting basic data of a seaweed farm ecosystem, and forming an ecological data set; preprocessing the ecological data set; determining a seaweed field prediction index, using a DMD mode to decompose and extract a time-delay main mode, then using convergence cross mapping to quantify causal intensity, constructing an environmental factor and biological index space-time diagram, and learning a causal edge weight through a graph attention network; predicting index change in combination with the incidence relation, and performing hybrid prediction by adopting a pulse disturbance-recovery coupling model and digital twinborn reinforcement learning; and visually outputting the prediction result. According to the method, a seaweed field ecological system monitoring and predicting system of data, information, knowledge and decision is constructed, the ecological system state characterization capability and risk early warning perspectiveness are improved, and scientific and efficient technical support is provided for marine ecological protection and management.

The present invention relates to the technical field of ecological suitability evaluation of agricultural land, and disclosed is a method for evaluating the ecological suitability of agricultural land. The present invention comprises: determining values of indicators of agricultural land, wherein the values of the indicators of the agricultural land comprise slope, elevation, slope length, profile curvature, soil thickness, plan curvature, the minimum number of days of continuous flooding, the maximum number of days of continuous flooding, the cumulative number of days of flooding, the average number of days of continuous flooding, minimum flooding depth, maximum flooding depth, cumulative flooding depth, and average flooding depth. In the present invention, the natural ecology of agricultural land, i.e., whether regional water, soil and climate conditions meet the ecological requirements of the agricultural land, is evaluated, so that it is ensured that the agricultural land can guarantee the sustainability of an ecosystem and environment; the ecological status thereof can be quickly and accurately identified, weights of indicators in an element layer can be determined, and finally, a system for evaluating the ecological suitability of agricultural land is constructed; the method can reflect the ecological suitability of agricultural land in a timely, macroscopic, and dynamic manner.

The invention discloses a multi-source remote sensing ecological production environment assessment system, and belongs to the field of ecological environment assessment. The system is composed of a data acquisition module, a data processing and fusion module, a generative artificial intelligence core engine, an ecological evaluation and decision support module and a user interaction interface, and all the modules are connected with one another, so that the overall function of the system is realized. According to the method, through a'representation-cognition-semantics' three-layer fusion architecture, the system can surpass traditional data piling, deep integration is carried out on multi-source information from bottom-layer features and spatial relationships to high-layer semantics, so that a complex interaction mechanism among ecological elements is more accurately understood and described, and the system is more efficient and efficient. And the overall cognitive ability and evaluation accuracy of the complex ecological system are remarkably improved. The system is based on a generative artificial intelligence core engine, not only can analyze the current situation, but also can simulate future scene evolution under different ecological management strategies.

The invention discloses a desert region water resource recycling method based on ecological restoration coupling, and the method comprises the steps: building a moisture-vegetation coupled spatial dynamic model through obtaining soil humidity distribution, vegetation coverage and regional microclimate data, and recognizing a suspected water resource retention region; the water resource circulation potential is evaluated in combination with microclimate fluctuation characteristics and earth surface characteristics, and an actual water resource optimal utilization area is screened; according to the water resource circulation potential, the vegetation planting density, variety and irrigation mode are dynamically adjusted, the ecological restoration gain coefficient is calculated, and collaborative optimization of the water resource utilization efficiency and the ecological restoration effect is achieved. Water resource management and ecological restoration are organically coupled, accurate utilization and efficient circulation of water resources are achieved, and the restoration capacity and sustainability of an ecological system in the desert area are remarkably improved.

The invention belongs to the technical field of ecological restoration and wetland engineering, and discloses an ecological corridor-based abandoned fishpond ecological restoration method, which comprises the following steps: S1, land forest restoration: planting saline-alkaline tolerant vegetation around an abandoned fishpond and in a land and abandoned fishpond transition area in a layered manner; s2, mangrove forest wetland construction: performing microtopography modification to adjust the bottom mud elevation, and planting mangrove forest plants in a layered manner; s3, ecological corridor construction: constructing an ecological corridor on one side of the abandoned fishpond and the land, and constructing an ecological corridor on one side of the abandoned fishpond and the ocean; s4, ecological monitoring and maintenance: carrying out hydrological, tidal and biological detection regularly; the three-dimensional ecological corridor system of'land forest-mangrove forest wetland-ocean 'is constructed, and the abandoned fish pond is transformed into the mangrove forest wetland, so that not only are biodiversity improvement and ecosystem connectivity realized, but also stable migration and inhabitation space can be provided for terrestrial and aquatic organisms.

The invention relates to the technical field of regional ecological risk assessment and space management and control, in particular to a regional ecological risk assessment and partitioning method based on a multi-system spatio-temporal dynamic relationship, which comprises the following steps: collecting and preprocessing multi-source spatio-temporal data; a natural ecological risk index and a human social risk index are fused, and a comprehensive ecological risk assessment model based on a social-ecological system is constructed; divariate spatial autocorrelation analysis and cold and hot spot analysis are adopted, and a region is divided into three-level subareas including a management and control area, a monitoring area and a prevention area and six types of subareas; and analyzing the partition dominant driving factor by using the optimal parameter geographic detector, and generating a differentiated control strategy. The method realizes quantitative coupling of natural ecology and human social system risk spatio-temporal dynamic relationships, solves the problems of strong subjectivity, insufficient system comprehensiveness and lack of dynamic association mechanisms of a traditional method through multi-dimensional index fusion and spatial analysis technologies, and provides systematic technical support for accurate management of regional ecological risks.

The invention discloses a territorial space planning optimization method and system based on an ecological safety pattern, and relates to the technical field of territorial space planning optimization and ecological safety protection, and the method comprises the steps: carrying out the system collection and preprocessing of multi-source space data, building a space planning optimization mechanism based on the ecological system features and regional development demands, and carrying out the optimization of the territorial space planning. And the spatial relationship among the ecological corridor, the buffer area and the development area is planned as a whole. According to the territorial space planning optimization method based on the ecological security pattern provided by the invention, effective coordination between ecological protection and economic and social development is realized by constructing the territorial space planning optimization method based on the ecological security pattern. By means of an optimized complex mathematical model combining ecological resistance, ecological connectivity, landscape heterogeneity, an ecological buffer area and ecological function compensation, the specific layout of an ecological sensitive area and an ecological corridor is accurately recognized, and the accuracy and the implementation effect of ecological protection measures are greatly improved.

The invention discloses a lead-zinc mine ecological restoration method driven by combination of pennisetum purpureum and soil microorganisms. After soil in a to-be-repaired area of a mine is loosened and conditioned, pennisetum purpureum is planted, different microorganisms A and microorganisms B are introduced before and after the pennisetum purpureum is planted respectively, the microorganisms A are composed of metal reducing bacteria and sulfate reducing bacteria, the microorganisms B are composed of heavy metal tolerant microorganisms and symbiotic nitrogen-fixing bacteria, and the heavy metal tolerant microorganisms and the symbiotic nitrogen-fixing bacteria can be obtained through the method that the different microorganisms are introduced in sequence. Heavy metals in the mine soil are transformed and absorbed for multiple times, and ecological restoration of the mine is realized. Through the combined action of microorganisms and plants, accumulation of organic matter in soil can be promoted, the diversity and activity of soil microbial communities can be restored, finally, restoration of a soil ecological system is achieved, in the restoration process, the root system of the pennisetum purpureum can assist in enhancing the structure and permeability of the soil through symbiosis with the microorganisms, and the soil quality is improved. And a foundation is laid for future ecological restoration.

The invention relates to the technical field of microbial agents, in particular to a composite microbial agent and application of the composite microbial agent in prevention and treatment of forest root diseases, and the composite microbial agent comprises the following components in parts by weight: 15-25 parts of Trichoderma harzianum ATCC 20847; 10 to 20 parts of bacillus subtilis ATCC 605, 10 to 20 parts of bacillus subtilis ATCC 605, 10 to 20 parts of bacillus subtilis ATCC 606 and 10 to 20 parts of bacillus subtilis ATCC 607. 5-10 parts of a seaweed extract; 3 to 8 parts of chitosan; 2-5 parts of humic acid; 1 to 3 parts of glycine betaine; 0.5 to 1.5 parts of a trace element compound; 30 to 40 parts of perlite powder; according to the present invention, the fertilizer has characteristics of significant inhibition effect on a variety of forest root pathogenic bacteria, wide prevention and control spectrum, and long-term and stable disease prevention effect by adjusting the rhizosphere micro-ecosystem. Diseases are prevented and controlled, and the growth and root development of the forest trees are remarkably promoted.

The invention relates to the technical field of reservoir ecological management, in particular to a reservoir ecological scheduling method and system and a storage medium. The method comprises the following steps: carrying out vertical section multi-source parameter acquisition on a reservoir through a sensor array to obtain an original section data set; carrying out bottom mud-water body substance exchange strength characterization on the original profile data set to obtain an exchange flux comprehensive index; layering the reservoir according to the exchange flux comprehensive index to obtain a reservoir horizon structure chart; performing season-depth partition according to the reservoir horizon structure chart to obtain a partition statistical feature set; performing ecological safety response association on the partitioned statistical feature set to obtain an ecological safety domain map; and performing exchange flux and scheduling constraint analysis according to the ecological security domain atlas to obtain an exchange flux deviation table and a scheduling constraint condition set. According to the invention, a scientific scheduling method is provided for health of the reservoir ecosystem through collaborative optimization of water level regulation and control and layered drainage.

The invention provides a wetland ecosystem health evaluation method based on multi-source remote sensing data, and belongs to the technical field of wetland ecosystems, and the method comprises the steps: carrying out the dense dark pixel and Kalman filtering cooperative atmospheric correction of a multi-spectral remote sensing image to obtain a surface reflectance image, and achieving the precise segmentation of a wetland landscape through a graph cut theory, a spectral unmixing model based on an improved Gaussian kernel is utilized to embed physical constraints to invert water quality parameters, a laser radar canopy height priori constraint three-dimensional radiation transmission model is combined to invert vegetation parameters, and a mixed pixel decomposition result is optimized through a Markov random field. A water quality, vegetation and landscape three-dimensional comprehensive health evaluation system is constructed, degradation dominant factors are identified, and the technical problem that it is difficult for multi-source remote sensing data to cooperatively invert wetland ecosystem multi-dimensional health state parameters is solved.

The embodiment of the invention provides an urban green land community ecosystem regulation service optimization factor identification method and device based on a fusion algorithm and electronic equipment, and belongs to the technical field of ecological data processing, and the method comprises the steps: collecting a plant community, an elevation model and meteorological monitoring data to form a basic data set; uniformly quantifying the data and evaluating the ecological service in combination with the measurement and calculation model to form a standardized data set; inputting the features into a plurality of machine learning models, and screening out a key feature set through operations such as guided aggregation and the like; constructing an IOFESRM-LMEM model, outputting an optimal model through a series of operations, and analyzing key factors; and finally, outputting an optimization result, a key factor and an evaluation result by using a multi-dimensional index evaluation model. According to the invention, data support is provided for improving the ecological function of the urban green land, formulating ecological planning and optimizing urban management.

The invention discloses a trend prediction and early warning method applied to health evaluation of a bay ecological system, and relates to the technical field of bay ecological early warning, and the method comprises the following steps: collecting monitoring data of bay ecology, and dividing the monitoring data into historical data and real-time data, wherein the monitoring data comprises water quality data, geological data and hydro meteorological data, the collected monitoring data is preprocessed, bay ecosystem impact factors are screened, the bay ecosystem impact factors comprise physical impact factors and chemical impact factors, and the preprocessed historical data and the bay ecosystem impact factors are utilized. According to the method, trend prediction is carried out on the health condition of an ecological system in a period of time in the future by constructing the gulf ecological prediction model based on historical data and real-time monitoring information, so that related departments and the public can take actions before problems occur, and potential ecological risks are effectively prevented.

The invention discloses a mangrove forest distribution information extraction method based on deep learning and remote sensing images, and the method comprises the steps: firstly, constructing a spatial diagram fusing ecological priori knowledge such as hydrological connectivity, and extracting high-dimensional features containing a complex space-time dependence relation from an irregular satellite image time sequence through employing a PG-STGT network; a physical information guided antagonism decoupling mechanism is subsequently adopted to explicitly decompose the high-dimensional feature into three subspaces. And finally, according to the method, a high-robustness distribution diagram is generated by applying the decoupled identity feature vectors, and a multi-dimensional mangrove forest health index is generated by using residual error abnormal features. According to the method, the physical mechanism and deep learning are deeply fused, the time consistency of the classification result is improved, and the ability of diagnosing the health condition of the ecological system is provided.

In certain aspects of the disclosure, a computer-implemented method includes receiving a selection of a model from a plurality of models running on an ecosystem. The method includes receiving annotated datasets with correct examples and incorrect examples. The method includes training, responsive to receiving the annotated datasets, the model based on the annotated datasets. The method includes running the model based on the training. The method includes receiving a feedback score of results from running the model based on the annotated datasets. The method includes iteratively running, until the feedback score is above a predetermined threshold, the model responsive to user evaluation of the results from running the model based on the annotated datasets. The method includes publishing the model responsive to the feedback score being above the predetermined threshold.

The invention relates to an ecological restoration method for a high and cold mine, and belongs to the technical field of ecological restoration. The ecological restoration method for the high-cold mine comprises the step of performing ecological restoration on the high-cold mine by adopting vegetation configuration of shrubs, herbaceous plants A and herbaceous plants B, the herbaceous plants A comprise at least four of elymus dahuricus, siberian wildrye herb, festuca arundinacea, bluegrass, stipa purpurea, ryegrass, frozen artemisia stelleriana and herba artemisiae annuae; the herbaceous plant B comprises at least three of artemisia desertorum, plantain herb, alfalfa, astragalus membranaceus, dandelion and oxytropis philippinarum; the shrub species comprise at least two of sophora moorcroftiana, sabina vulgaris, sea-buckthorn, caragana and buddleia. According to the method, specific vegetation configuration of shrubs, herbaceous plants A and herbaceous plants B is adopted, and soil microorganism resources are recovered quickly; the extreme environment of high and cold mines can be overcome; the ecological system is quickly and efficiently restored, only one-time sowing is needed, and the cost is low; the vegetation and microorganisms interact with each other, so that the survival rate of the vegetation is high.

The invention discloses a network toughness prediction method, system and device based on digital twinning, and relates to the technical field of ecological monitoring and network toughness modeling. The network toughness prediction method, system and device based on digital twinning comprises the following steps: S1, collecting multiple types of ecological monitoring data through ecological monitoring equipment, and carrying out standardized preprocessing on the ecological monitoring data; s2, the modeling difficulty of each piece of ecological data is comprehensively evaluated, and automatic screening and grading processing of data quality are achieved; s3, performing state synchronous evaluation on the to-be-modeled data, and dynamically updating the operation state of the corresponding ecological entity in the digital twin based on a state evaluation result; and S4, identifying key fragile nodes and risk paths in each ecological entity, and outputting corresponding ecological risk levels and regulation and control suggestions. The problem that in the prior art, static threshold risk judgment is carried out only based on a small amount of observation data, and multi-source isomerism and dynamic evolution characteristics existing in an ecological system cannot be effectively handled is solved.