154 results about "Ecological data" patented technology

The invention discloses a marine ecological protection and restoration project comprehensive evaluation method based on multi-dimensional analysis, and relates to the field of marine ecological analysis, and the method comprises the steps: obtaining multi-dimensional monitoring data through constructing a target region map model and setting a monitoring point, and generating an ecological feature vector; calculating a relative distance and a deviation between the monitoring point and the comparison feature vector to obtain a repair expected goodness of fit; screening monitoring points with low goodness of fit and integrating the ecological data set; training and generating an optimized simulation feature vector based on a GAN model; and analyzing the simulation parameters and evaluating the ecological evolution trend to complete comprehensive evaluation. According to the method, multi-dimensional and high-precision ecological assessment is realized, the accuracy of restoration effect prediction and the scientificity of an assessment result are improved, reliable support is provided for a marine ecological protection restoration decision, and the problems of one-sided monitoring, insufficient prediction and the like of an existing method are solved.

The invention relates to the technical field of intelligent mine and environmental protection crossing, and discloses a mine development ecological data fusion and causal mining method based on a double-lineage knowledge graph. The method comprises the steps of constructing a double-pedigree domain ontology model comprising a production activity pedigree and an ecological response pedigree, carrying out multi-modal data space-time alignment and standardization, constructing a dynamic map reflecting the real-time state of a mine, predicting future ecological indexes by using a time sequence diagram neural network introduced with physical constraints, and carrying out real-time monitoring on the real-time state of the mine. And calculating the contribution degree of each production link to abnormity by utilizing anti-fact reasoning so as to lock a disaster-causing source, and generating a production regulation and control instruction according to a causal analysis result, and feeding back and executing the production regulation and control instruction. According to the method and the system, full-process traceability and accurate regulation and control of mine environment problems such as surface deformation and water and soil pollution are realized, so that the problems that data multi-source heterogeneous is difficult to fuse and the causal relationship is difficult to confirm in mine ecological environment monitoring are solved.

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.

The invention discloses a water conservancy project ecological construction method and system based on artificial intelligence, and relates to the technical field of ecological system simulation, and the method comprises the steps: collecting historical ecological event data of each region of a water conservancy project, analyzing the causal association between events based on an artificial intelligence model, and calculating and dynamically updating the association degree index between any two regions; constructing a regional association network based on the association degree indexes, calculating core scores of nodes in the network to identify a core region, and dynamically improving the monitoring sampling frequency of ecological data for the core region; and when an abnormal state is monitored in a single region, predicting the abnormal risk probability of other regions, and generating and recommending an optimal coping plan. Compared with the prior art, the method has the advantages that by constructing a dynamic regional correlation analysis system, the mutual influence between ecological regions is quantified, the monitoring resources are distributed uniformly to be intelligently and optimally configured based on the network core degree, and the monitoring efficiency and the capturing capacity of key information are remarkably improved.

The invention discloses a lake and reservoir future carbon income and expenditure scenario prediction accounting method based on climate change influence, and relates to the technical field of ecological environment monitoring and carbon cycle research, and the method comprises the steps: S1, collecting climate data, social economic data and lake and reservoir ecological data of a target lake and reservoir and a surrounding region, and carrying out the cleaning and missing value supplementation of the data; according to the method, the social economy-climate coupling model is constructed, social economy factors such as population growth and economic development and climate change factors are cooperatively incorporated into lake and reservoir carbon income and expenditure prediction, comprehensive simulation of lake and reservoir carbon income and expenditure multi-driving factors is realized, the fitting degree of a prediction result and an actual situation is improved, and the prediction efficiency is improved. By setting multiple groups of social economy-climate scene combinations, lake and reservoir carbon income and expenditure prediction results under different development paths are output, a carbon income and expenditure accounting sub-model based on a process mechanism is embedded, and model parameters are verified and optimized in combination with historical data, so that the accuracy and reliability of lake and reservoir carbon income and expenditure prediction accounting are further improved.

A system for real-time certification and lifecycle automation of environmental credits. The system comprises: (i) a physical data collection layer equipped with on-land sensors, aerial LiDAR, satellite imagery, environmental DNA (eDNA) sampling, and community-contributed field data; (ii) an Ecological Oracle Engine, which uses an AI protocol to validate, classify, and interpret multi-source ecological data, supported by an adaptive reference library; and (iii) a smart contract protocol deployed on a blockchain network, configured to autonomously convert verified ecological data into financial instruments by issuing, pricing, transferring, freezing, and retiring tokenized environmental credits. The system performs continuous verification of each credit and includes freezing functionality based on ecological performance. It supports multiple credit types, including but not limited to carbon, biodiversity, and water credits. The system may be integrated with external modules for integrates with a Digital Twin of Nature and Web3 ecosystems, including decentralized marketplaces, ReFi platforms, and DAO mechanisms.

The invention discloses an innovation resource recommendation method and system based on an industrial chain knowledge graph, and relates to the technical field of industrial innovation decision support, and the method comprises the steps: collecting multi-source industrial chain innovation ecological data, and carrying out the preprocessing; performing entity recognition and relation extraction on the preprocessed multi-source industrial chain innovation ecological data, and constructing a static industrial chain knowledge graph; performing policy and regulation information analysis on the dynamic industry chain knowledge graph, extracting mandatory compliance terms and converting the mandatory compliance terms into a filtering rule set, filtering entity nodes and relation edges in the dynamic industry chain knowledge graph by using the filtering rule set, identifying encouraging resources, endowing policies with favorable identifiers, and forming a security resource pool. According to the method, entity nodes and relation edges in the dynamic industry chain knowledge graph are filtered to form a security resource pool, so that deep fusion of compliance screening and opportunity discovery is realized, and commercial feasibility and strategic guidance of a recommendation result are ensured.

The invention discloses a monthly meteorological and hydrological forecasting method and system based on multi-source data fusion, and relates to the technical field of meteorological and hydrological forecasting and data fusion, and the method comprises the steps: constructing a unified forecasting factor set through multi-source meteorological, hydrological and ecological data, and carrying out the feature screening; predicting meteorological elements based on a deep neural network, and correcting a prediction result by adopting a deviation correction method; and inputting the corrected meteorological data into the distributed hydrological model, and outputting a monthly runoff prediction result in combination with a data assimilation algorithm. According to the method, physical correlation screening and structure sparse optimization of heterogeneous data are realized, input variables are ensured to be scientific and explainable, space-time depth prediction and statistical distribution correction are combined, the precision and consistency of meteorological element prediction are improved, deep fusion of a physical model and statistical assimilation is realized, and the method is suitable for being applied to the field of meteorological element prediction. The prediction system has self-correction capability and long-term stability, and the scientificity and operability of monthly runoff prediction are improved.

The invention discloses an ecological restoration dynamic modeling system for a power grid project slash in a high-altitude area of the Tianshan Mountain in Xinjiang, and the system comprises an obtaining module which is used for obtaining historical multi-source heterogeneous ecological data of the power grid project slash in the high-altitude area of the Tianshan Mountain in Xinjiang Mountain, and carrying out the standardization processing of the historical multi-source heterogeneous ecological data to generate an ecological data set; the historical multi-source heterogeneous ecological data comprises climate data, soil data, hydrological data and vegetation data; the model construction module is used for constructing a climate-soil-hydrology-vegetation four-dimensional coupling ecological restoration dynamic prediction model based on the ecological data set; the dynamic simulation module is used for presetting an ecological restoration scene; inputting a preset ecological restoration scene into the four-dimensional coupling ecological restoration dynamic prediction model for dynamic simulation prediction, and when a dynamic simulation prediction result meets requirements, obtaining an ecological restoration dynamic prediction model of the power grid project slash in the high-altitude area of Tianshan Mountain in Xinjiang; and carrying out accurate dynamic simulation and prediction on the ecological system of the project slash, and formulating and adjusting a scientific full-period management and protection scheme.

The invention discloses a mine ecological restoration evaluation and analysis method, a mine ecological restoration evaluation and analysis device, a mine ecological restoration evaluation and analysis device and a computer readable storage medium, and the method comprises the steps: carrying out the basic data collection of a to-be-evaluated mine region, and obtaining an ecological restoration current situation data set; performing index system construction based on the ecological restoration current situation data set, the continuously monitored ecological data time sequence and the ecological system service function data to obtain an ecological restoration degree index set, an ecological stability index set and an ecological functional index set; environment coefficient calculation is carried out based on the obtained plateau environment characteristic data, and an environment stress coefficient is obtained; based on the ecological restoration degree index set, the ecological stability index set, the ecological functional index set and the environmental stress coefficient, evaluation model construction processing is carried out, and a comprehensive ecological restoration evaluation model is obtained; and calculating the actually measured index data based on the comprehensive ecological restoration evaluation model to obtain a comprehensive evaluation score.

The invention relates to the technical field of government affair services, in particular to an NLP entity recognition method based on semantic extension, which comprises the following steps: collecting multi-source time sequence data and generating an entrepreneurship ecological data graph through a dynamic time warping algorithm; dynamic evolution of a term library is realized by using a generative adversarial network, and a term semantic association graph is constructed in combination with a graph convolutional network; a double-path attention mechanism is deployed in a Transform encoder, and global semantics and local attention guided by terms are fused through a gating loop unit; modeling fuzzy query analysis into a Markov decision process, and optimizing a semantic extension strategy by adopting a reinforcement learning agent; multi-granularity features are extracted through a feature pyramid network, and model parameters are optimized in combination with a bidirectional long-short-term memory network and an online learning feedback loop; and finally, calculating entity service association strength by using a graph attention network, and generating an interpretable report based on a Shapley value attribution algorithm. A closed-loop learning system is formed, and the business starting policy matching accuracy is improved.

The invention relates to the technical field of territorial space ecological restoration, and discloses a territorial space improvement area ecological restoration effect evaluation system based on big data. The system continuously captures original monitoring data of ecological restoration through a multi-source ecological data acquisition engine to form a multi-source ecological data stream. And the time-space serialization processor carries out serialization recombination and standardization conversion on the data flow according to the time dimension and the space dimension to generate an ecological parameter sequence with unified time-space reference. And the ecological association network constructor analyzes the ecological elements in the sequence and constructs an ecological association network of an interaction relationship between the elements. And the repair path digger extracts a plurality of potential repair paths from the network, carries out path fusion and optimization, and generates a repair path set. And the dynamic evaluation generator calculates and outputs an ecological restoration effect evaluation index based on the path set and the real-time ecological state data. According to the system, dynamic and accurate evaluation of the ecological restoration effect is realized.

The invention discloses a hydropower station intelligent supervision method based on AI analysis, and relates to the technical field of hydropower station data analysis. The hydropower station intelligent supervision method and system based on AI analysis comprises the following steps: S1, collecting ecological environment parameter information, and establishing an ecological environment database; s2, establishing an ecological demand model based on historical data and biological rules, and executing ecological adaptation judgment; s3, ecological deviation evaluation is executed on the ecological environment data with the qualified ecological adaptation judgment result; s4, ecological environment data, an ecological adaptation judgment result and an ecological deviation evaluation result are integrated, and ecological release regulation analysis is carried out; and S5, providing a visual interface to display the change state of the ecological response adaptation value in real time. The problems that ecological perception is insufficient, regulation and control depend on fixed rules, supervision lacks intelligent response and closed-loop feedback, and dynamic adaptation cannot be achieved according to real-time ecological data and seasonal requirements are solved.

The invention relates to the technical field of environmental protection and monitoring, and discloses an arid region oasis water environment ecological safety early warning method, which comprises the following steps: step 1, constructing a sky-air-land-water three-dimensional monitoring network, the monitoring network comprises a satellite remote sensing monitoring subsystem, an unmanned aerial vehicle remote sensing monitoring subsystem, a ground sensor monitoring subsystem and an underwater monitoring subsystem, and the monitoring network is used for acquiring multi-scale and multi-element water environment ecological data; step 2, establishing an ecological safety evaluation index system of the oasis water environment in the arid region, the evaluation system including four first-level indexes of hydrology and water resource dimension, water environment quality dimension, ecological health dimension and social economy dimension, and setting a plurality of quantifiable second-level indexes under each first-level index. A combined prediction model in which a Markov chain and a long-short-term memory neural network are coupled is adopted, and a system dynamics scene simulation method is combined, so that the perspectiveness and scene adaptability of the early warning method are effectively enhanced.

The invention relates to the technical field of ecological environment monitoring, in particular to an environment assessment method and device based on carbon footprint and regional ecological data. The method comprises the following steps: acquiring carbon footprint data and regional ecological data of a target region; performing dimension alignment on the carbon footprint data and the regional ecological data to obtain an associated data set associated with a preset grid of the target region; and based on the associated data set, through at least one of a time sequence similarity analysis strategy, a spatial distribution overlapping degree analysis strategy and a causal relationship influence analysis strategy, determining an environment assessment result of the target area. Compared with the prior art, a manual evaluation mode is replaced, and the analysis efficiency is improved. And on the other hand, the carbon footprint data and the regional ecological data are aligned according to the preset grids of the region, so that the problem of non-uniform comparison dimensions and indexes is solved. And meanwhile, three analysis strategies are provided for reflecting the internal relation of the two types of data, so that the data analysis precision is improved.

The invention discloses a Yellow River basin heritage area ecological corridor environment design system based on digital twinning, belongs to the technical field of ecological corridor environment design, and aims to solve the problem that the Yellow River basin heritage area ecological corridor design is insufficient in accuracy and scientificity. The system comprises a multi-source ecological data acquisition module, an ecological data preprocessing module, a digital twin construction module, an ecological corridor planning design module and a visual output module. According to the method, terrain data, ecological element data and land utilization data are collected and preprocessed, ecological digital twin bodies of the heritage areas of the Yellow River basin are constructed, and in combination with an InVEST model, a minimum cost path algorithm, an RUSLE water and soil loss model and a CASA carbon sink model, ecological node recognition, optimal ecological corridor path planning and corridor environment design simulation are completed, so that the ecological digital twin bodies of the heritage areas of the Yellow River basin are constructed. And visually displaying the result. According to the method, accurate mapping of the ecological scene is achieved, the scientificity of ecological corridor design is improved, and support is provided for ecological corridor construction.

The invention relates to the technical field of data circulation and data security, and discloses a digital ecological data market circulation system, comprising: a data provider node deployed with a federated learning client and used for locally training a model by using original data, generating an encrypted intermediate result and managing a corresponding data asset voucher; the data demand side node is deployed with a federated learning coordination server and is used for defining a federated learning task, distributing an initial model and aggregating intermediate results from each data provider node to update a global model; the data element circulation method comprises the following steps of data capitalization and voucher generation, federal learning and process evidence storage, under-chain credible contribution degree evaluation and intelligent contract driven settlement. Compared with the prior art, the method has the advantages that the leakage risk is completely eradicated from the root of technology, a dynamic and accurate value evaluation and distribution system is achieved, a credible environment which is traceable in the whole process and transparent in rule is constructed, and the mobility and financial attributes of data assets are improved.

The invention discloses an ecological product value analysis method and system based on multi-source data fusion, and relates to the technical field of ecological product value analysis. Original ecological data are divided into two-dimensional space grid units according to a fixed scale through a space grid construction and index unit; according to the method, automatic mapping from an actual geographic coordinate system to an analysis grid unit is realized, so that multi-source data has a unified projection basis in space, the problems that multiple data source space references are inconsistent and results are difficult to transversely compare in original ecological evaluation are solved, and a strict space organization structure is provided for subsequent ecological supply modeling. In the process of mapping the ecological indexes to the grid units, the system designs a neighborhood interpolation-based mechanism for averaging and filling multiple observation points and invalid units, so that the problem of local deficiency caused by non-uniform distribution of the observation points or influence of shielding on remote sensing data in field sampling is effectively relieved, and the integrity and analysis reliability of a spatial expression matrix are improved.

The invention proposes a lake comprehensive ecological risk assessment method and system based on multi-source data fusion, and relates to the technical field of ecological risk assessment, and the method comprises the steps: carrying out the sampling of a preset assessment space range of a target lake, and obtaining the multi-source ecological data of the target lake; obtaining a water environment risk value according to historical water quality monitoring data in the multi-source information database; acquiring ecological water level demand data of the target lake according to the historical water level monitoring data, and acquiring a hydrological situation risk value of the target lake; based on remote sensing image data and historical survey monitoring data of the target lake in the multi-source information database, evaluating lakeside vegetation condition, wetland area, blue-green algae coverage area and benthonic animal monitoring data respectively to obtain a water ecology risk value; and performing weight distribution operation on the water environment risk value, the hydrological situation risk value and the water ecology risk value to obtain a comprehensive ecology risk assessment index corresponding to the target lake. The method is beneficial to the accuracy and systematicness of ecological risk assessment.

This invention discloses a method, device, medium, and product for assessing the human-river happiness index, relating to the technical field of human-river relationship evaluation. The method includes: collecting river ecological data and social water-related data of the river to be evaluated; performing standardization processing on the social water-related data according to preset human well-being evaluation rules to obtain a human well-being evaluation value; performing standardization processing on the river ecological data according to preset river-specific well-being evaluation rules to obtain a river-specific well-being evaluation value; inputting the human well-being evaluation value and the river-specific well-being evaluation value into a human-river fusion calculation model for fusion calculation to obtain a human-river happiness index matching the river to be evaluated. This achieves a synergistic consideration of human well-being and river-specific well-being, providing a scientific and quantitative decision-making basis for comprehensive water resource management and river and lake governance assessment, and avoiding evaluation bias where improving human well-being comes at the expense of river ecological health.

This invention relates to the field of wetland ecological regulation technology, specifically a method for optimizing the ecological restoration of small wetlands based on multimodal data. The method includes: collecting multimodal monitoring information such as remote sensing image sequences, time-series data of physical and chemical parameters, and ecological sample data of the target area; constructing a dynamic three-dimensional ecological field; assimilating and fusing multi-source data using a spatial grid as a basis to form a comprehensive ecological state attribute value with timestamps; utilizing an improved ecological cellular automata algorithm, combined with an ecological restoration intervention library and the attribute differences of adjacent grids, completing the synchronous evolution calculation of the ecological state of the entire grid, and generating a spatialized ecological evolution field; selecting spatially connected stable grid clusters and implementing connectivity enhancement and structural optimization; and outputting restoration layout, implementation timeline, and engineering quantity configuration content that matches site conditions. This method achieves spatiotemporal integration of multi-source heterogeneous ecological data, refines the accuracy of regional ecological evolution prediction, and enhances the ability to regulate the spatial structure of wetlands.

The present application relates to the technical field of land greening data management, in particular to a land greening system data information management method, comprising: arranging an ecological perception network composed of multiple source sensors in a target administrative region to collect vegetation physiology and soil environment data; carrying out denoising, interpolation preprocessing, standardization and coordinate system conversion in a data processing center to form a standardized basic ecological data set. Based on the data set, an attribute library containing multi-dimensional information such as tree species is constructed with a single plant or a reforestation plot as the smallest management unit, a dynamic three-dimensional green volume voxel model is generated in a geographic information system to reflect the spatial distribution of land greening resources. The model is used to calculate the carbon fixation and oxygen release potential values of different functional divisions, and a planning decision engine is called to generate suggestions for replanting or reforming in low potential value areas. The method effectively improves the data information processing efficiency, calls the planning decision engine to generate land greening implementation suggestions, and quickly and dynamically updates the land greening system data information.

This invention belongs to the field of coastal engineering and ecological restoration technology. It discloses a method for optimizing the design of beach ecological restoration trenches based on hydrodynamic simulation. The method includes: collecting beach hydrological datasets, topographic datasets, and ecological datasets, and preprocessing them. The hydrological dataset includes wave data, tidal current data, storm surge data, and sediment transport data. The topographic dataset includes shoreline slope, beach elevation, underwater topography data, and sediment source storage data. The ecological dataset includes tidal flat vegetation distribution, benthic organism density, ecologically sensitive area range, and water environment quality data. This invention, through the coupled processing of hydrological, topographic, and ecological multi-source datasets, obtains hydraulic reference values ​​and topographic adaptation values ​​for the trench, directly reflecting the regional dynamic conditions and the degree of topographic adaptation, significantly reducing the workload of manual calculation and trial and error.

The application discloses a network resilience prediction method, system and device based on digital twinning, and relates to the technical field of ecological monitoring and network resilience modeling. The network resilience prediction method, system and device based on digital twinning comprise the following steps: S1, collecting multiple types of ecological monitoring data through an ecological monitoring device, and performing standardized preprocessing on the ecological monitoring data; S2, comprehensively evaluating the modeling difficulty of each ecological data, and realizing automatic filtering and hierarchical processing of the data quality; S3, performing state synchronization evaluation on the data to be modeled, and dynamically updating the running state of the corresponding ecological entity in the digital twinning based on the state evaluation result; and S4, identifying key fragile nodes and risk paths in each ecological entity, and outputting corresponding ecological risk grades and control suggestions. The problems that in the prior art, only a small amount of observation data is used for static threshold risk judgment, and the problems that the dynamic evolution characteristics and the multi-source heterogeneity existing in the ecological system cannot be effectively coped with are solved.

The application discloses an acoustic coral reef ecosystem repairing method and related equipment, and the method comprises the following steps: matching a target sub-region from a healthy reference area; collecting water acoustic data of the target sub-region for frame processing, noise reduction and biological sound enhancement processing to obtain third water acoustic data; screening target water acoustic data from the third water acoustic data through preset spectrum characteristics; playing the target water acoustic data in a tentative repairing area, regularly acquiring real-time ecological data of the tentative repairing area; quantifying the real-time ecological data of each time node according to a time sequence to obtain a repairing effect of the tentative repairing area; when the repairing effect does not satisfy a preset condition, returning to execute the step of collecting the water acoustic data of the target sub-region until the repairing effect satisfies the preset condition. The application improves the data accuracy through the processing of acoustic data, and then optimizes the sound playing through a feedback cycle, improves the overall repairing success rate, and can be widely applied to the technical field of acoustic data processing.

The invention relates to the technical field of tree physiological monitoring and precision agriculture, in particular to a whole tree moisture utilization efficiency continuous monitoring system based on multi-type sensor integration, and adopts the technical scheme that a multi-sensor cooperative monitoring system and a multi-time-sequence data fusion algorithm are included, the multi-sensor cooperative monitoring system comprises a liquid flow monitoring unit, a trunk radial growth monitoring unit and an environment monitoring unit. A multi-time-sequence data fusion algorithm comprises time scale matching and a dynamic WUE model. By integrating various types of sensors such as trunk liquid flow, radial growth and temperature and humidity, 24-hour continuous monitoring of multi-source physiological and ecological data can be realized, and long-term operation can be realized after single-time equipment installation; according to the method, the monitoring efficiency can be remarkably improved, the manpower and material resource cost can be greatly reduced, in addition, the long-term stable data obtained through the method can reflect the dynamic law of the tree WUE, and convenient conditions are created for accurately analyzing the response of the tree WUE to the environment change.

The invention relates to the technical field of water transportation engineering, in particular to a method and system for analyzing the influence of water transportation engineering construction on the ecological integrity of a river corridor. Comprising the steps that monitoring equipment is deployed to collect hydrodynamic parameters and ecological data of a river gallery, the influence of water transportation engineering on a river gallery ecological system is evaluated based on the collected data, and the method further comprises the steps that composite hydrodynamic disturbance generated by ship navigation and ship lock dispatching is analyzed and quantified through multi-mode interference coupling; establishing a vegetative level transfer model of benthic organisms and planktons to evaluate a cascade effect of disturbance; a dynamic ecological integrity index is calculated in combination with the composite hydrodynamic disturbance and the cascade effect, and a space-time dynamic evaluation result of the ecological integrity of the river gallery is output according to the dynamic ecological integrity index; according to the method, the ecological integrity of the river gallery can be scientifically evaluated.

The invention discloses a plant reproduction ecological restoration method and system based on multi-source remote sensing and model driving. Relates to the technical field of plant reproduction ecological evaluation. The method comprises the following steps: step 1, acquiring basic ecological data and multi-source remote sensing data corresponding to a plurality of to-be-evaluated areas and preprocessing the basic ecological data and the multi-source remote sensing data; 2, constructing an evaluation model, and inputting the preprocessed basic ecological data and multi-source remote sensing data into the ecological restoration evaluation model for processing to obtain an evaluation result; 3, sorting evaluation results, and screening out an optimal plant reproduction area and a to-be-restored area according to a sorting result; and 4, formulating a plant reproduction strategy and an ecological restoration strategy according to a sorting result. Dynamic monitoring of the reproduction process is achieved through multi-source remote sensing, and the plant reproduction efficiency and the self-maintaining capacity are improved.

The present application relates to the field of data processing technology, and relates to an ecological safety pattern construction system based on a minimum cumulative resistance model, which comprises an ecological data preprocessing and source extraction module, a resistance factor extraction module, a dynamic resistance surface construction module, a cumulative resistance evaluation module, a key ecological element identification module and a safety pattern generation module, and is characterized in that: the ecological source data in a target region is subjected to feature density statistics to obtain an ecological source distribution map; the ecological source distribution map is subjected to inhibition influence analysis to obtain resistance factors; the resistance factors are subjected to spatial data superposition to obtain a dynamic resistance surface; the ecological source distribution map is subjected to spatial diffusion resistance cumulative evaluation to obtain a cumulative resistance surface; the cumulative resistance surface is subjected to key ecological element analysis to obtain ecological corridors and ecological nodes; and the ecological safety pattern of the target region is constructed according to the ecological corridors and the ecological nodes; and the present application can improve the efficiency of the ecological safety pattern construction based on the minimum cumulative resistance model.

The invention belongs to the technical field of ecological data processing. The invention provides an ecological environment admission intelligent analysis risk assessment method and system based on a large model. An integrated scheme of multi-source data acquisition and targeted preprocessing, large model driven knowledge extraction, dynamic ecological environment access knowledge graph construction, project information intelligent analysis, multi-dimensional intelligent matching, risk inference engine iterative reasoning, structured report generation and knowledge and rule base continuous optimization is adopted. A full-process automatic ecological environment admission analysis and risk assessment system is constructed, the core problems that traditional ecological environment admission assessment highly depends on manpower, is low in efficiency and is non-uniform in standard are solved, and the technical defects that an existing system lacks deep text understanding and automatic reasoning ability, knowledge updating lags behind and complex correlation analysis is difficult are overcome. Through close connection and data circulation of all links, the automation degree and operation efficiency of the assessment process are greatly improved, the consistency and objectivity of assessment standards of similar projects are ensured, and the comprehensiveness and accuracy of risk identification are improved.