232 results about "Ecological data" patented technology

The invention relates to a coastal wetland ecological restoration effect evaluation method and system, and belongs to the technical field of ecological monitoring and restoration. Aiming at the problems of static evaluation index lag, insufficient data fragmentation integration and lack of causal diagnosis mechanism in the prior art, multi-source time sequence ecological data are acquired by constructing a three-dimensional monitoring network consisting of satellite remote sensing, an unmanned aerial vehicle, an Internet of Things sensor and an underwater robot; a fusion data set is generated based on space-time alignment and tidal phase marking, dynamic evolution characteristics are extracted by using an LSTM network, and a spatial distribution difference chart of ecological parameters before and after restoration is generated in combination with a GAN; and furthermore, through hot area clustering and historical data association mining, a degradation driving factor is positioned, and an optimization suggestion is generated. The method breaks through the space-time limitation of a traditional evaluation method, remarkably improves the degradation diagnosis precision and the regulation and control efficiency of restoration engineering, and is suitable for various ecological restoration scenes such as estuary delta and coral reefs.

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 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 relates to the technical field of biodiversity assessment, and discloses a dynamic assessment method and system for the influence of engineering construction on biodiversity, and the method comprises the steps: obtaining a basic ecological data set, and carrying out the construction of an ecological patch graph structure and the edge building of hydrological connectivity according to the basic ecological data set, and obtaining a composite ecological graph model; performing plaque function heterogeneity aggregation and disturbance link simulation processing to obtain an ecological propagation path and a sensitivity pedigree of each node; performing spectral domain decomposition and key propagation node identification processing to obtain ecological intermediary nodes and propagation weights; performing reversible modeling and path entropy backtracking analysis processing to obtain a community reconstruction trend index and a function stability attenuation curve; and carrying out ecological response persistence analysis processing to obtain a time sequence biodiversity influence index. According to the method, the problems of static state, splitting, low coupling and the like in the prior art are solved, and the precision, timeliness and predictive capacity of ecological disturbance dynamic response evaluation are remarkably 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 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 an ocean three-dimensional space high-potential area identification layout method based on suitability evaluation, and relates to the technical field of ocean space planning management, and the method comprises the steps: collecting sea area natural, social and ecological data and historical three-dimensional right confirmation project cases, carrying out the preprocessing, and constructing a sea area three-dimensional space basic database; analyzing a historical three-dimensional right confirmation case based on a graph neural network, and constructing a sea activity-space layer relation graph; and analyzing the compatibility of different sea-using activity combinations in historical projects by using the sea-using activity-spatial layer relation graph. According to the method, a multi-dimensional suitability evaluation system and a compatibility probability matrix are constructed, a high-potential area meeting natural conditions, ecological constraints and social requirements at the same time can be recognized, plane conflicts of traditional two-dimensional planning are avoided through layered weighted stacking analysis, vertical space resource allocation is optimized through a three-dimensional layered utilization rule, and the compatibility of the high-potential area is improved. Therefore, the same sea area can be compatible with various sea-using activities, and low-efficiency or conflicting layout is reduced.

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 relates to the technical field of big data management, in particular to a collaborative optimization decision-making system for electric power-environment coupling big data, and the system comprises a drainage basin coupling module which is used for fusing multi-source ecological data obtained in real time with a preset mechanism model, and constructing a drainage basin water-energy-grain-ecological coupling model; the hierarchical decision-making module comprises a coordination layer agent representing a top layer strategy target and execution layer agents representing different benefit parties; the decision attribution analysis module is used for analyzing the collaborative scheduling strategy and acquiring a key driving factor causing a preset scheduling behavior; the anti-fact deduction optimization module is used for defining an anti-fact scheduling scene based on the key driving factors, calling a watershed water-energy-grain-ecology coupling model to perform rapid deduction, quantitatively comparing the comprehensive influence of the anti-fact scheduling scene and the collaborative scheduling strategy on water, energy, grain and ecology under a preset time scale, and performing collaborative scheduling on the water, the energy, the grain and the ecology. And optimizing the collaborative scheduling strategy.

The invention relates to an internet-of-things monitoring and early warning system for lake water quality. The internet-of-things monitoring and early warning system comprises a multi-mode intelligent sensor acquisition system, a self-adaptive wireless transmission system, a distributed data storage system, an intelligent data analysis system, a visual interaction system, an intelligent early warning system and a remote intelligent control and repair system. The invention also relates to a monitoring method using the lake water quality Internet of Things monitoring and early warning system. Traditional and innovative sensors are cooperated to comprehensively collect water quality and ecological data, the biosensor accurately detects specific pollutants, the hyperspectral imaging sensor monitors algae distribution and water color change, rich and high-precision data are provided for lake water quality monitoring, the monitoring comprehensiveness and precision are improved, and the water quality monitoring system is suitable for being popularized and applied. The lake ecological protection work is powerfully supported.

The invention relates to the technical field of GEEP accounting, in particular to an economic and ecological total production value accounting system based on multi-source data fusion, which comprises a multi-source data collection and management module, a GEEP accounting module and an authority management module. In the aspect of data processing, the GEEP accounting platform integrates multi-source real-time data such as remote sensing data and statistical data, the response speed and the analysis capability of economic and ecological data change are greatly improved by utilizing distribution, parallel and cooperative computing technologies, and in the accounting analysis process, the data processing flow is optimized to realize quick positioning of a key change area, so that the calculation efficiency is improved. And the economic and ecological contribution of each region is dynamically evaluated, so that the resource allocation is more accurate, and in the aspect of system management, an intelligent authority management module based on role access control ensures the data security and improves the reliability of the accounting process, so that the GEEP accounting is integrally promoted to be converted from static lag to dynamic efficient business, and the safety of the system is improved. And more timely and accurate data support is provided for continuous ecological economic decision making.

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 intelligent ecological system service partition management and control system, and relates to the technical field of ecological system management and control, and the system comprises a data collection module which is responsible for collecting and sorting ecological data from various sources, and providing basic original data for system partition management and control; the data processing module is responsible for processing the collected original data, and the ecological partition module is used for dividing ecological management and control partitions according to service characteristics of an ecological system and defining a space management and control boundary; the ecological evaluation module is used for carrying out quantitative evaluation on the ecological system condition of the whole region based on the characteristic condition of the partition; the strategy generation module generates differentiated management and control measures and treatment strategies of the ecological function areas based on the ecological zoning result and the ecological evaluation conclusion; and the data storage module is responsible for efficiently storing massive heterogeneous data and ensuring the traceability of the data of the whole system. According to the invention, accurate partitioning of the ecological system can be realized, and a personalized management and control strategy is generated according to the ecological condition in the partition.

The invention discloses a sand landscape pattern optimization method based on ecological water demand inside and outside rivers and lakes, and relates to the technical field of ecological restoration and water resource management, and the method comprises the following steps: 1, collecting a remote sensing image, field ecological data and hydro meteorological data, and carrying out the preprocessing to obtain ecological hydrological element data; 2, calculating the ecological water demand of the semi-arid sand landscape according to the ecological hydrological element data; 3, constructing a nonlinear-multi-target sand landscape pattern optimization model according to the ecological water demand and the ecological hydrological element data; 4, solving the nonlinear-multi-target sand landscape pattern optimization model by adopting a multi-target optimization algorithm according to the condition constraint to obtain a parameter optimal solution; and 5, constructing a sand landscape pattern strategy according to the parameter optimal solution. By comprehensively optimizing water and sand resource allocation and ecological water demand inside and outside rivers and lakes and cooperatively deploying all landscape elements, sustainable utilization of sand landscape water resources and improvement of an ecological hydrological function are achieved.

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 relates to the technical field of garden landscape design, in particular to a garden landscape design method based on a virtual reality technology, which comprises the following steps: step 1, multi-source data acquisition and three-dimensional modeling: adopting a laser radar to scan a design site to obtain high-precision terrain point cloud data and generate a three-dimensional terrain model, the method comprises the following steps: performing three-dimensional scanning on garden plants to construct a plant resource library containing plant morphological parameters, growth characteristics and a growth cycle algorithm, acquiring ecological data of field illumination intensity, soil pH value, annual precipitation and wind direction and wind speed through a sensor array, and establishing a field ecological parameter database; and 2, constructing an immersive virtual scene: importing the terrain model into a VR engine, and automatically generating a basic landform based on an ecological parameter database, and through growth simulation and space-time rendering, realizing full-cycle presentation from short-term landscape to long-term ecological change, improving the customer scheme recognition degree to more than 90%, and reducing the modification rate by 60%.

The invention discloses an urban garbage treatment station site selection method and device, electronic equipment and a storage medium, and relates to the technical field of site selection. The method comprises the following steps: dividing a target city area into a plurality of grid areas; acquiring signaling data of each grid region, and estimating population distribution characteristic data; acquiring historical garbage clearance data and commercial interest point data, and processing to obtain garbage prediction data; obtaining road data, establishing a topological road network model, and performing traffic characteristic evaluation on the topological road network model to obtain traffic characteristic data; acquiring ecological data, and acquiring service coverage data of each garbage disposal station; based on the obtained data, obtaining a multi-dimensional evaluation result, and determining a plurality of preliminary site selection of the garbage disposal station; and determining a preset number of addresses from the plurality of preliminary addresses as a final address of the garbage disposal station of the target city. By implementing the technical scheme provided by the invention, the accuracy of site selection of the urban garbage treatment station can be improved.

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, which relates to the intelligent agriculture field, discloses an artificial intelligence-driven multi-nutrition-level comprehensive culture and proliferation system comprising an ecological sensing module, an ecological topology module, a decision control module, an execution control module and a risk response module. Wherein the ecological sensing module is used for collecting multi-dimensional ecological parameters in a breeding environment and constructing an ecological data set; the ecological topology module is used for constructing a weighted directed graph topology structure; the decision control module is used for constructing an ecological regulation and control model based on the competitive reward function to generate a dynamic regulation strategy for ecological regulation and control; the execution control module is used for controlling cultivation related execution equipment; and the risk response module is used for recording the current operation state parameters and activating the standby biological reaction chain structure to reconstruct the ecological regulation and control model, and the system is supported by national key research and development plan subsidization (2024YFD2401801).

The invention discloses a stable and suitable coordination method for watershed mountain water, forest field, lake grass and sand, and relates to the technical field of ecological environment protection and governance, and the method comprises the following steps: 1, collecting watershed ecological background data, and constructing an ecological hydrological database; 2, constructing a landscape pattern-ecological system coupling model according to the ecological hydrological database, and carrying out ecological function partitioning; 3, constructing a comprehensive coupling relation framework in the drainage basin according to the ecological function partition, and identifying a key ecological hydrological problem; 4, constructing a nonlinear-multi-target dynamic planning model according to the key ecological hydrological problem; 5, solving the nonlinear-multi-target dynamic programming model to obtain a parameter optimal solution; and 6, constructing a coordination strategy according to the optimal solution of the parameters. The method comprises the following steps: establishing a drainage basin ecosystem collaborative regulation model by taking collaborative optimization of a drainage basin ecological hydrological function as a core target, determining optimal parameters by optimizing the model, and formulating a coordination strategy.

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 relates to the technical field of ecological data fusion, in particular to an atmospheric safety pattern construction method and system with cooperation of pollution reduction and carbon reduction, and the method comprises the steps: recognizing an ecological source land of a target region based on multi-source remote sensing data, and grading the ecological source land; constructing a comprehensive ventilation resistance surface based on the surface roughness, the vegetation roughness and the water area roughness of the target area, and dividing resistance grades of the comprehensive ventilation resistance surface based on the spatial game characteristics of the ecological land and the construction land in the target area; a ventilation corridor and an ecological corridor are extracted, and the width of the ventilation corridor and the width of the ecological corridor are set; and based on the ecological source land grading result, integrating the ventilation resistance surface resistance grading result, the path and width of the ventilation corridor and the path and width of the ecological corridor to carry out overlay analysis, and constructing a safety pattern result of the target area. According to the method, the defects of the existing ecological security pattern content are overcome, and the construction precision of the atmospheric security pattern is improved.

The invention discloses a method for analyzing sensitivity of terrestrial ecosystem carbon cycle to drought, and relates to the field of carbon neutralizer.The method comprises the steps that terrestrial ecological data are collected and preprocessed, a standardized soil humidity index is calculated, and a drought event is recognized through a three-dimensional clustering method; drought characteristics are extracted, the correlation degree of the standardized land ecological data and the drought characteristics is calculated by using a Pearson's correlation method, and importance degree sorting is performed on the standardized land ecological data in combination with an interpretable machine learning method to obtain main climate driving factors; analyzing the influence degree of the drought characteristics on the change trend of the main climate driving factors by using a multi-source linear regression method; and analyzing the influence degree of the main climate-driven factors on the carbon cycle during the drought period by using the partial correlation coefficient between the main climate-driven factors and the carbon flux. The invention discloses the change rule of the land carbon sink driven by different climates.

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.