293 results about "Ecological data" patented technology

The invention discloses a reservoir scheduling decision support system for multi-objective optimization, and relates to the technical field of hydraulic engineering scheduling. According to the system, comprehensive optimization of flood control, power generation and ecological targets is realized through cooperative work of the multi-source dynamic constraint analysis module, the collaborative optimization module, the scheduling module and the correction module. A dynamic constraint boundary table is generated by collecting meteorological, hydrological and ecological data in real time. And matching a multi-target coordination rule through a physical constraint double-depth network algorithm, generating a Pareto feasible solution set, and mapping the Pareto feasible solution set into a coordination strategy of flood discharge flow and power generation output. In combination with a hydraulic model, flood control and power generation weights are adjusted, an executable dispatching instruction is generated, it is ensured that the ecological flow reaches the standard, and the influence of a downstream submerged area is optimized. And correcting the dynamic constraint boundary table according to actual monitoring data, and continuously optimizing a scheduling decision. Accurate management and multi-objective optimization of reservoir dispatching are realized, and the utilization efficiency of water resources is improved.

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 data processing, and discloses a coal-based solid waste physicochemical property classification method and system based on regional ecological characteristics. The method comprises the following steps: collecting coal-based solid waste data, and establishing a resource and ecological database; analyzing association between the resource characteristics and the ecological elements, and obtaining association parameters and influence factors; performing classification modeling to form a classification model and characteristic prediction; evaluating a commercial value, and generating a value score and a market scheme; monitoring the whole life cycle, and obtaining circulation data and benefit evaluation; analyzing and deciding, and making a resource management scheme. According to the method, correlation analysis of coal-based solid waste resource characteristics and regional ecological elements is realized, a scientific classification model is constructed, and a full-life-cycle resource management scheme is provided, so that the utilization efficiency and the management level of coal-based solid waste resources are 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 an intelligent agricultural management method and system based on image processing, and the method comprises the steps: carrying out the rice-fish symbiotic region network deployment of a rice-fish symbiotic region, carrying out the multi-source data collection of rice, fish and environment based on the rice-fish symbiotic region network, obtaining the rice-fish symbiotic ecological data, carrying out the data preprocessing of the rice-fish symbiotic ecological data, and carrying out the data processing of the rice-fish symbiotic ecological data. Constructing a rice-fish data heterogeneous graph based on the rice-fish symbiotic ecological data after data preprocessing, constructing a rice-fish attention network model, importing the rice-fish data heterogeneous graph into the rice-fish attention network model, performing cross-domain feature fusion on the rice-fish symbiotic ecological data based on the rice-fish attention network model, and obtaining rice-fish associated data. And then performing rice-fish causal reasoning based on the rice-fish association data, generating a rice-fish association knowledge graph, establishing a rice-fish decision model, importing the rice-fish association knowledge graph into the rice-fish decision model, and generating a rice-fish regulation and control decision. Through the method, an accurate and efficient intelligent dynamic regulation and control decision is provided for a user.

The invention discloses a waterfowl habitat ecological data analysis method and system, a medium and electronic equipment. The waterfowl habitat ecological data analysis method comprises the steps that S1, ecological data of a waterfowl habitat is acquired and preprocessed; s2, constructing a waterfowl habitat ecological model based on the preprocessed data; s3, judging whether the ecological condition of the habitat meets a preset suitability standard or not according to an output result of the ecological model; the system comprises a multi-source data acquisition module based on a system architecture, an intelligent preprocessing module, an ecological model construction module, a habitat suitability evaluation module and a visualization and report module. Compared with the prior art, the method has the advantages of comprehensiveness (2) accuracy; and practicability.

The invention relates to the technical field of marine organism protection, in particular to a marine organism diversity protection method based on an ecological dynamic model, which comprises the following steps: collecting biological and non-biological data in a marine ecosystem, extracting DNA from a seawater sample by utilizing an environmental DNA technology, and constructing the ecological dynamic model based on the collected ecological data and eDNA analysis result. According to the method, the ecological dynamics model is established, the collected data is stored and verified through the block chain technology, and a marine biological diversity protection scheme is designed and implemented according to the ecological dynamics model prediction result and the block chain verification data. Scientific support is provided for protection decision making, protection measures and management regulations are automatically executed through the intelligent contract technology, the system is allowed to respond immediately when it is detected that key environment variables or biological indexes change, and the flexibility and timeliness of responding to environment changes are greatly improved.

The invention discloses a drainage basin ecological anomaly monitoring method based on clustering processing. The method comprises the steps of data acquisition, drainage basin ecological mapping, radius optimization, initial clustering center selection, drainage basin ecological data clustering processing and drainage basin ecological anomaly monitoring. The invention belongs to the field of ecological monitoring, and particularly relates to a clustering processing-based drainage basin ecological anomaly monitoring method, which comprises the following steps of: introducing a time weight coefficient to construct a time fusion feature vector, and improving the sensitivity to an emergency; the sampling density is automatically adapted by iteratively adjusting the radius, and the monitoring accuracy is improved; introducing a time change factor, constructing a composite index, selecting a core reference point, and objectively emphasizing the most representative core position; the sample weight is introduced to strengthen anomaly monitoring, the attention degree on different indexes is continuously adjusted through core reference point guidance, and the influence of important ecological variables is improved; the weight is updated based on the index stability, the contribution degrees of different indexes to anomaly monitoring are distinguished, and then the anomaly monitoring effect is 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 relates to the field of intelligent agricultural management and optimization, and discloses an AI vertical large model-based coffee global ecological intelligent management system, which comprises a data acquisition and fusion module, an AI vertical large model module, a state modeling and embedding module, a multi-objective optimization module, a multi-agent game control module and a control execution and feedback learning module, the invention also discloses a coffee global ecological intelligent management method based on the AI vertical large model, and the method comprises the following steps: data collection and fusion: collecting farmland meteorology, soil environment and crop growth multi-dimensional ecological data through the Internet of Things equipment, carrying out the cleaning, denoising and time sequence alignment of the collected original data, and carrying out the fusion of the data; and forming a multi-modal data stream which can be processed by the AI model. Through multi-target optimization, intelligent agent game control and a real-time feedback learning mechanism, collaborative optimization of ecology, economy and supply chain targets is realized, and the flexibility, adaptability and execution precision of the system in a complex environment are improved.

The invention provides a hydraulic engineering carbon sink value accounting method and system, and relates to the crossing field of hydraulic engineering and environmental science, and the method comprises the steps: collecting the engineering basic data and multi-dimensional ecological data of the hydraulic engineering; constructing a soil carbon sink sub-model, a water body carbon balance sub-model and a vegetation biological quantum model to form a carbon sink dynamic accounting model; and dynamically calculating the total carbon sink amount and converting the total carbon sink amount into an economic value according to the engineering basic data, the multi-dimensional ecological data and the carbon sink dynamic accounting model. The method is used for quantifying the carbon sink contribution of the water conservancy project to ecological systems such as soil, water and vegetation and converting the carbon sink contribution into economic value evaluation, so that the defects in the prior art are overcome, the carbon sink value of the water conservancy project is accurately and comprehensively calculated, and a scientific basis is provided for environmental benefit evaluation and sustainable development of the water conservancy project.

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 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.

According to the basic grassland ecological data monitoring and sampling system disclosed by the invention, in the sampling operation, cutting rings can be automatically taken out and stored through rotation of a turntable, rotation of a butt-clamping mechanical claw and lifting of a butt-clamping sliding block, so that an unmanned vehicle can carry a plurality of cutting rings for sampling work, the sampling work efficiency is improved, and the sampling time is shortened. The cutting ring inserting work can be automatically completed through cooperation of the butt-clamping mechanical claw and the pressing head, soil around the cutting ring can be automatically excavated through the hollow drill, the labor intensity of an operator is relieved, the automation level is improved, the butt-clamping mechanical claw can enter an annular groove excavated by the hollow drill, the cutting ring is taken out by clamping the side face of the cutting ring, and the cutting ring inserting efficiency is improved. The cutting ring does not need to be additionally transformed, the universality of the cutting ring is improved, and the sheath is pressed outside the cutting ring before the soil around the cutting ring is dug out, so that the situation that the accuracy of an analysis result is reduced due to soil disturbance in the cutting ring caused by displacement of the cutting ring is avoided.

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 provides an urban and rural planning surveying and mapping result generation method and system, and the method comprises the steps: obtaining ecological resource monitoring data, multiband spectrum remote sensing data and current urban and rural road network data of a target region, the spectral data comprises surface reflectance time sequence characteristics. Multi-modal environment sensing data is generated through dynamic coupling processing of vegetation distribution and reflectivity change, and then the multi-modal environment sensing data and road network density gradient information are subjected to adversarial learning matching to obtain surveying and mapping intermediate data. And based on a preset density constraint and an ecological bearing threshold value, cooperatively analyzing the intermediate data, and extracting topological constraint information fusing the road permeation path and the ecological boundary conflict. And generating an urban and rural planning surveying and mapping result through iterative spatial superposition processing. The collaborative optimization effect of ecological protection and construction development in urban and rural planning is improved.

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 provides a reservoir ecological scheduling method and system, and the method comprises the following steps: building a reservoir ecological scheduling model according to the historical and real-time hydrological data, ecological data and water supply demand data of a to-be-scheduled reservoir in consideration of upstream and downstream ecological demands and water supply demands; the reservoir ecological scheduling model is solved based on the following optimization objectives: in all water supply directions, the satisfaction degree of the water supply process is maximum; meanwhile, ecological water shortage generated by drainage of the reservoir to be dispatched is minimized; the discharged water temperature is close to the preset ecological target water temperature as much as possible, and the temperature deviation is reduced; the flushing of the scheduling scheme to the downstream river channel and the wetland beach change are minimized; the natural egg laying amount of the four major Chinese carps is promoted to be maximized; outputting a scheduling scheme; the scheduling scheme comprises the discharge flow and the ecological flow in each water supply direction in each time period. Technical support is provided for improvement and recovery of ecological environment of rivers and lakes and comprehensive scheduling management of water engineering.

The invention relates to the technical field of ecological compensation, and discloses an ecological compensation and biodiversity monitoring method based on big data, comprising the following steps: S101, acquiring ecological data of a to-be-monitored area, regularly dividing the area into N grid units, and constructing corresponding ecological data structure units; s102, based on the ecological service characteristic parameters and the biodiversity characteristic parameters, calculating ecological service value characteristics and biodiversity pressure indexes; s103, carrying out coupling processing on the ecological service value characteristics and the biodiversity pressure index, and calculating an ecological coordination coefficient and an elastic regulation coefficient; s104, calculating an ecological compensation amount through a first preset decision function; s105, calculating a cost-benefit ratio according to the ecological service value characteristics and the ecological compensation amount, and performing automatic adjustment when the cost-benefit ratio does not reach a preset performance standard threshold value; according to the invention, accurate identification, dynamic adjustment and performance closed-loop optimization of ecological compensation are realized.

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.