124 results about "Spatial database" patented technology

The invention provides a beach big data geographic space intelligent application service method based on a large model Agent, and relates to the technical field of geographic space data artificial intelligence processing and analysis. According to the method, a distributed platform comprising a parallel computing cluster, a spatial database and a large language model is constructed, and standardized storage and metadata management of multi-source remote sensing, vector and attribute data are supported. The system generates a spatio-temporal query instruction through natural language analysis, completes cross-source matching and spatial calculation, outputs an analysis result in a multi-modal form such as a map, a chart and a text, and realizes intelligent and interactive service of geographic data processing.

The invention discloses a drainage basin water quality pollution source flux identification method based on an SWAT model, computer equipment and a storage medium, and the method comprises the steps: obtaining topographic data, land utilization data, soil type data and meteorological data, and enabling the topographic data, the land utilization data, the soil type data and the meteorological data to form a drainage basin spatial database; based on the preprocessed digital elevation model, determining a water flow direction and setting a reasonable water collection area threshold value, and dividing sub-basins to construct a basin calculation unit network topology structure; obtaining pollution source data, and constructing an SWAT-CUP model according to the pollution source data; performing system calibration and verification on the watershed hydrological process by adopting an SUFI-2 algorithm in the SWAT-CUP model; carrying out system calibration and verification on the total nitrogen load of the drainage basin by adopting an SWAT-CUP model; and based on the calibrated SWAT hydrological model, the input condition of the pollution source is changed. The method can cover the whole watershed and quantify the contribution rate of different pollution sources; cost is high, operation is simple, and long-term change can be dynamically simulated.

The invention discloses an element quantitative fusion-based urban coastal zone landscape evaluation and prediction method, which comprises the following steps of delimiting a vector boundary of a target urban coastal zone based on land change data, and dividing an area covered by the vector boundary into a plurality of grid units; associating the preprocessed spatial element data to the corresponding grid units, and constructing a structured spatial database; establishing a multi-element quantitative index system, calculating a combined weight, and outputting a comprehensive evaluation score of each grid unit through weighted summation; calculating global and local Moran's I indexes based on the comprehensive evaluation score, and identifying a spatial aggregation region and an abnormal region with statistical significance; obtaining dynamic monitoring data in a coastal zone range of a target urban area, and updating the structured spatial database; and based on the updated structured spatial database, comprehensively evaluating the score and the recognition results of the spatial accumulation area and the abnormal area, and generating an evaluation and prediction result.

The invention discloses a low-altitude airspace noise assessment method based on space grids, and belongs to the technical field of low-altitude unmanned aerial vehicle flight monitoring and assessment. The objective of the invention is to solve the problem of depicting capability of a sound field state in a three-dimensional airspace. According to the method, noise sensitive objects in a low-altitude flight airspace and an air route range are identified, and a noise sensitive architectural space database with noise limit value labels is established based on set differentiated noise limit values; carrying out three-dimensional space rasterization modeling on the target evaluation area, and carrying out environment parameter assignment on each space grid unit to obtain a structured three-dimensional space grid framework of the target evaluation area; establishing a sound propagation attenuation model considering the multi-physics field coupling effect, and calculating the sound pressure intensity and the maximum allowable sound source intensity of each structured three-dimensional space grid unit; constructing a multi-dimensional data combined three-dimensional noise database; and carrying out airspace availability analysis and flight path feasibility evaluation. According to the invention, three-dimensional visualization and layering and partition quantization of low-altitude airspace noise influence are realized.

The invention discloses a dam multi-source data management method, system and device and a medium, and relates to the technical field of data processing, and the method comprises the steps: receiving monitoring data from a plurality of heterogeneous data sources, and carrying out the classification processing of the monitoring data; performing format conversion, identifier unification and data association processing on the received monitoring data; dividing the standardized data into a shared type resource set, and performing data interaction according to a preset exchange mode; dividing the data according to the type, the structural feature and the access requirement of the monitoring data, and storing different types of data in a database; and according to the data type, a differentiated backup strategy and a storage model are adopted for management. According to the method, the organization efficiency and the query performance of mass monitoring data are improved by constructing the basic database, the monitoring database, the spatial database, the multimedia database and other multi-layer structures and combining hierarchical storage, index optimization and structural standardization table design, and the multi-dimensional data service requirement is met.

The invention relates to the cross technical field of land resource management and information technology, in particular to a land management system and method based on a GIS system and big data analysis, and the system comprises a data layer, a support layer and an application layer. The data layer comprises a multi-source data collection module and a GIS spatial database; the support layer comprises a big data processing engine, a GIS analysis tool set and a machine learning modeling platform, the application layer comprises an intelligent supervision module, a planning auxiliary module and a decision support module, and the system is suitable for intelligent management and decision support of land resource investigation, planning, protection and development of a full life cycle.

This invention provides a Bayesian-based method and apparatus for spatial trade-off and synergistic optimization of ecosystem services, relating to the fields of ecology and statistics. The invention acquires an ecological spatial database of a target area, uses ArcGIS software's netting and clipping tools to generate a grid layer of a specified size for the target area, obtaining a pixel set. Based on the ecological spatial database and pixel set, the blue carbon storage, biodiversity maintenance capacity, and coastal protection capacity of the target area are calculated, representing three ecosystem services. Furthermore, the coupling coordination degree is obtained to analyze the overall coordination level among ecosystem services. A Bayesian-based ecosystem service synergy prediction model is constructed using Netica software to identify key driving factors and output the probability distribution of corresponding nodes, simulating and analyzing potential synergistic impacts under different scenarios. This invention can accurately identify and clarify the trade-off and synergistic relationships of key ecosystem services such as coastal wetlands, achieving synergistic spatial optimization of ecosystem services.

The present application relates to the technical field of road construction, and more particularly to a method and device for calculating and visualizing the number of compaction passes by a road roller, and a medium, the method comprising: constructing a motion line segment according to GPS track points of the road roller, assigning the motion line segment a WGS84 geographic coordinate system, and then converting the WGS84 geographic coordinate system into a corresponding projection coordinate system; performing buffer zone analysis on the motion line segment to obtain a rolling surface; performing intersection query on a spatial database with the rolling surface as a spatial range to obtain a surface intersecting the rolling surface and a historical rolling surface; adding one to the number of compaction passes of the intersecting surface, performing clipping calculation on a region outside the intersecting surface, and continuing to perform intersection calculation with other historical rolling surfaces until a stop clipping condition is met; saving the calculation result to the spatial database and sending the calculation result to a front end; querying, by the front end, whether a layer corresponding to a machine number of the road roller exists according to the machine number, appending layer data content if the layer exists, or creating a new layer if the layer does not exist; and rendering a map patch color according to the number of compaction passes by the front end, so that a visualized number of compaction passes is obtained.

The invention relates to the technical field of regional soil pollution health risk assessment, in particular to a regional soil pollution health risk assessment method based on POI data, and the method comprises the steps: firstly obtaining and preprocessing multi-source heterogeneous data, and constructing a POI spatial database; adopting a Kriging spatial interpolation method to generate a pollutant concentration spatial distribution grid map layer; then combining kernel density estimation and dynamic weight correction to construct a population activity intensity index surface; dynamically generating an exposure evaluation unit, and calculating the multi-path daily average exposure dose of people of different ages; and finally, quantifying the multi-path health risk, generating a risk level distribution map, and identifying the dominant POI category of the high-risk area. According to the method, deep fusion of multi-source data is realized, the association between population activity characteristics and pollution exposure is accurately depicted, the evaluation accuracy and suitability are improved, and a scientific decision basis is provided for pollution prevention and control and risk management and control.

The application provides a geological big data storage structure construction method, comprising: inputting engineering investigation data, regional geological data, groundwater data and three-dimensional geological model data generated by a data acquisition end into a geological big data center for storage; the geological big data center standardizes the engineering investigation data, the regional geological data, the groundwater data and the three-dimensional geological model data and stores them into a structured non-spatial database, a structured spatial database and an unstructured database of the geological big data center; a geological big data service center constructs standard services of the structured non-spatial data, the structured spatial data and the unstructured data and sends them to a data application end. The data big data center standardizes data management, classifies and converts data and stores the data in different areas, so that the purpose of multi-end synchronization and use is achieved.

The present application relates to a kind of Z order curve encoding and decoding method based on multi-order value lookup table, belong to spatial database index technical field.The present application includes multi-order encoding value lookup table construction stage: construct multi-order encoding value lookup table, for realizing the mapping between coordinate and encoding value;Encoding stage: each coordinate component is segmented, through iterative inquiry multi-order encoding value lookup table, the result of each segment is spliced to calculate Z order curve encoding;Multi-order decoding value lookup table construction stage: construct multi-order decoding value lookup table, for realizing the mapping between encoding value and coordinate;Decoding stage: to coordinate encoding value is segmented, through iterative inquiry multi-order decoding value lookup table and the result of each segment is spliced to calculate coordinate.The present application can convert step-by-step encoding and decoding operation into step-by-step encoding and decoding operation by introducing segmentation mechanism and other technologies, improve encoding and decoding efficiency.

The invention provides a carbon sink effect evaluation method based on a GIS spatial analysis function, and belongs to the technical field of water ecological environment protection, and the method comprises the steps: collecting multi-type data of an evaluation region, and carrying out the preprocessing of the multi-type data, and obtaining high-quality data; constructing a target layer-criterion layer-index layer three-level index system, and determining the weight of each level index; digital modeling is carried out on the evaluation area, a basic spatial database is obtained in combination with spatial processing of the evaluation area, and multi-source attributes of each unique identification point location in the evaluation area are extracted to be associated and bound with the basic spatial database to form a comprehensive database; by means of a GIS overlay analysis tool, spatial weighted overlay calculation is conducted on the spatialization data and the weight of each layer in the comprehensive database, and a comprehensive evaluation result for evaluating the regional water environment carbon sink effect is generated; and presenting the comprehensive evaluation result in a map form based on a GIS map making function. The problems that a traditional method is high in cost and low in space precision are solved.

This invention relates to the field of mineral deposit exploration technology, specifically disclosing a method for determining the extension of magmatic hydrothermal deposits using fluid inclusions. The method involves collecting mineral samples containing fluid inclusions from the target deposit and its surrounding area using a systematic grid. Physicochemical parameters are obtained through petrography, microthermometry, and isotope analysis, and a spatial database is established. Multiple initial hydrothermal centers are identified. A multi-dimensional spatial constraint field is constructed, incorporating temperature-salinity-isotope gradients, mineralization depth, and magma-water mixing ratio. Using the initial centers as seed points, a neighborhood search is performed along the gradient synthesis direction. Sub-hydrothermal centers are generated and continuously grow when preset conditions are met, until an overlap threshold is reached, at which point iteration stops. All hydrothermal centers and growth paths are integrated to construct a spatial extension model. High-potential areas are screened using a target area evaluation index, and the extension direction and potential mineralization target areas are determined by combining the mineralization depth. This significantly improves the accuracy of concealed ore body prediction and the efficiency of mineral exploration.

The application relates to a prospecting vision quantitative analysis method and device based on geosciences big data, and belongs to the technical field of mineral resources exploration. The method solves the problem that the level of a prospecting vision area is determined according to some subjective understanding in the existing prospecting prediction scheme, and the circled prospecting vision area is not accurate enough. In the method, the prospecting exploration marks are extracted from a geosciences big data spatial database, and the training area is divided into grid units according to the target deposit type, and a model unit is selected from the grid units. A prediction model is trained according to the prospecting exploration marks of the model unit, the metallogenic probability of each grid unit in the target working area and the prospecting vision area are calculated based on the prediction model, and the prospecting vision area is graded based on the metallogenic probability of each grid unit. Based on the method, the quantitative basis for the delineation of the prospecting vision area can be provided, the influence of subjective factors is avoided, and the delineation accuracy of the prospecting vision area is improved.

This invention discloses a method and system for identifying urban decline spaces, belonging to the field of urban planning technology. The method includes: S1. Acquiring population grid data and building area grid data of a target area for multiple consecutive years within a time interval; S2. Performing spatial alignment and standardization processing on the population grid data and building area grid data to form a standardized annual spatial database; S3. Removing grid units in the annual spatial database that do not possess effective urban activity characteristics to obtain a set of effective urban spatial grids; S4. Performing time series analysis on the effective urban spatial grid set to determine urban decline space grids; S5. Using a spatial clustering algorithm to cluster the determined urban decline space grids, dividing the urban decline space into continuous urban decline space and scattered urban decline space. This invention achieves automatic identification and classification of continuous and scattered urban decline spaces by analyzing the population and building area change trends over multiple consecutive years.

A power safeguard system and method belong to the technical field of new energy. The method comprises the following steps: acquiring acquisition information, wherein the acquisition information comprises electric equipment demand information and position information in a preset guarantee area, and environmental geographic information related to the area; receiving the collected information, processing the collected information into structured spatial data, and forming a structured spatial database; generating a charging pile site selection scheme based on the data in the spatial database and a genetic algorithm; generating a power transmission service path for the charging vehicle according to the charging pile site selection scheme and the weighted road network diagram; according to the real-time state and the task priority of the electric equipment, deciding to adopt a power conversion mode or a quick charging mode; and according to the charging pile site selection scheme, the power transmission service path and the decided power transmission mode, uniformly scheduling charging vehicles and resources to execute a power guarantee task. According to the method, multi-dimensional complex factors in a field environment are integrated, and charging facility site selection, power transmission path planning and service mode decision making are intelligently carried out.

The invention discloses a defect identification method and device based on multi-modal data of a chip preparation process, and the method comprises the steps: obtaining a graphite carrier image after epitaxial growth is completed, and generating a graphite carrier and wafer mapping graph; the method comprises the following steps of: performing multi-modal imaging on a wafer to be detected, acquiring a gray scale image, a reflectivity image and a photoluminescence intensity image, synchronizing according to a pixel level, respectively performing normalization processing, and calculating a physical normalization factor according to a normalization result to obtain a multi-modal image; constructing a wafer grid space database, and storing abnormal areas in the multi-modal image, the electrical test data and the graphite carrier image into the wafer grid space database; and based on the mapped multi-modal image, the electrical test data and the multi-source data of the abnormal region in the graphite carrier image, identifying the defect type according to a preset rule. The problem that in the prior art, due to the fact that data generated in the chip manufacturing process are mutually independent, the defect root cause analysis efficiency is low is solved.

The invention discloses a channel point location aggregation and frame selection query method based on an electronic map, belongs to the technical field of computer software and geographic information systems, and aims to solve the problems that in the prior art, dependency on a third-party map SDK and a spatial database plug-in is high, aggregation points are prone to visual jump, query performance is insufficient, and the service fusion degree is low. According to the method, spatial discretization mapping is achieved at a server side through fixed grid indexes, a standard structured query language is combined with a numerical processing function, point location gridding aggregation and polymorphic frame selection query are completed, and two-stage filtering, density self-adaptive adjustment, atomization permission control and an intelligent caching mechanism are matched. According to the method, a third-party special component is not needed, the aggregation stability, the query efficiency and the deployment suitability can be remarkably improved, and the method is suitable for massive point location map application scenes such as security monitoring and smart cities.

This application provides an oil and gas exploration spatial database system and a spatial data management method, relating to the field of database management technology in petroleum seismic exploration. The system includes: a data interface that receives various data requests from the oil and gas exploration business system; a unified object wrapper that encapsulates different types of spatial objects, identifies and parses the attribute information of each spatial object, converts it into a database-recognizable format, and restores it to the original spatial object type during data output; a data driver that interacts with the underlying database and executes data operation instructions; storage and retrieval of spatial data based on attribute information; a model object table structure that stores oil and gas exploration spatial data; an extended database that uses PostgreSQL as the underlying database and integrates PostGIS extensions; and a feature synchronization process that synchronizes spatial data features from the original table to a feature table, monitors changes in spatial data in the original table in real time, and updates corresponding information in the feature table in a timely manner, significantly improving the efficiency and quality of seismic exploration data synchronization and management.

The invention provides a vector geographic data efficient visualization method and system based on multi-scale optimization and containerization architecture, and belongs to the field of spatial big data visualization and cloud native GIS application. According to the method, the filling rate of the enclosing rectangles and the number of the vertexes are calculated for the original geographic element data, so that automatic classification of regular elements and irregular elements is realized; and respectively constructing two sets of multi-scale expression systems, and storing four types of multi-scale data tables in a spatial database. A containerized micro-service architecture is adopted, and dependence management and cooperative operation are automatically completed through a container arrangement tool. The vector slicing service dynamically selects a corresponding scale expression according to the scaling level. Through cooperative work of a database trigger, a monitoring service and a cache service, the system can calculate an affected slice number range and execute accurate cache deletion when element attributes are updated, and real-time and on-demand slice updating is realized. The method has the beneficial effects that the visualization performance and updating efficiency of massive vector elements are improved.

The invention belongs to the technical field of airborne electromechanical system digital twin modeling and simulation, and particularly relates to a multi-physical-domain agent model modeling and solving method and system and a medium, and the method comprises the steps: 1) carrying out the modeling of a general agent model based on a structured number table; firstly, a system mechanism model is used as a unique data source to solve and generate a model solution space database; secondly, the range of input parameters is determined, the influence of the input parameters on output parameter changes is analyzed, and all possible input combinations are formed; thirdly, all possible input combinations are submitted to the system mechanism model for calculation, response results are output, and input and output relations are clustered and sorted into a group of structured number tables; fourthly, converting the structured data table into an array in the code, and finally converting the algebraically expressed system mechanism model into a code array; 2) solving the general agent model established in the step 1); the method comprises the following steps: firstly, reading externally input to-be-solved input parameter values; secondly, determining a parameter value closest to a to-be-solved input parameter in a representation solution space array in a general agent model code; and thirdly, querying an output value of the closest parameter value, and outputting the output value as a solving result.

Embodiments of the present application relate to a carbon sequestration basic geology GIS data system platform and equipment. The platform comprises: a resource data layer configured to manage and organize regional spatial data, attribute data and resource data related to carbon sequestration; a technical support layer configured to be based on a preset platform to integrate object-oriented technology, component technology, GIS and Web GIS technology and three-dimensional modeling technology, including a spatial database for organizing the regional spatial data and a relational database for organizing the attribute data; a business application layer configured to provide a preset business according to a received user operation processing platform service function; and a user permission layer configured to manage application permissions of the preset business of a plurality of preset level users. Different users will be provided with source carbon reduction and carbon removal solution options, and scientific basis will be provided for CCUS regional large-scale deployment of geological sequestration site selection and large-scale demonstration of CCUS.

The invention relates to a soil polycyclic aromatic hydrocarbon migration flux Internet of Things-GIS spatial modeling analysis method and system, and the method comprises the steps: collecting data in real time through a Beidou satellite and LoRa dual-mode transmission technology, and outputting a standardized data set; based on the standardized data set, analyzing the PAHs source and the contribution rate thereof through a characteristic ratio method and an APCS-MLR model, determining adsorption and diffusion coefficients in combination with an indoor experiment, establishing a migration rate equation, and calculating key parameters; constructing a spatial database in an ArcGIS, fusing a physical mechanism and a random forest model based on the standardized data set and the key parameters, realizing PAHs migration simulation through Bayesian optimization, and constructing a GIS model; inputting real-time monitoring data into the GIS model, predicting spatial and temporal distribution of PAHs in a future preset time period, and outputting a migration probability graph and three-dimensional vertical migration characteristics; and based on the migration probability graph and the three-dimensional vertical migration characteristics, integrating a Nemero index, a toxic equivalent and a lifelong carcinogenic risk, and dividing risk levels.

The invention discloses a method for reducing GIS (Geographic Information System) coordinate pollution in a tool calling process of an AI (Artificial Intelligence) agent. The method comprises the following steps: generating a space reference identifier for replacing original GIS coordinate data; receiving a tool calling request which is initiated by an AI agent and contains a space reference identifier and task parameters, and performing verification and standardization processing to obtain a standardization request; retrieving corresponding geometric data from the spatial database based on a spatial reference identifier analyzed from the standardized request, performing coordinate system conversion, hierarchical abstraction and simplification on the geometric data based on task parameters, generating minimum sufficient geometric data, transmitting the minimum sufficient geometric data to a GIS tool to execute spatial operation, obtaining a spatial operation result, and storing the spatial operation result in the spatial database; and generating a result reference identifier and summary information, and returning the result reference identifier and the summary information to the AI agent. According to the method, the problems of context pollution, semantic lack and low processing efficiency caused by direct transmission of coordinate data are solved, and the reasoning accuracy and execution efficiency of the AI agent in a GIS task are improved.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for a multi-modal artificial intelligence platform for building construction. The multi-model artificial intelligence platform includes various engines that perform various computer-implemented methods. The various engines include a site selector artificial intelligence (AI) engine, a geospatial database, a site compliance analyzer AI engine, a masterplan generator AI engine, a compliance analyzer AI engine, an aesthetic generator AI engine, a schematic generator AI engine, a construction plan generator AI engine, a project timeline generator AI engine, a compliance application generator AI engine, and a financial model generator AI engine. Respective AI engines collaboratively cooperate for end-to-end AI-driven building construction design and development.

The invention discloses a karst surface collapse identification method and system based on GIS and machine learning, and relates to the technical field of geological disaster monitoring. The method comprises the specific steps that a karst surface collapse geographic space database is constructed; collapse point locations and non-collapse point locations are selected from the karst surface collapse geographic space database to form an initial sample data set, n influence factors are screened, and a sample set is generated through a geographic detector; constructing a karst surface collapse susceptibility evaluation model based on a random forest algorithm through the initial sample data set and the sample set; dividing the karst surface collapse susceptible place into a plurality of grid units, and predicting the collapse probability of each grid by using the karst surface collapse susceptibility evaluation model; and importing the probability value of collapse prediction into a GIS platform, and assigning values to grid points according to spatial positions to obtain a karst surface collapse susceptibility index layer. According to the invention, through coupling of geographical detection and machine learning, efficient prediction of karst surface collapse is realized.

This invention discloses a method, device, equipment, and medium for monitoring and early warning of agricultural food-water-energy-carbon emissions, belonging to the field of smart agriculture technology. The method includes: acquiring production big data of a target area; performing spatial registration based on the production big data and corresponding units in a preset static basic spatial database to construct a performance-environmental condition paired dataset; inputting the performance-environmental condition paired dataset into a causal inference engine to identify direct environmental factors that have a direct causal relationship with crop yield, and eliminating interference factors that only have a correlation relationship, generating a set of sensitive factors for triggering early warning; based on the set of sensitive factors, using a threshold search algorithm to automatically identify the optimal early warning threshold for each key factor affecting crop yield; and monitoring energy crops in the target area based on the set of sensitive factors and the corresponding optimal early warning threshold to obtain monitoring results. This application realizes the monitoring and early warning of land, food, energy, and carbon emissions.

The application discloses an agricultural field attraction range definition method and system based on an improved breaking point theory, relates to the technical field of agricultural fields, collects multi-source agricultural geographic spatial data and social economic data in a research area, sequentially carries out data cleaning, spatial coordinate matching and attribute standardization processing, and establishes a standardized spatial database; an agricultural field comprehensive quality evaluation index system including four dimensions of agricultural production capacity, infrastructure level, scientific and technological service capacity and ecological environment quality is constructed, the shortest time distance between any two agricultural fields is calculated, and the improved breaking point formula is used to calculate the breaking point position between adjacent agricultural fields, so that the problems of the traditional division result deviating from the regional traffic status and the boundary demarcation not conforming to the actual agricultural service radiation law are effectively solved, the finally determined agricultural field attraction range is more suitable for the practical scene of agricultural product transportation, grass-roots agricultural technology popularization and agricultural convenient service landing, and the division result is more reasonable.

The invention relates to the field of environment supervision, and particularly provides a site pollution tracing method and system based on a knowledge graph. The method comprises the following steps: when an environment abnormal event occurs at a monitoring point, determining path query information through a spatial database based on event information of the environment abnormal event; based on the path query information, performing path search in the knowledge graph, and determining all candidate paths from the potential pollution source node to the monitoring point node; based on a pre-trained scoring model, scoring each candidate path, and sorting the candidate paths according to a scoring result; based on the sorting result, selecting a preset number of candidate paths from high to low as candidate pollution paths; generating a traceability report based on the candidate pollution paths; wherein the spatial database and the knowledge graph are generated based on multi-source heterogeneous data related to environment supervision. According to the site pollution tracing method provided by the invention, pollution sources can be automatically and accurately traced in a complex environment.

The invention relates to the technical field of image processing and optical detection, in particular to an electrode particle optical image sequence acquisition method and an in-situ optical cell characterization method. When an optical imaging system is adopted to collect an optical image sequence of an electrode particle image at a to-be-detected battery pole piece of an in-situ battery module arranged at a three-dimensional displacement platform, the method comprises the following steps: establishing a scanning path point set of the three-dimensional displacement platform; driving the three-dimensional displacement platform to sequentially move to each scanning path point in the scanning path point set point by point, and constructing a target spatial database based on recognition of the target electrode particles; setting the number of cycles, performing traversal imaging on all the target electrode particles in the target spatial database, and constructing an optical image sequence of all the target electrode particles, thereby remarkably improving the image quality and the reliability of observation data.