Geographic information collection method and system based on multi-source data fusion

Abstract

The invention relates to a geographic information collection method and system based on multi-source data fusion. The system comprises an automatic data capture module, a multi-source data integration module, an environment state evaluation monitoring module, a human activity influence analysis module and a management strategy generation module. According to the scheme, the real-time dynamic evaluation capability is provided, so that the evaluation of the environment state and the analysis of the influence of human activities can quickly respond to the environment change, and the timeliness of decision making is improved. The human activity data and the natural environment state evaluation result are combined for cross analysis, positive and negative influences can be recognized, it is ensured that multiple influence factors of human activities are fully considered in an environment management decision, and therefore the comprehensiveness and scientificity of the decision are improved. Based on positive and negative impact analysis results, the scheme can generate specific environment management suggestions and cooperative treatment measures for all provinces and cities.

Description

Technical Field

[0001] The present invention relates to the field of natural environment analysis, and in particular to a geographic information collection method and system based on multi-source data fusion. Background Art

[0002] The field of natural environment analysis involves a variety of technologies and tools aimed at gaining a deeper understanding and assessment of the state of the natural environment and its changes. Remote sensing technology is an important part of this field, which uses platforms such as satellites, drones and aircraft to obtain images and data on the earth's surface to monitor large-scale environmental changes, such as forest cover, water area and urban expansion. In addition, geographic information systems (GIS) provide spatial data management and analysis capabilities, allowing researchers to visualize and interpret environmental data and conduct more sophisticated spatial analysis, such as ecosystem service assessment and land use planning.

[0003] The impact of human activities on the environment involves multiple fields, such as industry, agriculture, urban development, etc. The relevant data are usually collected by different institutions and organizations, including air quality, water quality, soil pollution, noise pollution, etc. This diversity leads to inconsistent data and is difficult to systematically integrate and analyze.

[0004] Relying solely on the assessment of the state of the natural environment often ignores the multiple impacts of human activities. For example, water pollution may be caused by multiple factors such as industrial emissions and agricultural runoff, and a single water quality monitoring cannot reveal these complex cause-and-effect relationships.

[0005] The existing assessment of the state of the natural environment is not sufficient to support comprehensive decision-making. The main problem is that there is a lack of comprehensive consideration of influencing factors. Environmental management decisions need to take into account multiple factors, including the natural environment, human activities, and social economy. Relying solely on the assessment of the state of the natural environment cannot fully understand the impact of these factors on the environment, resulting in incomplete decision-making. Summary of the invention

[0006] The present invention aims at solving the technical problems existing in the prior art and provides a geographic information collection method based on multi-source data fusion.

[0007] The technical solution of the present invention to solve the above technical problems is as follows: a method for collecting geographic information based on multi-source data fusion, the method comprising: Automatically capture real-time data from multiple sources and store the collected data in a centralized database; Integrate data from different sources to form a multi-source data set, determine whether the integrated data of all provinces and cities can be accessed in real time, and integrate the multi-source data sets of all provinces and cities again to generate a unified geographic information database; Establish a status assessment model to assess the status of the natural environment based on data in the geographic information database; At the same time, a spatial analysis model is established to extract human activity data from multi-source real-time data, and combined with the current natural environment status assessment results, the positive and negative impacts of human activities on the environment are analyzed; Based on the results of the positive and negative impact analysis, environmental management recommendations for each province and city are generated, as well as collaborative governance measures between provinces and cities.

[0008] As a further solution of the present invention, the automatic capture of multi-source real-time data and storage of the collected data in a centralized database specifically includes: Evaluate the update frequency and data quality of each data source and select the data source for collection; Set the crawling frequency and crawling time window to automatically crawl data from the data source, including: crawling meteorological data, environmental monitoring data and satellite remote sensing data of various provinces and cities; Obtain human activity data, including: Analyze remote sensing satellite image data to obtain the urbanization rate of the current region, the change data of urban construction land, and the spatial data of urban expansion; Obtain industrial emission monitoring data, including emissions of major pollutants; Obtain data on crop area, fertilizer application, and irrigation water use, and use remote sensing imagery to analyze changes in agricultural land use.

[0009] As a further solution of the present invention, the data from different sources are integrated to form a multi-source data set, and it is determined whether the integrated data of all provinces and cities can be accessed in real time, and the multi-source data sets of all provinces and cities are integrated again to generate a unified geographic information database, which specifically includes: Identify data formats from different data sources and convert data from different sources into a unified data structure and format, maintaining consistency in field names and data types; Merge the converted data to form a multi-source data set, and relate the data of each province and city to each other through common fields; Establish a unified geographic information database structure, store the integrated multi-source data sets in a unified geographic information database, and create indexes for the data in the database.

[0010] As a further solution of the present invention, the converted data are merged to form a multi-source data set, and the data of each province and city are associated with each other through a common field, specifically including: Identify common attributes and fields in different data sources, and uniformly name the same fields in different data sources; Add a timestamp field to the data to compare and correlate the data of each province and city based on time; Use geocoding services to convert addresses into longitude and latitude, standardize geographic location information, and use boundary data in geographic information systems to ensure that data for provinces and cities can be correctly matched at the regional level; Calculate the similarity of data to determine the relevance of records in different data sources, and merge data from different sources based on this; Design relational tables in a unified database and establish relationships between data.

[0011] As a further solution of the present invention, the establishment of a state assessment model to assess the state of the natural environment based on data in a geographic information database specifically includes: Identify the indicators of the state of the natural environment to be assessed and determine the geographical and temporal scope of the assessment; Extract data related to the evaluation indicators from the unified geographic information database; Selecting a feature vector and a target vector, wherein the feature vector represents a multi-source data set in a centralized database, and the target vector represents a natural environment state indicator; Construct a status assessment model, use the established status assessment model in combination with the spatial analysis model, extract human activity data and combine it with the natural environment status assessment results to analyze the positive and negative impacts.

[0012] As a further solution of the present invention, the construction of the state assessment model specifically includes: Construct a state assessment model, the model formula is: ; in, The output is the prediction result of the model, that is, the assessment result of the natural environment status; represents the input feature vector, which contains the features extracted from the geographic information database; is a weight vector, which indicates the influence of each feature on the evaluation result. Used to transform the weight vector Convert to a row vector; is a mapping function used to map features to a high-dimensional space. It is the dot product of the weight vector and the feature vector, which represents the weighted sum of the input features of the model; In the formula, the weight vector It is expressed as: Climate characteristic weights, reflecting the impact of climate change on the state of the natural environment; Land use characteristic weights, which represent the impact of land use changes on the environment; Environmental monitoring feature weights represent the reflection of existing environmental indicators on the natural state; Use the integrated multi-source dataset to train the model and optimize the weight vector and bias term: ; in, represents the true label.

[0013] As a further solution of the present invention, the spatial analysis model is simultaneously established to extract human activity data from multi-source real-time data, and combined with the current natural environment status assessment results, the positive and negative impacts of human activities on the environment are analyzed, specifically including: Extract relevant human activity data from centralized databases; Use geographic information systems to construct spatial distribution models of human activities; The results of the natural environment status assessment model are combined with human activity data for cross-analysis to determine the relationship between human activities and environmental status and identify positive and negative impacts.

[0014] As a further solution of the present invention, the use of a geographic information system to construct a spatial distribution model of human activities specifically includes: Construct a spatial distribution model of human activities: ; in, is the vector of environmental status assessment results, is the independent variable matrix, The matrix representing the interaction terms and polynomial terms, is the regression coefficient vector, which indicates the influence of each basic feature on the environmental status assessment result. is the regression coefficient vector of interaction terms and polynomial terms, representing the impact of complex relationships on environmental states, is the error term; Based on the collected human activity data, construct the independent variable matrix ; ; in, Indicates traffic flow, represents industrial emissions, represents population density; Compute interaction terms and polynomial terms and construct matrices : ; ; ; According to the environmental status assessment results, construct the dependent variable vector It is expressed as: ; in, Indicates Status assessment results of samples; Will and Combine into a new matrix : .

[0015] As a further solution of the present invention, the identifying of positive and negative impacts specifically includes: Calculate regression coefficients ; in, Included and , for The transpose of Through the regression coefficient The value of analyzes the positive and negative impact of various factors on the environmental state, specifically: like , it means that the corresponding independent variable has a positive impact on the environmental state, that is, increasing the independent variable will lead to an upward trend in the environmental state index; like , it means that the corresponding independent variable has a negative impact on the environmental state, that is, increasing the independent variable will lead to a downward trend in the environmental state index; Calculating Statistics , express The standard error of according to Statistics and Degrees of Freedom ,use Distribution table lookup corresponding value; like If the coefficient is less than 0.05, it is considered that the coefficient is statistically significant, indicating that the independent variable has a significant impact on the environmental state; like If the coefficient is less than 0.05, it is considered that the coefficient is not statistically significant, indicating that the influence of the independent variable on the environmental state is not obvious.

[0016] Another object of the present invention is to provide a geographic information collection system based on multi-source data fusion, the system comprising: The data automatic capture module is used to automatically capture real-time data from multiple sources and store the collected data in a centralized database; The multi-source data integration module is used to integrate data from different sources to form a multi-source data set, determine whether the integrated data of all provinces and cities can be accessed in real time, and integrate the multi-source data sets of all provinces and cities again to generate a unified geographic information database; Environmental status assessment and monitoring module, used to establish a status assessment model and conduct status assessment of the natural environment based on data in the geographic information database; The human activity impact analysis module is used to simultaneously establish a spatial analysis model, extract human activity data from multi-source real-time data, and analyze the positive and negative impacts of human activities on the environment in combination with the current natural environment status assessment results; The management strategy generation module is used to generate environmental management recommendations for provinces and cities, as well as collaborative governance measures between provinces and cities based on the results of positive and negative impact analysis.

[0017] The beneficial effects of the present invention are: The solution integrates multiple data sources such as meteorology, environmental monitoring, and satellite remote sensing, covering multiple influencing factors of the natural environment and human activities, thus achieving comprehensiveness and multi-dimensionality of data. This method can not only update data in real time and dynamically, but also ensure the consistency of data in terms of region and time, making environmental status assessment and analysis of human activity impact more accurate and timely.

[0018] By establishing a comprehensive state assessment model and spatial analysis model, the program can reveal complex causal relationships. For example, by analyzing industrial emission monitoring data, agricultural land change data, etc., the various sources of water pollution can be determined. This comprehensive causal relationship analysis provides a scientific basis for environmental management decisions and can effectively avoid the limitations of traditional single data source analysis.

[0019] In addition, the solution also provides real-time dynamic assessment capabilities, so that the assessment of environmental status and the analysis of the impact of human activities can quickly respond to environmental changes and improve the timeliness of decision-making. Cross-analysis of human activity data and natural environmental status assessment results can identify positive and negative impacts and ensure that the multiple influencing factors of human activities are fully considered in environmental management decisions, thereby improving the comprehensiveness and scientificity of decisions.

[0020] Based on the results of the positive and negative impact analysis, the plan can generate specific environmental management recommendations and collaborative governance measures for provinces and cities. This will not only help to formulate more targeted and operational environmental protection strategies, but also enable collaborative governance among different regions and improve the overall environmental management effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A flowchart of a geographic information collection method based on multi-source data fusion provided by the present invention; Figure 2 A flowchart of the present invention for automatically capturing multi-source real-time data and storing the collected data in a centralized database; Figure 3 A flowchart for determining whether the integrated data of all provinces and cities can be accessed in real time and integrating the multi-source data sets of all provinces and cities again provided by the present invention; Figure 4 A flow chart of establishing a state assessment model provided by the present invention to assess the state of the natural environment based on data in a geographic information database; Figure 5 A flowchart for establishing a spatial analysis model provided by the present invention, extracting human activity data from multi-source real-time data, and analyzing the positive and negative impacts of human activities on the environment in combination with the current natural environment status assessment results; Figure 6 This is a structural block diagram of the geographic information collection system based on multi-source data fusion provided by the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0023] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, "plurality" means two or more, unless otherwise clearly and specifically defined.

[0024] In the description of the present application, the term "for example" is used to mean "used as an example, illustration or description". Any embodiment described as "for example" in the present application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid unnecessary details to obscure the description of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present application.

[0025] Figure 1 The flowchart of the method for collecting geographic information based on multi-source data fusion provided by the present invention is as follows: Figure 1 As shown, the method includes: S100, automatically captures real-time data from multiple sources and stores the collected data in a centralized database; In this step, the specific implementation of real-time data capture includes multiple aspects. First, the system automatically captures meteorological data of various provinces and cities, such as temperature, humidity, and rainfall, from the Meteorological Bureau or related meteorological service APIs. Secondly, environmental data such as air quality and water quality monitoring are obtained from the environmental monitoring network to ensure the real-time and accuracy of the data. At the same time, the system obtains remote sensing image data through satellite remote sensing technology and performs preprocessing for subsequent analysis.

[0026] The acquisition of data on human activities is also crucial. The system analyzes remote sensing satellite images to extract the urbanization rate and change data of urban construction land in the current region, and obtains the distribution of buildings and changes in urban boundaries. In addition, the system automatically obtains industrial emission monitoring data of major pollutants (such as sulfur dioxide, nitrogen oxides, etc.) from the environmental protection department, including real-time monitoring data of industrial enterprises. At the same time, the system obtains data on crop planting area, fertilization and irrigation water through the agricultural department, and uses remote sensing images to analyze changes in agricultural land. This series of data acquisition processes ensures the comprehensiveness and diversity of multi-source data.

[0027] Finally, the system will initially integrate the captured data to ensure that the data format is consistent and store it in a centralized database. The management mechanism setting of the database helps to ensure efficient access and security of the data. The significant advantage of this process is that the system can obtain the latest environmental and human activity information in a timely manner with strong real-time characteristics, thereby providing support for decision-making. At the same time, the integration of multiple sources such as meteorological, environmental monitoring and satellite remote sensing data improves the comprehensiveness of the data and fully reflects the status of the natural environment and human activities. In addition, through strict evaluation of the data source, the collected data is ensured to have high accuracy and reliability, providing a solid foundation for subsequent analysis.

[0028] The highly automated capture and real-time update mechanism significantly reduces the need for manual intervention, improves work efficiency, and reduces human errors. At the same time, systematic data integration facilitates subsequent status assessment and spatial analysis, and helps to deeply understand the impact of human activities on the environment. Based on real-time data and high-quality analysis, the system can formulate scientific environmental management recommendations, thereby improving the pertinence and effectiveness of policies.

[0029] like Figure 2 As shown, the automatic capture of multi-source real-time data and storage of the collected data in a centralized database specifically includes: S110, evaluating the update frequency and data quality of each data source, and selecting a data source for collection; S120, setting a capture frequency and a capture time window, and automatically capturing data from a data source, including: capturing meteorological data, environmental monitoring data, and satellite remote sensing data of various provinces and cities; S130, obtaining human activity data, including: Analyze remote sensing satellite image data to obtain the urbanization rate of the current region, the change data of urban construction land, and the spatial data of urban expansion; Obtain industrial emission monitoring data, including emissions of major pollutants; Obtain data on crop area, fertilizer application, and irrigation water use, and use remote sensing imagery to analyze changes in agricultural land use.

[0030] Also includes: Urbanization data: Data sources: Obtain data on urbanization rate and changes in urban construction land from national or local statistical bureaus, and use remote sensing technology to obtain spatial data on urban expansion (such as building distribution and changes in urban boundaries).

[0031] Collection method: Automatically capture data from relevant government agencies and statistical yearbooks through the API interface, and analyze them using remote sensing satellite images.

[0032] Industrial emissions data: Data source: Industrial emission monitoring data obtained from environmental protection departments, including emissions of major pollutants (such as sulfur dioxide, nitrogen oxides, and volatile organic compounds).

[0033] Collection method: Automatically capture data from environmental monitoring networks and industrial enterprise reports to ensure real-time data updates.

[0034] Agricultural land change data: Data source: Obtain relevant data such as crop planting area, fertilizer application and irrigation water through the agricultural department, and use remote sensing images to analyze changes in agricultural land.

[0035] Collection method: Use geographic information system (GIS) technology and remote sensing data to automatically extract relevant agricultural data.

[0036] S200, integrating data from different sources to form a multi-source data set, determining whether the integrated data of all provinces and cities can be accessed in real time, and integrating the multi-source data sets of all provinces and cities again to generate a unified geographic information database; Data from different sources may have differences in structure and format. In order to achieve effective data integration, this step converts the data from each data source into a unified data structure and format to ensure the consistency of field names and data types. This process lays the foundation for subsequent data merging and improves data consistency and availability.

[0037] The converted data will be merged to form a multi-source data set. In this process, the system associates the data of various provinces and cities through common fields. To achieve this goal, the system identifies common attributes and fields in different data sources and uniformly names the same fields in different data sources. At the same time, the system adds a timestamp field to the data so that the data of various provinces and cities can be compared and associated based on time. The introduction of this time dimension makes data analysis more accurate and helps to reveal dynamic changes.

[0038] The application of geocoding services is also an important part of this stage. By converting addresses into longitude and latitude, the system can standardize geographic location information and use boundary data in the geographic information system to ensure that data of provinces and cities can be correctly matched at the regional level. This process not only enhances the geographic relevance of the data, but also improves the accuracy of subsequent analysis.

[0039] During the data integration process, the system also performs similarity calculations to determine the relevance of records in different data sources. Based on this, the system can effectively merge data from different sources to form a more comprehensive and consistent data set. In addition, in the unified database, the system designs a relationship table to establish the relationship between data for subsequent query and analysis.

[0040] Ultimately, the goal of this phase is to establish a unified geographic information database structure, store the integrated multi-source data sets in this database, and index the data in the database. This indexing mechanism not only improves the efficiency of data retrieval, but also facilitates subsequent analysis and application.

[0041] By standardizing and integrating data from different sources, this step can generate a more complete and consistent multi-source data set. This data integration not only improves the availability of data, but also provides a solid foundation for subsequent status assessment and spatial analysis. Since the consistency and accuracy of the data are guaranteed, the subsequent analysis results will be more reliable and decision-making supportive. In addition, the system's standardized processing of time dimensions and geographic information further enhances the dynamics and regional relevance of the data, which improves the pertinence and effectiveness of policy formulation and environmental management recommendations.

[0042] like Figure 3As shown, the data from different sources are integrated to form a multi-source data set, and it is determined whether the integrated data of all provinces and cities can be accessed in real time, and the multi-source data sets of all provinces and cities are integrated again to generate a unified geographic information database, which specifically includes: S210, identifying data formats of different data sources, and converting data from different sources into a unified data structure and format, maintaining consistency of field names and data types; S220, merging the converted data to form a multi-source data set, and associating the data of each province and city with each other through a common field; S230, establishing a unified geographic information database structure, storing the integrated multi-source data sets in the unified geographic information database, and establishing an index for the data in the database.

[0043] In this embodiment, the converted data are merged to form a multi-source data set, and the data of each province and city are associated with each other through a common field, specifically including: Identify common attributes and fields in different data sources, and uniformly name the same fields in different data sources; Add a timestamp field to the data to compare and correlate the data of each province and city based on time; Use geocoding services to convert addresses into longitude and latitude, standardize geographic location information, and use boundary data in geographic information systems to ensure that data for provinces and cities can be correctly matched at the regional level; Calculate the similarity of data to determine the relevance of records in different data sources, and merge data from different sources based on this; Design relational tables in a unified database and establish relationships between data.

[0044] S300, establishing a status assessment model to assess the status of the natural environment based on data in the geographic information database; In this step, the natural environment status indicators to be evaluated will be determined, and the geographical scope and time range of the evaluation will be clarified. This process lays the foundation for subsequent model construction and data extraction. The determined environmental status indicators may include water quality, air quality, land use change, ecosystem health, etc., which can be selected according to specific needs.

[0045] Next, the system will extract data related to the evaluation indicators from the unified geographic information database. These data provide the necessary information basis for the subsequent status assessment model, ensuring that the model can accurately reflect the current status of the natural environment. The selection of feature vectors and target vectors is a key step in model construction. The feature vector represents a multi-source data set in a centralized database, which contains various factors related to the status of the natural environment; while the target vector represents the natural environment status indicator that is expected to be evaluated. This construction enables the model to perform comprehensive analysis based on multivariate data.

[0046] In the specific model construction process, the system adopts a state assessment model based on weighted sum. The setting of weight vector includes multiple dimensions: climate feature weight reflects the impact of climate change on the state of natural environment, land use feature weight represents the impact of land use change on the environment, human activity feature weight reflects the positive and negative impact of human activities on the environment, and environmental monitoring feature weight reflects the reflection of existing environmental indicators on the natural state. By comprehensively considering these features, the model can provide a more comprehensive environmental status assessment.

[0047] After the model is built, the system uses the integrated multi-source data set to train the model and optimize the weight vector and bias term to improve the accuracy of the prediction. During the training process, the real label is used as the target to help the system continuously adjust and optimize the model parameters so that the output results are closer to the actual situation.

[0048] The state assessment model constructed by integrating multi-source data can provide a comprehensive and accurate assessment of the state of the natural environment. First, the model can effectively integrate data from different sources to enhance the reliability of the assessment results. Second, based on the selected features and target vectors, the model can quantify the impact of various factors on the natural environment and provide a scientific basis for decision-making. In addition, by introducing the concepts of time and geographic scope, the model can capture the dynamic characteristics of environmental changes and reflect potential environmental problems in a timely manner. This dynamic monitoring and assessment capability has significantly improved the pertinence and effectiveness of policy formulation and environmental management measures.

[0049] like Figure 4 As shown, the establishment of a state assessment model to assess the state of the natural environment based on data in a geographic information database specifically includes: S310, determining the natural environment status indicators to be evaluated, and determining the geographical scope and time scope of the evaluation; S320, extracting data related to the evaluation indicators from the unified geographic information database; S330, selecting a feature vector and a target vector, wherein the feature vector represents a multi-source data set in a centralized database, and the target vector represents a natural environment state indicator; S340, construct a status assessment model, use the established status assessment model in combination with the spatial analysis model, extract human activity data and combine it with the natural environment status assessment results to analyze the positive and negative impacts.

[0050] In this embodiment, the construction of the state assessment model specifically includes: Construct a state assessment model, the model formula is: ; in, The output is the prediction result of the model, that is, the assessment result of the natural environment status; represents the input feature vector, which contains the features extracted from the geographic information database; is a weight vector, which indicates the influence of each feature on the evaluation result. Used to transform the weight vector Convert to a row vector; is a mapping function used to map features to a high-dimensional space. It is the dot product of the weight vector and the feature vector, which represents the weighted sum of the input features of the model; In the formula, the weight vector It is expressed as: Climate characteristic weights, reflecting the impact of climate change on the state of the natural environment; Land use characteristic weights, which represent the impact of land use changes on the environment; Environmental monitoring feature weights represent the reflection of existing environmental indicators on the natural state; Use the integrated multi-source dataset to train the model and optimize the weight vector and bias term: ; in, represents the true label.

[0051] S400, at the same time, establishes a spatial analysis model to extract human activity data from multi-source real-time data, and analyzes the positive and negative impacts of human activities on the environment in combination with the current natural environment status assessment results; In this step, relevant human activity data are extracted from centralized databases, which may include traffic flow, industrial emissions, population density, etc. This information provides a basis for understanding how human activities affect the state of the environment.

[0052] Next, using a geographic information system (GIS), the system constructs a spatial distribution model of human activities. This process first requires the construction of an independent variable matrix, which contains various types of data related to human activities. For example, characteristics such as traffic flow, industrial emissions, and population density will be modeled as independent variables. On this basis, the system will calculate interaction terms and polynomial terms to build a matrix containing these complex relationships. This construction enables the model to capture the diversity and complexity of the interaction between human activities and environmental states.

[0053] When establishing the dependent variable vector, the system takes the natural environment status assessment results as output. Specifically, the dependent variable vector represents the status assessment results of each sample and is combined with the independent variable matrix to form a new comprehensive matrix. This process lays a solid foundation for the subsequent regression analysis and makes the relationship between the factors clear.

[0054] In the process of identifying positive and negative impacts, the system calculates the regression coefficient to analyze the impact of each independent variable on the environmental state. By analyzing the value of the regression coefficient, the system can determine the direction of influence of each factor: if the regression coefficient is greater than zero, it indicates that the corresponding independent variable has a positive impact on the environmental state, that is, increasing the independent variable will lead to an increase in the environmental state index; conversely, if the regression coefficient is less than zero, it means that the independent variable has a negative impact on the environmental state. By calculating the standard error and performing statistical analysis, the system can further determine the statistical significance of each coefficient. If the significance level is less than 0.05, it indicates that the coefficient is statistically significant, otherwise it is considered that the influence of the coefficient is not significant.

[0055] Through in-depth cross-analysis of human activities and environmental status, the system can more comprehensively understand the impact of human activities on the natural environment. This process not only reveals the positive and negative effects of human activities, but also provides a scientific basis for decision-making. Combined with GIS technology, the construction of a spatial distribution model makes the analysis results not only quantitative, but also visual in space, thereby more intuitively showing the relationship between human activities and environmental changes. In addition, this step can capture potential nonlinear relationships by establishing complex polynomial models and interaction terms, making the analysis results more refined and accurate.

[0056] like Figure 5 As shown, the spatial analysis model is established at the same time, human activity data is extracted from multi-source real-time data, and the positive and negative impacts of human activities on the environment are analyzed in combination with the current natural environment status assessment results, specifically including: S410, extracting relevant human activity data from a centralized database; S420, Use geographic information systems to construct spatial distribution models of human activities; S430, combining the results of the natural environment status assessment model with human activity data, conducting cross-analysis, determining the relationship between human activities and environmental status, and identifying positive and negative impacts.

[0057] In this embodiment, the use of a geographic information system to construct a spatial distribution model of human activities specifically includes: Construct a spatial distribution model of human activities: ; in, is the vector of environmental status assessment results, is the independent variable matrix, The matrix representing the interaction terms and polynomial terms, is the regression coefficient vector, which indicates the influence of each basic feature on the environmental status assessment result. is the regression coefficient vector of interaction terms and polynomial terms, representing the impact of complex relationships on environmental states, is the error term; Based on the collected human activity data, construct the independent variable matrix ; ; in, Indicates traffic flow, represents industrial emissions, represents population density; Compute interaction terms and polynomial terms and construct matrices : ; ; ; According to the environmental status assessment results, construct the dependent variable vector It is expressed as: ; in, Indicates Status assessment results of samples; Will and Combine into a new matrix : .

[0058] In this embodiment, the identifying of positive and negative impacts specifically includes: Calculate regression coefficients ; in, Included and , for The transpose of Through the regression coefficient The value of analyzes the positive and negative impact of various factors on the environmental state, specifically: like , it means that the corresponding independent variable has a positive impact on the environmental state, that is, increasing the independent variable will lead to an upward trend in the environmental state index; like , it means that the corresponding independent variable has a negative impact on the environmental state, that is, increasing the independent variable will lead to a downward trend in the environmental state index; Calculating Statistics , express The standard error of according to Statistics and Degrees of Freedom ,use Distribution table lookup corresponding value; like If the coefficient is less than 0.05, it is considered that the coefficient is statistically significant, indicating that the independent variable has a significant impact on the environmental state; like If the coefficient is less than 0.05, it is considered that the coefficient is not statistically significant, indicating that the influence of the independent variable on the environmental state is not obvious.

[0059] S500, based on the results of positive and negative impact analysis, generates environmental management recommendations for provinces and cities, as well as collaborative governance measures between provinces and cities.

[0060] Figure 6 The structural block diagram of the geographic information collection system based on multi-source data fusion provided by the present invention is as follows: Figure 6 As shown, the system comprises: The data automatic capture module 100 is used to automatically capture multi-source real-time data and store the collected data in a centralized database; The multi-source data integration module 200 is used to integrate data from different sources to form a multi-source data set, determine whether the integrated data of all provinces and cities can be accessed in real time, and integrate the multi-source data sets of all provinces and cities again to generate a unified geographic information database; The environmental status assessment and monitoring module 300 is used to establish a status assessment model and conduct status assessment on the natural environment based on the data in the geographic information database; The human activity impact analysis module 400 is used to simultaneously establish a spatial analysis model, extract human activity data from multi-source real-time data, and analyze the positive and negative impacts of human activities on the environment in combination with the current natural environment status assessment results; The management strategy generation module 500 is used to generate environmental management suggestions for each province and city, as well as collaborative governance measures between provinces and cities based on the positive and negative impact analysis results.

[0061] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0062] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0063] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0064] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0066] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0067] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A geographic information collection method based on multi-source data fusion, characterized in that: The method comprises: Automatically capture real-time data from multiple sources and store the collected data in a centralized database; Integrate data from different sources to form a multi-source data set, determine whether the integrated data of all provinces and cities can be accessed in real time, and integrate the multi-source data sets of all provinces and cities again to generate a unified geographic information database; Establish a status assessment model to assess the status of the natural environment based on data in the geographic information database; At the same time, a spatial analysis model is established to extract human activity data from multi-source real-time data, and combined with the current natural environment status assessment results, the positive and negative impacts of human activities on the environment are analyzed; Based on the results of the positive and negative impact analysis, environmental management recommendations for each province and city are generated, as well as collaborative governance measures between provinces and cities.

2. The method according to claim 1, characterized in that: The automatic capture of multi-source real-time data and storage of the collected data in a centralized database specifically includes: Evaluate the update frequency and data quality of each data source and select the data source for collection; Set the crawling frequency and crawling time window to automatically crawl data from the data source, including: crawling meteorological data, environmental monitoring data and satellite remote sensing data of various provinces and cities; Obtain human activity data, including: Analyze remote sensing satellite image data to obtain the urbanization rate of the current region, the change data of urban construction land, and the spatial data of urban expansion; Obtain industrial emission monitoring data, including emissions of major pollutants; Obtain data on crop area, fertilizer application, and irrigation water use, and use remote sensing imagery to analyze changes in agricultural land use.

3. The method according to claim 2, characterized in that The data from different sources are integrated to form a multi-source data set, and it is determined whether the integrated data of all provinces and cities can be accessed in real time, and the multi-source data sets of all provinces and cities are integrated again to generate a unified geographic information database, which specifically includes: Identify data formats from different data sources and convert data from different sources into a unified data structure and format, maintaining consistency in field names and data types; Merge the converted data to form a multi-source data set, and relate the data of each province and city to each other through common fields; Establish a unified geographic information database structure, store the integrated multi-source data sets in a unified geographic information database, and create indexes for the data in the database.

4. The method according to claim 3, characterized in that The converted data are merged to form a multi-source data set, and the data of each province and city are associated with each other through common fields, specifically including: Identify common attributes and fields in different data sources, and uniformly name the same fields in different data sources; Add a timestamp field to the data to compare and correlate the data of each province and city based on time; Use geocoding services to convert addresses into longitude and latitude, standardize geographic location information, and use boundary data in geographic information systems to ensure that data for provinces and cities can be correctly matched at the regional level; Calculate the similarity of data to determine the relevance of records in different data sources, and merge data from different sources based on this; Design relational tables in a unified database and establish relationships between data.

5. The method according to claim 4, characterized in that The establishment of the state assessment model, based on the data in the geographic information database, conducts a state assessment of the natural environment, specifically including: Identify the indicators of the state of the natural environment to be assessed and determine the geographical and temporal scope of the assessment; Extract data related to the evaluation indicators from the unified geographic information database; Selecting a feature vector and a target vector, wherein the feature vector represents a multi-source data set in a centralized database, and the target vector represents a natural environment state indicator; Construct a status assessment model, use the established status assessment model in combination with the spatial analysis model, extract human activity data and combine it with the natural environment status assessment results to analyze the positive and negative impacts.

6. The method according to claim 5, characterized in that The constructing of the state assessment model specifically includes: Construct a state assessment model, the model formula is: ； in, The output is the prediction result of the model, that is, the assessment result of the natural environment status; represents the input feature vector, which contains the features extracted from the geographic information database; is a weight vector, which indicates the influence of each feature on the evaluation result. Used to transform the weight vector Convert to a row vector; is a mapping function used to map features to a high-dimensional space. It is the dot product of the weight vector and the feature vector, which represents the weighted sum of the input features of the model; In the formula, the weight vector It is expressed as: Climate characteristic weights, reflecting the impact of climate change on the state of the natural environment; Land use characteristic weights, which represent the impact of land use changes on the environment; Environmental monitoring feature weights represent the reflection of existing environmental indicators on the natural state; Use the integrated multi-source dataset to train the model and optimize the weight vector and bias term: ； in, represents the true label.

7. The method according to claim 6, characterized in that The spatial analysis model is established to extract human activity data from multi-source real-time data, and combined with the current natural environment status assessment results, the positive and negative impacts of human activities on the environment are analyzed, including: Extract relevant human activity data from centralized databases; Use geographic information systems to construct spatial distribution models of human activities; The results of the natural environment status assessment model are combined with human activity data for cross-analysis to determine the relationship between human activities and environmental status and identify positive and negative impacts.

8. The method according to claim 7, characterized in that The use of a geographic information system to construct a spatial distribution model of human activities specifically includes: Construct a spatial distribution model of human activities: ； in, is the vector of environmental status assessment results, is the independent variable matrix, The matrix representing the interaction terms and polynomial terms, is the regression coefficient vector, which indicates the influence of each basic feature on the environmental status assessment result. is the regression coefficient vector of interaction terms and polynomial terms, representing the impact of complex relationships on environmental states, is the error term; Based on the collected human activity data, construct the independent variable matrix ; ； in, Indicates traffic flow, represents industrial emissions, represents population density; Compute interaction terms and polynomial terms and construct matrices : ； ； ； According to the environmental status assessment results, construct the dependent variable vector It is expressed as: ； in, Indicates Status assessment results of samples; Will and Combine into a new matrix : 。 9. The method according to claim 8, characterized in that The identification of positive and negative impacts specifically includes: Calculate regression coefficients ; in, Included and , for The transpose of Through the regression coefficient The value of analyzes the positive and negative impact of various factors on the environmental state, specifically: like , it means that the corresponding independent variable has a positive impact on the environmental state, that is, increasing the independent variable will lead to an upward trend in the environmental state index; like , it means that the corresponding independent variable has a negative impact on the environmental state, that is, increasing the independent variable will lead to a downward trend in the environmental state index; Calculating Statistics , express The standard error of according to Statistics and Degrees of Freedom ,use Distribution table lookup corresponding value; like If the coefficient is less than 0.05, it is considered that the coefficient is statistically significant, indicating that the independent variable has a significant impact on the environmental state; like If the coefficient is less than 0.05, it is considered that the coefficient is not statistically significant, indicating that the influence of the independent variable on the environmental state is not obvious.

10. A geographic information collection system based on multi-source data fusion, characterized in that: The system comprises: The data automatic capture module is used to automatically capture real-time data from multiple sources and store the collected data in a centralized database; The multi-source data integration module is used to integrate data from different sources to form a multi-source data set, determine whether the integrated data of all provinces and cities can be accessed in real time, and integrate the multi-source data sets of all provinces and cities again to generate a unified geographic information database; Environmental status assessment and monitoring module, used to establish a status assessment model and conduct status assessment of the natural environment based on data in the geographic information database; The human activity impact analysis module is used to simultaneously establish a spatial analysis model, extract human activity data from multi-source real-time data, and analyze the positive and negative impacts of human activities on the environment in combination with the current natural environment status assessment results; The management strategy generation module is used to generate environmental management recommendations for provinces and cities, as well as collaborative governance measures between provinces and cities based on the results of positive and negative impact analysis.

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