Ecological environment damage event space-time evolution analysis and dynamic evaluation system

Abstract

The invention relates to the technical field of environment monitoring and evaluation, in particular to an ecological environment damage event spatio-temporal evolution analysis and dynamic evaluation system, which comprises a data acquisition module, a spatio-temporal data processing platform, a scene simulation and prediction module, a multi-source data fusion module, a multi-source data fusion module and a data analysis and dynamic evaluation module, the space-time evolution module is connected with the space-time data processing platform through a data transmission technology, the space-time evolution analysis module is connected with the scene simulation prediction module through the data transmission technology, and the dynamic evaluation comparison module is connected with the space-time evolution analysis module through the data transmission technology. By constructing the spatial index, the time index and the space-time composite index, the retrieval efficiency of the data in the space-time dimension is greatly improved, and by constructing the ecological environment damage event prediction model, generating diversified scene simulation schemes and verifying and optimizing the model, the development trend of the ecological environment damage event can be accurately predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring and assessment, and in particular to a system for analyzing and dynamically assessing the spatiotemporal evolution of ecological environmental damage events. Background Art

[0002] At present, the global ecological environment faces multiple threats, and ecological damage caused by natural disasters (such as floods and earthquakes), industrial pollution (such as waste gas and wastewater emissions) and over-exploitation (such as deforestation and mineral mining) occurs frequently. The traditional ecological environment monitoring and assessment system relies on a single data source (such as ground monitoring stations or satellite remote sensing), which makes it difficult to fully reflect the temporal and spatial heterogeneity of the ecological environment. In addition, the indicator system with fixed weights cannot dynamically respond to environmental changes, and lacks the long-term trend prediction of ecological environment evolution and the in-depth mining of spatial diffusion laws. Summary of the invention

[0003] In view of the deficiencies of the prior art, the present invention provides a spatiotemporal evolution analysis and dynamic assessment system for ecological environmental damage events to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a system for analyzing and dynamically evaluating the spatiotemporal evolution of ecological environmental damage events, comprising:

[0005] Data collection module, used to obtain various data of the region, including but not limited to vegetation coverage, water pollution, atmospheric environment, soil parameters, population distribution, GDP data, industrial structure and policy clauses related to regional ecological and environmental damage;

[0006] The multi-source data fusion module is connected to the data acquisition module through data transmission technology, and is used to update data in real time, detect the acquired data, record the source of each data, the acquisition time and the data of the acquisition device, establish a data traceability link, pre-process the data, and perform standardized conversion and effective fusion of data in different formats and from different sources;

[0007] The spatiotemporal data processing platform is connected to the multi-source data fusion module through data transmission technology, and is used to build a distributed data processing platform, compress and back up data, and build a spatiotemporal composite index to improve the retrieval efficiency of data in the spatiotemporal dimension;

[0008] The scenario simulation and prediction module is connected to the spatiotemporal data processing platform through data transmission technology. It is used to build data models, set scenario conditions, simulate visual scenario interfaces, verify and optimize models, and evaluate scenario risks.

[0009] The spatiotemporal evolution analysis module is connected to the scenario simulation and prediction module through data transmission technology, and is used to evolve the changing trends of ecological environmental damage events at different time scales and analyze the evolution results;

[0010] The dynamic assessment comparison module is connected to the spatiotemporal evolution analysis module through data transmission technology. It is used to dynamically adjust the weights of assessment indicators according to different types of ecological environmental damage and assessment purposes, compare and analyze the assessment results of different periods, and evaluate the development trend and governance effect of ecological environmental damage events;

[0011] The result output module is connected to the dynamic evaluation comparison module through data transmission technology. It is used to combine the map engine to display the spatiotemporal evolution analysis results and dynamic evaluation reports in the form of intuitive three-dimensional maps, dynamic charts, and animations, and generate decision-making recommendations.

[0012] Preferably, the multi-source data fusion module performs preprocessing on the data including data anomaly processing, data missing value processing and data standardization processing. The data anomaly processing adopts standard deviation calculation, and the calculation formula is: , where is the standard deviation, refers to the number of ecological environment indicators. is the index of the data, For time point Or the serial number is The specific data values ​​corresponding to the ecological environment indicators, is the average of all data, and The missing data are processed by selecting the distance ecological environment index Recent Ecological environment indicators, denoted as ,according to The first Features to predict Missing values , the calculation formula is: , where All other ecological and environmental indicators are ecological and environmental indicators No. The calculation formula for data standardization is: , where is the standardized data value, For the The sample in The original data value on the indicator, For the The mean of the indicators, For the The standard deviation of an indicator.

[0013] Preferably, the spatiotemporal indexing of the spatiotemporal data processing platform comprises the following steps:

[0014] S1. Convert the spatial objects in the ecological environment data into the minimum enclosing rectangle and calculate the remaining space of the node. The calculation formula is: , where is the remaining space of the node, For Node The minimum circumscribed rectangle area of ​​, For Node The first The minimum enclosing rectangle area of ​​an object, For Node The quantity already included in

[0015] S2. Sort the time-related ecological environment data in chronological order to ensure the orderliness of the time data;

[0016] S3, using a B+ tree index structure, each node stores multiple time intervals and their corresponding pointers to child nodes or data blocks. When inserting new time ecological environment data, a binary search algorithm is used to quickly locate the appropriate node position for insertion;

[0017] S4. Find the node of the ecological environment data at the start time from the B+ tree, and then search sequentially through the linked list until the node position of the ecological environment data at the end time is found, and obtain all the ecological environment data that meet the time condition;

[0018] S5. Embed a time index pointer in the spatial index node to achieve an organic combination of the spatial index and the time index, forming a spatiotemporal composite index, and use the time index to filter out ecological and environmental data that meet the time conditions within the spatial range.

[0019] Preferably, the scenario simulation prediction module establishes the scenario section and performs verification optimization, including the following steps:

[0020] Ⅰ. Construct a spatiotemporal coupling model to capture the temporal dependence of ecological and environmental indicators and characterize the spatial heterogeneity of ecological and environmental indicators;

[0021] II. Quantify the impact of climate change on the ecological environment, simulate the impact of human intervention on the ecological environment, cover representative scenarios in the parameter space, and reduce simulation redundancy;

[0022] III. Use 3D dynamic rendering to intuitively display the spatiotemporal evolution of ecological environmental damage and generate interactive parameters to enhance users’ control and understanding of the simulation process;

[0023] IV. Quantify the model error, predict the deviation between the result and the real data, improve the generalization ability of the model, and avoid overfitting. The calculation formula is: , where It is an indicator to measure the deviation between the predicted value of the ecological environment damage event model and the actual value. The number of samples for ecological environment damage analysis, For the The actual observed values ​​of ecological environment damage related indicators, For the The corresponding indicator value calculated by the prediction model;

[0024] V. Comprehensively evaluate the ecological environment risk level based on multi-dimensional factors. The calculation formula is: , where As an assessment indicator of ecological environmental damage, Flux or flow indicators related to ecological and environmental damage, is the degree of exposure to the ecological environment, is the area of ​​the damaged region.

[0025] Preferably, in step I, a forget gate is used to control the degree of retention of historical information, which is suitable for predicting the temporal evolution of ecological environmental damage events, and the calculation formula is: , where For the The forget gate output at time is the activation function, is the weight matrix of the forget gate, For the historical ecological environment characteristics, is the ecological environment characteristics at the current moment, is the bias term of the forget gate. The local regression equation is used to allow the regression coefficient to vary with the spatial position, which improves the adaptability of the model to complex geographical conditions. The calculation formula is: , where For the The ecological environment response value of an unprecedented unit, For spatial location The interception item at is the number of explanatory variables, For the The independent variable is located in space The regression coefficient at For the independent variables, is the error term of random ecological environment damage events.

[0026] Preferably, the spatiotemporal evolution analysis module performs the following steps to evolve and analyze ecological environment damage events:

[0027] 1) Using the time series analysis method based on wavelet transform to extract the changing trend of ecological environmental damage events on different time scales, for a given time series data , the calculation formula is: , where To assess the extent of damage to the ecological environment, For over time Changing ecological environment indicators, is the time scale parameter, is the starting point of the impact of ecological environmental damage events on subsequent changes in environmental indicators, The characteristic changes of ecological environment damage events at different stages of the process, is the differential of the integrated variable;

[0028] 2) Use Fourier transform to determine the periodic characteristics of ecological environmental damage events and quickly discover sudden anomalies. The calculation formula is: , where is the cycle of ecological environment indicators. Under normal conditions, It shows a certain pattern. When the ecological environment is damaged and abnormalities occur, The distribution and value of will change, and the occurrence of abnormal events can be judged accordingly. is the ecological environment indicator under discrete time series, is the length of the time series of ecological environment damage, is the frequency index of ecological environment damage time, is an imaginary unit, and ;

[0029] 3) Use the kernel density estimation method to analyze the spatial distribution characteristics of ecological environmental damage events and find the clustering hot spots. The calculation formula is: , where For position The estimated value of the density of ecological environmental damage events at any location in space is obtained. The density of damage events occurring at the is the spatial position coordinate, For the The spatial position coordinates of the sample points, is the number of sample points, is the bandwidth parameter, which controls the smoothness of the kernel function. is the kernel function used to calculate the spatial position The density contribution at ;

[0030] 4) Through spatial autocorrelation analysis, identify the potential factors that affect the spatial distribution of ecological environmental damage events, and predict the damage events in unmonitored areas. The calculation formula is: , where is the correlation degree of ecological environment damage events in spatial distribution, and Represents the spatial position and Ecological environment indicators of the place, is the average value of the ecological environment indicators of all sample points, and is the spatial weight matrix used to measure the spatial location and The spatial relationship between is the number of sample points involved in spatial autocorrelation analysis.

[0031] Preferably, the dynamic evaluation and comparison module evaluates and compares the spatiotemporal evolution analysis results, including the following steps:

[0032] A. According to the type of ecological environmental damage events and the purpose of assessment, the disorder of ecological environmental damage events is quantified for the results of spatiotemporal evolution analysis. The calculation formula is: , where It is a dynamic assessment indicator that directly reflects the degree of disorder of the ecological environment damage system in the process of temporal and spatial evolution. The larger the value, the more unstable the temporal and spatial distribution of damage events is, and dynamic monitoring needs to be strengthened. It is the spatial unit in the analysis of spatiotemporal evolution. To define the spatial granularity of the analysis, is the time series variable corresponding to the dynamic evaluation, is the time range parameter for analysis, are variables for different ecosystem types, To combine spatial position and ecological factors The spatiotemporal sensitivity weights, is the ecological element diversity parameter, The probability of a damage event occurring in a specific time and space situation;

[0033] B. Calculate the entropy weight of the objective importance of ecological indicators and evaluate the degree of ecological damage. The calculation formula is: , where For the The weight of relevant factors in the assessment of ecological environmental damage events, is the total number of relevant factors involved in the assessment;

[0034] C. Use the linear weighting method to integrate the subjective judgment of the hierarchical analysis method and the objective data of the entropy weight method to determine the comprehensive weight, and comprehensively and reasonably determine the factor weights. The calculation formula is: , where is the time for assessing ecological environmental damage The comprehensive weight of the indicators, and is the weight coefficient, and ;

[0035] D. Regularly re-evaluate the indicator system and weights, and adjust the judgment matrix and data and recalculate the weights according to changes in the evaluation results;

[0036] E. Compare and analyze the assessment results of different periods to evaluate the development trend and governance effect of ecological environmental damage incidents.

[0037] The present invention provides a system for analyzing and dynamically evaluating the spatiotemporal evolution of ecological environmental damage events. It has the following beneficial effects:

[0038] 1. The present invention adopts a distributed storage architecture through a spatiotemporal big data platform, combined with spatiotemporal indexing and query optimization technology, and can efficiently store and manage massive ecological and environmental data. By constructing spatial indexes, time indexes, and spatiotemporal composite indexes, the retrieval efficiency of data in the spatiotemporal dimension is greatly improved. At the same time, the distributed parallel query and query caching mechanism are used to significantly shorten the query response time and improve the overall performance of the system.

[0039] 2. The present invention constructs an ecological environment damage event prediction model, generates a variety of scenario simulation schemes, and verifies and optimizes the model. It can accurately predict the development trend of ecological environment damage events. At the same time, it establishes a dynamic evaluation index system, combines hierarchical analysis method and entropy weight method to dynamically adjust the evaluation index weights, and realizes accurate evaluation of ecological environment damage events. It provides strong support for ecological environment management departments to make scientific and reasonable decisions, helps to take prevention and control measures in advance, and reduces ecological environment risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] like Figure 1As shown, the embodiment of the present invention provides a system for analyzing and dynamically evaluating the spatiotemporal evolution of ecological environmental damage events, including:

[0043] Data collection module, used to obtain various data of the region, including but not limited to vegetation coverage, water pollution, atmospheric environment, soil parameters, population distribution, GDP data, industrial structure and policy clauses related to regional ecological and environmental damage;

[0044] The multi-source data fusion module is connected to the data acquisition module through data transmission technology, and is used to update data in real time, detect the acquired data, record the source of each data, the acquisition time and the data of the acquisition device, establish a data traceability link, pre-process the data, and perform standardized conversion and effective fusion of data in different formats and from different sources;

[0045] The spatiotemporal data processing platform is connected to the multi-source data fusion module through data transmission technology, and is used to build a distributed data processing platform, compress and back up data, and build a spatiotemporal composite index to improve the retrieval efficiency of data in the spatiotemporal dimension;

[0046] The scenario simulation and prediction module is connected to the spatiotemporal data processing platform through data transmission technology. It is used to build data models, set scenario conditions, simulate visual scenario interfaces, verify and optimize models, and evaluate scenario risks.

[0047] The spatiotemporal evolution analysis module is connected to the scenario simulation and prediction module through data transmission technology, and is used to evolve the changing trends of ecological environmental damage events at different time scales and analyze the evolution results;

[0048] The dynamic assessment comparison module is connected to the spatiotemporal evolution analysis module through data transmission technology. It is used to dynamically adjust the weights of assessment indicators according to different types of ecological environmental damage and assessment purposes, compare and analyze the assessment results of different periods, and evaluate the development trend and governance effect of ecological environmental damage events;

[0049] The result output module is connected to the dynamic evaluation comparison module through data transmission technology. It is used to combine the map engine to display the spatiotemporal evolution analysis results and dynamic evaluation reports in the form of intuitive three-dimensional maps, dynamic charts, and animations, and generate decision-making recommendations.

[0050] In this embodiment, the multi-source data fusion module performs preprocessing on the data, including data anomaly processing, data missing value processing, and data standardization processing. The data anomaly processing adopts standard deviation calculation, and the calculation formula is: , where is the standard deviation, refers to the number of ecological environment indicators. is the index of the data, For time point Or the serial number is The specific data values ​​corresponding to the ecological environment indicators, is the average of all data, and , the missing data are processed by selecting the distance ecological environment index Recent Ecological environment indicators, denoted as ,according to The first Features to predict Missing values , the calculation formula is: , where All other ecological and environmental indicators are ecological and environmental indicators No. The calculation formula for data standardization is: , where is the standardized data value, For the The sample in The original data value on the indicator, For the The mean of the indicators, For the The standard deviation of an indicator.

[0051] In this embodiment, the spatiotemporal indexing of the spatiotemporal data processing platform includes the following steps:

[0052] S1. Convert the spatial objects in the ecological environment data into the minimum enclosing rectangle and calculate the remaining space of the node. The calculation formula is: , where is the remaining space of the node, For Node The minimum circumscribed rectangle area of ​​, For Node The first The minimum enclosing rectangle area of ​​an object, For Node The quantity already included in

[0053] S2. Sort the time-related ecological environment data in chronological order to ensure the orderliness of the time data;

[0054] S3, using a B+ tree index structure, each node stores multiple time intervals and their corresponding pointers to child nodes or data blocks. When inserting new time ecological environment data, a binary search algorithm is used to quickly locate the appropriate node position for insertion;

[0055] S4. Find the node of the ecological environment data at the start time from the B+ tree, and then search sequentially through the linked list until the node position of the ecological environment data at the end time is found, and obtain all the ecological environment data that meet the time condition;

[0056] S5. Embed a time index pointer in the spatial index node to achieve an organic combination of the spatial index and the time index, forming a spatiotemporal composite index, and use the time index to filter out ecological and environmental data that meet the time conditions within the spatial range.

[0057] Specifically, the multi-source data fusion module can collect data from multiple channels such as satellite remote sensing, ground monitoring stations, drones, social and economic databases, and policy and regulatory text libraries, and realize the effective fusion of different types of data through advanced data preprocessing and association technologies. This enables the system to obtain more comprehensive and accurate ecological and environmental information, providing a solid data foundation for subsequent analysis and evaluation. Through the distributed storage architecture of the spatiotemporal big data platform, combined with spatiotemporal indexing and query optimization technology, it can efficiently store and manage massive amounts of ecological and environmental data. By constructing spatial indexes, time indexes, and spatiotemporal composite indexes, the retrieval efficiency of data in the spatiotemporal dimension is greatly improved. At the same time, the distributed parallel query and query cache mechanism are used to significantly shorten the query response time and improve the overall performance of the system.

[0058] In this embodiment, the scenario simulation prediction module establishes the scenario cross section and performs verification optimization, including the following steps:

[0059] Ⅰ. Construct a spatiotemporal coupling model to capture the temporal dependence of ecological and environmental indicators and characterize the spatial heterogeneity of ecological and environmental indicators;

[0060] II. Quantify the impact of climate change on the ecological environment, simulate the impact of human intervention on the ecological environment, cover representative scenarios in the parameter space, and reduce simulation redundancy;

[0061] III. Use 3D dynamic rendering to intuitively display the spatiotemporal evolution of ecological environmental damage and generate interactive parameters to enhance users’ control and understanding of the simulation process;

[0062] IV. Quantify the model error, predict the deviation between the result and the real data, improve the generalization ability of the model, and avoid overfitting. The calculation formula is: , where It is an indicator to measure the deviation between the predicted value of the ecological environment damage event model and the actual value. The number of samples for ecological environment damage analysis, For the The actual observed values ​​of ecological environment damage related indicators, For the The corresponding indicator value calculated by the prediction model;

[0063] V. Comprehensively evaluate the ecological environment risk level based on multi-dimensional factors. The calculation formula is: , where As an assessment indicator of ecological environmental damage, is a flux or flow indicator related to ecological and environmental damage, is the degree of exposure to the ecological environment, is the area of ​​the damaged region.

[0064] In this embodiment, in step I, a forget gate is used to control the degree of retention of historical information, which is suitable for predicting the temporal evolution of ecological environmental damage events. The calculation formula is: , where For the The forget gate output at time is the activation function, is the weight matrix of the forget gate, For the historical ecological environment characteristics, is the ecological environment characteristics at the current moment, is the bias term of the forget gate. The local regression equation is used to allow the regression coefficient to vary with the spatial position, which improves the adaptability of the model to complex geographical conditions. The calculation formula is: , where For the The ecological environment response value of an unprecedented unit, For spatial location The interception item at is the number of explanatory variables, For the The independent variable is located in space The regression coefficient at For the independent variables, is the error term of random ecological environment damage events.

[0065] In this embodiment, the spatiotemporal evolution analysis module performs the following steps on the evolution and analysis of ecological environment damage events:

[0066] 1) Using the time series analysis method based on wavelet transform to extract the changing trend of ecological environmental damage events on different time scales, for a given time series data , the calculation formula is: , where To assess the extent of damage to the ecological environment, For over time Changing ecological environment indicators, is the time scale parameter, is the starting point of the impact of ecological environmental damage events on subsequent changes in environmental indicators, The characteristic changes of ecological environment damage events at different stages of the process, is the differential of the integrated variable;

[0067] 2) Use Fourier transform to determine the periodic characteristics of ecological environmental damage events and quickly discover sudden anomalies. The calculation formula is: , where is the cycle of ecological environment indicators. Under normal conditions, It shows a certain pattern. When the ecological environment is damaged and abnormalities occur, The distribution and value of will change, and the occurrence of abnormal events can be judged accordingly. is the ecological environment indicator under discrete time series, is the length of the time series of ecological environment damage, is the frequency index of ecological environment damage time, is an imaginary unit, and ;

[0068] 3) Use the kernel density estimation method to analyze the spatial distribution characteristics of ecological environmental damage events and find the clustering hot spots. The calculation formula is: , where For position The estimated value of the density of ecological environmental damage events at any location in space is obtained. The density of damage events. is the spatial position coordinate, For the The spatial position coordinates of the sample points, is the number of sample points, is the bandwidth parameter, which controls the smoothness of the kernel function. is the kernel function used to calculate the spatial position The density contribution at ;

[0069] 4) Through spatial autocorrelation analysis, identify the potential factors that affect the spatial distribution of ecological environmental damage events, and predict the damage events in unmonitored areas. The calculation formula is: , where is the correlation degree of ecological environment damage events in spatial distribution, and Represents the spatial position and Ecological environment indicators of the place, is the average value of the ecological environment indicators of all sample points, and is the spatial weight matrix used to measure the spatial location and The spatial relationship between is the number of sample points involved in spatial autocorrelation analysis.

[0070] In this embodiment, the dynamic evaluation and comparison module evaluates and compares the spatiotemporal evolution analysis results, including the following steps:

[0071] A. According to the type of ecological environmental damage events and the purpose of assessment, the disorder of ecological environmental damage events is quantified for the results of spatiotemporal evolution analysis. The calculation formula is: , where It is a dynamic assessment indicator that directly reflects the degree of disorder of the ecological environment damage system in the process of temporal and spatial evolution. The larger the value, the more unstable the temporal and spatial distribution of damage events is, and dynamic monitoring needs to be strengthened. It is the spatial unit in the analysis of spatiotemporal evolution. To define the spatial granularity of the analysis, is the time series variable corresponding to the dynamic evaluation, is the time range parameter for analysis, are variables for different ecosystem types, To combine spatial position and ecological factors The spatiotemporal sensitivity weights, is the ecological element diversity parameter, The probability of a damage event occurring in a specific time and space situation;

[0072] B. Calculate the entropy weight of the objective importance of ecological indicators and evaluate the degree of ecological damage. The calculation formula is: , where For the The weight of relevant factors in the assessment of ecological environmental damage events, is the total number of relevant factors involved in the assessment;

[0073] C. Use the linear weighting method to integrate the subjective judgment of the hierarchical analysis method and the objective data of the entropy weight method to determine the comprehensive weight, and comprehensively and reasonably determine the factor weights. The calculation formula is: , where is the time for assessing ecological environmental damage The comprehensive weight of the indicators, and is the weight coefficient, and ;

[0074] D. Regularly re-evaluate the indicator system and weights, and adjust the judgment matrix and data and recalculate the weights according to changes in the evaluation results;

[0075] E. Compare and analyze the assessment results of different periods to evaluate the development trend and governance effect of ecological environmental damage incidents.

[0076] Specifically, by using advanced spatiotemporal analysis algorithms, a comprehensive spatiotemporal evolution analysis of ecological environmental damage events is conducted, including time series analysis and spatial analysis. By constructing an ecological environmental damage event prediction model, a variety of scenario simulation schemes are generated, and the model is verified and optimized. This can accurately predict the development trend of ecological environmental damage events. At the same time, a dynamic evaluation index system is established, and the weights of evaluation indicators are dynamically adjusted by combining methods such as hierarchical analysis method and entropy weight method to achieve accurate assessment of ecological environmental damage events, providing strong support for ecological environmental management departments to make scientific and reasonable decisions, and helping to take prevention and control measures in advance to reduce ecological environmental risks.

[0077] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The spatiotemporal evolution analysis and dynamic assessment system of ecological environment damage events is characterized by: include: Data collection module, used to obtain various data of the region, including but not limited to vegetation coverage, water pollution, atmospheric environment, soil parameters, population distribution, GDP data, industrial structure and policy clauses related to regional ecological and environmental damage; The multi-source data fusion module is connected to the data acquisition module through data transmission technology, and is used to update data in real time, detect the acquired data, record the source of each data, the acquisition time and the data of the acquisition device, establish a data traceability link, pre-process the data, and perform standardized conversion and effective fusion of data in different formats and from different sources; The spatiotemporal data processing platform is connected to the multi-source data fusion module through data transmission technology, and is used to build a distributed data processing platform, compress and back up data, and build a spatiotemporal composite index to improve the retrieval efficiency of data in the spatiotemporal dimension; The scenario simulation and prediction module is connected to the spatiotemporal data processing platform through data transmission technology. It is used to build data models, set scenario conditions, simulate visual scenario interfaces, verify and optimize models, and evaluate scenario risks. The spatiotemporal evolution analysis module is connected to the scenario simulation and prediction module through data transmission technology, and is used to evolve the changing trends of ecological environmental damage events at different time scales and analyze the evolution results; The dynamic assessment comparison module is connected to the spatiotemporal evolution analysis module through data transmission technology. It is used to dynamically adjust the weights of assessment indicators according to different types of ecological environmental damage and assessment purposes, compare and analyze the assessment results of different periods, and evaluate the development trend and governance effect of ecological environmental damage events; The result output module is connected to the dynamic evaluation comparison module through data transmission technology. It is used to combine the map engine to display the spatiotemporal evolution analysis results and dynamic evaluation reports in the form of intuitive three-dimensional maps, dynamic charts, and animations, and generate decision-making recommendations.

2. The spatiotemporal evolution analysis and dynamic assessment system for ecological environment damage events according to claim 1 is characterized in that: The multi-source data fusion module performs data preprocessing including data anomaly processing, data missing value processing and data standardization processing. The data anomaly processing adopts standard deviation calculation, and the calculation formula is: , where is the standard deviation, refers to the number of ecological environment indicators. is the index of the data, For time point Or the serial number is The specific data values ​​corresponding to the ecological environment indicators, is the average of all data, and The missing data are processed by selecting the distance ecological environment index Recent Ecological environment indicators, denoted as ,according to The first Features to predict Missing values , the calculation formula is: , where All other ecological and environmental indicators are ecological and environmental indicators No. The calculation formula for data standardization is: , where is the standardized data value, For the The sample in The original data value on the indicator, For the The mean of the indicators, For the The standard deviation of an indicator.

3. The spatiotemporal evolution analysis and dynamic assessment system for ecological environment damage events according to claim 1 is characterized in that: The spatiotemporal indexing of the spatiotemporal data processing platform comprises the following steps: S1. Convert the spatial objects in the ecological environment data into the minimum enclosing rectangle and calculate the remaining space of the node. The calculation formula is: , where is the remaining space of the node, For Node The minimum circumscribed rectangle area of ​​, For Node The first The minimum enclosing rectangle area of ​​an object, For Node The quantity already included in S2. Sort the time-related ecological environment data in chronological order to ensure the orderliness of the time data; S3, using a B+ tree index structure, each node stores multiple time intervals and their corresponding pointers to child nodes or data blocks. When inserting new time ecological environment data, a binary search algorithm is used to quickly locate the appropriate node position for insertion; S4. Find the node of the ecological environment data at the start time from the B+ tree, and then search sequentially through the linked list until the node position of the ecological environment data at the end time is found, and obtain all the ecological environment data that meet the time condition; S5. Embed a time index pointer in the spatial index node to achieve an organic combination of the spatial index and the time index, forming a spatiotemporal composite index, and use the time index to filter out ecological and environmental data that meet the time conditions within the spatial range.

4. The spatiotemporal evolution analysis and dynamic assessment system for ecological environment damage events according to claim 1 is characterized in that: The scenario simulation prediction module establishes scenario sections and performs verification optimization, including the following steps: Ⅰ. Construct a spatiotemporal coupling model to capture the temporal dependence of ecological and environmental indicators and characterize the spatial heterogeneity of ecological and environmental indicators; II. Quantify the impact of climate change on the ecological environment, simulate the impact of human intervention on the ecological environment, cover representative scenarios in the parameter space, and reduce simulation redundancy; III. Use 3D dynamic rendering to intuitively display the spatiotemporal evolution of ecological environmental damage and generate interactive parameters to enhance users’ control and understanding of the simulation process; IV. Quantify the model error, predict the deviation between the result and the real data, improve the generalization ability of the model, and avoid overfitting. The calculation formula is: , where It is an indicator to measure the deviation between the predicted value of the ecological environment damage event model and the actual value. The number of samples for ecological environment damage analysis, For the The actual observed values ​​of ecological environment damage related indicators, For the The corresponding indicator value calculated by the prediction model; V. Comprehensively evaluate the ecological environment risk level based on multi-dimensional factors. The calculation formula is: , where As an assessment indicator of ecological environmental damage, Flux or flow indicators related to ecological and environmental damage, is the degree of exposure to the ecological environment, is the area of ​​the damaged region.

5. The spatiotemporal evolution analysis and dynamic assessment system for ecological environmental damage events according to claim 4 is characterized in that: In step I, a forget gate is used to control the degree of retention of historical information, which is suitable for predicting the temporal evolution of ecological environmental damage events. The calculation formula is: , where For the The forget gate output at time is the activation function, is the weight matrix of the forget gate, For the historical ecological environment characteristics, is the ecological environment characteristics at the current moment, is the bias term of the forget gate. The local regression equation is used to allow the regression coefficient to vary with the spatial position, which improves the adaptability of the model to complex geographical conditions. The calculation formula is: , where For the The ecological environment response value of an unprecedented unit, For spatial location The interception item at is the number of explanatory variables, For the The independent variable is located in space The regression coefficient at For the independent variables, is the error term of random ecological environment damage events.

6. The spatiotemporal evolution analysis and dynamic assessment system for ecological environmental damage events according to claim 1 is characterized in that: The spatiotemporal evolution analysis module evolves and analyzes ecological environmental damage events, including the following steps: 1) Using the time series analysis method based on wavelet transform to extract the changing trend of ecological environmental damage events on different time scales, for a given time series data , the calculation formula is: , where To assess the extent of damage to the ecological environment, For over time Changing ecological environment indicators, is the time scale parameter, is the starting point of the impact of ecological environmental damage events on subsequent changes in environmental indicators, The characteristic changes of ecological environment damage events at different stages of the process, is the differential of the integral variable; 2) Use Fourier transform to determine the periodic characteristics of ecological environmental damage events and quickly discover sudden anomalies. The calculation formula is: , where is the cycle of ecological environment indicators. Under normal conditions, It shows a certain pattern. When the ecological environment is damaged and abnormalities occur, The distribution and value of will change, and the occurrence of abnormal events can be judged accordingly. is the ecological environment indicator under discrete time series, is the length of the time series of ecological environment damage, is the frequency index of ecological environment damage time, is an imaginary unit, and ; 3) Use the kernel density estimation method to analyze the spatial distribution characteristics of ecological environmental damage events and find the clustering hot spots. The calculation formula is: , where For position The estimated value of the density of ecological environmental damage events at any location in space is obtained. The density of damage events. is the spatial position coordinate, For the The spatial position coordinates of the sample points, is the number of sample points, is the bandwidth parameter, which controls the smoothness of the kernel function. is the kernel function used to calculate the spatial position The density contribution at ; 4) Through spatial autocorrelation analysis, identify the potential factors that affect the spatial distribution of ecological environmental damage events, and predict the damage events in unmonitored areas. The calculation formula is: , where is the correlation degree of ecological environment damage events in spatial distribution, and Represents the spatial position and Ecological environment indicators of the place, is the average value of the ecological environment indicators of all sample points, and is the spatial weight matrix used to measure the spatial location and The spatial relationship between is the number of sample points involved in spatial autocorrelation analysis.

7. The spatiotemporal evolution analysis and dynamic assessment system for ecological environment damage events according to claim 1 is characterized in that: The dynamic evaluation and comparison module evaluates and compares the spatiotemporal evolution analysis results, including the following steps: A. According to the type of ecological environmental damage events and the purpose of assessment, the disorder of ecological environmental damage events is quantified for the results of spatiotemporal evolution analysis. The calculation formula is: , where It is a dynamic assessment indicator that directly reflects the degree of disorder of the ecological environment damage system in the process of temporal and spatial evolution. The larger the value, the more unstable the temporal and spatial distribution of damage events is, and dynamic monitoring needs to be strengthened. It is the spatial unit in the analysis of spatiotemporal evolution. To define the spatial granularity of the analysis, is the time series variable corresponding to the dynamic evaluation, is the time range parameter for analysis, are variables for different ecosystem types, To combine spatial position and ecological factors The spatiotemporal sensitivity weights, is the ecological element diversity parameter, The probability of a damage event occurring in a specific time and space situation; B. Calculate the entropy weight of the objective importance of ecological indicators and evaluate the degree of ecological damage. The calculation formula is: , where For the The weight of relevant factors in the assessment of ecological environmental damage events, is the total number of relevant factors involved in the assessment; C. Use the linear weighting method to integrate the subjective judgment of the hierarchical analysis method and the objective data of the entropy weight method to determine the comprehensive weight, and comprehensively and reasonably determine the factor weights. The calculation formula is: , where is the time for assessing ecological environmental damage The comprehensive weight of the indicators, and is the weight coefficient, and ; D. Regularly re-evaluate the indicator system and weights, and adjust the judgment matrix and data and recalculate the weights according to changes in the evaluation results; E. Compare and analyze the assessment results of different periods to evaluate the development trend and governance effect of ecological environmental damage incidents.

Images