Natural reserve ecological monitoring result display system based on geographic information data

Abstract

The invention relates to the technical field of environment monitoring, in particular to a natural reserve ecological monitoring result display system based on geographic information data, which comprises a data acquisition module, a data fusion module, a dynamic GIS module, an intelligent analysis module, a multi-dimensional display module, an interactive report generation module and a user interaction module. Wherein the data acquisition module is used for acquiring ecological monitoring data; the data fusion module is used for carrying out fusion processing on the multi-source ecological monitoring data; the dynamic GIS module is used for mapping the fused ecological monitoring data into a geographic space in real time; the intelligent analysis module is used for intelligently analyzing the geographic space data; and the multi-dimensional display module is used for displaying the ecological monitoring result. According to the system and the method, the ecological data processing capability is improved through an efficient data fusion technology and an advanced intelligent analysis module, and meanwhile, the user experience is greatly enhanced through an interactive report generation and multi-dimensional display module.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to a system for displaying ecological monitoring results of nature reserves based on geographic information data. Background Art

[0002] In the field of environmental science and ecological monitoring, real-time and accurate acquisition of ecological data of nature reserves and their effective display and analysis are crucial for protecting biodiversity, predicting environmental changes and formulating relevant policies. With the development of remote sensing technology, geographic information system (GIS) and machine learning, the ability to collect and process ecological data has been significantly improved. However, these data are usually very large and complex, involving multiple data formats and sources, such as satellite images, sensor data and meteorological records. Although existing technologies provide some solutions, how to effectively integrate these data and dynamically display them to users in an easy-to-understand way remains a challenge.

[0003] Existing technologies have several limitations in processing and displaying complex ecological monitoring data. First, data fusion technology often cannot effectively process data from different sources, resulting in low data utilization and possible information discontinuity. Second, although there are many ways to display data, these methods often lack flexibility and interactivity and cannot meet the specific needs of researchers and decision makers, such as conducting in-depth data analysis or customizing reports based on specific perspectives and conditions. In addition, existing systems generally do not provide sufficient tools to support in-depth analysis of ecological data, such as anomaly detection and risk assessment, which limits the ability to extract useful information from the data.

[0004] Therefore, it is very necessary to develop a system that integrates efficient data fusion, flexible interactive report generation, and advanced data analysis functions to improve data processing efficiency and user experience. Summary of the invention

[0005] Based on the above objectives, the present invention provides a natural conservation area ecological monitoring results display system based on geographic information data.

[0006] The ecological monitoring results display system for nature reserves based on geographic information data includes data collection module, data fusion module, dynamic GIS module, intelligent analysis module, multi-dimensional display module, interactive report generation module and user interaction module; among which:

[0007] Data collection module: used to obtain ecological monitoring data from various sensors, satellite images, drone collection systems and ground observation stations in nature reserves, including meteorological data, water quality data, vegetation coverage data and animal activity data;

[0008] Data fusion module: connected to the data acquisition module, used for fusion processing of multi-source ecological monitoring data, the data fusion includes spatial data alignment, time synchronization and multi-source data consistency correction;

[0009] Dynamic GIS module: connected to the data fusion module, used to map the fused ecological monitoring data to the geographic space in real time to achieve dynamic spatial visualization. The dynamic GIS module supports real-time data update, historical data backtracking and forecast data simulation;

[0010] Intelligent analysis module: connected to the dynamic GIS module, used for intelligent analysis of geographic spatial data, including ecological anomaly detection, change trend prediction and ecological risk assessment based on machine learning;

[0011] Multi-dimensional display module: connected to the intelligent analysis module and the dynamic GIS module, used to display ecological monitoring results in various forms, including three-dimensional stereograms, heat maps, change trend maps and multi-dimensional data association maps;

[0012] Interactive report generation module: connected to the multi-dimensional display module, used to generate an interactive ecological monitoring report according to user needs, the report includes data charts, spatial analysis results and intelligent analysis conclusions;

[0013] User interaction module: connects the dynamic GIS module and the multi-dimensional display module, and is used to provide an interactive interface between the user and the system, allowing the user to perform data query, analysis settings and display view customization through the interactive interface. The interactive interface supports web and mobile applications.

[0014] Optionally, the data acquisition module includes a meteorological sensor unit, a water quality sensor unit, a vegetation coverage monitoring unit, an animal activity monitoring unit and a ground observation unit; wherein:

[0015] Meteorological sensor unit: used to collect meteorological data within the nature reserve, including parameters such as temperature, humidity, wind speed, wind direction, rainfall and air pressure;

[0016] Water quality sensor unit: used to monitor water quality data of water bodies in nature reserves, including parameters such as pH, dissolved oxygen, turbidity, conductivity and temperature;

[0017] Vegetation coverage monitoring unit: the vegetation coverage data of the nature reserve is obtained by using high-resolution satellite images and drone images. The vegetation coverage monitoring unit includes an image acquisition device and an image processing device. The image acquisition device is used to acquire high-resolution images, and the image processing device is used to analyze the images to extract information on vegetation coverage and send the results to the data fusion module.

[0018] Animal activity monitoring unit: The animal activity data in the nature reserve is obtained through an infrared camera and a motion sensor. The animal activity monitoring unit includes an infrared camera and a motion sensor. The infrared camera is used to capture the image of the animal, and the motion sensor is used to detect the movement trajectory of the animal.

[0019] Ground observation unit: It is arranged at a predetermined location in a nature reserve and is used for long-term monitoring of environmental parameters in a predetermined area. The ground observation unit includes a sensor network and a data recording device. The sensor network is used to collect meteorological data and water quality data. The data recording device is used to store the collected data and upload the data to the data fusion module regularly.

[0020] Optionally, the data fusion module includes a spatial data alignment unit, a time synchronization unit, a multi-source data consistency correction unit, and a data storage unit; wherein:

[0021] A spatial data alignment unit, used for aligning spatial data from different sensors and observation systems, wherein the spatial data alignment unit uses geographic coding and coordinate conversion technology to map various types of data into a unified geographic coordinate system;

[0022] Time synchronization unit: used to perform time synchronization processing on multi-source ecological monitoring data. The time synchronization unit uses timestamp technology and time series analysis methods to align data recorded at different times to a unified time reference to ensure the time consistency of each data source;

[0023] Multi-source data consistency correction unit: used to perform consistency correction on the fused multi-source ecological monitoring data. The multi-source data consistency correction unit uses data cleaning, outlier detection and data interpolation technology to correct the differences and errors between the data sources to ensure the integrity and accuracy of the data;

[0024] Data storage unit: used to store processed and corrected ecological monitoring data.

[0025] Optionally, the dynamic GIS module includes a data receiving unit, a spatial mapping unit, a real-time updating unit, a historical data backtracking unit, and a prediction simulation unit; wherein:

[0026] Data receiving unit: used to receive the integrated and corrected ecological monitoring data;

[0027] Spatial mapping unit: used to map the received ecological monitoring data into geographic space. The spatial mapping unit accurately locates the data in the geographic coordinate system through geographic coding and spatial interpolation technology, and generates corresponding geographic layers;

[0028] Real-time update unit: used to dynamically update the geospatial display. The real-time update unit ensures that the geospatial display content is updated in real time as the data changes through timed refresh and event trigger mechanisms. The timed refresh mechanism automatically updates the data based on a preset time interval, and the event trigger mechanism immediately updates by monitoring data change events;

[0029] Historical data backtracking unit: used to conduct backtracking analysis on historical ecological monitoring data. The historical data backtracking unit stores historical data through a time series database, allowing users to input the start time and end time through a user interaction interface, retrieve historical data within the corresponding time period according to the timestamp, and display and compare and analyze in geographic space;

[0030] Prediction and simulation unit: used to predict and simulate future ecological conditions. The prediction and simulation unit uses model algorithms to predict ecological change trends based on current and historical data, and maps the prediction results into geographic space to generate a geographic layer of future scenarios.

[0031] Optionally, the space mapping unit includes:

[0032] Data preprocessing: preprocess the received ecological monitoring data, including data format conversion, missing value processing and noise filtering. Data format conversion converts the data into a standard format that the system can process through a unified format specification; missing value processing is completed through interpolation or mean value filling; noise filtering removes outliers in the data through a low-pass filter;

[0033] Geocoding: Convert the geographic information in ecological monitoring data into geographic coordinates. The formula for geocoding is: Where λ represents longitude, represents latitude, a represents an address or location description, d represents relevant information in the data, and Geicode represents a geocoding function;

[0034] Spatial interpolation: used to interpolate sparse ecological monitoring data in geographic space to generate continuous geographic layers;

[0035] Geographic layer generation: Map the interpolation results to the geographic coordinate system to form a visual geographic information layer. The formula is: Among them, T(x, y) represents the value of the location (x, y) in the geographic layer, λ and is the longitude and latitude obtained by geocoding, and f is the interpolation result function.

[0036] Optionally, the prediction simulation unit includes:

[0037] Data preparation: used to organize and prepare current and historical ecological monitoring data, including data cleaning, normalization, and feature extraction;

[0038] Model training: Train the ecological change trend prediction model based on current and historical data, specifically using the ARIMA model for training;

[0039] Prediction generation: Use the trained model to predict the data for future periods to obtain the ecological data of each monitoring point in the future period. The prediction generation formula is: in, is the predicted value for the next h periods, t is the current time, h is the predicted time step, p is the number of autoregressive terms, q is the number of moving average terms, is the autoregressive coefficient, θ j is the moving average coefficient, ∈ t+h-j is the error term of the predicted time t+hj;

[0040] Geocoding: The predicted ecological data is mapped to a specific geographical location through the geocoding function Geocode.

[0041] Optionally, the intelligent analysis module includes a data preprocessing unit, an ecological anomaly detection unit, a change trend prediction unit, an ecological risk assessment unit and an analysis result output unit; wherein:

[0042] Data preprocessing unit: connected to the dynamic GIS module, used to receive and preprocess geographic spatial data, data preprocessing includes data cleaning, normalization and feature extraction;

[0043] Ecological anomaly detection unit: connected to the data preprocessing unit, detecting ecological anomalies in geospatial data based on anomaly algorithms of machine learning, wherein the anomaly detection algorithms include isolation forest and support vector machine;

[0044] A change trend prediction unit: connected to the data preprocessing unit, used to predict the change trend of ecological data based on a machine learning model, wherein the trend prediction algorithm includes time series analysis and recursive neural network;

[0045] Ecological risk assessment unit: connected to the data preprocessing unit and the change trend prediction unit, used to perform ecological risk assessment based on the predicted data and existing ecological data. The risk assessment is specifically calculated using a Bayesian network. The conditional probability formula of the Bayesian network is: Among them, P(A|B) represents the probability of event A occurring under condition B, P(B|A) represents the probability of B occurring when event A occurs, and P(A) and P(B) are the independent probabilities of A and B respectively;

[0046] Analysis result output unit: used to summarize and output intelligent analysis results. The analysis results include detected ecological anomalies, predicted ecological change trends and assessed ecological risk levels. The result output formats include reports, charts and geospatial layers.

[0047] Optionally, the multi-dimensional display module includes a three-dimensional stereogram display unit, a heat map display unit, a change trend map display unit and a multi-dimensional data association map display unit: wherein:

[0048] A three-dimensional stereogram display unit: connected to the dynamic GIS module, used to display the ecological monitoring data in the form of a three-dimensional stereogram, specifically using three-dimensional rendering technology to convert two-dimensional maps and related ecological data into three-dimensional models, showing the spatial distribution of terrain and vegetation density, and controlled by a user interface to rotate, zoom and explore the three-dimensional model;

[0049] Heat map display unit: connected to the dynamic GIS module, used to display the density of data points or the value of a predetermined variable through color gradient, so as to intuitively display the data concentration and abnormal points; the heat map is color-coded by ecological data, including temperature, humidity or biological population density;

[0050] A change trend graph display unit, connected to the prediction simulation unit, for displaying the time series analysis results of the ecological monitoring data, specifically displaying the trend of data changes over time, including changes in temperature, rainfall or species number;

[0051] Multi-dimensional data association diagram display unit: connects the data fusion module and the intelligent analysis module, and is used to display the association and interaction between different data dimensions, and to display the relationship between multiple variables by using scatter plot or parallel coordinate graph technology.

[0052] Optionally, the interactive report generation module includes a user demand collection unit, a data extraction unit, a content generation unit, a visual editing unit and a report generation unit; wherein:

[0053] User demand collection unit: used to collect users' specific needs for ecological monitoring reports. The system will personalize the report content, format and time range according to specific needs by selecting the report content, format and time range parameters through the interface.

[0054] Data extraction unit: used to extract data that meets user needs from the ecological monitoring database. The data extraction unit queries and retrieves relevant ecological monitoring data according to the time range, geographical area and data type specified by the user;

[0055] Content generation unit: used to generate the content of ecological monitoring reports. The content generation unit processes and analyzes the extracted data and generates a variety of presentation forms including text descriptions, charts and maps. The report content includes data analysis results, trend forecasts, and ecological risk assessments.

[0056] Visual editing unit: It is used to provide an interface for users to edit and adjust the report content. The visual editing unit allows users to adjust the display mode and text description of charts and maps, and add comments and marks as needed;

[0057] Report generation unit: used to generate the final interactive report from the edited content. The report generation unit supports multiple output formats, including PDF, HTML and dynamic web pages; the generated report contains interactive elements, including click to view detailed data, dynamic charts and maps.

[0058] Optionally, the user interaction module includes a data query unit, an analysis setting unit, a display view customization unit and a user interface management unit; wherein:

[0059] Data query unit: used to provide users with an interface for querying ecological monitoring data. The data query unit includes an input box, a drop-down menu, and a filter, allowing users to perform conditional queries based on time range, geographic area, and data type;

[0060] Analysis setting unit: It is used to provide an interface for users to configure data analysis parameters. The analysis setting unit includes functions of parameter selection, model configuration and analysis options, allowing users to select specific analysis methods and set relevant parameters;

[0061] Display view customization unit: used to provide users with an interface for customizing data display views. The display view customization unit includes functions for selecting chart types, color configuration, and layout adjustment, allowing users to select different chart types and set display properties of charts;

[0062] User interface management unit: used to manage the overall layout and functional integration of the user interaction interface. The user interface management unit ensures the compatibility of the interface on different devices through responsive design. The user interface management unit is also responsible for user authentication and permission management to ensure that different users can only access and operate functions and data within their authority.

[0063] Beneficial effects of the present invention:

[0064] The present invention significantly improves the integration efficiency and accuracy of multi-source ecological data through advanced data fusion technology. By effectively integrating various types of ecological data such as satellite images, sensor data and meteorological records, the system ensures the consistency and integrity of the data. In addition, using the intelligent analysis module based on machine learning, the system can perform ecological anomaly detection, change trend prediction and ecological risk assessment, so that users can extract valuable information from huge data sets to support scientific research and environmental management decisions.

[0065] The present invention greatly enhances the user experience through the interactive report generation module and the multi-dimensional display module. Users can customize data query, analysis settings and display views according to personal needs, so that the report content is more in line with specific application scenarios. The multi-dimensional display module greatly improves the visualization quality and interactivity of the data by providing a variety of display forms such as three-dimensional stereograms, heat maps, change trend maps and multi-dimensional data association maps. These features enable users to understand complex ecological data more intuitively and effectively support the needs of environmental monitoring, educational display, policy formulation and other aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 A schematic diagram of an ecological monitoring achievement display system according to an embodiment of the present invention;

[0068] Figure 2 Schematic diagram of a dynamic GIS module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0070] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0071] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0072] like Figure 1-Figure 2 As shown, the ecological monitoring results display system of nature reserves based on geographic information data includes data acquisition module, data fusion module, dynamic GIS module, intelligent analysis module, multi-dimensional display module, interactive report generation module and user interaction module; among which:

[0073] Data collection module: used to obtain ecological monitoring data from various sensors, satellite images, drone collection systems and ground observation stations in nature reserves. The ecological monitoring data includes meteorological data, water quality data, vegetation coverage data and animal activity data;

[0074] Data fusion module: connected to the data acquisition module, used to fuse multi-source ecological monitoring data. Data fusion includes spatial data alignment, time synchronization and multi-source data consistency correction to ensure the accuracy and integrity of the data;

[0075] Dynamic GIS module: connected to the data fusion module, used to map the fused ecological monitoring data to the geographic space in real time, realizing dynamic spatial visualization. The dynamic GIS module supports real-time data update, historical data backtracking and forecast data simulation;

[0076] Intelligent analysis module: connected to the dynamic GIS module for intelligent analysis of geospatial data, including ecological anomaly detection, trend prediction and ecological risk assessment based on machine learning;

[0077] Multi-dimensional display module: connects the intelligent analysis module and the dynamic GIS module to display ecological monitoring results in various forms, including three-dimensional stereograms, heat maps, change trend maps and multi-dimensional data association maps;

[0078] Interactive report generation module: connected to the multi-dimensional display module, used to generate interactive ecological monitoring reports according to user needs. The report includes data charts, spatial analysis results and intelligent analysis conclusions, and supports users to dynamically query and customize the report content;

[0079] User interaction module: connects the dynamic GIS module and the multi-dimensional display module to provide an interactive interface between the user and the system, allowing the user to query data, perform analysis settings and customize display views through the interactive interface. The interactive interface supports web and mobile applications.

[0080] The data acquisition module includes a meteorological sensor unit, a water quality sensor unit, a vegetation coverage monitoring unit, an animal activity monitoring unit, and a ground observation unit; among which:

[0081] Meteorological sensor unit: used to collect meteorological data in the nature reserve, including temperature, humidity, wind speed, wind direction, rainfall and air pressure parameters, and send the collected data to the data fusion module through wireless transmission technology;

[0082] Water quality sensor unit: used to monitor water quality data of water bodies in nature reserves, including parameters such as pH value, dissolved oxygen, turbidity, conductivity and temperature. The water quality sensor unit sends the collected data to the data fusion module through wired or wireless transmission technology;

[0083] Vegetation coverage monitoring unit: The vegetation coverage data of the nature reserve is obtained by using high-resolution satellite images and drone images. The vegetation coverage monitoring unit includes an image acquisition device and an image processing device. The image acquisition device is used to acquire high-resolution images, and the image processing device is used to analyze the images to extract the information of vegetation coverage rate and send the results to the data fusion module;

[0084] Animal activity monitoring unit: The animal activity data in the nature reserve is obtained through infrared cameras and motion sensors. The animal activity monitoring unit includes infrared cameras and motion sensors. The infrared cameras are used to capture the images of animals, and the motion sensors are used to detect the movement trajectories of animals. The two work together to send the collected data to the data fusion module.

[0085] Ground observation unit: It is arranged at a predetermined location in the nature reserve and is used to monitor the environmental parameters of the predetermined area over a long period of time. The ground observation unit includes a sensor network and a data recording device. The sensor network is used to collect meteorological data and water quality data. The data recording device is used to store the collected data and upload the data to the data fusion module regularly.

[0086] Through the combination of the above units, the data acquisition module can comprehensively and accurately obtain multi-dimensional ecological monitoring data within the nature reserve. The meteorological sensor unit and the water quality sensor unit ensure the real-time monitoring of meteorological and water quality data; the vegetation coverage monitoring unit uses high-resolution satellite images and drone images to achieve high-precision monitoring of vegetation coverage; the animal activity monitoring unit uses infrared cameras and motion sensors to accurately record animal activity information; the ground observation unit ensures long-term monitoring of environmental data in specific areas. These data provide a high-quality foundation for subsequent data fusion, dynamic GIS display and intelligent analysis, ensuring the overall monitoring effect and data reliability of the system.

[0087] The data fusion module includes a spatial data alignment unit, a time synchronization unit, a multi-source data consistency correction unit, and a data storage unit; wherein:

[0088] The spatial data alignment unit is used to align the spatial data from different sensors and observation systems. The spatial data alignment unit uses geographic coding and coordinate conversion technology to map various types of data to a unified geographic coordinate system to ensure that spatial data from different data sources are analyzed within the same geographic reference frame. The formula for spatial data alignment is as follows: Among them, x and y represent the original coordinates, x' and y' represent the transformed coordinates, a, b, c, d are the rotation and scaling parameters, and e and f are the translation parameters;

[0089] Time synchronization unit: used to synchronize the multi-source ecological monitoring data. The time synchronization unit uses timestamp technology and time series analysis methods to align data recorded at different times to a unified time base to ensure the consistency of the time of each data source. The formula for time synchronization processing is as follows: t'=t+Δt, where t represents the original time, t' represents the time after synchronization, and Δt represents the time correction value. The correction value is calculated by the timestamp difference: Δt=t r -t o , where t r is the reference timestamp, t o is the original timestamp;

[0090] Multi-source data consistency correction unit: used to perform consistency correction on the fused multi-source ecological monitoring data. The multi-source data consistency correction unit uses data cleaning, outlier detection and data interpolation technology to correct the differences and errors between data sources to ensure the integrity and accuracy of the data. The formula for data consistency correction is: D c =w·D i +b, where D c represents the corrected data, D i represents the original data, w and b are correction coefficients, which are calculated by the least squares method. The formula for outlier detection is:

[0091] Outlier = |D i -μ|>k·σ, where μ is the data mean, s is the standard deviation, and k is the detection threshold;

[0092] Data storage unit: used to store processed and corrected ecological monitoring data. The data storage unit adopts an efficient database management system to support rapid access and management of large-scale data;

[0093] Through the organic combination of the above units, the data fusion module can efficiently process multi-source ecological monitoring data from different sensors and observation systems, ensuring that the ecological monitoring data output by the data fusion module are of high quality and high credibility, providing a reliable data foundation for subsequent dynamic GIS display and intelligent analysis.

[0094] The dynamic GIS module includes a data receiving unit, a spatial mapping unit, a real-time updating unit, a historical data backtracking unit, and a prediction simulation unit; among which:

[0095] Data receiving unit: used to receive the fused and corrected ecological monitoring data. The data receiving unit can receive updated data from multiple data sources in real time and transmit the data to the spatial mapping unit;

[0096] Spatial mapping unit: used to map the received ecological monitoring data into geographic space. The spatial mapping unit uses geographic coding and spatial interpolation technology to accurately locate the data in the geographic coordinate system and generate the corresponding geographic layer;

[0097] Real-time update unit: used to dynamically update the geospatial display. The real-time update unit ensures that the geospatial display content is updated in real time as the data changes through timed refresh and event trigger mechanisms, providing the latest ecological monitoring information. The timed refresh mechanism automatically updates the data based on a preset time interval (for example, once a minute), and the event trigger mechanism immediately updates through monitoring data change events (such as new data arrival or key parameter changes);

[0098] Historical data backtracking unit: used to conduct backtracking analysis on historical ecological monitoring data. The historical data backtracking unit stores historical data through a time series database, allowing users to input the start time and end time through the user interaction interface, retrieve historical data within the corresponding time period according to the timestamp, and display and compare and analyze in geographic space;

[0099] Prediction and simulation unit: used to predict and simulate future ecological conditions. The prediction and simulation unit uses model algorithms based on current and historical data to predict ecological change trends, and maps the prediction results into geographic space to generate geographic layers of future scenarios. The above units work together to ensure that the dynamic GIS module can comprehensively and accurately display the ecological monitoring results of nature reserves, providing a reliable data basis for subsequent intelligent analysis and decision-making.

[0100] The spatial mapping unit includes:

[0101] Data preprocessing: preprocess the received ecological monitoring data, including data format conversion, missing value processing and noise filtering. Data format conversion converts the data into a standard format that the system can process through a unified format specification; missing value processing is completed through interpolation or mean value filling; noise filtering removes outliers in the data through a low-pass filter;

[0102] Geocoding: convert the geographic information (such as address, location description, etc.) in the ecological monitoring data into geographic coordinates (longitude and latitude). The formula for geocoding is: Where λ represents longitude, represents latitude, a represents an address or location description, d represents relevant information in the data, and Geocode represents a geocoding function;

[0103] Spatial interpolation: used to interpolate sparse ecological monitoring data in geographic space to generate continuous geographic layers; spatial interpolation algorithms include Kriging interpolation (Kriging) and inverse distance weighting (IDW). The specific formula is as follows: Kriging interpolation formula is: Among them, Z(s0) represents the value at the predicted position s0, Z(s i ) indicates the known position s i The value of λ i is the weight coefficient, which is calculated by the semivariogram function; the inverse distance weighted formula is: Among them, d i Indicates the predicted position s0 to the known position s i The distance, p is the power parameter, generally 2;

[0104] Geographic layer generation: used to generate the corresponding geographic layer according to the results of geographic coding and spatial interpolation. Geographic layer generation is specifically formed by mapping the interpolation results into the geographic coordinate system to form a visual geographic information layer. The formula is: Among them, T(x, y) represents the value of the location (x, y) in the geographic layer, λ and is the longitude and latitude obtained by geocoding, and f is the interpolation result function; the above steps work together to ensure that the spatial mapping unit can accurately and reliably display the ecological monitoring data of nature reserves, providing a solid foundation for subsequent dynamic GIS display and intelligent analysis.

[0105] The forecast simulation unit includes:

[0106] Data preparation: used to organize and prepare current and historical ecological monitoring data, including data cleaning, normalization and feature extraction. Data cleaning improves data quality by removing outliers and filling missing values. Normalization eliminates scale differences by scaling data to a uniform range. Feature extraction improves the predictive power of the model by selecting relevant time series features.

[0107] Model training: Train the ecological change trend prediction model based on current and historical data, specifically using the ARIMA model for training; the specific steps include:

[0108] Step 1: Determine the parameters p (number of autoregressive terms), d (number of differences), and q (number of moving average terms) of the ARIMA model; commonly used methods include observing the autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs;

[0109] Step 2: Perform model fitting and use historical data to estimate model parameters. The specific formula is: Among them, y t is the predicted value at time t, c is a constant term, is the autoregressive coefficient, θ i is the moving average coefficient, ∈ t is the error term at time t;

[0110] Step 3: Check the residuals of the fitted model to ensure that the residuals are white noise (i.e., have a mean of zero and no autocorrelation), which can be statistically tested using the Ljung-Box test.

[0111] Prediction generation: Based on the trained ARIMA model, the ecological change trend is predicted. The trained model is used to predict the data of the future period to obtain the ecological data of each monitoring point in the future period. The prediction generation formula is: in, is the predicted value for the next h period, t is the current time, h is the predicted time step, p is the autoregressive coefficient, q is the number of moving average items, is the autoregressive coefficient, θ j is the moving average coefficient, ∈ t+h-j is the error term of the predicted time t+hj;

[0112] Geocoding: Convert the predicted future ecological data into geographic coordinates, and map the predicted ecological data to specific geographic locations through the geocoding function Geocode;

[0113] Generation of geographic layers: The predicted data are spatially interpolated and visualized to generate geographic layers displayed in the geographic information system. The formula for generating geographic layers is the same as above. The above steps work together to ensure that the prediction simulation unit can accurately and reliably predict the ecological change trends of nature reserves and provide scientific decision-making support for managers.

[0114] The intelligent analysis module includes a data preprocessing unit, an ecological anomaly detection unit, a change trend prediction unit, an ecological risk assessment unit, and an analysis result output unit; among which:

[0115] Data preprocessing unit: connected to the dynamic GIS module, used to receive and preprocess geospatial data. Data preprocessing includes data cleaning, normalization and feature extraction. Data cleaning improves data quality by removing outliers and filling missing values. Normalization eliminates scale differences by scaling data to a uniform range. Feature extraction improves analysis capabilities by selecting relevant time series features.

[0116] Ecological anomaly detection unit: connected to the data preprocessing unit, detects ecological anomalies in geospatial data based on anomaly algorithms based on machine learning. Anomaly detection algorithms include Isolation Forest and Support Vector Machine (SVM). The formula of Isolation Forest algorithm is as follows: Where I(x) is the anomaly score of point x, E(h(x)) is the average tree height, c(n) is the normalization constant, and n is the number of samples;

[0117] Change trend prediction unit: connected to the data preprocessing unit, used to predict the change trend of ecological data based on the machine learning model. The trend prediction algorithm includes time series analysis and recursive neural network (RNN). The ARIMA model formula used in time series analysis is as follows: Among them, y t is the predicted value at time t, c is a constant term, is the autoregressive coefficient, θ i is the moving average coefficient, ∈ t is the error term;

[0118] Ecological risk assessment unit: connects the data preprocessing unit and the change trend prediction unit, and is used to perform ecological risk assessment based on the predicted data and existing ecological data. The risk assessment is specifically calculated using the Bayesian network, and the conditional probability formula of the Bayesian network is: Among them, P(A|B) represents the probability of event A occurring under condition B, P(B|A) represents the probability of B occurring when event A occurs, and P(A) and P(B) are the independent probabilities of A and B respectively;

[0119] Analysis result output unit: used to summarize and output intelligent analysis results, which include detected ecological anomalies, predicted ecological change trends and assessed ecological risk levels. The result output formats include reports, charts and geospatial layers. Through the detailed explanation of the above units, the intelligent analysis module of the present invention can efficiently perform intelligent analysis on geospatial data, and the data preprocessing unit ensures the quality and consistency of the data. The ecological anomaly detection unit detects anomalies in geospatial data through machine learning algorithms. The change trend prediction unit predicts the change trend of ecological data through time series analysis and recursive neural network models. The ecological risk assessment unit performs risk assessment based on predicted data and existing ecological data, and calculates ecological risks using Bayesian networks. The analysis result output unit summarizes and outputs intelligent analysis results, providing intuitive and detailed ecological monitoring reports. These units work together to ensure that the intelligent analysis module can comprehensively and accurately analyze the ecological monitoring data of nature reserves, and provide scientific support and reference for decision makers.

[0120] The multi-dimensional display module includes a three-dimensional stereogram display unit, a heat map display unit, a change trend map display unit and a multi-dimensional data association map display unit:

[0121] 3D Stereoscopic Map Display Unit: Connected to the dynamic GIS module, it is used to display ecological monitoring data in the form of 3D stereoscopic maps. Specifically, it uses 3D rendering technology to convert 2D maps and related ecological data into 3D models to display the spatial distribution of terrain and vegetation density, enhance visual effects and users' spatial perception ability, and control through the user interface to rotate, zoom and explore the 3D model to obtain views from different angles and gain a deeper understanding of the ecological status of the region;

[0122] Heat map display unit: connected to the dynamic GIS module, used to display the density of data points or the value of a predetermined variable through color gradients, so as to intuitively display data concentration and abnormal points; heat maps color-code ecological data, including temperature, humidity or biological population density, to provide an intuitive view to identify high-density areas and potential ecological problems;

[0123] The trend chart display unit is connected to the prediction simulation unit and is used to display the time series analysis results of ecological monitoring data. Specifically, it displays the trend of data changes over time, including changes in temperature, rainfall or species number. Through charts and curves, the trend chart can help users understand past change patterns and predict possible future trends.

[0124] Multi-dimensional data association diagram display unit: connects the data fusion module and the intelligent analysis module, and is used to display the association and interaction between different data dimensions. By using scatter plots or parallel coordinates diagram technology, the relationship between multiple variables can be displayed. For example, the relationship between soil quality and vegetation health, or the correlation between climate change and animal migration patterns can be displayed. Through the detailed explanation of the above units, the multi-dimensional display module can comprehensively display the results of ecological monitoring in various forms. The three-dimensional stereogram display unit enhances the spatial representation of data and the user's interactive experience through advanced three-dimensional rendering technology. The heat map display unit provides an intuitive way to identify high-density areas and anomalies in ecological data. The change trend diagram display unit helps users understand the change trend and historical background of ecological data through time series analysis. The multi-dimensional data association diagram display unit reveals the complex relationship between different ecological variables through advanced data visualization technology, which promotes a deeper understanding of ecosystem dynamics. These units work together to ensure that the multi-dimensional display module can provide comprehensive, accurate and easy-to-understand data display to support scientific research and effective environmental management decisions.

[0125] The interactive report generation module includes a user demand collection unit, a data extraction unit, a content generation unit, a visual editing unit and a report generation unit; wherein:

[0126] User demand collection unit: used to collect users' specific needs for ecological monitoring reports. The system will personalize the report content, format and time range parameters according to specific needs. The user demand collection unit includes form input, option selection and free text input functions to ensure that the user's reporting needs can be fully captured.

[0127] Data extraction unit: used to extract data that meets user needs from the ecological monitoring database. The data extraction unit queries and retrieves relevant ecological monitoring data according to the time range, geographical area and data type specified by the user to ensure that the extracted data is accurate and meets user needs;

[0128] Content generation unit: used to generate the content of ecological monitoring reports. The content generation unit processes and analyzes the extracted data and generates a variety of presentation forms including text descriptions, charts and maps. The report content includes data analysis results, trend forecasts, and ecological risk assessments.

[0129] Visual editing unit: It is used to provide an interface for users to edit and adjust the report content. The visual editing unit allows users to adjust the display mode and text description of charts and maps as needed, add comments and marks, and ensure that the report content is accurate and readable. After editing, users can also preview the final report;

[0130] Report generation unit: used to generate the final interactive report from the edited content. The report generation unit supports multiple output formats, including PDF, HTML and dynamic web pages. Users can choose the appropriate format to save and share; the generated report contains interactive elements, including clicks to view detailed data, dynamic charts and maps, to enhance the user experience; through the collaborative work of the above units, it can ensure that the interactive report generation module can provide comprehensive, accurate and user-friendly ecological monitoring reports, providing strong support for scientific research and environmental management.

[0131] The user interaction module includes a data query unit, an analysis setting unit, a display view customization unit, and a user interface management unit; wherein:

[0132] Data query unit: used to provide users with an interface for querying ecological monitoring data. The data query unit includes an input box, a drop-down menu, and a filter, allowing users to perform conditional queries based on time range, geographic area, and data type. After the user enters the query conditions, the system will return the monitoring data that meets the conditions in real time and display the query results on the interface;

[0133] Analysis setting unit: It is used to provide an interface for users to configure data analysis parameters. The analysis setting unit includes functions of parameter selection, model configuration and analysis options. Users can select specific analysis methods (such as ecological anomaly detection, change trend prediction, etc.) and set relevant parameters (such as time interval, analysis model parameters, etc.). The system performs data analysis according to the user's settings and returns the analysis results to the user;

[0134] Display view customization unit: It is used to provide users with an interface for customizing data display views. The display view customization unit includes functions for selecting chart types, color configuration, and layout adjustment, allowing users to select different chart types (such as three-dimensional charts, heat maps, etc.) and set the display properties of charts. Users can also adjust the layout of charts and maps through drag-and-drop operations to create personalized display views;

[0135] User interface management unit: used to manage the overall layout and functional integration of the user interaction interface. The user interface management unit ensures the compatibility of the interface on different devices (such as computers, tablets, and mobile phones) through responsive design. The user interface management unit is also responsible for user identity authentication and permission management to ensure that different users can only access and operate functions and data within their authority. Through the combination of the above units, the user interaction module can provide an efficient and flexible interactive interface, allowing users to query data, set up analysis, and customize display views.

[0136] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0137] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. The ecological monitoring results display system of nature reserves based on geographic information data is characterized by: It includes data acquisition module, data fusion module, dynamic GIS module, intelligent analysis module, multi-dimensional display module, interactive report generation module and user interaction module; among which: Data collection module: used to obtain ecological monitoring data from various sensors, satellite images, drone collection systems and ground observation stations in nature reserves, including meteorological data, water quality data, vegetation coverage data and animal activity data; Data fusion module: connected to the data acquisition module, used for fusion processing of multi-source ecological monitoring data, the data fusion includes spatial data alignment, time synchronization and multi-source data consistency correction; Dynamic GIS module: connected to the data fusion module, used to map the fused ecological monitoring data to the geographic space in real time to achieve dynamic spatial visualization. The dynamic GIS module supports real-time data update, historical data backtracking and forecast data simulation; Intelligent analysis module: connected to the dynamic GIS module, used for intelligent analysis of geographic spatial data, including ecological anomaly detection, change trend prediction and ecological risk assessment based on machine learning; Multi-dimensional display module: connected to the intelligent analysis module and the dynamic GIS module, used to display ecological monitoring results in various forms, including three-dimensional stereograms, heat maps, change trend maps and multi-dimensional data association maps; Interactive report generation module: connected to the multi-dimensional display module, used to generate an interactive ecological monitoring report according to user needs, the report includes data charts, spatial analysis results and intelligent analysis conclusions; User interaction module: connects the dynamic GIS module and the multi-dimensional display module, and is used to provide an interactive interface between the user and the system, allowing the user to perform data query, analysis settings and display view customization through the interactive interface. The interactive interface supports web and mobile applications.

2. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 1 is characterized in that: The data acquisition module includes a meteorological sensor unit, a water quality sensor unit, a vegetation coverage monitoring unit, an animal activity monitoring unit and a ground observation unit; wherein: Meteorological sensor unit: used to collect meteorological data within the nature reserve, including parameters such as temperature, humidity, wind speed, wind direction, rainfall and air pressure; Water quality sensor unit: used to monitor water quality data of water bodies in nature reserves, including parameters such as pH, dissolved oxygen, turbidity, conductivity and temperature; Vegetation coverage monitoring unit: the vegetation coverage data of the nature reserve is obtained by using high-resolution satellite images and drone images. The vegetation coverage monitoring unit includes an image acquisition device and an image processing device. The image acquisition device is used to acquire high-resolution images, and the image processing device is used to analyze the images to extract information on vegetation coverage and send the results to the data fusion module. Animal activity monitoring unit: The animal activity data in the nature reserve is obtained through an infrared camera and a motion sensor. The animal activity monitoring unit includes an infrared camera and a motion sensor. The infrared camera is used to capture the image of the animal, and the motion sensor is used to detect the movement trajectory of the animal. Ground observation unit: It is arranged at a predetermined location in a nature reserve and is used for long-term monitoring of environmental parameters in a predetermined area. The ground observation unit includes a sensor network and a data recording device. The sensor network is used to collect meteorological data and water quality data. The data recording device is used to store the collected data and upload the data to the data fusion module regularly.

3. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 1 is characterized in that: The data fusion module includes a spatial data alignment unit, a time synchronization unit, a multi-source data consistency correction unit, and a data storage unit; wherein: A spatial data alignment unit, used for aligning spatial data from different sensors and observation systems, wherein the spatial data alignment unit uses geographic coding and coordinate conversion technology to map various types of data into a unified geographic coordinate system; Time synchronization unit: used to perform time synchronization processing on multi-source ecological monitoring data. The time synchronization unit uses timestamp technology and time series analysis methods to align data recorded at different times to a unified time reference to ensure the time consistency of each data source; Multi-source data consistency correction unit: used to perform consistency correction on the fused multi-source ecological monitoring data. The multi-source data consistency correction unit uses data cleaning, outlier detection and data interpolation technology to correct the differences and errors between the data sources to ensure the integrity and accuracy of the data; Data storage unit: used to store processed and corrected ecological monitoring data.

4. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 1 is characterized in that: The dynamic GIS module includes a data receiving unit, a spatial mapping unit, a real-time updating unit, a historical data backtracking unit and a prediction simulation unit; wherein: Data receiving unit: used to receive the integrated and corrected ecological monitoring data; Spatial mapping unit: used to map the received ecological monitoring data into geographic space. The spatial mapping unit accurately locates the data in the geographic coordinate system through geographic coding and spatial interpolation technology, and generates corresponding geographic layers; Real-time update unit: used to dynamically update the geospatial display. The real-time update unit ensures that the geospatial display content is updated in real time as the data changes through timed refresh and event trigger mechanisms. The timed refresh mechanism automatically updates the data based on a preset time interval, and the event trigger mechanism immediately updates by monitoring data change events; Historical data backtracking unit: used to conduct backtracking analysis on historical ecological monitoring data. The historical data backtracking unit stores historical data through a time series database, allowing users to input the start time and end time through a user interaction interface, retrieve historical data within the corresponding time period according to the timestamp, and display and compare and analyze in geographic space; Prediction and simulation unit: used to predict and simulate future ecological conditions. The prediction and simulation unit uses model algorithms to predict ecological change trends based on current and historical data, and maps the prediction results into geographic space to generate a geographic layer of future scenarios.

5. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 4 is characterized in that: The space mapping unit comprises: Data preprocessing: preprocess the received ecological monitoring data, including data format conversion, missing value processing and noise filtering. Data format conversion converts the data into a standard format that the system can process through a unified format specification; missing value processing is completed through interpolation or mean value filling; noise filtering removes outliers in the data through a low-pass filter; Geocoding: Convert the geographic information in ecological monitoring data into geographic coordinates. The formula for geocoding is: Where λ represents longitude, represents latitude, a represents an address or location description, d represents relevant information in the data, and Geocode represents a geocoding function; Spatial interpolation: used to interpolate sparse ecological monitoring data in geographic space to generate continuous geographic layers; Geographic layer generation: Map the interpolation results to the geographic coordinate system to form a visual geographic information layer. The formula is: Among them, T(x, y) represents the value of the location (x, y) in the geographic layer, λ and is the longitude and latitude obtained by geocoding, and f is the interpolation result function.

6. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 4 is characterized in that: The prediction simulation unit comprises: Data preparation: used to organize and prepare current and historical ecological monitoring data, including data cleaning, normalization, and feature extraction; Model training: Train the ecological change trend prediction model based on current and historical data, specifically using the ARIMA model for training; Prediction generation: Use the trained model to predict the data for future periods to obtain the ecological data of each monitoring point in the future period. The prediction generation formula is: in, is the predicted value for the next h periods, t is the current time, h is the predicted time step, p is the number of autoregressive terms, q is the number of moving average terms, is the autoregressive coefficient, θ j is the moving average coefficient, ∈ t+h-j is the error term of the predicted time t+hj; Geocoding: The predicted ecological data is mapped to a specific geographical location through the geocoding function Geocode.

7. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 1 is characterized in that: The intelligent analysis module includes a data preprocessing unit, an ecological anomaly detection unit, a change trend prediction unit, an ecological risk assessment unit and an analysis result output unit; wherein: Data preprocessing unit: connected to the dynamic GIS module, used to receive and preprocess geographic spatial data, data preprocessing includes data cleaning, normalization and feature extraction; Ecological anomaly detection unit: connected to the data preprocessing unit, detecting ecological anomalies in geospatial data based on anomaly algorithms of machine learning, wherein the anomaly detection algorithms include isolation forest and support vector machine; A change trend prediction unit: connected to the data preprocessing unit, used to predict the change trend of ecological data based on a machine learning model, wherein the trend prediction algorithm includes time series analysis and recursive neural network; Ecological risk assessment unit: connected to the data preprocessing unit and the change trend prediction unit, used to perform ecological risk assessment based on the predicted data and existing ecological data. The risk assessment is specifically calculated using a Bayesian network. The conditional probability formula of the Bayesian network is: Among them, P(A|B) represents the probability of event A occurring under condition B, P(B|A) represents the probability of B occurring when event A occurs, and P(A) and P(B) are the independent probabilities of A and B respectively; Analysis result output unit: used to summarize and output intelligent analysis results. The analysis results include detected ecological anomalies, predicted ecological change trends and assessed ecological risk levels. The result output formats include reports, charts and geospatial layers.

8. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 1 is characterized in that: The multi-dimensional display module includes a three-dimensional stereogram display unit, a heat map display unit, a change trend map display unit and a multi-dimensional data association map display unit: wherein: A three-dimensional stereogram display unit: connected to the dynamic GIS module, used to display the ecological monitoring data in the form of a three-dimensional stereogram, specifically using three-dimensional rendering technology to convert two-dimensional maps and related ecological data into three-dimensional models, showing the spatial distribution of terrain and vegetation density, and controlled by a user interface to rotate, zoom and explore the three-dimensional model; Heat map display unit: connected to the dynamic GIS module, used to display the density of data points or the value of a predetermined variable through color gradient, so as to intuitively display the data concentration and abnormal points; the heat map is color-coded by ecological data, including temperature, humidity or biological population density; A change trend graph display unit, connected to the prediction simulation unit, for displaying the time series analysis results of the ecological monitoring data, specifically displaying the trend of data changes over time, including changes in temperature, rainfall or species number; Multi-dimensional data association diagram display unit: connects the data fusion module and the intelligent analysis module, and is used to display the association and interaction between different data dimensions, and to display the relationship between multiple variables by using scatter plot or parallel coordinate graph technology.

9. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 1 is characterized in that: The interactive report generation module includes a user demand collection unit, a data extraction unit, a content generation unit, a visual editing unit and a report generation unit; wherein: User demand collection unit: used to collect users' specific needs for ecological monitoring reports. The system will personalize the report content, format and time range according to specific needs by selecting the report content, format and time range parameters through the interface. Data extraction unit: used to extract data that meets user needs from the ecological monitoring database. The data extraction unit queries and retrieves relevant ecological monitoring data according to the time range, geographical area and data type specified by the user; Content generation unit: used to generate the content of ecological monitoring reports. The content generation unit processes and analyzes the extracted data and generates a variety of presentation forms including text descriptions, charts and maps. The report content includes data analysis results, trend forecasts, and ecological risk assessments. Visual editing unit: It is used to provide an interface for users to edit and adjust the report content. The visual editing unit allows users to adjust the display mode and text description of charts and maps, and add comments and marks as needed; Report generation unit: used to generate the final interactive report from the edited content. The report generation unit supports multiple output formats, including PDF, HTML and dynamic web pages; the generated report contains interactive elements, including click to view detailed data, dynamic charts and maps.

10. The system for displaying ecological monitoring results of nature reserves based on geographic information data according to claim 1 is characterized in that: The user interaction module includes a data query unit, an analysis setting unit, a display view customization unit and a user interface management unit; wherein: Data query unit: used to provide users with an interface for querying ecological monitoring data. The data query unit includes an input box, a drop-down menu, and a filter, allowing users to perform conditional queries based on time range, geographic area, and data type; Analysis setting unit: It is used to provide an interface for users to configure data analysis parameters. The analysis setting unit includes functions of parameter selection, model configuration and analysis options. Users can select specific analysis methods and set related parameters. Display view customization unit: used to provide users with an interface for customizing data display views. The display view customization unit includes functions for selecting chart types, color configuration, and layout adjustment, allowing users to select different chart types and set display properties of charts; User interface management unit: used to manage the overall layout and functional integration of the user interaction interface. The user interface management unit ensures the compatibility of the interface on different devices through responsive design. The user interface management unit is also responsible for user authentication and permission management to ensure that different users can only access and operate functions and data within their authority.

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