Ecological restoration management evaluation system for surface mine

Abstract

The invention relates to the technical field of mine ecological restoration management, in particular to a surface mine ecological restoration management evaluation system, which comprises a data acquisition module, a database module, a data index system construction module, a restoration strategy generation module, a restoration effect evaluation module, a visual display module, a management decision support module and an evaluation model module. Through dynamic updating of the data index system and timely adjustment of the restoration strategy, the system can adapt to various changes in the ecological restoration process, and smooth restoration work is ensured. Meanwhile, due to real-time evaluation of the repairing effect and scientific formulation of management decisions, the efficiency and effect of repairing work are improved, and waste of resources and blindness of repairing work are avoided. In addition, the dynamic adjustment mechanism can discover and solve problems occurring in the repairing process in time, the repairing risk is reduced, and the success rate and sustainability of repairing work are improved.

Description

Technical Field

[0001] This invention relates to the field of mine ecological restoration management technology, specifically an evaluation system for open-pit mine ecological restoration management. Background Technology

[0002] With rapid economic development, while open-pit mining has met the demand for mineral resources, it has also caused serious ecological damage, such as reduced vegetation cover, degraded soil fertility, increased soil erosion, and decreased biodiversity. To achieve sustainable development of the ecological environment, ecological restoration of open-pit mines has become particularly important. To effectively promote ecological restoration, a scientific and reasonable management and evaluation system is needed to guide and optimize the restoration process.

[0003] However, existing open-pit mine ecological restoration management and evaluation systems have many shortcomings. The data indicator system construction module lacks dynamic updating capabilities, failing to adjust according to different ecological restoration stages and target characteristics, and thus struggling to adapt to dynamic changes during the ecological restoration process. The restoration strategy generation module, when formulating restoration plans, fails to fully integrate ecological principles, mathematical statistics methods, decision-making models, and expert knowledge bases, resulting in insufficient scientific rigor and specificity of the restoration plans. The management decision support module also cannot dynamically optimize restoration plans based on restoration effect evaluation results, lacking comprehensive consideration of multi-dimensional factors such as environmental, economic, and social goals. Furthermore, existing systems lack the function of long-term monitoring and feedback analysis of the restored ecosystem, making it difficult to ensure the long-term success of ecological restoration work and the sustainable development of the ecosystem. These problems make existing open-pit mine ecological restoration management and evaluation systems inadequate to meet the needs of efficient, scientific, and sustainable ecological restoration. Summary of the Invention

[0004] To address the problems in existing technologies, this invention provides an evaluation system for ecological restoration management of open-pit mines.

[0005] The technical solution adopted by this invention to solve its technical problem is: an open-pit mine ecological restoration management and evaluation system, including a data acquisition module, a database module, a data indicator system construction module, a restoration strategy generation module, a restoration effect evaluation module, a visualization display module, a management decision support module, and an evaluation model module. The data acquisition module is used to collect data before and during the ecological restoration of the open-pit mine, including multi-dimensional data such as soil, vegetation, hydrology, meteorology, and mining activities, and transmits the collected data to the database module for storage. The database module is connected to the data acquisition module and is used to store various types of data related to the ecological restoration of open-pit mines, including pre-restoration data, data during the restoration process, and pre-stored information such as multi-level ecological evaluation indicators and their weight coefficients corresponding to different ecological restoration stages and restoration goals. The data indicator system construction module is connected to the database module. Based on the data stored in the database module, it automatically generates a data indicator system library covering multiple dimensions of ecosystem structural integrity, functional stability, and biodiversity at regular intervals. This module can obtain data from the database module before and during restoration according to different ecological restoration stages and target characteristics, analyze and process the data, generate a dynamically updated data indicator system library, and store it in the database module. At the same time, it sends a notification of the data indicator system library update to the restoration strategy generation module, providing a quantitative basis for the formulation of restoration strategies. The restoration strategy generation module is connected to the database module and the data indicator system construction module. It is built based on ecological principles and mathematical statistics methods. According to the indicators and weights retrieved from the data indicator system library, combined with the current ecological status data of the open-pit mine obtained from the database module, it uses an integrated decision model and an expert knowledge base pre-stored in the database module to perform quantitative analysis on the processed data. This module can output a comprehensive analysis of the current ecological status of the open-pit mine and the scores of each sub-indicator. Based on the analysis results, it generates targeted ecological restoration plans. At the same time, it performs feasibility and cost-benefit analysis on the plans, selects the optimal plan, stores it in the database module, provides alternative plans for the management decision support module, and sends a plan display request to the visualization display module. The restoration effect evaluation module is connected to the database module and the restoration strategy generation module. It is used to conduct phased restoration effect evaluation and final restoration effect evaluation. It compares and analyzes the pre-restoration mine ecological status data, data changes during the restoration process, and the expected restoration effect in the restoration plan generated by the restoration strategy generation module to evaluate the restoration effect. At the end of each restoration phase, it automatically retrieves relevant data from the database module, performs comparative analysis, evaluates the restoration effect, and stores the evaluation results in the database module. At the same time, it sends an evaluation result display request to the visualization module and an evaluation result notification to the management decision support module. In the final restoration effect evaluation, it combines comprehensive indicators such as ecosystem service value evaluation and ecosystem health status evaluation to provide comprehensive restoration effect feedback to the management decision support module. The visualization module is connected to the database module, the restoration strategy generation module, and the restoration effect evaluation module, respectively. It is used to visualize the data, ecological restoration plans, and restoration effect evaluation results that need to be displayed. It presents complex data and information to users and decision-makers in an intuitive and easy-to-understand way through various forms such as chart display, map display, 3D model display, and dynamic simulation display. At the same time, it provides users with the function of customizing the display content and display format to meet the needs of different users. The management decision support module is connected to the restoration effect evaluation module. Based on the evaluation results of the restoration effect evaluation module, the module uses the data indicator system construction module and the restoration strategy generation module to formulate the next stage restoration plan. This module uses a multi-objective decision analysis method to comprehensively consider factors from multiple dimensions such as environmental, economic and social goals of ecological restoration, to comprehensively evaluate and select different restoration schemes and measures, determine the optimal restoration strategy, and store the next stage restoration plan in the database module. At the same time, it sends a notification to the restoration strategy generation module to formulate the next stage restoration plan, so as to realize the dynamic optimization and continuous improvement of the restoration process. The evaluation model module is used to comprehensively evaluate the entire open-pit mine ecological restoration process. It establishes an evaluation index system from multiple aspects, including the accuracy of data collection, the efficiency of database management, the rationality of data indicator system construction, the scientific nature of restoration strategy generation, the accuracy of restoration effect evaluation, the effect of visualization, and the scientific nature of management decision support. It quantifies and analyzes the entire restoration process, and the evaluation results are stored in the database module, providing a basis for the continuous improvement and optimization of the system, and ensuring the efficiency, scientific nature, and sustainability of the entire ecological restoration process.

[0006] Preferably, the data acquisition module includes various sensors and data input devices, capable of collecting soil data, vegetation data, hydrological data, meteorological data, and data related to mining activities in open-pit mines. Soil data includes soil texture, soil fertility, soil pH, and soil heavy metal content; vegetation data includes vegetation coverage, vegetation species, and vegetation growth status; hydrological data includes surface water quality, groundwater level, and surface runoff; meteorological data includes temperature, precipitation, wind speed, and wind direction; and mining activity-related data includes ore extraction volume, waste rock dumping volume, and mining area area. The data acquisition module preprocesses the collected data before transmitting it to the database module. Preprocessing includes data cleaning, format conversion, and data verification. Data verification uses an error range determination formula.

[0007] Where x is the collected data value, μ is the standard reference value of the data, and δ is the allowable error range.

[0008] Preferably, the database module uses a combination of relational and non-relational databases to store and manage different types of data. The relational database stores structured data, including but not limited to ecological evaluation indicators and their weighting coefficients, and parameters of restoration plans. The non-relational database stores unstructured data, including but not limited to remote sensing image data and mine topographic data. The database module provides data interfaces for other modules to read and write data. The data read efficiency is calculated using the following formula:

[0009] Where E is the data reading efficiency, N is the amount of data read, and t r This refers to the read time.

[0010] Preferably, in the data indicator system construction module, the ecological evaluation indicators and their weight coefficients corresponding to different ecological restoration stages are set according to the temporal process and target characteristics of ecological restoration. This module can obtain data before and during restoration from the database module according to the characteristics and needs of different ecological restoration stages, perform in-depth analysis and processing of the data, generate a dynamically updated data indicator system library, and store it in the database module. At the same time, it sends a notification of data indicator system library update to the restoration strategy generation module. The indicator weights are calculated using the analytic hierarchy process formula:

[0011] Where wi is the weight of the i-th indicator, aij is the element of the judgment matrix, and n is the number of indicators.

[0012] Preferably, after receiving a notification of an update to the data indicator system library, the restoration strategy generation module retrieves the latest indicators and weights from the database module. Combined with the current ecological status data of the open-pit mine obtained from the database module, it performs quantitative analysis using a decision-making model and expert knowledge base. Based on the analysis results, this module can generate multiple ecological restoration plans, conduct feasibility and cost-benefit analyses on these plans, select the optimal plan, store the generated ecological restoration plan in the database module, and send a plan display request to the visualization module. Simultaneously, it periodically updates and optimizes the restoration plans in the database module to adapt to the dynamic changes in the open-pit mine ecological restoration process. The cost-benefit analysis uses the net present value formula:

[0013] Where NPV is the net present value, Ct is the cash flow in period t, r is the discount rate, and T is the project calculation period.

[0014] Preferably, at the end of each restoration phase, the restoration effect evaluation module automatically retrieves pre-restoration mine ecological status data, data changes during restoration, and the predicted restoration effect data from the restoration plan generated by the restoration strategy generation module from the database module. It then performs comparative analysis to evaluate the restoration effect and stores the evaluation results in the database module. Simultaneously, it sends an evaluation result display request to the visualization module and an evaluation result notification to the management decision support module. In the final restoration effect evaluation, the module combines comprehensive indicators such as ecosystem service value assessment and ecosystem health status assessment to provide comprehensive restoration effect feedback to the management decision support module. The comprehensive restoration effect scoring formula is:

[0015] Where S is the overall score, w i Let s be the weight of the i-th indicator. i Let be the score of the i-th indicator, and m be the number of indicators.

[0016] Preferably, after receiving the evaluation result notification from the restoration effect evaluation module, the management decision support module calls the data indicator system construction module and the restoration strategy generation module to formulate the next-stage restoration plan based on the evaluation results and store the next-stage restoration plan in the database module. This module uses a multi-objective decision analysis method to comprehensively consider multiple dimensions of factors such as environmental, economic, and social goals of ecological restoration, to comprehensively evaluate and select different restoration schemes and measures, determine the optimal restoration strategy, store the next-stage restoration plan in the database module, and simultaneously send a notification to the restoration strategy generation module to formulate the next-stage restoration plan, thereby realizing dynamic optimization and continuous improvement of the restoration process. The multi-objective decision comprehensive value calculation formula is as follows:

[0017] Where V is the comprehensive value of multi-objective decision, and λs is the weight of the s-th objective. vs Let z be the normalized value of the s-th target, and z be the number of targets.

[0018] Preferably, the evaluation model module periodically evaluates each module, establishing an evaluation index system from multiple aspects such as system functionality, reliability, stability, usability, and scalability. Each module is quantitatively scored and analyzed, and the evaluation results are stored in the database module. Based on the evaluation results, the evaluation model module optimizes and adjusts the system, such as optimizing the sampling frequency and sampling point layout of the data acquisition module, adjusting the data storage structure of the database module, and improving the index system of the data index system construction module. The comprehensive evaluation formula for the modules is:

[0019] Where Q is the module's overall evaluation score, and α l Let q be the weight of the l-th evaluation dimension. l Let p be the score of the l-th evaluation dimension, and p be the number of evaluation dimensions. The evaluation model module establishes an evaluation index system from multiple aspects such as system functionality, reliability, stability, ease of use, and scalability, and conducts comprehensive quantitative scoring and analysis of the entire repair process.

[0020] Preferably, the system also includes an ecological continuous monitoring module. This module intervenes comprehensively after the overall restoration is completed, continuously monitoring the evolution of the restored ecosystem, including in-depth ecological indicators such as biodiversity changes and soil ecological function recovery. Data is collected and stored in the database module at preset frequencies to document ecological development. Simultaneously, it has preliminary analysis functions, capable of generating an ecological development status report with one click, directly connecting to the management decision support module to lay a data foundation for subsequent decision-making, and assisting in the long-term ecological maintenance of the mining area. The formula for calculating the ecological development status index is:

[0021] Where I is the ecological development trend index, βh is the weight of the h-th ecological indicator, ih is the normalized value of the h-th ecological indicator, and q is the number of ecological indicators.

[0022] Preferably, the system also includes an ecological feedback analysis module, deeply integrated with the ecological continuous monitoring module and the database module. This module focuses on in-depth mining of post-restoration ecological data, using multivariate statistics and ecological modeling to analyze ecological succession drivers and bottlenecks, generating high-value feedback reports stored in the database. This feedback is then linked to the management decision support module, providing reference for optimizing ecological conservation strategies and designing second-phase restoration projects, thus achieving closed-loop management of the entire ecological restoration lifecycle. The deep integration of the ecological feedback analysis module with the ecological continuous monitoring module and the database module enables in-depth mining of post-restoration ecological data. The formula for calculating the contribution of ecological succession drivers is as follows:

[0023] Among them, C f Contribution of γ to the driving factors of ecological succession g Let c be the weight of the g-th driving factor. g Let be the influence value of the g-th driving factor, and r be the number of driving factors.

[0024] The beneficial effects of this invention are: In this invention, the open-pit mine ecological restoration management and evaluation system forms a complete workflow through the collaboration of data acquisition module, database module, data indicator system construction module, restoration strategy generation module, restoration effect evaluation module, visualization display module, management decision support module, and evaluation model module.

[0025] In this invention, the restoration effect evaluation module of the open-pit mine ecological restoration management and evaluation system automatically retrieves relevant data from the database module at the end of each restoration stage. This data is then compared and analyzed with the predicted restoration effects in the restoration plans generated by the restoration strategy generation module to evaluate the restoration effect. The evaluation results are not only stored in the database module but also displayed through a visualization module and communicated to the management decision support module. Based on the evaluation results from the restoration effect evaluation module, the management decision support module calls the data indicator system construction module and the restoration strategy generation module to formulate the next stage of the restoration plan. Using a multi-objective decision analysis method, it comprehensively considers multiple dimensions of factors, including environmental, economic, and social goals of ecological restoration, to comprehensively evaluate and optimize different restoration plans and measures, determining the optimal restoration strategy. This process achieves dynamic optimization and continuous improvement of the restoration process. The beneficial effect of this collaborative mechanism lies in achieving dynamic optimization and continuous improvement of the restoration process. Through dynamic updates of the data indicator system and timely adjustments to the restoration strategy, the system can adapt to various changes in the ecological restoration process, ensuring the smooth progress of the restoration work. Simultaneously, real-time evaluation of the restoration effect and scientific formulation of management decisions improve the efficiency and effectiveness of the restoration work, avoiding resource waste and blind spots in the restoration efforts. In addition, this dynamic adjustment mechanism can promptly identify and resolve problems that arise during the repair process, reduce repair risks, and improve the success rate and sustainability of repair work.

[0026] In this invention, the ecological sustainability monitoring module of the open-pit mine ecological restoration management and evaluation system provides strong support for the long-term management and continuous improvement of open-pit mine ecological restoration work. Its long-term monitoring function and analytical capabilities not only record and evaluate the evolution of the restored ecosystem but also promptly identify and resolve emerging problems, laying a solid foundation for the long-term success of ecological restoration work and the sustainable development of the ecosystem. The ecological feedback analysis module plays an irreplaceable role in the open-pit mine ecological restoration management and evaluation system. Its deep data mining and analysis capabilities provide strong support for the optimization and decision support of ecological restoration work, contributing to improving the scientific rigor, effectiveness, and sustainability of ecological restoration efforts. Attached Figure Description

[0027] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0028] Figure 1This is an interactive diagram of the functional modules of the open-pit mine ecological restoration management and evaluation system of the present invention. Detailed Implementation

[0029] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0030] Example 1 like Figure 1 As shown, the open-pit mine ecological restoration management and evaluation system of the present invention includes a data acquisition module, a database module, a data indicator system construction module, a restoration strategy generation module, a restoration effect evaluation module, a visualization display module, a management decision support module, and an evaluation model module. The data acquisition module is used to collect data before and during the ecological restoration of the open-pit mine, including multi-dimensional data such as soil, vegetation, hydrology, meteorology, and mining activities, and transmits the collected data to the database module for storage. The database module is connected to the data acquisition module and is used to store various types of data related to the ecological restoration of open-pit mines, including pre-restoration data, data during the restoration process, and pre-stored information such as multi-level ecological evaluation indicators and their weight coefficients corresponding to different ecological restoration stages and restoration goals. The data indicator system construction module is connected to the database module. Based on the data stored in the database module, it automatically generates a data indicator system library covering multiple dimensions of ecosystem structural integrity, functional stability, and biodiversity on a regular basis. This module can retrieve data from the database module before and during restoration, analyze and process the data, generate a dynamically updated data indicator system library, and store it in the database module. Simultaneously, it sends notifications of data indicator system library updates to the restoration strategy generation module, providing quantitative basis for the formulation of restoration strategies. The indicator weights are calculated using the analytic hierarchy process (AHP) formula.

[0031] Among them, w i Let a be the weight of the i-th indicator. ij To determine the matrix elements, n is the number of indicators; The restoration strategy generation module is connected to the database module and the data indicator system construction module. Built based on ecological principles and mathematical statistics, it uses indicators and weights retrieved from the data indicator system library, combined with current ecological status data of the open-pit mine obtained from the database module, and employs an integrated decision-making model and a pre-stored expert knowledge base in the database module to quantitatively analyze the processed data. This module can output a comprehensive analysis of the current ecological status of the open-pit mine and the scores of each sub-indicator. Based on the analysis results, it generates targeted ecological restoration plans, performs feasibility and cost-benefit analyses on the plans, selects the optimal plan, stores it in the database module, provides alternative plans for the management decision support module, and sends a plan display request to the visualization module. The cost-benefit analysis uses the net present value formula.

[0032] Where NPV is the net present value, Ct is the cash flow in period t, r is the discount rate, and T is the project calculation period; The restoration effect evaluation module is connected to the database module and the restoration strategy generation module. It is used for phased and final restoration effect evaluations. It compares and analyzes pre-restoration mine ecological status data, data changes during restoration, and the predicted restoration effects in the restoration plans generated by the restoration strategy generation module to assess the restoration effect. At the end of each restoration phase, it automatically retrieves relevant data from the database module, performs comparative analysis, evaluates the restoration effect, and stores the evaluation results in the database module. Simultaneously, it sends evaluation result display requests to the visualization module and evaluation result notifications to the management decision support module. In the final restoration effect evaluation, it combines comprehensive indicators such as ecosystem service value assessment and ecosystem health status assessment to provide comprehensive restoration effect feedback to the management decision support module. The comprehensive restoration effect scoring formula is as follows:

[0033] Where S is the overall score, w i Let s be the weight of the i-th indicator. i Let m be the score of the i-th indicator, and m be the number of indicators. The visualization module is connected to the database module, the restoration strategy generation module, and the restoration effect evaluation module. It is used to visualize the data, ecological restoration plans, and restoration effect evaluation results. It presents complex data and information to users and decision-makers in an intuitive and easy-to-understand way through various forms such as charts, maps, 3D models, and dynamic simulations. At the same time, it provides users with the function of customizing the display content and display format to meet the needs of different users. The management decision support module is connected to the restoration effect evaluation module. Based on the evaluation results of the restoration effect evaluation module, it utilizes the data indicator system construction module and the restoration strategy generation module to formulate the next stage restoration plan. This module employs a multi-objective decision analysis method, comprehensively considering factors from multiple dimensions such as environmental, economic, and social goals of ecological restoration. It comprehensively evaluates and selects different restoration schemes and measures to determine the optimal restoration strategy and stores the next stage restoration plan in the database module. Simultaneously, it sends a notification to the restoration strategy generation module regarding the formulation of the next stage restoration plan, achieving dynamic optimization and continuous improvement of the restoration process. The formula for calculating the multi-objective decision comprehensive value is as follows:

[0034] Where V is the comprehensive value of multi-objective decision, and λs is the weight of the s-th objective. vs z is the normalized value of the s-th objective. g For the target quantity; The evaluation model module is used to comprehensively evaluate the entire open-pit mine ecological restoration process. It establishes an evaluation index system from multiple aspects, including the accuracy of data collection, the efficiency of database management, the rationality of the data indicator system construction, the scientific nature of restoration strategy generation, the accuracy of restoration effect evaluation, the effectiveness of visualization, and the scientific nature of management decision support. This system quantifies and analyzes the entire restoration process, and the evaluation results are stored in the database module, providing a basis for continuous system improvement and optimization, ensuring the efficiency, scientific nature, and sustainability of the entire ecological restoration process. The module's comprehensive evaluation formula is as follows:

[0035] Where Q is the module's overall evaluation score, and α l Let q be the weight of the l-th evaluation dimension. l Let be the score of the l-th evaluation dimension, and p be the number of evaluation dimensions.

[0036] This open-pit mine ecological restoration management and evaluation system forms an organic whole through close cooperation and synergy among its various modules. It achieves scientific management and comprehensive evaluation of the entire open-pit mine ecological restoration process. On one hand, the data acquisition module, database module, data indicator system construction module, restoration strategy generation module, restoration effect evaluation module, visualization module, management decision support module, and evaluation model module collaborate to form a complete workflow. The data acquisition module is responsible for continuously collecting multi-dimensional data before and during ecological restoration, providing rich basic information for the entire system. This data is uniformly stored and managed through the database module, ensuring data integrity and availability. Based on the data in the database, the data indicator system construction module can dynamically generate a multi-dimensional indicator system library covering ecosystem structural integrity, functional stability, and biodiversity, according to different ecological restoration stages and target characteristics. The output of this module directly provides quantitative basis for the restoration strategy generation module, making the formulation of restoration strategies more scientific and reasonable. The restoration strategy generation module combines ecological principles, mathematical statistics methods, decision-making models, and expert knowledge bases to generate targeted ecological restoration plans, conduct feasibility and cost-benefit analyses, and select the optimal plan. These solutions are not only stored in the database module for use by other modules, but also presented intuitively to users and decision-makers through the visualization module, facilitating their understanding and evaluation. On the other hand, at the end of each restoration phase, the restoration effect evaluation module automatically retrieves relevant data from the database module, compares it with the predicted restoration effects in the restoration solutions generated by the restoration strategy generation module, and evaluates the restoration effectiveness. The evaluation results are not only stored in the database module but also displayed through the visualization module and notified to the management decision support module. Based on the evaluation results from the restoration effect evaluation module, the management decision support module calls the data indicator system construction module and the restoration strategy generation module to formulate the next phase of the restoration plan. Using multi-objective decision analysis methods, it comprehensively considers multiple dimensions of factors, including environmental, economic, and social goals of ecological restoration, to comprehensively evaluate and select the optimal restoration strategy from different restoration solutions and measures. This process achieves dynamic optimization and continuous improvement of the restoration process. The evaluation model module periodically evaluates each module, establishing an evaluation index system based on multiple aspects such as system functionality, reliability, stability, usability, and scalability. Each module is quantitatively scored and analyzed, and the evaluation results are stored in the database module and sent as feedback to the corresponding modules, providing a basis for continuous system improvement and optimization. The coordinated operation between the modules enables the system to achieve comprehensive management and evaluation of the entire process of open-pit mine ecological restoration. From data collection to decision support, from restoration strategy generation to restoration effect evaluation, and from short-term restoration to long-term ecological maintenance, each link is closely connected and mutually reinforcing.This not only enhances the scientific rigor, systematic approach, and effectiveness of ecological restoration efforts but also provides strong support for the sustainable development of open-pit mines. Through dynamic optimization and continuous improvement, the system can adapt to the ecological restoration needs at different stages, adjust restoration strategies in a timely manner, and ensure the smooth progress of restoration work and the achievement of ecological goals. Simultaneously, the system's self-evaluation and optimization functions ensure its long-term stable operation and performance improvement, providing crucial support for technological advancements and management innovation in the field of open-pit mine ecological restoration.

[0037] Example 2 In one optional embodiment of this example, the data acquisition module includes various sensors and data input devices, capable of collecting soil data, vegetation data, hydrological data, meteorological data, and data related to mining activities in the open-pit mine. Soil data includes soil texture, soil fertility, soil pH, and soil heavy metal content; vegetation data includes vegetation coverage, vegetation species, and vegetation growth status; hydrological data includes surface water quality, groundwater level, and surface runoff; meteorological data includes temperature, precipitation, wind speed, and wind direction; and data related to mining activities includes ore extraction volume, waste rock dumping volume, and mining area area. The data acquisition module preprocesses the collected data before transmitting it to the database module. Preprocessing includes data cleaning, format conversion, and data verification. The data acquisition module forms the information foundation of the open-pit mine ecological restoration management and evaluation system. It comprehensively collects mine ecological data through various sensors and data input devices, including soil moisture sensors, vegetation coverage monitors, and water quality analyzers. These devices are deployed in different areas of the mine to ensure data representativeness. The data acquisition module not only collects current ecological status data but also records changes over time, providing dynamic data support for the ecological restoration process. Soil sensors can monitor changes in the physical and chemical properties of the soil in real time, while vegetation monitoring equipment can track changes in plant growth and species diversity. After preliminary processing, such as removing outliers and calibrating data formats, this data is transmitted to the database module for centralized management. Data verification uses an error range determination formula.

[0038] Where x is the collected data value, μ is the standard reference value of the data, and δ is the allowable error range.

[0039] Example 3 In one optional embodiment of this example, the database module uses a combination of relational and non-relational databases to store and manage different types of data. The relational database stores structured data, including but not limited to ecological evaluation indicators and their weighting coefficients, and parameters of restoration plans. The non-relational database stores unstructured data, including but not limited to remote sensing image data and mine topographic data. The database module provides a data interface for other modules to read and write data. The data read efficiency is calculated using the following formula:

[0040] Where E is the data reading efficiency, N is the amount of data read, and t r This refers to the read time.

[0041] The remediation strategy generation module can retrieve relevant ecological evaluation indicators from the database based on the remediation progress, while the data indicator system construction module can update the indicator system in real time and store it in the database.

[0042] Example 4 In an optional embodiment of this example, in the data indicator system construction module, the ecological evaluation indicators and their weight coefficients corresponding to different ecological restoration stages are set according to the temporal process and target characteristics of ecological restoration. This module can obtain data from the database module before and during restoration based on the characteristics and needs of different ecological restoration stages, perform in-depth analysis and processing of the data, generate a dynamically updated data indicator system library, and store it in the database module. Simultaneously, it sends a notification of data indicator system library updates to the restoration strategy generation module, ensuring that the restoration strategy generation module can obtain the latest indicator system information in a timely manner, providing a basis for generating scientific and reasonable restoration strategies. The indicator weights are calculated using the analytic hierarchy process (AHP) formula.

[0043] Among them, w i Let a be the weight of the i-th indicator. ij To determine the matrix elements, n represents the number of indicators.

[0044] In the early stages of ecological restoration, soil improvement and vegetation restoration indicators may be given higher weight, while in later stages, biodiversity and ecosystem service function indicators become more important. The constructed indicator system will be stored in a database for use by the restoration strategy generation module. Furthermore, this module has dynamic adjustment capabilities, enabling it to update the indicator system promptly based on new data and objectives during the restoration process.

[0045] Example 5 In one optional embodiment of this example, after receiving a notification of an update to the data indicator system library, the restoration strategy generation module retrieves the latest indicators and weights from the database module. Combined with the current ecological status data of the open-pit mine obtained from the database module, it performs quantitative analysis using a decision model and expert knowledge base. Based on the analysis results, this module can generate multiple ecological restoration plans, conduct feasibility and cost-benefit analyses on the plans, select the optimal plan, store the generated ecological restoration plan in the database module, and send a plan display request to the visualization module. Simultaneously, the restoration plans in the database module are periodically updated and optimized to adapt to the dynamic changes in the open-pit mine ecological restoration process. The cost-benefit analysis uses the net present value formula:

[0046] Where NPV is the net present value, Ct is the cash flow in period t, r is the discount rate, and T is the project calculation period.

[0047] This module can simulate the effects of different vegetation planting schemes on soil erosion control, or evaluate the promoting effects of different soil improvement measures on vegetation restoration. The generated strategies will undergo cost-benefit analysis and feasibility assessment to ensure their effectiveness and economy in practical applications. The optimal remediation strategy will be stored in a database and presented to decision-makers through a visualization module for further discussion and decision-making.

[0048] Example 6 In one optional embodiment of this example, at the end of each restoration stage, the restoration effect evaluation module automatically retrieves pre-restoration mine ecological status data, data changes during restoration, and predicted restoration effect data from the database module, compares and analyzes these data, evaluates the restoration effect, and stores the evaluation results in the database module. Simultaneously, it sends an evaluation result display request to the visualization module and an evaluation result notification to the management decision support module. In the final restoration effect evaluation, the module combines comprehensive indicators such as ecosystem service value assessment and ecosystem health status assessment to provide comprehensive restoration effect feedback to the management decision support module. The comprehensive restoration effect score uses the following formula:

[0049] Where S is the overall score, w i Let s be the weight of the i-th indicator. i Let be the score of the i-th indicator, and m be the number of indicators.

[0050] The effectiveness of vegetation restoration is assessed by comparing vegetation cover and soil fertility indicators before and after restoration. The assessment results are stored in a database to provide a basis for subsequent restoration decisions. Simultaneously, this module also has predictive capabilities, enabling it to forecast future ecological development trends based on current restoration results, providing a reference for long-term ecological restoration planning.

[0051] Example 7 In an optional embodiment of this example, after receiving the evaluation result notification from the restoration effect evaluation module, the management decision support module calls the data indicator system construction module and the restoration strategy generation module to formulate the next-stage restoration plan based on the evaluation results and store the next-stage restoration plan in the database module. This module uses a multi-objective decision analysis method to comprehensively consider multiple dimensions of factors such as environmental, economic, and social goals of ecological restoration, to comprehensively evaluate and optimize different restoration schemes and measures, determine the optimal restoration strategy, store the next-stage restoration plan in the database module, and simultaneously send a notification of the next-stage restoration plan formulation to the restoration strategy generation module, thereby achieving dynamic optimization and continuous improvement of the restoration process. In the open-pit mine ecological restoration management evaluation system, the close cooperation between the data indicator system construction module, the restoration strategy generation module, the restoration effect evaluation module, and the management decision support module achieves dynamic optimization and continuous improvement of the restoration process. The multi-objective decision comprehensive value calculation formula is as follows:

[0052] Where V is the comprehensive value of multi-objective decision, and λs is the weight of the s-th objective. vs z is the normalized value of the s-th objective. g The target quantity.

[0053] First, the data indicator system construction module can retrieve data from the database module before and during restoration, based on different stages and target characteristics of ecological restoration, and perform in-depth analysis and processing to generate a dynamically updated data indicator system library. This dynamic updating capability ensures that the data indicator system can promptly reflect changes and needs during the ecological restoration process, providing a scientific and reasonable quantitative basis for subsequent restoration strategy formulation. As restoration work progresses, the structure and function of the ecosystem will change. The data indicator system construction module can adjust indicators and weights in a timely manner according to these changes, enabling restoration strategies to be more accurately targeted at the current ecological situation. Next, upon receiving notification of an update to the data indicator system library, the restoration strategy generation module retrieves the latest indicators and weights from the database module, combines them with current ecological status data of the open-pit mine obtained from the database module, and uses decision-making models and expert knowledge bases for quantitative analysis. This module can generate multiple ecological restoration schemes based on the analysis results, conduct feasibility and cost-benefit analyses of the schemes, and select the optimal scheme. This restoration scheme generation mechanism based on the latest data and indicator system ensures the scientific validity and effectiveness of the restoration strategy and can adapt to dynamic changes during the ecological restoration process. If a remediation measure proves ineffective during the restoration process, the remediation strategy generation module can adjust the remediation plan promptly based on new data and indicator systems, generating a better strategy. At the end of each remediation phase, the remediation effectiveness evaluation module automatically retrieves pre-remediation mine ecological status data, data changes during the remediation process, and the predicted remediation effect data from the database module, performs comparative analysis, and evaluates the remediation effect. The evaluation results are stored in the database module and notified to the management decision support module. This real-time remediation effectiveness evaluation mechanism provides timely feedback on the effectiveness and problems of the remediation work, offering a scientific basis for management decisions. If the evaluation results show that the current remediation strategy has failed to achieve the expected results, the management decision support module can adjust the remediation plan in a timely manner and select a more suitable remediation strategy. Based on the evaluation results from the remediation effectiveness evaluation module, the management decision support module calls the data indicator system construction module and the remediation strategy generation module to formulate the next phase of the remediation plan. This module uses a multi-objective decision analysis method, comprehensively considering multiple dimensions of factors such as environmental, economic, and social goals of ecological restoration, to comprehensively evaluate and optimize different remediation plans and measures, determining the optimal remediation strategy. In this way, the management decision support module enables dynamic optimization and continuous improvement of the remediation process, ensuring the scientific rigor and effectiveness of the remediation work. Based on the evaluation results and the new data indicator system, the management decision support module can select more economical, efficient, and environmentally friendly remediation solutions, improving the overall effectiveness of the remediation work. The beneficial effect of this collaborative mechanism lies in achieving dynamic optimization and continuous improvement of the remediation process.Through dynamic updates to the data indicator system and timely adjustments to restoration strategies, the system can adapt to various changes during the ecological restoration process, ensuring the smooth progress of restoration work. Simultaneously, real-time assessment of restoration effects and scientific formulation of management decisions improve the efficiency and effectiveness of restoration work, avoiding resource waste and blind spots in restoration efforts. Furthermore, this dynamic adjustment mechanism can promptly identify and resolve problems arising during the restoration process, reducing restoration risks and increasing the success rate and sustainability of restoration work.

[0054] Example 8 In one optional implementation of this embodiment, the evaluation model module periodically evaluates each module, establishing an evaluation index system from multiple aspects such as system functionality, reliability, stability, usability, and scalability. Each module is quantitatively scored and analyzed, and the evaluation results are stored in the database module. Based on the evaluation results, the evaluation model module performs self-optimization and adjustment of the system, such as optimizing the sampling frequency and sampling point layout of the data acquisition module, adjusting the data storage structure of the database module, and improving the index system of the data index system construction module. The comprehensive evaluation formula for the modules is as follows:

[0055] Where Q is the module's overall evaluation score, and α l Let q be the weight of the l-th evaluation dimension. l Let be the score of the l-th evaluation dimension, and p be the number of evaluation dimensions.

[0056] The evaluation model module establishes an evaluation index system from multiple aspects, including system functionality, reliability, stability, usability, and scalability, to comprehensively quantify and analyze the entire restoration process. This comprehensive evaluation mechanism can fully and objectively reflect the system's operating status and performance, providing a scientific basis for continuous system improvement and optimization. By evaluating the accuracy of the data acquisition module, potential errors and omissions during data acquisition can be identified and resolved in a timely manner, improving data quality and reliability. Similarly, evaluating the management efficiency of the database module can optimize data storage structure and query algorithms, improving data read / write efficiency and response speed. The evaluation model module can self-optimize and adjust the system based on the evaluation results. It can optimize the sampling frequency and sampling point layout of the data acquisition module based on the evaluation results, ensuring that the collected data is more representative and timely. It can adjust the data storage structure of the database module to improve data organization and management efficiency. It can improve the index system of the data index system construction module to more scientifically and rationally reflect the actual situation of ecological restoration. This self-optimization capability enables the system to continuously improve its performance and functions, adapt to different ecological restoration needs and environmental conditions, and improve the overall efficiency and adaptability of the system. The evaluation model module provides strong support for the continuous improvement and optimization of the open-pit mine ecological restoration management evaluation system. Its comprehensive evaluation function and self-optimization capability enable the system to continuously improve its performance and functions, adapting to different ecological restoration needs and environmental conditions. At the same time, it also improves the system's reliability, stability, and ease of use, laying a solid foundation for the system's long-term stable operation and widespread application.

[0057] Example 9 In an optional embodiment of this invention, the system further includes an ecological continuous monitoring module. This module intervenes comprehensively after the overall restoration is completed, continuously monitoring the evolution of the restored ecosystem, including in-depth ecological indicators such as biodiversity changes and soil ecological function recovery. It collects and stores data in the database module at preset frequencies to document ecological development. Simultaneously, it possesses preliminary analysis capabilities, generating an ecological development status report with a single click. This report directly connects to the management decision support module, laying a data foundation for subsequent decision-making and supporting the long-term ecological maintenance of the mining area. The formula for calculating the ecological development status index is as follows:

[0058] Where I is the ecological development trend index, βh is the weight of the h-th ecological indicator, ih is the normalized value of the h-th ecological indicator, and q is the number of ecological indicators.

[0059] The ecological sustainability monitoring module intervenes comprehensively after the overall restoration is completed, continuously monitoring the evolution of the restored ecosystem, including deep ecological indicators such as biodiversity changes and soil ecological function recovery. This long-term monitoring can create a record of ecological development, documenting the changes and trends of the restored ecosystem, and providing valuable data support for subsequent ecological research and management. By monitoring changes in biodiversity, we can understand the survival and reproduction of different species after restoration and assess the stability and health of the ecosystem. Monitoring soil ecological functions can reflect the recovery of soil fertility, water retention capacity, etc., providing a scientific basis for agricultural planting or other land use methods. The ecological sustainability monitoring module has preliminary analysis functions, capable of collecting and storing data to the database module at preset frequencies, and generating ecological development status reports with one click. This automated data collection and analysis function greatly improves work efficiency, reduces the need for manual intervention, and ensures the timeliness and accuracy of data. The generated ecological development status reports can intuitively present the evolution of the restored ecosystem, providing timely and accurate information for the management decision support module, and assisting in the long-term maintenance and management of the mining area's ecology. The briefing can display key indicators such as the changing trends of biodiversity indices and the degree of improvement in soil quality, helping decision-makers quickly understand the long-term effects of ecological restoration and formulate corresponding maintenance measures and management strategies. The ecological sustainability monitoring module also provides data support for the long-term assessment and improvement of ecological restoration work. By accumulating and analyzing long-term monitoring data of the restored ecosystem, the long-term effects and sustainability of ecological restoration work can be evaluated, lessons learned can be summarized, and references can be provided for the implementation of similar projects in the future. The impact of different restoration measures on the long-term recovery of the ecosystem can be analyzed, restoration technologies and management strategies can be optimized, and the overall level of ecological restoration work can be improved.

[0060] In an optional embodiment of this example, the system further includes an ecological feedback analysis module, which is deeply integrated with the ecological continuous monitoring module and the database module. This module focuses on in-depth mining of post-restoration ecological data, using multivariate statistics and ecological modeling to analyze ecological succession driving factors and bottlenecks, generating high-value feedback reports stored in the database. This feedback is then linked to the management decision support module to provide reference for optimizing ecological conservation strategies and designing second-phase restoration projects, thus achieving closed-loop management of the entire ecological restoration lifecycle. The formula for calculating the contribution of ecological succession driving factors is as follows:

[0061] Among them, C f Contribution of γ to the driving factors of ecological succession g Let c be the weight of the g-th driving factor. g Let be the influence value of the g-th driving factor, and r be the number of driving factors.

[0062] The ecological feedback analysis module is deeply integrated with the ecological sustainability monitoring and database modules, enabling in-depth analysis of post-restoration ecological data. By employing multivariate statistical methods and ecological modeling, this module can dissect the driving factors and bottlenecks of ecological succession, identifying key factors affecting ecosystem restoration and development. Analyzing biodiversity data reveals which species play crucial roles in ecosystem restoration and which species' absence may limit functional recovery. This in-depth analysis helps to better understand the intrinsic mechanisms and evolutionary patterns of ecosystems, providing a scientific basis for optimizing ecological restoration efforts. The ecological feedback analysis module generates high-value feedback reports and stores them in the database. These reports not only record the evolutionary process of the ecosystem and the changing trends of key ecological indicators but also provide a comprehensive assessment of the effectiveness of ecological restoration work. Feedback reports can provide detailed analytical results and recommendations, helping decision-makers understand the effectiveness and shortcomings of current ecological restoration efforts and providing strong support for subsequent decision-making. Feedback reports can indicate that current restoration measures have been effective in promoting vegetation restoration, but further efforts are needed to improve soil fertility, thus guiding decision-makers to adjust restoration strategies and increase investment in soil improvement.

[0063] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An open-pit mine ecological restoration management and evaluation system, comprising a data acquisition module, a database module, a data indicator system construction module, a restoration strategy generation module, a restoration effect evaluation module, a visualization module, a management decision support module, and an evaluation model module, characterized in that: The data acquisition module is used to collect data before and during the ecological restoration of open-pit mines, and to transmit the collected data to the database module for storage. The database module is connected to the data acquisition module and is used to store various types of data related to the ecological restoration of open-pit mines; The data indicator system construction module is connected to the database module, and automatically generates a dynamically updated data indicator system library at regular intervals. The restoration strategy generation module is connected to the database module and the data indicator system construction module. It performs quantitative analysis on the processed data and generates targeted ecological restoration plans based on the analysis results. The repair effect evaluation module is connected to the database module and the repair strategy generation module, and is used to perform phased repair effect evaluation and final repair effect evaluation. The visualization module is connected to the database module, the restoration strategy generation module, and the restoration effect evaluation module, respectively, and is used to visualize the data, ecological restoration plan, and restoration effect evaluation results. The management decision support module is connected to the repair effect evaluation module. Based on the evaluation results of the repair effect evaluation module, the next stage repair plan is formulated using the data indicator system construction module and the repair strategy generation module. The evaluation model module is used to comprehensively evaluate the entire open-pit mine ecological restoration process.

2. The open-pit mine ecological restoration management and evaluation system according to claim 1, characterized in that: The data acquisition module includes various sensors and data input devices, capable of collecting soil data, vegetation data, hydrological data, meteorological data, and data related to mining activities in open-pit mines. The data acquisition module preprocesses the collected data before transmitting it to the database module. Preprocessing includes data cleaning, format conversion, and data verification. Data verification uses an error range determination formula. Where x is the collected data value, μ is the standard reference value of the data, and δ is the allowable error range.

3. The open-pit mine ecological restoration management and evaluation system according to claim 1, characterized in that: The database module uses a combination of relational and non-relational databases to store and manage different types of data, with the relational database used to store structured data. No-relational databases are used to store unstructured data, and the database module provides a data interface for other modules to perform data reading and writing operations. The formula for calculating data reading efficiency is: Where E is the data reading efficiency, N is the amount of data read, and t r This refers to the read time.

4. The open-pit mine ecological restoration management and evaluation system according to claim 1, characterized in that: In the data indicator system construction module, the ecological evaluation indicators and their weight coefficients corresponding to different ecological restoration stages are set according to the temporal process and target characteristics of ecological restoration. This module can obtain data before and during restoration from the database module according to the characteristics and needs of different ecological restoration stages, perform in-depth analysis and processing of the data, generate a dynamically updated data indicator system library, and store it in the database module. At the same time, it sends a notification of data indicator system library update to the restoration strategy generation module. The indicator weights are calculated using the analytic hierarchy process formula: Among them, w i Let a be the weight of the i-th indicator. ij To determine the matrix elements, n represents the number of indicators.

5. The open-pit mine ecological restoration management and evaluation system according to claim 4, characterized in that: Upon receiving a notification of an update to the data indicator system library, the restoration strategy generation module retrieves the latest indicators and weights from the database module. Combining this with current ecological status data of the open-pit mine obtained from the database module, it performs quantitative analysis using a decision-making model and expert knowledge base. Based on the analysis results, this module generates multiple ecological restoration plans, conducts feasibility and cost-benefit analyses on these plans, selects the optimal plan, stores the generated ecological restoration plan in the database module, and sends a plan display request to the visualization module. Simultaneously, it periodically updates and optimizes the restoration plans in the database module to adapt to the dynamic changes in the open-pit mine ecological restoration process. The cost-benefit analysis uses the net present value formula. Where NPV is the net present value, Ct is the cash flow in period t, r is the discount rate, and T is the project calculation period.

6. The open-pit mine ecological restoration management and evaluation system according to claim 1, characterized in that: At the end of each restoration phase, the restoration effectiveness evaluation module automatically retrieves pre-restoration mine ecological status data, data changes during restoration, and predicted restoration effect data from the database module, compares and analyzes these data, evaluates the restoration effect, and stores the evaluation results in the database module. Simultaneously, it sends an evaluation result display request to the visualization module and an evaluation result notification to the management decision support module. In the final restoration effectiveness evaluation, the module combines ecological service value assessment and ecosystem health status assessment indicators to provide comprehensive restoration effectiveness feedback to the management decision support module. The comprehensive restoration effectiveness scoring formula is as follows: Where S is the overall score, w i Let s be the weight of the i-th indicator. i Let be the score of the i-th indicator, and m be the number of indicators.

7. The open-pit mine ecological restoration management and evaluation system according to claim 1, characterized in that: After receiving the evaluation results from the restoration effect assessment module, the management decision support module calls the data indicator system construction module and the restoration strategy generation module to formulate the next-stage restoration plan based on the evaluation results and store it in the database module. This module uses a multi-objective decision analysis method, comprehensively considering multiple dimensions of environmental, economic, and social goals in ecological restoration, to comprehensively evaluate and optimize different restoration schemes and measures, determine the optimal restoration strategy, and store the next-stage restoration plan in the database module. Simultaneously, it sends a notification to the restoration strategy generation module regarding the formulation of the next-stage restoration plan, achieving dynamic optimization and continuous improvement of the restoration process. The multi-objective decision comprehensive value calculation formula is as follows: Where V is the comprehensive value of multi-objective decision, and λs is the weight of the s-th objective. vs Let z be the normalized value of the s-th target, and z be the number of targets.

8. The open-pit mine ecological restoration management and evaluation system according to claim 1, characterized in that: The evaluation model module periodically evaluates each module, establishing an evaluation index system from multiple aspects such as system functionality, reliability, stability, usability, and scalability. Each module is quantitatively scored and analyzed, and the evaluation results are stored in the database module. Based on the evaluation results, the evaluation model module optimizes and adjusts the system, including optimizing the sampling frequency and sampling point layout of the data acquisition module, adjusting the data storage structure of the database module, and improving the index system of the data index system construction module. The comprehensive evaluation formula for the modules is: Where Q is the module's overall evaluation score, and α l Let q be the weight of the l-th evaluation dimension. l Let be the score of the l-th evaluation dimension, and p be the number of evaluation dimensions.

9. The open-pit mine ecological restoration management and evaluation system according to claim 1, characterized in that: The system also includes an ecological continuous monitoring module, which intervenes comprehensively after the overall restoration is completed. This module continuously monitors the evolution of the restored ecosystem, including changes in biodiversity, deep ecological indicators of soil ecological function recovery, and collects and stores data in the database module at preset frequencies, creating a record of ecological development. It also has preliminary analysis functions, capable of generating an ecological development status report with one click, and directly connects to the management decision support module, laying a data foundation for subsequent decision-making and assisting in the long-term ecological maintenance of the mining area. The formula for calculating the ecological development status index is: Where I represents the ecological development trend index, and β h Let i be the weight of the h-th ecological indicator. h Let q be the normalized value of the h-th ecological indicator, and q be the number of ecological indicators.

10. The open-pit mine ecological restoration management and evaluation system according to claim 9, characterized in that: The system also includes an ecological feedback analysis module, deeply integrated with the ecological continuous monitoring module and the database module. It focuses on in-depth mining of post-restoration ecological data, using multivariate statistics and ecological modeling to analyze ecological succession drivers and bottlenecks, generating high-value feedback reports stored in the database. This, in turn, links with the management decision support module, providing references for optimizing ecological conservation strategies and designing follow-up decisions for second-phase restoration projects. This achieves closed-loop management of the entire ecological restoration lifecycle. The formula for calculating the contribution of ecological succession drivers is: Among them, C f Contribution of γ to the driving factors of ecological succession g Let c be the weight of the g-th driving factor. g Let be the influence value of the g-th driving factor, and r be the number of driving factors.

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