Method and system for estimating carbon emission and carbon reserve of mineral resource mining area

Abstract

The invention discloses a carbon emission and carbon reserve estimation method and system for a mineral resource mining area, and belongs to the technical field of carbon emission and carbon reserve estimation. The invention discloses a method for estimating carbon emission and carbon reserves in a mineral resource mining area. The method comprises the following steps of: 1, acquiring basic data of the mineral resource mining area and data of a weather station and a seismic station; 2, establishing a mining area carbon cycle model, and training and optimizing the mining area carbon cycle model; 3, inputting the data into an operation mining area carbon cycle model; 4, carrying out simulation prediction on carbon emission and carbon reserves; and 5, obtaining estimation results of the carbon emission and the carbon reserves. According to the method, the problem that the actual carbon emission and carbon reserve conditions of the mining area cannot be comprehensively and accurately reflected in the prior art is solved, the estimation results of the carbon emission and the carbon reserve can be updated in real time according to the basic data change of the mineral resource mining area, the accuracy and timeliness of the estimation results are ensured, and the real-time performance of the mining area is improved. And the estimation results of the carbon emission and the carbon reserves are more accurate and reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission and carbon reserve estimation, and in particular to a method and system for estimating carbon emission and carbon reserve in a mineral resource mining area. Background Art

[0002] The issue of carbon dioxide emissions and absorption has begun to be taken seriously by various industries, especially the energy system as the largest source of carbon emissions. When conducting mineral development, more attention should be paid to the estimation of carbon emissions and carbon reserves.

[0003] The Chinese patent with the publication number CN114969665B discloses a method and system for estimating carbon emissions and carbon reserves of a mineral resource base. By calculating the amount of ore corresponding to each type of ore in the area to be estimated, the carbon emissions of comprehensive energy consumption are obtained; at the same time, the regional area and carbon reserves of each area in the area to be estimated are calculated to obtain the ecological carbon loss; according to the average content of each mineral in the surface rock sample and the drill core sample, the mineral carbonate carbon reserve is obtained; based on the ecological carbon loss, the carbon emissions of comprehensive energy consumption and the mineral carbonate carbon reserve, the carbon emissions and carbon reserves of the area to be estimated are obtained. By integrating the estimation of carbon emissions and carbon reserves of mineral resource bases, the estimation efficiency of carbon emissions and carbon reserves before the development of mineral resource bases is improved, and at the same time, the gap in the current carbon emissions and carbon reserves estimation system before mining development is filled, providing important green support for subsequent environmental protection, resource utilization, geological exploration, mine planning and other activities.

[0004] In the actual use of the above patent, the carbon emissions and carbon reserves are estimated by using ecological carbon loss, comprehensive energy consumption carbon emissions and mineral carbonation carbon reserves, which cannot fully and accurately reflect the actual carbon emissions and carbon reserves of the mining area. For example, the calculation of ecological carbon loss may be affected by many factors, such as surface vegetation destruction, soil erosion, etc. These factors may not be fully considered in the current estimation method; therefore, it does not meet the existing needs. In this regard, we propose a method and system for estimating carbon emissions and carbon reserves in mineral resource mining areas. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for estimating carbon emissions and carbon reserves in a mineral resource mining area. The carbon cycle model of the mining area can comprehensively consider the carbon flow in the mineral resource mining area, so as to more accurately estimate the carbon emissions of the mineral resource mining area. The estimation results of carbon emissions and carbon reserves can be updated in real time according to the changes in the basic data of the mineral resource mining area, ensuring the accuracy and timeliness of the estimation results, so that the mineral resource mining area can timely grasp the latest situation of carbon emissions and carbon reserves. Through the calculation of the mining area carbon cycle model, the estimation results of carbon emissions and carbon reserves are more accurate and reliable, providing strong support for carbon management and carbon trading in the mining area, and solving the problems raised in the above-mentioned background technology.

[0006] To achieve the above purpose, the present invention provides the following technical solution: a method for estimating carbon emissions and carbon reserves in a mineral resource mining area, comprising:

[0007] Step 1: Use satellite remote sensing technology to obtain basic data of mineral resource mining areas, perform preprocessing, and obtain data from meteorological stations and seismic stations in mineral resource mining areas;

[0008] Step 2: Use the pre-processed mining area basic data to establish a mining area carbon cycle model, and use machine learning algorithms to train and optimize the established mining area carbon cycle model;

[0009] Step 3: Input the basic data of the mineral resource mining area and the data of the meteorological station and seismic station of the mineral resource mining area into the running mining area carbon cycle model;

[0010] Step 4: Run the mining area carbon cycle model to simulate and predict the carbon emissions and carbon reserves of the mineral resource mining area;

[0011] Step 5: Analyze the output results of the mining area carbon cycle model to obtain the estimated results of carbon emissions and carbon reserves in the mineral resource mining area.

[0012] Preferably, the method of obtaining basic mining area data by using satellite remote sensing technology and performing preprocessing specifically includes:

[0013] Use satellite remote sensing to obtain images of mineral resource mining areas, and at the same time obtain data from meteorological stations and seismic stations in mineral resource mining areas;

[0014] Preprocess the collected remote sensing images, including atmospheric correction, geometric correction, radiation correction and image registration;

[0015] Extract the geological structure, soil data and hydrological characteristics information of the mineral resource mining area from the pre-processed remote sensing images.

[0016] Preferably, the extraction of geological structure, soil data and hydrological characteristic information of the mineral resource mining area in the pre-processed remote sensing image specifically includes:

[0017] Use the Normalized Difference Vegetation Remote Sensing Index to identify the vegetation coverage of mineral resource mining areas, and evaluate soil quality, soil properties and soil nutrients based on the vegetation coverage;

[0018] Analyze the surface features in remote sensing images and the soil reflectance spectrum characteristics to determine soil data, and indirectly evaluate the soil organic matter content by monitoring the light emission characteristics and infrared reflection characteristics of the soil;

[0019] The meteorological sensors on remote sensing satellites capture the water vapor content, cloud type and movement speed in the clouds to estimate the precipitation in the mineral resource mining area. The thermal infrared sensors on remote sensing satellites measure the thermal radiation on the surface and in the atmosphere to infer the surface temperature and atmospheric temperature.

[0020] The intensity of solar radiation in mineral resource mining areas and the surface energy balance are measured by radiometers on remote sensing satellites;

[0021] Extract the hydrological variables of river width, water surface elevation, water surface velocity and river velocity from the collected remote sensing images, input the acquired river width, water surface elevation, water surface velocity and river velocity into the hydrological model to estimate the river flow and satellite gravity land water reserve changes, and obtain the hydrological conditions of the mineral resource mining area;

[0022] According to the image features and rules shown on the remote sensing images, the direct judgment method is used to interpret and extract the structure of the mineral resource mining area and the geological phenomenon information of the rock.

[0023] Preferably, the method of establishing a mining area carbon cycle model using the pre-processed mining area basic data specifically includes:

[0024] Receive geological data, soil data and hydrological data of mineral resource mining areas, and obtain data from meteorological stations and seismic stations in mining areas;

[0025] Extract original features from geological data, soil data, and hydrological data of mineral resource mining areas through deep learning methods;

[0026] Normalize the extracted original features to form geological data, soil data and hydrological data of new mineral resource mining areas;

[0027] The CENTURY model was selected and parameterized based on the collected geological data, soil data and hydrological data of the mineral resource mining area to obtain the initial mining area carbon cycle model.

[0028] Preferably, the method of using a machine learning algorithm to train and optimize the mining area carbon cycle model specifically includes:

[0029] Divide the geological data, soil data and hydrological data of the new mineral resource mining area into a training data set and a test data set;

[0030] Use the training data set to train the initial carbon cycle model, and optimize the initial mining area carbon cycle model based on the training results;

[0031] After the optimization is completed, the optimized mining area carbon cycle model is tested using the test data set to evaluate the performance of the mining area carbon cycle model until the performance of the mining area carbon cycle model meets the standard and the final mining area carbon cycle model is obtained.

[0032] Preferably, the initial mining area carbon cycle model is optimized according to the training results, specifically including:

[0033] Set the quality standards of the initial mining area carbon cycle model, which are the accuracy of the initial mining area carbon cycle model prediction and the degree of fit to the carbon cycle process of the actual mineral resource mining area;

[0034] The parameters of the initial mining area carbon cycle model are optimized using the gradient descent method, and the loss function for the optimization of the parameters of the initial mining area carbon cycle model is set;

[0035] Set the initial values ​​of the parameters of the initial mining area carbon cycle model, and iterate the parameters of the initial mining area carbon cycle model. In each iteration, calculate the gradient of each parameter of the loss function;

[0036] Use the gradient descent formula to update each parameter of the initial mining area carbon cycle model, repeat parameter iteration and calculate the gradient of each parameter of the loss function until the convergence condition is reached, and the convergence condition is to reach the maximum number of iterations;

[0037] During the optimization process, the cross-validation method is used to evaluate the generalization ability of the initial mining area carbon cycle model, and the initial mining area carbon cycle model is optimized and adjusted based on the evaluation results, including parameter adjustment and model fusion.

[0038] A carbon emission and carbon reserve estimation system for a mineral resource mining area, comprising:

[0039] The data acquisition module is used to obtain images of mineral resource mining areas using satellite remote sensing, perform preprocessing, extract feature information from the preprocessed remote sensing images, and simultaneously obtain data from the meteorological station and seismic station in the mining area;

[0040] The estimation module is used to construct and optimize the mining area carbon cycle model using the geological data, soil data and hydrological data of the mineral resource mining area, and use the mining area carbon cycle model to output the estimation results of the carbon emissions and carbon reserves of the mineral resource mining area.

[0041] Preferably, the data acquisition module comprises:

[0042] The data acquisition module is used to obtain images of mineral resource mining areas using satellite remote sensing, and to obtain data from meteorological stations and seismic stations in the mining areas;

[0043] The preprocessing module is used to perform image enhancement, classification and recognition processing on the acquired data, and extract the geological structure, soil data and hydrological characteristic information of the mineral resource mining area.

[0044] Preferably, the estimation module comprises:

[0045] Model building module, used to construct an initial mining area carbon cycle model using geological data, soil data and hydrological data of the mineral resource mining area;

[0046] A model optimization module is used to optimize and adjust the parameters of the initial mining area carbon cycle model using a gradient descent method to obtain an optimized mining area carbon cycle model;

[0047] The result output module is used to run the mining area carbon cycle model to simulate and predict the carbon emissions and carbon reserves of the mineral resource mining area, and obtain the estimated results of the carbon emissions and carbon reserves of the mineral resource mining area.

[0048] Preferably, the model optimization module includes:

[0049] Divide the geological data, soil data and hydrological data of the new mineral resource mining area into a training data set and a test data set;

[0050] The initial carbon cycle model is trained using the training data set, and the parameters of the initial mining area carbon cycle model are continuously iterated using the gradient descent method based on the training results;

[0051] In the iterative process, the cross-validation method is used to evaluate the generalization ability of the initial mining area carbon cycle model, and the initial mining area carbon cycle model is optimized and adjusted according to the evaluation results;

[0052] After the optimization is completed, the optimized mining area carbon cycle model is tested using the test data set to evaluate the performance of the mining area carbon cycle model until the performance of the mining area carbon cycle model meets the standard and the final mining area carbon cycle model is obtained.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] The present invention utilizes the mining area carbon cycle model to comprehensively consider the carbon flow within the mineral resource mining area, thereby more accurately estimating the carbon emissions of the mineral resource mining area, and can update the estimation results of carbon emissions and carbon reserves in real time according to the changes in the basic data of the mineral resource mining area, thereby ensuring the accuracy and timeliness of the estimation results, so that the mineral resource mining area can timely grasp the latest situation of carbon emissions and carbon reserves, and through the calculation of the mining area carbon cycle model, the estimation results of carbon emissions and carbon reserves are more accurate and reliable, providing strong support for carbon management and carbon trading in the mining area. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic diagram of a method for estimating carbon emissions and carbon reserves in a mineral resource mining area of ​​the present invention;

[0056] Figure 2 It is a schematic diagram of the carbon emission and carbon reserve estimation system of the mineral resource mining area of ​​the present invention. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] In order to solve the problem that the existing technology uses ecological carbon loss, comprehensive energy consumption carbon emissions and mineral carbonation carbon reserves to estimate carbon emissions and carbon reserves, which cannot fully and accurately reflect the actual carbon emissions and carbon reserves in the mining area, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions:

[0059] A method for estimating carbon emissions and carbon reserves in a mineral resource mining area, comprising:

[0060] Step 1: Use satellite remote sensing technology to obtain basic data of mineral resource mining areas and perform preprocessing. The basic data includes mining area geology, soil and hydrological data. At the same time, obtain data from meteorological stations and seismic stations in mineral resource mining areas, including soil data, pH value, initial organic matter content, precipitation, temperature, radiation, etc.;

[0061] Step 2: Use the pre-processed mining area basic data to establish a mining area carbon cycle model, and use machine learning algorithms to train and optimize the established mining area carbon cycle model;

[0062] Step 3: Input the basic data of the mineral resource mining area and the data of the meteorological station and seismic station of the mineral resource mining area into the running mining area carbon cycle model;

[0063] Step 4: Run the mining area carbon cycle model to simulate and predict the carbon emissions and carbon reserves of the mineral resource mining area;

[0064] Step 5: Analyze the output results of the mining area carbon cycle model to obtain the estimated results of carbon emissions and carbon reserves in the mineral resource mining area. By sharing data with meteorological stations, seismic stations and other departments, the real-time and accuracy of the model can be improved. This method can achieve accurate estimation of carbon emissions and carbon reserves in the mining area.

[0065] Use satellite remote sensing technology to obtain basic data of the mining area and perform preprocessing, including:

[0066] Use satellite remote sensing to obtain images of mineral resource mining areas, and at the same time obtain data from meteorological stations and seismic stations in the mining areas;

[0067] Preprocess the collected remote sensing images, including atmospheric correction, geometric correction, radiation correction and image registration. Preprocessing remote sensing images can ensure the accuracy and consistency of image data and reduce errors.

[0068] Extract geological structure, soil data and hydrological characteristics of mineral resource mining areas from pre-processed remote sensing images;

[0069] Satellite remote sensing technology is used to obtain geological, soil and hydrological data of mining areas, so as to achieve comprehensive and accurate acquisition of various data on mineral resource mining areas.

[0070] Extract the geological structure, soil data and hydrological characteristics of the mineral resource mining area from the pre-processed remote sensing image, including:

[0071] Use the Normalized Difference Vegetation Remote Sensing Index to identify the vegetation coverage of mineral resource mining areas, and evaluate soil quality, soil properties and soil nutrients based on the vegetation coverage;

[0072] Analyze the surface features in remote sensing images and the soil reflectance spectrum characteristics to determine soil data, and indirectly evaluate the soil organic matter content by monitoring the light emission characteristics and infrared reflection characteristics of the soil;

[0073] The meteorological sensors on remote sensing satellites capture the water vapor content, cloud type and movement speed in the clouds to estimate the precipitation in the mineral resource mining area. The thermal infrared sensors on remote sensing satellites measure the thermal radiation on the surface and in the atmosphere to infer the surface temperature and atmospheric temperature.

[0074] The intensity of solar radiation in mineral resource mining areas and the surface energy balance are measured by radiometers on remote sensing satellites;

[0075] Extract the hydrological variables of river width, water surface elevation, water surface velocity and river velocity from the collected remote sensing images, input the acquired river width, water surface elevation, water surface velocity and river velocity into the hydrological model to estimate the river flow and satellite gravity land water reserve changes, and obtain the hydrological conditions of the mineral resource mining area;

[0076] According to the image features and rules shown on the remote sensing images, the direct judgment method is used to interpret and extract the structure of the mineral resource mining area and the geological phenomenon information of the rock.

[0077] The carbon cycle model of the mining area is established using the pre-processed basic data of the mining area, including:

[0078] Receive geological data, soil data and hydrological data of mineral resource mining areas;

[0079] The original features of geological data, soil data and hydrological data of mineral resource mining areas are extracted through deep learning methods to extract features that are helpful for model prediction capabilities;

[0080] Normalize the extracted original features to form geological data, soil data and hydrological data of the new mineral resource mining area to adapt to the data distribution and feature relationship required by the model and ensure that the data meets the requirements and format of the model input;

[0081] The CENTURY model was selected and parameterized based on the collected geological data, soil data and hydrological data of the mineral resource mining area to obtain the initial mining area carbon cycle model. The CENTURY model is mainly used to simulate the long-term dynamics of C, N, P and S between different soil-vegetation systems.

[0082] Use machine learning algorithms to train and optimize the mining area carbon cycle model, including:

[0083] Divide the geological data, soil data and hydrological data of the new mineral resource mining area into a training data set and a test data set;

[0084] Use the training data set to train the initial carbon cycle model, and optimize the initial mining area carbon cycle model based on the training results;

[0085] After the optimization is completed, the optimized mining area carbon cycle model is tested using the test data set to evaluate the performance of the mining area carbon cycle model until the performance of the mining area carbon cycle model meets the standard and the final mining area carbon cycle model is obtained.

[0086] The initial mining area carbon cycle model is optimized based on the training results, including:

[0087] Set the quality standards of the initial mining area carbon cycle model, which are the accuracy of the initial mining area carbon cycle model prediction and the degree of fit to the carbon cycle process of the actual mineral resource mining area;

[0088] The parameters of the initial mining area carbon cycle model are optimized using the gradient descent method, and the loss function for the optimization of the parameters of the initial mining area carbon cycle model is set. The loss function is various variables in the carbon cycle process, such as photosynthesis and carbon absorption;

[0089] Set the initial values ​​of the parameters of the initial mining area carbon cycle model, and iterate the parameters of the initial mining area carbon cycle model. In each iteration, calculate the gradient of each parameter of the loss function;

[0090] Use the gradient descent formula to update each parameter of the initial mining area carbon cycle model, repeat parameter iteration and calculate the gradient of each parameter of the loss function until the convergence condition is reached, and the convergence condition is to reach the maximum number of iterations;

[0091] During the optimization process, the cross-validation method is used to evaluate the generalization ability of the initial mining area carbon cycle model, and the initial mining area carbon cycle model is optimized and adjusted based on the evaluation results, including parameter adjustment and model fusion.

[0092] Gradient descent is an iterative algorithm that updates the parameters of the model by minimizing the loss function (or objective function). The core idea is that in each iteration, for each variable, the corresponding parameter value is updated according to the objective function in the opposite direction of the gradient of the variable. The gradient descent method is used to train and optimize the mining area carbon cycle model. It is relatively simple to implement and does not require complex mathematical operations or additional storage space. When the objective function is a convex function, the gradient descent method can ensure that the global optimal solution is found, and when it is close to the optimal solution, the convergence speed will gradually slow down, thereby finely adjusting the model parameters to achieve higher accuracy. By calculating the gradient of the objective function with respect to the model parameters and updating the parameters in the opposite direction of the gradient, the model performance can be continuously optimized.

[0093] A carbon emission and carbon reserve estimation system for a mineral resource mining area is applied in a carbon emission and carbon reserve estimation method for a mineral resource mining area, including:

[0094] The data acquisition module is used to obtain images of mineral resource mining areas using satellite remote sensing, perform preprocessing, extract feature information from the preprocessed remote sensing images, and simultaneously obtain data from the meteorological station and seismic station in the mining area;

[0095] The estimation module is used to construct and optimize the mining area carbon cycle model using the geological data, soil data and hydrological data of the mineral resource mining area, and use the mining area carbon cycle model to output the estimation results of the carbon emissions and carbon reserves of the mineral resource mining area.

[0096] Data acquisition module, including:

[0097] The data acquisition module is used to obtain images of mineral resource mining areas using satellite remote sensing and extract basic data of mineral resource mining areas from the images.

[0098] The preprocessing module is used to perform image enhancement, classification and recognition processing on the acquired data, and extract the geological structure, soil data and hydrological characteristic information of the mineral resource mining area.

[0099] Estimation module, including

[0100] Model building module, used to construct an initial mining area carbon cycle model using geological data, soil data and hydrological data of the mineral resource mining area;

[0101] A model optimization module is used to optimize and adjust the parameters of the initial mining area carbon cycle model using a gradient descent method to obtain an optimized mining area carbon cycle model;

[0102] The result output module is used to run the mining area carbon cycle model to simulate and predict the carbon emissions and carbon reserves of the mineral resource mining area, and obtain the estimated results of the carbon emissions and carbon reserves of the mineral resource mining area.

[0103] Model optimization module, including:

[0104] Divide the geological data, soil data and hydrological data of the new mineral resource mining area into a training data set and a test data set;

[0105] Use the training data set to train the initial carbon cycle model, and set the quality standard of the initial mining area carbon cycle model based on the training results;

[0106] The parameters of the initial mining area carbon cycle model are optimized using the gradient descent method, and the loss function for the optimization of the parameters of the initial mining area carbon cycle model is set;

[0107] Set the initial values ​​of the parameters of the initial mining area carbon cycle model, and iterate the parameters of the initial mining area carbon cycle model. In each iteration, calculate the gradient of each parameter of the loss function;

[0108] Use the gradient descent formula to update each parameter of the initial mining area carbon cycle model, repeat parameter iteration and calculate the gradient of each parameter of the loss function until the convergence condition is reached;

[0109] In the optimization process, the cross-validation method is used to evaluate the generalization ability of the initial mining area carbon cycle model, and the initial mining area carbon cycle model is optimized and adjusted according to the evaluation results, including parameter adjustment and model fusion;

[0110] After the optimization is completed, the optimized mining area carbon cycle model is tested using the test data set to evaluate the performance of the mining area carbon cycle model until the performance of the mining area carbon cycle model meets the standard and the final mining area carbon cycle model is obtained.

[0111] By sharing data with meteorological stations, seismic stations and other departments, the real-time and accuracy of the mining area carbon cycle model can be effectively improved.

[0112] In summary, the carbon emission and carbon reserve estimation method and system of a mineral resource mining area of ​​the present invention uses the gradient descent method to train and optimize the mining area carbon cycle model, which is relatively simple to implement and does not require complex mathematical operations or additional storage space. When the objective function is a convex function, the gradient descent method can ensure that the global optimal solution is found, and when approaching the optimal solution, the convergence speed will gradually slow down, thereby finely adjusting the model parameters to achieve higher accuracy. By calculating the gradient of the objective function with respect to the model parameters and updating the parameters in the opposite direction of the gradient, the model performance can be continuously optimized. The mining area carbon cycle model can be used to comprehensively consider the mineral resource mining area. The carbon flow within the mineral resource mining area, including the source, path and reserves of carbon emissions, can more accurately estimate the carbon emissions of the mineral resource mining area. The mining area carbon cycle model can update the estimation results of carbon emissions and carbon reserves in real time according to the changes in the basic data of the mineral resource mining area. As the basic data of the mineral resource mining area changes, the mining area carbon cycle model can adjust the estimation value in time to ensure the accuracy and timeliness of the estimation results, so that the mineral resource mining area can grasp the latest situation of carbon emissions and carbon reserves in time. Through the calculation of the mining area carbon cycle model, the estimation results of carbon emissions and carbon reserves are more accurate and reliable, providing strong support for the carbon management and carbon trading of the mining area.

[0113] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0114] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for estimating carbon emissions and carbon reserves in a mineral resource mining area, characterized in that: include: Step 1: Use satellite remote sensing technology to obtain basic data of mineral resource mining areas, perform preprocessing, and obtain data from meteorological stations and seismic stations in mineral resource mining areas; Step 2: Use the pre-processed mining area basic data to establish a mining area carbon cycle model, and use machine learning algorithms to train and optimize the established mining area carbon cycle model; Step 3: Input the basic data of the mineral resource mining area and the data of the meteorological station and seismic station of the mineral resource mining area into the running mining area carbon cycle model; Step 4: Run the mining area carbon cycle model to simulate and predict the carbon emissions and carbon reserves of the mineral resource mining area; Step 5: Analyze the output results of the mining area carbon cycle model to obtain the estimated results of carbon emissions and carbon reserves in the mineral resource mining area.

2. A method for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 1, characterized in that ,The use of satellite remote sensing technology to obtain the basic data of the mining area and pre-process it specifically includes: Use satellite remote sensing to obtain images of mineral resource mining areas, and at the same time obtain data from meteorological stations and seismic stations in mineral resource mining areas; Preprocess the collected remote sensing images, including atmospheric correction, geometric correction, radiation correction and image registration; Extract the geological structure, soil data and hydrological characteristics information of the mineral resource mining area from the pre-processed remote sensing images.

3. A method for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 2, characterized in that , the extraction of geological structure, soil data and hydrological characteristic information of mineral resource mining areas in the pre-processed remote sensing image specifically includes: Use the Normalized Difference Vegetation Remote Sensing Index to identify the vegetation coverage of mineral resource mining areas, and evaluate soil quality, soil properties and soil nutrients based on the vegetation coverage; Analyze the surface features in remote sensing images and the soil reflectance spectrum characteristics to determine soil data, and indirectly evaluate the soil organic matter content by monitoring the light emission characteristics and infrared reflection characteristics of the soil; The meteorological sensors on remote sensing satellites capture the water vapor content, cloud type and movement speed in the clouds to estimate the precipitation in the mineral resource mining area. The thermal infrared sensors on remote sensing satellites measure the thermal radiation on the surface and in the atmosphere to infer the surface temperature and atmospheric temperature. The intensity of solar radiation in mineral resource mining areas and the surface energy balance are measured by radiometers on remote sensing satellites; Extract the hydrological variables of river width, water surface elevation, water surface velocity and river velocity from the collected remote sensing images, input the acquired river width, water surface elevation, water surface velocity and river velocity into the hydrological model to estimate the river flow and satellite gravity land water reserve changes, and obtain the hydrological conditions of the mineral resource mining area; According to the image features and rules shown on the remote sensing images, the direct judgment method is used to interpret and extract the structure of the mineral resource mining area and the geological phenomenon information of the rock.

4. The method for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 1, characterized in that The method of using the pre-processed basic data of the mining area to establish a mining area carbon cycle model specifically includes: Receive geological data, soil data and hydrological data of mineral resource mining areas, and obtain data from meteorological stations and seismic stations in mining areas; Extract original features from geological data, soil data, and hydrological data of mineral resource mining areas through deep learning methods; Normalize the extracted original features to form geological data, soil data and hydrological data of new mineral resource mining areas; The CENTURY model was selected and parameterized based on the collected geological data, soil data and hydrological data of the mineral resource mining area to obtain the initial mining area carbon cycle model.

5. The method for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 1, characterized in that The method of using machine learning algorithms to train and optimize the mining area carbon cycle model specifically includes: Divide the geological data, soil data and hydrological data of the new mineral resource mining area into a training data set and a test data set; Use the training data set to train the initial carbon cycle model, and optimize the initial mining area carbon cycle model based on the training results; After the optimization is completed, the optimized mining area carbon cycle model is tested using the test data set to evaluate the performance of the mining area carbon cycle model until the performance of the mining area carbon cycle model meets the standard and the final mining area carbon cycle model is obtained.

6. A method for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 5, characterized in that , the initial mining area carbon cycle model is optimized according to the training results, specifically including: Set the quality standards of the initial mining area carbon cycle model, which are the accuracy of the initial mining area carbon cycle model prediction and the degree of fit to the carbon cycle process of the actual mineral resource mining area; The parameters of the initial mining area carbon cycle model are optimized using the gradient descent method, and the loss function for the optimization of the parameters of the initial mining area carbon cycle model is set; Set the initial values ​​of the parameters of the initial mining area carbon cycle model, and iterate the parameters of the initial mining area carbon cycle model. In each iteration, calculate the gradient of each parameter of the loss function; Use the gradient descent formula to update each parameter of the initial mining area carbon cycle model, repeat parameter iteration and calculate the gradient of each parameter of the loss function until the convergence condition is reached, and the convergence condition is to reach the maximum number of iterations; During the optimization process, the cross-validation method is used to evaluate the generalization ability of the initial mining area carbon cycle model, and the initial mining area carbon cycle model is optimized and adjusted based on the evaluation results, including parameter adjustment and model fusion.

7. A system for estimating carbon emissions and carbon reserves in a mineral resource mining area, applied in the method for estimating carbon emissions and carbon reserves in a mineral resource mining area as claimed in claim 6, characterized in that ,include: The data acquisition module is used to obtain images of mineral resource mining areas using satellite remote sensing, perform preprocessing, extract feature information from the preprocessed remote sensing images, and simultaneously obtain data from the meteorological station and seismic station in the mining area; The estimation module is used to construct and optimize the mining area carbon cycle model using the geological data, soil data and hydrological data of the mineral resource mining area, and use the mining area carbon cycle model to output the estimation results of the carbon emissions and carbon reserves of the mineral resource mining area.

8. A system for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 7, characterized in that ,The data acquisition module includes: The data acquisition module is used to obtain images of mineral resource mining areas using satellite remote sensing, and to obtain data from meteorological stations and seismic stations in the mining areas; The preprocessing module is used to perform image enhancement, classification and recognition processing on the acquired data, and extract the geological structure, soil data and hydrological characteristic information of the mineral resource mining area.

9. A system for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 7, characterized in that ,The estimation module comprises: Model building module, used to construct an initial mining area carbon cycle model using geological data, soil data and hydrological data of the mineral resource mining area; A model optimization module is used to optimize and adjust the parameters of the initial mining area carbon cycle model using a gradient descent method to obtain an optimized mining area carbon cycle model; The result output module is used to run the mining area carbon cycle model to simulate and predict the carbon emissions and carbon reserves of the mineral resource mining area, and obtain the estimated results of the carbon emissions and carbon reserves of the mineral resource mining area.

10. A system for estimating carbon emissions and carbon reserves in a mineral resource mining area according to claim 9, characterized in that ,The model optimization module includes: Divide the geological data, soil data and hydrological data of the new mineral resource mining area into a training data set and a test data set; The initial carbon cycle model is trained using the training data set, and the parameters of the initial mining area carbon cycle model are continuously iterated using the gradient descent method based on the training results; In the iterative process, the cross-validation method is used to evaluate the generalization ability of the initial mining area carbon cycle model, and the initial mining area carbon cycle model is optimized and adjusted according to the evaluation results; After the optimization is completed, the optimized mining area carbon cycle model is tested using the test data set to evaluate the performance of the mining area carbon cycle model until the performance of the mining area carbon cycle model meets the standard and the final mining area carbon cycle model is obtained.

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