A land use planning system based on soil organic carbon monitoring

Abstract

The invention discloses a land use planning system based on soil organic carbon monitoring, including a data acquisition module, a data processing module, a data storage module, a model building module, a land use planning module and a report generation module; the data acquisition module is responsible for collecting soil organic carbon monitoring data and land use data; the data processing module performs data preprocessing on the collected data; the data analysis and evaluation module analyzes the data and evaluates the land use change; the report generation module makes a graphical report; the data storage module saves the collected data and the evaluation results; the model building module builds a prediction model based on the data and the evaluation results, and the land use planning module is used to generate a land use change plan. The system builds a prediction model through big data analysis, realizes efficient and accurate prediction of soil organic carbon content, comprehensively evaluates the impact of land use changes, reduces costs and improves prediction accuracy, and can generate a land use change plan for reference decision-making.

Description

Technical Field

[0001] The present invention belongs to the technical field of organic carbon monitoring, and specifically refers to a land use planning system based on soil organic carbon monitoring. Background Art

[0002] With the global population growth and economic development, land use change has become an inevitable phenomenon. These changes, including deforestation, urban expansion and agricultural cultivation, have not only reshaped the surface landscape, but also profoundly affected the dynamic balance of soil organic carbon. As a core indicator of soil quality, the fluctuation of organic carbon reserves is directly related to the health of ecosystems, agricultural productivity and the stability of the global carbon cycle. Therefore, the monitoring of organic carbon content under land use change is particularly critical, which is of great significance for guiding land management, responding to climate change and promoting sustainable development. Although traditional ground sampling and laboratory analysis methods provide an accurate means for the determination of organic carbon content, they have certain limitations in implementation. These methods are not only costly and time-consuming, but also difficult to adapt to large-scale and high-frequency monitoring needs. In addition, the lack of real-time monitoring and the complexity of data processing also limit the application of these technologies in rapidly changing environments. Existing technologies still have room for improvement in monitoring accuracy, data collection efficiency and model prediction capabilities. Summary of the invention

[0003] In order to solve the problems in the above-mentioned prior art of insufficient soil organic carbon content monitoring accuracy, difficulty in data acquisition, poor real-time performance, high cost, low technical integration and limited model prediction ability, the present invention proposes a land use planning system based on soil organic carbon monitoring, which can construct a prediction model through big data analysis, realize efficient and accurate prediction of soil organic carbon content, comprehensively evaluate the impact of land use changes, reduce costs and improve prediction accuracy, and generate land use change plans for reference decision-making.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: a land use planning system based on soil organic carbon monitoring, including a data acquisition module, a data processing module, a data storage module, a model building module, a land use planning module and a report generation module, wherein: the data acquisition module includes a land use change monitoring submodule and a soil carbon content monitoring submodule, the land use change monitoring submodule is used to monitor the land use situation of each region, the land use situation includes land use type, recording time and land use area; the soil carbon content monitoring submodule is used to monitor the soil organic carbon content of each region; the land use type includes: cultivated land, original land, forest land, grassland land, wetlands, land for transportation, urban and rural land, water areas and land for water conservancy facilities; the data processing module is used to pre-process the data collected by the data acquisition module; the data storage module is used to store the data collected by the data acquisition module; the model construction module is used to construct a soil carbon content change prediction model based on the data collected by the data acquisition module, and the soil carbon content change prediction model can predict the soil carbon content change in a specified future year based on the existing soil organic carbon content and land use changes; the land use planning module is used to plan land use according to the prediction results of the soil carbon content change prediction model; the report generation module is used to generate a report.

[0005] Furthermore, the land use planning module includes a carbon content calculation area selection unit, a land use planning area selection unit, a planning target input unit and a model deduction unit, wherein:

[0006] The carbon content calculation area selection unit is used for the user to select an area where soil carbon content calculation is required, and the soil carbon content change prediction model is used to predict the soil carbon content change in a specified future year according to the land use change input by the user;

[0007] The land use planning area selection unit is used for the user to select an area that needs to be land use planned. When planning land use, only the selected area will be changed in land use;

[0008] The planning target input unit is used for the user to input the planning target, including a target land setting unit, a change area setting unit, a soil carbon content target setting unit, and a year setting unit;

[0009] The model deduction unit is used to randomly generate a number of land use change plans and select a plan that meets the soil carbon content requirements in a set year. The deduction process specifically includes the following steps:

[0010] Step S1: randomly combining the areas selected by the selected unit in the land use planning area to generate a land use change plan, wherein the land use change plan includes a number of area numbers;

[0011] Step S2: searching the data storage module by the area number in the land use change plan to obtain the area, land use type and land use area of ​​each area;

[0012] Step S3: Calculate the sum of the area of ​​each region in each land use change plan, and filter out the land use change plans whose sum of area is smaller than the area set by the change area setting unit;

[0013] Step S4: inputting the land use change situation of each area into the soil carbon content change prediction model to obtain the soil carbon content prediction result of the selected area of ​​the selected unit in the carbon content calculation area, wherein the land use change situation includes the current land use type and the target land use type;

[0014] Step S5: obtaining the soil carbon content prediction result of each land use change plan in the target year set in the year setting unit;

[0015] Step S6: screening out land use change schemes whose soil carbon content meets the soil carbon content target set by the soil carbon content target setting unit;

[0016] Step S7: Generate a planning report through the report generation module. The land use plan can be used to deduce a land use change plan that meets the requirements based on the input target and the existing land use situation.

[0017] Furthermore, the land use planning module also includes a regional constraint input unit and a land use change difficulty assessment unit, wherein:

[0018] The regional constraint input unit is used to add constraint conditions to the deduction process of the model deduction unit, and can input the minimum number of connected areas for land use change to screen out land use change plans that do not meet the requirements;

[0019] The land use change difficulty assessment unit is used to assess the difficulty of land use change, and the assessment indicators include land use change cost and land use change time, and feedback is provided through the report generation module. This avoids the deduction result that the land use change area is too scattered, calculates the land use change difficulty of each scheme, and facilitates users to make decisions.

[0020] Furthermore, the data acquisition module also includes:

[0021] The historical data acquisition submodule is used to retrieve and import historical soil organic carbon monitoring data and land use change monitoring data. It can extract the changes in soil organic carbon content after land use changes.

[0022] Furthermore, the data processing module includes:

[0023] Data cleaning unit, used to remove abnormal and noisy data;

[0024] The regional division unit is used to divide the regions. Each region has a corresponding number, and the collected soil carbon content monitoring data and land use monitoring data are matched to their respective regions;

[0025] The data integration unit is used to integrate data from different sources.

[0026] Furthermore, the data processing module further includes a region division normalization processing submodule, and the region division normalization processing submodule includes:

[0027] Data mapping unit, used to map land use data collected over different periods into a unified reference frame or classification system;

[0028] Separation of standardized units is used to ensure that land use data collected in different periods follow a unified land use classification standard;

[0029] A region boundary correction unit, used to correct the boundaries of land use regions;

[0030] Attribute conversion unit, used to convert or adjust the attribute data of land use areas to ensure data consistency;

[0031] The time series alignment unit is used to adjust and calibrate the time series of monitoring data.

[0032] Furthermore, it also includes a data missing prompt module, which is used to detect whether the land use monitoring data and soil carbon content monitoring data of each area divided by the area division unit are complete, detect whether there is data missing, and generate a data missing report through the report generation module. Prompt to supplement and complete the data, and automatically fill in the data through the soil carbon content prediction model when necessary.

[0033] Furthermore, the land use change monitoring submodule includes a remote sensing monitoring unit and a proofreading and evaluation unit. The remote sensing monitoring unit is used to obtain remote sensing data of each region, perform regional division and image recognition on the remote sensing data, and evaluate the land use situation of each region; the proofreading and evaluation unit is used to compare the land use evaluation result of the remote sensing monitoring unit with the soil carbon content of the region, detect whether the land use evaluation result matches the soil carbon content, and generate a report through the report generation module if there is an abnormality;

[0034] The soil carbon content monitoring submodule includes a sampling location time recording unit and a sample detection result feedback unit. The sampling location time recording unit is used to record the coordinates and sampling time of the sampling position when soil sampling is performed in each area; the sample detection result feedback unit is used to feedback the organic carbon content detection results of multiple soil samples in each area.

[0035] Furthermore, the model building module includes:

[0036] A machine learning algorithm submodule for analyzing historical data and building predictive models;

[0037] Parameter optimization mechanism submodule, which is used to adjust model parameters to improve prediction accuracy.

[0038] Furthermore, it also includes a model iteration optimization module, and the model iteration optimization module includes:

[0039] A verification data input unit, used to input the newly collected monitoring data as verification data into each prediction model constructed by the model construction module, and obtain the prediction result;

[0040] The error analysis unit is used to analyze the differences between the prediction results of each prediction model and the actual monitoring data, and to score the prediction accuracy of the model;

[0041] A parameter adjustment unit, used to adjust the model parameters according to the analysis results;

[0042] The model optimization unit is used to retrain the model with updated parameters and new data. The model is continuously updated to make the prediction results of the soil organic carbon content prediction model more accurate.

[0043] The beneficial effects of the land use planning system based on soil organic carbon monitoring of the present invention are as follows: a data acquisition module is provided, which realizes rapid and comprehensive monitoring of soil organic carbon content by integrating a land use change monitoring submodule and a historical data acquisition submodule, and significantly improves the efficiency of monitoring work; a land use area normalization processing module ensures the consistency of monitoring data in different periods, and improves the comparability of data through data mapping, classification standardization and boundary correction, providing a basis for accurate trend analysis; a prediction model iterative optimization module uses newly acquired monitoring data to evaluate and optimize the prediction model in real time, ensuring the accuracy and reliability of the prediction results; by constructing a prediction model, the impact of land use changes on soil organic carbon content changes can be predicted, which is helpful to formulate more scientific soil management measures; a land use planning module is provided, which can deduce a land use change plan that meets the requirements based on the input land use goals and existing land use conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a system architecture diagram of a land use planning system based on soil organic carbon monitoring according to the present invention;

[0045] Figure 2 This is a system architecture diagram of a data acquisition module of a land use planning system based on soil organic carbon monitoring according to the present invention;

[0046] Figure 3 This is a system architecture diagram of a data processing module of a land use planning system based on soil organic carbon monitoring according to the present invention;

[0047] Figure 4 This is a system architecture diagram of a model building module of a land use planning system based on soil organic carbon monitoring according to the present invention;

[0048] Figure 5 A system architecture diagram of a land use planning module of a land use planning system based on soil organic carbon monitoring according to the present invention;

[0049] Figure 6 This is a system architecture diagram of a model iteration optimization module of a land use planning system based on soil organic carbon monitoring according to the present invention;

[0050] Figure 7 It is a schematic diagram of the deduction steps of a model deduction unit of a land use planning system based on soil organic carbon monitoring according to the present invention.

[0051] Among them, 1-data acquisition module, 11-land use change monitoring submodule, 111-remote sensing monitoring unit, 112-proofreading and evaluation unit, 12-soil carbon content monitoring submodule, 121-sampling location time recording unit, 122-sample test result feedback unit, 13-historical data acquisition submodule, 2-data processing module, 21-data cleaning unit, 22-regional division unit, 23-data integration unit, 24-regional division normalization processing submodule, 241-data mapping unit, 242-separation and standardization unit, 243-regional boundary correction unit, 244-attribute conversion unit, 245-time series alignment unit, 3-data storage module, 4-model building module Block, 41-machine learning algorithm submodule, 42-parameter optimization mechanism submodule, 5-land use planning module, 51-carbon content calculation area selection unit, 52-land use planning area selection unit, 53-planning target input unit, 531-target land use setting unit, 532-change area setting unit, 533-soil carbon content target setting unit, 534-year setting unit, 54-model deduction unit, 55-regional constraint input unit, 56-land use change difficulty assessment unit, 6-report generation module, 7-model iteration optimization module, 71-verification data input unit, 72-error analysis unit, 73-parameter adjustment unit, 74-model optimization unit. DETAILED DESCRIPTION

[0052] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. 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.

[0053] like Figure 1-7As shown, the present invention is a land use planning system based on soil organic carbon monitoring, including a data acquisition module 1, a data processing module 2, a data storage module 3, a model building module 4, a land use planning module 5 and a report generation module 6, wherein: the data acquisition module 1 includes a land use change monitoring submodule 11 and a soil carbon content monitoring submodule 12, the land use change monitoring submodule 11 is used to monitor the land use situation of each region, the land use situation includes land use type, recording time and land use area; the soil carbon content monitoring submodule 12 is used to monitor the soil organic carbon content of each region; the land use type includes: cultivated land, original land, forest land, grassland, wetland, Land for transportation, urban and rural land, water areas and land for water conservancy facilities; the data processing module 2 is used to pre-process the data collected by the data acquisition module 1; the data storage module 3 is used to store the data collected by the data acquisition module 1; the model construction module 4 is used to construct a soil carbon content change prediction model based on the data collected by the data acquisition module 1, and the soil carbon content change prediction model can predict the soil carbon content change in a specified future year based on the existing soil organic carbon content and land use changes; the land use planning module 5 is used to plan land use according to the prediction results of the soil carbon content change prediction model; the report generation module 6 is used to generate a report.

[0054] Furthermore, the land use planning module 5 includes a carbon content calculation area selection unit 51, a land use planning area selection unit 52, a planning target input unit 53 and a model deduction unit 54, wherein:

[0055] The carbon content calculation area selection unit 51 is used for allowing the user to select an area where soil carbon content calculation is required, and the soil carbon content change in a future specified year is predicted based on the land use change input by the user through the soil carbon content change prediction model;

[0056] The land use planning area selection unit 52 is used for the user to select an area that needs to be land use planned. When planning land use, only the selected area will be changed in land use;

[0057] The planning target input unit 53 is used for the user to input the planning target, and includes a target land setting unit 531, a change area setting unit 532, a soil carbon content target setting unit 533, and a year setting unit 534;

[0058] The model deduction unit 54 is used to randomly generate a number of land use change plans and select a plan that meets the soil carbon content requirements in a set year. The deduction process specifically includes the following steps:

[0059] Step S1: randomly combining the areas selected by the land use planning area selection unit 52 to generate a land use change plan, wherein the land use change plan includes a number of area numbers;

[0060] Step S2: searching the data storage module 3 by the area number in the land use change plan to obtain the area, land use type and land use area of ​​each area;

[0061] Step S3: Calculate the sum of the area of ​​each region in each land use change scheme, and filter out the land use change scheme whose sum of area is smaller than the area set by the change area setting unit 532;

[0062] Step S4: inputting the land use change situation of each region into the soil carbon content change prediction model to obtain the soil carbon content prediction result of the region selected by the carbon content calculation region selection unit 51, wherein the land use change situation includes the current land use type and the target land use type;

[0063] Step S5: obtaining the soil carbon content prediction result of each land use change scheme in the target year set in the year setting unit 534;

[0064] Step S6: Screening out land use change schemes whose soil carbon content meets the soil carbon content target set by the soil carbon content target setting unit 533;

[0065] Step S7: Generate a planning report through the report generation module 6. The land use planning can be used to deduce a land use change plan that meets the requirements based on the input target and the existing land use situation.

[0066] Furthermore, the land use planning module 5 also includes a regional constraint input unit 55 and a land use change difficulty assessment unit 56, wherein:

[0067] The regional constraint input unit 55 is used to add constraint conditions to the deduction process of the model deduction unit 54, and can input the minimum number of connected areas for land use change to filter out land use change plans that do not meet the requirements;

[0068] The land use change difficulty assessment unit 56 is used to assess the difficulty of land use change, and the assessment indicators include land use change cost and land use change time, and feedback is provided through the report generation module 6. In order to avoid obtaining deduction results that the land use change area is too dispersed, the land use change difficulty of each scheme is calculated, and it is convenient for users to make reference decisions.

[0069] Furthermore, the data acquisition module 1 also includes:

[0070] The historical data acquisition submodule 13 is used to retrieve and import historical soil organic carbon monitoring data and land use change monitoring data. The change in soil organic carbon content after the change in land use can be extracted.

[0071] Furthermore, the data processing module 2 includes:

[0072] A data cleaning unit 21, used to remove abnormal and noisy data;

[0073] The area division unit 22 is used to divide the areas, each area has a corresponding number, and the collected soil carbon content monitoring data and land use monitoring data are matched to their respective areas.

[0074] The data integration unit 23 is used to integrate data from different sources.

[0075] Furthermore, the data processing module 2 further includes a region division normalization processing submodule 24, and the region division normalization processing submodule 24 includes:

[0076] A data mapping unit 241 for mapping land use data collected at different periods into a unified reference frame or classification system;

[0077] A separation standardization unit 242 is used to ensure that the land use data collected in different periods follow a unified land use classification standard;

[0078] A region boundary correction unit 243, used to correct the boundary of the land use region;

[0079] The attribute conversion unit 244 is used to convert or adjust the attribute data of the land use area to ensure data consistency;

[0080] The time series alignment unit 245 is used to adjust and calibrate the time series of the monitoring data.

[0081] Furthermore, it also includes a data missing prompt module 8, which is used to detect whether the land use monitoring data and soil carbon content monitoring data of each area divided by the area division unit 22 are complete, detect whether there is data missing, and generate a data missing report through the report generation module 6. It reminds you to supplement and complete the data, and automatically fills in the data through the soil carbon content prediction model when necessary.

[0082] Furthermore, the land use change monitoring submodule 11 includes a remote sensing monitoring unit 111 and a proofreading and evaluation unit 112. The remote sensing monitoring unit 111 is used to obtain remote sensing data of each region, perform regional division and image recognition on the remote sensing data, and evaluate the land use situation of each region; the proofreading and evaluation unit 112 is used to compare the land use evaluation result of the remote sensing monitoring unit 111 with the soil carbon content of the region, detect whether the land use evaluation result matches the soil carbon content, and generate a report through the report generation module if there is an abnormality;

[0083] The soil carbon content monitoring submodule 12 includes a sampling location time recording unit 121 and a sample detection result feedback unit 122. The sampling location time recording unit 121 is used to record the coordinates and sampling time of the sampling position when soil sampling is performed in each area; the sample detection result feedback unit 122 is used to feedback the organic carbon content detection results of multiple soil samples in each area.

[0084] Furthermore, the model building module 4 includes:

[0085] A machine learning algorithm submodule 41 for analyzing historical data and building a prediction model;

[0086] The parameter optimization mechanism submodule 42 is used to adjust the model parameters to improve the prediction accuracy.

[0087] Furthermore, it also includes a model iteration optimization module 7, and the model iteration optimization module 7 includes:

[0088] A verification data input unit 71, used to input the newly collected monitoring data as verification data into each prediction model constructed by the model construction module 4, and obtain the prediction result;

[0089] The error analysis unit 72 is used to analyze the difference between the prediction results of each prediction model and the actual monitoring data, and to score the prediction accuracy of the model;

[0090] A parameter adjustment unit 73, used to adjust the model parameters according to the analysis results;

[0091] The model optimization unit 74 is used to retrain the model using updated parameters and new data, and continuously update the model to make the prediction results of the soil organic carbon content prediction model more accurate.

[0092] The beneficial effects of the land use planning system based on soil organic carbon monitoring of the present invention are as follows: a data acquisition module is provided, which realizes rapid and comprehensive monitoring of soil organic carbon content by integrating a land use change monitoring submodule and a historical data acquisition submodule, and significantly improves the efficiency of monitoring work; a land use area normalization processing module ensures the consistency of monitoring data in different periods, and improves the comparability of data through data mapping, classification standardization and boundary correction, providing a basis for accurate trend analysis; a prediction model iterative optimization module uses newly acquired monitoring data to evaluate and optimize the prediction model in real time, ensuring the accuracy and reliability of the prediction results; by constructing a prediction model, the impact of land use changes on soil organic carbon content changes can be predicted, which is helpful to formulate more scientific soil management measures; a land use planning module is provided, which can deduce a land use change plan that meets the requirements based on the input land use goals and existing land use conditions.

[0093] The present invention and its embodiments are described above, which is not restrictive. What is shown in the accompanying drawings is only one of the embodiments of the present invention, and the actual content is not limited to this. In short, if ordinary technicians in this field are inspired by it and do not deviate from the purpose of the invention, they can creatively design structural methods and embodiments similar to the technical scheme, which should all fall within the scope of protection of the present invention.

Claims

1. A land use planning system based on soil organic carbon monitoring, characterized by: The invention comprises a data collection module (1), a data processing module (2), a data storage module (3), a model building module (4), a land use planning module (5) and a report generation module (6), wherein: the data collection module (1) comprises a land use change monitoring submodule (11) and a soil carbon content monitoring submodule (12), the land use change monitoring submodule (11) is used to monitor the land use situation of each region, the land use situation includes land use type, recording time and land use area; the soil carbon content monitoring submodule (12) is used to monitor the soil organic carbon content of each region; the data processing module (2) used to pre-process the data collected by the data collection module (1); the data storage module (3) is used to store the data collected by the data collection module (1); the model construction module (4) is used to construct a soil carbon content change prediction model based on the data collected by the data collection module (1), and the soil carbon content change prediction model can predict the soil carbon content change in a specified future year based on the existing soil organic carbon content and land use changes; the land use planning module (5) is used to plan land use based on the prediction results of the soil carbon content change prediction model; the report generation module (6) is used to generate a report; The land use planning module (5) comprises a carbon content calculation area selection unit (51), a land use planning area selection unit (52), a planning target input unit (53) and a model deduction unit (54), wherein: The carbon content calculation area selection unit (51) is used for allowing a user to select an area where soil carbon content calculation is required, and the soil carbon content change prediction model is used to predict the soil carbon content change in a future specified year according to the land use change input by the user; The land use planning area selection unit (52) is used for the user to select an area that needs to be land use planned. When planning land use, only the selected area will be changed in land use; The planning target input unit (53) is used for the user to input the planning target, and includes a target land setting unit (531), a change area setting unit (532), a soil carbon content target setting unit (533), and a year setting unit (534); The model deduction unit (54) is used to randomly generate a number of land use change plans and select a plan that meets the soil carbon content requirements in a set year. The deduction process specifically includes the following steps: Step S1: randomly combining the areas selected by the land use planning area selection unit (52) to generate a land use change plan, wherein the land use change plan includes a plurality of area numbers; Step S2: searching the data storage module (3) by the area number in the land use change plan to obtain the area, land use type and land use area of ​​each area; Step S3: Calculate the sum of the area of ​​each region in each land use change plan, and filter out the land use change plans whose sum of area is smaller than the area set by the change area setting unit (532); Step S4: inputting the land use change situation of each area into the soil carbon content change prediction model to obtain the soil carbon content prediction result of the area selected by the carbon content calculation area selected unit (51), wherein the land use change situation includes the current land use type and the target land use type; Step S5: obtaining the soil carbon content prediction result of each land use change plan in the target year set in the year setting unit (534); Step S6: screening out land use change schemes whose soil carbon content meets the soil carbon content target set by the soil carbon content target setting unit (533); Step S7: Generate a planning scheme report through the report generation module (6).

2. A land use planning system based on soil organic carbon monitoring according to claim 1, characterized in that: The land use planning module (5) further comprises a regional constraint condition input unit (55) and a land use change difficulty assessment unit (56), wherein: The regional constraint condition input unit (55) is used to add constraint conditions to the deduction process of the model deduction unit (54), and can input the minimum number of connected areas for land use change to filter out land use change plans that do not meet the requirements; The land use change difficulty assessment unit (56) is used to assess the difficulty of land use change, and the assessment indicators include land use change cost and land use change time, and feedback is provided through the report generation module (6).

3. The land use planning system based on soil organic carbon monitoring according to claim 1, characterized in that: The data acquisition module (1) further comprises: The historical data acquisition submodule (13) is used to retrieve and import historical soil organic carbon monitoring data and land use change monitoring data.

4. The land use planning system based on soil organic carbon monitoring according to claim 3 is characterized by: The data processing module (2) comprises: A data cleaning unit (21) for removing abnormal and noisy data; A region division unit (22) is used to divide regions, each region has a corresponding number, and the collected soil carbon content monitoring data and land use monitoring data are matched to their respective regions; The data integration unit (23) is used to integrate data from different sources.

5. A land use planning system based on soil organic carbon monitoring according to claim 4, characterized in that: The data processing module (2) further comprises a region division normalization processing submodule (24), wherein the region division normalization processing submodule (24) comprises: A data mapping unit (241) for mapping land use data collected at different periods into a unified reference frame or classification system; A separation standardization unit (242) is used to ensure that the land use data collected at different times follow a unified land use classification standard; A region boundary correction unit (243) for correcting the boundary of a land use region; An attribute conversion unit (244) is used to convert or adjust the attribute data of the land use area to ensure data consistency; The time series alignment unit (245) is used to adjust and calibrate the time series of monitoring data.

6. A land use planning system based on soil organic carbon monitoring according to claim 5, characterized in that: It also includes a data missing prompt module (8), which is used to detect whether the land use monitoring data and soil carbon content monitoring data of each area divided by the area division unit (22) are complete, detect whether there is data missing, and generate a data missing report through the report generation module (6).

7. The land use planning system based on soil organic carbon monitoring according to claim 1, characterized in that: The land use change monitoring submodule (11) comprises a remote sensing monitoring unit (111) and a proofreading and evaluation unit (112), wherein the remote sensing monitoring unit (111) is used to obtain remote sensing data of each region, perform regional division and image recognition on the remote sensing data, and evaluate the land use situation of each region; The proofreading and evaluation unit (112) is used to compare the land use evaluation result of the remote sensing monitoring unit (111) with the soil carbon content of the area, to detect whether the land use evaluation result matches the soil carbon content, and if there is an abnormality, to generate a report through the report generation module; The soil carbon content monitoring submodule (12) comprises a sampling location time recording unit (121) and a sample detection result feedback unit (122), wherein the sampling location time recording unit (121) is used to record the coordinates of the sampling location and the sampling time when soil sampling is performed in each area; The sample detection result feedback unit (122) is used to feed back the detection results of the organic carbon content of multiple soil samples in various regions.

8. The land use planning system based on soil organic carbon monitoring according to claim 1, characterized in that: The model building module (4) comprises: A machine learning algorithm submodule (41) for analyzing historical data and building a prediction model; The parameter optimization mechanism submodule (42) is used to adjust the model parameters to improve the prediction accuracy.

9. A land use planning system based on soil organic carbon monitoring according to claim 8, characterized in that: The system also includes a model iteration optimization module (7), wherein the model iteration optimization module (7) includes: A verification data input unit (71) is used to input the newly collected monitoring data as verification data into each prediction model constructed by the model construction module (4) and obtain a prediction result; An error analysis unit (72) is used to analyze the difference between the prediction results of each prediction model and the actual monitoring data, and to score the prediction accuracy of the model; A parameter adjustment unit (73), used for adjusting model parameters according to the analysis results; The model optimization unit (74) is used to retrain the model using updated parameters and new data.

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