Topsoil retention method and system for brown soil farmland

Abstract

The present invention discloses a topsoil retention method and system for brown soil farmland, relating to the field of land erosion monitoring technology. The method comprises: retrieving brown soil farmland regional management data to collect farmland data, constructing a soil erosion prediction model and inputting the data to obtain prediction results, formulating a topsoil retention plan based on the results and matching the regional management data, executing the plan and activating a monitoring mechanism for evaluation, and optimizing the plan based on the evaluation results to intelligently retain the topsoil. This method solves the technical problems of existing topsoil retention technologies, such as inaccurate soil erosion prediction, lack of scientific and targeted plan formulation, and lack of effective monitoring and feedback optimization mechanisms. By optimizing the entire process of topsoil retention in brown soil farmland, the method achieves the technical effects of reducing soil erosion, improving soil fertility, and increasing crop yield and quality.

Description

Technical Field

[0001] The present application relates to the field of land erosion monitoring technology, and in particular to a method and system for retaining topsoil in brown soil farmland. Background Art

[0002] In the context of brown soil farmland management and protection, the problem of topsoil loss is becoming increasingly serious, and the corresponding demand for scientific and effective topsoil retention technology is becoming more urgent. Exploring and applying comprehensive and precise topsoil retention methods has become a key link in ensuring the sustainable use of brown soil farmland. Traditional methods of topsoil protection for brown soil farmland are often extensive and one-sided, focusing only on simple fertilization or single soil and water conservation projects. There is a lack of in-depth research on the causes and changing patterns of soil erosion, and a lack of comprehensive consideration of soil characteristics and farmland environment. It is difficult to accurately predict soil erosion conditions. In the formulation of topsoil retention plans, there is a lack of scientific and targeted approach, resulting in poor results in some areas and unsatisfactory input-output ratios in other areas. The ability to adapt to the actual needs of agricultural production is insufficient, and it cannot cope well with the complex and changing farmland ecological environment.

[0003] At present, relevant technologies still have technical problems such as inaccurate soil erosion prediction in topsoil retention technology, lack of scientific and targeted program formulation, and lack of effective monitoring and feedback optimization mechanism. Summary of the Invention

[0004] This application provides a topsoil retention method and system for brown soil farmland, collects farmland data by retrieving regional management data of brown soil farmland, constructs a soil erosion prediction model and inputs data to obtain prediction results, formulates a topsoil retention plan based on the results and matches regional management data, implements the plan and activates a monitoring mechanism for evaluation, optimizes the plan based on the evaluation results to intelligently retain the topsoil, and achieves the technical effects of reducing soil erosion, improving soil fertility, and increasing crop yield and quality through full-process optimization of topsoil retention in brown soil farmland.

[0005] The present application provides a topsoil fixation method for brown soil farmland, comprising:

[0006] Based on the brown soil farmland area, multiple regional management data are retrieved, and multiple farmland data of the brown soil farmland area are collected according to the multiple regional management data; a soil erosion prediction model is constructed, and the multiple farmland data are synchronized to the soil erosion prediction model for simulation prediction, and the soil erosion simulation prediction result is output; according to the soil erosion simulation prediction result, the multiple regional management data are traversed for matching, and a topsoil retention plan is formulated; the topsoil retention plan is executed on the brown soil farmland area, and the soil erosion monitoring mechanism is activated to regularly evaluate the brown soil farmland area and generate a regional erosion assessment result; the topsoil retention plan is feedback-optimized according to the regional erosion assessment result, and a topsoil retention optimization plan is generated to intelligently retain the topsoil in the brown soil farmland area.

[0007] This application also provides a topsoil retention system for brown soil farmland, including:

[0008] A farmland data collection module, the farmland data collection module is used to retrieve multiple regional management data based on the brown soil farmland area, and collect multiple farmland data in the brown soil farmland area according to the multiple regional management data; a prediction result output module, the prediction result output module is used to construct a soil erosion prediction model, synchronize the multiple farmland data to the soil erosion prediction model for simulation prediction, and output the soil erosion simulation prediction result; a retention plan formulation module, the retention plan formulation module is used to traverse the multiple regional management data according to the soil erosion simulation prediction result for matching, and formulate a topsoil retention plan; an evaluation result generation module, the evaluation result generation module is used to execute the topsoil retention plan on the brown soil farmland area, activate the soil erosion monitoring mechanism to regularly evaluate the brown soil farmland area, and generate a regional erosion evaluation result; an intelligent retention module, the intelligent retention module is used to feedback optimize the topsoil retention plan according to the regional erosion evaluation result, and generate a topsoil retention optimization plan to intelligently retain the topsoil in the brown soil farmland area.

[0009] The topsoil retention method and system for brown soil farmland proposed in this application first retrieves the regional management data of brown soil farmland to collect farmland data, constructs a soil erosion prediction model and inputs the data to obtain the prediction results, formulates a topsoil retention plan based on the results and matches the regional management data, implements the plan and activates the monitoring mechanism for evaluation, optimizes the plan based on the evaluation results to intelligently retain the topsoil, and through the full-process optimization of topsoil retention in brown soil farmland, achieves the technical effects of reducing soil erosion, improving soil fertility, and increasing crop yield and quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0011] Figure 1 A schematic diagram of a process for the topsoil retention method for brown soil farmland provided in an embodiment of the present application;

[0012] Figure 2 A schematic structural diagram of a topsoil retention system for brown soil farmland provided in an embodiment of the present application.

[0013] Explanation of the accompanying symbols: farmland data collection module 10, prediction result output module 20, holding plan formulation module 30, evaluation result generation module 40, intelligent holding module 50. DETAILED DESCRIPTION

[0014] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0015] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0016] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0017] The present application provides a method for retaining topsoil in brown soil farmland, such as Figure 1 As shown, the method includes:

[0018] Step S100 retrieves multiple regional management data based on the brown soil farmland region and collects multiple farmland data for the brown soil farmland region based on the multiple regional management data. Specifically, the farmland data refers to geographic data, meteorological data, soil property data, vegetation cover data, and historical soil erosion data acquired during the monitoring and analysis of the brown soil farmland. The brown soil farmland region to be studied is selected, data acquisition equipment is prepared, and acquisition parameters such as sampling point distribution and monitoring frequency are set. Data acquisition is then performed to obtain geographic data records. Geographic data records represent information such as the farmland's geographic location, area, terrain slope, and aspect, and are characterized by reflecting the spatial distribution of the farmland. Data acquisition is continued to obtain meteorological data records. Meteorological data records represent information such as rainfall, temperature, wind speed, and sunshine duration in the region, and are characterized by reflecting the climatic conditions of the farmland. Next, data acquisition is performed to obtain soil property data records. Soil property data records represent soil texture, pH, organic matter content, and nutrient content such as nitrogen, phosphorus, and potassium, and are characterized by revealing the inherent properties of the soil. Next, data collection was performed to obtain vegetation cover data records. Vegetation cover data records indicate the type, density, growth status, and coverage of vegetation in the farmland, and their characteristic is to show the ecological status of the farmland. Finally, historical soil erosion data records were obtained by reviewing past monitoring records and research reports. Historical soil erosion data records indicate the type, degree, and frequency of soil erosion that has occurred in the area, and their characteristic is to show the soil erosion history of the farmland.

[0019] Step S200 constructs a soil erosion prediction model, synchronizes the multiple farmland data with the soil erosion prediction model for simulation prediction, and outputs soil erosion simulation prediction results. Specifically, the soil erosion simulation prediction results refer to relevant information derived from analyzing the multiple farmland data input by the constructed soil erosion prediction model. An appropriate model architecture is selected, the necessary technical tools are prepared, and model parameters, such as soil texture weight, rainfall influencing factor, and terrain slope coefficient, are set. The soil erosion prediction model is constructed and the collected multiple farmland data are synchronously input into the model to obtain initial simulation prediction data. Initial simulation prediction data represents a preliminary assessment of soil erosion severity at the beginning of the model run and is characterized by preliminary prediction trends. Model run operations continue to produce mid-term simulation prediction data. Mid-term simulation prediction data represents a further refinement of soil erosion type and extent during the intermediate stages of the model run and is characterized by refined prediction content. Finally, the model run is completed and the soil erosion simulation prediction results are output. This result represents a comprehensive assessment of soil erosion after a comprehensive analysis of various factors, including erosion severity, type, and potential risk areas. It is characterized by comprehensive and accurate predictions.

[0020] Step S300 involves traversing the multiple regional management data sets based on the soil erosion simulation prediction results and performing matching to formulate a topsoil retention plan. Specifically, the topsoil retention plan refers to a strategy developed based on a matching analysis of the soil erosion simulation prediction results and the multiple regional management data sets. A brown soil farmland area for which a plan is to be formulated is selected, relevant data processing tools are prepared, matching parameters are set, such as soil erosion threshold, tillage method impact weight, vegetation coverage index, etc., and data matching operations are performed to obtain preliminary matching result data. The preliminary matching result data represents the initial correlation analysis process between soil erosion and regional management data at the initial stage of matching, and is characterized by preliminary correlation analysis. Data matching is continued to obtain deep matching result data. The deep matching result data represents a more detailed and comprehensive comparison process of various data sets at the in-depth stage of matching, and is characterized by deep comparative analysis. Based on these matching results, a topsoil retention plan is formulated. This plan covers specific retention measures for different regions, including but not limited to changing tillage methods, optimizing vegetation planting, adjusting irrigation strategies, etc., and is characterized by being comprehensive and targeted.

[0021] Step S400 involves implementing the topsoil retention program on the brown soil farmland area, activating the soil erosion monitoring mechanism, and periodically assessing the brown soil farmland area to generate regional erosion assessment results. Specifically, the regional erosion assessment results refer to the analytical conclusions drawn after implementing the topsoil retention program and activating the soil erosion monitoring mechanism on the brown soil farmland area. The brown soil farmland area to be assessed is selected, the tools and equipment required for monitoring and assessment are prepared, and assessment parameters, such as soil erosion severity classification standards, monitoring cycle intervals, and assessment indicator weights, are set. The topsoil retention program is then implemented, and preliminary implementation effect data is obtained. This preliminary implementation effect data records the initial improvement in farmland soil conditions during the initial implementation of the program, and is characterized by initial improvement feedback. The topsoil retention program is then continued to be implemented, and the soil erosion monitoring mechanism is activated to obtain regular monitoring data. Regular monitoring data represents information obtained from monitoring the farmland according to a set period, and is characterized by periodic data collection. Based on this data and the implementation status, the brown soil farmland area is assessed, and a regional erosion assessment result is generated. This result includes a detailed description of the current status of farmland soil erosion, an evaluation of the program's effectiveness, and directions for future improvements.

[0022] In one possible implementation, the topsoil retention scheme is implemented in the brown soil farmland area, the soil erosion monitoring mechanism is activated to regularly evaluate the brown soil farmland area, and regional erosion assessment results are generated. Step S400 further includes step S410, which determines the monitoring target of the brown soil farmland area based on the topsoil retention scheme. Specifically, the topsoil retention scheme that has been formulated is analyzed, and the topsoil retention scheme includes various specific measures and expected effects, such as specific tillage method improvements, vegetation planting plans, etc. According to the content of the plan, the aspects that need to be focused on and monitored are clearly identified, such as certain areas prone to severe erosion, areas where new soil and water conservation measures are adopted, etc., so as to determine the monitoring targets of the brown soil farmland area.

[0023] Step S420: Defining a monitoring scope based on the monitoring target and establishing the soil erosion monitoring mechanism. Specifically, based on the determined monitoring target and taking into account the actual topography and soil distribution of the brown soil farmland, a specific monitoring scope is precisely defined. This could be a specific region, a section of farmland flowing through a river, or contiguous farmland with similar soil and topographic characteristics. Based on the characteristics of the monitoring scope and the requirements of the monitoring target, a comprehensive soil erosion monitoring mechanism is established, including selecting appropriate monitoring equipment and technology, determining the frequency and method of data collection, and establishing a data storage and analysis system.

[0024] Step S430: When the topsoil retention scheme is executed, a monitoring start instruction is triggered. Specifically, when the topsoil retention scheme is implemented in the brown soil farmland area, such as starting a new tillage operation or planting specific vegetation, the monitoring start instruction is automatically triggered, notifying the monitoring system to begin operation.

[0025] Step S440 activates the soil erosion monitoring mechanism in accordance with the monitoring initiation instruction, performs erosion monitoring on the brown soil farmland area according to a preset monitoring cycle, and obtains erosion data for multiple farmland areas. Specifically, upon receiving the monitoring initiation instruction, the soil erosion monitoring mechanism is activated and performs comprehensive and systematic erosion monitoring on the brown soil farmland area according to a preset monitoring cycle, such as once a month or once a quarter, using various monitoring equipment and technologies. Monitoring methods may include field sampling and analysis, remote sensing image monitoring, and real-time sensor data collection, thereby obtaining erosion data for multiple farmland areas, such as data on soil loss, changes in vegetation cover, and changes in terrain.

[0026] Step S450 calculates multiple erosion indices for the brown soil farmland region based on the erosion data for the multiple farmland regions. Specifically, the collected erosion data for the numerous farmland regions is analyzed and calculated, and multiple relevant factors are comprehensively analyzed to convert the raw data into multiple erosion indices that can more intuitively reflect the extent and trends of soil erosion. The indices include a soil erosion intensity index and a vegetation cover change index.

[0027] Step S460: Perform an erosion assessment based on the multiple erosion indices to generate the regional erosion assessment results. Specifically, based on the calculated multiple erosion indices, the soil erosion status of the brown soil farmland area is assessed. The numerical values ​​and changing trends of each indices are analyzed to determine whether soil erosion is worsening or being effectively controlled. The effectiveness of the topsoil retention program is evaluated, and detailed regional erosion assessment results are generated. The results are presented in the form of a report, including specific assessment conclusions, existing problems, and corresponding suggestions and improvement measures.

[0028] In one possible implementation, after performing an erosion assessment based on the multiple erosion indices to generate the regional erosion assessment result, step S460 further includes step S461 of retrieving historical monitoring data logs for the brown soil farmland region based on the soil erosion monitoring mechanism. Specifically, utilizing the database system and permissions provided by the established soil erosion monitoring mechanism, all historical monitoring data records for the brown soil farmland region are retrieved. The data logs contain detailed information for different time periods and monitoring points.

[0029] Step S462 extracts historical soil monitoring data, historical environmental monitoring data, and historical erosion monitoring data from the historical monitoring data logs. Specifically, the retrieved historical monitoring data logs are carefully screened and classified to accurately extract historical soil monitoring data, such as information on soil texture, fertility, and pH; historical environmental monitoring data, including rainfall, temperature, and wind speed; and historical erosion monitoring data, such as soil loss and eroded area.

[0030] Step S463: Regression analysis is performed based on the historical soil monitoring data, the historical environmental monitoring data, and the historical erosion monitoring data to determine a preset erosion threshold. Specifically, statistical regression analysis is performed using the extracted historical soil, environmental, and erosion monitoring data as input variables to identify the inherent relationships and patterns between the data, thereby determining a preset erosion threshold that can be used to determine whether the current soil erosion situation is severe.

[0031] Step S464 determines whether the multiple erosion indices are greater than or equal to the preset erosion threshold. Specifically, the newly acquired multiple erosion indices are compared with the previously determined preset erosion threshold. If the erosion index is greater than or equal to the preset threshold, it indicates that the area may have a relatively serious soil erosion problem; if it is less than the preset threshold, it may indicate that the current erosion situation is relatively mild.

[0032] Step S465: Extract erosion indices greater than or equal to the preset erosion threshold and traverse the brown soil farmland region to identify multiple farmland erosion areas. Specifically, for erosion indices greater than or equal to the preset erosion threshold, the brown soil farmland region is comprehensively traversed and located based on the corresponding monitoring point locations and ranges, to identify multiple farmland areas with severe erosion problems.

[0033] In step S466, an erosion label set is generated. The multiple farmland erosion areas are identified using the erosion label set to determine multiple erosion identification results. Specifically, a set of corresponding erosion labels is developed based on different degrees of erosion, such as mild erosion, moderate erosion, and severe erosion. The multiple identified farmland erosion areas are then combined with the generated erosion label set to clearly identify each area, resulting in multiple clear erosion identification results.

[0034] Step S467: Perform an erosion assessment based on the multiple erosion identification results to generate the regional erosion assessment results. Specifically, the multiple erosion identification results are comprehensively analyzed, including factors such as the scope, extent, and distribution of the eroded areas, to conduct a comprehensive and in-depth assessment of the soil erosion status of the entire brown soil farmland area. The assessment results are presented in the form of a detailed report, including a detailed description of the different erosion areas, an analysis of the causes of erosion, and corresponding treatment recommendations.

[0035] In one possible implementation, an erosion label set is generated, the multiple farmland erosion areas are identified in combination with the erosion label set, and multiple erosion identification results are determined. Step S466 further includes step S4661, performing weighted calculation based on the historical soil monitoring data, the historical environmental monitoring data, and the historical erosion monitoring data to generate an erosion classification standard. Specifically, the collected historical soil monitoring data, historical environmental monitoring data, and historical erosion monitoring data are analyzed. The data contains various key indicators and information related to soil erosion. Different weight values ​​are assigned to each data according to the importance of the data to the degree of soil erosion. For example, historical erosion monitoring data may be assigned a higher weight because it directly reflects the past erosion conditions. Using calculation methods such as weighted average, the data is comprehensively calculated and processed. Through weighted calculation, a series of numerical ranges that can represent different degrees of erosion are obtained, thereby generating a set of scientific and reasonable erosion classification standards.

[0036] Step S4662: Classify the erosion data of the multiple farmland areas according to the erosion classification standard to generate multiple erosion grades. Specifically, the newly acquired erosion data of the multiple farmland areas are compared and matched with the generated erosion classification standard. Based on the numerical range of the erosion data in the classification standard, these farmland areas are divided into corresponding grades one by one. For example, if the erosion data of a farmland area falls within the numerical range of mild erosion, it is classified as mild erosion. Through such comparison and classification, the erosion grade to which each farmland area belongs is determined, thereby generating multiple clear erosion grades.

[0037] Step S4663 determines the erosion label set based on the multiple erosion levels. Specifically, a specific erosion label is assigned to each of the multiple erosion levels. For example, a mild erosion level can be labeled "mild," a moderate erosion level "moderate," and a severe erosion level "severe." These labels form a complete erosion label set. This label set allows for clear and intuitive identification and differentiation of erosion levels across different farmland areas, facilitating subsequent assessment, management, and remediation efforts.

[0038] Step S500 is to perform feedback optimization on the topsoil retention scheme based on the regional erosion assessment results, generate a topsoil retention optimization scheme, and intelligently retain the topsoil in the brown soil farmland area. Specifically, the topsoil retention optimization scheme refers to a strategy formed by adjusting and improving the original topsoil retention scheme based on the regional erosion assessment results. The topsoil retention scheme to be optimized is selected, and data and tools for analysis are prepared. The regional erosion assessment results, such as the degree, type, and scope of erosion in the brown soil farmland area, are obtained. Optimization parameters, such as vegetation coverage targets, the extent of improvements to soil and water conservation projects, and the degree of adjustment to farming methods, are set. The original topsoil retention scheme is reviewed to obtain preliminary optimization idea data. The preliminary optimization idea data represents the preliminary analysis results of the original scheme's shortcomings based on the assessment results, and its characteristic is to identify the problem. The original scheme is further analyzed to obtain detailed optimization direction data. The detailed optimization direction data represents detailed improvement measures and goals proposed for specific problems, and its characteristic is to clearly define the direction of improvement. Based on these analyses and directions, an optimization plan for topsoil retention was generated. This plan included a comprehensive upgrade and adjustment of the original plan. The generated optimization plan was applied to intelligently retain the topsoil in the brown soil farmland area, and the key data and effects of the entire optimization and retention process were recorded.

[0039] In one possible implementation, feedback optimization is performed on the topsoil retention scheme based on the regional erosion assessment results to generate an optimized topsoil retention scheme for intelligently retaining topsoil in the brown soil farmland region. Step S500 further includes step S510, randomly selecting N farmland region erosion data based on the multiple farmland region erosion data to construct an initial optimization memory library. Specifically, N farmland region erosion data are randomly selected from the multiple farmland region erosion data using random sampling, and the N data are aggregated to form a preliminary data set. This initial optimization memory library is then constructed, and the memory library serves as a starting reference for subsequent evaluation and optimization.

[0040] Step S520 randomly selects the i-th farmland area erosion data based on the plurality of farmland area erosion data, and scores the data based on the regional erosion assessment result to obtain an i-th farmland area erosion score, wherein the i-th farmland area erosion data is different from the N farmland area erosion data. Specifically, the i-th data is randomly selected from the entire farmland area erosion data set, and the i-th data must not be one of the N data in the initial optimization memory bank. Based on the standards and indicators set by the regional erosion assessment result, a comprehensive assessment and quantitative scoring of the i-th farmland area erosion data is performed to obtain a specific score for the i-th farmland area erosion.

[0041] In step S530, when the i-th farmland area erosion score is greater than the minimum output value of the initial optimization memory library, the i-th farmland area erosion score replaces the farmland area erosion data with the minimum output value of the initial optimization memory library, thereby obtaining an updated optimization memory library. Specifically, when the i-th farmland area erosion score is greater than the minimum value among all the scores in the initial optimization memory library, the farmland area erosion data corresponding to the i-th score is used to replace the data with the minimum output value in the initial optimization memory library, thereby obtaining an updated optimization memory library.

[0042] In step S540, if the erosion score of the i-th farmland region is less than or equal to the minimum output value of the initial optimization memory library, the i-th farmland region erosion data is eliminated. Specifically, if the erosion score of the i-th farmland region is less than or equal to the minimum output value in the initial optimization memory library, the i-th data is considered to be of poor quality and is no longer included in the optimization memory library.

[0043] Step S550: After the plurality of farmland area erosion data are traversed, the farmland area erosion data with the maximum output value from the updated optimization memory is output. Specifically, the aforementioned random sampling, scoring, and comparison steps are repeated to traverse all farmland area erosion data. After all data are traversed, the farmland area erosion data with the maximum score is found in the updated optimization memory and output.

[0044] Step S560: Feedback optimization is performed on the topsoil retention scheme based on the maximum-scoring farmland erosion data to generate the optimized topsoil retention scheme. Specifically, based on the output farmland erosion data with the maximum score, the existing topsoil retention scheme is improved to identify any issues with the original scheme. The improved topsoil retention scheme is then refined to generate an optimized and effective topsoil retention scheme.

[0045] In one possible implementation, based on the multiple farmland area erosion data, the i-th farmland area erosion data is randomly screened, scored based on the regional erosion assessment result, and the i-th farmland area erosion score value is obtained, wherein the i-th farmland area erosion data is different from the N farmland area erosion data, step S520 further includes step S521, extracting the N farmland area erosion data based on the multiple farmland area erosion data, and performing regional identification on the remaining farmland area erosion data to generate a regional identification result. Specifically, among the numerous farmland area erosion data, a specific number of N farmland area erosion data are extracted according to preset extraction rules or specific algorithms. The extraction rules are based on the data collection time sequence, data integrity or other relevant screening conditions. After the extraction is completed, the remaining unextracted farmland area erosion data are divided into different areas according to their geographical location, soil type, topography and other factors, and each area is assigned a unique identification code or label. All remaining data are classified and marked according to the area to which they belong, thereby generating detailed and accurate regional identification results. The results provide a clear regional division basis for subsequent random screening, ensuring randomness while avoiding repeated processing of data in the same area.

[0046] In step S522, a random number generation algorithm is used to randomly screen the region identification results to determine the erosion data for the i-th farmland region. Specifically, the random number generation algorithm generates a series of random numbers, which are matched with different region identifications. During the matching process, the principle of selecting each region only once is strictly adhered to to ensure randomness and diversity in the selection. For example, the random number generated by the algorithm may correspond to the identification of a specific region. Then, a random number is randomly selected from the unprocessed data within that region as the erosion data for the i-th farmland region. This avoids repeated selection of data from the same region, ensures that the selected data fully represents the erosion conditions in different regions, and provides a broader and more comprehensive sample for subsequent analysis.

[0047] Step S523: Based on the regional erosion assessment results, a multidimensional analysis is performed on the erosion data of the i-th farmland region to generate the erosion intensity, erosion area, and erosion rate of the i-th farmland region. Specifically, based on the indicators and data included in the pre-established regional erosion assessment results, a multidimensional analysis is performed on the erosion data of the selected i-th farmland region. For example, the erosion intensity of the region is calculated through various means and data sources such as chemical analysis of soil samples, measurement of terrain slope, and monitoring of rainfall and water flow rate. The erosion intensity reflects the severity of soil particle removal and transportation per unit time and is usually measured by the amount of soil loss per unit area. Remote sensing images, field measurements, and other technical means are used to determine the erosion area, that is, to clarify the actual scope of land affected by erosion. The erosion rate, that is, the rate of soil loss per unit time, is calculated by combining time series data and changes in soil loss. The calculation and determination of these parameters provides a key quantitative basis for a comprehensive assessment of the erosion status of the region.

[0048] Step S524: Weights are assigned based on the erosion intensity, erosion area, and erosion rate of the i-th farmland area. The erosion data of the i-th farmland area is scored based on the weighted assignment results to generate an erosion score for the i-th farmland area. Specifically, the relative importance and influence of erosion intensity, erosion area, and erosion rate on soil erosion conditions are analyzed, and different weights are assigned to the three parameters. The weight assignment is based on expert experience, statistical analysis of historical data, or relevant research results. For example, if erosion intensity is considered to have the most significant impact on soil quality and ecosystems, it is assigned a higher weight, while erosion area and erosion rate are assigned relatively lower weights. After the weights are determined, the erosion intensity, erosion area, and erosion rate values ​​of the i-th farmland area are multiplied by their respective weights, and then summed. The calculated sum is the erosion score for the i-th farmland area. The score is presented in a specific numerical form and is defined as the i-th farmland area erosion score, which reflects the severity and condition of soil erosion in the area and provides an intuitive and powerful basis for subsequent decision-making and solution optimization.

[0049] In one possible implementation, the topsoil retention scheme is optimized based on the regional erosion assessment results, generating an optimized topsoil retention scheme for intelligently retaining the topsoil in the brown soil farmland area. Step S500 further includes step S570, where abnormal activation trigger statistics are collected for the soil erosion monitoring mechanism, generating abnormal activation trigger information, wherein the abnormal activation trigger information includes an abnormal trigger value. Specifically, the operation of the soil erosion monitoring mechanism is monitored and recorded, and any abnormal activation of the monitoring mechanism is recorded and counted in detail. Through continuous observation and recording, abnormal activation trigger information containing rich information is generated, and the abnormal trigger value in the information can quantitatively reflect the severity of the abnormal activation or specific abnormal characteristics.

[0050] Step S580 retrieves the trigger frequency based on the abnormal initiation trigger information, and constructs an abnormality file for the soil erosion monitoring mechanism based on the trigger frequency and the abnormal trigger value. Specifically, based on the generated abnormal initiation trigger information, the trigger frequency of the abnormal initiation is extracted. The trigger frequency represents the number of abnormal initiations that occurred within a certain time period. The trigger frequency is combined with the abnormal trigger value to create an abnormality file. The file systematically organizes and summarizes the abnormalities of the soil erosion monitoring mechanism, providing a clear reference for subsequent analysis and processing.

[0051] Step S590 involves backtracking the topsoil retention plan based on the anomaly profile to determine the source of the anomaly. Specifically, the constructed anomaly profile is used to backtrack and analyze the implementation of the topsoil retention plan. By carefully comparing the information in the anomaly profile with various aspects and relevant data of the topsoil retention plan, the source of the abnormal activation of the monitoring mechanism is identified. This source is then determined to be the source of the anomaly. This could be due to improper implementation of a specific measure in the topsoil retention plan, errors in data collection, or other related factors.

[0052] Step S5100 involves performing anomaly backtracking on the topsoil retention scheme based on the anomaly file to determine the source of the anomaly data. Specifically, based on the determined anomaly data source, targeted improvements and optimizations are made to the soil erosion monitoring mechanism, including adjusting monitoring equipment parameter settings, improving data collection and processing methods, refining the execution process of the topsoil retention scheme, or implementing other relevant management measures. This optimized management based on the anomaly data source aims to improve the accuracy and reliability of the soil erosion monitoring mechanism, thereby better supporting the implementation of topsoil retention work.

[0053] The embodiment of the present application uses the method of retrieving brown soil farmland regional management data to collect farmland data, constructing a soil erosion prediction model and inputting data to obtain prediction results, formulating a topsoil retention plan based on the results and matching regional management data, executing the plan and activating the monitoring mechanism for evaluation, and optimizing the plan based on the evaluation results to intelligently retain the topsoil, thereby achieving the technical effect of reducing soil erosion, improving soil fertility, and increasing crop yield and quality through the full-process optimization of topsoil retention in brown soil farmland.

[0054] In the above, refer to Figure 1 The topsoil holding method for brown soil farmland according to an embodiment of the present invention is described in detail. Figure 2 A topsoil retaining system for brown soil farmland according to an embodiment of the present invention is described.

[0055] The topsoil retention system for brown soil farmland, according to an embodiment of the present invention, addresses the technical challenges of existing topsoil retention technologies, including inaccurate soil erosion predictions, unscientific and targeted topsoil retention plans, and a lack of effective monitoring and feedback optimization mechanisms. By optimizing the entire topsoil retention process for brown soil farmland, the system achieves the technical benefits of reducing soil erosion, improving soil fertility, and increasing crop yield and quality. The topsoil retention system for brown soil farmland includes a farmland data acquisition module 10, a prediction result output module 20, a retention plan formulation module 30, an evaluation result generation module 40, and an intelligent retention module 50.

[0056] A farmland data collection module 10 is configured to retrieve a plurality of regional management data based on a brown soil farmland region, and collect a plurality of farmland data of the brown soil farmland region according to the plurality of regional management data;

[0057] A prediction result output module 20 is used to construct a soil erosion prediction model, synchronize the plurality of farmland data to the soil erosion prediction model for simulation prediction, and output a soil erosion simulation prediction result;

[0058] A retention plan formulation module 30 is configured to traverse the plurality of regional management data for matching based on the soil erosion simulation prediction results to formulate a topsoil retention plan;

[0059] An assessment result generating module 40 is configured to implement the topsoil retention scheme on the brown soil farmland area, activate a soil erosion monitoring mechanism to regularly assess the brown soil farmland area, and generate a regional erosion assessment result;

[0060] The intelligent retaining module 50 is used to perform feedback optimization on the topsoil retaining scheme according to the regional erosion assessment result, generate a topsoil retaining optimization scheme and perform intelligent retaining of the topsoil in the brown soil farmland area.

[0061] The specific configuration of the assessment result generation module 40 will be described in detail below. As described above, the topsoil retention scheme is implemented in the brown soil farmland area, and the soil erosion monitoring mechanism is activated to regularly evaluate the brown soil farmland area to generate a regional erosion assessment result. The assessment result generation module 40 further includes: a monitoring target determination unit, which is used to determine the monitoring target of the brown soil farmland area based on the topsoil retention scheme; a monitoring mechanism construction unit, which is used to define the monitoring range based on the monitoring target and construct the soil erosion monitoring mechanism; a start instruction triggering unit, which is used to trigger a monitoring start instruction when the topsoil retention scheme is implemented; an erosion data acquisition unit, which is used to activate the soil erosion monitoring mechanism according to the monitoring start instruction, perform erosion monitoring on the brown soil farmland area according to a preset monitoring period, and obtain erosion data for multiple farmland areas; an erosion index calculation unit, which is used to calculate multiple erosion indices for the brown soil farmland area based on the erosion data of the multiple farmland areas; and an erosion assessment result generation unit, which is used to perform erosion assessment based on the multiple erosion indices and generate the regional erosion assessment result.

[0062] Wherein, erosion assessment is performed according to the multiple erosion indices to generate the regional erosion assessment result, and the erosion assessment result generating unit further includes: a data log retrieval subunit, the data log retrieval subunit is used to retrieve the historical monitoring data log of the brown soil farmland area based on the soil erosion monitoring mechanism; a monitoring data extraction subunit, the monitoring data extraction subunit is used to extract historical soil monitoring data, historical environmental monitoring data, and historical erosion monitoring data according to the historical monitoring data log; an erosion threshold determination subunit, the erosion threshold determination subunit is used to perform regression analysis based on the historical soil monitoring data, the historical environmental monitoring data, and the historical erosion monitoring data to determine a preset erosion threshold; An index judgment subunit, the erosion index judgment subunit is used to judge whether the multiple erosion indices are greater than or equal to the preset erosion threshold; a farmland erosion area determination subunit, the farmland erosion area determination subunit is used to extract erosion indices greater than or equal to the preset erosion threshold, traverse the brown soil farmland area, and determine multiple farmland erosion areas; an erosion label set generation subunit, the erosion label set generation subunit is used to generate an erosion label set, identify the multiple farmland erosion areas in combination with the erosion label set, and determine multiple erosion identification results; an erosion assessment result generation subunit, the erosion assessment result generation subunit is used to perform erosion assessment based on the multiple erosion identification results, and generate the regional erosion assessment result.

[0063] Wherein, an erosion label set is generated, the multiple farmland erosion areas are identified in combination with the erosion label set, and multiple erosion identification results are determined. The erosion label set generation subunit further includes: an erosion classification standard generation microunit, the erosion classification standard generation microunit is used to perform weighted calculation based on the historical soil monitoring data, the historical environmental monitoring data, and the historical erosion monitoring data to generate an erosion classification standard; an erosion grade generation microunit, the erosion grade generation microunit is used to perform grade division according to the erosion classification standard in combination with the erosion data of the multiple farmland areas to generate multiple erosion grades; an erosion label set determination microunit, the erosion label set determination microunit is used to determine the erosion label set based on the multiple erosion grades;

[0064] The specific configuration of the intelligent holding module 50 will be described in detail below. As described above, the topsoil holding scheme is feedback optimized according to the regional erosion assessment result, and a topsoil holding optimization scheme is generated to intelligently hold the topsoil of the brown soil farmland area. The intelligent holding module 50 further includes: an optimization memory library construction unit, the optimization memory library construction unit is used to randomly screen N farmland area erosion data based on the multiple farmland area erosion data, and construct an initial optimization memory library; an erosion score value acquisition unit, the erosion score value acquisition unit is used to randomly screen the i-th farmland area erosion data based on the multiple farmland area erosion data, and score based on the regional erosion assessment result to obtain the i-th farmland area erosion score value, wherein the i-th farmland area erosion data is different from the N farmland area erosion data; an update optimization memory library acquisition unit, the update optimization memory library acquisition unit is used to update the optimization memory library when the i-th farmland area erosion data is different from the N farmland area erosion data; If the regional erosion score value is greater than the minimum output value of the initial optimization memory library, the i-th farmland regional erosion score value replaces the farmland regional erosion data of the minimum output value of the initial optimization memory library to obtain an updated optimization memory library; an erosion data elimination unit, the erosion data elimination unit is used to eliminate the i-th farmland regional erosion data when the i-th farmland regional erosion score value is less than or equal to the minimum output value of the initial optimization memory library; an erosion data output unit, the erosion data output unit is used to output the farmland regional erosion data with the maximum output value of the updated optimization memory library after traversing the multiple farmland regional erosion data; a topsoil retention optimization scheme generation unit, the topsoil retention optimization scheme generation unit is used to perform feedback optimization on the topsoil retention scheme based on the farmland regional erosion data with the maximum value to generate the topsoil retention optimization scheme.

[0065] Wherein, based on the multiple farmland area erosion data, the i-th farmland area erosion data is randomly screened, and a score is performed based on the regional erosion assessment result to obtain the i-th farmland area erosion score value, wherein the i-th farmland area erosion data is different from the N farmland area erosion data, and the erosion score value acquisition unit further includes: a regional identification result generation subunit, the regional identification result generation subunit is used to extract the N farmland area erosion data based on the multiple farmland area erosion data, and perform regional identification on the remaining farmland area erosion data to generate a regional identification result; a random screening subunit, the random screening subunit is used to use random A data generation algorithm is provided, which randomly screens the erosion data of the i-th farmland area according to the regional identification result to determine the erosion data of the i-th farmland area; a multidimensional analysis subunit is used to perform multidimensional analysis on the erosion data of the i-th farmland area based on the regional erosion assessment result to generate the erosion intensity, erosion area and erosion rate of the i-th farmland area; a scoring subunit of erosion data is used to perform weight allocation based on the erosion intensity, erosion area and erosion rate of the i-th farmland area, and score the erosion data of the i-th farmland area according to the weight allocation result to generate the erosion score value of the i-th farmland area.

[0066] Among them, the intelligent holding module 50 further includes: an abnormal start trigger information generation unit, the abnormal start trigger information generation unit is used to perform trigger statistics of abnormal start of the soil erosion monitoring mechanism, and generate abnormal start trigger information, wherein the abnormal start trigger information includes an abnormal trigger value; an abnormal file construction unit, the abnormal file construction unit is used to retrieve the trigger frequency based on the abnormal start trigger information, and construct an abnormal file of the soil erosion monitoring mechanism according to the trigger frequency and the abnormal trigger value; an abnormal data source determination unit, the abnormal data source determination unit is used to perform abnormal backtracking on the topsoil holding scheme based on the abnormal file and determine the abnormal data source; an optimization management unit, the optimization management unit is used to optimize and manage the soil erosion monitoring mechanism according to the abnormal data source.

[0067] The topsoil retaining system for brown soil farmland provided by the embodiment of the present invention can execute the topsoil retaining method for brown soil farmland provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0068] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0069] The above specific embodiments do not constitute a limitation to the scope of protection of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of this application should be included in the scope of protection of this application. In some cases, the actions or steps recorded in this application can be performed in an order different from that in the embodiments and can still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for retaining topsoil in brown soil farmland, characterized in that: The method comprises: Retrieving a plurality of regional management data based on the brown soil farmland region, and collecting a plurality of farmland data in the brown soil farmland region according to the plurality of regional management data, wherein the farmland data includes geographic data, meteorological data, soil property data, vegetation cover data, and historical soil erosion data; Constructing a soil erosion prediction model, synchronizing the plurality of farmland data to the soil erosion prediction model for simulation prediction, and outputting a soil erosion simulation prediction result; According to the soil erosion simulation prediction results, the plurality of regional management data are traversed and matched, and a topsoil retention plan is formulated; Implement the topsoil retention program for brown soil farmland areas, activate the soil erosion monitoring mechanism to regularly assess brown soil farmland areas, and generate regional erosion assessment results; Feedback optimization is performed on the topsoil retention scheme based on the regional erosion assessment results, generating a topsoil retention optimization scheme to intelligently retain the topsoil in the brown soil farmland area; Implement the topsoil retention program for the brown soil farmland area, activate the soil erosion monitoring mechanism to regularly assess the brown soil farmland area, and generate regional erosion assessment results, including the following methods: Determining monitoring targets for brown soil farmland areas based on the topsoil retention scheme; Delineating the monitoring scope based on the monitoring target and establishing the soil erosion monitoring mechanism; When the topsoil retention scheme is executed, a monitoring start instruction is triggered; activating the soil erosion monitoring mechanism according to the monitoring start instruction, performing erosion monitoring on the brown soil farmland area according to a preset monitoring period, and obtaining erosion data of multiple farmland areas; Calculating a plurality of erosion indices for the brown soil farmland region based on the plurality of farmland region erosion data; Performing erosion assessment based on the multiple erosion indices to generate the regional erosion assessment result; Performing erosion assessment based on the multiple erosion indices to generate the regional erosion assessment result, the method comprising: Retrieving historical monitoring data logs of brown soil farmland areas based on the soil erosion monitoring mechanism; Extracting historical soil monitoring data, historical environmental monitoring data, and historical erosion monitoring data according to the historical monitoring data log; Performing regression analysis based on the historical soil monitoring data, the historical environmental monitoring data, and the historical erosion monitoring data to determine a preset erosion threshold; Determining whether the plurality of erosion indices are greater than or equal to the preset erosion threshold; Extracting erosion indices greater than or equal to the preset erosion threshold value and traversing the brown soil farmland area to determine multiple farmland erosion areas; generating an erosion label set, identifying the plurality of farmland erosion areas in combination with the erosion label set, and determining a plurality of erosion identification results; Performing erosion assessment based on the multiple erosion identification results to generate the regional erosion assessment result; The erosion label set method comprises: Performing weighted calculation based on the historical soil monitoring data, the historical environmental monitoring data, and the historical erosion monitoring data to generate an erosion classification standard; Performing classification based on the erosion classification standard and the erosion data of the plurality of farmland areas to generate a plurality of erosion grades; determining the erosion label set based on the plurality of erosion levels; Methods include: Performing trigger statistics of abnormal startup of the soil erosion monitoring mechanism to generate abnormal startup trigger information, wherein the abnormal startup trigger information includes an abnormal trigger value; Retrieving a trigger frequency based on the abnormal start trigger information, and constructing an abnormality file of the soil erosion monitoring mechanism according to the trigger frequency and the abnormal trigger value; Perform anomaly backtracking on the topsoil retention scheme based on the anomaly file to determine the source of the anomaly data; The soil erosion monitoring mechanism is optimized and managed based on the abnormal data source.

2. The topsoil holding method for brown soil farmland according to claim 1, characterized in that: Feedback optimization of the topsoil retention scheme is performed based on the regional erosion assessment results, the method comprising: Based on the plurality of farmland area erosion data, randomly selecting N farmland area erosion data to construct an initial optimization memory library; Based on the plurality of farmland area erosion data, randomly selecting the i-th farmland area erosion data, scoring based on the regional erosion assessment result, and obtaining the i-th farmland area erosion score value, wherein the i-th farmland area erosion data is different from the N farmland area erosion data; When the i-th farmland area erosion score value is greater than the minimum output value of the initial optimization memory library, the i-th farmland area erosion score value replaces the farmland area erosion data of the minimum output value of the initial optimization memory library to obtain an updated optimization memory library; When the erosion score value of the i-th farmland area is less than or equal to the minimum output value of the initial optimization memory library, the erosion data of the i-th farmland area is eliminated; When the plurality of farmland area erosion data are traversed, the farmland area erosion data with the maximum output value of the updated optimization memory bank is output; The topsoil retention scheme is feedback-optimized based on the maximum farmland area erosion data to generate the topsoil retention optimization scheme.

3. The topsoil holding method for brown soil farmland according to claim 2, characterized in that: Based on the plurality of farmland area erosion data, randomly selecting the i-th farmland area erosion data, scoring the i-th farmland area erosion score based on the regional erosion assessment results, and obtaining the i-th farmland area erosion score value, the method comprising: Extracting the N farmland area erosion data based on the plurality of farmland area erosion data, and performing area identification on the remaining farmland area erosion data to generate an area identification result; Using a random number generation algorithm, random screening is performed according to the regional identification results to determine the erosion data of the i-th farmland area; Performing a multidimensional analysis on the erosion data of the i-th farmland region based on the regional erosion assessment results to generate the erosion intensity, erosion area, and erosion rate of the i-th farmland region; A weight distribution is performed based on the erosion intensity, the erosion area, and the erosion rate of the i-th farmland area, and the erosion data of the i-th farmland area is scored according to the weight distribution result to generate an erosion score value for the i-th farmland area.

4. A topsoil retention system for brown soil farmland, characterized in that: The system is used to implement the topsoil retention method for brown soil farmland according to any one of claims 1 to 3, and the system comprises: A farmland data collection module, the farmland data collection module is used to retrieve multiple regional management data based on the brown soil farmland area, and collect multiple farmland data in the brown soil farmland area based on the multiple regional management data, the farmland data including geographic data, meteorological data, soil property data, vegetation cover data and historical soil erosion data; A prediction result output module is used to build a soil erosion prediction model, synchronize the plurality of farmland data to the soil erosion prediction model for simulation prediction, and output a soil erosion simulation prediction result; A retention plan formulation module, configured to traverse the plurality of regional management data for matching according to the soil erosion simulation prediction results, and formulate a topsoil retention plan; An assessment result generation module, the assessment result generation module being configured to implement the topsoil retention scheme on the brown soil farmland area, activate a soil erosion monitoring mechanism to regularly assess the brown soil farmland area, and generate a regional erosion assessment result; An intelligent retention module is used to perform feedback optimization on the topsoil retention scheme according to the regional erosion assessment results, generate a topsoil retention optimization scheme, and perform intelligent retention of the topsoil in the brown soil farmland area.

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