Soil improvement method and system for improving re-greening efficiency of mountain reclamation land

Abstract

This invention belongs to the field of soil improvement technology. It discloses a soil improvement method and system for improving the efficiency of revegetation of reclaimed mountain land. The system includes: a soil improvement intelligent formula library management module, a precise improvement operation instruction generation module, a vegetation-soil evolution monitoring and evaluation module, a vegetation configuration and restoration strategy module, and a system adaptive control module. The system generates soil improvement formula recommendation reports, precise improvement operation instruction reports, and comprehensive improvement effect evaluation reports. Based on the three-dimensional soil obstacle diagnosis report and the comprehensive improvement effect evaluation report, it recommends and adjusts vegetation restoration plans, generating vegetation-related strategy recommendation reports. It also controls the startup, operation, and iterative optimization of the entire system. Overall, this invention has significant advantages such as high reliability of basic data, strong synergy of improvement and restoration measures, and good system adaptive management effect.

Description

Technical Field

[0001] This invention relates to the field of soil improvement technology, and more specifically, to a soil improvement method and system for improving the efficiency of revegetation of reclaimed mountain land. Background Technology

[0002] The mountain reclamation soil improvement system is a comprehensive technical system designed to rapidly reconstruct the function of damaged mountain soils and create the basic conditions for vegetation restoration through engineering and biological measures. Its core objective is to overcome the obstacles commonly found in reclaimed land, such as soil infertility, poor structure, and poor water and fertilizer retention capacity, thereby improving revegetation efficiency and ecological stability.

[0003] However, traditional soil improvement systems for mountain reclamation areas suffer from several shortcomings. First, these systems rely heavily on manual soil sampling and laboratory testing, leading to high costs for basic data collection. Furthermore, the basic data only reflects the surface soil condition of the sampled area, making it difficult for the system to identify the spatial distribution of obstacles at different soil depths, thus lacking reliable data support. Second, traditional systems typically apply improvement measures uniformly, making it difficult to customize improvements based on soil needs. Poor vegetation selection and soil condition compatibility also result in insufficient revegetation effects. Third, traditional systems terminate operation after executing a preset plan, making it difficult to obtain improvement results. This makes it difficult to identify the causes and adjust subsequent strategies when improvement is ineffective, limiting the stability and success rate of revegetation. Therefore, effectively addressing the problems of unreliable basic data, insufficient adaptability of improvement and restoration measures, and limited adaptive management capabilities in traditional systems has become a bottleneck issue that current soil improvement systems for mountain reclamation areas need to address.

[0004] In view of this, the present invention proposes a soil improvement method and system for improving the efficiency of revegetation of reclaimed mountain land in order to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution, including:

[0006] The multi-source data acquisition and fusion module is used to acquire raw data streams in real time based on sensor networks and perform preprocessing to obtain a multi-source spatiotemporal fusion dataset.

[0007] Furthermore, the steps of real-time acquisition and preprocessing of raw data streams based on sensor networks include:

[0008] S1.1: Collect raw data streams and UAV remote sensing image data based on wireless sensor networks and UAV platforms;

[0009] S1.2: Remove outliers from the original data stream and fill it with linear interpolation to obtain the original sensor dataset;

[0010] S1.3: Preprocess the UAV remote sensing image data to generate a surface reflectance image report;

[0011] S1.4: Define a two-dimensional grid and set the smallest management unit as the grid unit;

[0012] By using the GPS coordinates in the original sensor dataset, the original sensor dataset is associated and aggregated into the corresponding two-dimensional grid, and the surface reflectance image report is resampled into it to obtain a spatiotemporally aligned two-dimensional grid;

[0013] S1.5: For each spatiotemporally aligned 2D grid at time... Create a fusion record;

[0014] A multi-source spatiotemporal fusion dataset is generated based on the fusion records of all spatiotemporally aligned two-dimensional grids at all times.

[0015] S1.6: Store the multi-source spatiotemporal fusion dataset in the database;

[0016] The 3D soil health diagnosis module is used to quantitatively assess soil health based on multi-source spatiotemporal fusion datasets and diagnose soil obstacles, resulting in a 3D soil obstacle diagnosis report.

[0017] Furthermore, the steps for quantitatively assessing soil health and diagnosing soil obstacles based on multi-source spatiotemporal fusion datasets include:

[0018] S2.1: Based on the database, retrieve the multi-source spatiotemporal fusion dataset within the preset extraction period, and calculate the initial value of the barrier factor for each soil layer in each spatiotemporally aligned two-dimensional grid to obtain the barrier factor report;

[0019] S2.2: Input the obstacle factor report into the diagnostic model for calculation, and output the soil health index report. The specific formula for calculation is as follows:

[0020] ;

[0021] Obtain a spatiotemporally aligned 2D mesh In the soil layer The soil health index, among which, , , and As a weighting factor, Spatiotemporally aligned 2D grid In the soil layer Moisture threats, Spatiotemporally aligned 2D grid In the soil layer Salt threat factors, To align spacetime with a two-dimensional grid In the soil layer The compactness factor is mapped to a function in the interval [0,1]. To align spacetime with a two-dimensional grid In the soil layer The function that maps the effective content of soil nutrients to the interval [0,1] after comprehensive evaluation;

[0022] S2.3: Based on the soil health index report and compared with the obstacle threshold, when the soil health index is less than the obstacle threshold, it is determined that there is an obstacle in the soil layer of the spatiotemporally aligned two-dimensional grid, and an obstacle grid soil layer report is obtained.

[0023] S2.4: Based on the obstacle grid soil layer report, compare the scores of water threat factor, salinity threat factor, compaction factor and soil nutrient availability content, and determine the item with the lowest score as the main obstacle type of the soil layer in the spatiotemporally aligned two-dimensional grid, and obtain the grid soil main obstacle report;

[0024] S2.5: Based on the obstacle grid soil layer report and the grid soil main obstacle report, spatial cluster analysis is performed, and combined with the soil health index report, a three-dimensional soil obstacle diagnosis report is generated;

[0025] S2.6: Output the three-dimensional soil obstacle diagnosis report to the soil improvement intelligent formula library management module;

[0026] The intelligent soil amendment formula library management module is used to match and optimize based on the three-dimensional soil obstacle diagnosis report, generate targeted amendment material formula suggestions, and obtain a soil amendment formula suggestion report;

[0027] Furthermore, the steps for generating targeted improvement material formulation recommendations based on the three-dimensional soil obstacle diagnostic report through matching and optimization include:

[0028] S3.1: Read the three-dimensional soil obstacle diagnosis report and match it with the obstacle material rule table retrieved from the database to obtain an initial matching report;

[0029] S3.2: Based on the three-dimensional soil obstacle diagnosis report and initial matching report, and combined with the standard usage dosage of recommended materials, a theoretical material requirement report is obtained;

[0030] S3.3: Based on the three-dimensional soil obstacle diagnosis report, initial matching report and theoretical material requirement report, a soil improvement formula recommendation report is generated;

[0031] S3.4: Output the soil amendment formula recommendation report to the precision amendment operation instruction generation module;

[0032] The precision improvement operation instruction generation module is used to convert the three-dimensional soil obstacle diagnosis report and soil improvement formula recommendation report into digital operation instructions that can be executed by external intelligent equipment, and obtain a precision improvement operation instruction report.

[0033] Furthermore, the steps to transform the three-dimensional soil obstacle diagnostic report and soil amendment formulation recommendation report into digital operation instructions executable by external intelligent equipment include:

[0034] S4.1: The spatial clustering results of the obstacle area in the three-dimensional soil obstacle diagnosis report are used as the work unit, and the work mode report is obtained by mapping according to the obstacle type and soil depth of each work unit.

[0035] S4.2: Based on the work mode report, and according to the requirements, create one or more prescription diagrams aligned with the spatiotemporal two-dimensional grid for each work unit to obtain a material usage prescription diagram report;

[0036] S4.3: Use prescription diagram reports and work metadata reports for packaging materials to obtain precise improvement work instruction reports;

[0037] S4.4: Output the precision improvement operation instruction report to the vegetation and soil evolution monitoring and evaluation module;

[0038] The vegetation and soil evolution monitoring and evaluation module is used to monitor the execution effect of the precision improvement operation instruction report, and evaluate the actual effect of the improvement measures by comparing and analyzing the new round of monitoring data, and obtain a comprehensive evaluation report of the improvement effect.

[0039] Furthermore, the steps for monitoring the implementation effectiveness of precise improvement work instruction reports and evaluating the actual effectiveness of improvement measures by comparing and analyzing the new round of monitoring data include:

[0040] S5.1: Record the expected targets of all work units in the precision improvement work instruction report, and extract the data items from the multi-source spatiotemporal fusion dataset of the corresponding work unit before the work as the benchmark value to obtain the evaluation benchmark report;

[0041] S5.2: Extract the data items of the corresponding task unit from the latest multi-source spatiotemporal fusion dataset after the task is completed, calculate the performance index, and obtain the performance index report;

[0042] S5.3: Based on the performance indicator report, calculate the comprehensive index of improvement effect for each work unit to obtain the improvement effect report;

[0043] S5.4: Based on the performance indicator report and the improvement performance report, generate a comprehensive evaluation report on the improvement performance;

[0044] S5.5: Output the comprehensive evaluation report of the improvement effect to the vegetation configuration and restoration strategy module;

[0045] The vegetation configuration and restoration strategy module is used to recommend and adjust vegetation restoration plans based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effect, and to obtain a vegetation-related strategy suggestion report.

[0046] Furthermore, the steps for recommending and adjusting vegetation restoration plans based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effects include:

[0047] S6.1: Based on the soil health index and obstacle type of the region in the three-dimensional soil obstacle diagnosis report, and matched with the recommended plant configuration table, an initial configuration report is obtained;

[0048] S6.2: Analyze the areas with poor performance in the comprehensive evaluation report of improvement effects, and adjust the initial configuration report based on the analysis results to obtain the original configuration report;

[0049] S6.3: Generate a vegetation-related strategy recommendation report based on the original configuration report;

[0050] S6.4: Output the vegetation-related strategy recommendation report to the system's adaptive control module;

[0051] The system adaptive control module is used to control the startup, operation, and iterative optimization of the entire system.

[0052] Furthermore, the steps for controlling the startup, operation, and iterative optimization of the entire system include:

[0053] S7.1: Start the system workflow based on diagnostic trigger conditions and output the precise improvement operation instruction report to the external execution terminal;

[0054] S7.2: Start the evaluation optimization flow based on the preset evaluation cycle. The evaluation optimization flow includes calling the multi-source data acquisition and fusion module, the vegetation and soil evolution monitoring and evaluation module, and the vegetation configuration and restoration strategy module to run. It also analyzes the comprehensive improvement effect index in the comprehensive improvement effect evaluation report. When the comprehensive improvement effect index of all regions is greater than or equal to the success threshold, the system operation ends. When the comprehensive improvement effect index of all regions is less than the success threshold, proceed to step S7.3.

[0055] S7.3: Based on areas where the comprehensive index of improvement effect is less than the success threshold, combine the new multi-source spatiotemporal fusion dataset, comprehensive evaluation report of improvement effect, and vegetation-related strategy suggestion report generated in the evaluation optimization flow to generate a supplementary improvement operation instruction set and output it to the external execution terminal.

[0056] S7.4: Record the data from each cycle and store it in the database for use in the 3D soil health diagnosis module and the vegetation soil evolution monitoring and assessment module;

[0057] Furthermore, a soil improvement method to enhance the efficiency of revegetation on reclaimed mountain land includes:

[0058] S1: Real-time acquisition of raw data streams based on sensor networks, followed by preprocessing, to obtain a multi-source spatiotemporal fusion dataset;

[0059] S2: Based on a multi-source spatiotemporal fusion dataset, soil health is quantitatively assessed and soil obstacle diagnosis is performed to obtain a three-dimensional soil obstacle diagnosis report;

[0060] S3: Based on the three-dimensional soil obstacle diagnosis report, match and optimize to generate targeted improvement material formulation suggestions, and obtain a soil improvement formulation suggestion report;

[0061] S4: Transform the three-dimensional soil obstacle diagnosis report and soil improvement formula recommendation report into digital operation instructions that can be executed by external intelligent equipment, and obtain a precise improvement operation instruction report;

[0062] S5: Monitor the execution effect of the precision improvement operation instruction report, and evaluate the actual effect of the improvement measures by comparing and analyzing the new round of monitoring data to obtain a comprehensive evaluation report on the improvement effect;

[0063] S6: Based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effect, the vegetation restoration plan is recommended and adjusted to obtain a vegetation-related strategy suggestion report;

[0064] S7: Controls the startup, operation, and iterative optimization of the entire system.

[0065] This invention relates to a soil improvement method and system for improving the efficiency of revegetation of reclaimed mountain land, and its technical effects and advantages are as follows:

[0066] This invention acquires raw data streams in real time through a sensor network, preprocesses them to obtain a multi-source spatiotemporal fusion dataset, quantitatively assesses soil health based on the dataset, diagnoses soil obstacles, and generates a three-dimensional soil obstacle diagnosis report. Based on this report, matching and optimization are performed to generate targeted improvement material formulation recommendations, resulting in a soil improvement formulation recommendation report. The three-dimensional soil obstacle diagnosis report and the soil improvement formulation recommendation report are then converted into digital operation instructions executable by external intelligent equipment, resulting in a precise improvement operation instruction report. The execution effect of these instructions is monitored, and the actual effectiveness of the improvement measures is evaluated by comparing and analyzing the latest monitoring data, resulting in a comprehensive improvement effect evaluation report. Based on the three-dimensional soil obstacle diagnosis report and the comprehensive improvement effect evaluation report, vegetation restoration plans are recommended and adjusted, resulting in a vegetation-related strategy recommendation report. The system's startup, operation, and iterative optimization are controlled, enabling the system to leverage multi-source data acquisition and fusion modules and three-dimensional soil... The soil health diagnosis module collects basic data and performs in-depth analysis, providing a solid data foundation for subsequent system analysis. Furthermore, this invention utilizes a soil improvement intelligent formula library management module, a precise improvement operation instruction generation module, and a vegetation-soil evolution monitoring and evaluation module to provide precise and reliable countermeasures for different locations in different regions. These countermeasures are then transformed into operation prescription maps that can directly drive the operating equipment, ensuring that the vegetation planting plan matches the soil improvement plan. This maximizes the efficiency of revegetation and significantly improves improvement efficiency and resource utilization. Finally, through a vegetation configuration and restoration strategy module and a system adaptive control module, the system possesses the ability to learn and optimize. While addressing uncertainties in the revegetation process of reclaimed land, it maximizes the ecological restoration of the entire region and ensures long-term usability. Overall, this invention has significant advantages such as high reliability of basic data, strong synergy of improvement and restoration measures, and good system adaptive management. Attached Figure Description

[0067] Figure 1 This is a schematic diagram of a soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to the present invention;

[0068] Figure 2 This is a schematic diagram of a soil improvement method for improving the revegetation efficiency of reclaimed mountain land according to the present invention. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” used in the embodiments of this invention are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0071] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0072] Furthermore, the timing of the steps in the following method embodiments is merely an example and not a strict limitation.

[0073] In practice, the server-side equipment deployed in the soil improvement system for enhancing the revegetation efficiency of reclaimed mountain land may consist of one or more devices. This soil improvement system can be implemented as a business instance, a virtual machine, or hardware devices. For example, it can be implemented as a business instance deployed on one or more devices in a cloud node. Simply put, it can be understood as software deployed on a cloud node, providing the soil improvement system to various user terminals. Alternatively, it can be implemented as a virtual machine deployed on one or more devices in a cloud node, with application software installed to manage various user terminals. Or, it can also be implemented as a server composed of numerous identical or different types of hardware devices, with one or more hardware devices configured to provide the soil improvement system to various user terminals.

[0074] In terms of implementation, the soil improvement system for enhancing the revegetation efficiency of reclaimed mountain land and the user terminal are mutually compatible. That is, if the soil improvement system for enhancing the revegetation efficiency of reclaimed mountain land is an application installed on a cloud service platform, then the user terminal is a client that establishes a communication connection with the application; or if the soil improvement system for enhancing the revegetation efficiency of reclaimed mountain land is implemented as a website, then the user terminal is implemented as a webpage; or if the soil improvement system for enhancing the revegetation efficiency of reclaimed mountain land is implemented as a cloud service platform, then the user terminal is implemented as a mini-program in an instant messaging application.

[0075] like Figure 1 The figure shown is a system architecture diagram of a soil improvement system for improving the revegetation efficiency of reclaimed mountain land provided by an embodiment of the present invention.

[0076] The soil improvement system for enhancing the revegetation efficiency of reclaimed mountain land, as described in this invention, can be hosted on a cloud server. In terms of implementation, it can function as one or more service devices, or as an application installed in the cloud (e.g., a mobile service operator's server or server cluster), or it can be developed into a website. Depending on the functions implemented, the soil improvement system for enhancing the revegetation efficiency of reclaimed mountain land may include a multi-source data acquisition and fusion module, a three-dimensional soil health diagnosis module, a soil improvement intelligent formula library management module, a precision improvement operation instruction generation module, a vegetation and soil evolution monitoring and evaluation module, a vegetation configuration and restoration strategy module, and a system adaptive control module. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by an electronic device's processor and perform a fixed function, stored in the electronic device's memory.

[0077] In this embodiment of the invention, in the soil improvement system for improving the revegetation efficiency of reclaimed mountain land, each of the above-mentioned modules can be implemented independently and can call other modules. Here, "calling" can be understood as one module connecting to multiple modules of another type and providing corresponding services to those connected modules. For example, the system's adaptive control module can call the same information acquisition module to obtain information collected by that module. Based on the above characteristics, in the soil improvement system for improving the revegetation efficiency of reclaimed mountain land provided by this embodiment of the invention, without modifying the program code, the applicable scope of the soil improvement system architecture for improving the revegetation efficiency of reclaimed mountain land can be adjusted by adding modules and directly calling them, achieving cluster-based horizontal expansion to quickly and flexibly expand the soil improvement system for improving the revegetation efficiency of reclaimed mountain land. In practical applications, the above-mentioned modules can be set in the same device or different devices, or they can be set in virtual devices, such as service instances in a cloud server.

[0078] Example 1

[0079] Please see Figure 1As shown in this embodiment, a soil improvement system for improving the revegetation efficiency of reclaimed mountain land includes:

[0080] The multi-source data acquisition and fusion module is used to acquire raw data streams in real time based on sensor networks and perform preprocessing to obtain a multi-source spatiotemporal fusion dataset.

[0081] Furthermore, the steps of real-time acquisition and preprocessing of raw data streams based on sensor networks include:

[0082] S1.1: Collect raw data streams and UAV remote sensing image data based on wireless sensor networks and UAV platforms;

[0083] S1.2: Remove outliers from the original data stream and fill it with linear interpolation to obtain the original sensor dataset;

[0084] It should be explained that outliers in step S1.2 refer to data items that exceed the physical range, such as soil moisture exceeding 100%.

[0085] S1.3: Preprocess the UAV remote sensing image data to generate a surface reflectance image report;

[0086] It should be explained that the preprocessing in step S1.3 includes, but is not limited to, radiometric calibration, atmospheric correction, and geometric correction;

[0087] S1.4: Define a two-dimensional grid and set the smallest management unit as the grid unit;

[0088] It should be explained that the two-dimensional grid covers the entire mountain reclamation area and has a fixed geographic coordinate reference system; the size of the smallest management unit is manually set and entered into the system, for example, the smallest management unit is one meter by one meter;

[0089] By using the GPS coordinates in the original sensor dataset, the original sensor dataset is associated and aggregated into the corresponding two-dimensional grid, and the surface reflectance image report is resampled into it to obtain a spatiotemporally aligned two-dimensional grid;

[0090] S1.5: For each spatiotemporally aligned 2D grid at time... Create a fusion record;

[0091] It should be explained that the fusion record includes soil profile data, surface meteorological data, and vegetation spectral data. Taking soil profile data as an example, soil profile data includes, but is not limited to, data such as temperature, volumetric water content, and electrical conductivity of each soil layer.

[0092] A multi-source spatiotemporal fusion dataset is generated based on the fusion records of all spatiotemporally aligned two-dimensional grids at all times.

[0093] S1.6: Store the multi-source spatiotemporal fusion dataset in the database;

[0094] The three-dimensional soil health diagnosis module is used to quantitatively assess soil health based on a multi-source spatiotemporal fusion dataset, and to diagnose soil obstacles, thereby obtaining a three-dimensional soil obstacle diagnosis report.

[0095] Furthermore, the steps for quantitatively assessing soil health and diagnosing soil obstacles based on multi-source spatiotemporal fusion datasets include:

[0096] S2.1: Based on the database, retrieve the multi-source spatiotemporal fusion dataset within the preset extraction period, and calculate the initial value of the barrier factor for each soil layer in each spatiotemporally aligned two-dimensional grid to obtain the barrier factor report;

[0097] It should be explained that the obstacle factors include water threat factor, salinity threat factor and compaction factor. Taking water threat factor as an example, the water threat factor is obtained by calculating the difference between field water holding capacity and volumetric water content of a specified soil layer and dividing it by the difference between field water holding capacity and wilting coefficient. Field water holding capacity and wilting coefficient are known soil physical constants.

[0098] S2.2: Input the obstacle factor report into the diagnostic model for calculation, and output the soil health index report. The specific formula for calculation is as follows:

[0099] ;

[0100] Obtain a spatiotemporally aligned 2D mesh In the soil layer The soil health index, among which, , , and As a weighting factor, Spatiotemporally aligned 2D grid In the soil layer Moisture threats, Spatiotemporally aligned 2D grid In the soil layer Salt threat factors, To align spacetime with a two-dimensional grid In the soil layer The compactness factor is mapped to a function in the interval [0,1]. To align spacetime with a two-dimensional grid In the soil layer The function that maps the effective content of soil nutrients to the interval [0,1] after comprehensive evaluation;

[0101] It should be explained that soil nutrients refer to soil-related nutrients such as nitrogen, phosphorus, and potassium;

[0102] S2.3: Based on the soil health index report and compared with the obstacle threshold, when the soil health index is less than the obstacle threshold, it is determined that there is an obstacle in the soil layer of the spatiotemporally aligned two-dimensional grid, and an obstacle grid soil layer report is obtained.

[0103] It should be explained that the obstacle threshold is manually set and entered into the system; for example, the obstacle threshold is 0.6.

[0104] S2.4: Based on the obstacle grid soil layer report, compare the scores of water threat factor, salinity threat factor, compaction factor and soil nutrient availability content, and determine the item with the lowest score as the main obstacle type of the soil layer in the spatiotemporally aligned two-dimensional grid, and obtain the grid soil main obstacle report;

[0105] S2.5: Based on the obstacle grid soil layer report and the grid soil main obstacle report, spatial cluster analysis is performed, and combined with the soil health index report, a three-dimensional soil obstacle diagnosis report is generated;

[0106] It should be explained that cluster analysis refers to identifying contiguous obstacle areas, such as soil compaction areas and soil infertility areas; the three-dimensional soil obstacle diagnosis report includes, but is not limited to, a spatial distribution map of the soil health index of the entire region, obstacle type, severity, scores of the main obstacle type, and spatial clustering results of obstacle areas, wherein the severity is obtained based on the soil health index;

[0107] S2.6: Output the three-dimensional soil obstacle diagnosis report to the soil improvement intelligent formula library management module;

[0108] The intelligent soil amendment formula library management module is used to match and optimize based on the three-dimensional soil obstacle diagnosis report, generate targeted amendment material formula suggestions, and obtain a soil amendment formula suggestion report.

[0109] Furthermore, the steps for matching and optimizing based on the three-dimensional soil obstacle diagnostic report to generate targeted improvement material formulation recommendations include:

[0110] S3.1: Read the three-dimensional soil obstacle diagnosis report and match it with the obstacle material rule table retrieved from the database to obtain an initial matching report;

[0111] It needs to be explained that matching means, for example, if the three-dimensional soil obstacle diagnosis report shows that the main obstacle type is acid compaction and the soil layer is 0-20 cm, then the matching result is: {Recommended material group: organic fertilizer, lime, structural probability agent};

[0112] S3.2: Based on the three-dimensional soil obstacle diagnosis report and initial matching report, and combined with the standard usage dosage of recommended materials, a theoretical material requirement report is obtained;

[0113] It should be explained that, taking lime as the recommended material as an example, the required amount of lime material is obtained by calculating the product of the grid area, the depth of the soil layer to be improved, the soil bulk density, the difference between the target pH value and the current pH value, the soil cation exchange capacity, and the lime equivalent coefficient.

[0114] S3.3: Based on the three-dimensional soil obstacle diagnosis report, initial matching report and theoretical material requirement report, a soil improvement formula recommendation report is generated;

[0115] It should be explained that the soil amendment formulation recommendation report is based on a region and lists the region ID, main obstacle types, target soil layer, recommended material group and dosage of each recommended material;

[0116] S3.4: Output the soil amendment formula recommendation report to the precision amendment operation instruction generation module;

[0117] The precision improvement operation instruction generation module is used to convert the three-dimensional soil obstacle diagnosis report and soil improvement formula recommendation report into digital operation instructions that can be executed by external intelligent equipment, and obtain a precision improvement operation instruction report.

[0118] Furthermore, the steps to transform the 3D soil obstacle diagnostic report and soil amendment formulation recommendation report into digital operation instructions executable by external intelligent equipment include:

[0119] S4.1: The spatial clustering results of the obstacle area in the three-dimensional soil obstacle diagnosis report are used as the work unit, and the work mode report is obtained by mapping according to the obstacle type and soil depth of each work unit.

[0120] It should be explained that the mapping in step S4.1 means, for example, if the obstacle type of the work unit is soil compaction and the soil depth is 20-50 cm, then the work mode is deep loosening and grouting.

[0121] S4.2: Based on the work mode report, and according to the requirements, create one or more prescription diagrams aligned with the spatiotemporal two-dimensional grid for each work unit to obtain a material usage prescription diagram report;

[0122] It should be explained that, taking the deep tillage and grouting operation mode as an example, the material usage prescription report should include at least one deep tillage depth prescription and one grouting volume prescription. The deep tillage depth prescription is the depth of the bottom of the hardened layer that needs to be broken for each operation unit, and the grouting volume prescription is the volume of liquid modifier that needs to be injected for each operation unit.

[0123] S4.3: Use prescription diagram reports and work metadata reports for packaging materials to obtain precise improvement work instruction reports;

[0124] It should be explained that the job metadata report includes, but is not limited to, instruction ID, job unit, job mode, and recommended job equipment type;

[0125] S4.4: Output the precision improvement operation instruction report to the vegetation and soil evolution monitoring and evaluation module;

[0126] The vegetation and soil evolution monitoring and evaluation module is used to monitor the execution effect of the precision improvement operation instruction report, and to evaluate the actual effect of the improvement measures by comparing and analyzing the new round of monitoring data, so as to obtain a comprehensive evaluation report of the improvement effect.

[0127] Furthermore, the steps for monitoring the implementation effectiveness of precise improvement work instructions and reports, and evaluating the actual effectiveness of improvement measures through comparative analysis of the new round of monitoring data, include:

[0128] S5.1: Record the expected targets of all work units in the precision improvement work instruction report, and extract the data items from the multi-source spatiotemporal fusion dataset of the corresponding work unit before the work as the benchmark value to obtain the evaluation benchmark report;

[0129] It should be explained that the expected goal refers to, for example, improving the soil health index of a specified soil layer to a target value;

[0130] S5.2: Extract the data items of the corresponding task unit from the latest multi-source spatiotemporal fusion dataset after the task is completed, calculate the performance index, and obtain the performance index report;

[0131] It should be explained that the effectiveness indicators include, for example, the relative improvement in soil health and the vegetation response index;

[0132] S5.3: Based on the performance indicator report, calculate the comprehensive index of improvement effect for each work unit to obtain the improvement effect report;

[0133] It needs to be explained that this is achieved by substituting into the calculation formula: The comprehensive index of the improvement effect was obtained. ,in, These are the weighting coefficients. This represents the average relative improvement in soil health across all grids within the work unit. This is the average of the vegetation response indices of all grids within the work unit;

[0134] S5.4: Based on the performance indicator report and the improvement performance report, generate a comprehensive evaluation report on the improvement performance;

[0135] It should be explained that the comprehensive evaluation report on the improvement effect includes, but is not limited to, the comprehensive index of improvement effect for all work units, the ranking of the comprehensive index, the spatial distribution map of the relative improvement of soil health, the spatial distribution map of vegetation response, and areas with poor effect. Among them, areas with poor effect refer to areas where the comprehensive index of improvement effect is lower than the preset comprehensive index threshold.

[0136] S5.5: Output the comprehensive evaluation report of the improvement effect to the vegetation configuration and restoration strategy module;

[0137] The vegetation configuration and restoration strategy module is used to recommend and adjust vegetation restoration plans based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effect, and to obtain a vegetation-related strategy suggestion report.

[0138] Furthermore, the steps for recommending and adjusting vegetation restoration plans based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effects include:

[0139] S6.1: Based on the soil health index and obstacle type of the region in the three-dimensional soil obstacle diagnosis report, and matched with the recommended plant configuration table, an initial configuration report is obtained;

[0140] It should be explained that the matching in step S6.2 means, for example, if the soil health index is less than 0.4 and the obstacle type is soil infertility, then the matching result is: it is recommended to plant 60% of the soil infertility tolerant plants, 40% of the legume nitrogen-fixing shrubs and the planting density is D;

[0141] S6.2: Analyze the areas with poor performance in the comprehensive evaluation report of improvement effects, and adjust the initial configuration report based on the analysis results to obtain the original configuration report;

[0142] It should be explained that the analysis in step S6.2 refers to reasoning by combining the latest relative improvement of soil health and vegetation response index in areas with poor results. For example, when the value of relative improvement of soil health is high, but the value of vegetation response index is low, the reason may be that the plant type is inappropriate. In this case, the recommended plant type in the initial configuration report will be adjusted to the alternative plant type.

[0143] S6.3: Generate a vegetation-related strategy recommendation report based on the original configuration report;

[0144] It should be explained that the vegetation-related strategy recommendation report includes recommended plant types, planting ratios, planting quantities, and recommended planting times for areas where the effects are not good;

[0145] S6.4: Output the vegetation-related strategy recommendation report to the system's adaptive control module;

[0146] The system adaptive control module is used to control the startup, operation and iterative optimization of the entire system.

[0147] Furthermore, the steps for controlling the startup, operation, and iterative optimization of the entire system include:

[0148] S7.1: Start the system workflow based on diagnostic trigger conditions and output the precise improvement operation instruction report to the external execution terminal;

[0149] It should be explained that the diagnostic trigger conditions are manually set and input into the system. For example, the diagnostic trigger conditions are automatically executed on the first of each month or when data import from the reclaimed area is received. The system workflow refers to the operation of calling the multi-source data acquisition and fusion module, the three-dimensional soil health diagnosis module, the soil improvement intelligent formula library management module, and the precision improvement operation instruction generation module.

[0150] S7.2: Start the evaluation optimization flow based on the preset evaluation cycle. The evaluation optimization flow includes calling the multi-source data acquisition and fusion module, the vegetation and soil evolution monitoring and evaluation module, and the vegetation configuration and restoration strategy module to run. It also analyzes the comprehensive improvement effect index in the comprehensive improvement effect evaluation report. When the comprehensive improvement effect index of all regions is greater than or equal to the success threshold, the system operation ends. When the comprehensive improvement effect index of all regions is less than the success threshold, proceed to step S7.3.

[0151] It should be explained that the preset evaluation period is manually set and entered into the system, for example, the 60th day after step S7.1 is completed;

[0152] S7.3: Based on areas where the comprehensive index of improvement effect is less than the success threshold, combine the new multi-source spatiotemporal fusion dataset, comprehensive evaluation report of improvement effect, and vegetation-related strategy suggestion report generated in the evaluation optimization flow to generate a supplementary improvement operation instruction set and output it to the external execution terminal.

[0153] S7.4: Record the data from each cycle and store it in the database for use in the 3D soil health diagnosis module and the vegetation soil evolution monitoring and assessment module;

[0154] It should be explained that the use of step S7.4 refers to optimizing the weight factor of step S2.2 and the weight coefficient of step S5.3;

[0155] The beneficial effects of this embodiment are as follows: Raw data streams are collected in real time through a sensor network and preprocessed to obtain a multi-source spatiotemporal fusion dataset. Soil health is quantitatively assessed based on this dataset, and soil obstacle diagnosis is performed to obtain a three-dimensional soil obstacle diagnosis report. Based on this report, matching and optimization are performed to generate targeted improvement material formulation suggestions, resulting in a soil improvement formulation suggestion report. The three-dimensional soil obstacle diagnosis report and the soil improvement formulation suggestion report are converted into digital operation instructions executable by external intelligent equipment, resulting in a precise improvement operation instruction report. The execution effect of the precise improvement operation instruction report is monitored, and the actual effect of the improvement measures is evaluated by comparing and analyzing the new round of monitoring data, resulting in a comprehensive improvement effect evaluation report. Based on the three-dimensional soil obstacle diagnosis report and the comprehensive improvement effect evaluation report, vegetation restoration plans are recommended and adjusted, resulting in a vegetation-related strategy suggestion report. The system's startup, operation, and iterative optimization are controlled, enabling the system to achieve multi-source data acquisition and fusion. The three-dimensional soil health diagnosis module collects basic data and performs in-depth analysis, providing a solid data foundation for subsequent system analysis. Furthermore, this embodiment utilizes a soil improvement intelligent formula library management module, a precise improvement operation instruction generation module, and a vegetation-soil evolution monitoring and evaluation module to provide precise and reliable countermeasures for different locations in different regions. These countermeasures are then transformed into operation prescription maps that can directly drive the operating equipment, ensuring that the vegetation planting plan matches the soil improvement plan. This maximizes the efficiency of revegetation and significantly improves improvement efficiency and resource utilization. Finally, through the vegetation configuration and restoration strategy module and the system adaptive control module, the system possesses the ability to learn and optimize. While addressing uncertainties in the revegetation process of reclaimed land, it maximizes the ecological restoration of the entire region and ensures the system's long-term usability. Overall, this embodiment has significant advantages such as high reliability of basic data, strong synergy of improvement and restoration measures, and good adaptive management effect.

[0156] Example 2

[0157] Please see Figure 2 As shown, the parts not described in detail in this embodiment are described in Embodiment 1. A soil improvement method for improving the revegetation efficiency of reclaimed mountain land is provided. The method includes: S1: Real-time acquisition of raw data streams based on sensor networks and preprocessing to obtain multi-source spatiotemporal fusion datasets;

[0158] S2: Based on a multi-source spatiotemporal fusion dataset, soil health is quantitatively assessed and soil obstacle diagnosis is performed to obtain a three-dimensional soil obstacle diagnosis report;

[0159] S3: Based on the three-dimensional soil obstacle diagnosis report, match and optimize to generate targeted improvement material formulation suggestions, and obtain a soil improvement formulation suggestion report;

[0160] S4: Transform the three-dimensional soil obstacle diagnosis report and soil improvement formula recommendation report into digital operation instructions that can be executed by external intelligent equipment, and obtain a precise improvement operation instruction report;

[0161] S5: Monitor the execution effect of the precision improvement operation instruction report, and evaluate the actual effect of the improvement measures by comparing and analyzing the new round of monitoring data to obtain a comprehensive evaluation report on the improvement effect;

[0162] S6: Based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effect, the vegetation restoration plan is recommended and adjusted to obtain a vegetation-related strategy suggestion report;

[0163] S7: Controls the startup, operation, and iterative optimization of the entire system.

[0164] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the present invention.

Claims

1. A soil improvement system for enhancing the efficiency of revegetation on reclaimed mountain land, characterized in that, The system includes: a soil improvement intelligent formula library management module, a precision improvement operation instruction generation module, a vegetation and soil evolution monitoring and evaluation module, a vegetation configuration and restoration strategy module, and a system adaptive control module, wherein: The intelligent soil amendment formula library management module is used to match and optimize based on the three-dimensional soil obstacle diagnosis report, generate targeted amendment material formula suggestions, and obtain a soil amendment formula suggestion report. The precision improvement operation instruction generation module is used to convert the three-dimensional soil obstacle diagnosis report and soil improvement formula recommendation report into digital operation instructions that can be executed by external intelligent equipment, and obtain a precision improvement operation instruction report. The vegetation and soil evolution monitoring and evaluation module is used to monitor the execution effect of the precision improvement operation instruction report, and to evaluate the actual effect of the improvement measures by comparing and analyzing the new round of monitoring data, so as to obtain a comprehensive evaluation report of the improvement effect. The vegetation configuration and restoration strategy module is used to recommend and adjust vegetation restoration plans based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effect, and to obtain a vegetation-related strategy suggestion report. The system adaptive control module is used to control the startup, operation, and iterative optimization of the entire system.

2. The soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 1, characterized in that, The system also includes: a multi-source data acquisition and fusion module and a three-dimensional soil health diagnosis module, wherein: The multi-source data acquisition and fusion module is used to acquire raw data streams in real time based on sensor networks and perform preprocessing to obtain a multi-source spatiotemporal fusion dataset. The three-dimensional soil health diagnosis module is used to quantitatively assess soil health based on a multi-source spatiotemporal fusion dataset and to diagnose soil obstacles, thereby obtaining a three-dimensional soil obstacle diagnosis report.

3. The soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 2, characterized in that, The steps for real-time acquisition and preprocessing of raw data streams based on sensor networks include: S1.1: Collect raw data streams and UAV remote sensing image data based on wireless sensor networks and UAV platforms; S1.2: Remove outliers from the original data stream and fill it with linear interpolation to obtain the original sensor dataset; S1.3: Preprocess the UAV remote sensing image data to generate a surface reflectance image report; S1.4: Define a two-dimensional grid and set the smallest management unit as the grid unit; By using the GPS coordinates in the original sensor dataset, the original sensor dataset is associated and aggregated into the corresponding two-dimensional grid, and the surface reflectance image report is resampled into it to obtain a spatiotemporally aligned two-dimensional grid; S1.5: For each spatiotemporally aligned 2D grid at time... Create a fusion record; A multi-source spatiotemporal fusion dataset is generated based on the fusion records of all spatiotemporally aligned two-dimensional grids at all times. S1.6: Store the multi-source spatiotemporal fusion dataset in the database.

4. A soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 3, characterized in that, The steps for quantitatively assessing soil health and diagnosing soil obstacles based on multi-source spatiotemporal fusion datasets include: S2.1: Based on the database, retrieve the multi-source spatiotemporal fusion dataset within the preset extraction period, and calculate the initial value of the barrier factor for each soil layer in each spatiotemporally aligned two-dimensional grid to obtain the barrier factor report; S2.2: Input the obstacle factor report into the diagnostic model for calculation, and output the soil health index report; S2.3: Based on the soil health index report and compared with the obstacle threshold, when the soil health index is less than the obstacle threshold, it is determined that there is an obstacle in the soil layer of the spatiotemporally aligned two-dimensional grid, and an obstacle grid soil layer report is obtained. S2.4: Based on the obstacle grid soil layer report, compare the scores of water threat factor, salinity threat factor, compaction factor and soil nutrient availability content, and determine the item with the lowest score as the main obstacle type of the soil layer in the spatiotemporally aligned two-dimensional grid, and obtain the grid soil main obstacle report; S2.5: Based on the obstacle grid soil layer report and the grid soil main obstacle report, spatial cluster analysis is performed, and combined with the soil health index report, a three-dimensional soil obstacle diagnosis report is generated; S2.6: Output the three-dimensional soil obstacle diagnosis report to the soil improvement intelligent formula library management module.

5. A soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 4, characterized in that, The steps for generating targeted improvement material formulation recommendations based on matching and optimization of three-dimensional soil obstacle diagnostic reports include: S3.1: Read the three-dimensional soil obstacle diagnosis report and match it with the obstacle material rule table retrieved from the database to obtain an initial matching report; S3.2: Based on the three-dimensional soil obstacle diagnosis report and initial matching report, and combined with the standard usage dosage of recommended materials, a theoretical material requirement report is obtained; S3.3: Based on the three-dimensional soil obstacle diagnosis report, initial matching report and theoretical material requirement report, a soil improvement formula recommendation report is generated; S3.4: Output the soil amendment formula recommendation report to the precision amendment operation instruction generation module.

6. A soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 4, characterized in that, The steps to transform 3D soil obstacle diagnostic reports and soil amendment formulation recommendation reports into digital operation instructions executable by external intelligent equipment include: S4.1: The spatial clustering results of the obstacle area in the three-dimensional soil obstacle diagnosis report are used as the work unit, and the work mode report is obtained by mapping according to the obstacle type and soil depth of each work unit. S4.2: Based on the work mode report, and according to the requirements, create one or more prescription diagrams aligned with the spatiotemporal two-dimensional grid for each work unit to obtain a material usage prescription diagram report; S4.3: Use prescription diagram reports and work metadata reports for packaging materials to obtain precise improvement work instruction reports; S4.4: Output the precision improvement operation instruction report to the vegetation and soil evolution monitoring and evaluation module.

7. A soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 6, characterized in that, The steps for monitoring the implementation effectiveness of precise improvement work instructions and reports, and evaluating the actual effectiveness of improvement measures by comparing and analyzing the new round of monitoring data, include: S5.1: Record the expected targets of all work units in the precision improvement work instruction report, and extract the data items from the multi-source spatiotemporal fusion dataset of the corresponding work unit before the work as the benchmark value to obtain the evaluation benchmark report; S5.2: Extract the data items of the corresponding task unit from the latest multi-source spatiotemporal fusion dataset after the task is completed, calculate the performance index, and obtain the performance index report; S5.3: Based on the performance indicator report, calculate the comprehensive index of improvement effect for each work unit to obtain the improvement effect report; S5.4: Based on the performance indicator report and the improvement performance report, generate a comprehensive evaluation report on the improvement performance; S5.5: Output the comprehensive evaluation report of the improvement effect to the vegetation configuration and restoration strategy module.

8. A soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 4, characterized in that, The steps for recommending and adjusting vegetation restoration plans based on three-dimensional soil obstacle diagnosis reports and comprehensive evaluation reports of improvement effects include: S6.1: Based on the soil health index and obstacle type of the region in the three-dimensional soil obstacle diagnosis report, and matched with the recommended plant configuration table, an initial configuration report is obtained; S6.2: Analyze the areas with poor performance in the comprehensive evaluation report of improvement effects, and adjust the initial configuration report based on the analysis results to obtain the original configuration report; S6.3: Generate a vegetation-related strategy recommendation report based on the original configuration report; S6.4: Output vegetation-related strategy recommendation reports to the system's adaptive control module.

9. A soil improvement system for improving the revegetation efficiency of reclaimed mountain land according to claim 1, characterized in that, The steps for controlling the startup, operation, and iterative optimization of the entire system include: S7.1: Start the system workflow based on diagnostic trigger conditions and output the precise improvement operation instruction report to the external execution terminal; S7.2: Start the evaluation optimization flow based on the preset evaluation cycle. The evaluation optimization flow includes calling the multi-source data acquisition and fusion module, the vegetation and soil evolution monitoring and evaluation module, and the vegetation configuration and restoration strategy module to run. It also analyzes the comprehensive improvement effect index in the comprehensive improvement effect evaluation report. When the comprehensive improvement effect index of all regions is greater than or equal to the success threshold, the system operation ends. When the comprehensive improvement effect index of all regions is less than the success threshold, proceed to step S7.

3. S7.3: Based on areas where the comprehensive index of improvement effect is less than the success threshold, combine the new multi-source spatiotemporal fusion dataset, comprehensive evaluation report of improvement effect, and vegetation-related strategy suggestion report generated in the evaluation optimization flow to generate a supplementary improvement operation instruction set and output it to the external execution terminal. S7.4: Record the data from each cycle and store it in the database for use in the 3D soil health diagnosis module and the vegetation soil evolution monitoring and assessment module.

10. A soil improvement method for enhancing the revegetation efficiency of reclaimed mountain land, implemented according to any one of claims 1-9, characterized in that, The work includes the following steps: S1: Real-time acquisition of raw data streams based on sensor networks, followed by preprocessing, to obtain a multi-source spatiotemporal fusion dataset; S2: Based on a multi-source spatiotemporal fusion dataset, soil health is quantitatively assessed and soil obstacle diagnosis is performed to obtain a three-dimensional soil obstacle diagnosis report; S3: Based on the three-dimensional soil obstacle diagnosis report, match and optimize to generate targeted improvement material formulation suggestions, and obtain a soil improvement formulation suggestion report; S4: Transform the three-dimensional soil obstacle diagnosis report and soil improvement formula recommendation report into digital operation instructions that can be executed by external intelligent equipment, and obtain a precise improvement operation instruction report; S5: Monitor the execution effect of the precision improvement operation instruction report, and evaluate the actual effect of the improvement measures by comparing and analyzing the new round of monitoring data to obtain a comprehensive evaluation report on the improvement effect; S6: Based on the three-dimensional soil obstacle diagnosis report and the comprehensive evaluation report of improvement effect, the vegetation restoration plan is recommended and adjusted to obtain a vegetation-related strategy suggestion report; S7: Controls the startup, operation, and iterative optimization of the entire system.

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