Ecological restoration monitoring method for soil environment

Abstract

The invention discloses an ecological restoration monitoring method for a soil environment, and relates to the technical field of ecological restoration monitoring, and the method comprises the steps: collecting the growth state data of a target plant in an ecological restoration region, constructing a growth value, carrying out the soil data collection in the ecological restoration region if the growth value is lower than a growth threshold value, and carrying out the feature extraction, a corresponding fertility optimization and adjustment scheme is given in the ecological restoration area, and a targeted pest control scheme is adopted when a target plant has pest damage; and collecting ecological restoration parameters and vegetation coverage rate data in an ecological restoration period, screening out key factors from the ecological restoration parameters through correlation analysis, and adjusting the key factors by using an optimization algorithm to obtain an optimized ecological environment monitoring strategy. The influence of insect pests on ecological restoration is reduced, the growth state of target plants is improved, and the vegetation coverage rate and the species diversity are rapidly increased.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological restoration monitoring, and in particular to an ecological restoration monitoring method for a soil environment. Background Art

[0002] Ecological restoration refers to the process of using nature's self-repairing ability, supplemented by appropriate artificial measures, to restore the original ecological functions of the ecosystem, such as maintaining water and soil, regulating microclimate, maintaining biodiversity, and economic functions such as development and utilization. It is not simply restoring the ecosystem to its original state, but through restoration, the functions of the ecosystem are continuously restored and improved, thereby promoting the overall quality improvement of the ecosystem and ensuring national ecological security.

[0003] In the Chinese invention patent with application publication number CN118465234A, a soil environment ecological restoration monitoring method is disclosed, which includes the following steps: step S1, establishing monitoring points; step S2, equipment installation; step S3, data transmission; step S4, data processing and analysis; step S5, scheme adjustment. The soil environment ecological restoration monitoring method of the present invention can obtain various parameters of the soil environment to be restored in real time by setting monitoring devices at monitoring points; in the process of installing the monitoring sensor, the drill tube rotates and moves downward, and the limiting mechanism is driven by the driving mechanism to limit the monitoring sensor from moving, and the drill tube protects the monitoring sensor; when the drill tube moves down to the target depth, the limiting mechanism no longer limits the monitoring sensor, and the monitoring sensor extends from the lower end of the drill tube and is inserted into the soil.

[0004] Combined with the above application and the contents of the prior art:

[0005] After soil remediation in a polluted area, in order to verify the soil remediation effect and quickly restore the vegetation and species diversity in the polluted area, the ecological environment in the polluted area is usually further repaired and monitored.

[0006] In the existing ecological environment monitoring and restoration methods, real-time data is usually collected and monitored in the ecological restoration area. If there are abnormalities in the acquired monitoring data, emergency measures are taken to ensure the normal ecological restoration process. However, when the environmental conditions in the ecological environment area still have a certain degree of abnormality, which is not conducive to vegetation growth, when emergency measures are needed, managers may find it difficult to quickly obtain corresponding response plans, resulting in poor targeted emergency measures, which in turn affects the effect of ecological restoration.

[0007] To this end, the present invention provides an ecological restoration monitoring method for a soil environment. Summary of the invention

[0008] 1. Technical issues to be resolved

[0009] In view of the deficiencies of the prior art, the present invention provides an ecological restoration monitoring method for the soil environment. The growth value is constructed by collecting the growth status data of the target plants in the ecological restoration area. If the growth value is lower than the growth threshold, soil data is collected in the ecological restoration area, and after feature extraction, a corresponding fertility optimization adjustment plan is given for the ecological restoration area. When the target plants are pest-prone, a targeted pest control plan is adopted. The ecological restoration parameters and vegetation coverage rate data within the ecological restoration cycle are collected, and the key factors are screened out from the ecological restoration parameters through correlation analysis. The key factors are adjusted using an optimization algorithm to obtain an optimized ecological environment monitoring strategy. The growth status of the target plants is improved, and the vegetation coverage rate and species diversity are rapidly increased; thereby solving the technical problems raised in the background technology.

[0010] (II) Technical solution

[0011] To achieve the above objectives, the present invention is implemented through the following technical solutions: a soil environment ecological restoration monitoring method, comprising: generating a restoration condition value after collecting restoration environment data in an ecological restoration area; if the restoration condition value is lower than expected, screening out abnormal factors in the restoration environment data, and processing the restoration environment according to the abnormal factors;

[0012] After collecting the growth status data of the target plants in the ecological restoration area, the growth value is constructed; if the growth value is lower than the growth threshold, soil data is collected in the ecological restoration area;

[0013] After feature extraction, a fertility optimization adjustment plan is given for the ecological restoration area; when there are pests on the target plants, a targeted pest control plan is adopted;

[0014] Collect ecological restoration parameters and vegetation coverage data during the ecological restoration cycle, screen out key factors from several ecological restoration parameters, use optimization algorithms to adjust the key factors, and obtain optimized ecological environment monitoring strategies.

[0015] Furthermore, when conducting ecological monitoring and restoration in the ecological restoration area, a number of evenly distributed monitoring points are set up in the ecological restoration area, and environmental data such as soil moisture, air humidity, groundwater level, etc. in the ecological restoration area are monitored in real time at each monitoring point, and the restoration environment data set is summarized and generated.

[0016] Furthermore, a repair condition value is constructed from the repair environment data, and if the repair condition value is lower than a condition threshold, an adjustment instruction is issued to the outside;

[0017] After receiving the adjustment instruction, the environmental parameters of several time nodes are continuously obtained to construct the abnormality of each environmental parameter. If the abnormality exceeds expectations, the corresponding environmental parameter is determined as an abnormal factor.

[0018] Furthermore, several target plants are selected in the vicinity of each monitoring point, and growth data of the target plants are collected and recorded to construct a growth status data set. Conventional growth parameters of the target plants are obtained and used as qualified reference values, and growth values ​​are constructed from the growth status data set.

[0019] Furthermore, after receiving the alarm instruction, several collection points are selected in the ecological restoration area, soil is collected at each collection point, and corresponding soil monitoring data is obtained after the soil is tested and analyzed, and several fertility optimization features are obtained after feature extraction of the soil monitoring data;

[0020] Taking fertility optimization and adjustment as the target word, a fertility optimization and adjustment knowledge graph is pre-constructed. According to the correspondence between fertility optimization characteristics and fertility optimization and adjustment plans, the fertility optimization and adjustment knowledge graph provides corresponding fertility optimization and adjustment plans for the ecological restoration area.

[0021] Furthermore, after completing the fertility optimization in the ecological restoration area, image data of the target plants are collected in each sub-period and then image recognition is performed to identify whether the target plants have pests. If there are pests and the pest area exceeds the expected proportion, pest control instructions are issued to the outside.

[0022] Furthermore, after receiving the pest control instruction, the pest type and pest infection status are obtained through image recognition, and the corresponding pest features are obtained after feature extraction;

[0023] According to the correspondence between pest characteristics and pest control plans, the pre-built pest control plan library matches the corresponding pest control plan for the ecological restoration area.

[0024] Furthermore, after the target plant is finished, the vegetation coverage rate of each stage of ecological environment monitoring is obtained, and the coverage of the ecological environment monitoring stage is constructed. If the coverage is lower than the coverage threshold, an analysis instruction is issued to the outside;

[0025] Collect and summarize environmental data, plant growth data and fertility optimization data during the ecological environment restoration cycle, and summarize and construct an ecological environment monitoring data set.

[0026] Furthermore, a correlation analysis was conducted between the various ecological restoration parameters in the ecological environment monitoring set and the vegetation coverage rate to obtain the corresponding correlation coefficients; multiple linear regression analysis was performed with the ecological restoration parameters as independent variables and the vegetation coverage rate as the dependent variable, and the corresponding linear regression equations were obtained, and the regression coefficients corresponding to each ecological restoration parameter were obtained from the linear regression equations.

[0027] Furthermore, after obtaining each correlation coefficient, the closeness centrality of each ecological restoration parameter is constructed, and the influence is constructed by combining the closeness centrality and regression coefficient of the ecological restoration parameter;

[0028] Several ecological restoration parameters are ranked by influence and the parameter ranking is obtained. The first several ecological restoration parameters in the parameter ranking are used as key factors, and the key factors are adjusted using the optimization algorithm to obtain the optimized ecological environment monitoring strategy.

[0029] (III) Beneficial effects

[0030] The present invention provides a soil environment ecological restoration monitoring method, which has the following beneficial effects:

[0031] 1. Judge whether the environmental conditions in the ecological restoration area are suitable for ecological environmental restoration based on the value of the restoration condition value Tot, and handle abnormal environmental conditions in a timely manner.

[0032] 2. The constructed anomaly degree is used to select abnormal factors within several environmental parameters. After obtaining the abnormal factors, the environmental conditions of the ecological restoration area are adjusted in a targeted manner based on the abnormal factors. On the basis of completing the restoration of the soil, the ecological restoration area is made more suitable for ecological environmental restoration.

[0033] 3. Obtain the growth value Rot used to evaluate the growth status of the target plant. If the growth status of the target plant lags behind expectations, it is necessary to ensure that the growth status of the target plant remains normal to ensure the vegetation coverage rate. After constructing the fertility optimization and adjustment knowledge graph, the corresponding fertility optimization and adjustment plan can be quickly determined to improve the growth status of the target plant through fertility optimization.

[0034] 4. After obtaining the type of pests, formulate targeted pest control strategies to reduce the impact of pests on ecological restoration, improve the growth status of target plants, and quickly increase vegetation coverage and species diversity.

[0035] 5. Judge the degree of ecological environment restoration based on the coverage Jot, and determine which ecological restoration parameters have a greater impact on vegetation coverage based on the correlation between the ecological restoration parameters and the vegetation coverage rate, and take the ones with the greater impact as the key factors; in order to improve the vegetation coverage rate and subsequent biodiversity, adjust several corresponding ecological restoration parameters, and obtain new ecological environment monitoring and management strategies. When the new management strategy is used for ecological environment monitoring, the yield of target plants can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the flow chart of the ecological restoration monitoring method of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] See also Figure 1 The present invention provides a soil environment ecological restoration monitoring method, comprising:

[0039] Step 1: After collecting restoration environment data in the ecological restoration area, generate the restoration condition value Tot. If the restoration condition value Tot is lower than expected, screen out abnormal factors in the restoration environment data and process the restoration environment based on the abnormal factors;

[0040] The step 1 includes the following contents:

[0041] Step 101: When ecological monitoring and restoration are performed in an ecological restoration area, a number of evenly distributed monitoring points are set in the ecological restoration area, and environmental data such as soil moisture, air humidity, and groundwater level in the ecological restoration area are monitored in real time at each monitoring point, and the collected environmental data are aggregated to generate a restoration environment data set;

[0042] Step 102: construct the restoration condition value Tot from the restoration environment data, wherein the soil moisture Co, groundwater level So and air humidity Cs are linearly normalized, and the corresponding data values ​​are mapped to the interval [0,1], and then according to the following formula:

[0043]

[0044] Weight coefficient: 0≤F1≤1, 0≤F2≤1, 0≤F3≤1, and F1+F2+F3=1. The weight coefficient can be obtained by referring to the hierarchical analysis method; i=1,2,…,m,m is the total number of monitoring points, Co i is the soil moisture at the ith monitoring point, is the qualified reference value of soil moisture; So i is the groundwater level at the ith monitoring point, is the qualified reference value of groundwater level; Cs i is the air humidity at the ith monitoring point, It is the qualified reference value of air humidity;

[0045] Pre-set condition thresholds based on historical data and management expectations for environmental conditions;

[0046] If the restoration condition value Tot is lower than the condition threshold, it means that the environmental conditions in the ecological restoration area are poor, which is not conducive to ecological environmental restoration and does not meet current expectations. It needs to be adjusted. At this time, an adjustment instruction is issued to the outside.

[0047] When in use, after collecting various parameters in the ecological restoration area, the restoration condition value Tot is constructed from the collected data. The environmental conditions in the ecological restoration area are judged whether they are suitable for ecological environmental restoration based on the value of the restoration condition value Tot. If suitable, the current state can be maintained. If the conditions are poor, targeted adjustments can be made. Through real-time data collection, abnormal environmental conditions can be dealt with in a timely manner.

[0048] Step 103: After receiving the adjustment instruction, continuously obtain the environmental parameters of several time nodes, and construct the abnormality Yot of each environmental parameter according to the following formula under dimensionless conditions:

[0049]

[0050] Where i = 1, 2, ..., k, k is the total number of time nodes, Z i is the environmental parameter value at the i-th time node, Z avg is the mean value of the environmental parameter;

[0051] If the abnormality Yot exceeds expectations, the corresponding environmental parameters will be identified as abnormal factors, and the environmental conditions in the ecological restoration area will be targeted according to the abnormal factors in the following ways: install an intelligent drip irrigation system, including drip irrigation pipes, drippers, water pumps and filters, to ensure that water is accurately delivered to the root zone of the target plants;

[0052] Set up an automatic controller to adjust the irrigation frequency and water volume in real time according to soil moisture, and automatically adjust the irrigation system; set up an automatic ventilation system, control the fan and sunshade through temperature and humidity sensors, optimize the air circulation in the ecological restoration area, and install an adjustable sunshade net that automatically opens or closes according to light intensity to ensure plant photosynthesis. When light is insufficient, use plant growth lights to supplement light to ensure the normal growth of target plants.

[0053] When using, combine the contents in steps 101 to 103:

[0054] When the environmental conditions in the ecological restoration area are abnormal, various environmental parameters are analyzed and screened, and the abnormal factors are selected from several environmental parameters by the constructed abnormality degree. After the abnormal factors are obtained, the environmental conditions in the ecological restoration area are adjusted in a targeted manner based on the abnormal factors. On the basis of completing the soil restoration, the ecological restoration area is made more suitable for ecological environmental restoration.

[0055] Step 2: After collecting the growth status data of the target plants in the ecological restoration area, a growth value Rot is constructed from the growth status data. If the growth value Rot is lower than the growth threshold, an alarm instruction is issued to the outside;

[0056] The step 2 includes the following contents:

[0057] Step 201: select a number of target plants in the vicinity of each monitoring point, and use sensors and IoT devices, such as image sensors or size sensors, to collect and record the growth data of the target plants, including plant height, number of leaves, color, etc., and then summarize and construct a growth status data set.

[0058] Step 202: Obtain the conventional growth parameters of the target plant and use them as qualified reference values. Construct the growth value Rot from the growth status data set. After linear normalization processing is performed on the obtained plant height Gs and leaf number Ys, the corresponding data values ​​are mapped to the interval [0,1] according to the following formula:

[0059]

[0060] Weight coefficient, 0≤α≤1, 0≤β≤1, and α+β=1, Gs avg is the mean plant height of each target plant, Ys is the qualified reference value of plant height; avg is the mean number of leaves, is the qualified reference value of the number of leaves;

[0061] Pre-set growth thresholds based on historical data and management expectations for the ecological environment monitoring phase;

[0062] Whether the growth stage meets expectations is determined based on the growth value Rot. If the obtained growth value Rot is lower than the growth threshold, it means that the growth degree of the target plant has not met expectations, which may be due to the lack of sufficient nutrient supply in the ecological restoration area or similar reasons. At this time, an alarm command is issued to the outside;

[0063] When using, combine the contents in steps 201 and 202:

[0064] When the environmental conditions in the ecological restoration area are at a roughly normal stage, after monitoring the growth status of the target plant and obtaining the corresponding planting data, a number of monitoring data are comprehensively correlated and processed to obtain the growth value Rot used to evaluate the growth status of the target plant. If the growth status of the target plant lags behind expectations, it is necessary to make timely adjustments, for example, adjust the nutritional environment and soil conditions of the target plant. In this scenario, by timely determining the growth status of the target plant, it is possible to ensure that the growth status of the target plant remains normal, thereby ensuring the vegetation coverage rate;

[0065] Step 3: Collect soil data in the ecological restoration area, and after feature extraction, provide a corresponding fertility optimization adjustment plan for the ecological restoration area. When there are pests on the target plants, take targeted pest control plans;

[0066] The step three includes the following contents:

[0067] Step 301: After receiving the alarm instruction, select several collection points in the ecological restoration area, collect soil at each collection point, and obtain corresponding soil monitoring data after testing and analyzing the soil, including:

[0068] Soil physical properties: Particle composition: describes the proportion of particles of different sizes (such as sand, silt, clay) in the soil. Specific gravity: the ratio of the weight of soil solid particles to the weight of the same volume of water. Wet density and dry density: indicate the unit volume weight of the soil in a wet and dry state, respectively. Moisture content: the water content in the soil, usually expressed as a percentage by weight. Limit moisture content: includes plastic limit moisture content and liquid limit moisture content, which indicate the limit moisture content of the soil from semi-solid to plastic and from plastic to liquid, respectively.

[0069] Soil chemical properties: pH value: an indicator of soil acidity and alkalinity, which has an important impact on plant growth and the existence of nutrient elements. Soil nutrients: including total nitrogen, total phosphorus, total potassium, available phosphorus, available potassium, etc., are the main nutrient elements for plant growth. Calcium carbonate in the soil: has an indicative effect on the formation and fertility characteristics of calcareous soil.

[0070] Soil biological properties: number and types of microorganisms: including total colony count, coliform bacteria, molds, yeasts and other conventional microorganisms, as well as unconventional microorganisms such as Enterobacteriaceae and osmophilic yeast.

[0071] Soil pollution and hazardous substances: Heavy metal content: such as lead, cadmium, mercury, etc., which pose a potential threat to plant growth and human health. Pesticide and antibiotic residues: Assess the impact of chemical pollutants on the soil.

[0072] According to the management of soil fertility in the ecological restoration area, set corresponding qualified standard values ​​for various soil test data;

[0073] After feature extraction of soil monitoring data, several fertility optimization features are obtained;

[0074] Taking fertility optimization and adjustment as the target word, after deep retrieval and entity relationship building, a fertility optimization and adjustment knowledge graph is pre-built. Using the trained matching model, according to the correspondence between fertility optimization features and fertility optimization and adjustment plans, the fertility optimization and adjustment knowledge graph provides corresponding fertility optimization and adjustment plans for the ecological restoration area.

[0075] When in use, when the growth progress of the target plant is slow, the soil data at various locations in the ecological restoration area are first detected and analyzed, and the corresponding fertility optimization features are obtained after feature extraction. After constructing the fertility optimization adjustment knowledge graph, if the growth progress of the target plant is slower than expected, the corresponding fertility optimization adjustment plan can be quickly determined to improve the growth status of the target plant through fertility optimization.

[0076] Step 302: After the fertility optimization is completed in the ecological restoration area, an observation period including several sub-periods is set;

[0077] After collecting image data of the target plant in each sub-period, image recognition is performed to identify whether the target plant is infested with insects. If there is an insect infestation and the infestation area exceeds the expected proportion, an external pest control instruction is issued;

[0078] Step 303: after receiving the pest control instruction, the pest type and pest infection status are obtained through image recognition, and the corresponding pest features are obtained after feature extraction;

[0079] After obtaining several pest control plans through online search or offline formulation, a pest control plan library is pre-built;

[0080] Based on the correspondence between pest characteristics and pest control plans, a pre-constructed pest control plan library is used to match the corresponding pest control plan for the ecological restoration area. For example, biological control can be used, such as releasing natural enemy insects and using biological pesticides to reduce the use of chemical pesticides.

[0081] When using, combine the contents in steps 301 to 303:

[0082] In addition to targeted fertility optimization, image recognition and analysis of target plants are performed to determine whether there are pests at present. If there are pest problems, targeted pest control strategies can be formulated after obtaining the pest type to reduce the impact of pests on ecological restoration, improve the growth status of target plants, and quickly increase vegetation coverage and species diversity.

[0083] Step 4: Collect ecological restoration parameters and vegetation coverage data within the ecological restoration cycle, select key factors from several ecological restoration parameters through correlation analysis, use optimization algorithms to adjust key factors, and obtain optimized ecological environment monitoring strategies;

[0084] The step 4 includes the following contents:

[0085] Step 401: After the target plant is planted, the vegetation coverage rate of each stage of the ecological environment monitoring is obtained, and the coverage Jot of the ecological environment monitoring stage is constructed. The current ecological restoration state is determined according to the coverage Jot.

[0086] After linear normalization of the vegetation coverage Hs, the corresponding data value is mapped to the interval [0,1] according to the following formula:

[0087]

[0088] Where i = 1, 2, ..., p, p is the number of breeding stages, weight coefficient: 0 ≤ S1 ≤ 1, 0 ≤ S2 ≤ 1 and S2 + S1 = 1; Hs i is the vegetation coverage rate of the ith sub-region, Hs avg is the mean value of vegetation coverage, is the qualified reference value of vegetation coverage; the weight coefficient can be obtained by referring to the hierarchical analysis method;

[0089] Pre-set coverage thresholds based on historical data and management expectations for ecological and environmental restoration;

[0090] If the coverage Jot is lower than the coverage threshold, it means that the current ecological environment restoration has not achieved the expected effect. At this time, an analysis instruction is issued to the outside;

[0091] When in use, the coverage Jot is constructed based on the vegetation coverage data within the period, and the degree of ecological environment restoration is judged based on the coverage Jot. If the coverage Jot exceeds the coverage threshold, it means that the ecological environment restoration has reached expectations. Otherwise, it needs to be readjusted.

[0092] Step 402: After collecting and summarizing environmental data, plant growth data, and fertility optimization data during the ecological environment restoration period, a collection of ecological environment monitoring data is constructed;

[0093] Conduct correlation analysis between various ecological restoration parameters and vegetation coverage in the ecological environment monitoring set, obtain the corresponding correlation coefficient, determine the influence of various ecological restoration parameters on vegetation coverage, use ecological restoration parameters as independent variables and vegetation coverage as dependent variables to conduct multiple linear regression analysis, and obtain the corresponding linear regression equation, and obtain the regression coefficient Sp corresponding to each ecological restoration parameter from the linear regression equation;

[0094] Step 403: After obtaining each correlation coefficient, construct the closeness centrality Cn of each ecological restoration parameter. The specific method is as follows:

[0095]

[0096] Among them, k is the number of ecological restoration parameters, Q ij is the correlation coefficient between ecological restoration parameter i and ecological restoration parameter j; under dimensionless conditions, the influence Xot is constructed by combining the closeness centrality Cn and regression coefficient Sp of the ecological restoration parameters as follows:

[0097]

[0098] Weight coefficient: 0≤S1≤1, 0≤S2≤1 and S2+S1=1; the weight coefficient can be consistent with the previous value; Sp i is the regression coefficient of the ith ecological restoration parameter, Sp avg is the mean of the regression coefficient, Cn i is the closeness centrality of the i-th ecological restoration parameter, Cn avg is the mean of the proximity centrality;

[0099] Sort several ecological restoration parameters by the influence degree Xot and obtain the parameter ranking. Take the first several ecological restoration parameters in the parameter ranking as the key factors, and use the optimization algorithm to adjust the key factors, such as adjusting irrigation, fertility optimization and soil pollution remediation, to obtain the optimized ecological environment monitoring strategy;

[0100] When using, combine the contents in steps 401 to 403:

[0101] After the ecological restoration cycle is over, obtain the ecological restoration parameters during the ecological restoration cycle, such as irrigation volume, fertility optimization degree, etc., and determine which ecological restoration parameters have a greater impact on vegetation coverage based on the correlation between the ecological restoration parameters and the vegetation coverage rate, and take the ones with the greater impact as the key factors;

[0102] While continuing ecological and environmental restoration, in order to increase vegetation coverage and subsequent biodiversity, several corresponding ecological restoration parameters can be adjusted to obtain new ecological and environmental monitoring and management strategies. When the new ecological and environmental monitoring is carried out using the new management strategies, the yield of target plants can be improved.

[0103] The Analytic Hierarchy Process (AHP) is a decision-making method that decomposes decision-related elements into levels such as goals, criteria, and plans, and conducts qualitative and quantitative analysis on this basis. It is particularly suitable for dealing with target systems with hierarchical and staggered evaluation indicators, and when the target value is difficult to describe quantitatively, the AHP is an effective decision-making tool.

[0104] The core of the hierarchical analysis method is to decompose the decision problem into multiple levels to form a hierarchical structure, which usually includes the target level, the criterion level, the sub-criterion level and the solution level. By solving the eigenvector of the judgment matrix, the priority weight of each element of each level to an element of the previous level is obtained, and the final weight of each alternative solution to the total goal is recursively merged by the weighted sum method, so as to find the optimal solution.

[0105] First, it is necessary to clarify the field and scope of the knowledge graph, namely, fertility optimization and adjustment. This includes determining the soil types, crop types, fertilization methods, soil testing indicators and other related content that the knowledge graph will cover.

[0106] Ontology is the basis of knowledge graph, which is used to describe concepts, attributes and relationships in a field. In the knowledge graph of fertility optimization and adjustment, the ontology may include concepts such as soil type, crop, fertilizer, fertilizer amount, fertilizer application time, and the attribute relationship between them, such as the appropriate fertilizer amount and fertilizer application time of a certain fertilizer for a certain crop.

[0107] The construction of knowledge graphs requires a large amount of data as a basis. In the field of fertility optimization and adjustment, data can come from many aspects, such as soil test reports, agricultural test data, agricultural literature, network resources, etc. The data collection process includes data extraction, cleaning, conversion and other operations to ensure the accuracy and consistency of the data.

[0108] Identify entities (such as soil type, crop name, fertilizer type, etc.) from the collected data and link them to associate different representations of the same entity. Entity identification and linking are key steps in building a knowledge graph, helping to ensure that the entities in the knowledge graph are accurate and consistent.

[0109] On the basis of entity recognition and linking, the relationship between entities is further extracted from the data to form edges in the knowledge graph. In the knowledge graph of fertility optimization and adjustment, the relationship may include the relationship between soil type and crop growth, the relationship between fertilizer type and fertilizer application amount, etc. Relationship extraction can adopt rule-based methods, supervised learning methods, or semi-supervised learning methods.

[0110] Knowledge fusion is the process of integrating and unifying knowledge from different sources, formats or structures. In the knowledge graph of fertility optimization and adjustment, it may be necessary to fuse knowledge from different data sources to ensure the integrity and consistency of the knowledge graph. Knowledge fusion includes fusion at the concept level and fusion at the instance level, involving issues such as knowledge consistency, completeness, and deduplication.

[0111] Knowledge reasoning is to derive new knowledge based on known facts and rules in the knowledge graph. In the knowledge graph of fertility optimization and adjustment, knowledge reasoning can be achieved through logical reasoning, machine learning, deep learning and other methods to expand the knowledge in the knowledge graph and discover potential associations. For example, based on historical fertilization data and crop growth conditions, the optimal amount and time of fertilizer application for a certain crop under specific soil conditions can be derived.

[0112] After the knowledge graph is built, it can be applied to various scenarios, such as intelligent fertilization recommendations, soil fertility assessment, etc. At the same time, the knowledge graph needs to be continuously optimized and updated to adapt to changing needs and data. Optimization may include adding new entities and relationships, updating existing entity and relationship attributes, etc.

[0113] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0114] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0115] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only some logical function divisions. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0116] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0118] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A soil environment ecological restoration monitoring method, characterized in that: include, After collecting restoration environment data in the ecological restoration area, the restoration condition value is generated. If the restoration condition value is lower than expected, the abnormal factors are screened out in the restoration environment data, and the restoration environment is processed according to the abnormal factors; After collecting the growth status data of the target plants in the ecological restoration area, the growth value is constructed; if the growth value is lower than the growth threshold, soil data is collected in the ecological restoration area; After feature extraction, a fertility optimization adjustment plan is given for the ecological restoration area; when there are pests on the target plants, a targeted pest control plan is adopted; Collect ecological restoration parameters and vegetation coverage data during the ecological restoration cycle, screen out key factors from several ecological restoration parameters, use optimization algorithms to adjust the key factors, and obtain optimized ecological environment monitoring strategies.

2. The method for monitoring the ecological restoration of soil environment according to claim 1, characterized in that: When conducting ecological monitoring and restoration in an ecological restoration area, a number of evenly distributed monitoring points are set up in the ecological restoration area. At each monitoring point, environmental data such as soil moisture, air humidity, groundwater level, etc. in the ecological restoration area are monitored in real time, and the restoration environment data set is summarized and generated.

3. The method for monitoring the ecological restoration of soil environment according to claim 2, characterized in that: The repair condition value is constructed from the repair environment data. If the repair condition value is lower than the condition threshold, an adjustment instruction is issued to the outside. After receiving the adjustment instruction, the environmental parameters of several time nodes are continuously obtained to construct the abnormality of each environmental parameter. If the abnormality exceeds expectations, the corresponding environmental parameter is determined as an abnormal factor.

4. The method for monitoring the ecological restoration of soil environment according to claim 3, characterized in that: Select several target plants in the vicinity of each monitoring point, collect and record the growth data of the target plants, construct a growth status data set, obtain the conventional growth parameters of the target plants, use them as qualified reference values, and construct growth values ​​from the growth status data set.

5. The method for monitoring the ecological restoration of soil environment according to claim 4, characterized in that: After receiving the alarm instruction, several collection points are selected in the ecological restoration area, soil is collected at each collection point, and the corresponding soil monitoring data is obtained after the soil is tested and analyzed. After feature extraction of the soil monitoring data, several fertility optimization features are obtained; Taking fertility optimization and adjustment as the target word, a fertility optimization and adjustment knowledge graph is pre-constructed. According to the correspondence between fertility optimization characteristics and fertility optimization and adjustment plans, the fertility optimization and adjustment knowledge graph provides corresponding fertility optimization and adjustment plans for the ecological restoration area.

6. The method for monitoring the ecological restoration of soil environment according to claim 5, characterized in that: After completing fertility optimization in the ecological restoration area, image data of the target plants are collected in each sub-period and image recognition is performed to identify whether the target plants are infested with pests. If there are pests and the infestation area exceeds the expected proportion, pest control instructions are issued to the outside.

7. The method for monitoring ecological restoration of soil environment according to claim 6, characterized in that: After receiving the pest control instruction, the pest type and pest infection status are obtained through image recognition, and the corresponding pest features are obtained after feature extraction; According to the correspondence between pest characteristics and pest control plans, the pre-built pest control plan library matches the corresponding pest control plan for the ecological restoration area.

8. The method for monitoring ecological restoration of soil environment according to claim 7, characterized in that: After the target plant is finished, the vegetation coverage rate of each stage of ecological environment monitoring is obtained, and the coverage of the ecological environment monitoring stage is constructed. If the coverage is lower than the coverage threshold, an analysis instruction is issued to the outside; Collect and summarize environmental data, plant growth data and fertility optimization data during the ecological environment restoration cycle, and summarize and construct an ecological environment monitoring data set.

9. The method for monitoring ecological restoration of soil environment according to claim 8, characterized in that: Conduct correlation analysis between various ecological restoration parameters and vegetation coverage in the ecological environment monitoring set to obtain the corresponding correlation coefficients; perform multiple linear regression analysis with ecological restoration parameters as independent variables and vegetation coverage as dependent variables, and obtain the corresponding linear regression equations, and obtain the regression coefficients corresponding to each ecological restoration parameter from the linear regression equations.

10. The method for monitoring ecological restoration of soil environment according to claim 9, characterized in that: After obtaining each correlation coefficient, the closeness centrality of each ecological restoration parameter is constructed, and the influence is constructed by combining the closeness centrality and regression coefficient of the ecological restoration parameter; Several ecological restoration parameters are ranked by influence and the parameter ranking is obtained. The first several ecological restoration parameters in the parameter ranking are used as key factors, and the key factors are adjusted using the optimization algorithm to obtain the optimized ecological environment monitoring strategy.

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