Land ecological condition monitoring system and method

Abstract

The invention belongs to the technical field of land ecological monitoring, and discloses a land ecological condition monitoring system and method. The method comprises the following steps: acquiring pollutant concentration data of R sampling points at N time points in a land ecological monitoring area, constructing a pollutant concentration set and performing fitting analysis to obtain a pollutant concentration equation and a corresponding pollutant concentration derivative set; collecting physicochemical index data including soil pH value, organic matter content and permeability, forming a physicochemical index set, and performing change analysis to obtain a physicochemical index change set; evaluating the ecological condition of the land based on the pollutant concentration derivative set and the physicochemical index change set, judging the ecological degradation degree of the land, and generating corresponding early warning information and a restoration scheme according to the degradation degree; according to the method, the ecological degradation degree of the land can be accurately identified, a graded early warning and restoration scheme is generated, and the intelligence and response timeliness of ecological monitoring are improved.

Description

Technical Field

[0001] This invention relates to the field of land ecological monitoring technology, and more specifically, to a land ecological status monitoring system and method. Background Technology

[0002] With the continuous increase in industrialization and agricultural intensification, land ecosystems are subjected to long-term accumulation and disturbance by various pollutants, manifesting as rising soil pollution loads, degradation of physicochemical properties, and weakening of ecological functions. The migration and transformation of pollutant concentrations in soil exhibit significant nonlinear dynamic characteristics, and physicochemical indicators such as soil pH, organic matter content, and permeability also change in complex ways with time and environmental conditions. To effectively understand the status of land ecological quality, existing technologies typically monitor and assess land pollution and ecological degradation through regular sampling, laboratory analysis, and manual threshold comparison, combined with human experience to determine risk levels and formulate remediation measures.

[0003] However, existing technologies still have certain shortcomings in practical applications. Specifically, pollutant concentration monitoring is mostly limited to static measurements, and cannot reveal the rate and trend of pollutant concentration changes through regression fitting and derivative analysis, resulting in untimely identification of abnormal increases in pollution load; soil physicochemical indicators are mostly based on single-point results, lacking linkage analysis with dynamic pollutant data, making it difficult to comprehensively reflect the process of land ecological degradation and evolution; in addition, the lack of an automated linkage system for graded early warning and emergency intervention leads to a lag in response to the spread of ecological degradation, failing to meet the needs of practical applications.

[0004] Therefore, there is an urgent need to provide a land ecological status monitoring system and method that can combine changes in pollutant concentration with changes in soil physicochemical indicators for comprehensive analysis and support graded intervention and restoration, so as to improve the scientific and intelligent level of land ecological degradation identification and management.

[0005] In view of this, the present invention proposes a land ecological status monitoring system and method to solve the above problems. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a method for monitoring land ecological conditions, comprising:

[0007] Acquire pollutant concentration data at N time points for R sampling points in a land ecological monitoring area;

[0008] The pollutant concentrations of each pollutant in the pollutant concentration data are used to form a corresponding pollutant concentration set. The pollutant concentration set is fitted and analyzed to obtain a set of pollutant concentration equations. Then, derivative analysis is performed based on the pollutant concentration equation set to obtain a set of pollutant concentration derivatives for each pollutant.

[0009] Obtain soil physicochemical index data for R sampling points at N time points in a land ecological monitoring area;

[0010] The soil physicochemical indexes in the soil physicochemical index data are used to form a corresponding set of soil physicochemical indexes, and the change analysis of the set of soil physicochemical indexes is carried out to obtain the set of physicochemical index changes of each soil physicochemical index.

[0011] Land ecological status is assessed based on the set of pollutant concentration derivatives and the set of changes in physicochemical indicators to obtain the degree of land ecological degradation.

[0012] Based on the degree of land ecological degradation, early warning information on land ecological degradation and land ecological degradation restoration plans are generated adaptively.

[0013] Furthermore, methods for adaptively generating land ecological degradation early warning information and land ecological degradation restoration plans based on the degree of land ecological degradation include:

[0014] When the degree of land ecological degradation is at the low level, a low degradation warning message is generated. No immediate restoration measures are required; only regular monitoring is recommended.

[0015] When the degree of land ecological degradation is moderate, an early warning message is generated that includes a moderate degradation risk warning and a moderate ecological degradation intervention suggestion. The moderate ecological degradation intervention suggestion retrieves matching degradation restoration measures from a preset degradation restoration scheme library.

[0016] When the degree of land ecological degradation reaches the level of severe land ecological degradation, a severe degradation early warning information is generated, and severe degradation emergency intervention measures are automatically implemented. The severe degradation emergency intervention measures include controlling irrigation equipment to flush or dilute the soil to reduce the degree of land ecological degradation, controlling spraying equipment to apply soil conditioners to the soil, and closing sewage channels in the land ecological monitoring area.

[0017] Furthermore, the method for obtaining the degree of land ecological degradation includes:

[0018] The set of pollutant concentration derivatives and the set of soil physicochemical indicators corresponding to R sampling points are respectively input into the land ecological degradation assessment model to obtain R corresponding land ecological degradation scores;

[0019] Preset land ecological degradation scoring threshold one and land ecological degradation scoring threshold two; land ecological degradation scoring threshold one is less than land ecological degradation scoring threshold two;

[0020] Based on R land ecological degradation scores, land ecological degradation score threshold one, and land ecological degradation score threshold two, a comprehensive assessment of the land ecological status is conducted to obtain the land ecological degradation level of the land ecological monitoring area, and the land ecological degradation level is used as the degree of land ecological degradation.

[0021] Furthermore, the method for obtaining the land ecological degradation level of the land ecological monitoring area includes:

[0022] Obtain land ecological degradation scores for R sampling points; compare each land ecological degradation score with a preset land ecological degradation score threshold 1 and a preset land ecological degradation score threshold 2.

[0023] If the land ecological degradation score is less than the first threshold for land ecological degradation, it is determined to be at the low level of land ecological degradation; if the land ecological degradation score is greater than or equal to the first threshold for land ecological degradation but less than the second threshold for land ecological degradation, it is determined to be at the moderate level of land ecological degradation; if the land ecological degradation score is greater than or equal to the second threshold for land ecological degradation, it is determined to be at the severe level of land ecological degradation.

[0024] A comprehensive assessment is conducted based on R land ecological degradation scores and their corresponding land ecological degradation levels to obtain the land ecological degradation level of the land ecological monitoring area.

[0025] Furthermore, methods for obtaining the land ecological degradation level of the land ecological monitoring area by comprehensively assessing R land ecological degradation scores and their corresponding land ecological degradation levels include:

[0026] The number of sampling points corresponding to the low degradation level, moderate degradation level, and severe degradation level of land ecology were counted separately, and the proportion of each degradation level was calculated.

[0027] Determine whether the proportion of land ecological degradation levels exceeds a preset threshold for severe degradation.

[0028] If the judgment result is yes, then the land ecological degradation level of the land ecological monitoring area is defined as the severe land ecological degradation level;

[0029] If the judgment result is negative, a comprehensive land ecological degradation score is calculated based on R land ecological degradation scores. If the comprehensive land ecological degradation score is greater than the preset comprehensive land ecological degradation score threshold, the land ecological degradation level of the land ecological monitoring area is defined as a moderate land ecological degradation level. If the comprehensive land ecological degradation score is not greater than the preset comprehensive land ecological degradation score threshold, the land ecological degradation level of the land ecological monitoring area is defined as a low land ecological degradation level.

[0030] Furthermore, the method for obtaining the set of pollutant concentration derivatives includes:

[0031] Obtain each pollutant concentration set; use the matrix method to perform regression fitting on the pollutant concentration set to obtain the corresponding pollutant concentration equation, which is a quadratic polynomial equation; differentiate the pollutant concentration equation to obtain the concentration equation derivative corresponding to the pollutant concentration equation; substitute the pollutant concentrations in the pollutant concentration set into the concentration equation derivative to form the corresponding pollutant concentration derivative set.

[0032] Furthermore, methods for using matrix methods to regress and fit the pollutant concentration set to obtain the corresponding pollutant concentration equations include:

[0033] Construct a time point matrix from N time points, and construct a pollutant concentration matrix from the set of pollutant concentrations;

[0034] Multiply the transpose of the time point matrix by the time point matrix to obtain the time point square matrix;

[0035] Calculate the inverse matrix of the time point square matrix, and label it as the inverse matrix of the square matrix;

[0036] The equation coefficient matrix is ​​calculated based on the inverse matrix of the square matrix, the transpose of the time point matrix, and the pollutant concentration matrix; the equation coefficient matrix has a dimension of 3×1.

[0037] Initialize the quadratic polynomial equation, take the first row of the equation coefficient matrix as the quadratic term coefficient, take the second row of the equation coefficient matrix as the linear term coefficient, and take the third row of the equation coefficient matrix as the constant term, to obtain the pollutant concentration equation.

[0038] Furthermore, the methods for obtaining the set of changes in various soil physicochemical indicators include:

[0039] For R sampling points, the soil pH values ​​at adjacent time points are subtracted to obtain pH difference values, and these pH difference values ​​are added to the pH change set; the soil organic matter content at adjacent time points is subtracted to obtain organic matter content difference values, and these organic matter content difference values ​​are added to the organic matter change set; the soil permeability at adjacent time points is subtracted to obtain permeability difference values, and these permeability difference values ​​are added to the permeability change set.

[0040] Furthermore, the training method for the land ecological degradation assessment model includes:

[0041] A land ecological degradation assessment dataset containing a set of pollutant concentration derivatives and a set of soil physicochemical indicators, along with corresponding land ecological degradation scores, was constructed. The land ecological degradation assessment dataset was divided into a training set and a validation set. A deep neural network with a multilayer perceptron as its core was used to train the model by inputting the standardized data. The model consists of an input layer, hidden layers, and a softmax output layer. The model training used the cross-entropy loss function as the optimization objective, updated the weights using the gradient descent algorithm, and monitored the validation set performance through an early stopping strategy. When the prediction accuracy reached a preset threshold, convergence was determined and training was terminated.

[0042] A land ecological status monitoring system, implementing the aforementioned land ecological status monitoring method, includes:

[0043] The first data acquisition module is used to acquire pollutant concentration data at N time points corresponding to R sampling points in the land ecological monitoring area.

[0044] The first processing module is used to construct a corresponding pollutant concentration set from the pollutant concentration data of each pollutant, perform fitting analysis on the pollutant concentration set to obtain a pollutant concentration equation set, and perform derivative analysis based on the pollutant concentration equation set to obtain a pollutant concentration derivative set corresponding to each pollutant.

[0045] The second data acquisition module is used to acquire soil physicochemical index data corresponding to R sampling points at N time points in the land ecological monitoring area; the soil physicochemical index data includes soil pH value, soil organic matter content and soil permeability;

[0046] The second processing module is used to construct a corresponding set of soil physicochemical indicators from the soil physicochemical index data, and to perform change analysis on the set of soil physicochemical indicators to obtain the set of physicochemical index changes for each soil physicochemical indicator.

[0047] The ecological status diagnosis module assesses the land ecological status based on the set of pollutant concentration derivatives and the set of changes in physicochemical indicators, and obtains the degree of land ecological degradation.

[0048] The ecological degradation response module is used to adaptively generate early warning information on land ecological degradation and land ecological degradation restoration plans based on the degree of land ecological degradation.

[0049] The technical effects and advantages of the land ecological status monitoring system and method of the present invention are as follows:

[0050] This application, by combining dynamic analysis of pollutant concentrations with multidimensional monitoring of soil physicochemical indicators, enables the comprehensive, hierarchical, and quantitative identification of land ecological degradation. Specifically, by utilizing pollutant concentration regression fitting and derivative analysis methods, it accurately characterizes the nonlinear changes of pollutants over time, sensitively capturing abnormal growth trends in pollution loads and significantly improving the early warning sensitivity to potential ecological degradation risks. The set of changes in soil physicochemical indicators, through difference analysis, comprehensively reflects the dynamic evolution of key ecological indicators such as soil pH, organic matter content, and permeability, helping to reveal the long-term impact of pollution accumulation on soil physicochemical properties and achieving a three-dimensional characterization of the land ecological degradation process.

[0051] Furthermore, by inputting the set of pollutant concentration derivatives and the set of soil physicochemical indicators into the land ecological degradation assessment model, a multi-point distributed land ecological degradation score is generated. Combined with the dynamically set degradation score threshold by the scoring threshold setting module, this improves the adaptability of degradation level determination and reduces the risk of false alarms or missed detections caused by fixed thresholds, thereby enhancing the scientific rigor and accuracy of degradation identification results. Through a hierarchical response mechanism, the system can adaptively generate tiered early warning information and remediation strategies based on different degradation levels. Specifically, for severe degradation levels, emergency intervention measures such as flushing and dilution, application of amendments, and closure of sewage channels are automatically triggered, achieving a closed-loop linkage from monitoring to intervention, effectively preventing further spread or deterioration of land ecological degradation.

[0052] In summary, this application has significant advantages in terms of monitoring accuracy, risk warning, threshold adaptation, and governance response, and comprehensively improves the intelligence level and timeliness of land ecological status monitoring and management, thus having high practical application value. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of a land ecological status monitoring system according to Embodiment 1 of the present invention;

[0054] Figure 2 This is a schematic diagram of a land ecological status monitoring system according to Embodiment 2 of the present invention;

[0055] Figure 3 This is a flowchart of a land ecological status monitoring method according to Embodiment 3 of the present invention;

[0056] Figure 4 This is a flowchart of the method for adaptively generating land ecological degradation early warning information and land ecological degradation restoration plan based on the degree of land ecological degradation according to Embodiment 1 of the present invention;

[0057] Figure 5 This is a flowchart of the method for obtaining the degree of land ecological degradation in Embodiment 1 of the present invention. Detailed Implementation

[0058] 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.

[0059] Example 1

[0060] Please see Figure 1 As shown in the figure, the land ecological status monitoring system described in this embodiment includes a first acquisition module, a first processing module, a second acquisition module, a second processing module, an ecological status diagnosis module, and an ecological degradation response module. Each module is connected by wires and / or wirelessly to realize data transmission.

[0061] The first acquisition module is used to acquire pollutant concentration data at N time points corresponding to R sampling points in the land ecological monitoring area.

[0062] It should be noted that the first acquisition module is used to acquire pollutant concentration data at N time points corresponding to R sampling points in the land ecological monitoring area. As an embodiment of this application, the pollutant concentration data may include heavy metal pollutants, organic pollutants, nutrients, acidic and alkaline substances, and pesticide residues. Examples of heavy metal pollutants include lead, cadmium, mercury, and chromium; examples of organic pollutants include polycyclic aromatic hydrocarbons, benzene compounds, and petroleum hydrocarbons; examples of nutrients include nitrogen and phosphorus; and examples of acidic and alkaline substances include sulfate and chloride ions.

[0063] In practical applications, the embodiments of this application can be customized and expanded to include different types of pollutants collected at sampling points based on the land use, historical pollution status, and geographical and climatic conditions of the monitoring area. For example, for agricultural land, the focus can be on monitoring organic pollutants and pesticide residues; for industrial land, the focus can be on monitoring heavy metals and acidic / alkaline pollutants. The pollutant data cited in this application are only partial examples and are not intended to limit the technical solution of this invention. Those skilled in the art can select or add other types of pollutants according to actual needs and monitoring purposes, and all such selections should be considered to fall within the protection scope of this invention.

[0064] The first processing module is used to construct a corresponding pollutant concentration set from the pollutant concentration data, perform fitting analysis on the pollutant concentration set to obtain a pollutant concentration equation set, and perform derivative analysis based on the pollutant concentration equation set to obtain a pollutant concentration derivative set corresponding to each pollutant.

[0065] The method for obtaining the pollutant concentration set includes:

[0066] S121: Let r be initially 1, let i be initially 1; the range of r is 1 to R, and the range of i is 1 to N;

[0067] S122: Obtain the pollutant concentration at the r-th monitoring sampling point at the i-th time point;

[0068] S123: Add the pollutant concentration to the pollutant concentration set corresponding to the r monitoring sampling points;

[0069] S124: Let i = i + 1. If i is less than or equal to N, then execute S122 to S123. If i is greater than N, then let r = r + 1. If r is less than or equal to R, then let i = 1 and execute S122 to S123. If r is greater than R, then end the current process.

[0070] like Figure 4 As shown, the method for obtaining the set of pollutant concentration derivatives includes:

[0071] Obtain a set of pollutant concentrations for each pollutant; perform regression fitting on the pollutant concentration set using the matrix method to obtain the corresponding pollutant concentration equation, which is a quadratic polynomial equation; differentiate the pollutant concentration equation to obtain the derivative of the concentration equation; substitute the pollutant concentrations in the pollutant concentration set into the derivative of the concentration equation to construct the corresponding set of pollutant concentration derivatives. The specific implementation method is as follows:

[0072] S131: Let r be initially 1; the range of r is from 1 to R;

[0073] S132: Obtain the set of concentrations of the r-th pollutant;

[0074] S133: Use the matrix method to perform regression fitting on the pollutant concentration set to obtain the pollutant concentration equation C corresponding to the r-th pollutant concentration set. r (t)=α1×t 2 +α2×t+α3;C r (t) is the pollutant concentration equation corresponding to the r-th pollutant concentration set, t is the corresponding time point, and α1, α2 and α3 are the coefficients obtained by regression fitting.

[0075] S134: Differentiate the pollutant concentration equation to obtain the derivative of the concentration equation corresponding to the pollutant concentration equation;

[0076] S135: Substitute the pollutant concentrations in the pollutant concentration set into the derivatives of the concentration equation to form the pollutant concentration derivative set corresponding to the r-th monitoring sample;

[0077] S136: Let r = r + 1. If r is less than or equal to R, then execute S132 to S135; if r is greater than R, then end the current process.

[0078] Methods for using the matrix method to perform regression fitting on the pollutant concentration set to obtain the pollutant concentration equation include:

[0079] Construct a time point matrix from N time points, and construct a pollutant concentration matrix from the set of pollutant concentrations;

[0080] The time point matrix is ​​expressed as follows:

[0081]

[0082] The pollutant concentration matrix is ​​expressed as follows:

[0083]

[0084] Where X is the time point matrix, t n Let D be the nth time point; D is the pollutant concentration matrix, D n This represents the pollutant concentration at the nth time point in the pollutant concentration set.

[0085] Multiply the transpose of the time point matrix by the time point matrix to obtain the time point square matrix;

[0086] The method for obtaining the time point matrix is ​​as follows:

[0087]

[0088] Among them, X T X is a time-point matrix, X T Let X be the transpose of X;

[0089] It should be noted that the new matrix obtained by interchanging the rows and columns of a matrix is ​​called the transpose matrix; that is, the rows of the original matrix are converted into the columns of the transpose matrix, and the columns of the original matrix are converted into the rows of the transpose matrix. For example, the original matrix is... The transpose of the original matrix is

[0090] Calculate the inverse matrix of the time point square matrix, and label it as the inverse matrix of the square matrix;

[0091] The method for calculating the inverse matrix of the square matrix is ​​as follows:

[0092] Construct an augmented matrix from the time point square matrix and the identity matrix E. Perform row operations on the augmented matrix to obtain That is, the time-point square matrix on the left side of the augmented matrix becomes the identity matrix E, and the matrix on the right side of the augmented matrix (X) becomes the identity matrix E. T X) -1It is the inverse matrix corresponding to the time point square matrix.

[0093] It should be noted that the identity matrix is ​​a matrix where the values ​​on the main diagonal are 1s and all other elements are 0s. For example, a 3x3 identity matrix is... The augmented matrix method is a commonly used method in linear algebra for finding matrix inverses, and will not be elaborated on here.

[0094] The equation coefficient matrix is ​​calculated based on the inverse matrix of the square matrix, the transpose of the time point matrix, and the pollutant concentration matrix. The elements in the equation coefficient matrix are the corresponding coefficients in the pollutant concentration equation. The equation coefficient matrix has a dimension of 3×1.

[0095] The method for calculating the coefficient matrix of the equation is as follows:

[0096]

[0097] Where α is the coefficient matrix of the equation;

[0098] The presupposed quadratic polynomial equation is C(t)=β1×t 2 +β2×t+β3; Update β1 to the element in the first row of the equation coefficient matrix; Update β2 to the element in the second row of the equation coefficient matrix; Update β3 to the element in the third row of the equation coefficient matrix; That is, replace β1 in the quadratic polynomial equation with α1 in the equation coefficient matrix, replace β2 in the quadratic polynomial equation with α2 in the equation coefficient matrix, and replace β3 in the quadratic polynomial equation with α3 in the equation coefficient matrix to obtain the pollutant concentration equation;

[0099] For example, in a preferred embodiment of this application, there are four time points and corresponding pollutant concentrations for the four time points: the time points are 1, 2, 3, and 4; the pollutant concentration set ND = 2, 5, 10, and 17.

[0100] Construct a time point matrix X,

[0101] Construct the pollutant concentration matrix D.

[0102] Calculate the time point matrix X T X;

[0103]

[0104] Calculate the inverse matrix (X) T X) -1 ;

[0105] Calculate the coefficient matrix α of the equation;

[0106]

[0107]

[0108] In summary, the value of α1 is 1, the value of α2 is 0, and the value of α3 is 1, meaning the fitted quadratic equation is C(t) = t 2 +1.

[0109] It should be noted that the applicant found that pollutant concentrations are influenced by a complex interplay of factors, including pollution source emission intensity, soil physicochemical indicators, pollutant composition, and their migration and transformation characteristics, resulting in nonlinear changes in pollutant concentrations over time. To accurately describe and predict the dynamic trends of pollutant concentrations, and thus reflect the impact of pollutant accumulation on land ecology, this application employs nonlinear equations to model the time-varying process of pollutant concentrations. Nonlinear regression can more accurately characterize the complex features of pollutant concentration changes, improving the sensitivity and discriminative ability to detect changes in land pollution load.

[0110] Based on this, the derivative of the concentration equation plays a crucial role in the analysis of land ecological degradation risk. The derivative of the concentration equation reflects the rate and direction of change in pollutant concentration at different time points. When the derivative of the concentration equation is positive, it indicates that the pollutant concentration is increasing; under the condition of a positive derivative, the larger the value of the derivative, the faster the pollution load increases, and the greater the potential risk of ecological degradation. When the derivative of the concentration equation is negative, it indicates that the pollutant concentration is decreasing; under the condition of a negative derivative, the larger the absolute value of the derivative, the faster the rate of pollutant depletion, which is conducive to land ecological restoration.

[0111] In the absence of significant pollution input, pollutant concentrations typically exhibit slight fluctuations, with their derivatives fluctuating within a reasonable range and showing no sustained upward trend. However, when a land ecosystem experiences abnormal pollution input, the derivatives of the concentration equations often show a sustained increase above historical averages or a sudden surge, indicating a significant ecological degradation process in the affected area. Real-time monitoring of pollutant concentration derivatives can sensitively capture abnormal rates of change in land pollution loads. Combined with dynamic changes in soil physicochemical indicators, a comprehensive assessment of the land's ecological condition can be conducted, identifying ecological degradation levels and issuing early warning information. This allows for timely remediation and restoration measures to be implemented before irreversible damage to ecological functions occurs.

[0112] The second acquisition module is used to acquire soil physicochemical index data corresponding to R sampling points at N time points in the land ecological monitoring area; the soil physicochemical index data includes soil pH value, soil organic matter content and soil permeability.

[0113] Specifically, the methods for obtaining soil physicochemical indicators include: collecting soil samples at each sampling point at predetermined time points, and measuring soil pH, organic matter content, and permeability using laboratory analysis or portable on-site testing equipment. Soil pH can be measured using the potentiometry method or pH test paper; soil organic matter content can be quantitatively analyzed using the potassium dichromate oxidation capacity method or high-temperature combustion method; and soil permeability can be measured using the ring cutter method or a permeameter.

[0114] It should be further explained that the dynamic monitoring of soil physicochemical indicators has a significant correlation with pollutant concentration data in this application. On the one hand, changes in soil pH directly affect the mobility and availability of pollutants in the soil, thus reflecting the potential impact of pollution accumulation on the land's ecological environment. On the other hand, changes in organic matter content are closely related to the soil's self-purification capacity; high organic matter levels generally contribute to the fixation and degradation of pollutants, while a decrease in organic matter indicates an increased risk of ecological degradation. Furthermore, changes in soil permeability can reveal the degree of soil structural damage or blockage, providing important indications for vertical pollutant diffusion and groundwater pollution. This application, by simultaneously collecting data on soil physicochemical indicators and pollutant concentration changes, achieves a multi-dimensional joint analysis of the land's ecological status, enabling a more comprehensive and objective identification of ecological degradation trends and improving the accuracy and reliability of early warning systems.

[0115] The second processing module is used to construct a corresponding set of soil physicochemical indicators from the soil physicochemical index data, and to perform change analysis on the set of soil physicochemical indicators to obtain the set of physicochemical index changes for each soil physicochemical indicator.

[0116] Soil pH, organic matter content, and permeability are used to construct corresponding sets of pH, organic matter content, and permeability. Difference analysis is then performed on these sets to obtain sets of pH changes, organic matter changes, and permeability changes.

[0117] The methods for obtaining the soil physicochemical index sets corresponding to each soil physicochemical index include:

[0118] S101: Let r be initially 1, let i be initially 1, the value of r is from 1 to R; the value of i is from 1 to N;

[0119] S102: Obtain the soil pH, organic matter content, and permeability at the r-th sampling point at the i-th time point;

[0120] S103: Add the soil pH value to the pH value set corresponding to the r sampling points, add the organic matter content to the organic matter content set corresponding to the r sampling point, and add the permeability to the permeability set corresponding to the r sampling point.

[0121] S104: Let i = i + 1. If i is less than or equal to N, then execute S102 to S103. If i is greater than N, then let r = r + 1. If r is less than or equal to R, then let i = 1 and execute S102 to S103. If r is greater than R, then end the current process.

[0122] The methods for obtaining the set of changes in various soil physicochemical indicators include:

[0123] For R sampling points, the soil pH values ​​at adjacent time points are subtracted to obtain pH difference values, and these pH difference values ​​are added to the pH change set. Similarly, the soil organic matter content at adjacent time points is subtracted to obtain organic matter content difference values, and these organic matter content difference values ​​are added to the organic matter change set. The soil permeability at adjacent time points is subtracted to obtain permeability difference values, and these permeability difference values ​​are added to the permeability change set. The specific implementation method is as follows:

[0124] S111: Let r be initially 1, and let d be initially 2; the value of d ranges from 2 to N;

[0125] S112: Subtract the pH value at time d from the pH value at time d-1 in the pH value set corresponding to the r-th sampling point to obtain the pH difference value, and add the pH difference value to the pH change set; Subtract the organic matter content at time d from the organic matter content at time d-1 in the organic matter content set corresponding to the r-th sampling point to obtain the organic matter content difference value, and add the organic matter content difference value to the organic matter change set; Subtract the permeability at time d from the permeability at time d-1 in the permeability set corresponding to the r-th sampling point to obtain the permeability difference value, and add the permeability difference value to the permeability change set;

[0126] S113: Let d = d + 1. If d is less than or equal to N, then execute S112. If d is greater than N, then let r = r + 1. If r is less than or equal to R, then let d = 2 and execute S112. If r is greater than R, then end the current process.

[0127] It should be noted that the physicochemical index change set, by calculating the differences between soil physicochemical index data at each sampling point at consecutive time points, can intuitively reflect the dynamic change trend of soil physicochemical properties over time. Specifically, for example, the pH value change set can characterize the fluctuation of acidity and alkalinity; if there is a continuous significant decrease or increase, it indicates that the soil is affected by the input of external pollutants or a decline in its internal buffering capacity; the organic matter change set is used to monitor the accumulation or loss of soil organic matter; an abnormal decrease in organic matter means soil fertility degradation and a decline in microbial activity; the permeability change set can identify changes in soil physical structure, such as the impact of particle aggregation or pore blockage on water conduction capacity.

[0128] This application, by acquiring a set of changes in various soil physicochemical indicators, not only enables static assessment of soil conditions at a single point in time but also captures the dynamic evolution of physicochemical properties and cross-validates them with pollutant concentration trends. This effectively improves the early identification capability and warning accuracy of land ecological degradation, allowing the monitoring system to issue timely warnings before irreversible damage to soil ecological functions occurs, providing data support for formulating scientifically sound remediation strategies. Therefore, the set of changes in physicochemical indicators plays a crucial technical role in this invention for quantifying land ecological changes, supporting ecological status grading assessments, and assisting in remediation decision-making.

[0129] The ecological status diagnosis module assesses the land ecological status based on the set of pollutant concentration derivatives and the set of changes in physicochemical indicators, and obtains the degree of land ecological degradation.

[0130] like Figure 5 As shown, the method for obtaining the degree of land ecological degradation includes:

[0131] The set of pollutant concentration derivatives and the set of soil physicochemical indicators corresponding to R sampling points are respectively input into the land ecological degradation assessment model to obtain R corresponding land ecological degradation scores;

[0132] Preset land ecological degradation scoring threshold 1 and land ecological degradation scoring threshold 2; land ecological degradation scoring threshold 1 is less than land ecological degradation scoring threshold 2; land ecological degradation scoring threshold 1 represents an ecological degradation early warning threshold, and land ecological degradation scoring threshold 2 represents a severe ecological degradation threshold; the higher the land ecological degradation score, the more severe the land ecological degradation.

[0133] Based on R land ecological degradation scores, land ecological degradation score threshold one, and land ecological degradation score threshold two, a comprehensive assessment of the land ecological status is conducted to obtain the land ecological degradation level of the land ecological monitoring area, and the land ecological degradation level is used as the degree of land ecological degradation.

[0134] The training methods for the land ecological degradation assessment model include:

[0135] A land ecological degradation assessment dataset is pre-constructed, which includes land ecological degradation assessment data of group TH and the corresponding land ecological degradation scores of the land ecological degradation assessment data of group TH, where TH is a positive integer; the land ecological degradation assessment data includes a set of pollutant concentration derivatives and a set of soil physicochemical indicators;

[0136] The land ecological degradation assessment dataset was divided into a training set and a validation set. The training set was used for parameter learning of the equipment operation diagnosis model, while the validation set was used to monitor the generalization performance and overfitting degree of the equipment operation diagnosis model in real time. A deep neural network with a multilayer perceptron as its core was used as the equipment operation diagnosis model. The land ecological degradation assessment data was standardized and vectorized before being input into the deep neural network, which consisted of an input layer, hidden layers, and an output layer. Each hidden layer used a nonlinear activation function to extract features, and the output layer used a softmax activation function to obtain the probability distribution corresponding to each land ecological degradation score. Finally, the land ecological degradation score corresponding to the highest probability was taken as the prediction result of the equipment operation diagnosis model. During the training process, the cross-entropy loss function was used as the optimization objective, and a gradient descent-type optimization algorithm was used to update the network weights. An early stopping strategy was set: when the prediction accuracy on the validation set reached or exceeded a preset threshold, the equipment operation diagnosis model was determined to have converged and training was terminated.

[0137] The methods for obtaining the land ecological degradation level of the land ecological monitoring area include:

[0138] S200: Let r be initially 1, and the range of r is from 1 to R;

[0139] S201: Obtain the land ecological degradation score corresponding to the r-th sampling point;

[0140] If the land ecological degradation score is less than the land ecological degradation score threshold, then the land ecological degradation level of the land ecological degradation score is the low land ecological degradation level.

[0141] If the land ecological degradation score is less than the land ecological degradation score threshold two and greater than or equal to the land ecological degradation score threshold one, then the land ecological degradation level of the land ecological degradation score is the moderate land ecological degradation level.

[0142] If the land ecological degradation score is greater than or equal to the land ecological degradation score threshold two, then the land ecological degradation level of the land ecological degradation score is the severe land ecological degradation level.

[0143] S202: If r is less than or equal to R, then return to S201 for execution; if r is greater than R, then execute S203.

[0144] S203: Based on R land ecological degradation scores and their corresponding land ecological degradation levels, a comprehensive assessment is conducted to obtain the land ecological degradation level of the land ecological monitoring area.

[0145] The method for obtaining the land ecological degradation level of a land ecological monitoring area by comprehensively assessing R land ecological degradation scores and their corresponding land ecological degradation levels includes:

[0146] The number of sampling points corresponding to the low degradation level, moderate degradation level, and severe degradation level of land ecology were counted separately, and the proportion of each degradation level was calculated.

[0147] Determine whether the proportion of land ecological degradation levels exceeds a preset threshold for severe degradation.

[0148] If the judgment result is yes, then the land ecological degradation level of the land ecological monitoring area is defined as the severe land ecological degradation level;

[0149] If the judgment result is negative, a comprehensive land ecological degradation score is calculated based on R land ecological degradation scores. If the comprehensive land ecological degradation score is greater than the preset comprehensive land ecological degradation score threshold, the land ecological degradation level of the land ecological monitoring area is defined as a moderate land ecological degradation level. If the comprehensive land ecological degradation score is not greater than the preset comprehensive land ecological degradation score threshold, the land ecological degradation level of the land ecological monitoring area is defined as a low land ecological degradation level.

[0150] It should be noted that the severe degradation proportion threshold and the comprehensive land ecological degradation score threshold used in this application for comprehensively assessing the level of land ecological degradation can be set based on the current status of the regional ecological environment and historical monitoring data. The severe degradation proportion threshold is used to identify situations where there is a large area of ​​severe degradation within the monitoring area, and to prioritize triggering a high-level warning. For example, in an embodiment of this application, the severe degradation proportion threshold can be set to 30%, that is, when the proportion of sampling points with severe degradation is greater than 30%, it is determined to be a state of overall severe degradation.

[0151] The comprehensive land ecological degradation scoring threshold is used to further quantify the overall degradation level of a region when the severe degradation proportion threshold has not been triggered. The comprehensive land ecological degradation scoring threshold is set based on the historical distribution range of regional degradation scores and management standards. For example, when the standardized degradation score range is 0 to 100, the comprehensive land ecological degradation scoring threshold can be set to 50. That is, when the average land ecological degradation score of all sampling points is higher than 50, it is judged as a moderate land ecological degradation level; when the average land ecological degradation score of all sampling points is not higher than 50, it is judged as a low land ecological degradation level. For example, with R = 10 sampling points, if the land ecological degradation scores are 60, 55, 40, 45, 50, 48, 52, 46, 44, and 42, the comprehensive land ecological degradation score is 48.2, which is lower than the comprehensive land ecological degradation scoring threshold of 50, and is judged as a low land ecological degradation level.

[0152] The setting of the severe degradation proportion threshold and the comprehensive land ecological degradation scoring threshold is mainly based on the consideration of the comprehensive assessment of the spatial distribution characteristics and degree of ecological degradation in this application. On the one hand, the severe degradation proportion threshold can quickly identify and issue early warnings when significant degradation occurs in local areas, preventing further expansion of ecological risks. On the other hand, the comprehensive land ecological degradation scoring threshold can comprehensively reflect the overall degradation level of a region even when local areas have not reached the severe degradation proportion threshold, thereby improving the scientificity, rationality, and sensitivity of land ecological status classification. Furthermore, it can be flexibly adapted to different ecological scenarios, providing more accurate data support for ecological restoration and management.

[0153] The calculation method for the comprehensive score of land ecological degradation includes:

[0154]

[0155] Among them, ZHPF is the comprehensive score for land ecological degradation, and SL l SL represents the quantity corresponding to the low level of land ecological degradation. m SL represents the number of land ecological degradation levels of moderate severity. h THPF indicates the level of severe ecological degradation of land. g THPF represents the g-th land degradation score corresponding to a low level of land degradation. q THPF represents the q-th land ecological degradation score corresponding to the low level of land ecological degradation. p This represents the p-th land ecological degradation score corresponding to the severe land ecological degradation level. μ1, μ2, and μ3 are the corresponding weighting coefficients, and the sum of μ1, μ2, and μ3 is 1.

[0156] It should be noted that the calculation method for the comprehensive score of land ecological degradation described in this application is based on the distribution and number of sampling points at different degradation levels and the corresponding scoring results, and adopts a weighted summation method for evaluation. This method comprehensively considers three factors: first, the quantitative weights of different levels of land ecological degradation (low, moderate, and severe); second, the degradation score value corresponding to each degradation level; and third, the relative contribution of different degradation levels to the overall level of ecological degradation.

[0157] Specifically, the calculation formula for the comprehensive score of land ecological degradation involves counting the number of sampling points corresponding to the low, moderate, and severe land ecological degradation levels, denoted as SL. l SL m and SL h The land ecological degradation scores of each sampling point were grouped and accumulated, and then different levels of influence weights were assigned through weight coefficients μ1, μ2 and μ3 to obtain the comprehensive land ecological degradation score.

[0158] The calculation method adopted in this application has significant rationality and practicality. Specifically, on the one hand, there are significant differences in the ecological risks and management priorities corresponding to low, moderate, and severe degradation levels. The introduction of weighting coefficients μ1, μ2, and μ3 allows for flexible setting of the weight contribution of each degradation level in the comprehensive land ecological degradation score according to actual conditions, improving the model's adaptability and scientific rigor. On the other hand, by weighted summing of the number of sampling points and the land ecological degradation score, the distortion effect of a single extreme value on the overall degradation assessment can be avoided, while fully reflecting the overall characteristics of the distribution of each level within the monitoring area, achieving an objective, quantitative, and comparable comprehensive evaluation of the land ecological degradation level. This provides an important basis for subsequent tiered decision-making on ecological restoration measures.

[0159] The ecological degradation response module is used to adaptively generate early warning information on land ecological degradation and land ecological degradation restoration plans based on the degree of land ecological degradation.

[0160] like Figure 4 As shown, the methods for adaptively generating land ecological degradation early warning information and land ecological degradation restoration plans based on the degree of land ecological degradation include:

[0161] When the degree of land ecological degradation is at the low level, a low degradation warning message is generated. No immediate restoration measures are required; only regular monitoring is recommended.

[0162] When the degree of land ecological degradation is moderate, an early warning message is generated that includes a moderate degradation risk warning and a moderate ecological degradation intervention suggestion. The moderate ecological degradation intervention suggestion retrieves matching degradation restoration measures from a preset degradation restoration scheme library. The moderate ecological degradation intervention suggestion includes, for example, applying organic amendments, adjusting farming methods, increasing soil cover, or optimizing water management, to restore soil physicochemical indicators.

[0163] When the degree of land ecological degradation reaches the level of severe land ecological degradation, a severe degradation early warning information is generated, and severe degradation emergency intervention measures are automatically implemented. The severe degradation emergency intervention measures include controlling irrigation equipment to flush or dilute the soil to reduce the degree of land ecological degradation, controlling spraying equipment to apply soil conditioners to the soil, and closing sewage channels in the land ecological monitoring area to prevent the spread of land ecological degradation. The soil conditioners are, for example, lime, biochar, or organic fertilizer, to neutralize acidity or alkalinity or increase organic matter content.

[0164] It should be noted that this application achieves graded response and precise intervention for different degradation scenarios by adaptively generating land ecological degradation early warning information and matching restoration plans based on the degree of land ecological degradation. Specifically, by generating graded early warning information according to the degradation level, the state of land ecological degradation can be promptly and clearly communicated to regulatory personnel and management entities, enabling them to grasp the dynamics of land quality in the early stages of ecological degradation and improving the transparency and operability of monitoring results.

[0165] When the degree of land ecological degradation is at the low level, only low degradation warning information is generated and regular monitoring is recommended. This helps to rationally allocate regulatory resources and avoid waste of management costs caused by excessive intervention.

[0166] When the degree of land ecological degradation is at the moderate level, the system automatically generates a moderate degradation risk warning and matching intervention suggestions. When the ecological degradation is still in a reversible stage, measures such as applying organic amendments, optimizing cultivation and water management can be used to specifically restore soil physicochemical indicators, delay or reverse the trend of land ecological degradation, and reduce the probability of the spread of land ecological degradation areas.

[0167] When the degree of land ecological degradation reaches the level of severe land ecological degradation, an early warning message of severe degradation is automatically generated, and emergency intervention measures such as flushing and dilution, application of amendments, and closure of sewage channels are immediately implemented. This can reduce the soil pollution load in the first instance, block the migration and diffusion paths of pollutants, prevent the further expansion of the land ecological degradation range, and buy time for subsequent restoration measures.

[0168] This application achieves a closed-loop linkage between land ecological monitoring, hierarchical assessment, intervention decision-making, and emergency restoration through a tiered early warning and adaptive restoration strategy. This not only improves the timeliness and scientific nature of land ecological degradation governance, but also significantly enhances the system's proactive response capability to sudden or cumulative soil ecological degradation. It has high application and promotion value and ecological protection significance.

[0169] Example 2

[0170] Please see Figure 2 As shown, this embodiment provides a land ecological status monitoring system, which also includes:

[0171] The scoring threshold setting module dynamically sets two scoring thresholds for land ecological degradation based on the set of pollutant concentration derivatives corresponding to R sampling points and the set of soil physicochemical indicators.

[0172] The methods for dynamically setting land ecological degradation scoring threshold one and land ecological degradation scoring threshold two based on the set of pollutant concentration derivatives corresponding to R sampling points and the set of soil physicochemical indicators include:

[0173] The set of pollutant concentration derivatives and the set of soil physicochemical indicators corresponding to R sampling points are input into the scoring threshold setting model to obtain a dynamically set set of land ecological degradation scoring thresholds; the set of land ecological degradation scoring thresholds includes land ecological degradation scoring threshold one and land ecological degradation scoring threshold two.

[0174] The training method for the scoring threshold setting model includes:

[0175] A scoring threshold setting dataset is pre-collected, which includes scoring threshold setting data and a set of land ecological degradation scoring thresholds corresponding to the scoring threshold setting data; the scoring threshold setting dataset is divided into a training set and a test set, the scoring threshold setting data in the training set is used as the input of the scoring threshold setting model, and the set of land ecological degradation scoring thresholds in the training set is used as the output of the scoring threshold setting model;

[0176] During the training of the scoring threshold setting model, minimizing the cross-entropy loss function is used as the optimization objective. An early stopping strategy is used to monitor the performance on the validation set. By continuously adjusting the network parameters, training stops when the prediction accuracy on the test set reaches the expected accuracy. The scoring threshold setting model is a gradient boosting tree model.

[0177] It should be noted that this application, through a scoring threshold setting module, dynamically sets two land ecological degradation scoring thresholds based on the set of pollutant concentration derivatives corresponding to R sampling points and the set of soil physicochemical indicators. This has significant technical value and application implications. Specifically, traditional fixed threshold assessment methods typically set thresholds based on prior experience or single historical data, which makes it difficult to accurately reflect the ecological degradation distribution characteristics of the monitoring area under different times and pollution scenarios. This can easily lead to insufficient threshold adaptability, low sensitivity, or the risk of misjudgment.

[0178] This application inputs the set of pollutant concentration derivatives corresponding to R sampling points and the set of soil physicochemical indicators into the scoring threshold setting model, and combines multi-dimensional data for analysis and calculation. Based on the current ecological environment status, pollution load level and indicator fluctuation characteristics, it can automatically generate the set of land ecological degradation scoring thresholds that best matches the current monitoring scenario, thereby effectively improving the matching degree between the threshold and the actual degradation risk.

[0179] The implementation of the method of dynamically setting the first and second thresholds for land ecological degradation scoring can achieve dynamic adaptation of land ecological degradation classification. On the one hand, it enhances the system's sensitivity to nonlinear fluctuations in pollutant concentrations and sudden changes in soil physicochemical indicators, improving the accuracy and timeliness of degradation level determination. On the other hand, it helps to reasonably distinguish between low degradation and moderate degradation, and moderate degradation and severe degradation, by dynamically adjusting the thresholds when ecological degradation is in a critical state, effectively reducing false alarms or missed alarms caused by fixed thresholds.

[0180] Through a dynamic threshold setting mechanism, this application enables more refined and scenario-based degradation level assessment, providing scientific and accurate data support for subsequent early warning response, governance measure classification, and resource allocation, and significantly enhancing the intelligence level and adaptability of the land ecological degradation monitoring system.

[0181] Example 3

[0182] Please see Figure 3 As shown, this embodiment provides a method for monitoring land ecological conditions, including:

[0183] Acquire pollutant concentration data at N time points for R sampling points in a land ecological monitoring area;

[0184] The pollutant concentrations of each pollutant in the pollutant concentration data are used to form a corresponding pollutant concentration set. The pollutant concentration set is fitted and analyzed to obtain a set of pollutant concentration equations. Then, derivative analysis is performed based on the pollutant concentration equation set to obtain a set of pollutant concentration derivatives for each pollutant.

[0185] Obtain soil physicochemical index data for R sampling points at N time points in a land ecological monitoring area;

[0186] The soil physicochemical indexes in the soil physicochemical index data are used to form a corresponding set of soil physicochemical indexes, and the change analysis of the set of soil physicochemical indexes is carried out to obtain the set of physicochemical index changes of each soil physicochemical index.

[0187] Land ecological status is assessed based on the set of pollutant concentration derivatives and the set of changes in physicochemical indicators to obtain the degree of land ecological degradation.

[0188] Based on the degree of land ecological degradation, early warning information on land ecological degradation and land ecological degradation restoration plans are generated adaptively.

[0189] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0190] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for monitoring land ecological conditions, characterized in that, include: Acquire pollutant concentration data at N time points for R sampling points in a land ecological monitoring area; The pollutant concentrations of each pollutant in the pollutant concentration data are used to form a corresponding pollutant concentration set. The pollutant concentration set is fitted and analyzed to obtain a set of pollutant concentration equations. Then, derivative analysis is performed based on the pollutant concentration equation set to obtain a set of pollutant concentration derivatives for each pollutant. Obtain soil physicochemical index data for R sampling points at N time points in a land ecological monitoring area; The soil physicochemical indexes in the soil physicochemical index data are used to form a corresponding set of soil physicochemical indexes, and the change analysis of the set of soil physicochemical indexes is carried out to obtain the set of physicochemical index changes of each soil physicochemical index. Land ecological status is assessed based on the set of pollutant concentration derivatives and the set of changes in physicochemical indicators to obtain the degree of land ecological degradation. Based on the degree of land ecological degradation, early warning information on land ecological degradation and land ecological degradation restoration plans are generated adaptively.

2. The land ecological status monitoring method according to claim 1, characterized in that, Methods for adaptively generating land ecological degradation early warning information and land ecological degradation restoration plans based on the degree of land ecological degradation include: When the degree of land ecological degradation is at the low level, a low degradation warning message is generated. No immediate restoration measures are required; only regular monitoring is recommended. When the degree of land ecological degradation is moderate, an early warning message is generated that includes a moderate degradation risk warning and a moderate ecological degradation intervention suggestion. The moderate ecological degradation intervention suggestion retrieves matching degradation restoration measures from a preset degradation restoration scheme library. When the degree of land ecological degradation reaches the level of severe land ecological degradation, a severe degradation early warning information is generated, and severe degradation emergency intervention measures are automatically implemented. The severe degradation emergency intervention measures include controlling irrigation equipment to flush or dilute the soil to reduce the degree of land ecological degradation, controlling spraying equipment to apply soil conditioners to the soil, and closing sewage channels in the land ecological monitoring area.

3. The land ecological status monitoring method according to claim 1, characterized in that, The methods for obtaining the degree of land ecological degradation include: The set of pollutant concentration derivatives and the set of soil physicochemical indicators corresponding to R sampling points are respectively input into the land ecological degradation assessment model to obtain R corresponding land ecological degradation scores; Preset land ecological degradation scoring threshold one and land ecological degradation scoring threshold two; land ecological degradation scoring threshold one is less than land ecological degradation scoring threshold two; Based on R land ecological degradation scores, land ecological degradation score threshold one, and land ecological degradation score threshold two, a comprehensive assessment of the land ecological status is conducted to obtain the land ecological degradation level of the land ecological monitoring area, and the land ecological degradation level is used as the degree of land ecological degradation.

4. The land ecological status monitoring method according to claim 3, characterized in that, The methods for obtaining the land ecological degradation level of the land ecological monitoring area include: Obtain land ecological degradation scores for R sampling points; compare each land ecological degradation score with a preset land ecological degradation score threshold 1 and a preset land ecological degradation score threshold 2. If the land ecological degradation score is less than the first threshold for land ecological degradation, it is determined to be at the low level of land ecological degradation; if the land ecological degradation score is greater than or equal to the first threshold for land ecological degradation but less than the second threshold for land ecological degradation, it is determined to be at the moderate level of land ecological degradation; if the land ecological degradation score is greater than or equal to the second threshold for land ecological degradation, it is determined to be at the severe level of land ecological degradation. A comprehensive assessment is conducted based on R land ecological degradation scores and their corresponding land ecological degradation levels to obtain the land ecological degradation level of the land ecological monitoring area.

5. The land ecological status monitoring method according to claim 4, characterized in that, The method for obtaining the land ecological degradation level of a land ecological monitoring area by comprehensively assessing R land ecological degradation scores and their corresponding land ecological degradation levels includes: The number of sampling points corresponding to the low degradation level, moderate degradation level, and severe degradation level of land ecology were counted separately, and the proportion of each degradation level was calculated. Determine whether the proportion of land ecological degradation levels exceeds a preset threshold for severe degradation. If the judgment result is yes, then the land ecological degradation level of the land ecological monitoring area is defined as the severe land ecological degradation level; If the judgment result is negative, a comprehensive land ecological degradation score is calculated based on R land ecological degradation scores. If the comprehensive land ecological degradation score is greater than the preset comprehensive land ecological degradation score threshold, the land ecological degradation level of the land ecological monitoring area is defined as a moderate land ecological degradation level. If the comprehensive land ecological degradation score is not greater than the preset comprehensive land ecological degradation score threshold, the land ecological degradation level of the land ecological monitoring area is defined as a low land ecological degradation level.

6. The land ecological status monitoring method according to claim 1, characterized in that, The method for obtaining the set of pollutant concentration derivatives includes: Obtain each pollutant concentration set; use the matrix method to perform regression fitting on the pollutant concentration set to obtain the corresponding pollutant concentration equation, which is a quadratic polynomial equation; differentiate the pollutant concentration equation to obtain the concentration equation derivative corresponding to the pollutant concentration equation; substitute the pollutant concentrations in the pollutant concentration set into the concentration equation derivative to form the corresponding pollutant concentration derivative set.

7. A method for monitoring land ecological status according to claim 6, characterized in that, Methods for using matrix methods to perform regression fitting on a set of pollutant concentrations to obtain the corresponding pollutant concentration equations include: Construct a time point matrix from N time points, and construct a pollutant concentration matrix from the set of pollutant concentrations; Multiply the transpose of the time point matrix by the time point matrix to obtain the time point square matrix; Calculate the inverse matrix of the time point square matrix, and label it as the inverse matrix of the square matrix; The equation coefficient matrix is ​​calculated based on the inverse matrix of the square matrix, the transpose of the time point matrix, and the pollutant concentration matrix; the equation coefficient matrix has a dimension of 3×1. Initialize the quadratic polynomial equation, take the first row of the equation coefficient matrix as the quadratic term coefficient, take the second row of the equation coefficient matrix as the linear term coefficient, and take the third row of the equation coefficient matrix as the constant term, to obtain the pollutant concentration equation.

8. The method for monitoring land ecological status according to claim 1, characterized in that, The methods for obtaining the set of changes in various soil physicochemical indicators include: For R sampling points, the soil pH values ​​at adjacent time points are subtracted to obtain pH difference values, and these pH difference values ​​are added to the pH change set; the soil organic matter content at adjacent time points is subtracted to obtain organic matter content difference values, and these organic matter content difference values ​​are added to the organic matter change set; the soil permeability at adjacent time points is subtracted to obtain permeability difference values, and these permeability difference values ​​are added to the permeability change set.

9. A method for monitoring land ecological status according to claim 3, characterized in that, The training methods for the land ecological degradation assessment model include: A land ecological degradation assessment dataset containing a set of pollutant concentration derivatives and a set of soil physicochemical indicators, along with corresponding land ecological degradation scores, was constructed. The land ecological degradation assessment dataset was divided into a training set and a validation set. A deep neural network with a multilayer perceptron as its core was used to train the model by inputting the standardized data. The model consists of an input layer, hidden layers, and a softmax output layer. The model training used the cross-entropy loss function as the optimization objective, updated the weights using the gradient descent algorithm, and monitored the validation set performance through an early stopping strategy. When the prediction accuracy reached a preset threshold, convergence was determined and training was terminated.

10. A land ecological status monitoring system, implementing the land ecological status monitoring method according to any one of claims 1-9, characterized in that, include: The first data acquisition module is used to acquire pollutant concentration data at N time points corresponding to R sampling points in the land ecological monitoring area. The first processing module is used to construct a corresponding pollutant concentration set from the pollutant concentration data of each pollutant, perform fitting analysis on the pollutant concentration set to obtain a pollutant concentration equation set, and perform derivative analysis based on the pollutant concentration equation set to obtain a pollutant concentration derivative set corresponding to each pollutant. The second data acquisition module is used to acquire soil physicochemical index data corresponding to R sampling points at N time points in the land ecological monitoring area; the soil physicochemical index data includes soil pH value, soil organic matter content and soil permeability; The second processing module is used to construct a corresponding set of soil physicochemical indicators from the soil physicochemical index data, and to perform change analysis on the set of soil physicochemical indicators to obtain the set of physicochemical index changes for each soil physicochemical indicator. The ecological status diagnosis module assesses the land ecological status based on the set of pollutant concentration derivatives and the set of changes in physicochemical indicators, and obtains the degree of land ecological degradation. The ecological degradation response module is used to adaptively generate early warning information on land ecological degradation and land ecological degradation restoration plans based on the degree of land ecological degradation.

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