Remote sensing monitoring-based cultivated land ecosystem service evaluation method

Abstract

The invention relates to the technical field of ecosystem service assessment, in particular to a remote sensing monitoring-based cultivated land ecosystem service assessment method, which comprises the following steps of: acquiring multi-dimensional cultivated land data of a to-be-assessed region by utilizing a remote sensing technology, and performing data dimension reduction processing on the acquired data to obtain a to-be-assessed region; meanwhile, sparsity constraint is introduced to reduce interference of redundant features in a data set; cultivated land ecological service evaluation is realized according to the collected data; intelligent optimization is carried out based on the collaborative relationship between the data; according to the method, the multi-dimensional cultivated land data is collected and the sparsity constraint is combined to carry out dimension reduction processing, so that a high-quality data basis is provided for subsequent ecological service evaluation; on the basis of collaborative relationship analysis between data, the adaptability of service evaluation of the cultivated land ecosystem is improved by utilizing a collaborative effect coefficient and a weight dynamic allocation technology; in combination with a performance function and a weight optimization method, quantitative comprehensive evaluation of services such as soil conservation, water conservation and carbon sequestration is realized, and scientificity and universality of an evaluation model are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of ecosystem service assessment, and in particular to a method for assessing cultivated land ecosystem services based on remote sensing monitoring. Background Art

[0002] Cultivated land ecosystem service assessment refers to the quantification, analysis and evaluation of the ability of cultivated land to provide ecosystem services through scientific methods; however, at present, the assessment of cultivated land ecosystem services through remote sensing technology faces the following difficulties:

[0003] Remote sensing data come from a variety of sources, with different spatial resolutions, temporal resolutions, band settings, and observation angles, making it difficult to directly and uniformly use the data for ecosystem service assessment;

[0004] The assessment of ecosystem services (such as soil conservation, water conservation, carbon sequestration, habitat maintenance, and wind and sand fixation) requires high-quality input data. However, there are differences between the parameters in remote sensing images (such as NDVI, land cover type, etc.) and the actual situation, which affects the accuracy and regional applicability of the calculation results. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] To solve the above technical problems, the present invention provides the following technical solution: a method for evaluating cultivated land ecosystem services based on remote sensing monitoring, comprising the following steps:

[0007] Use remote sensing technology to obtain multi-dimensional cultivated land data in the area to be evaluated, and perform data dimensionality reduction on the collected data. At the same time, introduce sparsity constraints to reduce the interference of redundant features in the data set.

[0008] The ecological service evaluation of cultivated land is realized based on the collected data, specifically:

[0009] Based on the spatial analysis and quantitative estimation of the cultivated land ecological service system, the cultivated land ecological service evaluation model is built, and the cultivated land data is used as the input data of the model. According to the output results of the model, the cultivated land ecological service evaluation is realized, which also includes:

[0010] When comprehensively evaluating the ecological services of cultivated land in different regions, formulate the distribution rules of ecological service weight coefficients to achieve dynamic distribution of weight coefficients;

[0011] Intelligent optimization is performed based on the collaborative relationship between data, specifically:

[0012] Based on the data correlation analysis between ecological services, the synergy coefficient between the two service functions is determined, and the cultivated land ecological service evaluation model is intelligently optimized according to the determined synergy coefficient, and whether the optimization is completed is judged based on the service deviation.

[0013] As a preferred solution of the method for evaluating cultivated land ecosystem services based on remote sensing monitoring described in the present invention, the construction of the cultivated land ecosystem service evaluation model is specifically as follows:

[0014] The area to be evaluated is divided into a two-dimensional grid network with a grid unit of g. Each grid unit has different ecological attributes, including vegetation index, soil moisture and slope data. Then,

[0015] G = {g i,j |i=1,2,3,...,M; j=1,2,3,...,N}

[0016] Wherein, G represents a two-dimensional grid network divided by the area to be evaluated, M and N represent the rows and columns corresponding to the grid network, respectively, and i and j represent the serial number indexes of the rows and columns of the grid cells in the grid network;

[0017] According to different cultivated land ecological services, a function f is set accordingly. k (g i,j ), and calculate the service value of each service in the grid cell according to the set functional function, then,

[0018]

[0019] Among them, f k (g i,j ) represents the functional function corresponding to the kth ecological service, M and N represent the rows and columns corresponding to the grid network, i and j represent the grid units in the grid network, S k represents the service value of the kth ecological service in the grid cell;

[0020] According to the needs of the area to be assessed, the corresponding weight coefficient w is assigned to different ecological services. k , and calculate the comprehensive service value, then we have,

[0021]

[0022] Among them, S k represents the service value of the kth ecological service in the grid cell, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k represents the weight coefficient of different ecological service allocations, S total Represents the calculated comprehensive service value.

[0023] As a preferred solution of the method for evaluating cultivated land ecosystem services based on remote sensing monitoring described in the present invention, the allocation rules for formulating the ecological service weight coefficient are as follows:

[0024] Assign an initial priority weight p to each ecological service based on the needs of the area to be assessed k , the value range is [0,1], and satisfies the formula:

[0025]

[0026] Among them, p k represents the initial priority weight of the kth ecological service, and K represents the upper limit of the number of ecological service types in the area to be evaluated;

[0027] According to the set initial priority weight, calculate the corresponding service value S of each ecological service in the grid cell k , and normalized, we have,

[0028]

[0029] Among them, S i,k represents the kth service value corresponding to the i-th grid cell, R i,k represents the normalized value, S k represents the corresponding service value of the kth ecological service in the grid cell, max and min represent the maximum value function and the minimum value function respectively;

[0030] Based on the normalized value, the entropy value corresponding to each service is calculated, and then,

[0031]

[0032] Among them, R i,k represents the normalized value, g M,N Represents the total number of grid cells, M represents the upper limit of the grid cell sequence number, H k Indicates the entropy value corresponding to the kth service;

[0033] According to the entropy value corresponding to the ecological service, the weight coefficient of the corresponding service is adjusted, and then,

[0034]

[0035] Among them, H k represents the entropy value corresponding to the kth service, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k Indicates the weight corresponding to the k-th service.

[0036] As a preferred solution of the method for evaluating cultivated land ecosystem services based on remote sensing monitoring of the present invention, the evaluation of cultivated land ecosystem services is specifically implemented as follows:

[0037] Set the comprehensive service value standard threshold S T , according to the comprehensive service value S total The comparison results between the comprehensive service standard threshold and the cultivated land ecosystem service assessment show that:

[0038] If the comparison result satisfies the formula S total ≥S T , indicating that the cultivated land ecosystem service corresponding to the current area is qualified;

[0039] If the comparison result satisfies the formula S total <S T , indicating that the corresponding cultivated land ecosystem service in the current area is unqualified.

[0040] As a preferred solution of the method for evaluating cultivated land ecosystem services based on remote sensing monitoring described in the present invention, the data correlation analysis between the ecological services is as follows:

[0041] Based on the data correlation analysis at the grid level, the types of synergies between services are determined as follows:

[0042]

[0043] Among them, cov(S k ,S m ) represents the covariance data between the k-th service and the m-th service, denote the standard deviation of the kth service and the mth service, ρ k,m It represents the correlation coefficient between the kth service and the mth service, which is used to determine the type of synergy between service functions. Specifically:

[0044] If the calculated correlation coefficient satisfies the formula ρ k,m >0, indicating that the synergy type between the two service functions is positive synergy;

[0045] If the calculated correlation coefficient satisfies the formula ρ k,m <0, indicating that the synergy type between the two service functions is positive or negative synergy;

[0046] If the calculated correlation coefficient satisfies the formula ρ k,m =0, indicating that the synergy type between the two service functions is no synergy.

[0047] As a preferred solution of the method for evaluating cultivated land ecosystem services based on remote sensing monitoring of the present invention, the synergy effect coefficient between the two service functions is determined as follows:

[0048] C k,m =ρ k,m ·(1+α k,m )

[0049] Among them, ρ k,m represents the correlation coefficient between the kth service and the mth service, C k,m represents the calculated synergy coefficient between the two services, α k,m It represents the correction coefficient between services, which is determined by the type of synergy between services, specifically:

[0050] If the synergy type between the two services is positive synergy, the correction coefficient value satisfies the formula α k,m >0;

[0051] If the synergy type between the two services is negative synergy, the correction coefficient value satisfies the formula α k,m <0;

[0052] If the synergy type between the two services is no synergy, the correction coefficient value satisfies the formula α k,m =0.

[0053] As a preferred solution of the method for evaluating cultivated land ecosystem services based on remote sensing monitoring described in the present invention, the intelligent optimization of the cultivated land ecosystem service evaluation model is specifically as follows:

[0054] Construct the weight coefficient target optimization function, then we have,

[0055]

[0056] And set constraints to constrain the function, specifically:

[0057] w k >0

[0058]

[0059] Among them, S k represents the service value of the kth ecological service in the grid cell, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k represents the weight coefficient of the kth ecological service allocation, w m represents the weight coefficient of the mth ecological service allocation, C k,m represents the calculated synergy coefficient between the two services, f(w k) represents the weight coefficient objective optimization function, which is used to maximize the function by adjusting the synergy effect coefficients between services to achieve intelligent optimization of the cultivated land ecological service evaluation model.

[0060] As a preferred solution of the method for evaluating cultivated land ecosystem services based on remote sensing monitoring described in the present invention, the determination of whether the optimization based on service deviation is completed is specifically as follows:

[0061] The weight coefficient w when the input function is maximized k , and calculate the comprehensive service value S under the current weight coefficient t ' otal And the service value S of the kth ecological service in the grid cell k ′;

[0062] Collect the actual value S of the comprehensive service obtained during the field survey actual ;

[0063] Calculate the combined deviation between the two and the deviation of a single service, then we have,

[0064] D=S t ' otal -S actual

[0065] ΔS k =S k ′-S k

[0066] Among them, S t ' otal represents the comprehensive service value when the objective function is maximized, S actual represents the actual value of the comprehensive service obtained in the field survey, S k ′ represents the service value of the kth ecological service in the grid cell when the objective function is maximized, S k represents the service value of the kth ecological service in the grid cell, D represents the comprehensive deviation of the calculation, ΔS k represents the deviation of the calculated single service;

[0067] Set the comprehensive deviation threshold D T And the single service deviation threshold ΔS k,T Determine whether the set weight coefficient needs to be adjusted dynamically, specifically:

[0068] If the calculated comprehensive deviation and the single service deviation are compared with the set threshold, the formula D≥D T And ΔS k ≥ΔS k,T , indicating that the calculated deviation exceeds the deviation threshold, and the weight distribution needs to be dynamically adjusted, specifically:

[0069] Dynamically adjust the weight distribution according to the calculated deviation, then we have,

[0070] Dynamically adjust the initial priority weight based on the deviation of a single service, then we have:

[0071]

[0072] Dynamically adjust the synergy coefficient based on the comprehensive deviation, then we have:

[0073]

[0074] Among them, p k represents the initial priority weight of the kth ecological service, represents the adjusted initial priority weight of the kth ecological service, ΔS k represents the deviation of the calculated single service, C k,m represents the synergy coefficient between the two services, represents the adjusted synergy coefficient between the two services, and D represents the calculated comprehensive deviation;

[0075] Recalculate the comprehensive service value S for the adjusted initial priority weight and synergy coefficient. t ' otal ;

[0076] And calculate the new comprehensive deviation D′ and the single service deviation ΔS k ′;

[0077] If the newly calculated comprehensive deviation and single service deviation satisfy the formula D′<D T And ΔS k ′<ΔS k,T , it means that the calculated deviation does not exceed the deviation threshold, the dynamic adjustment of the weight coefficient is stopped, and the intelligent optimization of the cultivated land ecological service evaluation model is completed.

[0078] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a method for evaluating cultivated land ecosystem services based on remote sensing monitoring when executing the computer program.

[0079] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for evaluating cultivated land ecosystem services based on remote sensing monitoring.

[0080] Beneficial effects of the present invention:

[0081] The present invention collects multi-dimensional cultivated land data through remote sensing technology and performs dimensionality reduction processing in combination with sparsity constraints, which can reduce redundant feature interference and provide a high-quality data basis for subsequent ecological service evaluation;

[0082] Based on the analysis of the synergistic relationship between data, the synergistic effect coefficient and weight dynamic allocation technology are used to significantly improve the intelligence and adaptability of the cultivated land ecosystem service assessment;

[0083] Combine functional functions and weight optimization methods to achieve quantitative comprehensive evaluation of soil conservation, water conservation, carbon sequestration and other services, and enhance the scientificity and universality of the evaluation model;

[0084] By comparing field monitoring feedback with model output results, bias correction and parameter optimization are performed to ensure that the model's evaluation results are closer to actual needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0086] Figure 1 It is a schematic diagram of the overall method steps of the cultivated land ecosystem service assessment method based on remote sensing monitoring of the present invention. DETAILED DESCRIPTION

[0087] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0088] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0089] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0090] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0091] Meanwhile, in the description of the present invention, it should be noted that the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0092] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0093] Example 1

[0094] Reference Figure 1 , as an embodiment of the present invention, provides a method for evaluating cultivated land ecosystem services based on remote sensing monitoring, comprising the following steps:

[0095] S1: Remote sensing data acquisition and feature processing.

[0096] Specifically, the remote sensing data collection and feature processing is to use satellite remote sensing technology to obtain multi-dimensional cultivated land data of the area to be detected, and to process the collected multi-dimensional cultivated land data, so as to provide an accurate data basis for the subsequent cultivated land ecological service evaluation, which is specifically implemented as follows:

[0097] Satellite remote sensing technology is used to collect multidimensional cultivated land data of the area to be detected, including surface cover type data, vegetation index data and soil moisture data. The surface cover type data is based on the spectral reflectance characteristics of surface objects, and the spectral characteristic values ​​of different objects in different bands are extracted. The extracted spectral characteristic values ​​are combined with the spatial distribution, and each pixel is classified and labeled to generate a surface cover type distribution map; and the collected multidimensional cultivated land data is constructed into a multidimensional cultivated land data set X to provide a data basis for subsequent data processing.

[0098] Furthermore, the data processing of the collected multidimensional cultivated land data is to reduce the dimension of the constructed multidimensional cultivated land data set, and at the same time, introduce sparsity constraints to ensure that the features after the data dimension reduction can reduce the interference of redundant features while maintaining key information. The specific implementation is as follows:

[0099] Based on the constructed multidimensional cultivated land data set, it is divided into n sample sets, and the corresponding covariance matrix is ​​constructed based on the divided sample sets, then,

[0100]

[0101] Among them, X i represents the i-th sample of the division, μ represents the mean of the multidimensional cultivated land data set, n represents the upper limit of the number of divided samples, i represents the divided sample index, T represents the transposed matrix, and C represents the calculated covariance matrix;

[0102] By reducing the dimensionality of the multidimensional cultivated land data set and reconstructing it, we have:

[0103] According to the calculated covariance matrix, the eigenvalue decomposition of the multidimensional cultivated land data set is performed, and then,

[0104] C=Q∧Q T

[0105] Among them, C represents the calculated covariance matrix, T represents the transposed matrix, and Q represents the eigenvector matrix, which is composed of multiple eigenvectors;

[0106] Projecting the original multidimensional farmland data set X into the dimensionality reduction space, we have:

[0107] Y=X·W

[0108] Among them, Y represents the multidimensional cultivated land data set after dimension reduction, and W represents the projection matrix;

[0109] Introducing sparsity constraints to ensure that the data after dimensionality reduction retains the relevant features of cultivated land ecological service evaluation, we have:

[0110]

[0111] in, Represents the reconstruction error, and the sparsity constraint on data reconstruction is achieved by minimizing the error. ||W||1 represents the sparsity regularization term, and L represents the introduced sparsity constraint, which is used to ensure that the relevant features of cultivated land ecological service evaluation are retained in the data after dimensionality reduction.

[0112] It should be noted that by reducing the dimensionality of the collected data and reconstructing it and introducing sparsity constraints, it is possible to achieve dimensionality reduction while ensuring that the relevant characteristics of the subsequent cultivated land ecological service assessment are retained, thereby enhancing the reliability of the subsequent cultivated land ecological service assessment.

[0113] S2: Implement farmland ecological service assessment based on the collected data.

[0114] Specifically, the method of implementing the cultivated land ecological service evaluation based on the collected data is to build a cultivated land ecological service evaluation model, use the collected cultivated land data as the input data of the model, and implement the cultivated land ecological service evaluation based on the output results of the model.

[0115] Furthermore, the farmland ecological service assessment model is based on the spatial analysis and quantitative estimation of the farmland ecological service system to evaluate the comprehensive assessment capabilities of different regions in terms of soil conservation, water conservation, carbon fixation, habitat maintenance, and wind and sand fixation. The specific construction is as follows:

[0116] For the area to be evaluated, the area to be evaluated is divided into a two-dimensional grid network, the grid unit is g, and each grid unit has different ecological attributes, including vegetation index, soil moisture and slope data. The ecological attributes are diversified, which are not listed one by one in this embodiment, and there are,

[0117] G = {g i,j |i=1,2,3,...,M; j=1,2,3,...,N}

[0118] Wherein, G represents a two-dimensional grid network divided by the area to be evaluated, M and N represent the rows and columns corresponding to the grid network, respectively, and i and j represent the serial number indexes of the rows and columns of the grid cells in the grid network;

[0119] According to different cultivated land ecological services, a function f is set accordingly. k (g i,j ), and calculate the service value of each service in the grid cell according to the set functional function, then,

[0120]

[0121] Among them, f k (g i,j ) represents the functional function corresponding to the kth ecological service, M and N represent the rows and columns corresponding to the grid network, i and j represent the grid units in the grid network, S k represents the service value of the kth ecological service in the grid cell;

[0122] According to the needs of the area to be assessed, the corresponding weight coefficient w is assigned to different ecological services. k , and calculate the comprehensive service value, then we have,

[0123]

[0124] Among them, S k represents the service value of the kth ecological service in the grid cell, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w krepresents the weight coefficient of different ecological service allocations, S total Represents the calculated comprehensive service value.

[0125] It should be noted that for the functional functions corresponding to different ecological services, the expressions of the functions are different according to different ecological services, as follows:

[0126] For soil conservation services, the function is:

[0127] f k (g i,j )=(R·K·LS·O·P)-(K·LS·O·P)

[0128] Among them, R represents the rainfall erosivity factor, K represents the soil erodibility factor, LS represents the slope length factor, O represents the vegetation coverage factor, and P represents the soil protection measure factor;

[0129] When providing water conservation services, the function is:

[0130] f k (g i,j )=N P -AET-N Q

[0131] Among them, N P represents rainfall, AET represents actual evapotranspiration, N Q It represents the surface runoff;

[0132] When providing carbon fixation service, the function is:

[0133] f k (g i,j )=C veg +C soil

[0134] Among them, C veg Represents vegetation carbon storage, C soil represents soil carbon storage;

[0135] When the habitat is maintained, the function is:

[0136]

[0137] Among them, z represents the comprehensive impact value of landscape fragmentation and habitat threat factors;

[0138] When providing wind and sand fixation services, the function is:

[0139] f k (g i,j )=NDVI·W s

[0140] Among them, NDVI represents the vegetation index, W s represents the wind speed weight factor;

[0141] The expression of functional functions has different manifestations in different services. In this embodiment, only water conservation service, soil conservation service, carbon fixation service, habitat maintenance service and wind and sand fixation service are used for illustration. It does not include all functional expressions. In actual applications, the implementers select different expressions according to different ecological services, which will not be elaborated in this embodiment.

[0142] It should be noted that in order to comprehensively evaluate the ecological services of cultivated land in different regions, the allocation rules of ecological service weight coefficients are formulated to achieve dynamic and scientific allocation of weight coefficients and improve the comprehensiveness of cultivated land ecological service evaluation. The specific allocation rules are as follows:

[0143] Assign an initial priority weight p to each ecological service based on the needs of the area to be assessed k , the value range is [0,1], and satisfies the formula:

[0144]

[0145] Among them, p k represents the initial priority weight of the kth ecological service, and K represents the upper limit of the number of ecological service types in the area to be evaluated;

[0146] According to the set initial priority weight, calculate the corresponding service value S of each ecological service in the grid cell k , and normalized, we have,

[0147]

[0148] Among them, S i,k represents the kth service value corresponding to the i-th grid cell, R i,k represents the normalized value, S k represents the corresponding service value of the kth ecological service in the grid cell, max and min represent the maximum value function and the minimum value function respectively;

[0149] Based on the normalized value, the entropy value corresponding to each service is calculated, and then,

[0150]

[0151] Among them, R i,k represents the normalized value, g M,N Represents the total number of grid cells, M represents the upper limit of the grid cell sequence number, H k Indicates the entropy value corresponding to the kth service;

[0152] According to the entropy value corresponding to the ecological service, the weight coefficient of the corresponding service is adjusted, and then,

[0153]

[0154] Among them, H k represents the entropy value corresponding to the kth service, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k Indicates the weight corresponding to the k-th service.

[0155] Furthermore, the implementation of the ecological service evaluation of cultivated land is evaluated based on the calculated comprehensive service value, and the specific evaluation is as follows:

[0156] Set the comprehensive service value standard threshold S T , according to the comprehensive service value S total The comparison results between the comprehensive service standard threshold and the cultivated land ecosystem service assessment show that:

[0157] If the comparison result satisfies the formula S total ≥S T , indicating that the cultivated land ecosystem service corresponding to the current area is qualified;

[0158] If the comparison result satisfies the formula S total <S T , indicating that the corresponding cultivated land ecosystem service in the current area is unqualified.

[0159] S3: Intelligent optimization based on the synergistic relationship between data.

[0160] Specifically, the intelligent optimization based on the synergistic relationship between data is to intelligently optimize the cultivated land ecological service assessment model according to the synergistic relationship between ecosystem services in the area to be assessed, so as to improve the accuracy of the model.

[0161] Furthermore, the synergistic relationship between the ecosystem services is determined based on the data correlation analysis between the ecosystem services, the synergistic effect coefficient between the two service functions is determined, and the cultivated land ecological service evaluation model is intelligently optimized according to the determined synergistic effect coefficient, which is specifically implemented as follows:

[0162] Set the type of synergy between two services, including positive synergy, negative synergy and no synergy. Positive synergy means that the improvement of one service can promote another service (such as the increase of vegetation cover helps carbon sequestration and water conservation). Negative synergy means that the improvement of one service has a negative impact on another service (such as excessive cultivation will lead to a decrease in habitat maintenance). No synergy means that there is no direct relationship between the two services.

[0163] Based on the data correlation analysis at the grid level, the types of synergies between services are determined as follows:

[0164]

[0165] Among them, cov(S k ,S m ) represents the covariance data between the k-th service and the m-th service, denote the standard deviation of the kth service and the mth service, ρ k,m It represents the correlation coefficient between the kth service and the mth service, which is used to determine the type of synergy between service functions. Specifically:

[0166] If the calculated correlation coefficient satisfies the formula ρ k,m >0, indicating that the synergy type between the two service functions is positive synergy;

[0167] If the calculated correlation coefficient satisfies the formula ρ k,m <0, indicating that the synergy type between the two service functions is positive or negative synergy;

[0168] If the calculated correlation coefficient satisfies the formula ρ k,m =0, indicating that the synergy type between the two service functions is no synergy;

[0169] According to the determined synergy type, the synergy coefficient between the two service functions is calculated, specifically:

[0170] C k,m =ρ k,m ·(1+α k,m )

[0171] Among them, ρ k,m represents the correlation coefficient between the kth service and the mth service, C k,m represents the calculated synergy coefficient between the two services, α k,m It represents the correction coefficient between services, which is determined by the type of synergy between services, specifically:

[0172] If the synergy type between the two services is positive synergy, the correction coefficient value satisfies the formula α k,m >0, the specific value is set by the implementer according to the actual application scenario;

[0173] If the synergy type between the two services is negative synergy, the correction coefficient value satisfies the formula α k,m <0, the specific value is set by the implementer according to the actual application scenario;

[0174] If the synergy type between the two services is no synergy, the correction coefficient value satisfies the formula α k,m =0.

[0175] Furthermore, the intelligent optimization of the cultivated land ecological service evaluation model is to construct a weight coefficient target optimization function according to the calculated synergy effect coefficient, and realize the intelligent optimization of the cultivated land ecological service evaluation model by optimizing the ecological service weight coefficient, which is specifically realized as follows:

[0176] Construct the weight coefficient target optimization function, then we have,

[0177]

[0178] And set constraints to constrain the function, specifically:

[0179] w k >0

[0180]

[0181] Among them, S k represents the service value of the kth ecological service in the grid cell, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k represents the weight coefficient of the kth ecological service allocation, w m represents the weight coefficient of the mth ecological service allocation, C k,m represents the calculated synergy coefficient between the two services, f(w k ) represents the weight coefficient objective optimization function, which is used to maximize the function by adjusting the synergy effect coefficients between services to achieve intelligent optimization of the cultivated land ecological service evaluation model. Specifically:

[0182] The weight coefficient w when the input function is maximized k , and calculate the comprehensive service value S under the current weight coefficient t ' otal And the service value S of the kth ecological service in the grid cell k ′;

[0183] Collect the actual value S of the comprehensive service obtained during the field survey actual ;

[0184] Calculate the combined deviation between the two and the deviation of a single service, then we have,

[0185] D=S t ' otal -S actual

[0186] ΔS k =S k′-S k

[0187] Among them, S t ' otal represents the comprehensive service value when the objective function is maximized, S actual represents the actual value of the comprehensive service obtained in the field survey, S k ′ represents the service value of the kth ecological service in the grid cell when the objective function is maximized, S k represents the service value of the kth ecological service in the grid cell, D represents the comprehensive deviation of the calculation, ΔS k represents the deviation of the calculated single service;

[0188] Set the comprehensive deviation threshold D T And the single service deviation threshold ΔS k,T Determine whether the set weight coefficient needs to be adjusted dynamically, specifically:

[0189] If the calculated comprehensive deviation and the single service deviation are compared with the set threshold, the formula D≥D T And ΔS k ≥ΔS k,T , indicating that the calculated deviation exceeds the deviation threshold, and the weight distribution needs to be dynamically adjusted, specifically:

[0190] Dynamically adjust the weight distribution according to the calculated deviation, then we have,

[0191] Dynamically adjust the initial priority weight based on the deviation of a single service, then we have:

[0192]

[0193] Dynamically adjust the synergy coefficient based on the comprehensive deviation, then we have:

[0194]

[0195] Among them, p k represents the initial priority weight of the kth ecological service, represents the adjusted initial priority weight of the kth ecological service, ΔS k represents the deviation of the calculated single service, C k,m represents the synergy coefficient between the two services, represents the adjusted synergy coefficient between the two services, and D represents the calculated comprehensive deviation;

[0196] Recalculate the comprehensive service value S for the adjusted initial priority weight and synergy coefficient. t ' otal ;

[0197] And calculate the new comprehensive deviation D′ and the single service deviation ΔS k ′;

[0198] If the newly calculated comprehensive deviation and single service deviation satisfy the formula D′<D T And ΔS k ′<ΔS k,T , it means that the calculated deviation does not exceed the deviation threshold, the dynamic adjustment of the weight coefficient is stopped, and the intelligent optimization of the cultivated land ecological service evaluation model is completed.

[0199] Furthermore, if the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0200] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0201] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0202] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention) may not be described.

[0203] It will be appreciated that in the development of any actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but will be a routine task of design, fabrication, and production for those of ordinary skill having the benefit of this disclosure without undue experimentation.

[0204] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating cultivated land ecosystem services based on remote sensing monitoring, characterized by: The following steps are included: Use remote sensing technology to obtain multi-dimensional cultivated land data in the area to be evaluated, and perform data dimensionality reduction on the collected data. At the same time, introduce sparsity constraints to reduce the interference of redundant features in the data set. The ecological service evaluation of cultivated land is realized based on the collected data, specifically: Based on the spatial analysis and quantitative estimation of the cultivated land ecological service system, the cultivated land ecological service evaluation model is built, and the cultivated land data is used as the input data of the model. According to the output results of the model, the cultivated land ecological service evaluation is realized, which also includes: When comprehensively evaluating the ecological services of cultivated land in different regions, formulate the distribution rules of ecological service weight coefficients to achieve dynamic distribution of weight coefficients; Intelligent optimization is performed based on the collaborative relationship between data, specifically: Based on the data correlation analysis between ecological services, the synergy coefficient between the two service functions is determined, and the cultivated land ecological service evaluation model is intelligently optimized according to the determined synergy coefficient, and whether the optimization is completed is judged based on the service deviation.

2. The method for evaluating cultivated land ecosystem services based on remote sensing monitoring according to claim 1, characterized in that: The construction of the cultivated land ecological service evaluation model is as follows: The area to be evaluated is divided into a two-dimensional grid network with a grid unit of g. Each grid unit has different ecological attributes, including vegetation index, soil moisture and slope data. Then, G={g i,j |i=1,2,3,...,M;j=1,2,3,...,N} Wherein, G represents a two-dimensional grid network divided by the area to be evaluated, M and N represent the rows and columns corresponding to the grid network, respectively, and i and j represent the serial number indexes of the rows and columns of the grid cells in the grid network; According to different cultivated land ecological services, a function f is set accordingly. k (g i,j ), and calculate the service value of each service in the grid cell according to the set functional function, then, Among them, f k (g i,j ) represents the functional function corresponding to the kth ecological service, M and N represent the rows and columns corresponding to the grid network, i and j represent the grid units in the grid network, S k represents the service value of the kth ecological service in the grid cell; According to the needs of the area to be assessed, the corresponding weight coefficient w is assigned to different ecological services. k , and calculate the comprehensive service value, then we have, Among them, S k represents the service value of the kth ecological service in the grid cell, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k represents the weight coefficient of different ecological service allocations, S total Represents the calculated comprehensive service value.

3. The method for evaluating cultivated land ecosystem services based on remote sensing monitoring according to claim 2, characterized in that: The specific rules for allocating ecological service weight coefficients are as follows: Assign an initial priority weight p to each ecological service based on the needs of the area to be assessed k , the value range is [0,1], and satisfies the formula: Among them, p k represents the initial priority weight of the kth ecological service, and K represents the upper limit of the number of ecological service types in the area to be evaluated; According to the set initial priority weight, calculate the corresponding service value S of each ecological service in the grid cell k , and normalized, we have, Among them, S i,k represents the kth service value corresponding to the i-th grid cell, R i,k represents the normalized value, S k represents the corresponding service value of the kth ecological service in the grid cell, max and min represent the maximum value function and the minimum value function respectively; Based on the normalized value, the entropy value corresponding to each service is calculated, and then, Among them, R i,k represents the normalized value, g M,N Represents the total number of grid cells, M represents the upper limit of the grid cell sequence number, H k Indicates the entropy value corresponding to the kth service; According to the entropy value corresponding to the ecological service, the weight coefficient of the corresponding service is adjusted, and then, Among them, H k represents the entropy value corresponding to the kth service, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k Indicates the weight corresponding to the k-th service.

4. The method for evaluating cultivated land ecosystem services based on remote sensing monitoring according to claim 3, characterized in that: The implementation of the ecological service assessment of cultivated land is as follows: Set the comprehensive service value standard threshold S T , according to the comprehensive service value S total The comparison results between the comprehensive service standard threshold and the cultivated land ecosystem service assessment show that: If the comparison result satisfies the formula S total ≥S T , indicating that the cultivated land ecosystem service corresponding to the current area is qualified; If the comparison result satisfies the formula S total <S T , indicating that the corresponding cultivated land ecosystem service in the current area is unqualified.

5. The method for evaluating cultivated land ecosystem services based on remote sensing monitoring according to claim 4, characterized in that: The data correlation analysis between the ecological services is as follows: Based on the data correlation analysis at the grid level, the types of synergies between services are determined as follows: Among them, cov(S k ,S m ) represents the covariance data between the k-th service and the m-th service, denote the standard deviation of the kth service and the mth service, respectively, k,m It represents the correlation coefficient between the kth service and the mth service, which is used to determine the type of synergy between service functions. Specifically: If the calculated correlation coefficient satisfies the formula ρ k,m >0, indicating that the synergy type between the two service functions is positive synergy; If the calculated correlation coefficient satisfies the formula ρ k,m <0, indicating that the synergy type between the two service functions is positive or negative synergy; If the calculated correlation coefficient satisfies the formula ρ k,m =0, indicating that the synergy type between the two service functions is no synergy.

6. The method for evaluating cultivated land ecosystem services based on remote sensing monitoring according to claim 5, characterized in that: The determination of the synergy coefficient between the two service functions is as follows: C k,m =ρ k,m ·(1+a k,m ) Among them, ρ k,m represents the correlation coefficient between the kth service and the mth service, C k,m represents the calculated synergy coefficient between the two services, α k,m It represents the correction coefficient between services, which is determined by the type of synergy between services, specifically: If the synergy type between the two services is positive synergy, the correction coefficient value satisfies the formula α k,m >0; If the synergy type between the two services is negative synergy, the correction coefficient value satisfies the formula α k,m <0; If the synergy type between the two services is no synergy, the correction coefficient value satisfies the formula α k,m =0.

7. The method for evaluating cultivated land ecosystem services based on remote sensing monitoring according to claim 6, characterized in that: The intelligent optimization of the cultivated land ecological service evaluation model is specifically as follows: Construct the weight coefficient target optimization function, then we have, And set constraints to constrain the function, specifically: w k ＞0 Among them, S k represents the service value of the kth ecological service in the grid cell, K represents the upper limit of the number of ecological service types in the area to be evaluated, and w k represents the weight coefficient of the kth ecological service allocation, w m represents the weight coefficient of the mth ecological service allocation, C k,m represents the calculated synergy coefficient between the two services, f(w k ) represents the weight coefficient objective optimization function, which is used to maximize the function by adjusting the synergy effect coefficients between services to achieve intelligent optimization of the cultivated land ecological service evaluation model.

8. The method for evaluating cultivated land ecosystem services based on remote sensing monitoring according to claim 7, characterized in that: The specific judgment of whether the optimization based on service deviation is completed is as follows: The weight coefficient w when the input function is maximized k , and calculate the comprehensive service value S under the current weight coefficient t ' otal And the service value S of the kth ecological service in the grid cell k ′; Collect the actual value S of the comprehensive service obtained during the field survey actual ; Calculate the combined deviation between the two and the deviation of a single service, then we have, D=S t ′ otal -S actual ΔS k =S k ′-S k Among them, S t ' otal represents the comprehensive service value when the objective function is maximized, S actual represents the actual value of the comprehensive service obtained in the field survey, S k ′ represents the service value of the kth ecological service in the grid cell when the objective function is maximized, S k represents the service value of the kth ecological service in the grid cell, D represents the comprehensive deviation of the calculation, ΔS k represents the deviation of the calculated single service; Set the comprehensive deviation threshold D T And the single service deviation threshold ΔS k,T Determine whether the set weight coefficient needs to be adjusted dynamically, specifically: If the calculated comprehensive deviation and the single service deviation are compared with the set threshold, the formula D≥D T And ΔS k ≥ΔS k,T , indicating that the calculated deviation exceeds the deviation threshold, and the weight distribution needs to be dynamically adjusted, specifically: Dynamically adjust the weight distribution according to the calculated deviation, then we have, Dynamically adjust the initial priority weight based on the deviation of a single service, then we have: Dynamically adjust the synergy coefficient based on the comprehensive deviation, then we have: Among them, p k represents the initial priority weight of the kth ecological service, represents the adjusted initial priority weight of the kth ecological service, ΔS k represents the deviation of the calculated single service, C k,m represents the synergy coefficient between the two services, represents the adjusted synergy coefficient between the two services, and D represents the calculated comprehensive deviation; Recalculate the comprehensive service value S for the adjusted initial priority weight and synergy coefficient. t ' otal ; And calculate the new comprehensive deviation D′ and the single service deviation ΔS k ′; If the newly calculated comprehensive deviation and single service deviation satisfy the formula D′<D T And ΔS k ′<ΔS k,T , it means that the calculated deviation does not exceed the deviation threshold, the dynamic adjustment of the weight coefficient is stopped, and the intelligent optimization of the cultivated land ecological service evaluation model is completed.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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