Ecological protection compensation policy optimization evaluation method and device, storage medium and computer equipment

Abstract

The ecological protection compensation policy optimization evaluation method and device, the storage medium and the computer equipment provided by the application can obtain the ecological parameter sequence and the ecological economic data of a target region, and quantize the ecological service value according to the two data, so that the ecological service value index obtained can accurately measure the actual value of the ecological environment at present. The ecological value conversion rate generated according to the ecological economic data and the value index can reflect the balance between ecological protection and economic development. Therefore, the market equilibrium state parameters obtained by simulating the market based on the value index and the value conversion rate can predict the dynamic changes of the market in advance. Then, a plurality of policy optimization schemes are generated based on the ecological parameter sequence, the ecological value conversion rate and the market equilibrium state parameters, the ecological parameter improvement prediction and the market equilibrium simulation are performed on each scheme, and the compensation policy optimization evaluation report is generated according to the simulation results, which is used to guide the dynamic optimization of the compensation policy.

Description

Technical Field

[0001] This application relates to the field of ecological protection technology, and in particular to a method, apparatus, storage medium and computer equipment for optimizing and evaluating ecological protection compensation policies. Background Technology

[0002] With the deepening of ecological civilization construction, ecological protection compensation policy has become the core mechanism for balancing ecological protection and regional development, playing an important role in ensuring the sustainability of ecological functions. It incentivizes all parties to participate in ecological protection through interest adjustment mechanisms, and plays a key role in maintaining ecosystem service functions and promoting green transformation.

[0003] Currently, the evaluation of ecological protection compensation policies mainly adopts static statistical analysis. Relying on historical data or single indicators for ex-post evaluation makes it difficult to accurately reflect the balance between ecological protection investment and economic development, and even more difficult to predict the effects of policy implementation in advance, thus failing to provide scientific decision support for policy optimization. As a result, the adjustment of compensation policies often lags behind the needs of ecological and environmental changes and economic development, thereby affecting the long-term effectiveness and accuracy of the ecological protection compensation mechanism. Summary of the Invention

[0004] The purpose of this application is to address at least one of the aforementioned technical deficiencies, particularly the technical deficiency in the prior art where adjustments to ecological protection compensation policies often lag behind changes in the ecological environment and the needs of economic development, thereby affecting the long-term effectiveness and accuracy of the ecological protection compensation mechanism.

[0005] This application provides a method for optimizing and evaluating ecological protection compensation policies, the method comprising: An ecological parameter sequence is generated based on remote sensing image data and ecological monitoring data collected from the target area, and ecological and economic data of the target area are obtained from the regional economic management system. The value of each ecological service in the target area is quantified based on the ecological parameter sequence and the ecological economic data to obtain an ecological service value index, and the ecological value conversion rate of the target area is determined based on the ecological economic data and the ecological service value index. Based on the ecological service value index and the ecological value conversion rate, a market equilibrium simulation model for the target area is constructed, and the market equilibrium simulation model is solved to obtain the market equilibrium state parameters. Based on the ecological parameter sequence and the ecological value conversion rate assessment, ecological constraint factors are obtained, and multiple compensation policy optimization schemes are generated according to the market equilibrium state parameters and the ecological constraint factors. For each compensation strategy optimization scheme, ecological parameter improvement prediction and market equilibrium simulation are performed to obtain the predicted state parameters of each compensation strategy optimization scheme. The effect of each predicted state parameter is evaluated, and a compensation policy optimization evaluation report is generated.

[0006] Optionally, generating the ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area includes: Collect raw ecological parameters in the target area; the raw ecological parameters include remote sensing image data and ecological monitoring data; The original ecological parameters are cleaned and then spatiotemporally aligned to form an ecological parameter sequence.

[0007] Optionally, the step of quantifying the value of each ecological service in the target area based on the ecological parameter sequence and the ecoeconomic data to obtain an ecological service value index includes: Based on the ecological parameter sequence and the ecoeconomic data, multiple ecological services covered in the target area are identified, and a value quantification model corresponding to each ecological service is determined. The input parameters corresponding to each value quantification model are extracted from the ecological parameter sequence and the ecological economic data, and each input parameter is input into the corresponding value quantification model for value quantification to obtain the service value of each ecological service. The evaluation coefficient for each ecosystem service is determined, and the service value of each ecosystem service is weighted and summed using each evaluation coefficient to obtain the ecosystem service value index of the target area.

[0008] Optionally, determining the ecological value conversion rate of the target area based on the ecological economic data and the market value of the ecological products includes: The market price data and product output data of each ecological product in the ecological economic data are extracted, and the market value of the ecological products in the target area is determined based on the market price data and the product output data. The ecological conversion rate of the target area is obtained by calculating the ratio between the market value of the ecological products and the ecological service value index.

[0009] Optionally, the step of constructing a market equilibrium simulation model for the target region based on the ecosystem service value index and the ecosystem value conversion rate includes: An ecological supply function is constructed using the ecological service value index, and a market demand function is constructed using the ecological value conversion rate. By simultaneously solving the ecological supply function and the market demand function, a market equilibrium simulation model for the target region is obtained.

[0010] Optionally, the step of solving the market equilibrium simulation model to obtain market equilibrium state parameters includes: The equilibrium price point of the market equilibrium simulation model is solved using Newton's iterative method. The market transaction size is obtained by solving the ecological supply function using the equilibrium price point. The market value is obtained by multiplying the equilibrium price point and the market transaction size. The equilibrium price point, the market transaction volume, and the market value volume are combined to form the market equilibrium state parameters.

[0011] Optionally, the step of generating multiple compensation policy optimization schemes based on the market equilibrium state parameters and the ecological constraint factors includes: The ecological constraint factors are matched with indicators in the policy scenario database to obtain compensation indicators and the basic compensation standards for the compensation indicators. Based on the market equilibrium parameters, a compensation analysis is performed on the basic compensation standard to obtain the compensation budget range; A random search algorithm is used to generate multiple compensation policy optimization schemes corresponding to the compensation indicators within the compensation budget range.

[0012] Optionally, the step of evaluating the effects of each predicted state parameter and generating a compensation policy optimization evaluation report includes: The optimal predicted state parameter among all predicted state parameters is marked as the optimal state parameter, and the compensation strategy optimization scheme corresponding to the optimal state parameter is marked as the optimal compensation policy optimization scheme. The optimal state parameters are compared and analyzed with the market equilibrium state parameters to obtain the analysis results; An evaluation report on the optimization of the compensation policy is generated based on the optimal compensation policy optimization scheme, the optimal state parameters, the market equilibrium state parameters, and the analysis results.

[0013] This application also provides an ecological protection compensation policy optimization and evaluation device, including: The data acquisition module is used to generate an ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area, and to acquire ecological and economic data of the target area from the regional economic management system. The value quantification module is used to quantify the value of each ecological service in the target area based on the ecological parameter sequence and the ecological economic data to obtain an ecological service value index, and to determine the ecological value conversion rate of the target area based on the ecological economic data and the ecological service value index. The market simulation module is used to construct a market equilibrium simulation model for the target area based on the ecological service value index and the ecological value conversion rate, and to solve the state of the market equilibrium simulation model to obtain market equilibrium state parameters. The scheme generation module is used to obtain ecological constraint factors based on the ecological parameter sequence and the ecological value conversion rate assessment, and to generate multiple compensation policy optimization schemes based on the market equilibrium state parameters and the ecological constraint factors. The optimization evaluation module is used to predict the improvement of ecological parameters and simulate market equilibrium for each compensation strategy optimization scheme, obtain the predicted state parameters of each compensation strategy optimization scheme, evaluate the effect of each predicted state parameter, and obtain a compensation policy optimization evaluation report.

[0014] This application also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the ecological protection compensation policy optimization and evaluation method as described in any of the above embodiments.

[0015] This application also provides a computer device, including: one or more processors, and memory; The memory stores computer-readable instructions, which, when executed by the one or more processors, perform the steps of the ecological protection compensation policy optimization and evaluation method as described in any of the above embodiments.

[0016] As can be seen from the above technical solutions, the embodiments of this application have the following advantages: The ecological protection compensation policy optimization assessment method, device, storage medium, and computer equipment provided in this application can, during policy optimization assessment, first generate an ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area, and obtain ecological and economic data of the target area from the regional economic management system, thereby comprehensively reflecting the real-time ecological status of the target area. Then, based on the ecological parameter sequence and ecological and economic data, the value of each ecological service in the target area can be quantified to obtain an ecological service value index, which can accurately measure the actual value of the ecological environment. Based on the ecological and economic data and the ecological service value index, the ecological value conversion rate of the target area can be determined to reflect the balance between ecological protection and economic development. Therefore, a market equilibrium simulation model for the target area can be constructed based on the ecosystem service value index and the ecosystem value conversion rate. The market equilibrium state parameters obtained by solving the state of this model can predict market dynamics in advance. Subsequently, ecological constraints can be assessed based on the ecosystem parameter sequence and the ecosystem value conversion rate. Multiple compensation policy optimization schemes can be generated based on the market equilibrium state parameters and the ecosystem constraints. The generated optimization schemes can fully consider the constraints of the ecological environment on policy implementation. By predicting the improvement of ecosystem parameters and simulating market equilibrium for each scheme, and evaluating the effects of each predicted state parameter obtained from the simulation, the resulting compensation policy optimization evaluation report can be used to guide the dynamic optimization of compensation policies, thereby improving the long-term effectiveness and accuracy of the ecological protection compensation mechanism. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating an ecological protection compensation policy optimization and evaluation method provided in this application embodiment; Figure 2 A flowchart illustrating an ecosystem service value quantification process provided in this application embodiment; Figure 3 A schematic diagram of the structure of an ecological protection compensation policy optimization and evaluation device provided in this application embodiment; Figure 4 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] Currently, the evaluation of ecological protection compensation policies mainly adopts static statistical analysis. Relying on historical data or single indicators for ex-post evaluation makes it difficult to accurately reflect the balance between ecological protection investment and economic development, and even more difficult to predict the effects of policy implementation in advance, thus failing to provide scientific decision support for policy optimization. As a result, the adjustment of compensation policies often lags behind the needs of ecological and environmental changes and economic development, thereby affecting the long-term effectiveness and accuracy of the ecological protection compensation mechanism.

[0021] Based on this, this application proposes the following technical solution, as detailed below: In one embodiment, such as Figure 1 As shown, Figure 1 This application provides a flowchart illustrating an optimization evaluation method for ecological protection compensation policies. The method specifically includes the following: S110: Generate an ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area, and obtain ecological and economic data of the target area from the regional economic management system.

[0022] In this step, during policy optimization assessment, computer equipment can first acquire ecological data in the target area, including generating ecological parameter sequences based on remote sensing image data and ecological monitoring data collected from the target area, and acquiring ecological and economic data of the target area from the regional economic management system, thereby comprehensively reflecting the real-time ecological status of the target area.

[0023] Specifically, remote sensing image data refers to spatially distributed image data acquired through satellite remote sensing systems for Earth observation of a target area. This data can include land use data, vegetation indices, water body distribution data, forest cover, etc., and is primarily used to reflect changes in the ecological pattern and resource distribution of the target area. Ecological monitoring data, on the other hand, refers to data collected in real time by various ecological and environmental monitoring devices or systems deployed within the target area. This data can include biodiversity indicators, soil quality indicators, water quality indicators, climate monitoring data, etc., and is primarily used to characterize the operational status of the ecosystem and the environmental quality. Therefore, computer equipment can fuse and analyze remote sensing image data and ecological monitoring data to generate a temporally continuous sequence of ecological parameters, used to characterize the real-time ecological state of the target area.

[0024] Furthermore, ecoeconomic data refers to data generated during the integration of ecological protection and economic activities. It can include data such as ecological agricultural output, ecological product prices, and ecotourism revenue, primarily used to characterize the development and utilization of ecological resources in a target area and the realization of their economic value. When acquiring ecoeconomic data, computer equipment can communicate with the regional economic management system through a data interface to obtain ecoeconomic data for the target area within a corresponding time frame. Further, the computer equipment can perform standardization processing and time series construction on the acquired ecoeconomic data to ensure its consistency and comparability with ecological parameter sequences over time.

[0025] Understandably, through ecological parameter sequences and ecoeconomic data, this application can form a comprehensive data foundation covering both ecological status and economic activities, thereby achieving a comprehensive characterization of the real-time ecological status and ecoeconomic relationship of the target area, and providing high-quality input data support for the subsequent evaluation, analysis and optimization decision-making of ecological protection compensation policies.

[0026] S120: Based on the ecological parameter sequence and ecoeconomic data, the value of each ecological service in the target area is quantified to obtain the ecological service value index. Based on the ecoeconomic data and the ecological service value index, the ecological value conversion rate of the target area is determined.

[0027] In this step, after obtaining the ecological parameter sequence and ecoeconomic data through step S110, the computer equipment can quantify the value of each ecological service in the target area based on the ecological parameter sequence and ecoeconomic data to obtain the ecoservice value index. This can accurately measure the actual value of the ecological environment. Based on the ecoeconomic data and ecoservice value index, the ecological value conversion rate of the target area can be determined, which is mainly used to reflect the balance between ecological protection and economic development.

[0028] Among them, the ecosystem service value index refers to the weighted summation of various ecosystem service functions within the target area after quantitative assessment, and is used to comprehensively characterize the overall value level of the regional ecosystem; the ecosystem value conversion rate refers to the efficiency indicator of converting ecosystem service value into actual economic benefits within the target area, and is used to characterize the degree of realization of ecological resource value and the ecological-economic coupling relationship.

[0029] Specifically, the computer equipment can first identify the various ecosystem services covered in the target area, including water conservation services, soil conservation services, and biodiversity conservation services. Then, the computer equipment can select the corresponding characterization parameters for different types of ecosystem services and combine them with a preset value quantification model or ecological value assessment function to quantitatively calculate each ecosystem service, thereby obtaining the corresponding ecosystem service value. Then, the value of each ecosystem service can be weighted and summarized to obtain an ecosystem service value index that represents the overall ecological value level of the target area.

[0030] Furthermore, after determining the ecological service value index of the target area, the computer equipment can also combine ecological economic data to correlate the ecological service value index with economic benefit indicators in the ecological economic data, thereby determining the ecological value conversion rate of the target area, which is used to reflect the coordination relationship between ecological protection input and economic development output.

[0031] S130: Based on the ecological service value index and ecological value conversion rate, a market equilibrium simulation model for the target area is constructed, and the market equilibrium simulation model is solved to obtain the market equilibrium state parameters.

[0032] In this step, after determining the ecological service value index and ecological value conversion rate through step S120, the computer equipment can construct a market equilibrium simulation model of the target area based on the ecological service value index and ecological value conversion rate. The market equilibrium state parameters obtained by solving the state of the model can predict market dynamic changes in advance.

[0033] Among them, the market equilibrium simulation model refers to an economic model used to simulate the supply and demand relationship and price formation mechanism of the ecological service market in a target area. Its core lies in using mathematical equations to characterize the dynamic relationship between the supply and demand of ecological services as prices change.

[0034] Specifically, in model construction, this application can use the ecosystem service value index as a key indicator representing ecosystem supply and the ecosystem value conversion rate as a key indicator representing market demand, constructing a market equilibrium simulation model that includes an ecosystem supply function and a market demand function. After the model is constructed, computer equipment can use numerical solution methods to solve the state of the market equilibrium simulation model, such as using iterative convergence algorithms or optimization algorithms, to solve for the key variables in the model, thereby obtaining market equilibrium state parameters, including equilibrium price point, market transaction size, market value size, etc., which can be used to predict the supply and demand balance point and economic value size of the ecosystem service market under natural conditions.

[0035] S140: Based on the ecological parameter sequence and ecological value conversion rate assessment, ecological constraint factors are obtained, and multiple compensation policy optimization schemes are generated according to market equilibrium state parameters and ecological constraint factors.

[0036] In this step, after obtaining the current market equilibrium parameters of the target area through step S130, the computer equipment can obtain the ecological constraint factors based on the ecological parameter sequence and the ecological value conversion rate assessment, and generate multiple compensation policy optimization schemes based on the market equilibrium parameters and the ecological constraint factors. The generated optimization schemes can fully consider the constraints of the ecological environment on the implementation of the policies.

[0037] Among them, ecological constraints refer to the key limiting factors that affect the ecological carrying capacity and sustainable supply of ecosystem services in the target area. These factors directly determine the boundary conditions for the implementation of ecological protection policies and the reasonable threshold for resource input. The compensation policy optimization scheme refers to a variety of alternative schemes formulated for the specific implementation content and adjustment direction of the ecological protection compensation policy. In this application, it can be used to further optimize the current ecological protection compensation policy in the target area.

[0038] Specifically, computer equipment can establish a linear regression model, then use this model to analyze the influence weight of each ecological parameter in the ecological parameter sequence on the ecological value conversion rate, and identify key constraint factors whose influence exceeds a preset threshold, thereby generating ecological constraint factors. Subsequently, the computer equipment can combine these ecological constraint factors with market equilibrium parameters to construct multiple compensation policy optimization schemes. For example, by adjusting compensation standards, differentiated compensation coefficients, or industry guidance parameters, the market equilibrium state can be adjusted while satisfying the ecological constraint factors, thus generating multiple compensation policy optimization schemes.

[0039] S150: For each compensation strategy optimization scheme, predict the improvement of ecological parameters and simulate market equilibrium to obtain the predicted state parameters of each compensation strategy optimization scheme, evaluate the effect of each predicted state parameter, and generate a compensation policy optimization evaluation report.

[0040] In this step, after generating multiple compensation strategy optimization schemes through step S140, the computer equipment can predict the improvement of ecological parameters and simulate market equilibrium for each scheme, and evaluate the effects of each predicted state parameter obtained from the simulation. The compensation policy optimization evaluation report generated in this way can be used to guide the dynamic optimization of compensation policies, thereby improving the long-term effectiveness and accuracy of the ecological protection compensation mechanism.

[0041] Specifically, for each compensation strategy optimization scheme, the computer equipment can use a pre-set ecological parameter prediction model, combined with the policy parameter adjustment direction and intensity of the scheme, to predict the improvement trend of the ecological parameter sequence of the target area over a certain period of time, obtaining the predicted results of ecological parameter improvement, such as the increase in vegetation coverage and the degree of improvement in water purification. Simultaneously, the computer equipment can recalculate the ecological service value index and ecological value conversion rate using the parameters obtained after the improvement and adjustment through the compensation strategy optimization scheme, and then solve for the market equilibrium state, obtaining the market equilibrium simulation results corresponding to the scheme, i.e., the predicted state parameters, including the adjusted equilibrium price point, market transaction scale, and market value scale. Subsequently, based on a pre-set evaluation index system, the computer equipment can quantitatively score each predicted state parameter and conduct a comprehensive effect evaluation, ultimately generating a compensation policy optimization evaluation report containing compensation scheme recommendations, providing policymakers with a clear and scientific basis for decision-making.

[0042] More specifically, the ecological parameter prediction model of this application can adopt an input improvement response function, as specifically expressed below:

[0043] In the formula, This represents the amount of improvement in ecological parameter i; This represents the theoretical limit of physical improvement; This represents the response sensitivity coefficient; This indicates the compensation intensity set in the compensation strategy optimization scheme.

[0044] In the above embodiments, during policy optimization evaluation, an ecological parameter sequence can be generated first based on remote sensing image data and ecological monitoring data collected from the target area, and ecological and economic data of the target area can be obtained from the regional economic management system, thereby comprehensively reflecting the real-time ecological status of the target area. Then, the value of each ecological service in the target area can be quantified based on the ecological parameter sequence and ecological and economic data to obtain an ecological service value index. This can accurately measure the actual value of the ecological environment. Based on the ecological and economic data and the ecological service value index, the ecological value conversion rate of the target area can be determined to reflect the balance between ecological protection and economic development. Therefore, a market equilibrium simulation model for the target area can be constructed based on the ecosystem service value index and the ecosystem value conversion rate. The market equilibrium state parameters obtained by solving the state of this model can predict market dynamics in advance. Subsequently, ecological constraints can be assessed based on the ecosystem parameter sequence and the ecosystem value conversion rate. Multiple compensation policy optimization schemes can be generated based on the market equilibrium state parameters and the ecosystem constraints. The generated optimization schemes can fully consider the constraints of the ecological environment on policy implementation. By predicting the improvement of ecosystem parameters and simulating market equilibrium for each scheme, and evaluating the effects of each predicted state parameter obtained from the simulation, the resulting compensation policy optimization evaluation report can be used to guide the dynamic optimization of compensation policies, thereby improving the long-term effectiveness and accuracy of the ecological protection compensation mechanism.

[0045] In one embodiment, the process of generating an ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area in step S110 may include: S111: Collect raw ecological parameters in the target area; raw ecological parameters include remote sensing image data and ecological monitoring data.

[0046] S112: Clean the original ecological parameters and perform spatiotemporal alignment on the cleaned original ecological parameters to form an ecological parameter sequence.

[0047] In this embodiment, the computer device can collect remote sensing image data and ecological monitoring data in the target area as raw ecological parameters. Then, the raw ecological parameters can be cleaned and spatiotemporally aligned to form an ecological parameter sequence.

[0048] Specifically, the cleaning process in this application mainly includes identifying and processing outliers, missing values, and noisy data in the original ecological parameters. For outliers, the computer equipment can use interpolation or mean replacement methods to correct them; for missing values, the computer equipment can use linear interpolation, moving average, or machine learning-based prediction models to fill them in based on the time-series characteristics of the data; for noisy data, the computer equipment can use smoothing filtering algorithms to reduce data fluctuations, ensuring the accuracy and reliability of the original ecological parameters.

[0049] Because remote sensing imagery data and ecological monitoring data come from different sources, were acquired at different times, and have different spatial resolutions, a unified spatiotemporal benchmark transformation can be performed on the cleaned remote sensing imagery data and ecological monitoring data after the original ecological parameters have been cleaned. In the temporal dimension, computer equipment can use time interpolation or resampling techniques to adjust data with different time granularities to a consistent time interval. In the spatial dimension, computer equipment can use Geographic Information System (GIS) technology to match the spatial coordinates of the remote sensing imagery data with the deployment locations of the ecological monitoring equipment, achieving precise spatial correspondence of the data. This ultimately forms a sequence of ecological parameters with a unified spatiotemporal scale, providing a standardized data foundation for subsequent quantification of ecosystem service value and policy evaluation.

[0050] In one embodiment, such as Figure 2 As shown, Figure 2 A flowchart illustrating an ecosystem service value quantification process provided in this application embodiment; Figure 2 In step S120, the process of quantifying the value of each ecosystem service in the target area based on the ecological parameter sequence and ecoeconomic data to obtain the ecosystem service value index may include: S121: Based on the ecological parameter sequence and ecoeconomic data, identify multiple ecological services covered in the target area and determine the value quantification model corresponding to each ecological service.

[0051] S122: Extract the input parameters corresponding to each value quantification model from the ecological parameter sequence and ecological economic data, and input each input parameter into the corresponding value quantification model to quantify the value and obtain the service value of each ecological service.

[0052] S123: Determine the evaluation coefficient for each ecosystem service, and use each evaluation coefficient to perform a weighted summation of the service value of each ecosystem service to obtain the ecosystem service value index of the target area.

[0053] In this embodiment, when quantifying the ecosystem service value of a target area, the computer device can first identify multiple ecosystem services covered in the target area based on the ecosystem parameter sequence and ecoeconomic data, and determine the value quantification model corresponding to each ecosystem service. Then, it can extract the input parameters corresponding to each value quantification model from the ecosystem parameter sequence and ecoeconomic data, and input each input parameter into the corresponding value quantification model to quantify the value, thereby obtaining the service value of each ecosystem service. Subsequently, the computer device can determine the evaluation coefficient corresponding to each ecosystem service, and use each evaluation coefficient to perform a weighted summation of the service values ​​of each ecosystem service to obtain the ecosystem service value index of the target area.

[0054] Specifically, computer equipment can combine data such as vegetation cover, soil erosion modulus, and biodiversity abundance from ecological parameter sequences with information such as land use type and ecological protection investment from ecoeconomic data to identify specific ecosystem services within a target area, such as water conservation services, soil conservation services, and biodiversity conservation services. For different ecosystem services, the computer equipment can obtain pre-constructed value quantification models for their types. Simultaneously, the computer equipment can extract input parameters corresponding to each model from the ecological parameter sequences and ecoeconomic data. For example, input parameters for water conservation services may include precipitation, evapotranspiration, and runoff from the ecological parameter sequences, as well as unit reservoir capacity cost from the ecoeconomic data; input parameters for soil conservation services may include soil retention capacity from the ecological parameter sequences, as well as siltation costs and equivalent fertility compensation unit prices from the ecoeconomic data; input parameters for biodiversity conservation services may include unit area protection compensation standards from the ecoeconomic data. After obtaining the input parameters for the ecosystem services, the computer equipment can input them into the corresponding models for value quantification, thereby obtaining the service value of each ecosystem service.

[0055] When weighting and summing the values ​​of various ecosystem services, computer equipment can first determine the evaluation coefficient for each service. This coefficient primarily measures the relative importance of different ecosystem services within the target area's ecological environment and their contribution weight to the overall ecological value. It needs to consider factors such as the target area's ecological protection priorities, economic development needs, and the scarcity of ecosystem services. For example, for ecologically fragile areas, the evaluation coefficient for biodiversity conservation services can be appropriately increased; for water-scarce areas, the evaluation coefficient for water conservation services can be given a higher weight. Here, computer equipment can scientifically determine the evaluation coefficients for each ecosystem service using methods such as the analytic hierarchy process (AHP), entropy weighting, or expert scoring to ensure that the weighted summation result truly reflects the comprehensive value of the regional ecosystem.

[0056] More specifically, the calculation expression for the value quantification model corresponding to water conservation services can be represented as follows:

[0057] In the formula, Indicates the value of water conservation; Indicates water production; This indicates the cost per unit of warehouse capacity; Indicates precipitation; Indicates evaporation rate; This indicates runoff volume.

[0058] The calculation expression for the value quantification model corresponding to soil conservation services can be represented as follows:

[0059] In the formula, Indicates soil conservation value; Indicates soil retention capacity; Indicates the value of silt removal; This indicates the unit price for equivalent fertilizer compensation; Indicates the potential amount of erosion; This indicates the actual amount of erosion.

[0060] The calculation expression for the value quantification model corresponding to biodiversity conservation services can be represented as follows:

[0061] In the formula, It indicates the value of biodiversity conservation; Indicates the area of ​​the target region; It represents the biodiversity abundance coefficient, which can be calculated based on biodiversity indicators; It signifies the protection of biodiversity.

[0062] In one embodiment, the process of determining the ecological value conversion rate of the target area based on ecoeconomic data and the market value of ecological products in step S120 may include: S124: Extract market price data and product output data of various ecological products from the ecological economic data, and determine the market value of ecological products in the target area based on the market price data and product output data.

[0063] S125: Calculate the ratio of the market value of ecological products to the value index of ecological services to obtain the ecological conversion rate of the target area.

[0064] In this embodiment, when calculating the ecological value conversion rate, the computer device can first extract the market price data and product output data of each ecological product from the ecological economic data, and determine the market value of the ecological products in the target area based on the market price data and product output data. Then, the ratio of the market value of the ecological product to the ecological service value index can be calculated to obtain the ecological conversion rate of the target area.

[0065] Specifically, computer equipment can filter market price data and corresponding output data directly related to ecological products from ecoeconomic data. By multiplying the market price and output of each ecological product, the market value of an individual ecological product is obtained. Then, by summing the market values ​​of all ecological products, the overall market value of ecological products in the target area can be determined. After obtaining the market value of ecological products, the computer equipment can perform a ratio calculation with the ecological service value index, that is, divide the market value of ecological products by the ecological service value index. The result is the ecological value conversion rate. This conversion rate can intuitively reflect the efficiency of converting ecological service value into economic value. The higher the value, the greater the economic benefit brought by a unit of ecological service value; conversely, the lower the value, the lower the conversion efficiency. This provides a crucial quantitative reference for adjusting ecological protection investment and economic development strategies in subsequent policy optimization.

[0066] In one embodiment, the process of constructing a market equilibrium simulation model for the target area based on the ecosystem service value index and the ecosystem value conversion rate in step S130 may include: S131: Construct an ecological supply function using the ecological service value index, and construct a market demand function using the ecological value conversion rate.

[0067] S132: By solving the equations of the ecological supply function and the market demand function simultaneously, a market equilibrium simulation model for the target region is obtained.

[0068] In this embodiment, when constructing a market equilibrium simulation model, the computer device can first construct an ecological supply function using the ecological service value index and a market demand function using the ecological value conversion rate. Then, the ecological supply function and the market demand function can be combined into equations to obtain a market equilibrium simulation model for the target area.

[0069] Understandably, the ecological supply function can be expressed as the relationship between the ecological service value index and ecological protection investment. An increase in ecological protection investment directly boosts the ecological service value index, thereby increasing the supply of ecological products. The market demand function, constructed based on the ecological value conversion rate, reflects the relationship between market demand for ecological products and the efficiency of ecological value conversion. A higher ecological value conversion rate means more economic value can be converted from a unit of ecological service value, leading to a corresponding increase in market demand for ecological products. By simultaneously establishing the ecological supply function and the market demand function, the equilibrium solution for the supply and demand of ecological products under market equilibrium can be obtained. Therefore, a market equilibrium simulation model capable of simulating the dynamic balance of market supply and demand can be constructed.

[0070] Specifically, the calculation expression for the ecological supply function can be as follows:

[0071] In the formula, Indicates the ecological supply; Indicates the resource contribution coefficient; The ecosystem service value index represents the upper limit of the supply potential of ecosystem resources. This represents the price elasticity coefficient; This indicates market incentives.

[0072] The market demand function can be expressed as follows:

[0073] In the formula, Indicates market demand; This represents the basic demand scale constant, used to characterize the market potential capacity and basic consumer preferences of regional ecological products. It is mainly obtained by regression fitting of historical market transaction scale data. This indicates the conversion rate of ecological value, representing consumers' recognition of the region's ecological brands; This represents the price elasticity of demand.

[0074] Furthermore, by combining the ecological supply function and the market demand function, Thus, a market equilibrium simulation model can be constructed, specifically represented as follows:

[0075] In one embodiment, the process of solving the market equilibrium simulation model for state parameters in step S130 may include: S133: Solve the equilibrium price point of the market equilibrium simulation model using the Newton-Raphson iteration method.

[0076] S134: Solve the ecological supply function using the equilibrium price point to obtain the market transaction scale.

[0077] S135: Multiply the equilibrium price point and the market transaction size to obtain the market value.

[0078] S136: Combine the parameters of equilibrium price point, market transaction size, and market value size to form the market equilibrium state parameters.

[0079] In this embodiment, the market equilibrium state parameters obtained from the market equilibrium simulation model mainly consist of the equilibrium price point, market transaction size, and market value size. When solving for these parameters, the equilibrium price point of the market equilibrium simulation model can first be solved using the Newton-Raphson iteration method. Then, the ecological supply function can be solved using the equilibrium price point to obtain the market transaction size. Finally, the market value size can be obtained by multiplying the equilibrium price point and the market transaction size.

[0080] Specifically, Newton's iterative method can efficiently solve for the equilibrium price in a market equilibrium simulation model by iteratively approaching the zero point of a function. In this process, the computer can first set an initial price iteration value, substitute it into the market equilibrium simulation model to calculate the function value and derivative, and gradually adjust the price parameters until the price difference between two iterations is less than a set threshold. The price obtained at this point is the equilibrium price point. Substituting this equilibrium price point into the ecological supply function expression, and calculating the product relationship between the resource contribution coefficient, the ecological service value index, the price elasticity coefficient, and the market incentive, the corresponding market transaction scale can be obtained. This reflects the actual transaction volume of ecological products under market equilibrium. Further, multiplying the equilibrium price point by the market transaction scale yields the market value scale, which reflects the total economic volume of ecological product transactions under equilibrium. Finally, combining these three parameters in the order of equilibrium price point, market transaction scale, and market value scale forms a complete set of market equilibrium parameters, providing a quantitative basis for subsequent evaluation of the implementation effect of ecological protection compensation policies.

[0081] In one embodiment, step S140, which generates multiple compensation policy optimization schemes based on market equilibrium parameters and ecological constraints, may include: S141: Match ecological constraint factors with indicators in the policy scenario database to obtain compensation indicators and the basic compensation standards for the compensation indicators.

[0082] S142: Based on the market equilibrium state parameters, perform compensation analysis on the basic compensation standard to obtain the compensation budget range.

[0083] S143: Use a random search algorithm to generate multiple compensation policy optimization schemes corresponding to compensation indicators within the compensation budget range.

[0084] In this embodiment, when generating an optimized compensation policy scheme, the computer device can first perform index matching of ecological constraint factors in the policy scenario library to obtain compensation indicators and basic compensation standards for the compensation indicators. Then, it can perform compensation analysis on the basic compensation standards based on market equilibrium state parameters to obtain a compensation budget range. Subsequently, it can use a random search algorithm to generate multiple optimized compensation policy schemes corresponding to the compensation indicators within the compensation budget range.

[0085] The policy scenario database stores the correspondence between different types of ecological constraints and compensation indicators, as well as the basic compensation standards for each compensation indicator under normal circumstances. These basic compensation standards refer to the benchmark compensation amount or proportion pre-set for a single compensation indicator within the framework of ecological protection policies for a specific region. For example, the basic compensation standard for water conservation services may be determined based on the product of the water conservation volume per unit area and the compensation price per unit water volume, while the basic compensation standard for soil conservation services may refer to the fertility restoration cost or sediment management cost corresponding to the soil conservation volume per unit area.

[0086] Understandably, after identifying the ecological constraints of a target area, computer equipment can match corresponding compensation indicators from a policy scenario database. For example, water quality constraints can be matched with compensation for water pollution prevention and drinking water source protection; land degradation constraints can be matched with subsidies for returning farmland to forest and grassland and improving farmland quality; and biological resource constraints can be matched with special compensation for biodiversity conservation and hunting bans. These compensation indicators, by changing the behavior of operators, directly affect ecological monitoring data, leading to improvements in ecological parameter sequences, thereby increasing the ecosystem service value index and the ecosystem value conversion rate, and thus influencing the simulation results of the market equilibrium simulation model.

[0087] Specifically, after matching the compensation indicators and basic compensation standards corresponding to the ecological constraints, the computer equipment can perform a compensation budget analysis on the basic compensation standards in conjunction with market equilibrium parameters. This determines a reasonable compensation budget range, which must ensure that the compensation policy effectively promotes ecological protection while avoiding excessively high or low compensation amounts that could adversely affect market equilibrium. Subsequently, the computer equipment can use a random search algorithm within this compensation budget range to combine parameters for different compensation indicators, generating multiple different compensation policy optimization schemes. From these alternative schemes, it can then find the policy equilibrium point that achieves the maximum market benefit increment with the minimum fiscal compensation cost.

[0088] Furthermore, during the scheme generation process, the computer equipment can also generate a series of compensation policy optimization schemes within the compensation budget range using a fixed step size, without any restrictions.

[0089] In one embodiment, the process of evaluating the effects of each predicted state parameter and generating a compensation policy optimization evaluation report in step S150 may include: S151: Mark the best predicted state parameter among all predicted state parameters as the optimal state parameter, and mark the compensation strategy optimization scheme corresponding to the optimal state parameter as the optimal compensation policy optimization scheme.

[0090] S152: Compare and analyze the optimal state parameters with the market equilibrium state parameters to obtain the analysis results.

[0091] S153: Generate a compensation policy optimization evaluation report based on the optimal compensation policy optimization scheme, optimal state parameters, market equilibrium state parameters, and analysis results.

[0092] In this embodiment, during policy optimization evaluation, the computer device can mark the best predicted state parameter among all predicted state parameters as the optimal state parameter, and mark the compensation strategy optimization scheme corresponding to the optimal state parameter as the optimal compensation policy optimization scheme. Then, the computer device can compare and analyze the optimal state parameter with the market equilibrium state parameter to obtain the analysis results. Subsequently, a compensation policy optimization evaluation report can be generated based on the optimal compensation policy optimization scheme, the optimal state parameter, the market equilibrium state parameter, and the analysis results.

[0093] Specifically, computer equipment can screen the optimal state parameters through pre-set multi-dimensional evaluation indicators. For example, the growth rate of market value scale, the increase in the ecological service value index, and the rate of return on compensation costs can be used as core evaluation indicators. A weighted scoring method is used to comprehensively score each predicted state parameter. The predicted state parameter with the highest score is the optimal state parameter, and its corresponding compensation policy optimization scheme is determined as the optimal compensation policy optimization scheme.

[0094] After determining the optimal compensation policy optimization scheme and its optimal state parameters, the computer equipment can compare the equilibrium price point, market transaction scale, and market value scale in the optimal state parameters with the initial market equilibrium state parameters one by one. It analyzes the magnitude and trend of changes before and after policy implementation, such as the growth rate of market value scale and the fluctuation range of the equilibrium price point. Combined with the degree of improvement in ecological constraints, it generates an analysis result including data comparison tables, trend charts, and key conclusions. Finally, the computer equipment can integrate the specific content of the optimal compensation policy optimization scheme, the specific values ​​of the optimal state parameters, the initial market equilibrium state parameters, and the comparative analysis results of the real-time effects before and after policy optimization, generating a compensation policy optimization evaluation report according to a standardized report format.

[0095] Furthermore, the compensation policy optimization report can also include potential risk warnings and adaptive adjustment suggestions for policy implementation, providing comprehensive and quantitative decision support for relevant departments to formulate ecological protection compensation policies. No restrictions are placed on the specific extended content in the compensation policy optimization report.

[0096] The following describes the ecological protection compensation policy optimization and evaluation device provided in the embodiments of this application. The ecological protection compensation policy optimization and evaluation device described below and the ecological protection compensation policy optimization and evaluation method described above can be referred to and correspond to each other.

[0097] In one embodiment, such as Figure 3 As shown, Figure 3 This application provides a schematic diagram of an ecological protection compensation policy optimization and evaluation device according to an embodiment of the present application. The present application also provides an ecological protection compensation policy optimization and evaluation device, including a data acquisition module 210, a value quantification module 220, a market simulation module 230, a scheme generation module 240, and an optimization and evaluation module 250, specifically comprising the following: The data acquisition module 210 is used to generate an ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area, and to acquire ecological and economic data of the target area from the regional economic management system. The value quantification module 220 is used to quantify the value of each ecological service in the target area based on the ecological parameter sequence and ecological economic data, to obtain the ecological service value index, and to determine the ecological value conversion rate of the target area based on the ecological economic data and the ecological service value index.

[0098] The market simulation module 230 is used to construct a market equilibrium simulation model of the target area based on the ecological service value index and the ecological value conversion rate, and to solve the state of the market equilibrium simulation model to obtain the market equilibrium state parameters.

[0099] The scheme generation module 240 is used to obtain ecological constraint factors based on ecological parameter sequences and ecological value conversion rate assessment, and to generate multiple compensation policy optimization schemes based on market equilibrium state parameters and ecological constraint factors.

[0100] The optimization evaluation module 250 is used to predict the improvement of ecological parameters and simulate market equilibrium for each compensation strategy optimization scheme, obtain the predicted state parameters of each compensation strategy optimization scheme, evaluate the effect of each predicted state parameter, and obtain a compensation policy optimization evaluation report.

[0101] In the above embodiments, during policy optimization evaluation, an ecological parameter sequence can be generated first based on remote sensing image data and ecological monitoring data collected from the target area, and ecological and economic data of the target area can be obtained from the regional economic management system, thereby comprehensively reflecting the real-time ecological status of the target area. Then, the value of each ecological service in the target area can be quantified based on the ecological parameter sequence and ecological and economic data to obtain an ecological service value index. This can accurately measure the actual value of the ecological environment. Based on the ecological and economic data and the ecological service value index, the ecological value conversion rate of the target area can be determined to reflect the balance between ecological protection and economic development. Therefore, a market equilibrium simulation model for the target area can be constructed based on the ecosystem service value index and the ecosystem value conversion rate. The market equilibrium state parameters obtained by solving the state of this model can predict market dynamics in advance. Subsequently, ecological constraints can be assessed based on the ecosystem parameter sequence and the ecosystem value conversion rate. Multiple compensation policy optimization schemes can be generated based on the market equilibrium state parameters and the ecosystem constraints. The generated optimization schemes can fully consider the constraints of the ecological environment on policy implementation. By predicting the improvement of ecosystem parameters and simulating market equilibrium for each scheme, and evaluating the effects of each predicted state parameter obtained from the simulation, the resulting compensation policy optimization evaluation report can be used to guide the dynamic optimization of compensation policies, thereby improving the long-term effectiveness and accuracy of the ecological protection compensation mechanism.

[0102] In one embodiment, the data acquisition module 210 may include: The parameter acquisition submodule is used to collect raw ecological parameters in the target area; the raw ecological parameters include remote sensing image data and ecological monitoring data.

[0103] The parameter processing submodule is used to clean the original ecological parameters and perform spatiotemporal alignment on the cleaned original ecological parameters to form an ecological parameter sequence.

[0104] In one embodiment, the value quantification module 220 may include: The service identification submodule is used to identify multiple ecological services covered in the target area based on ecological parameter sequences and ecological economic data, and to determine the value quantification model corresponding to each ecological service.

[0105] The model quantization submodule is used to extract the input parameters corresponding to each value quantification model from the ecological parameter sequence and ecological economic data, and input each input parameter into the corresponding value quantification model to quantify the value and obtain the service value of each ecological service.

[0106] The weighted summation submodule is used to determine the evaluation coefficient corresponding to each ecosystem service, and to use each evaluation coefficient to perform a weighted summation of the service value of each ecosystem service to obtain the ecosystem service value index of the target area.

[0107] In one embodiment, the value quantification module 220 may further include: The data extraction submodule is used to extract market price data and product output data of various ecological products from the ecological economic data, and to determine the market value of ecological products in the target area based on the market price data and product output data.

[0108] The ratio calculation submodule is used to calculate the ratio between the market value of ecological products and the value index of ecological services to obtain the ecological conversion rate of the target area.

[0109] In one embodiment, the market simulation module 230 may include: The function construction submodule is used to construct an ecological supply function using the ecological service value index and a market demand function using the ecological value conversion rate.

[0110] The equation-simultaneous submodule is used to perform simultaneous equations on the ecological supply function and the market demand function to obtain a market equilibrium simulation model for the target region.

[0111] In one embodiment, the market simulation module 230 may further include: The model solver submodule is used to solve for the equilibrium price point of the market equilibrium simulation model using Newton's iteration method.

[0112] The function solver submodule is used to solve the ecological supply function using the equilibrium price point to obtain the market transaction scale.

[0113] The product operation submodule is used to perform a product operation on the equilibrium price point and the market transaction size to obtain the market value size.

[0114] The parameter combination submodule is used to combine the equilibrium price point, market transaction size, and market value size to form the market equilibrium state parameters.

[0115] In one embodiment, the solution generation module 240 may include: The indicator matching submodule is used to match ecological constraint factors with indicators in the policy scenario library to obtain compensation indicators and the basic compensation standards for the compensation indicators.

[0116] The compensation analysis submodule is used to perform compensation analysis on the basic compensation standard based on market equilibrium state parameters to obtain the compensation budget range.

[0117] The scheme generation submodule is used to generate multiple compensation policy optimization schemes corresponding to compensation indicators within the compensation budget range using a random search algorithm.

[0118] In one embodiment, the optimization evaluation module 250 may include: The optimal labeling submodule is used to label the best predicted state parameter among all predicted state parameters as the optimal state parameter, and to label the compensation strategy optimization scheme corresponding to the optimal state parameter as the optimal compensation policy optimization scheme.

[0119] The comparative analysis submodule is used to compare and analyze the optimal state parameters with the market equilibrium state parameters to obtain the analysis results.

[0120] The report generation submodule is used to generate an evaluation report on the optimization of the compensation policy based on the optimal compensation policy optimization scheme, optimal state parameters, market equilibrium state parameters, and analysis results.

[0121] In one embodiment, this application also provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the ecological protection compensation policy optimization evaluation method as described in any of the above embodiments.

[0122] In one embodiment, this application also provides a computer device storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the ecological protection compensation policy optimization evaluation method as described in any of the above embodiments.

[0123] Indicatively, such as Figure 4 As shown, Figure 4 This is a schematic diagram of the internal structure of a computer device 300 provided in an embodiment of this application. The computer device 300 can be provided as a server. (Refer to...) Figure 4 The computer device 300 includes a processing component 302, which further includes one or more processors, and memory resources represented by memory 301 for storing instructions, such as application programs, that can be executed by the processing component 302. The application programs stored in memory 301 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 302 is configured to execute instructions to perform the ecological protection compensation policy optimization assessment method of any of the above embodiments.

[0124] The computer device 300 may also include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 may operate on an operating system stored in memory 301, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or similar.

[0125] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0126] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0127] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0128] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing and evaluating ecological protection compensation policies, characterized in that, The method includes: An ecological parameter sequence is generated based on remote sensing image data and ecological monitoring data collected from the target area, and ecological and economic data of the target area are obtained from the regional economic management system. The value of each ecological service in the target area is quantified based on the ecological parameter sequence and the ecological economic data to obtain an ecological service value index, and the ecological value conversion rate of the target area is determined based on the ecological economic data and the ecological service value index. Based on the ecological service value index and the ecological value conversion rate, a market equilibrium simulation model for the target area is constructed, and the market equilibrium simulation model is solved to obtain the market equilibrium state parameters. Based on the ecological parameter sequence and the ecological value conversion rate assessment, ecological constraint factors are obtained, and multiple compensation policy optimization schemes are generated according to the market equilibrium state parameters and the ecological constraint factors. For each compensation strategy optimization scheme, ecological parameter improvement prediction and market equilibrium simulation are performed to obtain the predicted state parameters of each compensation strategy optimization scheme. The effect of each predicted state parameter is evaluated, and a compensation policy optimization evaluation report is generated.

2. The method for optimizing and evaluating ecological protection compensation policies according to claim 1, characterized in that, The process of generating an ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area includes: Collect raw ecological parameters in the target area; the raw ecological parameters include remote sensing image data and ecological monitoring data; The original ecological parameters are cleaned and then spatiotemporally aligned to form an ecological parameter sequence.

3. The method for optimizing and evaluating ecological protection compensation policies according to claim 1, characterized in that, The step of quantifying the value of each ecosystem service in the target area based on the ecological parameter sequence and the ecoeconomic data to obtain an ecosystem service value index includes: Based on the ecological parameter sequence and the ecoeconomic data, multiple ecological services covered in the target area are identified, and a value quantification model corresponding to each ecological service is determined. The input parameters corresponding to each value quantification model are extracted from the ecological parameter sequence and the ecological economic data, and each input parameter is input into the corresponding value quantification model for value quantification to obtain the service value of each ecological service. The evaluation coefficient for each ecosystem service is determined, and the service value of each ecosystem service is weighted and summed using each evaluation coefficient to obtain the ecosystem service value index of the target area.

4. The method for optimizing and evaluating ecological protection compensation policies according to claim 1, characterized in that, The step of determining the ecological value conversion rate of the target area based on the ecological economic data and the market value of the ecological products includes: The market price data and product output data of each ecological product in the ecological economic data are extracted, and the market value of the ecological products in the target area is determined based on the market price data and the product output data. The ecological conversion rate of the target area is obtained by calculating the ratio between the market value of the ecological products and the ecological service value index.

5. The method for optimizing and evaluating ecological protection compensation policies according to claim 1, characterized in that, The market equilibrium simulation model for the target region, constructed based on the ecosystem service value index and the ecosystem value conversion rate, includes: An ecological supply function is constructed using the ecological service value index, and a market demand function is constructed using the ecological value conversion rate. By simultaneously solving the ecological supply function and the market demand function, a market equilibrium simulation model for the target region is obtained.

6. The method for optimizing and evaluating ecological protection compensation policies according to claim 5, characterized in that, The process of solving the market equilibrium simulation model to obtain market equilibrium state parameters includes: The equilibrium price point of the market equilibrium simulation model is solved using Newton's iterative method. The market transaction size is obtained by solving the ecological supply function using the equilibrium price point. The market value is obtained by multiplying the equilibrium price point and the market transaction size. The equilibrium price point, the market transaction volume, and the market value volume are combined to form the market equilibrium state parameters.

7. The method for optimizing and evaluating ecological protection compensation policies according to claim 1, characterized in that, The process of generating multiple compensation policy optimization schemes based on the market equilibrium parameters and the ecological constraints includes: The ecological constraint factors are matched with indicators in the policy scenario database to obtain compensation indicators and the basic compensation standards for the compensation indicators. Based on the market equilibrium parameters, a compensation analysis is performed on the basic compensation standard to obtain the compensation budget range; A random search algorithm is used to generate multiple compensation policy optimization schemes corresponding to the compensation indicators within the compensation budget range.

8. The method for optimizing and evaluating ecological protection compensation policies according to claim 1, characterized in that, The process of evaluating the effectiveness of each predicted state parameter and generating a compensation policy optimization evaluation report includes: The optimal predicted state parameter among all predicted state parameters is marked as the optimal state parameter, and the compensation strategy optimization scheme corresponding to the optimal state parameter is marked as the optimal compensation policy optimization scheme. The optimal state parameters are compared and analyzed with the market equilibrium state parameters to obtain the analysis results; An evaluation report on the optimization of the compensation policy is generated based on the optimal compensation policy optimization scheme, the optimal state parameters, the market equilibrium state parameters, and the analysis results.

9. An ecological protection compensation policy optimization and evaluation device, characterized in that, include: The data acquisition module is used to generate an ecological parameter sequence based on remote sensing image data and ecological monitoring data collected from the target area, and to acquire ecological and economic data of the target area from the regional economic management system. The value quantification module is used to quantify the value of each ecological service in the target area based on the ecological parameter sequence and the ecological economic data to obtain an ecological service value index, and to determine the ecological value conversion rate of the target area based on the ecological economic data and the ecological service value index. The market simulation module is used to construct a market equilibrium simulation model for the target area based on the ecological service value index and the ecological value conversion rate, and to solve the state of the market equilibrium simulation model to obtain market equilibrium state parameters. The scheme generation module is used to obtain ecological constraint factors based on the ecological parameter sequence and the ecological value conversion rate assessment, and to generate multiple compensation policy optimization schemes based on the market equilibrium state parameters and the ecological constraint factors. The optimization evaluation module is used to predict the improvement of ecological parameters and simulate market equilibrium for each compensation strategy optimization scheme, obtain the predicted state parameters of each compensation strategy optimization scheme, evaluate the effect of each predicted state parameter, and obtain a compensation policy optimization evaluation report.

10. A storage medium, characterized in that: The storage medium stores computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the ecological protection compensation policy optimization evaluation method as described in any one of claims 1 to 8.

11. A computer device, characterized in that, include: One or more processors, and memory; The memory stores computer-readable instructions, which, when executed by the one or more processors, perform the steps of the ecological protection compensation policy optimization evaluation method as described in any one of claims 1 to 8.

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