Configuration optimization system and method for water and soil conservation type protection forest

Abstract

The invention provides a configuration optimization system and method for a water and soil conservation type protection forest, and relates to the technical field of protection forest configuration, and the system comprises an information collection module which is used for obtaining multi-source data of a target area; the information matching module is used for screening a candidate tree species set; the grid generation module is used for dividing a region into a plurality of evaluation unit grids with geographic attributes; the configuration strategy generation module is used for generating an initial configuration scheme; the strategy optimization module is used for constructing a water and soil conservation benefit evaluation model and generating a recommendation configuration scheme with optimal comprehensive benefits; and the man-machine interaction module is used for finely adjusting and confirming the recommended configuration scheme. According to the invention, through multi-module cooperation and intelligent analysis, the improvement of protection forest configuration from extensive experience decision making to scientific and accurate planning is realized, the scientificity, high efficiency and sustainability of protection forest construction are significantly improved, and a powerful decision support tool is provided for the synergistic interaction of water and soil loss treatment and ecological system service functions.

Description

Technical Field

[0001] This invention relates to the field of shelterbelt configuration technology, and in particular to a configuration optimization system and method for soil and water conservation shelterbelts. Background Technology

[0002] Soil and water conservation shelterbelts are a key biological measure for preventing regional soil erosion and improving the ecological environment. Their core objective is to effectively slow surface runoff, conserve water and soil, and maintain water resources through scientific vegetation configuration, while also considering certain ecological and economic values. The planning and construction of such shelterbelts is a complex systems engineering project, and its technical practice deeply depends on an accurate understanding of the natural geographical conditions of the target area. This involves the integrated analysis of multi-scale, multi-source data, including site factors such as regional topography, meteorology, hydrology, soil physicochemical properties, and existing vegetation conditions. Simultaneously, the decision-making process must closely integrate the ecological characteristics of tree species to ensure that the selected tree species are suitable for the site conditions. Traditional configuration methods largely rely on the practical experience and historical patterns of experts in the field, and their technical foundation is built upon the interdisciplinary integration of soil and water conservation, ecology, forestry, and soil science. Furthermore, the development of spatial information technologies such as geographic information systems, remote sensing technology, and process models has provided new technological possibilities for refined planning from macro-regional assessments to micro-site units.

[0003] The optimization of typical shelterbelt configurations relies heavily on human experience and qualitative judgment, which has systemic flaws. It struggles to comprehensively and accurately reflect the spatial heterogeneity of site conditions such as topography, soil, and vegetation within a region, resulting in insufficient basic data support. At the decision-making level, tree species selection often depends on historical experience or simply applying established guidelines, lacking refined coupling analysis with specific site conditions. This can easily lead to inappropriate species selection or a monotonous configuration, affecting stand stability and ecological function. The use of static, fixed configuration patterns often makes it difficult to maximize overall benefits and to dynamically respond to complex changes in natural geographical conditions.

[0004] To address the shortcomings of the existing technology, this technical solution proposes a configuration optimization system and method for soil and water conservation shelterbelts. Summary of the Invention

[0005] This invention provides a configuration optimization system and method for soil and water conservation shelterbelts to address the deficiencies in the prior art.

[0006] On one hand, the present invention provides a configuration optimization system for soil and water conservation shelterbelts, comprising: The information acquisition module is used to acquire multi-source data of the target area, perform preprocessing, and output comprehensive regional data, which includes topographic and geomorphological data. The information matching module is used to match comprehensive regional data with a preset tree species ecological characteristics database to select a set of candidate tree species suitable for growth in the target area. The grid generation module is used to divide a region into several evaluation unit grids with geographical attributes based on topographic data. The configuration strategy generation module is used to allocate initial tree species, planting density and spatial layout to each evaluation unit grid from the candidate tree species set according to the site conditions of each evaluation unit grid, and generate an initial configuration scheme. The strategy optimization module is used to construct a soil and water conservation benefit assessment model, simulate and evaluate the benefits of the initial configuration scheme, and iteratively adjust the configuration parameters through a multi-objective optimization algorithm to generate a recommended configuration scheme with optimal comprehensive benefits; wherein, the comprehensive benefits include at least soil erosion control benefits, water conservation benefits, and ecological and economic benefits; The human-computer interaction module is used to visually display recommended configuration schemes, simulation and benefit evaluation results, and receive user feedback and adjustment instructions based on the actual situation, so as to fine-tune and confirm the recommended configuration schemes.

[0007] According to the present invention, a configuration optimization system for soil and water conservation shelterbelts includes an information acquisition module comprising: a remote sensing data acquisition unit, a ground survey unit, and a data processing unit; the remote sensing data acquisition unit is used to acquire large-scale vegetation cover, land use type, and topographic elevation information from satellite and airborne remote sensing platforms, and outputs a remote sensing dataset; the ground survey unit is used to collect data on soil physicochemical properties, groundwater level, and existing vegetation community structure, and outputs a ground feature dataset; the data processing unit is used to preprocess the remote sensing dataset and the ground feature dataset, and output comprehensive regional data.

[0008] According to the present invention, a configuration optimization system for soil and water conservation shelterbelts includes an information matching module comprising: a site condition analysis unit, a tree species suitability assessment unit, and a candidate set generation unit. The site condition analysis unit is used to analyze the site type based on the geographical attributes of the target area. The tree species suitability assessment unit is used to couple the site type with the suitable growth conditions of tree species in the tree species ecological characteristic database to calculate the suitability index of each tree species under different site types. The candidate set generation unit is used to screen tree species that meet the suitability index based on a preset suitability threshold to form a differentiated candidate tree species set for different site types.

[0009] According to the configuration optimization system for soil and water conservation shelterbelts provided by the present invention, the step of calculating the suitability index by the tree species suitability assessment unit includes: The suitable range of a specific tree species for a single site factor is obtained from the tree species ecological characteristics database. Based on the suitable range, the membership function corresponding to the site factor is constructed. The single-factor suitability of the tree species for this site factor within the evaluation unit grid is calculated. The single-factor suitability value range is [0,1]. Weights are assigned to each site factor; based on the weighted average method, the suitability of all single factors and their weights are integrated to calculate the comprehensive suitability index of the tree species within the evaluation unit grid.

[0010] According to the present invention, a configuration optimization system for soil and water conservation shelterbelts includes a grid generation module comprising: a topographic factor extraction unit, a grid division unit, and an attribute assignment unit; the topographic factor extraction unit is used to extract topographic factors such as slope, slope length, runoff accumulation, and topographic humidity index based on a digital elevation model; the grid division unit is used to dynamically divide the grid based on topographic data to generate irregular evaluation unit grids; and the attribute assignment unit is used to assign each evaluation unit grid its corresponding topographic factor value and soil and meteorological attribute values ​​extracted from comprehensive regional data.

[0011] According to the present invention, a configuration optimization system for soil and water conservation shelterbelts includes a configuration strategy generation module comprising: a rule base, a strategy reasoning unit, and a scheme integration unit. The rule base stores configuration rules based on the principles of soil and water conservation ecology, including rules for pairing pioneer tree species with associated tree species, rules for mixing deep-rooted and shallow-rooted tree species, and minimum vegetation cover requirements under different erosion intensities. The strategy reasoning unit, based on the site conditions of each evaluation unit grid, calls the configuration rules in the rule base to automatically infer the recommended tree species combination, initial planting density, and row / belt configuration pattern for that grid. The scheme integration unit spatially integrates the initial configurations of all evaluation unit grids and checks the ecological coordination between adjacent grids to form a complete initial configuration scheme.

[0012] According to the present invention, a configuration optimization system for soil and water conservation shelterbelts is provided. The strategy optimization module includes a simulation unit, an evaluation unit, and an optimization unit. The simulation unit is used to simulate changes in soil erosion, surface runoff, and vegetation biomass in the target area under different configuration schemes based on a process model, and outputs the membrane simulation results. The evaluation unit is used to calculate the comprehensive benefit score of each scheme under a preset evaluation index system based on the simulation results. The optimization unit is used to automatically adjust the tree species composition, density, and spatial structure parameters of each grid using a multi-objective optimization algorithm with the goal of maximizing the comprehensive benefit score, and outputs a recommended configuration scheme.

[0013] According to the configuration optimization system for soil and water conservation shelterbelts provided by the present invention, the steps for the evaluation unit to calculate the comprehensive benefit score include: Construct an evaluation index system, including multiple quantitative indicators for soil erosion control benefits, water conservation benefits, and ecological and economic benefits; The simulation results of each scheme output by the simulation unit are quantified to obtain the corresponding quantitative indicators for each scheme; the normalization method is used to eliminate the dimensional differences of each quantitative indicator and output the normalized quantitative indicators. The weights of each quantitative indicator in the comprehensive benefit evaluation were determined using the analytic hierarchy process. Based on the normalized quantitative indicators and indicator weights, the comprehensive benefit score of each configuration scheme is calculated by linear weighted summation.

[0014] According to the configuration optimization system for soil and water conservation shelterbelts provided by the present invention, the step of the optimization unit outputting a recommended configuration scheme includes: The initial configuration scheme is encoded into an initial population for a multi-objective optimization algorithm, where each individual represents a complete configuration scheme; The simulation and evaluation units are invoked to calculate the comprehensive benefit score of each individual in the current population; based on non-dominated ordering and crowding calculation, the Pareto optimal solution set is selected. Based on preset decision preferences, a recommended configuration scheme is output from the final Pareto optimal solution set.

[0015] A method for optimizing the configuration of soil and water conservation shelterbelts according to the present invention includes: Acquire multi-source data of the target area, perform preprocessing, and output comprehensive regional data, which includes topographic and geomorphological data; By matching comprehensive regional data with a pre-set database of tree species ecological characteristics, a set of candidate tree species suitable for growth in the target area is selected. Based on topographic data, the region is divided into several evaluation unit grids with geographical attributes. Based on the site conditions of each evaluation unit grid, the initial tree species, planting density and spatial layout are assigned to each evaluation unit grid from the candidate tree species set to generate an initial configuration scheme; A soil and water conservation benefit assessment model is constructed to simulate and evaluate the benefits of the initial configuration scheme. The configuration parameters are iteratively adjusted through a multi-objective optimization algorithm to generate a recommended configuration scheme with optimal comprehensive benefits. The system provides a visual representation of recommended configuration schemes, simulation and benefit evaluation results, and receives user feedback and adjustment instructions based on actual conditions, allowing for fine-tuning and confirmation of the recommended configuration schemes.

[0016] This invention provides a system and method for optimizing the configuration of shelterbelts for soil and water conservation. Through multi-module collaboration and intelligent analysis, it achieves a leap from extensive experience-based decision-making to scientific and precise planning in shelterbelt configuration. By integrating multi-source data and conducting precise site analysis based on the ecological characteristics of tree species, the scientific nature and regional suitability of tree species selection are ensured. By decomposing macro-regions into micro-evaluation units and automatically generating preliminary configuration schemes according to ecological rules, a foundation for refined spatial management is laid. By constructing a soil and water conservation benefit assessment model and combining it with a multi-objective optimization algorithm, the initial scheme is simulated and iterated to optimize comprehensive benefits, thereby outputting a recommended scheme that maximizes comprehensive benefits, effectively overcoming the limitations of traditional methods that sometimes overlook certain aspects. This significantly improves the scientific nature, efficiency, and sustainability of shelterbelt construction, providing a powerful decision support tool for the synergistic effect of soil erosion control and ecosystem service functions. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention 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 some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of a configuration optimization system for soil and water conservation shelterbelts provided in an embodiment of the present invention; Figure 2 This is a flowchart of a method for optimizing the configuration of soil and water conservation shelterbelts, provided by an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] Example 1: The following is combined with Figures 1-2 This invention describes a configuration optimization system and method for soil and water conservation shelterbelts.

[0021] like Figures 1-2 As shown in the figure, an embodiment of the present invention provides a configuration optimization system for soil and water conservation shelterbelts, comprising: an information acquisition module, an information matching module, a grid generation module, a configuration strategy generation module, a strategy optimization module, and a human-computer interaction module.

[0022] The information acquisition module is used to acquire multi-source data of the target area, mainly including remote sensing data, ground-measured data, and basic geographic information data. It then performs preprocessing and outputs comprehensive regional data, which includes topographic and geomorphological data.

[0023] The information acquisition module includes a remote sensing data acquisition unit, a ground survey unit, and a data processing unit. The remote sensing data acquisition unit is used to acquire large-scale vegetation cover, land use types, and topographic elevation information from satellite and airborne remote sensing platforms, outputting a remote sensing dataset. Topographic elevation information is mainly obtained through digital elevation models (DEMs). A DEM is a physical ground model that represents ground elevation using an ordered array of numerical values. It is the foundation of topographic data and can be used to extract topographic factors such as slope, aspect, slope position, and catchment area.

[0024] The ground survey unit is used to collect data on soil physicochemical properties, groundwater levels, and existing vegetation community structure, outputting a ground feature dataset. The data processing unit is used to preprocess the remote sensing dataset and the ground feature dataset, outputting comprehensive regional data. Preprocessing steps mainly include a series of operations such as standardization, denoising, correction, registration, and fusion of the raw data to eliminate errors and inconsistencies and make them meet the requirements of subsequent analysis. For example, radiometric calibration, atmospheric correction, and geometric correction are performed on remote sensing imagery; outlier removal and standardization are performed on ground survey data.

[0025] The information matching module is used to match comprehensive regional data with a preset database of tree species ecological characteristics to select a set of candidate tree species suitable for growth in the target area.

[0026] The information matching module includes a site condition analysis unit, a tree species suitability assessment unit, and a candidate set generation unit. The site condition analysis unit is used to analyze the site type based on the geographical attributes of the target area. The tree species suitability assessment unit is used to couple the site type with the suitable growth conditions of tree species in the tree species ecological characteristics database to calculate the suitability index of each tree species under different site types.

[0027] The steps for calculating the suitability index in the tree species suitability assessment unit include: The suitability range of a specific tree species for a single site factor is obtained from a tree species ecological characteristic database. Based on this suitability range, a membership function corresponding to the site factor is constructed. The single-factor suitability of the tree species for this site factor within the evaluation unit grid is calculated, with the single-factor suitability value ranging from [0,1]. The membership function describes the degree to which the measured value of a site factor belongs to "suitable for the growth of a certain tree species". Commonly used membership functions include upper-type, lower-type, and peak-type. For soil pH, if the optimal range for a certain tree species is [6.0, 7.5], a trapezoidal or triangular membership function can be used, expressed by the formula:

[0028] Where, μ pH This represents the membership degree at a given pH value, i.e., the single-factor fitness, with a value range of [0,1]. a and d represent the lower and upper critical pH values ​​for tree species survival, respectively; values ​​outside these ranges indicate complete unsuitability. b and c represent the lower and upper limits of the optimal pH range for tree species growth, respectively; growth is most suitable within this range.

[0029] Weights are assigned to each site factor. Based on the weighted average method, the overall suitability index of the tree species within the evaluation unit grid is calculated by integrating the suitability of all individual factors and their weights. The formula is as follows:

[0030]

[0031] Among them, S ij w represents the overall suitability index of tree species i in evaluation cell grid j; k It is the weight of the k-th location factor, μ ijk Let be the single-factor fitness (or membership degree) of tree species i in grid j for the k-th site factor, where n is the total number of site factors. This formula is a linear aggregation method based on a weighted average model. Each factor contributes independently to the overall fitness, and the overall fitness is the weighted sum of the fitness of all factors.

[0032] The candidate set generation unit is used to select tree species that meet the suitability index based on a preset suitability threshold, forming a differentiated candidate tree species set for different site types.

[0033] The grid generation module is used to divide a region into several evaluation unit grids with geographical attributes based on topographic data. The evaluation unit grid is the basic spatial unit for the system's analysis, calculation, and decision-making. Unlike regular rectangular grids, this system emphasizes dynamic division based on topography, generating irregular grids.

[0034] The mesh generation module includes a terrain factor extraction unit, a mesh generation unit, and an attribute assignment unit. The terrain factor extraction unit is used to extract terrain factors from slope, slope length, runoff accumulation, and topographic moisture index based on the digital elevation model. The topographic moisture index (TWI) is a commonly used indicator to describe the influence of topography on the spatial distribution of soil moisture, and its formula is expressed as:

[0035] Where α is the upstream catchment area per unit isotropic length, representing the inflow volume; tanβ is the slope, representing the flow velocity. A larger TWI value indicates that the soil moisture conditions at that location are likely to be better.

[0036] Grid division is used to dynamically divide the area based on topographic data, generating irregular evaluation unit grids. Dynamic division methods typically employ hydrological analysis-based approaches, such as identifying valley lines by calculating runoff accumulation and combining this with ridge lines to divide the region into relatively homogeneous slopes or small watersheds as evaluation units. This method ensures that the hydrological processes and soil conditions within each unit are relatively consistent, better conforming to ecological principles.

[0037] The attribute assignment unit is used to assign the corresponding topographic factor value and soil and meteorological attribute values ​​extracted from the integrated regional data to each evaluation unit grid.

[0038] The configuration strategy generation module is used to allocate initial tree species, planting density and spatial layout to each evaluation unit grid from the candidate tree species set according to the site conditions of each evaluation unit grid, and generate an initial configuration scheme.

[0039] The configuration strategy generation module includes a rule base, a strategy reasoning unit, and a scheme integration unit. The rule base stores configuration rules based on soil and water conservation ecology principles. These rules include pairing rules for pioneer tree species and associated tree species, mixed planting rules for deep-rooted and shallow-rooted tree species, and minimum vegetation cover requirements under different erosion intensities. Specifically, these include: In grids with poor site conditions (poor soil, severe erosion), pioneer tree species, such as black locust and sea buckthorn, should be prioritized, accounting for no less than 70%; after the site conditions improve, companion tree species, such as oak and hazelnut, can be introduced.

[0040] On slopes with a gradient greater than 15 degrees, a mixed planting ratio of deep-rooted to shallow-rooted tree species of 6:4 is recommended to simultaneously enhance the vertical anchoring of the soil and the surface erosion resistance.

[0041] Based on the soil erosion intensity level of this grid, including light, moderate, strong, and extremely strong, the minimum canopy coverage requirements that must be achieved in the third year after afforestation are mapped from the rule base, corresponding to 30%, 50%, 70%, and 85%, respectively.

[0042] The strategy reasoning unit, based on the site conditions of each evaluation unit grid, invokes configuration rules from the rule base to automatically infer the recommended tree species combination, initial planting density, and row / belt configuration pattern for that grid. The scheme integration unit spatially integrates the initial configurations of all evaluation unit grids and checks the ecological compatibility between adjacent grids to form a complete initial configuration scheme. Ecological compatibility checks include verifying whether there are shrub or grassland grids serving as buffer zones between high-density arbor grids and bare land grids. If not, the system may suggest adjusting the configuration in the transition zone, establishing a progressive vegetation belt composed of trees, shrubs, and herbs to enhance landscape connectivity and stability.

[0043] The strategy optimization module is used to construct a soil and water conservation benefit assessment model, simulate and evaluate the benefits of the initial configuration scheme, and iteratively adjust the configuration parameters through a multi-objective optimization algorithm to generate a recommended configuration scheme with optimal comprehensive benefits. These comprehensive benefits include at least soil erosion control benefits, water conservation benefits, and ecological and economic benefits.

[0044] The strategy optimization module includes a simulation unit, an evaluation unit, and an optimization unit. The simulation unit, based on a process model, simulates changes in soil erosion, surface runoff, and vegetation biomass in the target area under different configuration schemes, and outputs the simulation results. The process model is a mechanistic distributed hydrological soil erosion model, such as the combination of a modified soil loss equation and a hydrological model. For example, soil erosion A can be calculated based on Rusle: A = R·K·L·S·C·P. Where R is the rainfall erosivity factor, K is the soil erodibility factor, L and S are topographic factors, C is the vegetation cover and management factor, and P is the soil and water conservation measures factor. Different configuration schemes will significantly change the C and P factors.

[0045] The evaluation unit is used to calculate the comprehensive benefit score of each scheme under the preset evaluation index system based on the simulation results.

[0046] The steps for calculating the overall benefit score for the evaluation unit include: An evaluation index system was constructed, including multiple quantitative indicators for soil erosion control benefits, water conservation benefits, and ecological and economic benefits.

[0047] The simulation results of each scheme output by the simulation unit are quantified to obtain the corresponding quantitative indicators for each scheme. A normalization method is used to eliminate the dimensional differences among the quantitative indicators, outputting normalized quantitative indicators. For benefit-type indicators, the normalization formula is expressed as:

[0048] For cost-based indicators, such as soil erosion, the normalization formula is expressed as:

[0049] Where I is the original value of the indicator, I max and I min These are the maximum and minimum values ​​of this indicator across all evaluated schemes, respectively. After normalization, the indicator values ​​I for each type are... norm It is compressed to the [0,1] interval.

[0050] The weights of each quantitative indicator in the comprehensive benefit evaluation are determined using the Analytic Hierarchy Process (AHP). The steps for determining the weights using AHP include: For each indicator at the same level, pairwise comparisons are made, and their relative importance is determined using the 1-9 scale method, forming a judgment matrix A=(a{ij}){n×n}, where a{ij} represents the importance of indicator i relative to indicator j.

[0051] Calculate the largest eigenvalue λ of the judgment matrix A. max And its corresponding eigenvector W. After normalizing the eigenvector W, its components are the weights of each index.

[0052] Calculate the consistency ratio CR = CI / RI, where CI = (λ) max -n) / (n-1) is the consistency index, and RI is the average random consistency index. If CR < 0.1, the consistency of the judgment matrix is ​​considered acceptable, and the weight allocation is reasonable.

[0053] Based on the normalized quantitative indicators and indicator weights, the comprehensive benefit score (Score) for each configuration scheme is calculated through linear weighted summation, expressed by the formula:

[0054] Where M is the total number of evaluation indicators, m is the index of the evaluation indicator, and I... norm,m w is the normalized value of the m-th indicator. m The weight of the m-th evaluation indicator reflects its relative importance in the overall benefit assessment. For example, if windbreak and sand fixation are the primary objectives, the weight w of the soil erosion control-related indicators would be set higher. All weights must satisfy the normalization condition: and .

[0055] The optimization unit aims to maximize the overall benefit score. It uses a multi-objective optimization algorithm to automatically adjust the tree species composition, density, and spatial structure parameters of each grid cell, outputting a recommended configuration scheme. The steps include: The initial configuration scheme is encoded into an initial population for a multi-objective optimization algorithm, where each individual represents a complete configuration scheme.

[0056] The simulation and evaluation units are invoked to calculate the overall benefit score for each individual in the current population. Based on non-dominated ranking and crowding calculation, the Pareto optimal solution set is selected. Non-dominated ranking involves pairwise comparisons of individuals in the population. For example, if Solution 1 is no worse than Solution 2 in all objective benefits and is strictly superior to Solution 2 in at least one objective, then Solution 2 is said to dominate Solution 1. Individuals not dominated by any other individual constitute the first non-dominated layer, i.e., the frontier of the Pareto optimal solution set, and so on. Crowding calculation measures the density of other individuals around an individual within the same non-dominated layer. Higher crowding indicates a sparser solution distribution in the individual's region, which helps maintain population diversity. The calculation formula is typically the sum of the differences in function values ​​between the two adjacent individuals above and below each objective function.

[0057] Based on preset decision preferences, a recommended configuration scheme is output from the final Pareto optimal solution set.

[0058] The human-computer interaction module is used to visually display recommended configuration schemes, simulation and benefit evaluation results, and receive user feedback and adjustment instructions based on actual conditions, allowing for fine-tuning and confirmation of the recommended configuration schemes. The visualization includes showing the spatial distribution of the recommended configuration schemes and the spatial differences in various benefit scores; radar charts comparing the benefits of different schemes; bar charts displaying the area proportions of different tree species; and combining DEM and vegetation models to perform three-dimensional dynamic simulation and walkthrough of the configuration schemes.

[0059] Users can directly provide feedback and fine-tune the recommended solutions on the interactive interface based on their local knowledge and field survey experience. For example, in a grid recommended by the system, if a user knows that there are special soil conditions or existing vegetation, they can manually replace tree species or adjust the density. The user's adjustments will be fed back to the strategy optimization module as new constraints, and the system can perform local re-optimization based on the adjusted solution, achieving closed-loop optimization through human-machine collaboration.

[0060] This embodiment also provides a method for optimizing the configuration of soil and water conservation shelterbelts, including: Acquire multi-source data for the target area, preprocess it, and output comprehensive regional data, which includes topographic and geomorphological data.

[0061] By matching comprehensive regional data with a pre-set database of tree species ecological characteristics, a set of candidate tree species suitable for growth in the target area is selected.

[0062] Based on topographic data, the region is divided into several evaluation unit grids with geographical attributes.

[0063] Based on the site conditions of each evaluation unit grid, an initial tree species, planting density, and spatial layout are assigned to each evaluation unit grid from the candidate tree species set, generating an initial configuration scheme.

[0064] A soil and water conservation benefit assessment model is constructed to simulate and evaluate the benefits of the initial configuration scheme. The configuration parameters are iteratively adjusted through a multi-objective optimization algorithm to generate a recommended configuration scheme with optimal comprehensive benefits.

[0065] The system provides a visual representation of recommended configuration schemes, simulation and benefit evaluation results, and receives user feedback and adjustment instructions based on actual conditions, allowing for fine-tuning and confirmation of the recommended configuration schemes.

[0066] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A configuration optimization system for soil and water conservation shelterbelts, characterized in that, include: The information acquisition module is used to acquire multi-source data of the target area, perform preprocessing, and output comprehensive regional data, which includes topographic data. The information matching module is used to match the comprehensive regional data with a preset tree species ecological characteristics database to select a set of candidate tree species suitable for growth in the target region. The grid generation module is used to divide the region into several evaluation unit grids with geographical attributes based on the terrain and landform data. The configuration strategy generation module is used to allocate initial tree species, planting density and spatial layout to each evaluation unit grid from the candidate tree species set according to the site conditions of each evaluation unit grid, and generate an initial configuration scheme. The strategy optimization module is used to construct a soil and water conservation benefit assessment model, simulate and evaluate the benefits of the initial configuration scheme, and iteratively adjust the configuration parameters through a multi-objective optimization algorithm to generate a recommended configuration scheme with optimal comprehensive benefits; wherein, the comprehensive benefits include at least soil erosion control benefits, water conservation benefits, and ecological and economic benefits; The human-computer interaction module is used to visually display the recommended configuration scheme, simulation and benefit evaluation results, and receive user feedback and adjustment instructions based on the actual situation, so as to fine-tune and confirm the recommended configuration scheme.

2. The configuration optimization system for soil and water conservation shelterbelts according to claim 1, characterized in that, The information acquisition module includes: a remote sensing data acquisition unit, a ground survey unit, and a data processing unit; the remote sensing data acquisition unit is used to acquire large-scale vegetation cover, land use type, and topographic elevation information from satellite and airborne remote sensing platforms, and output a remote sensing dataset; the ground survey unit is used to collect soil physicochemical properties, groundwater level, and existing vegetation community structure data, and output a ground feature dataset; the data processing unit is used to preprocess the remote sensing dataset and the ground feature dataset, and output the comprehensive regional data.

3. The configuration optimization system for soil and water conservation shelterbelts according to claim 2, characterized in that, The information matching module includes: a site condition analysis unit, a tree species suitability assessment unit, and a candidate set generation unit; the site condition analysis unit is used to analyze the site type based on the geographical attributes of the target area; the tree species suitability assessment unit is used to couple the site type with the suitable growth conditions of tree species in the tree species ecological characteristic database to calculate the suitability index of each tree species under different site types; the candidate set generation unit is used to screen tree species that meet the suitability index based on a preset suitability threshold to form a differentiated candidate tree species set for different site types.

4. The configuration optimization system for soil and water conservation shelterbelts according to claim 3, characterized in that, The steps for calculating the suitability index using the tree species suitability assessment unit include: The suitable range of a specific tree species for a single site factor is obtained from the tree species ecological characteristics database, and the membership function corresponding to the site factor is constructed based on the suitable range. The single-factor suitability of the tree species for this site factor within the evaluation unit grid is calculated. The single-factor suitability range is [0,1]. Weights are assigned to each of the site factors; based on the weighted average method, the suitability of all the single factors and their weights are integrated to calculate the comprehensive suitability index of the tree species within the evaluation unit grid.

5. The configuration optimization system for soil and water conservation shelterbelts according to claim 1, characterized in that, The grid generation module includes: a terrain factor extraction unit, a grid division unit, and an attribute assignment unit; the terrain factor extraction unit is used to extract terrain factors from slope, slope length, runoff accumulation, and terrain humidity index based on the digital elevation model; the grid division unit is used to dynamically divide the terrain data to generate irregular evaluation unit grids; the attribute assignment unit is used to assign corresponding terrain factor values ​​and soil and meteorological attribute values ​​extracted from the comprehensive regional data to each evaluation unit grid.

6. The configuration optimization system for soil and water conservation shelterbelts according to claim 1, characterized in that, The configuration strategy generation module includes a rule base, a strategy reasoning unit, and a scheme integration unit. The rule base stores configuration rules based on the principles of soil and water conservation ecology. These rules include rules for pairing pioneer tree species with associated tree species, rules for mixing deep-rooted and shallow-rooted tree species, and minimum vegetation cover requirements under different erosion intensities. The strategy reasoning unit, based on the site conditions of each evaluation unit grid, calls the configuration rules in the rule base to automatically infer the recommended tree species combination, initial planting density, and row / strip configuration pattern for that grid. The scheme integration unit spatially integrates the initial configurations of all evaluation unit grids and checks the ecological coordination between adjacent grids to form a complete initial configuration scheme.

7. The configuration optimization system for soil and water conservation shelterbelts according to claim 1, characterized in that, The strategy optimization module includes a simulation unit, an evaluation unit, and an optimization unit. The simulation unit is used to simulate changes in soil erosion, surface runoff, and vegetation biomass in the target area under different configuration schemes based on a process model, and outputs the membrane simulation results. The evaluation unit is used to calculate the comprehensive benefit score of each scheme under a preset evaluation index system based on the simulation results. The optimization unit is used to automatically adjust the tree species composition, density, and spatial structure parameters of each grid using a multi-objective optimization algorithm with the goal of maximizing the comprehensive benefit score, and outputs the recommended configuration scheme.

8. The configuration optimization system for soil and water conservation shelterbelts according to claim 7, characterized in that, The steps for the evaluation unit to calculate the overall benefit score include: Construct an evaluation index system, including multiple quantitative indicators for soil erosion control benefits, water conservation benefits, and ecological and economic benefits; The simulation results of each scheme output by the simulation unit are quantified to obtain the corresponding quantitative indicators for each scheme; the normalization method is used to eliminate the dimensional differences of each quantitative indicator and output the normalized quantitative indicators. The weights of each quantitative indicator in the comprehensive benefit evaluation are determined by the analytic hierarchy process. Based on the normalized quantitative indicators and the indicator weights, the comprehensive benefit score of each configuration scheme is calculated by linear weighted summation.

9. The configuration optimization system for soil and water conservation shelterbelts according to claim 7, characterized in that, The step of the optimization unit outputting the recommended configuration scheme includes: The initial configuration scheme is encoded into the initial population of the multi-objective optimization algorithm, where each individual represents a complete configuration scheme; The simulation and evaluation units are invoked to calculate the comprehensive benefit score of each individual in the current population; based on non-dominated sorting and crowding calculation, the Pareto optimal solution set is selected. Based on preset decision preferences, the recommended configuration scheme is output from the final Pareto optimal solution set.

10. A method for optimizing the configuration of soil and water conservation shelterbelts, based on a configuration optimization system for soil and water conservation shelterbelts as described in any one of claims 1 to 9, characterized in that, include: Acquire multi-source data of the target area, perform preprocessing, and output comprehensive regional data, which includes topographic data; The comprehensive regional data is matched with a preset tree species ecological characteristics database to select a set of candidate tree species suitable for growth in the target region. Based on the topographic data, the region is divided into several evaluation unit grids with geographical attributes. Based on the site conditions of each evaluation unit grid, an initial tree species, planting density, and spatial layout are assigned to each evaluation unit grid from the candidate tree species set to generate an initial configuration scheme; A soil and water conservation benefit assessment model is constructed to simulate and evaluate the benefits of the initial configuration scheme. The configuration parameters are iteratively adjusted through a multi-objective optimization algorithm to generate a recommended configuration scheme with optimal comprehensive benefits. The system visualizes the recommended configuration scheme, simulation and benefit evaluation results, and receives user feedback and adjustment instructions based on the actual situation, allowing for fine-tuning and confirmation of the recommended configuration scheme.

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