Urban blue-green space biodiversity leisure area planning system integrating accessibility and health benefits

Abstract

The invention relates to the technical field of crossing of urban planning and public health, and discloses an urban blue-green space biodiversity leisure area planning system integrating accessibility and health benefits, which comprises a data integration module used for integrating and managing multi-source regional space data, the multi-source regional space data at least comprises regional biodiversity distribution data, urban land utilization data, traffic network data, population distribution data and social economic data, the blue-green space mental health benefits are accurately quantified, planning is promoted to be transformed to health guidance, and public health values are released; a space-time-economy comprehensive accessibility system is constructed, weak areas and vulnerable groups are accurately identified, and public health service equalization is assisted; planning scheme simulation prediction, quantitative comparison and cost-benefit analysis are supported, experience decision is replaced with scientific data, and scheme demonstration persuasion and decision efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of interdisciplinary technology of urban planning and public health, specifically to a planning system for urban blue-green space biodiversity recreational areas that integrates accessibility and health benefits. Background Technology

[0002] With the acceleration of global urbanization, urban residents face increasingly severe mental health challenges, and the disease burden of mental illnesses such as depression and anxiety continues to increase. Meanwhile, several cutting-edge scientific studies (such as the research published in *Nature Cities*) have confirmed that exposure to biodiverse natural environments has significantly greater positive benefits for mental health than ordinary urban artificial green spaces. This finding provides a solid scientific basis for utilizing natural spaces surrounding cities (such as nature reserves, forest parks, and wetlands, collectively referred to as "blue-green spaces") as a nature-based public health intervention.

[0003] Existing urban planning and natural resource management systems focus on ecological protection or landscape beautification, lacking assessment models that directly quantify biodiversity characteristics into benefits for improving residents' mental health. This results in planning failing to proactively respond to and maximize public health and well-being. Traditional geographic information systems primarily assess spatial distance or time costs, severely neglecting the real access barriers for different income groups due to economic costs such as transportation expenses, exacerbating the unfairness in the enjoyment of natural health resources. Existing tools are insufficient for prospective simulation and quantitative comparison of the potential mental health benefits of different planning intervention programs, leading to decision-making that relies on experience and lacks scientific basis. Furthermore, there is a lack of tools that can automatically link the health outputs of planning projects with their economic costs and compare them against public health economics standards, making it difficult to provide compelling arguments when seeking public resources. Therefore, we propose a planning system for urban blue-green space biodiversity recreational areas that integrates accessibility and health benefits to address these issues. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a planning system for urban blue-green space biodiversity recreational areas that integrates accessibility and health benefits. It solves the problems of existing planning tools that focus on ecological protection or landscape beautification and lack the ability to quantitatively assess health benefits, traditional accessibility assessments that ignore economic costs and exacerbate unequal access to resources, and the lack of forward-looking simulation and economic demonstration functions, and decision-making that relies on experience.

[0005] To achieve the above objectives, this invention provides the following technical solution: a planning system for urban blue-green space biodiversity recreational areas that integrates accessibility and health benefits, comprising: The data integration module is used to integrate and manage multi-source geographic spatial data, which includes at least: regional biodiversity distribution data, urban land use data, transportation network data, population distribution data, and socioeconomic data. The accessibility calculation and analysis module is communicatively connected to the data integration module. It is used to construct a spatiotemporal-economic cost model based on the traffic network data, population distribution data, and socioeconomic data, and to calculate a comprehensive accessibility index from multiple settlements in the city to at least one target biodiversity-rich area. The comprehensive accessibility index includes at least the shortest travel time and the ratio of travel cost to income. The health benefit quantification assessment module communicates with the data integration module and the accessibility calculation and analysis module. It is used to call a preset mental health benefit quantification model, and combine the biodiversity distribution data, population distribution data and comprehensive accessibility indicators to quantify the reduction in mental health disease burden that can be achieved by accessing the target biodiversity-rich area. The disease burden is measured in disability-adjusted life years. The program planning simulation module is communicatively connected to the accessibility calculation and analysis module and the health benefit quantification assessment module. It is used to receive the planned intervention program input by the user, and drive the accessibility calculation and analysis module and the health benefit quantification assessment module to recalculate based on the updated data, simulate and output the changes in the comprehensive accessibility index and the reduction in mental health disease burden after the implementation of the planned intervention program. The cost-benefit analysis module is communicatively connected to the health benefit quantification assessment module and the program planning simulation module, and is used to perform economic analysis based on the planned intervention program and its corresponding health benefit assessment results provided by the program planning simulation module. The visualization output module is used to spatially visualize the comprehensive accessibility index, the reduction in mental health disease burden, and the simulation results of different planning intervention schemes.

[0006] Preferably, the regional biodiversity distribution data integrated by the data integration module specifically includes: real-time or historical species distribution hotspot data obtained from citizen science observation platforms, official protected area boundary data from global or national protected area databases, and key biodiversity area data from ecological research institutions.

[0007] Preferably, the spatiotemporal-economic cost model constructed by the accessibility calculation and analysis module specifically includes the following calculation process: Time cost calculation steps: Based on geographical data reflecting surface traffic resistance, the optimal travel time path from each residential area to the target biodiversity-rich area is calculated using a path optimization algorithm, and the corresponding shortest travel time is obtained. Economic cost calculation steps: Identify the main modes of transportation used in the optimal travel time route, and calculate the direct monetary cost of a single round trip by combining the corresponding fuel price or public transportation fare data; Affordability integration step: The direct monetary cost is correlated with the per capita or household income data of the residential area to calculate the proportion of the cost to the residents' income; The shortest travel time and the ratio of transportation costs to revenue together constitute the comprehensive accessibility index.

[0008] Preferably, the mental health benefit quantification model called by the health benefit quantification assessment module is constructed by meta-analysis of multiple empirical studies on the relationship between natural environment exposure and improvement of depression and anxiety symptoms. The model uses biodiversity level parameters and access frequency parameters predicted based on the comprehensive accessibility index as core input variables.

[0009] Preferably, the planning intervention schemes received by the scheme planning simulation module include at least one of the following types: Construct or optimize pedestrian / bicycle paths between the city and the target area, add or adjust public transportation routes and stations leading to the target area, relax or adjust public access policies and boundaries of specific protected areas, and plan and construct blue-green spaces with high biodiversity in areas with low accessibility.

[0010] Preferably, the scheme planning simulation module is further configured as follows: Based on a preset optimization objective function, multiple candidate intervention plans are automatically generated or iteratively optimized; wherein the optimization objective function is at least one of maximizing the reduction in total mental health disease burden, minimizing the Gini coefficient of health benefits among different socioeconomic groups, or ensuring that the cost of avoiding life-years of disability is below the threshold recommended by the World Health Organization.

[0011] Preferably, the program planning simulation module is configured to separately analyze and output the incremental increase in the overall accessibility of the planned intervention program for predefined vulnerable groups and the incremental reduction in the burden of mental health diseases during the evaluation.

[0012] Preferably, the cost-benefit analysis module is configured to: calculate the cost required to avoid one disability adjustment life year for the planned intervention scheme output by the scheme planning simulation module, compare this cost with a preset reference threshold based on the regional per capita economic level, and generate and output an evaluation conclusion on whether the planned intervention scheme is economical as a public health intervention measure.

[0013] Preferably, the spatial visualization provided by the visualization output module includes displaying the spatial distribution of comprehensive accessibility indicators in the form of a heat map, displaying the reduction in mental health disease burden obtained by residents in different areas in the form of a hierarchical symbol map, and displaying the changes in key indicators before and after the implementation of the planned intervention program in a side-by-side comparison view.

[0014] Preferably, the system is implemented with a distributed service architecture, wherein the data integration module, accessibility calculation and analysis module, and health benefit quantitative assessment module are deployed as backend analysis services; the scheme planning simulation module and visualization output module are deployed as frontend interactive applications, and the frontend and backend interact with each other through standardized interfaces for data and command exchange.

[0015] Beneficial effects This invention provides a planning system for urban blue-green space biodiversity recreational areas that integrates accessibility and health benefits. Compared with existing technologies, it has the following advantages:

[0016] This urban blue-green space biodiversity recreation area planning system, which integrates accessibility and health benefits, directly transforms the biodiversity characteristics of blue-green spaces into measurable reductions in mental health disease burden by integrating biodiversity distribution data and empirical research on mental health. For the first time, it achieves a precise quantitative assessment of health benefits, enabling urban planning to proactively respond to public health needs and make maximizing public health well-being one of its core objectives. This promotes the transformation of blue-green space planning from "ecological orientation" and "landscape orientation" to "health orientation," fully releasing the public health value of blue-green spaces. This system constructs a comprehensive accessibility assessment framework integrating time, space, and economy. By integrating two core indicators—shortest travel time and the ratio of transportation costs to income—it comprehensively reflects the true barriers for different income groups to access biodiversity blue-green spaces. This system can accurately identify areas with weak accessibility and vulnerable groups such as low-income individuals, providing targeted support for planning interventions. It helps formulate equitable solutions such as increasing affordable public transportation and optimizing pedestrian paths, breaking down class barriers to accessing natural health resources and promoting the equalization of public health services.

[0017] This system addresses the shortcomings of existing tools in lacking forward-looking simulation and economic justification capabilities, possessing functions for simulating and predicting intervention plans, quantitative comparison, and cost-benefit analysis. It supports user input or automatic generation of multiple planning schemes, and through data updates and module linkage, accurately predicts the improvement in accessibility and the increase in health benefits after implementation, providing scientific data support for decision-making and replacing traditional experience-based judgments. Simultaneously, based on public health economics standards, it automatically calculates the unit DALY (Daily Average Cost of Avoidance) of the plan and compares it with preset thresholds to generate clear economic conclusions. This ensures that planning schemes have solid quantitative justification when seeking public resources, significantly improving the persuasiveness of the arguments and the efficiency of decision-making. Attached Figure Description

[0018] Figure 1 This is a block diagram of the overall system connection of the present invention. Detailed Implementation

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

[0020] like Figure 1 As shown: A planning system for urban blue-green space biodiversity recreational areas that integrates accessibility and health benefits includes: The data integration module forms the system's data foundation, integrating and managing multi-source geographic spatial data to provide comprehensive and accurate data support for subsequent analysis and calculations in other modules. The multi-source geographic spatial data integrated by this module includes at least the following categories:

[0021] Regional biodiversity distribution data: Specifically, this includes real-time or historical hotspot data of species distribution obtained from citizen science observation platforms (such as observation records and dense distribution area data of species like birds and plants), official protected area boundary data from global or national protected area databases (clearly defining the geographical scope and boundary information of existing protected areas), and key biodiversity area data from ecological research institutions (data on areas with high biodiversity value confirmed by scientific research). Urban land use data: covering the distribution information of various land use types within the city, such as residential land, commercial land, industrial land, transportation land, green space, etc., providing a basis for analyzing the spatial relationship between resident distribution and blue-green space; Transportation network data includes urban road networks (highways, main roads, secondary roads, branch roads, etc.), public transportation routes and station data (buses, subways, light rail, etc.), and pedestrian and bicycle path distribution data, which are used to calculate residents' travel routes, time, and economic costs to target blue-green spaces. Population distribution data: including population size, population density, age structure, gender ratio, etc. in different areas of the city, used to accurately assess the demand for blue-green spaces and the coverage of health benefits for residents in different areas; Socioeconomic data: mainly includes economic data such as per capita income and household income levels in different regions, used to analyze the impact of economic costs on residents' access to blue and green spaces and to assess the fairness of accessibility; The data integration module integrates and standardizes multi-source data from different sources and formats through standardized data interfaces and data cleaning and transformation algorithms to form a unified database, ensuring data consistency, integrity and availability. It is important to note that data is obtained by calling various standardized application programming interfaces (APIs). For example, JSON format data of species observations can be obtained through the eBirdAPI, GML format vector data of official protected areas can be obtained through the OGCWFS service, and GeoTIFF raster data of population distribution from WorldPop can be obtained through HTTP requests.

[0022] The accessibility calculation and analysis module communicates with the data integration module. Based on traffic network data, population distribution data, and socioeconomic data provided by the data integration module, it constructs a spatiotemporal-economic cost model to calculate a comprehensive accessibility index from multiple settlements within the city to at least one target biodiversity-rich area (blue-green space). This module overcomes the limitations of traditional accessibility assessments that focus only on a single dimension, achieving a comprehensive consideration of spatiotemporal and economic costs. Its calculation process specifically includes the following steps:

[0023] Time cost calculation steps: Based on geographical data reflecting the resistance to surface traffic, such as road grade, topography and other factors affecting traffic speed, the optimal travel time path from each residential area to the target biodiversity-rich area is calculated through path optimization algorithms, such as Dijkstra's algorithm and A* algorithm, and the corresponding shortest travel time is obtained. Economic cost calculation steps: Identify the main modes of transportation used for the optimal travel time route, such as walking, cycling, public transportation, subway, private car, etc., and combine the corresponding fuel prices (private car) or public transportation fare data (public transportation, subway, etc.) to calculate the direct monetary cost of a resident's single round trip to the target area; Affordability integration steps: The above direct monetary costs are correlated with per capita or household income data of residential areas to calculate the proportion of the cost to residents' income, thereby reflecting the economic affordability of different income groups to access the target blue-green space; Among them, the shortest travel time and the ratio of transportation costs to income together constitute a comprehensive accessibility indicator, which comprehensively and objectively assesses the ease and fairness of residents' access to target blue-green spaces. It is important to note that, based on a global friction surface dataset and combined with local high-precision road network data, a travel cost weight is assigned to each 1km×1km grid cell. The specific assignment rules are as follows: for example, highway cell weight = 1, main road = 3, secondary road = 5, pedestrian path = 10, water body = 100 (impassable), dense forest = 50. This weight matrix reflects the relative time cost of traversing each grid. Using the grid cost surface as input, the A* path search algorithm is employed to calculate the shortest travel time from each residential area to the target blue-green space. The algorithm's heuristic function is the ratio of Euclidean distance to the maximum travel speed. For each optimal path, the system infers the main transportation mode combination based on the grid weight types it passes through. For example, if more than 80% of the path consists of grids with weights of 1-3, it is inferred to be "driving-dominated". The economic cost calculation formula is as follows:

[0024] This refers to the driving distance. The local fuel price per unit. This represents the vehicle's average fuel consumption. The fare for a section of public transportation; The health benefit quantification assessment module communicates with the data integration module and the accessibility calculation and analysis module. It is used to invoke a pre-defined mental health benefit quantification model, combining biodiversity distribution data, population distribution data, and comprehensive accessibility indicators to quantify the reduction in mental health disease burden that can be achieved by accessing target biodiversity-rich areas. Disease burden is measured using disability-adjusted life years (DALYs), a core internationally accepted indicator for measuring disease burden that comprehensively reflects the mortality and disability impacts caused by disease.

[0025] The mental health benefit quantification model invoked in this module was constructed through meta-analysis of multiple empirical studies on the relationship between natural environmental exposure and the improvement of depression and anxiety symptoms, thus possessing a solid scientific basis. The model uses a biodiversity level parameter (reflecting the richness of biodiversity in the target blue-green space) and an access frequency parameter predicted based on a comprehensive accessibility index (higher accessibility generally corresponds to higher visit frequency) as core input variables. The model calculates the reduction in mental health burden due to visits to the target blue-green space for residents in different regions.

[0026] It should be noted that this module calls a dose-response model calibrated by meta-analysis, the specific form of which is: Adjust life years to predict reduced disability; The biodiversity index of the target area; , The aforementioned accessibility indicators; P represents the population of the residential area; Parameter calibration: The model parameters (α,λ,κ,ω,η,ξ,ρ) were determined by fitting data from multiple empirical studies, including those published in Nature Cities, using the nonlinear least squares method (Levenberg-Marquardt algorithm). The program planning simulation module communicates with the accessibility calculation and analysis module and the health benefit quantitative assessment module, mainly realizing the functions of inputting, automatically generating, simulating, analyzing and optimizing planned intervention programs, specifically including the following two aspects: The plan includes at least one of the following types: constructing or optimizing pedestrian / bicycle paths between the city and the target area; adding or adjusting public transportation routes and stations leading to the target area; relaxing or adjusting public access policies and boundaries of specific protected areas; and planning and constructing blue-green spaces with high biodiversity in areas with low accessibility. Based on a preset optimization objective function, multiple candidate planning intervention schemes are automatically generated or iteratively optimized. The optimization objective function is at least one of the following:

[0027] Maximize the reduction in the total mental health burden, minimize the Gini coefficient of health benefits among different socioeconomic groups, and ensure that the cost per unit of disability-adjusted life years is below the threshold recommended by the World Health Organization. Meanwhile, during the evaluation, the program planning simulation module is configured to separately analyze and output the overall improvement in accessibility and the incremental reduction in mental health burden of the planned intervention program for predefined vulnerable groups (such as low-income groups, the elderly, and people with disabilities), focusing on the interests of vulnerable groups and ensuring the fairness and inclusiveness of the program. After receiving user input or automatically generating a planned intervention plan, the scheme planning simulation module drives the accessibility calculation and analysis module and the health benefit quantitative assessment module to recalculate based on updated data (such as traffic network data after adding new transportation routes, biodiversity distribution data after creating new blue-green spaces, etc.), simulates and outputs the changes in comprehensive accessibility indicators and the reduction in mental health disease burden after the implementation of the planned intervention plan, and provides data support for scheme comparison. The cost-benefit analysis module communicates with the health benefit quantification assessment module and the program planning simulation module. It is used to conduct economic analysis based on the planned intervention program and its corresponding health benefit assessment results provided by the program planning simulation module, and to provide a basis for the feasibility and priority ranking of the planning program. The core function of the cost-benefit analysis module is to calculate the cost required to avoid one disability-adjusted life year (DALY) for each planned intervention scheme output by the scheme planning simulation module. This cost is then compared with a preset reference threshold based on the region's per capita economic level, such as the cost threshold recommended by the World Health Organization or the average unit cost of similar public health projects in the region. Based on this comparison, an evaluation conclusion on the economic viability of the planned intervention scheme as a public health intervention measure is generated and output. If the cost to avoid one DALY is lower than the reference threshold, the scheme is considered to have good economic viability; otherwise, it is considered insufficiently economical and requires further optimization and adjustment.

[0028] The visualization output module spatially visualizes the comprehensive accessibility indicators, the reduction in the burden of mental health disorders, and the simulation results of different planned intervention programs. It presents the analysis results in an intuitive and easy-to-understand manner, facilitating quick comprehension and decision-making for users. The module offers the following spatial visualization formats:

[0029] The spatial distribution of comprehensive accessibility indicators is displayed in the form of a heat map: different shades of color represent the level of comprehensive accessibility, with darker colors indicating better accessibility and lighter colors indicating poorer accessibility, intuitively presenting the differences in accessibility of target blue-green spaces for residents in different areas of the city. The reduction in mental health disease burden (DALY) achieved by residents in different regions is displayed in the form of a hierarchical symbol diagram: the size of the symbol represents the amount of reduction in DALY, and the larger the symbol, the more significant the mental health benefits achieved by residents in that region, clearly showing the spatial distribution pattern of health benefits; The map displays the changes in key indicators before and after the implementation of the planning intervention program in a side-by-side comparative view: the distribution of comprehensive accessibility and health benefits before implementation is compared with the corresponding distribution after implementation, which intuitively presents the improvement brought about by the planning intervention program and helps users quickly evaluate the effectiveness of the program. This system is implemented using a distributed service architecture. The data integration module, accessibility calculation and analysis module, and health benefit quantitative assessment module are deployed as backend analysis services, responsible for core business logic such as data processing and model calculation. The scheme planning simulation module and visualization output module are deployed as frontend interactive applications, providing user operation interface and result display functions. The frontend and backend interact with each other through standardized interfaces to ensure the system's flexibility, scalability, and ease of use.

[0030] In this implementation plan: First, the data integration module collects multi-source data such as regional biodiversity distribution data, urban transportation networks, population distribution, and socioeconomic data through standardized interfaces. After cleaning and transformation, a unified structured database is constructed to provide high-quality data support for subsequent analysis. Next, the accessibility calculation and analysis module calls upon transportation, population, and socioeconomic data to construct a spatiotemporal-economic cost model. The A* path optimization algorithm is used to calculate the shortest travel time from settlements to biodiversity hotspots. Combining the monetary costs corresponding to transportation modes with residents' income data, the proportion of transportation costs to income is derived, forming a comprehensive accessibility index. Subsequently, the health benefit quantification and assessment module calls upon biodiversity data, population data, and the comprehensive accessibility index. Based on a psychological health benefit quantification model constructed from cutting-edge research such as *Nature Cities*, using biodiversity levels and access frequency as core inputs, it quantifies the reduction in the psychological health burden (measured by DALYs) that residents can achieve by visiting the target area. The scheme planning and simulation module receives user input or automatically generates planning intervention schemes. After updating the data, it drives the first two modules to recalculate, simulating the changes in indicators after the scheme implementation, while focusing on analyzing the incremental benefits to vulnerable groups. The cost-benefit analysis module calculates the DALY avoidance cost per unit for each scheme and compares it with preset thresholds to generate economic conclusions. Finally, the visualization output module uses heatmaps, hierarchical symbol diagrams, and other formats to visualize accessibility, health benefits, and scheme comparison results, providing intuitive support for planning decisions.

[0031] This plan, by integrating biodiversity distribution data with empirical research on mental health, directly transforms the biodiversity characteristics of blue-green spaces into measurable reductions in the burden of mental health diseases, achieving for the first time a precise quantitative assessment of health benefits. This enables urban planning to proactively respond to public health needs, making the maximization of public health well-being one of its core objectives, and promoting the transformation of blue-green space planning from "ecological orientation" and "landscape orientation" to "health orientation," fully releasing the public health value of blue-green spaces. This system constructs a comprehensive accessibility assessment framework integrating time, space, and economy. By integrating two core indicators—shortest travel time and the ratio of transportation costs to income—it comprehensively reflects the true barriers for different income groups to access biodiversity blue-green spaces. This system can accurately identify areas with weak accessibility and vulnerable groups such as low-income individuals, providing targeted support for planning interventions. It helps formulate equitable solutions such as increasing affordable public transportation and optimizing pedestrian paths, breaking down class barriers to accessing natural health resources and promoting the equalization of public health services.

[0032] This system addresses the shortcomings of existing tools in lacking forward-looking simulation and economic justification capabilities, possessing functions for simulating and predicting intervention plans, quantitative comparison, and cost-benefit analysis. It supports user input or automatic generation of multiple planning schemes, and through data updates and module linkage, accurately predicts the improvement in accessibility and the increase in health benefits after implementation, providing scientific data support for decision-making and replacing traditional experience-based judgments. Simultaneously, based on public health economics standards, it automatically calculates the unit DALY (Daily Average Cost of Avoidance) of the plan and compares it with preset thresholds to generate clear economic conclusions. This ensures that planning schemes have solid quantitative justification when seeking public resources, significantly improving the persuasiveness of the arguments and the efficiency of decision-making.

[0033] It should be noted that any content not described in detail in this specification may be based on existing technology known to those skilled in the art.

[0034] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A planning system for urban blue-green space biodiversity recreational areas that integrates accessibility and health benefits, characterized by: include: The data integration module is used to integrate and manage multi-source geographic spatial data, which includes at least: regional biodiversity distribution data, urban land use data, transportation network data, population distribution data, and socioeconomic data. The accessibility calculation and analysis module is communicatively connected to the data integration module. It is used to construct a spatiotemporal-economic cost model based on the traffic network data, population distribution data, and socioeconomic data, and to calculate a comprehensive accessibility index from multiple settlements in the city to at least one target biodiversity-rich area. The comprehensive accessibility index includes at least the shortest travel time and the ratio of travel cost to income. The health benefit quantification assessment module communicates with the data integration module and the accessibility calculation and analysis module. It is used to call a preset mental health benefit quantification model, and combine the biodiversity distribution data, population distribution data and comprehensive accessibility indicators to quantify the reduction in mental health disease burden that can be achieved by accessing the target biodiversity-rich area. The disease burden is measured in disability-adjusted life years. The program planning simulation module is communicatively connected to the accessibility calculation and analysis module and the health benefit quantification assessment module. It is used to receive the planned intervention program input by the user, and drive the accessibility calculation and analysis module and the health benefit quantification assessment module to recalculate based on the updated data, simulate and output the changes in the comprehensive accessibility index and the reduction in mental health disease burden after the implementation of the planned intervention program. The cost-benefit analysis module is communicatively connected to the health benefit quantification assessment module and the program planning simulation module, and is used to perform economic analysis based on the planned intervention program and its corresponding health benefit assessment results provided by the program planning simulation module. The visualization output module is used to spatially visualize the comprehensive accessibility index, the reduction in mental health disease burden, and the simulation results of different planning intervention schemes.

2. The urban blue-green space biodiversity recreation area planning system integrating accessibility and health benefits as described in claim 1, characterized in that: The data integration module integrates regional biodiversity distribution data, specifically including: real-time or historical species distribution hotspot data obtained from citizen science observation platforms, official protected area boundary data from global or national protected area databases, and key biodiversity area data from ecological research institutions.

3. The urban blue-green space biodiversity recreation area planning system integrating accessibility and health benefits as described in claim 1, characterized in that: The spatiotemporal-economic cost model constructed by the accessibility calculation and analysis module includes the following specific calculation process: Time cost calculation steps: Based on geographical data reflecting surface traffic resistance, the optimal travel time path from each residential area to the target biodiversity-rich area is calculated using a path optimization algorithm, and the corresponding shortest travel time is obtained. Economic cost calculation steps: Identify the main modes of transportation used in the optimal travel time route, and calculate the direct monetary cost of a single round trip by combining the corresponding fuel price or public transportation fare data; Affordability integration step: The direct monetary cost is correlated with the per capita or household income data of the residential area to calculate the proportion of the cost to the residents' income; The shortest travel time and the ratio of transportation costs to revenue together constitute the comprehensive accessibility index.

4. The urban blue-green space biodiversity recreation area planning system integrating accessibility and health benefits as described in claim 1, characterized in that: The mental health benefit quantification model called by the health benefit quantification assessment module was constructed through meta-analysis of multiple empirical studies on the relationship between natural environment exposure and improvement of depression and anxiety symptoms. The model uses biodiversity level parameters and access frequency parameters predicted based on the comprehensive accessibility index as core input variables.

5. The urban blue-green space biodiversity recreational area planning system integrating accessibility and health benefits as described in claim 1, characterized in that: The planning intervention schemes received by the scheme planning simulation module include at least one of the following types: Construct or optimize pedestrian / bicycle paths between the city and the target area, add or adjust public transportation routes and stations leading to the target area, relax or adjust public access policies and boundaries of specific protected areas, and plan and construct blue-green spaces with high biodiversity in areas with low accessibility.

6. The urban blue-green space biodiversity recreation area planning system integrating accessibility and health benefits as described in claim 1, characterized in that: The scheme planning simulation module is also configured as follows: Based on a preset optimization objective function, multiple candidate intervention plans are automatically generated or iteratively optimized; wherein the optimization objective function is at least one of maximizing the reduction in total mental health disease burden, minimizing the Gini coefficient of health benefits among different socioeconomic groups, or ensuring that the cost of avoiding life-years of disability is below the threshold recommended by the World Health Organization.

7. The urban blue-green space biodiversity recreation area planning system integrating accessibility and health benefits as described in claim 6, characterized in that: During the evaluation, the program planning simulation module is configured to separately analyze and output the incremental improvement in the overall accessibility of the planned intervention program for predefined vulnerable groups and the incremental reduction in the burden of mental health diseases.

8. The urban blue-green space biodiversity recreation area planning system integrating accessibility and health benefits as described in claim 1, characterized in that: The cost-benefit analysis module is configured to: calculate the cost required to avoid one disability adjustment life year for each planned intervention scheme output by the scheme planning simulation module, compare this cost with a preset reference threshold based on the regional per capita economic level, and generate and output an evaluation conclusion on whether the planned intervention scheme is economical as a public health intervention measure.

9. The urban blue-green space biodiversity recreation area planning system integrating accessibility and health benefits as described in claim 1, characterized in that: The spatial visualization output module provides spatial visualization displays, including a heat map showing the spatial distribution of comprehensive accessibility indicators, a hierarchical symbol map showing the reduction in mental health burden achieved by residents in different areas, and a side-by-side comparison view showing the changes in key indicators before and after the implementation of the planned intervention program.

10. The urban blue-green space biodiversity recreation area planning system that integrates accessibility and health benefits according to claim 8 or 9, characterized in that: The system is implemented with a distributed service architecture, wherein the data integration module, accessibility calculation and analysis module, and health benefit quantitative assessment module are deployed as backend analysis services; the scheme planning simulation module and visualization output module are deployed as frontend interactive applications, and the frontend and backend interact with each other through standardized interfaces for data and command exchange.

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