Greenway recreation service value evaluation system and method based on recreation equity

Abstract

The application discloses a greenway recreation service value evaluation system and method based on recreation fairness, the evaluation method comprises the following steps of S1, determining an evaluation object, S2, calculating urban recreation fairness, S3, counting average location entropy in a greenway service range and S4, calculating a greenway service value evaluation result; and the evaluation system comprises an evaluation object determination unit, an urban recreation fairness calculation unit, an average location entropy counting unit in the greenway service range and a greenway service value evaluation result calculation unit. The application focuses on the perspective of recreation fairness, forms a complete and quantifiable urban greenway service capacity evaluation technical process by using open source big data and spatial statistical research methods, and provides a scientific basis for objective evaluation, planning and updating of the urban greenway.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of greenway evaluation, in particular to a greenway recreational service value evaluation system and method based on recreational equity. BACKGROUND

[0002] As a linear green open space connecting cities, greenways play multiple roles such as ecology, recreation, and commuting. As of the end of 2021, more than 80,000 kilometers of greenways have been built in China, and cities such as Beijing, Chengdu, and Shenzhen have formed their own greenway network systems to varying degrees. However, the planning and construction of greenways are mostly a "top-down" process, and the actual results produced after the completion of greenway construction are difficult to reflect. In this context, how to scientifically and quantitatively evaluate the actual service value of greenways, so as to accurately focus on the subsequent planning, construction, or renovation of greenways, is a topic worth exploring.

[0003] At the same time, in today's emphasis on high-quality urban development, "equity" is a hot topic in the fields of urban planning and landscape architecture. By quantitatively representing and analyzing equity, we can guide the balanced distribution of life service facilities to maximize the equalization of basic public services in different areas of the city. In the context of leisure and recreation, many cities have experienced rapid expansion and unscientific planning, resulting in a significant imbalance in the distribution of parks, squares, and other recreational spaces. Greenways, on the other hand, can connect isolated recreational spaces, improve the structure of urban green spaces, and provide linear recreational spaces for residents in areas with insufficient recreational spaces, thereby meeting the recreational needs of residents. From this perspective, evaluating the service value of greenways from the perspective of recreational equity has certain scientific significance.

[0004] Currently, domestic greenway-related technologies mainly focus on greenway route planning, design, and internal facilities and materials. However, there is a lack of quantitative evaluation methods for the post-construction effects and satisfaction of greenways. On the one hand, traditional methods such as questionnaires and field surveys are still the main methods, which lack quantitative techniques, require high time and cost, and have certain subjectivity in the evaluation results. On the other hand, there are relatively more quantitative methods for evaluating the ecological function of greenways, but fewer quantitative methods for human recreational behavior.

[0005] With the development of the Internet, large data recording various human behaviors such as food, housing, and transportation have gradually become a new medium for academic research on cities from a human perspective. In the field of greenways, some scholars have conducted site selection planning research based on population heat maps, but these methods only serve as auxiliary support for the overall technology and do not reveal scientific laws in a deeper way.

[0006] In summary, the application focuses on the perspective of recreation equity, forms a complete and quantifiable urban greenway service capacity evaluation technical process by using open source big data and spatial statistical research methods, and provides a scientific basis for objective evaluation, planning and updating of urban greenways. SUMMARY

[0007] To overcome the above problems, the application provides a greenway recreation service value evaluation system and method based on recreation equity to solve the problem of quantifying the service value of greenways from a human perspective.

[0008] The technical scheme adopted by the application to solve the technical problems is:

[0009] The greenway recreation service value evaluation method based on recreation equity comprises

[0010] S1 determine the evaluation object

[0011] Obtain greenway data within a certain city, divide the greenway into multiple road segments at an equal distance of 1000 meters as the evaluation basic unit;

[0012] S2 calculate the urban recreation equity

[0013] Divide the city area into multiple grids with 1000*1000 meters as the side length as the calculation basic unit;

[0014] Obtain the park square AOI data within the city area, superimpose and analyze it with each grid to obtain the park square area in each grid as the recreation space supply capacity parameter;

[0015] Obtain the residential POI data within the city area, superimpose and analyze it with each grid to obtain the number of residential areas in each grid as the recreation space demand parameter;

[0016] Calculate the location entropy LQ between the recreation space supply capacity and the recreation space demand of each grid ij , obtain the recreation equity result:

[0017]

[0018] Wherein: LQ ij is the location entropy of the grid ij, ij is the row and column number of the grid; D ij is the recreation space supply capacity parameter of the grid ij, S ij is the recreation space demand parameter of the grid ij; D is the total recreation space supply capacity parameter of all grids, S is the total recreation space demand parameter of all grids;

[0019] S3 statistics average location entropy in the service range of greenway

[0020] Obtaining road network data in a city area;

[0021] With 1000 meters as the farthest travel distance, the farthest distance reachable along the road network with the node closest to the green road segment and the road network as the starting point is calculated as the service range of the green road segment.

[0022] The grid entropy in the service range of the green road segment is counted, and the average value is obtained:

[0023]

[0024] Wherein: is the average value of the location entropy of the ith green road segment; LQ x is the location entropy of the xth grid in the service range of the green road segment;

[0025] S4 calculates the greenway service value evaluation result

[0026] The average location entropy in the service range of the greenway and the greenway service value are negatively correlated.

[0027] The evaluation result of the greenway service value is:

[0028]

[0029] Wherein: GS i is the evaluation result value of the ith green road segment service value, is the average value of the location entropy of the ith green road segment, is the maximum value of the average value of the location entropy of all green road segments, is the minimum value of the average value of the location entropy of all green road segments.

[0030] As an improvement of the above technical solution, in step S1:

[0031] The greenway data is based on the city greenway planning or current CAD drawing as the base map, and the spatial coordinate information is given by using ArcGIS software to form vector data with spatial coordinate system as greenway data.

[0032] As an improvement of the above technical solution, in step S2:

[0033] The park square AOI data in the city area and the residential POI data in the city area are obtained through the Gaode map API method.

[0034] As an improvement of the above technical solution, in step S3:

[0035] The farthest distance reachable along the road network with the node closest to the green road segment and the road network as the starting point is calculated as the service range of the green road segment by the GIS network analysis method.

[0036] The application also aims to provide a greenway recreation service value evaluation system based on recreation equity, comprising:

[0037] An evaluation object determination unit is configured to obtain greenway data within a city area, divide the greenway into a plurality of road segments at equal intervals of 1000 meters as evaluation basic units;

[0038] A city recreation equity calculation unit is configured to:

[0039] divide the city area into a plurality of grids with a side length of 1000*1000 meters as calculation basic units;

[0040] obtain park square AOI data within the city area through a Gaode map API mode, superimpose and analyze the data with each grid to obtain the area of the park square in each grid as a recreation space supply capacity parameter;

[0041] obtain residential POI data within the city area through the Gaode map API mode, superimpose and analyze the data with each grid to obtain the number of residential areas in each grid as a recreation space demand parameter;

[0042] calculate the location quotient LQ between the recreation space supply capacity and the recreation space demand of each grid ij to obtain a recreation equity result;

[0043] A greenway service range average location quotient statistical unit is configured to:

[0044] obtain road network data within the city area;

[0045] take 1000 meters as the farthest travel distance, calculate the farthest distance along the road network reachable from the node closest to the green road segment as the service range of the green road segment through a GIS network analysis method;

[0046] statistically obtain the location quotient of the grid within the service range of the green road segment, and obtain the average value of the location quotient , i.e., the average value of the location quotient of the i-th green road segment;

[0047] and a greenway service value evaluation result calculation unit configured to quantize and calculate the evaluation result of the greenway service value.

[0048] The application has the following beneficial effects:

[0049] The evaluation system and method quantitatively represent the supply-demand balance relationship of city recreation services by introducing spatial big data and using spatial statistical methods, and obtain the greenway service value evaluation result by statistically weighting the recreation equity index of the grid within the 1km reachable range of the greenway, and the innovation lies in:

[0050] 1) using open source spatial big data such as AOI, POI and the like;

[0051] 2) the concept of location entropy is introduced to quantitatively represent the supply-demand relationship of the recreational space, and the recreational service value evaluation result of the greenway is represented in a quantitative and spatial form to each road section of the greenway;

[0052] 3) from the perspective of recreational fairness, the service value of the urban greenway is evaluated.

[0053] In order to scientifically and quantitatively evaluate the service capability of the greenway to the surrounding residents, the present application considers the supply-demand balance relationship between the population in different regions of the city and the recreational space, and quantitatively represents the recreational service value of the urban greenway from bottom to top. The present application uses network public data, and the evaluation process is in a quantitative form, which has good feasibility and objectivity, and can intuitively present the service value of the greenway in different regions, so as to scientifically guide the planning and construction of the urban greenway. BRIEF DESCRIPTION OF DRAWINGS

[0054] The present application will be further described below in combination with the drawings and specific embodiments:

[0055] Figure 1 It is a flowchart of the greenway recreational service value evaluation method based on recreational fairness of the present application. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be described clearly and completely below in combination with the drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0057] Embodiment 1

[0058] Referring to Figure 1 , the greenway recreational service value evaluation method based on recreational fairness comprises the following steps:

[0059] S1 determining the evaluation object

[0060] Greenway data in a city area is obtained, and the greenway is divided into a plurality of road sections at an equal distance of 1000 meters as an evaluation basic unit. Specifically, the greenway data is mainly based on the CAD drawing of the city greenway planning or present situation, and the spatial coordinate information is given by using ArcGIS software, and finally the vector data with the spatial coordinate system is formed as the greenway data;

[0061] S2 calculating the urban recreational fairness

[0062] The city area is divided into multiple grids with 1000*1000 meters as the side length as the basic unit of calculation;

[0063] The park square AOI data in the city area is obtained through the Gaode map API method, which is superimposed and analyzed with each grid to obtain the area of the park square in each grid as the recreational space supply capacity parameter;

[0064] The residential POI data in the city area is obtained through the Gaode map API method, which is superimposed and analyzed with each grid to obtain the number of residential areas in each grid as the recreational space demand parameter;

[0065] The location entropy LQ between the recreational space supply capacity and the recreational space demand of each grid is calculated ij , and the recreational fairness result is obtained:

[0066]

[0067] Wherein: LQ ij is the location entropy of the grid ij, and ij is the row and column number of the grid; D ij is the recreational space supply capacity parameter of the grid ij, S ij is the recreational space demand parameter of the grid ij; D is the total recreational space supply capacity parameter of all grids, and S is the total recreational space demand parameter of all grids;

[0068] LQ ij Take 1 as the critical value, if LQ ij > 1, it means that the supply is greater than the demand, and the degree of increase gradually deepens with LQ ij ; if LQ ij < 1, it means that the supply is less than the demand, and the degree of decrease gradually deepens with LQ ij ;

[0069] S3 calculates the average location entropy in the service range of the green road

[0070] Obtain the road network data in the city area;

[0071] Take 1000 meters as the farthest travel distance, calculate the farthest distance along the road network from the node closest to the green road segment as the service range of the green road segment through GIS network analysis method;

[0072] Statistical grid location entropy located in the service range of the green road segment, take its average value to get:

[0073]

[0074] Wherein: is the average value of the location entropy of the i-th green road segment; LQx the location entropy of the xth grid located in the service range of the green road section;

[0075] S4 calculates the greenway service value evaluation result

[0076] Based on the present embodiment, the location entropy refers to the supply-demand relationship between the recreational space and the population. The smaller the location entropy of a grid is, the more insufficient the recreational space supply of the grid is, and the grid belongs to the recreational service unfair area. The greenway near such an area has a higher recreational and leisure service value. Based on this, the average location entropy in the service range of the greenway and the service value of the greenway should be negatively correlated. Therefore, the final evaluation result of the greenway service value can be quantified as:

[0077]

[0078] wherein: GS i is the evaluation result value of the i th green road section, is the average value of the location entropy of the i th green road section, is the maximum value of the average value of the location entropy of all green road sections, is the minimum value of the average value of the location entropy of all green road sections.

[0079] In the present embodiment, L1, L2 and L3 are all preferably 1000 meters, but this does not mean that there is a constraint relationship between the above data. L1 is selected to be 1000 meters mainly for the convenience of calculation and spatial display. L2 is selected to be 1000 meters mainly for the consideration of the display effect of spatial calculation at the city scale. L3 is the farthest reachable distance from the greenway along the road network. In the present embodiment, the definition of the greenway service radius in the latest Chinese Garden City Evaluation Standard is mainly referred to: 1 kilometer service range on both sides of the greenway in the built-up area.

[0080] Embodiment 2

[0081] The greenway recreational service value evaluation system based on recreational fairness mainly includes:

[0082] An evaluation object determination unit is configured to obtain greenway data in the city area, divide the greenway into multiple road sections at an equal distance of 1000 meters, and take the road sections as basic evaluation units;

[0083] A city recreational fairness calculation unit is configured to:

[0084] divide the city area into multiple spatial grids with a side length of 1000*1000 meters as basic calculation units;

[0085] obtain park square AOI data in the city area through the Gaode map API, superimpose and analyze the data with each grid, obtain the park square area in each grid, and take the park square area as a recreational space supply capacity parameter;

[0086] Get the residential POI data in the city area through the Gaode map API method, overlay it with each grid, get the number of residential areas in each grid as the recreational space demand parameter;

[0087] Calculate the location entropy LQ between the recreational space supply capacity and the recreational space demand of each grid ij , get the recreational fairness result:

[0088]

[0089] Where: LQ ij is the location entropy of grid ij, ij is the row and column number of the grid; D ij is the recreational space supply capacity parameter of grid ij, S ij is the recreational space demand parameter of grid ij; D is the total recreational space supply capacity parameter of all grids, S is the total recreational space demand parameter of all grids;

[0090] The average location entropy statistical unit within the service range of the greenway is used to:

[0091] Get the road network data in the city area;

[0092] Take 1000 meters as the farthest travel distance, calculate the farthest distance reachable along the road network with the node closest to the green road segment and the road network as the starting point as the service range of the green road segment through GIS network analysis method;

[0093] Statistical grid location entropy located in the service range of the green road segment, take its average value to get:

[0094]

[0095] Where: is the average location entropy of the ith green road segment, LQ x is the location entropy of the xth grid located in the service range of the green road segment;

[0096] And the greenway service value evaluation result calculation unit is used for the quantitative calculation of the final evaluation result of the greenway service value:

[0097]

[0098] Where: GS i is the service value evaluation result value of the ith green road segment, is the average location entropy of the ith green road segment, is the maximum value of the average location entropy of all green road segments, is the minimum value of the average location entropy of all green road segments.

[0099] It should be noted that the above only describes the preferred embodiments of the present application and is not used to limit the present application. Although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art can modify the technical solutions described in the foregoing embodiments or equivalently replace some technical features thereof, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating the recreational service value of greenways based on recreational equity, characterized by: include S1 Determine the evaluation object Obtain greenway data within the city limits of a certain city, and then classify the greenways as... The road is divided into multiple segments at equal intervals, which serve as the basic unit for evaluation. S2 calculates urban recreational equity. by The city's urban area is divided into multiple grids based on the side length, which serve as the basic unit of computation. Obtain AOI data of parks and squares within the city area, overlay and analyze them with each grid to obtain the area of ​​parks and squares in each grid, which serves as a parameter for the supply capacity of recreational space. Acquire POI data of residential areas within the city's urban area, overlay and analyze them with each grid to obtain the number of residential areas in each grid, which serves as a parameter for recreational space demand. Calculate the location entropy between the recreation space supply capacity and recreation space demand for each grid. The recreational fairness results are obtained as follows: ； in: It is a grid Location entropy, These are the row and column numbers of the grid, respectively; It is a grid The parameters of recreational space supply capacity It is a grid Recreational space requirements parameters; For the total recreational space supply capacity parameters of all grids, The total recreational space requirement parameter for all grids; S3 statistical greenway service area average location entropy Obtain road network data within the city's urban area; by To determine the farthest travel distance, the farthest distance reachable along the road network is calculated, starting from the node closest to the road network of the green road segment, and this distance is taken as the service area of ​​the green road segment. The location entropy of the grid areas within the service area of ​​this greenway segment is calculated, and the average value is obtained as follows: ； in: For the first Average location entropy of each green road segment; For the first within the service area of ​​the greenway section Location entropy of each grid; S4 Calculation Results of Greenway Service Value Evaluation The average location entropy within the service area of ​​a greenway is negatively correlated with the service value of the greenway. The evaluation results of the greenway service value are as follows: ； in: For the first The service value evaluation result of the green road section. For the first Average location entropy of each green road segment The maximum value of the average location entropy of all green road segments. It is the minimum of the average location entropy of all green road segments.

2. The method for evaluating the recreational service value of greenways according to claim 1, characterized in that: In step S1: Greenway data is based on urban greenway planning or existing drawings, and spatial coordinate information is assigned to them using ArcGIS software to form vector data with a spatial coordinate system as greenway data.

3. The method for evaluating the recreational service value of greenways according to claim 1, characterized in that: In step S2: The AOI data of parks and squares within the city area and the POI data of residential points within the city area are obtained through the Gaode Map API.

4. The method for evaluating the recreational service value of greenways according to claim 1, characterized in that: In step S3: The service range of the green road segment is calculated by using GIS network analysis, taking the node closest to the road network as the starting point and the farthest distance that can be reached along the road network.

5. A greenway recreation service value evaluation system based on recreational equity, characterized in that: The system is used to implement the greenway recreation service value evaluation method based on recreational equity as described in any one of claims 1 to 4, including... The evaluation object determination unit is used to obtain greenway data within the city's urban area, and divide the greenway into multiple segments at equal intervals as the basic evaluation unit; The urban recreation equity calculation unit is used for: The city's urban area is divided into multiple grids, which serve as the basic units for computation. Obtain AOI data of parks and squares within the city area, overlay and analyze them with each grid to obtain the area of ​​parks and squares in each grid, which serves as a parameter for the supply capacity of recreational space. Acquire POI data of residential areas within the city's urban area, overlay and analyze them with each grid to obtain the number of residential areas in each grid, which serves as a parameter for recreational space demand. Calculate the location entropy between the recreation space supply capacity and recreation space demand of each grid to obtain the recreation fairness results; The average location entropy statistical unit within the service area of ​​the greenway is used for: Obtain road network data within the city's urban area; The service area of ​​a green road segment is calculated by taking the node closest to the road network as the starting point and the farthest distance that can be reached along the road network. Calculate the location entropy of the grid areas within the service area of ​​this greenway segment, and take the average value to obtain the first... Average location entropy of each green road segment; And a greenway service value evaluation result calculation unit, which is used to quantify and calculate the evaluation results of greenway service value.

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