Urban community public service facility refined planning method based on demand density

Abstract

The invention relates to the field of community public service facility planning, in particular to a community public service facility refined configuration method, and provides an urban community public service facility refined planning method based on demand density. Integrating a facility demand density database; determining demand density threshold parameters of various types of community facilities, and debugging to obtain a refined facility content system; acquiring basic data such as a community road network and a community boundary to form a community basic information database; a community center point site selection algorithm is developed from three dimensions of road network reachability geometrical shape-demand density by using an ArcGis platform, boundaries are calibrated in combination with a multivariate method, and living circle boundaries of communities are re-divided for 5-10-15 minutes; carrying out ideal space layout and merging optimization on the facilities in combination with a refined facility content system; and comparing and correcting the new community facility layout with the original facility layout.

Description

Technical Field

[0001] The present invention relates to the field of community public service facility planning, and in particular to a method for fine-grained configuration of community public service facilities. Background Art

[0002] Since the late 20th century, the size and proportion of my country's elderly population has continued to rise. Actively addressing the aging population has become a national strategy in the new development stage. Communities have become a crucial spatial dimension for addressing aging issues and planning elderly care service facilities. However, current community elderly care service facility planning often relies on the per capita construction land quota in the "Public Service Facility Planning Standard" (GB 50442-2018). This traditional allocation approach is overly "homogeneous" and "one-size-fits-all," easily leading to a mismatch between supply and demand, with insufficient supply of needed facilities and redundant unneeded ones. This phenomenon, on the one hand, results in a significant waste of community public resources and, on the other hand, a decline in community satisfaction.

[0003] In the planning of community public service facilities, the content system for public service facilities was often based on rigid requirements in government documents. Some techniques have also proposed constructing a content system based on demand. Previously, the equalization of public service facilities was discussed from the perspective of facility supply. Based on "egalitarianism," the spatial layout of facilities was calculated based on core indicators such as per capita public service facility land, emphasizing "land adaptability." With the evolution of planning concepts, existing techniques have also addressed the issue of "focusing on the land but not the people" in such public facility allocation methods, and have begun to explore community elderly care service facility planning from the perspective of living circles. Existing techniques first explored the division of living circles from different perspectives to clarify the spatial boundaries of facility allocation. Subsequently, techniques studied the allocation content of service facilities within different living circles based on the connotation characteristics and construction requirements of living circles. Finally, based on the principle of matching supply and demand, they proposed a tiered and hierarchical optimization strategy for the supply of public service facilities.

[0004] These methods offer significant improvements over traditional rigid allocation, but they still lack systematicity and efficiency. While research has been conducted on refined demand in the construction of content systems, existing approaches rely too heavily on primary survey data and lack a standardized system that links actual needs and can be applied across different regions. Constructing systems based on overall resident needs presents challenges such as simplistic categorization and inconsistent allocation standards. Furthermore, a "technical intermediary" is lacking to balance efficiency and fairness within the refined nature of these approaches. Egalitarian-oriented scale allocations struggle to adapt to the spatial heterogeneity of planning units, and allocation results can easily deviate from actual needs. Consequently, existing technical approaches consistently favor refined facility planning based on the perspective of living circles. However, scientific delineation of living circle boundaries remains a lack of exploration, and mainstream delineation methods are often overly mechanistic and subjective. Furthermore, the lack of integration between content system construction and facility spatial layout methods has resulted in planning methods remaining largely theoretical, unable to provide concrete guidance for practical planning.

[0005] Therefore, this invention is based on the efficiency and fairness of the refined connotation, introduces a "technical intermediary" that balances the two, develops a set of objective and feasible living circle delineation methods, and proposes a complete and replicable planning method system, which is crucial to optimizing the planning method system of community elderly care service facilities. Summary of the Invention

[0006] To solve the above problems, the present invention proposes a method for refined planning of urban community public service facilities based on demand density to assist conventional community planning.

[0007] The present invention proposes a method for refined planning of urban community public service facilities based on demand density, comprising:

[0008] Obtain data on the demand for community public service facilities and establish a database on the demand for community public service facilities;

[0009] Based on demand translation technology, a community public service facility demand density database is established;

[0010] Combined with expert evaluation, the threshold parameters for the demand density of public service facilities in various types of communities are determined, and supply and demand adjustments are conducted to obtain a regional refined public service facility content system;

[0011] Obtain community basic geographic information data and use the ArcGis platform to form a community basic information database;

[0012] Develop a community center location algorithm based on the three dimensions of "road network accessibility, geometry, and demand density," and combine multivariate methods to calibrate boundaries and redraw the boundaries of the community's 5-10-15 minute living circle;

[0013] Combined with the regional refined public service facilities content system, the ideal spatial layout and merger optimization of facilities are carried out, and compared and corrected with the original facility layout to obtain the final refined planning layout of public service facilities.

[0014] Furthermore, we will obtain data on the demand for community public service facilities and establish a database on the demand for community public service facilities, including:

[0015] Divide the communities in the target area into commercial housing, resettlement housing, affordable housing and mixed-use housing according to housing types;

[0016] The public service facility demand of residents in the target area is obtained according to the community type classification. The questionnaire is designed with the help of Likert scale to quantify the facility demand and form a community public service facility demand database.

[0017] Furthermore, the questionnaire was designed with the help of Likert scale, in which 5, 4, 3, 2, and 1 respectively represent the degree of residents' demand for public service facilities, representing "very need", "need", "don't care", "no need", and "very no need", so as to quantify the degree of residents' demand for various public service facilities in communities with different housing types.

[0018] Furthermore, based on demand translation technology, a community public service facility demand density database is established, specifically including:

[0019] Pre-process the data in the community public service facility demand database, including data cleaning, missing value filling and outlier processing, to ensure the accuracy and completeness of the data;

[0020] The demand translation technology is a demand degree-demand density translation technology algorithm. Based on demand data, it calculates the demand density of public service facilities in each community and forms a database of the demand density of public service facilities in the community within the region.

[0021] Furthermore, the demand translation technology is to translate the demand data obtained from the questionnaire into demand density, and calculate the demand density of different facilities for various types of communities in the target area. The demand density conversion formula is:

[0022]

[0023] Where i ranges from 1 to 4, representing four different types of communities; j ranges from 1 to 15, representing fifteen types of facilities; D ij represents the demand density of facility j in community i, x ij,n P represents the number of answers to the questionnaire with facility j in the i-type community in the questionnaire survey. i represents the density of elderly population in community i.

[0024] Furthermore, based on expert evaluation, the threshold parameters for the demand density of public service facilities in various types of communities were determined, and supply and demand adjustments were made to obtain a regional refined public service facility content system, specifically including:

[0025] Determining the demand density threshold parameters for various types of community public service facilities includes using the Delphi method (expert judgment method) to determine the demand density threshold parameters for the target area;

[0026] The commissioning process includes determining whether the community's demand density for facilities meets a given demand threshold. If so, the facilities will be included in the community's elderly care service facility system; if not, the facilities will be removed.

[0027] According to the debugging standards, the content system of elderly care service facilities for four types of communities was derived. At the same time, based on the "Urban Residential Area Planning and Design Standards (GB50180-2018)" and "Community Living Circle Planning Technical Guidelines (TD_T 1062-2021)", the system was divided according to the service radius of 5-10-15 minutes.

[0028] The "regional refined public service facilities content system" is mainly because different types of communities have different demands for public service facilities. The Delphi method is first used to determine the demand density threshold parameters for public service facilities in each type of community, and then the demand density obtained in the previous article is compared with the demand density threshold parameters.

[0029] Furthermore, there is no fixed standard or calculation method for the demand density threshold, as it is influenced by a variety of factors, including but not limited to the nature of the facility, community characteristics, resident demand distribution, financial status, and policy orientation. The specific value of the threshold should be determined by the community government based on the results of a needs assessment, expert judgment, and the actual situation of the community and the nature of the facility.

[0030] Furthermore, basic community geographic information data is obtained and a community basic information database is formed using the ArcGis platform, including: the boundaries of the target area, road network data within the target area, natural geographic data within the target area, community boundary data within the target area, boundary data of residential areas in each community in the target area, and facility demand density data within the target area.

[0031] Furthermore, the present invention proposes a method for establishing a physical boundary within a specific area that couples geographical boundaries with social needs. This method develops a community center location algorithm based on the three dimensions of road network accessibility, geometry, and demand density. Furthermore, it combines a multivariate approach to calibrate the boundary and redraw the boundaries of the community's 5-10-15 minute living circle. Specifically, this method includes:

[0032] The three dimensions of “road network accessibility-geometry-demand density” include the road network accessibility center point identification algorithm, the community scale geometric centroid identification algorithm, and the demand density centroid identification algorithm;

[0033] Based on the three-point center calibration algorithm, the three points are calibrated using the average algorithm to obtain the center location of the final living circle, and then the preliminary living circle is delineated;

[0034] Based on a refined optimization algorithm for living circle boundaries constrained by multiple factors, including administrative boundaries, road networks, and natural conditions, the preliminary boundaries of living circles are optimized, and ultimately the required boundaries of living circles at all levels of communities are obtained.

[0035] Furthermore, the road network accessibility center point identification algorithm includes:

[0036] Obtain regional road network data and regional boundary data through the Institute of Surveying and Mapping and open source map data;

[0037] The area is gridded into 50m grids, and the intersection of the grid and the road is used as the center point candidate. Multiple candidate points are generated, and these candidate points will be used to calculate the time to the area boundary;

[0038] Using ArcGIS platform, the road network data is converted into points to obtain the node data of each road network;

[0039] For each candidate point, the shortest path time to each point on the region boundary is calculated based on the Dijkstra algorithm. The shortest path algorithm formula is:

[0040] if:d[u]+w(u,v) <d[u]

[0041] Then: d[v]=d[u]+w(u,v)

[0042] Where u is the current node, v is any adjacent node of u, d[u] represents the currently known shortest distance from the source to u, d[v] represents the currently known shortest distance from the source to v, and w(u,v) represents the distance weight from node u to v. The formula means: if the path length from the current node u to v via (u,v) is less than the known path length d[v] from the source to v, then update d[v] to the path length from u to v.

[0043] Use SPSS to calculate the standard deviation of the time from the candidate point to all boundary points, and select the point with the smallest standard deviation as the center point. The standard deviation formula is:

[0044]

[0045] Where: s is the standard deviation of the time data from the candidate point to the boundary, x iis the time data from the candidate point to the boundary, It is the average of all time data from the candidate point to the boundary.

[0046] Furthermore, the community-scale geometric centroid identification algorithm specifically includes:

[0047] Obtain boundary data for each community in the region through the Institute of Surveying and Mapping and open source map data;

[0048] Use ArcGIS platform to identify the centroid of each community's surface data and obtain the community scale geometry and centroid.

[0049] Calculation formula:

[0050]

[0051] Where: (x rc ,y rc ) is the coordinate of the center of mass, x i 、y i are the horizontal and vertical coordinates of point i.

[0052] Furthermore, the demand density center of gravity identification algorithm specifically includes:

[0053] Obtain boundary data of each residential area under the community through the Surveying and Mapping Institute;

[0054] The demand density of each residential area obtained by translating the demand data;

[0055] Use ArcGIS platform to identify the centroid of residential areas;

[0056] Assign the demand density of each residential area to the centroid of the corresponding residential area, and use the weighted average algorithm to identify the centroid of community demand density. The formula of the centroid weighted average algorithm is:

[0057]

[0058] Where: (x dc ,y dc ) is the coordinate of the center of gravity, x i 、y i is the horizontal and vertical coordinates of point i, w i is the weight of point i, that is, the density requirement.

[0059] Furthermore, the three points of the road network accessibility center, the community scale geometric centroid, and the demand density centroid are calibrated by using an average algorithm. The formula of the average algorithm is:

[0060]

[0061] Where: (x, y) is the calibration coordinate, (x nc ,y nc ) is the accessibility center of the road network, (x rc ,y rc ) is the community scale geometric centroid, (x dc ,y dc ) is the center of facility demand density.

[0062] Furthermore, the re-division of the community 5-10-15 minute living circle boundaries is performed according to the following steps:

[0063] The definition of the 15-minute living circle requirements includes:

[0064] The calibrated center point is used as the center of the living circle and a 15-minute range is defined;

[0065] The centroid of the overlapping parts of the 15-minute living circle of each community was re-selected as the demarcation center of the 15-minute living circle, and the scope of the 15-minute living circle was demarcated to obtain the preliminary boundary;

[0066] The preliminary boundary is calibrated according to the actual administrative boundary and natural status to obtain the final 15-minute social demand boundary;

[0067] The definition of the 10-minute living circle requirements includes:

[0068] The calibrated center point is used as the center of the living circle and a 10-minute range is defined;

[0069] The centroid of the overlapping parts of the 10-minute living circle of each community was re-selected as the demarcation center of the 10-minute living circle, and the scope of the 10-minute living circle was demarcated to obtain the preliminary boundary;

[0070] The preliminary boundary is calibrated according to the actual administrative boundary and natural status to obtain the final 10-minute social demand boundary;

[0071] The definition of the 5-minute living circle needs boundaries includes:

[0072] The calibrated center point is used as the center of the living circle and a 5-minute range is defined;

[0073] The preliminary boundary is calibrated according to the actual administrative boundary and natural status to obtain the final 5-minute social demand boundary.

[0074] Furthermore, the preliminary spatial layout and merger optimization of facilities were carried out in combination with the regional refined public service facilities content system. After comparison and correction with the original facility layout, the final refined planning layout of public service facilities was obtained, which specifically includes:

[0075] Based on the regional refined public service facility content system, the service radius of each facility is the basis, and each demand boundary is used as a unit. In combination with the radiation range of the 5-10-15 minute living circle of each community within the unit, the ideal layout point of the facility is selected near the centroid of the overlapping range;

[0076] The ideal layout of community elderly care service facilities in each living circle was obtained respectively. Then, the ideal facility layout was preliminarily optimized twice based on the facility configuration requirements and efficiency indicators to obtain the preliminary layout of community elderly care service facilities.

[0077] Compare the preliminary layout with the actual layout of the target area, including:

[0078] If the community has the capacity in the preliminary layout and there are existing available facilities nearby, the existing facilities will be used for layout;

[0079] If the preliminary layout shows that there is space for the community but no facilities are available nearby, new facilities will be constructed;

[0080] If the community does not have the capacity to accommodate the ideal layout, the capacity to accommodate the space around the preliminary layout will be screened and the above steps will be repeated to obtain the final layout of the community elderly care service facilities.

[0081] The calculation of the centroid of the coincident range includes:

[0082] The number of overlaps between life circles was visualized using the ArcGIS platform and displayed in the attribute table;

[0083] Extract the overlapping surface data with the largest number of overlaps;

[0084] The centroid of the extracted surface data is identified and used as the center point of the 15-minute living circle.

[0085] Furthermore, we conducted two preliminary optimizations of the ideal facility layout based on the facility configuration requirements and efficiency indicators, and obtained the preliminary layout of community elderly care service facilities, which specifically includes:

[0086] Determine facility configuration requirements and efficiency indicators based on the Urban Residential Area Planning and Design Standards (GB50180-2018) and the Technical Guidelines for Community Living Circle Planning (TD_T1062-2021);

[0087] The primary optimization is to merge facilities of the same type that can be integrated according to efficiency indicators, and at the same time refer to the configuration requirements to optimize the ideal layout of facilities, such as only one facility is required in the street;

[0088] The second optimization is to merge facilities of different types that belong to the same living circle and can be set up in an integrated manner, and finally obtain the preliminary layout of community elderly care service facilities.

[0089] The above technical solution of the present invention has the following beneficial technical effects:

[0090] 1) The present invention combines the construction of the public service facility content system with the facility space layout to form a complete set of technical methods for refined planning of public service facilities.

[0091] 2) Based on the refined connotation of efficiency and fairness, the present invention introduces a "technical intermediary" that balances the two, and uses this as the standard for constructing the community public service facility content system, thereby realizing a more accurate, targeted, and universal facility content system construction method.

[0092] 3) This study develops an objective and feasible method for delineating living zones, proposing a comprehensive, replicable, and scalable planning methodology. This approach enables the scientific and precise allocation of community public service facilities, which is crucial for optimizing the planning methodology for community public service facilities. This research provides an intelligent, digital perspective for community planning and development, playing a significant role in improving the fairness of community facility allocation and resident satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] Figure 1 It is a flowchart of the present invention;

[0094] Figure 2 This is a diagram showing the demand characteristics of various types of community elderly care service facilities in the case area of the present invention;

[0095] Figure 3 A flowchart for constructing a content system for community elderly care service facilities in a case study area for the present invention;

[0096] Figure 4 This is a flowchart of a method for spatial layout of community elderly care service facilities in a case study area of the present invention;

[0097] Figure 5 Flowchart of the center identification method of road network accessibility of the present invention;

[0098] Figure 6 Flowchart of the community scale geometric centroid identification method of the present invention;

[0099] Figure 7 A flow chart of the method for identifying the center of gravity of facility demand density according to the present invention;

[0100] Figure 8 A diagram showing the center point of the road network accessibility in the case area of the present invention;

[0101] Figure 9 A diagram showing the geometric centroid of the community scale in the case area of the present invention;

[0102] Figure 10A diagram showing the center of gravity of facility demand density in the case area of the present invention;

[0103] Figure 11 A diagram showing the community center point after three-point calibration in the implementation case area of the present invention;

[0104] Figure 12 This is a schematic diagram of the selection of the center point of the 15-minute living circle demand boundary in the implementation case area of the present invention;

[0105] Figure 13 This is a schematic diagram of the center point of the 10-minute living circle demand boundary selected in the implementation case area of the present invention;

[0106] Figure 14 This is a diagram showing the 5-10-15 minute living circle demand boundary in the implementation case area of the present invention;

[0107] Figure 15 A schematic diagram of a method for selecting an ideal spatial layout of community elderly care service facilities in an implementation case area of the present invention;

[0108] Figure 16 A diagram showing the ideal spatial layout of community elderly care service facilities in the implementation case area of the present invention;

[0109] Figure 17 A diagram showing the preliminary layout of community elderly care service facilities in the implementation case area of the present invention;

[0110] Figure 18 A diagram showing the spatial layout of existing community elderly care service facilities in the implementation area of the present invention;

[0111] Figure 19 This is a diagram showing the final layout of the community elderly care service facility space in the implementation case area of the present invention. DETAILED DESCRIPTION

[0112] The technical solution of the present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings.

[0113] Example 1

[0114] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further described below in conjunction with specific embodiments and drawings, but the following embodiments are only preferred embodiments of the present invention, not all. Based on the embodiments in the implementation manner, other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0115] refer to Figure 1, This invention belongs to technology development research, which originates from practical problems. The invention aims at the supply and demand mismatch problem in the current configuration of community public service facilities. The invention results have strong guiding significance for solving this practical problem. It is expected that the invention results have the potential for promotion and replication, and have a relatively broad application prospect. The application of the invention results is of great value for saving social public service resources and promoting the high-quality development of community public services. The layout configuration of community public service facilities can be deconstructed into a point-on-surface layout. The invention focuses on the refinement theory and explores the fairness and efficiency of the point layout. It mainly relies on the ArcGis platform and integrates computer calculation methods to quickly integrate community-related feature data to construct a refined planning method system for urban community public service facilities based on demand density.

[0116] To this end, the present invention provides a method for refined planning of public service facilities in urban communities, including:

[0117] Step S01: Obtain community public service facility demand data and establish a community public service facility demand database;

[0118] Step S02: Building a community public service facility demand density database based on demand translation technology;

[0119] Step S03: Determine the density threshold parameters of public service facilities in various types of communities based on expert evaluation, and conduct supply and demand adjustments to obtain a regional refined public service facilities content system;

[0120] Step S04: Obtain community basic geographic information data and use the ArcGis platform to form a community basic information database;

[0121] Step S05: Develop a community center location selection algorithm based on the three dimensions of "road network accessibility, geometry, and demand density," and combine multivariate methods to calibrate boundaries and redraw the boundaries of the community's 5-10-15 minute living circle.

[0122] Step S06: Combine the regional refined public service facility content system to optimize the ideal spatial layout and merger of the facilities, and compare and correct them with the original facility layout to obtain the final refined planning layout of the public service facilities.

[0123] experiment:

[0124] This experimental example takes the 25 communities under the jurisdiction of Dinglan Street in Hangzhou as the research object, and takes the community elderly care service facilities as an example of community public service facilities. The demand density-based refined planning method for urban community public service facilities of the present invention is used to carry out refined planning of community elderly care service facilities in Dinglan Street.

[0125] In the above step S01, data on the elderly population in Dinglan Subdistrict, community housing types, public service facility demand data, and community elderly care service facility types are obtained;

[0126] It should be noted that the study adopted a stratified sampling method, which involves dividing the population into different "strata," each representing an important subgroup, such as communities with different housing types. Random samples were then drawn from each stratum. This ensured that every type of community was represented in the sample, thereby improving the broad applicability and accuracy of the survey results. A Likert scale (5-point scale) was used to quantify the subjective demand for different facilities, with 5, 4, 3, 2, and 1 representing "very necessary," "somewhat necessary," "indifferent," "not very necessary," and "no need," respectively.

[0127] By consulting the literature and referring to the Urban Public Service Facility Planning Standard GB50442 (revised), the National Basic Public Service Standard (2021 edition), and the Zhejiang Province Basic Public Service Standard (2021 edition), we have summarized the content of existing facilities in my country: five major categories of facilities and fifteen minor categories of facilities, which serve as standard guidelines; Table 1 below shows the content of community elderly care service facilities;

[0128] Table 1

[0129]

[0130] Table 2 below shows the data on the elderly population in Dinglan Subdistrict:

[0131] Table 2

[0132]

[0133] Since the present invention uses the survey questionnaire data, the data is first cleaned to obtain the community elderly care service facility demand database, and then the data is used as the reference. Figure 2 , and established a database of demand characteristics of various types of community elderly care service facilities in Dinglan Street.

[0134] In step S02, the demand characteristic database of various types of community elderly care service facilities in Dinglan Street is translated. Using the data translation calculation algorithm, the demand degree data in the community elderly care service facility demand database is translated into demand density, and the demand density data of community elderly care service facilities in Dinglan Street is obtained. The following table 3 is the translated demand density data table:

[0135] Table 3

[0136]

[0137] In step S03, a refined content system of community elderly care service facilities in Dinglan Subdistrict is established. First, the expert evaluation method is used to determine the demand density threshold of each facility configuration in each type of community in the target area Dinglan Subdistrict. Then, a comparison and debugging of the demand density of community elderly care service facilities is performed, and a refined content system of community elderly care service facilities in Dinglan Subdistrict is constructed. The specific steps are as follows:

[0138] Step S031, using the demand density data in Table 3, gradually compare the community type and facility type with their demand density thresholds;

[0139] Step S032: If the demand density in Table 3 reaches a given demand density threshold, the elderly care service facility content system of Dinglan Street is included;

[0140] Step S033: if the demand density in Table 3 does not reach the demand density threshold, then the system is eliminated;

[0141] Step S034: Divide the system into service radii of 5, 10, and 15 minutes in accordance with the Urban Residential Area Planning and Design Standard (GB50180-2018) and the Technical Guidelines for Community Living Circle Planning (TD_T 1062-2021);

[0142] Refer to Table 4 below for the content system of refined community elderly care service facilities in Dinglan Street.

[0143] Table 4

[0144]

[0145]

[0146] It should be noted that the specific process of constructing the content system of community elderly care service facilities in Dinglan Street is as follows: Figure 3 .

[0147] Furthermore, Dinglan Street information data collection was carried out. In addition to the road data, natural geographic data, community zoning data, and residential zoning data directly obtained from the Zhejiang Institute of Surveying and Mapping Science and Technology, multi-source data such as POI data obtained using network data crawling software such as the AutoNavi Map Open Platform, as well as real estate type and population data obtained from the local government, were also collected. Furthermore, the spatial layout of the elderly care service facilities in Dinglan Street was carried out. The overall process of the facility spatial layout is detailed in the following. Figure 4 .

[0148] In step S05, the present invention proposes a method for establishing a physical boundary that couples geographical boundaries and social needs in a specific area, and redivides the 5-10-15 minute living circle demand boundary of Dinglan Street. First, the community center point location selection algorithm is developed from the three dimensions of "road network accessibility-geometric shape-demand density"; the center point location determination mainly includes: first, the road network accessibility center point identification algorithm research, it is intended to refer to the Dijkstra algorithm, optimize it, and calculate the accessibility center point in combination with actual needs; second, the community scale geometric center identification algorithm research, with the administrative boundary as the benchmark, the community scale geometric center point is identified by reverse calculation; third, the demand density center of gravity identification algorithm research, it is intended to use the community as the basic unit to identify its demand density, and identify the demand density center of gravity position through the grid assignment method; fourth, the three-point center calibration algorithm research based on the three points, the above three points are calibrated using the average algorithm to obtain the final center location of the living circle.

[0149] The specific process of the research on the road network accessibility center point identification algorithm is shown in Figure 5 , the steps are as follows:

[0150] Step S051, obtaining the road network data of Dinglan Street and the boundary data of the area through open source map data, and importing them into the ArcGis platform to convert them into line data and surface data;

[0151] Step S052: Gridding the Dinglan Street (250 meters) to generate multiple candidate points for calculating the time to the area boundary;

[0152] Step S053, using the ArcGIS platform to perform feature-to-point processing on the road network line data to obtain node data of each road network;

[0153] Step S054: For each candidate point, based on the Dijkstra algorithm, a network dataset is created for each community surface data in the ArcGis platform, followed by network analysis and OD cost matrix analysis, to determine the shortest path time to each point on the Dinglan Street boundary.

[0154] Step S055: Calculate the standard deviation of the time from the candidate point to all boundary points using the SPSS tool, and select the point with the smallest standard deviation as the center point.

[0155] The specific process of the community scale geometric center identification algorithm is shown in Figure 6 , the steps are as follows:

[0156] Step S056: Obtain boundary data of each community in Dinglan Subdistrict through open source map data, and import it into the ArcGis platform to convert it into surface data;

[0157] Step S057, using the ArcGIS platform to calculate the centroid location of each community surface data.

[0158] The specific process of the demand density center of gravity identification algorithm is shown in Figure 7 , the steps are as follows:

[0159] Step S058: Obtain the boundaries of each residential area in Dinglan Street through open source map data, and import it into the ArcGis platform to convert it into surface data;

[0160] Step S059: Obtain the demand density of facilities for different types of housing. The proportion of housing types in each residential area is known through the real estate information of each residential area, and the demand density value of each area is recalculated according to the proportion.

[0161] Step S0510, using the ArcGIS platform to calculate the centroid position of each residential area surface data in the community;

[0162] Step S0511: assign the demand density of each residential area to the centroid of the corresponding residential area, and use the weighted average algorithm to identify the center of gravity of the community demand density.

[0163] Furthermore, the above three points are calibrated using the average algorithm, and finally the calibrated regional center point is obtained; the accessibility center point of the community road network in Dinglan Street, the geometric center point of the community scale, the center point of demand density and the calibration of the community center position are as follows: Figure 8 、 Figure 9 、 Figure 10 、 Figure 11 shown.

[0164] After the site selection of the Dinglan Subdistrict Community Center is completed, the preliminary boundaries of the living circle will be delineated in the order of 15-minute, 10-minute, and 5-minute living circles with it as the center;

[0165] The steps for defining the boundaries of the 15-minute living circle are as follows:

[0166] Step S0512: Using the calibrated center point as the center of the living circle to define a 15-minute range;

[0167] Step S0513: Reselect the centroid of the overlapping parts of the 15-minute living circle of each community as the demarcation center of the 15-minute living circle. The confirmation diagram of the demarcation center point of the 15-minute living circle of each community in Dinglan Street is as follows: Figure 12 As shown, the 15-minute living circle is defined to obtain a preliminary boundary;

[0168] Step S0514: manually calibrate the preliminary boundary based on the actual administrative boundary and natural conditions to obtain the final 15-minute social demand boundary;

[0169] The steps for defining the boundaries of the 10-minute living circle are as follows:

[0170] Step S0515: Use the calibrated center point as the center of the living circle and define a 10-minute range;

[0171] Step S0516: Reselect the centroid of the overlapping parts of the 10-minute living circle of each community as the demarcation center of the 10-minute living circle. The confirmation diagram of the demarcation center point of the 10-minute living circle of each community in Dinglan Street is as follows: Figure 13 As shown, the 10-minute living circle is defined to obtain a preliminary boundary;

[0172] Step S0517: manually calibrate the preliminary boundary based on the actual administrative boundary and natural conditions to obtain the final 10-minute social demand boundary;

[0173] The steps for defining the boundaries of the 5-minute living circle are as follows:

[0174] Step S0518, using the calibrated center point as the center of the life circle to define a 5-minute range;

[0175] In step S0519, the preliminary boundary is manually calibrated according to the actual administrative boundary and natural conditions to obtain the final 5-minute social demand boundary.

[0176] Finally, the demand boundaries of community life circles at all levels were obtained, and 25 5-minute life circles, 14 10-minute life circles and 6 15-minute life circles were finally divided, such as Figure 14 shown.

[0177] In the above step S06, based on the regional refined public service facility content system, taking the service radius of each facility as the basis, taking each demand boundary as the unit, and combining the radiation range of the 15-minute, 10-minute, and 5-minute living circles of each community within the unit, the ideal layout point of the facility is selected near the centroid of the overlapping range. The schematic diagram of the method for selecting the ideal layout of the elderly care service facility space in Dinglan Street Community is shown as follows: Figure 15 As shown;

[0178] The ideal layout of community elderly care service facilities in Dinglan Street is as follows: Figure 16 shown.

[0179] In step S06, it is necessary to combine the regional refined public service facility content system to make an ideal spatial layout of the facilities, and then perform facility merger optimization;

[0180] Therefore, in step S06, it is necessary to first organize the processing suggestions for the ideal layout. According to the facility configuration requirements and efficiency indicators in the "Urban Residential Area Planning and Design Standard (GB50180-2018)" and the "Community Living Circle Planning Technical Guidelines (TD_T 1062-2021)", the configuration suggestions for community elderly care service facilities are obtained. Refer to Table 5 below.

[0181] Table 5

[0182]

[0183] The first optimization is to merge the facilities of the same type that can be integrated according to the efficiency index, and at the same time refer to the configuration requirements, and optimize the ideal layout of the facilities, such as only one is required in the street; the second optimization is to merge the facilities of different types that are in the same living circle and can be integrated, and finally get the preliminary layout of community elderly care service facilities; the preliminary layout of the community elderly care service facility space in Dinglan Street is as follows Figure 17 shown.

[0184] Furthermore, when comparing the preliminary layout with the actual layout of Dinglan Street, it was found that there were significant differences; the actual layout of community elderly care service facilities in Dinglan Street is as follows: Figure 18 As shown;

[0185] Therefore, the preliminary layout is calibrated by comparing with the existing facilities in Dinglan Street. If the community has carrying space and there are existing available facilities nearby, the existing facilities will be used for layout; if the community has carrying space but there are no available facilities nearby, new facilities will be built; if the community has no carrying space in the ideal layout, the carrying space around the preliminary layout will be screened and the above steps will be repeated to obtain the final layout of community elderly care service facilities. Figure 19 shown.

[0186] This demand-density-based refined planning method for urban community public service facilities includes content system construction and facility space layout; it also optimizes the layout of facilities multiple times, taking into account the principles of resource utilization efficiency, economic costs and benefits, and avoiding resource waste. At the same time, it compares with existing facilities and specifically points out the deficiencies in facility layout; improves the community's refined governance model, strengthens the updating of community facility demand data, and meets the community's current and future development needs.

[0187] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A refined planning method for urban community public service facilities based on demand density, characterized by: include: Step S01: Obtain community public service facility demand data and establish a community public service facility demand database; Step S02: Building a community public service facility demand density database based on demand translation technology; Step S03: Determine the density threshold parameters of public service facilities in various types of communities based on expert evaluation, and conduct supply and demand adjustments to obtain a regional refined public service facilities content system; Step S04: Obtain community basic geographic information data and use the ArcGis platform to form a community basic information database; Step S05: Calculate the location of the community center based on the three dimensions of "road network accessibility, geometry, and demand density," and use a multivariate approach to calibrate the boundaries and redraw the boundaries of the community's 5-10-15 minute living circle. Step S06: Combine the regional refined public service facility content system to optimize the ideal spatial layout and merger of the facilities, and compare and correct them with the original facility layout to obtain the final refined planning layout of the public service facilities.

2. The method for refined planning of urban community public service facilities based on demand density according to claim 1 is characterized in that: Step S01 specifically includes: dividing the communities in the target area into commercial housing, resettlement housing, affordable housing and mixed-use housing according to housing type; obtaining the public service facility demand of residents in the target area according to community type classification, designing a questionnaire with the help of Likert scale, quantifying the facility demand, and forming a community public service facility demand database.

3. The method for refined planning of urban community public service facilities based on demand density according to claim 1 or 2 is characterized in that Step S02 specifically includes: Pre-process the data in the community public service facility demand database, including data cleaning, missing value filling and outlier processing, to ensure the accuracy and completeness of the data; The demand translation technology uses the demand degree-demand density translation technology algorithm to calculate the public service facility demand density of each community based on demand data, and form a community public service facility demand density database.

4. The method for refined planning of urban community public service facilities based on demand density according to claim 1 is characterized in that Step S03 specifically includes: The Delphi method was used to determine the threshold parameters for the density of public service facilities required for each type of community; The commissioning process of the regional refined public service facility content system specifically includes: determining whether the community's demand density for facilities meets a given demand density threshold. If so, the facilities will be included in the community's elderly care service facility system; if not, the facilities will be removed; According to the debugging standards, a content system of elderly care service facilities for four types of communities was derived, and the system was divided according to a service radius of 5-10-15 minutes.

5. The method for refined planning of urban community public service facilities based on demand density according to claim 1 is characterized in that: Step S05 specifically includes: Community center site selection includes: road network accessibility center point identification algorithm, community scale geometric centroid identification algorithm, demand density center of gravity identification algorithm; Based on the three-point center calibration algorithm, the average algorithm is used to calibrate the three points obtained by the road network accessibility center point identification algorithm, the community scale geometric centroid identification algorithm, and the demand density centroid identification algorithm to obtain the final center location of the living circle; A refined optimization algorithm for living circle boundaries based on multi-factor constraints, including administrative boundaries, road networks, and natural conditions, is used to optimize the preliminary boundaries of living circles and ultimately obtain the required boundaries of living circles at all levels of communities.

6. The method for refined planning of urban community public service facilities based on demand density according to claim 5, characterized in that: The road network accessibility center point identification algorithm uses the Dijkstra algorithm and combines it with actual needs to calculate the accessibility center point; The community-scale geometric center identification algorithm uses administrative boundaries as a benchmark to inversely calculate and identify the community-scale geometric center point; The demand density center identification algorithm uses the cell as the basic unit to identify its demand density and uses the grid assignment method to identify the demand density center position; in: The road network accessibility center point identification algorithm includes: Obtain regional road network data and regional boundary data through the Institute of Surveying and Mapping and open source map data; The area is gridded into 50m grids, and the intersection of the grid and the road is used as the center point candidate. Multiple candidate points are generated, and these candidate points will be used to calculate the time to the area boundary; Use ArcGIS platform to convert road network line data into points to obtain node data of each road network; For each candidate point, the shortest path time to each point on the region boundary is calculated based on the Dijkstra algorithm; The standard deviation of the time from the candidate point to all boundary points is calculated using the SPSS tool, and the point with the smallest standard deviation is selected as the center point. The community-scale geometric centroid identification algorithm specifically includes: Obtain boundary data for each community in the region through the Institute of Surveying and Mapping and open source map data; The ArcGIS platform was used to identify the centroid of each community's surface data and obtain the community-scale geometric centroid; Demand density center of gravity identification algorithm, specifically including: Obtain boundary data of each residential area under the community through the Surveying and Mapping Institute; The demand density of each residential area obtained by translating the demand data; Use ArcGIS platform to identify the centroid of residential areas; The demand density of each residential area is assigned to the centroid of the corresponding residential area, and the weighted average algorithm is used to identify the center of gravity of the community demand density.

7. The method for refined planning of urban community public service facilities based on demand density according to claim 5 is characterized in that: The three-point center calibration algorithm, combined with a multivariate approach to calibrate boundaries, redefined the boundaries of the community's 5-10-15 minute living circle, specifically including: The boundaries of the 15-minute living circle are defined, including: The center point after the three-point calibration is used as the center of the living circle and a 15-minute range is defined; The centroid of the overlapping parts of the 15-minute living circle of each community was re-selected as the demarcation center of the 15-minute living circle, and the scope of the 15-minute living circle was demarcated to obtain the preliminary boundary; The preliminary boundary was calibrated according to the actual administrative boundary and natural conditions to obtain the final 15-minute living zone boundary; The boundaries of the 10-minute living circle are defined, including: Use the calibrated center point as the center of the living circle and define a 10-minute range; The centroid of the overlapping parts of the 10-minute living circle of each community was re-selected as the demarcation center of the 10-minute living circle, and the scope of the 10-minute living circle was demarcated to obtain the preliminary boundary; The preliminary boundary was calibrated according to the actual administrative boundary and natural conditions to obtain the final 10-minute living zone boundary; The boundaries of the 5-minute living circle are defined, including: Use the calibrated center point as the center of the living circle and define a 5-minute range; The preliminary boundary was calibrated according to the actual administrative boundary and natural conditions to obtain the final 5-minute living circle boundary.

8. The method for refined planning of urban community public service facilities based on demand density according to claim 1 is characterized in that: Step S06 specifically includes: Based on the regional refined public service facility content system, the service radius of each facility is the basis, and each demand boundary is used as a unit. In combination with the radiation range of the 5-10-15 minute living circle of each community within the unit, the ideal layout point of the facility is selected near the centroid of the overlapping range; The ideal layout of community elderly care service facilities in each living circle was obtained respectively. The ideal facility layout was preliminarily optimized twice based on the facility configuration requirements and efficiency indicators to obtain the preliminary layout of community elderly care service facilities. Compare the preliminary layout with the actual layout of the target area, including: If the community has the capacity in the preliminary layout and there are existing available facilities nearby, the existing facilities will be used for layout; If the preliminary layout shows that there is space for the community but no facilities are available nearby, new facilities will be constructed; If there is no suitable space in the community according to the ideal layout, the suitable space around the preliminary layout will be screened and the above steps will be repeated to obtain the final layout of the community elderly care service facilities. The calculation of the centroid of the coincident range includes: The number of overlaps between life circles was visualized using the ArcGIS platform and displayed in the attribute table; Extract the overlapping surface data with the largest number of overlaps; The centroid of the extracted surface data is identified and used as the center point of the 15-minute living circle.

9. The method for refined planning of urban community public service facilities based on demand density according to claim 1 is characterized in that: Step S06 specifically includes: Step S061: Based on the regional refined public service facility content system, the service radius of each facility is used as the basis, and the demand boundary is used as the unit. In combination with the radiation range of the 5-10-15 minute living circle of each community within the unit, the ideal layout point of the facility is selected near the centroid of the overlapping range; Step S062: construct a facility configuration suggestion table based on the facility configuration requirements and efficiency indicators, and organize processing suggestions for the ideal layout; In step S063, two layout optimizations are performed. The first optimization is to merge the facilities of the same type that can be integrated according to the efficiency index, and at the same time optimize the ideal layout of the facilities with reference to the configuration requirements in the facility configuration recommendation table; the second optimization is to merge the facilities of different types that are in the same living circle and can be integrated, and finally obtain the preliminary layout of community elderly care service facilities.

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