Method and device for dividing regional scope of urban and rural living circle based on data analysis
By constructing a basic information database and a supply-demand matching model, the problem of inaccurate division of living circles in existing technologies has been solved, enabling quantitative identification of urban and rural living circles and rational allocation of public service facilities.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NORTHWEST ENGINEERING CORPORATION LIMITED
- Filing Date
- 2024-04-30
- Publication Date
- 2026-06-16
AI Technical Summary
The existing scheme for dividing living circles does not use scientific statistical methods for data analysis, resulting in low accuracy in the division of urban and rural living circle areas and a lack of reasonable allocation of public service facilities.
A basic information database is constructed by acquiring feature data of the target analysis area, and the area is divided using a trained living circle area division model. An evaluation is then conducted based on a supply and demand matching model to determine the living circle level and area scope.
It enables quantitative identification and division of urban and rural living circles, improves the accuracy of regional scope, and can reasonably determine the allocation of public service facilities, providing scientific evaluation standards.
Smart Images
Figure CN118445465B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of living circle division technology, and in particular to a method and apparatus for dividing urban and rural living circle areas based on data analysis. Background Technology
[0002] With the continuous improvement of residents' living standards and the acceleration of urbanization, the living communities on the outskirts of cities are no longer bound by the traditional urban-rural dual administrative framework. Cities and their surrounding rural areas have formed interdependent, interactive, and mutually developing living communities.
[0003] Existing schemes for delineating urban and rural living circles mainly fall into two categories: those based on administrative boundaries and those based on indicators. The administrative boundary-based scheme primarily determines the spatial scope of urban and rural living circles through manual surveys. For example, existing research uses field visits and sampling surveys to understand residents' daily life behaviors, studies the spatial layout of settlements within the living circle, and explores the supply and demand matching of public service facilities in rural areas from the perspective of residents' daily lives, thus dividing urban and rural living circles. The indicator-based scheme delineates living circles at different levels, such as 5 minutes, 10 minutes, and 15 minutes, based on the "per thousand people indicator" and residents' travel time. However, existing living circle delineation schemes do not use scientific statistical methods for data collection and analysis, and they do not rationally allocate urban and rural public service facilities, resulting in low accuracy and an inability to judge the rationality of the delineation results. Summary of the Invention
[0004] To overcome the problems existing in related technologies, this application provides a method for dividing the urban and rural living circle area based on data analysis and a device for dividing the urban and rural living circle area based on data analysis.
[0005] According to a first aspect of the embodiments of this application, a method for dividing the regional scope of urban and rural living circles based on data analysis is provided, the method comprising:
[0006] Acquire target type feature data for the target analysis area, and construct a basic information database based on the target type feature data; wherein, the target type feature data includes: geospatial information data, environmental feature data, economic data, and human data;
[0007] The basic information database is parsed, and the living circle level classification information corresponding to the target analysis area is determined based on the data parsing results. The living circle level classification information includes the service radius corresponding to different levels of living circles.
[0008] The target analysis area is divided using a trained living area range division model, and the living area range division information corresponding to the target analysis area is determined based on the living areas formed by the division and the living area level division results.
[0009] The matching evaluation of the living area area division information is performed based on the supply and demand matching model to obtain the corresponding matching evaluation information.
[0010] According to a second aspect of the embodiments of this application, a device for delineating the regional scope of urban and rural living circles based on data analysis is provided, comprising:
[0011] The database construction module is used to acquire target type feature data of the target analysis area and construct a basic information database based on the target type feature data; wherein, the target type feature data includes: geospatial information data, environmental feature data, economic data, and human data;
[0012] The living circle level classification module is used to parse the basic information database and determine the living circle level classification information corresponding to the target analysis area based on the data parsing results. The living circle level classification information includes the service radius corresponding to different levels of living circles.
[0013] The living circle segmentation module is used to segment the target analysis area using a trained living circle area segmentation model, and to determine the living circle area segmentation information corresponding to the target analysis area based on the segmented living circles and the living circle level segmentation results.
[0014] The living circle evaluation module is used to evaluate the matching of the living circle area division information based on the supply and demand matching model in order to obtain the corresponding matching evaluation information.
[0015] According to a third aspect of the embodiments of this application, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for dividing the urban and rural living circle area based on data analysis as described in the first aspect.
[0016] The technical solution provided in this application can achieve the following beneficial effects:
[0017] By collecting target type characteristic data of the target analysis area to construct a basic information database and parsing the database, the corresponding living circle level classification information can be obtained. A trained living circle area classification model is then used to divide the target analysis area. Based on the resulting living circles and their level classifications, the corresponding living circle area classification information is determined. This living circle area classification information, obtained through data analysis, enables the quantitative identification and division of "urban and rural living circles," improving the accuracy of their regional scope. Furthermore, a supply-demand matching model is used to evaluate the matching of the living circle area classification information, allowing for accurate judgment of its rationality. This fills a research gap in the delineation and evaluation mechanisms of urban and rural living circles, providing a reliable foundation for their delineation and evaluation, and ultimately guiding the allocation of public service facilities within these circles.
[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0019] The accompanying drawings, which are incorporated in and form part of this application, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0020] Figure 1 This is a schematic diagram of the system architecture for a data analysis-based method for dividing urban and rural living areas, as shown in an embodiment of this application.
[0021] Figure 2 This is a flowchart illustrating a method for dividing urban and rural living areas based on data analysis, as shown in an embodiment of this application.
[0022] Figure 3 This is a schematic diagram illustrating the process of constructing a basic information database as shown in an embodiment of this application.
[0023] Figure 4 This is a schematic diagram illustrating the process of obtaining information on the classification of living circles, as shown in an embodiment of this application.
[0024] Figure 5 This is a schematic diagram illustrating the process of determining the scope of a living area as shown in an embodiment of this application.
[0025] Figure 6 This is a hardware structure diagram of a computer device shown in an embodiment of this application.
[0026] Figure 7 This is a block diagram illustrating a data analysis-based device for dividing urban and rural living areas according to an embodiment of this application. Detailed Implementation
[0027] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0028] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.
[0029] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."
[0030] In the relevant technologies of this field, the concept of "living circle" first appeared in the mid-20th century. The Japanese planning field proposed a broad concept of living circle, defining its spatial layout and planning units to optimize the allocation and efficient management of community public service facilities during urbanization. Subsequently, the concept of living circle developed in Japanese public service facility planning practices, gradually forming a system centered on residents and using their quality of life and living experience as standards for shaping living circles. Following this, concepts such as settlement circles and permanent residence circles emerged, aiming to meet residents' living needs and connecting these needs with their daily living spatial trajectories, thereby efficiently and orderly optimizing the layout of urban and rural public service facilities. Meanwhile, other countries and regions, due to excessive resource concentration and accelerated urbanization, began to construct regional-level hierarchical classification systems for living circles to guide the layout of various public service facilities. For example, in some regions, a residential area-neighborhood-cluster system is used, focusing on strengthening the allocation of facilities in education, healthcare, transportation, and communication. In other regions, the concept of "local living circle" is adopted, dividing multiple living circles based on natural geographical conditions, residents' travel characteristics, shopping and commuting distances, and production and lifestyle patterns.
[0031] In the process of rapid urbanization, most urban fringe areas are no longer bound by the traditional urban-rural dual administrative framework. Cities and their surrounding rural areas have formed interdependent, interactive, and mutually developing communities. The allocation of urban and rural public service facilities is no longer limited to the optimization of quantity and structure. Compared with the simple rules for dividing living circles in the past, there is now a greater need for universal, refined, and scientific methods for delineating urban and rural living circles, so as to promote the rational allocation of urban and rural public service facilities.
[0032] The main approaches to delineating living circles in related technologies include those based on administrative boundaries and those based on indicators. Administrative boundary-based approaches primarily determine the spatial scope of living circles through manual surveys. For example, existing research uses field visits and sampling surveys to understand residents' daily life behaviors, studies the spatial layout of settlements within living circles, and explores the supply and demand matching of public service facilities in rural areas from the perspective of residents' daily lives, thus dividing living circles. Indicator-based approaches delineate living circles at different levels (5 minutes, 10 minutes, 15 minutes, etc.) based on the "thousand-person index" and residents' travel time. Research on living circle delineation largely focuses on urban community living circles or rural living circles, lacking quantitative, scientific, and data-driven methods for identifying and delineating living circles in urban fringe areas.
[0033] To address the problems existing in related technologies, this application proposes a method and apparatus for delineating the urban and rural living circle area based on data analysis. Before providing a detailed description of the technical solution of this application, a system applying the data analysis-based method for delineating the urban and rural living circle area in this application will be described.
[0034] Figure 1 The diagram illustrates the system architecture of a data-driven method for defining urban and rural living areas.
[0035] like Figure 1 As shown, the system architecture may include terminal device 101, network 102, and server 103. Terminal device 101 may be an electronic device with a display screen, such as a computer, desktop computer, or smartphone; network 102 is used as a medium to provide a communication link between terminal device 101 and server 103, and network 102 may include various link types, such as wired communication links, wireless communication links, etc.
[0036] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, there can be any number of terminal devices, networks, and servers. For example, the servers could be a server cluster.
[0037] This application first provides a method for dividing the urban and rural living circle area based on data analysis.
[0038] Figure 2 The flowchart illustrates a method for delineating urban and rural living circle areas based on data analysis, as shown below. Figure 2 As shown, the process includes at least the following steps:
[0039] Step S21: Obtain target type feature data of the target analysis area, and construct a basic information database based on the target type feature data; wherein, the target type feature data includes: geospatial information data, environmental feature data, economic data, and human data;
[0040] Step S22: Perform data parsing on the basic information database, and determine the living circle level classification information corresponding to the target analysis area based on the data parsing results, wherein the living circle level classification information includes: the service radius corresponding to different levels of living circles;
[0041] Step S23: Divide the target analysis area using the trained living area range division model, and determine the living area range division information corresponding to the target analysis area based on the living areas formed by the division and the living area level division results;
[0042] Step S24: Based on the supply and demand matching model, perform a matching assessment on the area division information of the living circle to obtain the corresponding matching assessment information.
[0043] Next, the method for dividing the urban and rural living circle area based on data analysis in this application will be described in detail.
[0044] In step S21: target type feature data of the target analysis area is obtained, and a basic information database is constructed based on the target type feature data; wherein, the target type feature data includes: geospatial information data, environmental feature data, economic data and human data.
[0045] In an exemplary embodiment of this application, before dividing the urban and rural living circles, it is first necessary to determine the target analysis area, i.e., the research area where the living circle area scope needs to be divided, and then the living circle is divided for the target analysis area. When determining the target analysis area, a living circle area scope division request sent by a terminal device can be received. This living circle area scope division request includes the target analysis area. The living circle area scope division request can then be parsed to obtain the target analysis area. Further, the urban and rural living circle area scope can be divided for the target analysis area.
[0046] For example, a user can initiate a request to define the scope of their living area on their computer, configuring information about the target analysis region, such as the region name and coordinate range, within the request. The computer then sends the request to the server. The server parses the request, retrieves the target analysis region, creates a corresponding living area definition task, writes the task into a task queue, executes the tasks sequentially, generates the corresponding living area definition information, and sends this information back to the user's computer.
[0047] In an exemplary embodiment of this application, after determining the target analysis region, target type feature data of the target analysis region can be obtained, and a basic information database can be constructed based on the target type feature data. Figure 3 This diagram illustrates the process of building a basic information database, such as... Figure 3 As shown, the process includes at least:
[0048] Step S31: Determine the area geographic range corresponding to the target analysis area, obtain the geospatial information corresponding to the target analysis area based on the area geographic range, and import the geospatial information into the information processing platform for spatial positioning to obtain geographic information;
[0049] Step S32: Obtain economic and cultural data corresponding to the target analysis area, and import the economic and cultural data into the information processing platform for data matching to obtain urban and rural population distribution information;
[0050] Step S33: Obtain environmental feature data corresponding to the target analysis area, and import the environmental feature data into the information processing platform for data analysis to obtain slope and aspect vector data corresponding to the target analysis area;
[0051] Step S34: Construct the basic information database based on the geographic information, the urban and rural population distribution data, the slope and the slope aspect vector data.
[0052] Specifically, in step S31, the geographic extent of the target analysis area can be determined first, and sampling point coordinates can be obtained within this geographic extent. Then, using Python web crawling technology and a pre-defined map API (Application Programming Interface), geospatial information such as vector boundaries and road networks of the target analysis area can be obtained based on the sampling point coordinates. This geospatial information is then imported into an information processing platform for spatial localization to obtain geographic information. Specifically, the information processing platform is the ArcGIS platform, a geographic information management system used for editing, managing, and displaying geographic information and map data.
[0053] In step S32, socio-economic development data of the target analysis area can be obtained from statistical yearbooks and population census data, and economic data can be constructed based on the socio-economic development data. The target analysis area contains multiple urban and rural location data. In the ArcGIS platform, the urban and rural location data can be reduced and sorted. Then, the population census data in the target analysis area can be matched with the processed urban and rural location data to obtain a spatial distribution map of urban and rural population. Humanistic data can be constructed based on the spatial distribution map of urban and rural population. In the embodiments of this application, humanistic data includes population data and urban and rural location data.
[0054] In step S33, spectral, texture, and shape features can be obtained from high-resolution remote sensing images. Based on the obtained features, information such as land use, lakes, mountains, and vegetation cover in the images can be identified. At the same time, DEM (Digital Elevation Model) data of the target analysis area can be obtained from the National Earth System Science Data Platform, and elevation analysis can be used in the ArcGIS platform to obtain slope and aspect vector data of the target analysis area.
[0055] In step S22, the basic information database is parsed, and the living circle level classification information corresponding to the target analysis area is determined based on the data parsing results.
[0056] In an exemplary embodiment of this application, before dividing the target analysis area into living area ranges, it is also necessary to determine the living area level division information. The living area level division information can be determined based on the data parsing results obtained by parsing the basic information database through preset indicators.
[0057] Figure 4 This diagram illustrates the process of obtaining information on the hierarchy of living circles, such as... Figure 4 As shown, the process includes at least:
[0058] Step S41: Analyze the basic information database based on preset indicators, and determine the living circle level corresponding to different service objects based on the data analysis results; wherein, the preset indicators include: the service level, service objects, and radiation range of public service facilities corresponding to the target analysis area shown.
[0059] Step S42: Determine the service radius corresponding to different levels of living circles based on the residents' travel time and distance-cost information corresponding to the target analysis area; wherein, the different levels of living circles include: Level 1 living circle, Level 2 living circle, Level 3 living circle and Level 4 living circle.
[0060] Specifically, based on the identified target analysis area and the corresponding urban and rural population spatial distribution map, the urban and rural living circles can be divided into four levels using the service level, service targets, and radiation range of public service facilities in the urban and rural living circles as indicators. These are: Level 1 living circles serving the entire city, Level 2 living circles serving townships and district planning units, Level 3 living circles serving specific blocks, and Level 4 living circles serving community neighborhood committees and villages.
[0061] Based on the travel time and distance-cost information of residents in the target analysis area, the service radius corresponding to the four levels of urban and rural living circles can be determined as follows: the service radius of the first-level living circle is greater than 15km, the service radius of the second-level living circle is 10-15km, the service radius of the third-level living circle is 3km, and the service radius of the fourth-level living circle is 800m.
[0062] In step S23, the target analysis area is divided using a trained living area range division model, and the living area range division information corresponding to the target analysis area is determined based on the living areas formed by the division and the living area level division results.
[0063] In an exemplary embodiment of this application, a living area range division model can be used to divide the target analysis area into living areas. The living area range division model includes a cost distance sub-model and a Thiessen polygon sub-model, wherein the cost distance sub-model is used to determine the center point of the living area, and the Thiessen polygon sub-model is used to determine the Thiessen polygon living area.
[0064] Figure 5 This schematic diagram illustrates the process of determining the boundaries of a living area, such as... Figure 5 As shown, the process includes at least:
[0065] In step S51, the target information corresponding to the target analysis area is rasterized to obtain the cost raster corresponding to the target analysis area.
[0066] In step S52, the cost distance of each position in the cost grid is determined using the cost distance sub-model, and the position corresponding to the minimum cost distance is taken as the center point of the living circle;
[0067] In step S53, based on the center point of the living circle, the target analysis area is divided into multiple Tyson polygon living circles using the Tyson polygon sub-model. The living circle area range division information is determined according to the service radius corresponding to different levels of living circles and each Tyson polygon living circle.
[0068] Specifically, in step S51, land use type, roads, and slope can be used as three factors for calculating the cost raster in the ArcGIS platform. Land use types are subdivided into cultivated land, residential land, construction land, and water areas, and the land uses are reclassified. Subsequently, the reclassified land use type, road, and slope data are rasterized, and weights are assigned using a raster calculator to obtain the cost raster of the target analysis area. Rasterization involves converting vector graphics into bitmaps, i.e., raster images. A raster is a pixel in a raster image, and each pixel represents an attribute value within the target analysis area. For example, it can reflect terrain features (such as elevation and slope), traffic conditions (such as road type and speed limits), environmental conditions (such as soil type and vegetation cover), or other factors that affect travel costs. Correspondingly, each pixel in the cost raster corresponds to a cost distance at different locations.
[0069] In step S52, a cost distance sub-model can be used to process the cost grid to determine the center point of the living circle. When determining the center point, the impedance of the terrain, rivers, and land use type in the target analysis area needs to be considered, i.e., the access cost impedance. Since different access cost impedances result in different cost distances, in this embodiment, the location with the smallest cost distance can be used as the center point of the living circle. It is worth noting that when determining the center point of the living circle, it is also necessary to identify areas with the highest cost values, such as large lakes, reservoirs, and mountains, and these areas need to be avoided when selecting the center point. The formula for calculating the cost distance using the cost distance model is as follows:
[0070] d b =d a +((c a +c b ) / 2)×d (1)
[0071] Where, d b Let d be the cost distance corresponding to pixel b. a c is the cost distance to the previous neighboring pixel a of pixel b. b c aLet be the passage cost impedances of pixels a and b, respectively, and d be the Euclidean distance between pixels a and b.
[0072] In formula (1), the toll cost impedance is related to spatial elements such as road traffic network conditions, terrain slope, and water distribution. This application comprehensively considers the correlation between these elements and the toll cost impedance, and calculates the cost impedance of terrain slope, water bodies, and road traffic network conditions in the target analysis area by superimposing them to obtain the cost grid of the target analysis area. That is, the cost distances corresponding to different pixels in the target analysis area constitute the cost grid, and the cost distances corresponding to different pixels in the target analysis area are represented by the grid form. Furthermore, the point with the smallest cost distance among the different levels of living circles contained in the target analysis area can be taken as the center point of the living circle.
[0073] In step S53, based on the center point of the living circle determined using the cost distance sub-model, the target analysis area can be divided into several Thiessen polygon living circles in the ArcGIS platform using the Thiessen polygon sub-model. Service convenience is guaranteed as long as the geometric distance between any public service facility within each Thiessen polygon living circle and the center point of that living circle is minimized. Furthermore, based on the service radii of the four determined levels of living circles, multiple Thiessen polygon living circles can be classified into different levels to form living circle area delineation information, completing the area delineation of urban and rural living circles, and using this as the basis for configuring the spatial range of public service facilities. The calculation formula for the Thiessen polygon living circle is:
[0074]
[0075] in, Let x be a public service facility element in the Tyson polygon living circle, d(x, pi) be the Euclidean distance from the public service facility element x to the center point pi of the living circle, and d(x, pj) be the Euclidean distance from the public service facility element x to the center point pj of the living circle.
[0076] In this embodiment of the application, the delineation of urban and rural living circles is based on the cost distance sub-model and the Thiessen polygon sub-model, that is, the SAVD (Spatial distance voronoi diagram) method is used for the division, which realizes the quantitative and accurate division of urban and rural living circles.
[0077] In step S24, the matching evaluation of the living area range division information is performed based on the supply and demand matching model to obtain the corresponding matching evaluation results.
[0078] In an exemplary embodiment of this application, the matching evaluation of the living area area division information can be performed based on the supply and demand matching model. The living area area division information includes multiple Tyson polygon living areas. That is, it is necessary to perform a matching evaluation for each Tyson polygon living area based on the supply and demand matching model in order to obtain matching evaluation information corresponding to each Tyson polygon living area.
[0079] Specifically, the supply-demand matching degree of public service facilities in each Tyson polygon living circle can be determined based on the number of service population and the total population with actual needs within each Tyson polygon living circle. Then, matching assessment information is determined based on the supply-demand matching degree of public service facilities in each Tyson polygon living circle and the total number of Tyson polygon living circles. In this embodiment, the calculation formulas for the supply-demand matching degree and the matching assessment are as follows:
[0080]
[0081]
[0082] Among them, E i The supply and demand matching degree of public service facilities in the i-th Tyson polygonal living circle; Let n be the number of people served within the i-th Tyson polygonal living area, i.e., the supply; n is the total number of Tyson polygonal living areas. Let be the total population with actual needs within the i-th Thiessen polygonal living area. Define the average overall matching degree for the living circle, i.e., the matching assessment information.
[0083] In an exemplary embodiment of this application, the rationality of each living circle can be evaluated based on a first matching degree threshold and a second matching degree threshold. Specifically, the first matching degree threshold can be 0.8 and the second matching degree threshold can be 1.2.
[0084] Supply and demand matching degree E i The closer the value is to 1, the more reasonable the delineation of the living circle is. A supply-demand matching degree between 0.8 and 1.2 indicates that the delineation of the living circle is relatively reasonable. A supply-demand matching degree less than 0.8 indicates that the public service facilities within the living circle may not be able to meet the needs of residents; a supply-demand matching degree greater than 1.2 indicates that there may be unreasonable allocation of public service facilities and waste of resources within the living circle.
[0085] In an exemplary embodiment of this disclosure, living areas with a supply-demand matching degree less than a first matching degree threshold can be used as the first living area region segmentation information, and living areas with a supply-demand matching degree greater than a second matching degree threshold can be used as the second living area region segmentation information. The total number of the first and second living areas is compared with a preset threshold. When the total number of unreasonable living areas exceeds the preset threshold, it indicates that the living areas need to be redefined. Specifically, the target range corresponding to the first and second living area region segmentation information can be obtained, and the target range can be updated with sample points, which are the sampling points corresponding to the target range. Then, the target range updated with sample points is redefined using the living area region segmentation model until the supply-demand matching degree corresponding to the redefined living areas is greater than or equal to the first matching degree threshold and less than or equal to the second matching degree threshold. The method of redefineding the target range updated with sample points using the living area region segmentation model is the same as the method of segmenting the target analysis area into living areas in the above embodiment, and will not be described again in this embodiment.
[0086] In an exemplary embodiment of this application, when the supply-demand matching degree and / or matching evaluation result is less than a preset threshold, the sample points in the target analysis area can be updated, and the target analysis area can be re-rasterized. The cost raster obtained by the rasterization process can be processed using the cost distance model to obtain a new living circle center point. Then, the living circle can be re-divided based on the new living circle center point through the living circle area division model, and the supply-demand matching degree and / or matching evaluation information of the living circle can be recalculated until the supply-demand matching degree and / or matching evaluation information is greater than or equal to the preset threshold, and the iteration ends.
[0087] In an exemplary embodiment of this application, a public service facility configuration strategy is determined based on the area division information of the living circle.
[0088] Specifically, after the iteration, the optimized delineation results can be output. These results are then combined with the population per thousand people in the target analysis area to form a "service level + population size" allocation method, providing guidance for the allocation strategy of public service facilities in urban and rural living circles. The public service facility allocation strategy can be based on the "Public Service Facility Allocation Standards for Living Circles at All Levels," allocating public facilities according to the area delineation information of the living circle, including the type and scale of public service facilities. For example, allocated public service facilities may include: educational facilities, medical facilities, cultural facilities, etc.; allocated cultural facilities may include municipal libraries, cultural activity centers, etc. The public service facility allocation standards for living circles at all levels are shown in Table 1.
[0089] Table 1 Standards for the Configuration of Public Service Facilities in Each Level of Living Circle
[0090]
[0091] This application proposes a quantitative method for the delineation and evaluation of urban and rural living circles. By analyzing relevant data on living circles, it innovatively uses a SAVD (Spatial Distance Voronoidiagram, cost distance function and Thiessen polygon)-based method for delineating urban and rural living circles, achieving quantitative and accurate delineation for the first time in the field of urban and rural living circle delineation, achieving this for the first time. Simultaneously, based on a supply-demand matching model, this application proposes a method for the delineation and evaluation of urban and rural living circles, calculating the "supply-demand matching degree" (E) by comparing the number of people served by the living circle with the actual total population demanded. i The size of the area is used to calculate the "matching assessment result" by considering the supply and demand matching degree of each living circle and the number of living circles. Then, the rationality of the living circle division is evaluated based on the "supply and demand matching degree". This is helpful to provide a quantitative and scientific evaluation standard for the effect of living circle delineation and improve the efficiency of public service facility allocation.
[0092] Corresponding to the embodiments of the aforementioned methods, this application also provides an embodiment of a data analysis-based device for dividing urban and rural living areas and the terminal to which it is applied.
[0093] The embodiments of the urban-rural living circle area division device based on data analysis of this application can be applied to computer equipment, such as servers or terminal devices. The device embodiments can be implemented through software, hardware, or a combination of both. Taking software implementation as an example, as a logical device, it is formed by the processor of its data analysis system reading the corresponding computer program instructions from non-volatile memory into memory for execution. From a hardware perspective, such as... Figure 6 The diagram shown is a hardware structure diagram of a computer device used in the data analysis-based urban-rural living circle area division system according to an embodiment of this application. Except for... Figure 6 In addition to the processor 610, memory 630, network interface 620, and non-volatile memory 640 shown, the server or electronic device on which the urban and rural living circle area division device 631 based on data analysis is located in the embodiment may also include other hardware depending on the actual function of the computer device, which will not be described in detail here.
[0094] like Figure 7 As shown, Figure 7 This is a block diagram illustrating a data analysis-based urban-rural living circle area delineation device 70, as shown in an embodiment of this application. The data analysis-based urban-rural living circle area delineation device 70 includes:
[0095] The database construction module 701 is used to acquire target type feature data of the target analysis area and construct a basic information database based on the target type feature data; wherein, the target type feature data includes: geospatial information data, environmental feature data, economic data and human data;
[0096] The living circle level classification module 702 is used to parse the basic information database and determine the living circle level classification information corresponding to the target analysis area based on the data parsing results. The living circle level classification information includes the service radius corresponding to different levels of living circles.
[0097] The living circle segmentation module 703 is used to segment the target analysis area using a trained living circle area segmentation model, and to determine the living circle area segmentation information corresponding to the target analysis area based on the segmented area and the living circle level segmentation result.
[0098] The living circle evaluation module 704 is used to perform a matching evaluation on the living circle area division information based on the supply and demand matching model, so as to obtain the corresponding matching evaluation information.
[0099] Accordingly, this application also provides a computer device, the computer device including a processor; a memory for storing processor-executable instructions; wherein the processor is configured to: acquire target type feature data of a target analysis area, and construct a basic information database based on the target type feature data; wherein the target type feature data includes: geospatial information data, environmental feature data, economic data, and human data; perform data parsing on the basic information database, and determine the living circle level division information corresponding to the target analysis area based on the data parsing results, wherein the living circle level division information includes: service radii corresponding to different levels of living circles; divide the target analysis area using a trained living circle area division model, and determine the living circle area division information corresponding to the target analysis area based on the divided living circles and the living circle level division results; and perform a matching evaluation on the living circle area division information based on a supply and demand matching model to obtain corresponding matching evaluation information.
[0100] The specific implementation process of the functions and roles of each module in the above computer equipment can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.
[0101] For the computer device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The computer device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.
[0102] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0103] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention filed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not claimed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.
[0104] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.
[0105] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A data analysis-based urban and rural living circle regional range division method, characterized in that, The method includes: Acquire target type feature data for the target analysis area, and construct a basic information database based on the target type feature data; wherein, the target type feature data includes: geospatial information data, environmental feature data, economic data, and human data; The basic information database is parsed, and the living circle level classification information corresponding to the target analysis area is determined based on the data parsing results. The living circle level classification information includes the service radius corresponding to different levels of living circles. The target analysis area is divided using a trained living area range division model, and the living area range division information corresponding to the target analysis area is determined based on the living areas formed by the division and the living area level division results. The matching evaluation of the area division information of the living circle is performed based on the supply and demand matching model to obtain the corresponding matching evaluation information; The living circle area division model includes a cost distance sub-model and a Thiessen polygon sub-model. The step of dividing the target analysis area using a trained living area segmentation model, and determining living area segmentation information based on the resulting living areas and the living area level classification results, includes: The target information corresponding to the target analysis area is rasterized to obtain the cost raster corresponding to the target analysis area; The cost distance of each position in the cost grid is determined using the cost distance sub-model, and the position corresponding to the minimum cost distance is taken as the center point of the living circle. Based on the center point of the living circle, the target analysis area is divided into multiple Tyson polygon living circles using the Tyson polygon sub-model. The area division information of the living circle is determined according to the service radius corresponding to different levels of living circles and each Tyson polygon living circle. The matching assessment of the regional division information of the living area based on the supply and demand matching model to obtain the corresponding matching assessment information includes: The supply and demand matching degree of public service facilities in each of the aforementioned Tyson polygon living circles is determined based on the number of service population in each Tyson polygon living circle and the total number of actual demand population in each Tyson polygon living circle. The matching assessment information corresponding to each of the Tyson polygonal living circles is determined based on the supply and demand matching degree of public service facilities in each of the Tyson polygonal living circles and the total number of the Tyson polygonal living circles. The supply and demand matching degree of each of the Thiessen polygon living circles is compared with the first matching degree threshold and the second matching degree threshold respectively to obtain the first living circle area division information where the supply and demand matching degree is less than the first matching degree threshold and the second living circle area division information where the supply and demand matching degree is greater than the second matching degree threshold; The total number of the first living circle area division information and the second living circle area division information is compared with a preset threshold. When the total number is greater than the preset threshold, the target range corresponding to the first living circle area division information and the second living circle area division information is obtained, and the sample points of the target range are updated. The target range after the sample points are updated is re-divided using the living area area division model until the supply and demand matching degree corresponding to the re-divided living area is greater than or equal to the first matching degree threshold and less than or equal to the second matching degree threshold. Wherein, the first matching degree threshold is less than the second matching degree threshold.
2. The method of claim 1, wherein, The step of acquiring target type feature data of the target analysis area and constructing a basic information database based on the target type feature data includes: Determine the area geographic range corresponding to the target analysis area, obtain the geospatial information corresponding to the target analysis area based on the area geographic range, and import the geospatial information into the information processing platform for spatial positioning to obtain geographic information; The system acquires economic and cultural data corresponding to the target analysis area, and imports the economic and cultural data into the information processing platform for data matching to obtain urban and rural population distribution information. The environmental feature data corresponding to the target analysis area is obtained, and the environmental feature data is imported into the information processing platform for data analysis to obtain the slope and aspect vector data corresponding to the target analysis area. The basic information database is constructed based on the geographic information, the urban and rural population distribution data, the slope, and the slope aspect vector data.
3. The method according to claim 1 or 2, characterized in that, The step of parsing the basic information database and determining the living circle level classification information corresponding to the target analysis area based on the data parsing results includes: The basic information database is analyzed based on preset indicators, and the living circle level corresponding to different service objects is determined based on the data analysis results; wherein, the preset indicators include: the service level, service objects, and radiation range of public service facilities corresponding to the target analysis area; Based on the residents' travel time and distance-cost information corresponding to the target analysis area, the service radius corresponding to different levels of living circles is determined; wherein, the different levels of living circles include: Level 1 living circle, Level 2 living circle, Level 3 living circle and Level 4 living circle.
4. The method of claim 1, wherein, The method further includes: Based on the information on the division of the living area, a strategy for configuring public service facilities is determined.
5. The method of claim 1, wherein, Before acquiring the target type feature data of the target analysis region, the method further includes: Receive a request from the terminal device to define the scope of the living area; Parse the request to define the living area range in order to obtain the target analysis area.
6. A device for delineating the regional scope of urban and rural living circles based on data analysis, characterized in that, The device includes: The database construction module is used to acquire target type feature data of the target analysis area and construct a basic information database based on the target type feature data; wherein, the target type feature data includes: geospatial information data, environmental feature data, economic data, and human data; The living circle level classification module is used to parse the basic information database and determine the living circle level classification information corresponding to the target analysis area based on the data parsing results. The living circle level classification information includes the service radius corresponding to different levels of living circles. The living circle segmentation module is used to segment the target analysis area using a trained living circle area segmentation model, and to determine the living circle area segmentation information based on the segmented area and the living circle level segmentation results. The living circle area division model includes a cost distance sub-model and a Thiessen polygon sub-model. The step of dividing the target analysis area using a trained living area segmentation model, and determining living area segmentation information based on the resulting living areas and the living area level classification results, includes: The target information corresponding to the target analysis area is rasterized to obtain the cost raster corresponding to the target analysis area; the cost distance of each position in the cost raster is determined using the cost distance sub-model, and the position corresponding to the minimum cost distance is taken as the center point of the living circle; based on the center point of the living circle, the target analysis area is divided into multiple Tyson polygon living circles using the Tyson polygon sub-model; the living circle area range division information is determined according to the service radius corresponding to different levels of living circles and each Tyson polygon living circle; The living circle evaluation module is used to evaluate the matching of the living circle area division information based on the supply and demand matching model in order to obtain the corresponding matching evaluation information. The matching assessment of the regional division information of the living area based on the supply and demand matching model to obtain the corresponding matching assessment information includes: The supply-demand matching degree of public service facilities in each Tyson polygon living circle is determined based on the number of service population within each Tyson polygon living circle and the total number of actual demand population within each Tyson polygon living circle; the matching assessment information corresponding to each Tyson polygon living circle is determined based on the supply-demand matching degree of public service facilities in each Tyson polygon living circle and the total number of Tyson polygon living circles. The supply and demand matching degree of each of the Thiessen polygon living circles is compared with a first matching degree threshold and a second matching degree threshold, respectively, to obtain the first living circle area division information where the supply and demand matching degree is less than the first matching degree threshold and the second living circle area division information where the supply and demand matching degree is greater than the second matching degree threshold. The total number of the first living circle area division information and the second living circle area division information is compared with a preset threshold. When the total number is greater than the preset threshold, the target range corresponding to the first living circle area division information and the second living circle area division information is obtained, and the target range is updated with sample points. The target range after the sample point update is re-divided using the living circle area division model until the supply and demand matching degree corresponding to the re-divided living circle is greater than or equal to the first matching degree threshold and less than or equal to the second matching degree threshold; wherein, the first matching degree threshold is less than the second matching degree threshold.
7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, When the processor executes the program, it implements the method for dividing the urban and rural living circle area based on data analysis as described in any one of claims 1-5.