CN116630117A - Urban population structure analysis method, system, terminal and medium - Google Patents
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Abstract
The application relates to a method, a system, a terminal and a medium for analyzing urban population structure, which relate to the technical field of urban population structure analysis, and the method comprises the following steps: collecting relevant information of population and economy in a preset area; constructing a spatial information database according to the related information, and storing the related information in the spatial information database in real time; and calling the related information, constructing a spatial analysis model of the population structure and the economic structure according to the related information, and analyzing the population result and the economic structure according to the spatial analysis model to obtain an analysis result. The application has the effect of improving the efficiency of statistics and analysis of population structures.
Description
Technical Field
The application relates to the technical field of urban population structure analysis, in particular to an urban population structure analysis method, an urban population structure analysis system, an urban population structure analysis terminal and an urban population structure analysis medium.
Background
The population structure is not only the result of human development, but also a very important factor that profoundly influences future social development.
Population structure refers to the division of the population into individual components. With the current development of society, three kinds of population constitution including natural constitution of population, regional constitution and social constitution can be obtained according to different characteristics of population. Wherein, the natural constitution is obtained by dividing according to physiological attributes of population, and mainly comprises sex constitution and age constitution; regional composition refers to the geographic distribution of the population, including administrative, natural and economic regional distribution, urban and rural distribution, and the like; social formations are defined in terms of socioeconomic properties of the population, including marital status formations, family type formations, cultural education level formations, etc.
The population structure analysis of the related art is mostly performed by adopting an offline questionnaire investigation mode, and the offline questionnaire investigation mode can cause the problem of low statistics and analysis efficiency.
Disclosure of Invention
The application aims to provide an urban population structure analysis method, system, terminal and medium capable of improving population structure statistics and analysis efficiency.
In a first aspect, the method for analyzing urban population structure provided by the application adopts the following technical scheme:
a method of urban population structure analysis, comprising:
collecting relevant information of population and economy in a preset area;
constructing a spatial information database according to the related information, and storing the related information in the spatial information database in real time;
and calling the related information, constructing a spatial analysis model of the population structure and the economic structure according to the related information, and analyzing the population result and the economic structure according to the spatial analysis model to obtain an analysis result.
By adopting the technical scheme, the population and economic related information in the preset area is collected, a spatial information database is constructed according to the collected related information so as to conveniently store the related information, then a spatial analysis model of population results and economic structures can be constructed according to the related information, and finally the population structures and the economic structures are analyzed by using the spatial analysis model to obtain analysis results; compared with the traditional method of analyzing population structure and economic structure by adopting manual off-line questionnaires, the method can effectively improve statistics and analysis efficiency.
Optionally, the related information includes industry data, enterprise data, cell phone signaling data, and questionnaire interview data.
By adopting the technical scheme, the information is combined to form the population and economy related information so as to analyze the population structure and the economy structure in the preset area.
Optionally, the constructing a spatial analysis model according to the related information specifically includes:
dividing industries according to preset industry codes to obtain industry types, respectively summarizing industry data of each industry at a space unit level according to the industry types to generate an industry data table, and linking the industry data table to a preset city group base map by utilizing ArcGIS software to obtain an industry space information database;
collecting enterprise directories in the preset area according to the industry type, screening, sorting, classifying, correcting coordinates and converting formats of the enterprise directories to obtain processed enterprise directories, and generating an enterprise space information database by ArcGIS software according to the processed enterprise directories;
acquiring mobile phone signaling data according to a user activity type, acquiring user attribute information according to the mobile phone signaling data, and generating a user space information database by utilizing ArcGIS software according to the user attribute information;
collecting questionnaire interview data according to a first preset rule, and generating a questionnaire interview spatial information database by utilizing ArcGIS software according to the questionnaire interview data;
and merging the industry space information database, the enterprise space information database, the user space information database and the questionnaire interview space information database to obtain the space information database.
By adopting the technical scheme, the industry data is summarized to obtain the industry data table, the industry data table is linked to the city group base map to generate the industry space information database, the enterprise directory is collected and processed to obtain the processed enterprise directory, the enterprise space information database is generated according to the processed enterprise directory, the user attribute information is collected, the user space information database is generated according to the user attribute information, the questionnaire interview data is collected, the questionnaire interview space information database is generated according to the questionnaire interview data, and the space information database is generated by fusing the plurality of databases, so that the various data can be conveniently summarized and stored.
Optionally, the user attribute information includes a user name, a user gender, a user age, a user location, an activity start time, an activity end time, and a longitude and latitude of a base station providing the service.
Optionally, the retrieving the related information, constructing a spatial analysis model of the population structure and the economic structure according to the related information, and analyzing the population structure and the economic structure according to the spatial analysis model to obtain an analysis result, which specifically includes:
the relevant information is called, and the relevant information is analyzed to obtain population structural space information and economic structural space information, wherein the population structural space information comprises young people, middle-aged people, teenager children and old people, and the economic structural space information comprises agricultural economic activities, manufacturing economic activities and service industry economic activities;
and establishing an association relation between the population structure and the economic structure according to the population structure space information and the economic structure space information, establishing a space analysis model according to the association relation, and analyzing the population structure and the economic structure according to the space analysis model to obtain an analysis result.
By adopting the technical scheme, the relevant information is analyzed to obtain the population structural space information and the economic structural space information, then the association relation between the population structure and the economic structure is established according to the population structural space information and the economic structural space information, and the space analysis model is constructed according to the association relation, so that the construction of the space analysis model is facilitated.
Optionally, the establishing the association relationship between the population structure and the economic structure according to the population structure space information and the economic structure space information specifically includes:
acquiring first stay time of a user in a first area in a first preset observation time period, and if the first stay time exceeds a first preset time threshold value, determining the first area as an effective working place of the user;
acquiring second residence time of the user in a second area in the first preset observation time period, and if the second residence time exceeds a second preset time threshold value, determining the second area as an effective residence of the user;
and respectively establishing association relations between the effective workplaces of the users and the effective living places of the users and the economic structure.
Through adopting above-mentioned technical scheme, through observing the dwell time of user in the first time quantum of predetermineeing, when the first dwell time of first regional exceeds first time threshold value of predetermineeing, then can regard as the effective place of working of user with first regional, when the second dwell time of second regional exceeds second time threshold value of predetermineeing, then can regard as the effective place of living of user with the second regional, and then can establish the association between effective place of working and economic structure and effective place of living and the economic structure respectively to the convenience carries out statistical analysis to the population structure in the area of predetermineeing.
Optionally, the spatial information database includes a base database and an incremental database, the base database is used for storing the related information and deleting failure information, and the incremental database is used for acquiring the updated related information in the cloud server and supplementing the updated related information to the base database.
By adopting the technical scheme, the basic database has the function of deleting the failure information, the available capacity of the basic database can be increased, the data transmission efficiency of the basic database can be further improved, the incremental database acquires the updated relevant information in the cloud server, and the updated relevant information is supplemented to the basic database, so that the real-time update of the relevant information stored in the basic database is realized.
In a second aspect, the present application provides an urban population structure analysis system, which adopts the following technical scheme:
a city population structural analysis system, comprising:
the acquisition module is used for acquiring the related information of population and economy in a preset area;
the first construction module is used for constructing a spatial information database according to the related information and storing the related information in the spatial information database in real time;
the second construction module is used for calling the related information, constructing a spatial analysis model of the population structure and the economic structure according to the related information, and analyzing the population structure and the economic structure according to the spatial analysis model to obtain an analysis result.
By adopting the technical scheme, the acquisition module acquires the population and economic related information in the preset area, the first construction module constructs a spatial information database according to the acquired related information so as to store the related information conveniently, the second construction module can construct a spatial analysis model of population results and economic structures according to the related information, and finally the spatial analysis model is utilized to analyze the population structures and the economic structures to obtain analysis results; compared with the traditional method of analyzing population structure and economic structure by adopting manual off-line questionnaires, the method can effectively improve statistics and analysis efficiency.
In a third aspect, the present application provides a terminal, which adopts the following technical scheme:
a terminal comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, the processor loading the computer program, performing the method of the first aspect.
By adopting the technical scheme, the method of the first aspect generates a computer program and stores the computer program in the memory to be loaded and executed by the processor, so that a user can establish a connection with the system through the terminal and inquire about various contents processed by the system.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer readable storage medium having stored therein a computer program which, when loaded by a processor, performs the method of the first aspect.
By adopting the technical scheme, the method of the first aspect generates a computer program and stores the computer program in a computer readable storage medium, and after the computer readable storage medium is loaded into any computer, any computer can execute the method of the first aspect.
Drawings
FIG. 1 is a flow chart of a method of steps S100-S300 in an embodiment of the application;
FIG. 2 is a flow chart of a method of steps S210-S250 in an embodiment of the application;
FIG. 3 is a flow chart of a method of steps S310-S320 in an embodiment of the application;
FIG. 4 is a flow chart of the method of steps S321-S323 in an embodiment of the application;
FIG. 5 is a block diagram of a urban population structure analysis system of the present application;
in the figure, 1, an acquisition module; 2. a first building block; 3. and a second building block.
Detailed Description
The present application will be described in further detail with reference to fig. 1 to 5.
In analyzing the progress of urbanization and economic development, the extra large city and its surrounding areas are called focus of attention. New spaces in the form of "broad islands of large urban areas" (Zhao et al, 2017:148) produce various terms, such as "global urban area" (Scott, 2001), "extra large urban area" (Hall and paint, 2016), (multi-core urban area) (Turok and Bailey, 2004) and (metropolitan area) (growth, 2012), each associated with a different theoretical concept, so chinese students commonly put them into urban groups.
A method of urban population structure analysis, referring to fig. 1, comprising the steps of:
s100: and collecting relevant information of population and economy in a preset area.
In one embodiment of the application, the relevant information may include industry data, enterprise data, cell phone signaling data, questionnaire interview data, and the like.
Related information table:
s200: and constructing a spatial information database according to the related information, and storing the related information in the spatial information database in real time.
In one embodiment of the present application, referring to fig. 2, step S200 specifically includes the following steps:
s210: dividing industries according to preset industry codes to obtain industry types, respectively summarizing industry data of each industry on a space unit level according to the industry types to generate an industry data table, and linking the industry data table to a preset city group base map by utilizing ArcGIS software to obtain an industry space information database.
Specifically, in the embodiment, the industry data of the city and county level directly come from economic census and population census, and the industry data of the village and town street level is obtained by summarizing and calculating enterprise interest Point (POI) data; because of the adjustment of national economy industry classification, for the convenience of longitudinal comparison, the industry classification of different years is unified based on the national economy industry classification standard (GBT 4754-2017), and the manufacturing industry is divided into labor-intensive manufacturing industry, capital-intensive manufacturing industry and technology-intensive manufacturing industry according to two-digit industry classification codes, wherein the two-digit industry classification codes 13-42 are formed by 29 departments; the productive service industry is divided into logistics service industry, information service industry, financial service industry, business service industry and science and technology service industry, and consists of 19 departments of 53-60, 63-69 and 71-75; and secondly, respectively summarizing the data of each industry department according to space units such as a city, a county, a village, a town or a street.
The method comprises the steps of collecting employment and enterprise data of each industry department by using population census data in 2000, 2010 and 2020 and economic census data in 2004, 2008, 2013 and 2018 at the level of the city and county; at the street level of villages and towns, the enterprise interest point data are utilized to summarize the number of enterprises of each industry department of each space unit; and finally, summarizing the obtained industry data of the space unit layers of the city, county and village and town streets to generate an industry data table, and linking the obtained industry data table with the city group base map (a shift format) through an ArcGIS software platform so as to generate a planar industry space information database.
S220: and acquiring the enterprise directory in the preset area according to the industry type, screening, sorting, classifying, correcting coordinates and converting the format of the enterprise directory to obtain a processed enterprise directory, and generating an enterprise space information database by utilizing ArcGIS software according to the processed enterprise directory.
Specifically, in this embodiment, the enterprise data is mainly POI data of an enterprise, and the enterprise POI data is obtained through a conventional website or App, for example, enterprise knows or performs sky and eye inspection, so as to obtain an enterprise directory of the urban mass production service industry and the manufacturing industry.
The system screening, sorting, classifying, coordinate correcting and format converting are carried out on the obtained enterprise directory to obtain a processed enterprise directory, and the urban mass production service industry and manufacturing industry punctiform enterprise space information database is generated through the ArcGIS software platform.
S230: and acquiring mobile phone signaling data according to the user activity type, acquiring user attribute information according to the mobile phone signaling data, and generating a user space information database by utilizing ArcGIS software according to the user attribute information.
Specifically, the user activity type in this embodiment includes at least one of calling, surfing the internet and sending a short message, that is, when the user has at least one of calling, surfing the internet and sending a short message, the background will automatically acquire the attribute information of the user.
Specifically, the user attribute information in this embodiment includes a user name, a user gender, a user age, a user location, an activity start time, an activity end time, and a longitude and latitude of a base station providing a service; the user attribute information is acquired by a communication company, for example, mobile, connected or telecommunication, the activity start time is the activity start time, and the activity end time is the activity end time.
The mobile phone data with the characteristics of large data are important data sources for researching urban population geography, so that the defect of statistical data is greatly overcome, and strict encryption treatment measures are carried out on the acquired data before the data are acquired in order to protect the privacy of users.
The mobile phone signaling data mainly selects the track of the user in 2021 and 2022 working days at random.
S240: the questionnaire interview data is collected according to a first preset rule and a questionnaire interview spatial information database is generated using ArcGIS software according to the questionnaire interview data.
Specifically, in this embodiment, key enterprises, related government departments, residents of different ages and sexes in a preset area are selected, and questionnaire interview data is obtained through on-line and off-line questionnaire surveys, semi-structure interviews and the like.
S250: and integrating the industry space information database, the enterprise space information database, the user space information database and the questionnaire interview space information database to obtain a space information database.
Specifically, in this embodiment, according to the obtained industry spatial information database, enterprise spatial information database, user spatial information database, and questionnaire interview spatial information database, the above databases are fused by using an existing database fusion tool, so that the spatial information database can be obtained.
S300: and calling the related information, constructing a spatial analysis model of the population structure and the economic structure according to the related information, and analyzing the population structure and the economic structure according to the spatial analysis model to obtain an analysis result.
In one embodiment of the present application, referring to fig. 3, step S300 specifically includes the following steps:
s310: and the relevant information is called and analyzed to obtain population structural space information and economic structural space information, wherein the population structural space information comprises young population, middle-aged population, juvenile population and aged population, and the economic structural space information comprises agricultural economic activities, manufacturing economic activities and service industry economic activities.
S320: and establishing an association relation between the population structure and the economic structure according to the population structure space information and the economic structure space information, establishing a space analysis model according to the association relation, and analyzing the population structure and the economic structure according to the space analysis model to obtain an analysis result.
The spatial analysis model in the embodiment mainly adopts enterprise density, enterprise space superposition analysis, enterprise bivariate spatial autocorrelation and the like to quantitatively describe urban population and economic spatial distribution, spatial relationship and change trend.
The density condition of the discrete points in the surrounding neighborhood can be calculated by adopting an enterprise density analysis method, so that economy presents continuous space change, and the space distribution characteristics of the points are researched through the space change of the point density in the area.
The enterprise density analysis method uses the following formula to calculate:
wherein fn (x) is enterprise density, n is enterprise number, h is search radius, K is kernel density coefficient, and x-xi is distance from enterprise estimated position to enterprise actual position.
And the density condition of enterprises in the preset area can be calculated through the formula, so that the productive service industry and manufacturing industry gathering areas with different gathering levels can be obtained.
The enterprise space superposition analysis method refers to the interdependence relationship of the space unit attribute on the space position, represents the space aggregation degree, and is divided into global space autocorrelation and local space autocorrelation according to the size of the analysis space range.
Global spatial autocorrelation uses the following formula:
wherein Moran 'S (I) is a global space autocorrelation index, the value range of Moran' S (I) is [ 1,1 ], S2 is a variance value of industry employment, n is a sample number, yi is an industry employment number of an I area, yj is an industry employment number of a j area, Y0 is an industry employment average, and Wij is a corresponding element of a space weight matrix.
Further, if Moran's (I) is greater than 0, it means that there is a positive correlation in space, if Moran's (I) is less than 0, it means that there is a negative correlation in space, and if Moran's (I) is equal to 0, it means that there is no spatial correlation and it is in a random distribution state.
Wherein the local spatial autocorrelation may represent a similarity or difference between spatial reference units and their neighboring spatial unit property values.
The local spatial autocorrelation uses the following formula:
wherein Local Moran's (I) is a Local spatial autocorrelation index, n is a sample number, yi is an industry employment number in an I area, yj is an industry employment number in a j area, Y0 is an industry employment average number, wij is a corresponding element of a spatial weight matrix, and Zi and Zj are observation attribute values respectively.
Further, if Local Moran's (I) is greater than 0, it means that the Local spatial unit similarity values tend to be spatially aggregated, whereas if Local Moran's (I) is less than 0, it means that the Local spatial unit similarity values tend to be dispersed.
And the distribution conditions of industries and enterprises in the preset area can be analyzed through the three sub-models, so that the population structure in the preset area can be conveniently analyzed subsequently according to the distribution conditions of the industries and enterprises obtained by analysis, and a space analysis model between the population structure and the economic structure in the preset area is constructed.
In one embodiment of the present application, referring to fig. 4, step S320 specifically includes the following steps:
s321: and acquiring the first stay time of the user in the first area in a first preset observation time period, and if the first stay time exceeds a first preset time threshold value, determining the first area as the effective work area of the user.
S322: and acquiring second residence time of the user in the second area in the first preset observation time period, and if the second residence time exceeds a second preset time threshold value, determining the second area as the effective residence of the user.
S323: and respectively establishing association relations between the effective work places of the users and the effective living places of the users and the economic structure.
In one embodiment of the present application, the effective operation area and the effective residence area are identified by using the mobile phone signaling data, so as to evaluate the association relation between the effective operation area and the effective residence area and the economic structure respectively.
Specifically, the first preset observation period in this embodiment is set to be nine am to five pm, the first preset time threshold in this embodiment is set to be six hours, and the user is observed every day between nine am and five pm to record the residence time of the user in the first area, and when the first residence time exceeds six hours, the first area can be considered as the effective working area of the user.
Specifically, the second preset time threshold in this embodiment is set to five hours, and the user is observed every day between nine am and five pm to record the residence time of the user in the second area, and when the second residence time exceeds eight hours, the second area can be considered as the effective residence of the user.
Furthermore, the space dislocation index, the job position deviation degree, the job position separation rate and other indexes are used for measuring the space matching relation between the residence of the employment population and the work of the urban population, so that the effective working place of the user and the association relation between the effective residence place of the user and the economic structure can be established according to the space matching relation between the residence of the employment population and the work, namely, when the users staying in the effective working place for a long time are more, the employment situation of the user is indicated to be good, and on the contrary, when the users staying in the effective residence place for a long time are more, the employment situation of the user is indicated to be not optimistic, and the economic structure in the preset area is also indicated to be bad.
The implementation principle of the embodiment of the application is as follows: and acquiring industry data, enterprise data, user attribute information and questionnaire interview data in the preset area, processing according to the information to construct a spatial information database, and then constructing a spatial analysis model of population structure and economic structure according to the processed information, so that the population structure and the economic structure can be analyzed by using the spatial analysis model to finally obtain an analysis result, if the employment situation of personnel in the preset area is good, the economic structure in the preset area can be indicated to be good, otherwise, if the employment situation of personnel in the preset area is not optimistic, the economic structure in the preset area can be indicated to be bad.
The embodiment of the application discloses an urban population structure analysis system, referring to fig. 5, which specifically comprises an acquisition module 1, a first construction module 2 and a second construction module 3; the acquisition module 1 is used for acquiring relevant information of population and economy in a preset area, the first construction module 2 is used for constructing a spatial information database according to the relevant information and storing the relevant information in the spatial information database in real time, and the second construction module 3 is used for calling the relevant information, constructing a spatial analysis model of population structure and economy structure according to the relevant information and analyzing the population structure and economy structure according to the spatial analysis model to obtain an analysis result.
In particular, the system in this embodiment adopts the urban population structure analysis method in the foregoing embodiment, so specific details about the system are not described herein.
The embodiment of the application discloses a terminal, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the urban population structure analysis method of the embodiment is executed when the processor loads the computer program.
In one embodiment of the present application, the terminal may be a desktop computer, a notebook computer, or a cloud server, and the terminal includes, but is not limited to, a processor and a memory, for example, the terminal may further include an input/output device, a network access device, a bus, and the like.
In one embodiment of the present application, the processor may be a central processing unit, and of course, other general purpose processors, digital signal processors, application specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. may also be used according to actual usage requirements, and the general purpose processor may be a microprocessor or any conventional processor, etc., which is not limited by the present application.
In one embodiment of the present application, the memory may be an internal storage unit of the terminal, for example, a hard disk or a memory of the terminal, or may be an external storage device of the terminal, for example, a plug-in hard disk, a smart memory card, a secure digital card, or a flash memory card provided on the terminal, or the like, and the terminal may also be a combination of the internal storage unit of the terminal and the external storage device, where the memory is used to store a computer program and other programs and data required by the terminal, and the memory may also be used to temporarily store data that has been output or is to be output, which is not limited by the present application.
Through the setting of the terminal, the urban population structure analysis method of the embodiment is stored in the memory of the terminal and can be loaded and executed on the processor of the terminal, so that a user can establish contact with the system through the terminal and inquire various contents processed by the system.
The embodiment of the application discloses a computer readable storage medium, and a computer program is stored in the computer readable storage medium, wherein the computer program is loaded by a processor to execute the urban population structure analysis method of the embodiment.
In one embodiment of the present application, the computer program may be stored in a computer readable storage medium, where the computer program includes computer program code, where the computer program code may be in a source code form, an object code form, or some middleware form, etc., and the computer readable storage medium includes any entity or device capable of carrying the computer program code, a recording medium, a usb disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, a software distribution medium, etc., where the computer readable storage medium includes, but is not limited to, the above components.
The urban population structure analysis method of the above embodiment is stored in a computer readable storage medium through the arrangement of the computer readable storage medium, and is loaded and executed on a processor, and after the computer readable storage medium is loaded into any computer, any computer can execute the urban population structure analysis method of the above embodiment.
The embodiments of the present application are all preferred embodiments of the present application, and are not intended to limit the scope of the present application, wherein like reference numerals are used to refer to like elements throughout. Therefore: all equivalent changes in structure, shape and principle of the application should be covered in the scope of protection of the application.
Claims (10)
1. A method for analyzing urban population structure, comprising:
collecting relevant information of population and economy in a preset area;
constructing a spatial information database according to the related information, and storing the related information in the spatial information database in real time;
and calling the related information, constructing a spatial analysis model of the population structure and the economic structure according to the related information, and analyzing the population result and the economic structure according to the spatial analysis model to obtain an analysis result.
2. The urban population structure analysis method of claim 1, wherein the related information comprises industry data, enterprise data, cell phone signaling data, and questionnaire interview data.
3. The urban population structure analysis method according to claim 2, wherein said constructing a spatial analysis model from said related information comprises:
dividing industries according to preset industry codes to obtain industry types, respectively summarizing industry data of each industry at a space unit level according to the industry types to generate an industry data table, and linking the industry data table to a preset city group base map by utilizing ArcGIS software to obtain an industry space information database;
collecting enterprise directories in the preset area according to the industry type, screening, sorting, classifying, correcting coordinates and converting formats of the enterprise directories to obtain processed enterprise directories, and generating an enterprise space information database by ArcGIS software according to the processed enterprise directories;
acquiring mobile phone signaling data according to a user activity type, acquiring user attribute information according to the mobile phone signaling data, and generating a user space information database by utilizing ArcGIS software according to the user attribute information;
collecting questionnaire interview data according to a first preset rule, and generating a questionnaire interview spatial information database by utilizing ArcGIS software according to the questionnaire interview data;
and merging the industry space information database, the enterprise space information database, the user space information database and the questionnaire interview space information database to obtain the space information database.
4. The urban population structure analysis method of claim 3, wherein the user attribute information comprises a user name, a user gender, a user age, a user location, an activity start time, an activity end time, and a latitude and longitude of a base station providing the service.
5. The urban population structure analysis method according to claim 1, wherein the retrieving the related information, constructing a spatial analysis model of population structure and economic structure according to the related information, and analyzing the population structure and the economic structure according to the spatial analysis model to obtain an analysis result, specifically comprising:
the relevant information is called, and the relevant information is analyzed to obtain population structural space information and economic structural space information, wherein the population structural space information comprises young people, middle-aged people, teenager children and old people, and the economic structural space information comprises agricultural economic activities, manufacturing economic activities and service industry economic activities;
and establishing an association relation between the population structure and the economic structure according to the population structure space information and the economic structure space information, establishing a space analysis model according to the association relation, and analyzing the population structure and the economic structure according to the space analysis model to obtain an analysis result.
6. The urban population structure analysis method according to claim 5, wherein the establishing an association relationship between population structure and economic structure according to the population structure space information and economic structure space information specifically comprises:
acquiring first stay time of a user in a first area in a first preset observation time period, and if the first stay time exceeds a first preset time threshold value, determining the first area as an effective working place of the user;
acquiring second residence time of the user in a second area in the first preset observation time period, and if the second residence time exceeds a second preset time threshold value, determining the second area as an effective residence of the user;
and respectively establishing association relations between the effective workplaces of the users and the effective living places of the users and the economic structure.
7. The urban population structure analysis method according to any one of claims 1 to 6, wherein the spatial information database comprises a base database for storing the related information and deleting failure information, and an incremental database for acquiring the related information updated in a cloud server and supplementing the updated related information to the base database.
8. A system for urban population structure analysis, comprising:
the acquisition module (1) is used for acquiring relevant information of population and economy in a preset area;
the first construction module (2) is used for constructing a spatial information database according to the related information and storing the related information in the spatial information database in real time;
and the second construction module (3) is used for calling the related information, constructing a spatial analysis model of the population structure and the economic structure according to the related information, and analyzing the population structure and the economic structure according to the spatial analysis model to obtain an analysis result.
9. A terminal comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, characterized in that the processor performs the method of any of claims 1-7 when the computer program is loaded by the processor.
10. A computer readable storage medium having a computer program stored therein, characterized in that the computer program, when loaded by a processor, performs the method of any of claims 1-7.
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| CN202310651733.0A CN116630117A (en) | 2023-06-03 | 2023-06-03 | Urban population structure analysis method, system, terminal and medium |
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| CN202310651733.0A CN116630117A (en) | 2023-06-03 | 2023-06-03 | Urban population structure analysis method, system, terminal and medium |
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