Urban three-dimensional space expansion simulation method, terminal equipment and storage medium

Abstract

The invention provides an urban three-dimensional space expansion simulation method, terminal equipment and a storage medium, and relates to the technical field of urban planning and management.The method specifically comprises the steps that social economic parameters, environmental parameters and traffic parameters are collected, and after the parameters are subjected to dimensionless processing, a land availability index, a traffic convenience index and an environmental quality index are calculated; key parameters of the city are generated according to the indexes; and analyzing the correlation among the infrastructure adaptability index, the urban development potential index and the urban expansion area by using a Pearson's correlation coefficient method, and predicting the urban expansion area. The invention provides the urban three-dimensional space expansion simulation method which comprehensively considers social economy, environment and traffic factors through systematized parameter acquisition and analysis. According to the method, quantitative evaluation of land availability, traffic convenience and environment quality is realized, and the influence of infrastructure adaptability and urban development potential on urban expansion is clarified through correlation analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of urban planning and management, and in particular to a method for simulating urban three-dimensional space expansion, a terminal device and a storage medium. Background Art

[0002] With the rapid advancement of urbanization around the world, urban expansion has become an important challenge faced by all countries. Traditional urban expansion simulation methods often focus on the analysis of a single factor, such as population growth or land use change, and lack comprehensive consideration of multi-dimensional factors. This limitation makes the simulation results often unable to accurately reflect the complexity and dynamics of urban development. In practical applications, there is a close relationship between socioeconomic factors such as economic growth rate, employment opportunities and coverage of public service facilities and urban expansion; while environmental factors such as green space area, air quality and water resource utilization also play a vital role in the sustainability of urban expansion. In addition, traffic parameters such as traffic flow and accident rate directly affect the accessibility of the city and people's quality of life. However, existing simulation technologies often ignore the interaction of these multi-level factors, resulting in a lack of scientific basis for urban planning and difficulty in coping with increasingly severe urban problems.

[0003] In addition, traditional methods are also deficient in data analysis. Many urban expansion studies rely mainly on qualitative descriptions and empirical rules, lacking systematic statistical analysis and model building. This makes it impossible for researchers to achieve quantitative evaluation when exploring the relationship between urban expansion and related factors. For example, the adaptability of infrastructure and the development potential of cities are often difficult to quantify, and their impact on urban expansion has not been clearly presented through scientific methods. This lack of quantitative analysis often causes urban managers to face insufficient information and decision-making blind spots when formulating relevant policies. Therefore, there is an urgent need for a new simulation method that can comprehensively consider a variety of socio-economic, environmental and traffic parameters, and reveal the inherent mechanism of urban expansion through quantitative analysis to support scientific urban planning and sustainable development strategies. Summary of the invention

[0004] The purpose of the present invention is to provide a method, a terminal device and a storage medium for simulating the expansion of a three-dimensional urban space, so as to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for simulating urban three-dimensional space expansion, the specific steps comprising: Step 1: Collect socioeconomic parameters, environmental parameters and traffic parameters related to urban expansion. The socioeconomic parameters are population density, economic growth rate, public transportation coverage and per capita commuting time. The environmental parameters are total building area, total land area, green area, air quality index, water quality index, noise level and waste treatment rate. The traffic parameters are traffic flow and traffic accident rate. Step 2: Based on the dimensionless socio-economic parameters, environmental parameters and traffic parameters, the land availability index, traffic convenience index and environmental quality index of the city are calculated; and the key parameters of the city are generated according to the above indexes, which are the infrastructure adaptability index and the urban development potential index; Step 3: Use the Pearson correlation coefficient method to analyze the correlation between the infrastructure adaptability index and the urban expansion area, and the correlation between the urban development potential index and the urban expansion area, and combine the correlation analysis results to calculate the predicted urban expansion area.

[0006] Furthermore, the socio-economic parameters, environmental parameters and traffic parameters related to urban expansion are collected based on the following specific logic: Obtain the population density of the city from the local statistics bureau and record it as ; The economic growth rate is obtained from the local economic report and recorded as ; The city's green area, total building area and total land area are collected through environmental protection departments, monitoring stations and statistical data, and the city's green coverage rate and building density are calculated according to the following formula: ; in, is the green area coverage rate, is the green area, is the total land area; ; in, is the building density, is the total building area, is the total land area; Obtain public transportation operation data from the local transportation management department, including bus and subway station distribution and service range. By analyzing the operation data, the public transportation coverage rate of the city is obtained, which is recorded as ; Query the commuting time statistics released by the local traffic management department and the statistics bureau to obtain the average commuting time per person, recorded as ; The public transportation accessibility index of the city is calculated according to the following formula: ; in, is the public transportation accessibility index, is the public transportation coverage rate, is the average commuting time per capita; Obtain the city’s traffic flow and traffic accident rate from the local traffic management department and the public security traffic police department, and record the traffic flow as , the traffic accident rate is recorded as ; The traffic flow safety index of the city is calculated according to the following formula: ; in, is the traffic flow safety index, For traffic flow, is the traffic accident rate; The city's air quality index, water quality index, noise level and waste treatment rate are collected through environmental protection departments, monitoring stations and statistical data. The noise level is the average noise level during the morning and evening peak hours, and the waste treatment rate is the ratio of the treatment and recycling of urban garbage.

[0007] Furthermore, the calculation obtains the land availability index, transportation convenience index and environmental quality index of the city, and the formula based on which is as follows: ; in, is the land availability index, is the green area coverage rate, is the building density, is the first constant correction exponent; The traffic convenience index of the city is calculated according to the following formula: ; in, is the traffic convenience index, is the public transportation accessibility index, is the traffic flow safety index, is the second constant correction exponent; The environmental quality index of the city is calculated according to the following formula: ; in, is the environmental quality index, is the air quality index, is the water quality index, is the green area coverage rate, is the noise level, is the waste treatment rate, , , is the preset scaling factor, and , is the third constant correction exponent.

[0008] Furthermore, the specific logic for generating the key parameters of the city is as follows: ; in, is the infrastructure adaptability index, is the population density, is the economic growth rate, is the traffic convenience index, is the land availability index, a, b, c are preset proportional coefficients, and ; ; in, is the city development potential index, is the economic growth rate, is the traffic convenience index, is the environmental quality index, m and n are preset proportional coefficients, and .

[0009] Furthermore, the Pearson correlation coefficient method is used to analyze the correlation between the infrastructure adaptability index and the urban expansion area, and the correlation between the urban development potential index and the urban expansion area, respectively, based on the specific logic: The Pearson correlation coefficient is a statistic that measures the strength and direction of the linear relationship between two variables, and its value range is: , the specific steps are as follows: Collect a set of historical key parameters of the city and the corresponding urban expansion area, the key parameters are infrastructure adaptability index and urban development potential index; The Pearson correlation coefficient is calculated according to the following formula: ; in, is the Pearson correlation coefficient, Indicates The key parameters of the samples, namely the infrastructure adaptability index or urban development potential index in the i-th sample, are used to conduct correlation analysis with the corresponding urban expansion area. Indicates The urban expansion area of ​​the samples is is the mean of the key parameter X, is the mean of urban expansion area; The calculated Pearson correlation coefficient r is used to analyze the relationship between each key parameter and the urban expansion area: when When , it indicates that there is a positive correlation between this parameter and the urban expansion area, which means that when the parameter increases, the urban expansion area also increases; when When , it indicates that there is a negative correlation between this parameter and the urban expansion area, which means that when the parameter increases, the urban expansion area decreases; when When , there is no correlation, which means that there is no linear relationship between this parameter and the urban expansion area; Among them, when The closer it is to 1, the stronger the correlation is.

[0010] Furthermore, the specific logic for calculating the predicted urban expansion area by combining the analysis results of the correlation is as follows: ; in, is the predicted urban expansion area, is the infrastructure adaptability index, is the city development potential index, , is the preset proportional coefficient, and its specific value is determined according to the correlation analysis results. is the fourth constant correction exponent.

[0011] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a method for simulating urban three-dimensional spatial expansion that comprehensively considers socio-economic, environmental and traffic factors through systematic parameter collection and analysis. This method not only achieves a quantitative assessment of land availability, traffic convenience and environmental quality, but also clarifies the impact of infrastructure adaptability and urban development potential on urban expansion through correlation analysis. This systematic simulation method can provide a scientific basis for urban planning, effectively guide the management and regulation of urban expansion, reduce the negative impact of urban expansion on the environment, and improve the sustainability of urban development. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the overall method flow of the present invention. DETAILED DESCRIPTION

[0013] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0014] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0015] Example: See also Figure 1 , the present invention provides a technical solution: A method for simulating urban three-dimensional space expansion, the specific steps comprising: Step 1: Collect socioeconomic parameters, environmental parameters and traffic parameters related to urban expansion. The socioeconomic parameters are population density, economic growth rate, public transportation coverage and per capita commuting time. The environmental parameters are total building area, total land area, green area, air quality index, water quality index, noise level and waste treatment rate. The traffic parameters are traffic flow and traffic accident rate. In this embodiment, the social economic parameters, environmental parameters and traffic parameters related to urban expansion are collected, and the specific logic is as follows: Obtain the population density of the city from the local statistics bureau and record it as ; The economic growth rate is obtained from the local economic report and recorded as ; The city's green area, total building area and total land area are collected through environmental protection departments, monitoring stations and statistical data, and the city's green coverage rate and building density are calculated according to the following formula: ; in, is the green area coverage rate, is the green area, is the total land area; ; in, is the building density, is the total building area, is the total land area; Obtain public transportation operation data from the local transportation management department, including bus and subway station distribution and service range. By analyzing the operation data, the public transportation coverage rate of the city is obtained, which is recorded as ; Query the commuting time statistics released by the local traffic management department and the statistics bureau to obtain the average commuting time per person, recorded as ; The public transportation accessibility index of the city is calculated according to the following formula: ; in, is the public transportation accessibility index, is the public transportation coverage rate, is the average commuting time per capita; Obtain the city’s traffic flow and traffic accident rate from the local traffic management department and the public security traffic police department, and record the traffic flow as , the traffic accident rate is recorded as ; The traffic flow safety index of the city is calculated according to the following formula: ; in, is the traffic flow safety index, For traffic flow, is the traffic accident rate; The city's air quality index, water quality index, noise level and waste treatment rate are collected through environmental protection departments, monitoring stations and statistical data. The air quality index includes the monitoring of the following key pollutants: PM2.5 and PM10, sulfur dioxide, carbon monoxide, nitrogen oxides and ozone; the water quality index includes the monitoring of the following key indicators: dissolved oxygen, pH value, biochemical oxygen demand, total suspended solids and heavy metal content; the calculation methods and standards of the air quality index and water quality index usually refer to national environmental protection standards; the noise level is the average noise level during the morning peak and evening peak hours; the waste treatment rate is the ratio of the treatment and recycling of urban garbage.

[0016] The advantage of step 1 is that it provides a comprehensive data basis by systematically collecting multi-dimensional parameters related to urban expansion, ensuring the comprehensiveness and accuracy of the simulation analysis. Compared with traditional methods, this comprehensive data collection method can deeply explore the interaction between different factors, avoid the one-sidedness and misleadingness that may be caused by single factor analysis, and thus provide a more reliable basis for subsequent analysis.

[0017] Compared with the existing technology, step 1 can more accurately reflect the complexity and diversity of urban expansion by introducing the quantification of multiple key parameters. Traditional urban expansion models often focus on one aspect of factors and ignore the impact of other related factors. The implementation of this step enables the model to not only evaluate the impact of a single factor, but also reveal the intrinsic relationship between different parameters, thereby improving the scientificity and practicality of the research. In this patent scheme, the implementation of step 1 lays a solid foundation for the overall scheme, making subsequent index calculations, correlation analysis and urban expansion forecasts more accurate and reliable. Through systematic data collection and processing, the entire scheme can achieve a comprehensive analysis of urban development potential and expansion patterns, thereby providing urban planners with more guiding suggestions and decision-making basis, and promoting sustainable development and effective management of cities.

[0018] Step 2: Based on the dimensionless socio-economic parameters, environmental parameters and traffic parameters, the land availability index, traffic convenience index and environmental quality index of the city are calculated; and the key parameters of the city are generated according to the above indexes, which are the infrastructure adaptability index and the urban development potential index; In this embodiment, the land availability index, traffic convenience index and environmental quality index of the city are calculated based on the following formula: ; in, is the land availability index, is the green area coverage rate, is the building density, is the first constant correction index; when the green coverage ratio When it increases, it means that the green space provides more ecological space and leisure areas, improves the quality of land use and living environment, so Increase accordingly; when the building density When the land is enlarged, high-density buildings can concentrate resources and services, improve the economic efficiency and functional diversity of land, and thus increases accordingly; that is, , and There is a positive correlation.

[0019] The traffic convenience index of the city is calculated according to the following formula: ; in, is the traffic convenience index, is the public transportation accessibility index, is the traffic flow safety index, is the second constant correction index; when the public transportation accessibility index increases, the traffic convenience index increases, because higher accessibility means that residents and users can more easily access various transportation facilities and services, improving travel efficiency; when the traffic flow safety index increases, the traffic convenience index increases, because higher safety reduces the risk of traffic accidents, making people more confident and comfortable when traveling, thereby promoting traffic utilization; that is, , and There is a positive correlation.

[0020] The environmental quality index of the city is calculated according to the following formula: ; in, is the environmental quality index, is the air quality index, is the water quality index, is the green area coverage rate, is the noise level, is the waste treatment rate, , , is the preset scaling factor, and , because the quality of air and water directly affects the health and quality of life of residents, so their weight should be higher than the green space coverage and waste treatment rate related to environmental beauty and ecological services. The impact of noise level is usually indirect, reflected by the impact on residents' psychology and living comfort, so its weight is the lowest; is the third constant correction index; from the formula, it can be obtained that , , , Environmental Quality Index There is a positive correlation, Environmental Quality Index There is a negative correlation.

[0021] The specific logic for generating the key parameters of the city is as follows: ; in, is the infrastructure adaptability index, is the population density, is the economic growth rate, is the traffic convenience index, is the land availability index, a, b, c are preset proportional coefficients, and This is because economic growth rate plays a core role in infrastructure adaptability, while transportation convenience and land availability are relatively less important, and the impact of population density is more basic and indirect; the agglomeration effect generated in densely populated areas will attract more investment and business activities, which will further promote the improvement and expansion of infrastructure, thereby improving infrastructure adaptability; that is, , , , There is a positive correlation with the infrastructure adaptability index; ; in, is the city development potential index, is the economic growth rate, is the traffic convenience index, is the environmental quality index, m and n are preset proportional coefficients, and This is because economic growth provides cities with the necessary resources and funds to promote infrastructure construction and environmental improvement. If economic growth is weak, even if the quality of transportation and environment is good, the city's development potential will be limited. Therefore, the role of economic growth is considered to be fundamental and its weight should be higher, which means that , , Urban Development Potential Index There is a positive correlation.

[0022] The advantage of step 2 is that the land availability index, transportation convenience index and environmental quality index obtained through dimensionless processing can standardize data of different dimensions so that they can be compared and analyzed at the same level. This processing not only eliminates the impact of different indicator dimensions, but also enhances the comparability between indicators, providing more intuitive and powerful support for subsequent decision-making, and ensuring the accuracy and reliability of the model in analyzing and predicting urban expansion.

[0023] Compared with the existing technology, step 2 significantly improves the scientificity and systematicness of urban expansion simulation by introducing the calculation of comprehensive indexes. Traditional urban models often rely only on simple linear relationships or qualitative analysis, and lack an in-depth understanding of the combined effects of multiple factors. This step, by constructing multiple key indexes, can more comprehensively reflect the status of urban development and its potential trends, thereby providing more solid data support for the prediction of urban expansion. In this patent scheme, the implementation of step 2 provides a key quantitative tool for the entire model, making the subsequent Pearson correlation coefficient analysis and the prediction of urban expansion area more scientific and accurate. Through clear index classification and precise parameter calculation, this step provides a quantitative basis for urban planning decisions, helping decision makers better understand the driving factors and potential challenges of urban expansion, thereby promoting scientific management and sustainable development of cities.

[0024] Step 3: Use the Pearson correlation coefficient method to analyze the correlation between the infrastructure adaptability index and the urban expansion area, and the correlation between the urban development potential index and the urban expansion area, and combine the correlation analysis results to calculate the predicted urban expansion area; In this embodiment, the Pearson correlation coefficient method is used to analyze the correlation between the infrastructure adaptability index and the urban expansion area, and the correlation between the urban development potential index and the urban expansion area, respectively, based on the specific logic: The Pearson correlation coefficient is a statistic that measures the strength and direction of the linear relationship between two variables, and its value range is: , the specific steps are as follows: Collect a set of historical key parameters of the city and the corresponding urban expansion area, the key parameters are infrastructure adaptability index and urban development potential index; The Pearson correlation coefficient is calculated according to the following formula: ; in, is the Pearson correlation coefficient, Indicates The key parameters of the samples, namely the infrastructure adaptability index or urban development potential index in the i-th sample, are used to conduct correlation analysis with the corresponding urban expansion area. Indicates The urban expansion area of ​​the samples is is the mean of the key parameter X, is the mean of urban expansion area; The calculated Pearson correlation coefficient r is used to analyze the relationship between each key parameter and the urban expansion area: when When , it indicates that there is a positive correlation between this parameter and the urban expansion area, which means that when the parameter increases, the urban expansion area also increases; when When , it indicates that there is a negative correlation between this parameter and the urban expansion area, which means that when the parameter increases, the urban expansion area decreases; when When , there is no correlation, which means that there is no linear relationship between this parameter and the urban expansion area; Among them, when The closer it is to 1, the stronger the correlation is.

[0025] The specific logic for calculating the predicted urban expansion area by combining the analysis results of the correlation is as follows: ; in, is the predicted urban expansion area, is the infrastructure adaptability index, is the city development potential index, , is the preset proportional coefficient, and its specific value is determined according to the correlation analysis results: the Pearson correlation index between the infrastructure adaptability index and the urban expansion area, and the Pearson correlation index between the urban development potential index and the urban expansion area are calibrated as r1 and r2 respectively, r1 and r2 are scaled proportionally to convert them into the preset proportional coefficients in this formula, and the sum of the absolute values ​​of the two preset proportional coefficients is ensured to be equal to 1. is the fourth constant correction exponent.

[0026] The advantage of step 3 is that it uses the Pearson correlation coefficient method to systematically analyze the correlation between the infrastructure adaptability index, the urban development potential index and the urban expansion area. This statistical analysis method can not only quantify the relationship between different variables, but also reveal potential causal relationships, making the prediction of urban expansion more scientific and accurate. Through this data-driven approach, step 3 can provide a stronger logical basis for decision-making.

[0027] Compared with the prior art, the introduction of step 3 makes the urban expansion prediction not limited to simple empirical rules or qualitative judgments, but is based on a solid statistical analysis foundation. Many traditional methods often ignore the relationship and influence between various factors when predicting urban expansion. This step can clearly identify the key factors affecting urban expansion through Pearson correlation coefficient analysis, thereby improving the accuracy and reliability of the prediction. In this patent scheme, the implementation of step 3 plays a key role in promoting the overall scheme, so that the entire simulation process not only has a scientific basis, but also improves the value of practical application. Through in-depth analysis of correlations, decision makers can better understand which factors have a significant impact on urban expansion, so as to formulate more effective urban planning strategies. At the same time, the results of this step can provide a clear direction for the formulation and implementation of subsequent policies, and promote the sustainable development and reasonable layout of cities.

[0028] The present invention also includes a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, any one of the modules in the system is implemented.

[0029] The present invention also includes a terminal device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute any one of the modules in the system through the computer program.

[0030] In the formula, a, b, c, m, n, , , , The specific values ​​of and ω are generally determined by those skilled in the art according to actual conditions. The technicians in this field collect multiple groups of sample data, set corresponding preset proportional coefficients for each group of sample data, substitute the preset proportional coefficients and the collected sample data into the formula, observe the accuracy of the model output and the rationality of the results through repeated experiments and parameter adjustments, gradually adjust these factor coefficients, and compare the performance and effect of the model under different parameter settings to find the optimal coefficient combination, screen the calculated factor coefficients and take the average, and obtain a, b, c, m, n, , , , and the value of ω.

[0031] In addition, the size of the preset factor coefficient is to quantify each parameter to obtain a specific value. In order to facilitate subsequent comparison, the size of the coefficient depends on the amount of sample data and the preset proportional coefficient initially set by technical personnel in this field for each set of sample data. It is not unique as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0032] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0033] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0034] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0035] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for simulating urban three-dimensional space expansion, characterized in that: The specific steps include: Step 1: Collect socioeconomic parameters, environmental parameters and traffic parameters related to urban expansion. The socioeconomic parameters are population density, economic growth rate, public transportation coverage and per capita commuting time. The environmental parameters are total building area, total land area, green area, air quality index, water quality index, noise level and waste treatment rate. The traffic parameters are traffic flow and traffic accident rate. Step 2: Based on the dimensionless socio-economic parameters, environmental parameters and traffic parameters, the land availability index, traffic convenience index and environmental quality index of the city are calculated; and the key parameters of the city are generated according to the above indexes, which are the infrastructure adaptability index and the urban development potential index; Step 3: Use the Pearson correlation coefficient method to analyze the correlation between the infrastructure adaptability index and the urban expansion area, and the correlation between the urban development potential index and the urban expansion area, and combine the correlation analysis results to calculate the predicted urban expansion area.

2. A method for simulating urban three-dimensional space expansion according to claim 1, characterized in that: The specific logic for collecting socio-economic, environmental and traffic parameters related to urban expansion is as follows: Obtain the population density of the city from the local statistics bureau and record it as ; The economic growth rate is obtained from the local economic report and recorded as ; The city's green area, total building area and total land area are collected through environmental protection departments, monitoring stations and statistical data, and the city's green coverage rate and building density are calculated according to the following formula: ； in, is the green area coverage rate, is the green area, is the total land area; ； in, is the building density, is the total building area, is the total land area; Obtain public transportation operation data from the local transportation management department, including bus and subway station distribution and service range. By analyzing the operation data, the public transportation coverage rate of the city is obtained, which is recorded as ; Query the commuting time statistics released by the local traffic management department and the statistics bureau to obtain the average commuting time per person, recorded as ; The public transportation accessibility index of the city is calculated according to the following formula: ； in, is the public transportation accessibility index, is the public transportation coverage rate, is the average commuting time per capita; Obtain the city’s traffic flow and traffic accident rate from the local traffic management department and the public security traffic police department, and record the traffic flow as , the traffic accident rate is recorded as ; The traffic flow safety index of the city is calculated according to the following formula: ； in, is the traffic flow safety index, For traffic flow, is the traffic accident rate; The city's air quality index, water quality index, noise level and waste treatment rate are collected through environmental protection departments, monitoring stations and statistical data. The noise level is the average noise level during the morning and evening peak hours, and the waste treatment rate is the ratio of the treatment and recycling of urban garbage.

3. A method for simulating urban three-dimensional space expansion according to claim 2, characterized in that: The calculations obtained the city's land availability index, transportation convenience index and environmental quality index, based on the following formula: ； in, is the land availability index, is the green area coverage rate, is the building density, is the first constant correction exponent; The traffic convenience index of the city is calculated according to the following formula: ； in, is the traffic convenience index, is the public transportation accessibility index, is the traffic flow safety index, is the second constant correction exponent; The environmental quality index of the city is calculated according to the following formula: ； in, is the environmental quality index, is the air quality index, is the water quality index, is the green area coverage rate, is the noise level, is the waste treatment rate, , , is the preset scaling factor, and , is the third constant correction exponent.

4. The method for simulating urban three-dimensional space expansion according to claim 1, characterized in that: The specific logic for generating the key parameters of the city is as follows: ； in, is the infrastructure adaptability index, is the population density, is the economic growth rate, is the traffic convenience index, is the land availability index, a, b, c are preset proportional coefficients, and ; ； in, is the city development potential index, is the economic growth rate, is the traffic convenience index, is the environmental quality index, m and n are preset proportional coefficients, and .

5. A method for simulating urban three-dimensional space expansion according to claim 4, characterized in that: The Pearson correlation coefficient method is used to analyze the correlation between the infrastructure adaptability index and the urban expansion area, and the correlation between the urban development potential index and the urban expansion area, respectively. The specific logic is as follows: The Pearson correlation coefficient is a statistic that measures the strength and direction of the linear relationship between two variables, and its value range is: , the specific steps are as follows: Collect a set of historical key parameters of the city and the corresponding urban expansion area, the key parameters are infrastructure adaptability index and urban development potential index; The Pearson correlation coefficient is calculated according to the following formula: ； in, is the Pearson correlation coefficient, Indicates The key parameters of the samples, namely the infrastructure adaptability index or urban development potential index in the i-th sample, are used to conduct correlation analysis with the corresponding urban expansion area. Indicates The urban expansion area of ​​the samples is is the mean of the key parameter X, is the mean of urban expansion area; The calculated Pearson correlation coefficient r is used to analyze the relationship between each key parameter and the urban expansion area: when When , it indicates that there is a positive correlation between this parameter and the urban expansion area, which means that when the parameter increases, the urban expansion area also increases; when When , it indicates that there is a negative correlation between this parameter and the urban expansion area, which means that when the parameter increases, the urban expansion area decreases; when When , there is no correlation, which means that there is no linear relationship between this parameter and the urban expansion area; Among them, when The closer it is to 1, the stronger the correlation is.

6. The method for simulating urban three-dimensional space expansion according to claim 1, characterized in that: The specific logic for calculating the predicted urban expansion area by combining the analysis results of the correlation is as follows: ； in, is the predicted urban expansion area, is the infrastructure adaptability index, is the city development potential index, , is the preset proportional coefficient, and its specific value is determined according to the correlation analysis results. is the fourth constant correction exponent.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it is used to implement the following modules: A parameter collection module is used to collect socio-economic parameters, environmental parameters and traffic parameters related to urban expansion, wherein the socio-economic parameters are population density, economic growth rate, public transportation coverage rate and per capita commuting time, the environmental parameters are total building area, total land area, green area, air quality index, water quality index, noise level and waste treatment rate, and the traffic parameters are traffic flow and traffic accident rate; The data processing module calculates the land availability index, traffic convenience index and environmental quality index of the city based on the dimensionless processed socio-economic parameters, environmental parameters and traffic parameters; and generates the key parameters of the city according to the above indexes, which are the infrastructure adaptability index and the urban development potential index; The correlation analysis and prediction module is used to use the Pearson correlation coefficient method to analyze the correlation between the infrastructure adaptability index and the urban expansion area, the correlation between the urban development potential index and the urban expansion area, and combine the correlation analysis results to calculate the predicted urban expansion area.

8. A terminal device, comprising a memory and a processor, characterized in that: The memory stores a computer program that can be executed by a processor, and the memory adopts the storage medium according to claim 7.

Images