Multi-parameter-based collaborative rail transit station area space updating intensity definition method and system

Abstract

The application discloses a multi-parameter-based collaborative rail transit station area space updating intensity definition method and system, relates to the technical field of rail transit station area space updating intensity evaluation, and comprises the following steps: receiving an initial sample area, defining the range of the initial sample area, and obtaining plots in the station area; dividing the plots in the station area, obtaining plots of different updating types, and calculating the station updating intensity definition index by using the plots of different updating types; performing correlation analysis on the station updating intensity definition index, obtaining an analysis result, generating different analysis groups according to the analysis result, obtaining rail transit station intensity characteristic research elements according to the analysis groups, wherein the rail transit station intensity characteristic research elements correspond to the station updating intensity definition index; receiving a sample station, taking the station updating intensity definition index corresponding to different rail transit station intensity characteristic research elements as input variables of the sample station, and performing cluster analysis to obtain a definition result.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rail transit station area space updating intensity evaluation, in particular to a multi-parameter-based collaborative rail transit station area space updating intensity definition method and system. BACKGROUND

[0002] After experiencing the rapid urbanization development stage, the urban space pattern and land use of China gradually step into stability, and the focus of urban development gradually shifts to the perfection of urban functions and the improvement of spatial quality. At the same time, cities advocate low-carbon travel, and with the large-scale construction of rail transit, it brings a good opportunity for urban renewal.

[0003] In order to make full use of the land value around the station, the development intensity is often improved. However, the land use structure of the built-up area is stable and the ownership is complex, so it is not easy to improve the development intensity in a large-scale incremental way, and a fine development intensity evaluation method is needed. The current evaluation method mainly focuses on development intensity, which is used to evaluate urban land and urban capacity, and is a comprehensive reflection of urban land use degree and spatial carrying capacity. The indexes for measuring development intensity usually include building area, population and employment scale, etc. These indexes show the characteristics of multi-level, multi-purpose, multi-element, complexity and dynamics. However, in the current control detailed planning and land transfer conditions, the development intensity index mainly focuses on the volume rate, and there is a problem of one-dimensional analysis caused by single index. Moreover, the existing development intensity evaluation method is difficult to adapt to the development of rail transit station area urban space renewal in the context of urban renewal, and cannot fully reflect the degree of change. SUMMARY

[0004] To solve the problems mentioned in the background, the purpose of the present application is to provide a multi-parameter-based collaborative rail transit station area space updating intensity definition method and system.

[0005] The purpose of the present application can be achieved by the following technical solution: a multi-parameter-based collaborative rail transit station area space updating intensity definition method, characterized in that the method comprises the following steps:

[0006] An initial sample area is received, and the initial sample area is range-defined to obtain a plot within the station area, wherein the initial sample area is divided by a part of the range around the rail transit station;

[0007] The plot within the station area is divided to obtain plots of different updating types, and the station updating intensity definition index is calculated using the plots of different updating types;

[0008] Correlation analysis is performed on the station renewal intensity definition indexes to obtain an analysis result, different analysis groups are generated according to the analysis result, and track transportation station intensity characteristic research elements are obtained according to the analysis groups, wherein the track transportation station intensity characteristic research elements correspond to the station renewal intensity definition indexes.

[0009] A sample station is received, and clustering analysis is performed on the sample station by taking the station renewal intensity definition indexes corresponding to different track transportation station intensity characteristic research elements as input variables to obtain a definition result.

[0010] Preferably, the land blocks in the station area are divided into a reduced update land block, an unchanged update land block, a stock update land block and an incremental update land block.

[0011] Preferably, the reduced update land block refers to a land block that originally accommodates building functions and undertakes urban functions, and is currently in a state of demolition and construction, or is updated to a public space such as green space or square; the unchanged update land block refers to a land block whose buildings and land use remain unchanged, and only the appearance of part of the buildings, the space quality and the urban environment are improved; the stock update land block refers to a land block whose buildings are replaced due to functional requirements or urban space planning adjustment, and the overall development amount increases, decreases or remains unchanged; and the incremental update land block refers to a land block that is initially in a state of planned development or unplanned development, and has a building development amount after several years.

[0012] Preferably, the station renewal intensity definition indexes include a building relative update amount Q, a building absolute update amount S, a volume rate update amount V, a building density update amount R, a functional density update amount D and a functional mix degree update amount LM.

[0013] Preferably, the building relative update amount Q is calculated according to the following formula:

[0014] Q = A1 - A0

[0015] In the formula, A1 is the total area of the building after update, A0 is the total area of the building before update, and Q is the building relative update amount.

[0016] The building absolute update amount S is calculated according to the following formula:

[0017] S = |Qi|

[0018] ∑S = ∑|Qi|

[0019] In the formula, Qi is the building relative update amount of different update land block types (i = 1, 2, 3, 4, 1, 2, 3, 4 respectively represent the reduced update land block, the unchanged update land block, the stock update land block and the incremental update land block), and S is the building absolute update amount.

[0020] The volume rate update amount V is calculated according to the following formula:

[0021]

[0022] In the formula, Q is the relative building renewal amount; SM is the total land area; and V is the volume rate renewal amount.

[0023] Preferably, the calculation formula of the building density renewal amount R is as follows:

[0024]

[0025] In the formula, B1 is the total building site area after renewal, B0 is the total building site area before renewal; SM is the total land area; and R is the building density renewal amount.

[0026] The calculation formula of the functional density renewal amount D is as follows:

[0027]

[0028] In the formula, P1 is the number of POIs in the station area range after renewal, P0 is the number of POIs in the station area range before renewal; SM is the total land area; and D is the functional density renewal amount.

[0029] The calculation formula of the functional mix renewal amount LM is as follows:

[0030]

[0031]

[0032] LM = LM1-LM0

[0033] In the formula, F u represents the proportion of the number of POIs of the u type in the research area, and k represents the total number n u of the u type; N represents the total amount of POI data in the research area; and LM a represents the land functional mix in the station research range, when a = 1, it represents the land functional mix after renewal, when a = 0, it represents the land functional mix before renewal, and LM is the functional mix renewal amount.

[0034] Preferably, the process of performing correlation analysis on the station update intensity definition indicators adopts correlation analysis in SPSS, adopts Pearson correlation coefficient test, inputs 6 station update intensity definition indicators as analysis variables, obtains the correlation strength between different station update intensity definition indicators through correlation analysis, and obtains an analysis result.

[0035] Preferably, the track transit station intensity characteristic research elements include development volatility, land intensification, and functional diversity.

[0036] In a second aspect, to achieve the above object, the present application discloses a multi-parameter-based collaborative rail transit station area space update intensity definition system, comprising:

[0037] A range defining module is configured to receive an initial sample area, define the range of the initial sample area, and obtain a land block in the station area, wherein the initial sample area is divided by a partial range around the rail transit station.

[0038] A land block dividing module is configured to divide the land block in the station area to obtain land blocks of different update types, and calculate a station update intensity definition index by using the land blocks of different update types.

[0039] A correlation analysis module is configured to analyze the correlation of the station update intensity definition index, obtain an analysis result, generate different analysis groups according to the analysis result, and obtain a rail transit station intensity characteristic research element according to the analysis groups, wherein the rail transit station intensity characteristic research element corresponds to the station update intensity definition index.

[0040] A definition analysis module is configured to receive a sample station, take the station update intensity definition index corresponding to different rail transit station intensity characteristic research elements as an input variable, and perform clustering analysis to obtain a definition result.

[0041] In another aspect of the present application, to achieve the above object, a device is disclosed, comprising:

[0042] One or more processors;

[0043] A memory for storing one or more programs;

[0044] When one or more programs are executed by one or more processors, one or more processors implement the multi-parameter-based collaborative rail transit station area space update intensity definition method as described above.

[0045] The present application has the following advantages:

[0046] The application provides a scientific and objective evaluation method, which helps government decision-makers, urban planners and developers make more intelligent planning and development strategies. Based on specific renewal intensity data, it can be determined whether to build new buildings, rebuild or retain existing buildings and infrastructure; by evaluating the spatial renewal intensity, urban planners can better plan land use and ensure optimal use of land resources. This helps to reduce unnecessary land waste and increase the value of land; the automatic calculation and data visualization function of the method can improve planning efficiency and reduce the time and cost of decision-making. This makes the urban planning process more efficient and convenient; by considering multiple factors, including environmental and social factors, the method helps to reduce the risk in the planning and development process. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction will be given below to the drawings needed to be used in the embodiments or prior art descriptions. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor;

[0048] Figure 1 is a flowchart of the method of the present application;

[0049] Figure 2 is a schematic diagram of the evaluation index correlation result derivation research element of the present application;

[0050] Figure 3 is a S-Q-V linear relationship distribution diagram of the present application;

[0051] Figure 4 is a R-Q linear relationship distribution V-Q linear relationship distribution diagram of the present application;

[0052] Figure 5 is a D-R linear relationship distribution D-Q linear relationship distribution diagram of the present application;

[0053] Figure 6 is a LM-S-D linear relationship distribution diagram of the present application;

[0054] Figure 7 is a system structure diagram of the present application;

[0055] Figure 8 is a ten-minute walking distance diagram of the present application;

[0056] Figure 9 is a renewal fluctuation intensity inter-class distance diagram of the present application;

[0057] Figure 10 is a land use intensity inter-class distance diagram of the present application;

[0058] Figure 11 is a functional diversity intensity inter-class distance map of the present application. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work are within the protection scope of the present application.

[0060] As shown in Figure 1 the multi-parameter-based collaborative rail transit station area spatial update intensity definition method, the method comprises the following steps:

[0061] An initial sample area is received, and the initial sample area is range-defined to obtain a plot within a station area, wherein the initial sample area is divided by a partial range around a rail transit station;

[0062] First, a certain range around a rail transit station needs to be determined as an initial sample area, so that the area around the station that can be reached by a ten-minute walk is completely obtained. Therefore, in this paper, the station area within 4km 2 around the station is selected as the initial sample area. Then, each entrance of a station along a subway line in a city is taken as a starting point, and the research range is obtained by superimposing the reachable range within ten minutes by walking. According to the present road network and the entrances of the rail transit station, an Arcgis road network dataset is established. The walking speed of a person is usually 80-100m / min. The reachable range within ten minutes by walking is calculated at a speed of 80m / min.

[0063] The plots within the station area are divided to obtain plots of different update types, and the station update intensity definition index is calculated by using the plots of different update types;

[0064] The plots within the station area are divided according to the change characteristics before and after the update to obtain plots of reduction update, non-update, stock update and increment update.

[0065] The reduced amount of land update mainly refers to the original building function, bearing the city function of land present situation for demolition to be built state, or update to green, square and other public space. The land use is not updated, which refers to the building and land use in the land. The present situation basically remains unchanged, only the improvement of part of building appearance, space quality, urban environment and so on. The stock of land update mainly refers to the building on the land due to the functional demand or the adjustment of urban space planning replacement, the total development amount may increase, decrease or remain unchanged, such as the shantytown is updated to parking lot land. The result of stock update is not only the improvement of strength, the improvement of human space use experience comfort, the balance of urban function in the whole region and the rationality, which are the significance of stock update. The incremental update land refers to the initial state of land which is planned to be developed or is not planned to be developed, and after several years, the land has building development amount.

[0066] The site update intensity definition index includes building relative update amount Q, building absolute update amount S, volume rate update amount V, building density update amount R, function density update amount D and function mixing degree update amount LM.

[0067] The building relative update amount Q is defined as the difference between the total area of the building after update and the total area of the building before update, and the calculation formula of the building relative update amount Q is as follows:

[0068] Q=A1-A0

[0069] In the formula, A1 is the total area of the building after update, A0 is the total area of the building before update, and Q is the building relative update amount;

[0070] Compared with Q, |Q| represents the absolute update amount of the building on the land, which reflects the change degree of the building layout on the land, and can better reflect the update intensity of the site, and the calculation formula of the building absolute update amount S is as follows:

[0071] S=|Qi|

[0072] ∑S=∑|Qi|

[0073] In the formula, Qi is the building relative update amount of different update land types (i=1, 2, 3, 4, 1, 2, 3, 4 represent reduced amount of land update, land not updated, stock of land update and incremental update land respectively), and S is the building absolute update amount;

[0074] Different from the conventional definition of volume rate index, the volume rate update amount is the ratio of the building relative update amount on the land in the site to the land area, and the calculation formula of the volume rate update amount V is as follows:

[0075]

[0076] In the formula, Q is the building relative update amount, SM is the total area of the land, and V is the volume rate update amount.

[0077] The building density update amount is defined as the ratio of the relative update amount of the total building projection area to the plot construction land area, which is used to evaluate the space environment in the plot and has an important influence on the city interface. The calculation formula of the building density update amount R is as follows:

[0078]

[0079] In the formula, B1 is the total area of the building site after the update, B0 is the total area of the building site before the update, SM is the total land area, and R is the building density update amount.

[0080] The calculation of the functional density update amount relies on the POI information in the station area range. The data is mainly sourced from the OSM open map. The functional density update amount analysis of the functional industry in the rail transit station area before and after the update can reflect the change degree of the target aggregation in space and also reflect the change degree of the domain vitality. The calculation formula of the functional density update amount D is as follows:

[0081]

[0082] In the formula, P1 is the number of POIs in the station area range after the update, P0 is the number of POIs in the station area range before the update, SM is the total land area, and D is the functional density update amount.

[0083] The functional mixing degree is an important index for studying the functional structure of the plot. Its essence is the concept of "entropy" in the field of thermodynamics, which is used to reflect the overall confusion degree of a system. This method mainly considers a POI data-based expression method of the functional mixing degree of the urban area. Based on the calculation method of the functional mixing degree in the related research, the calculation formula of the functional mixing degree update amount LM is as follows:

[0084]

[0085]

[0086] LM = LM1-LM0

[0087] In the formula, F u is the proportion of the number of u-type functional POIs in the study area, k represents the total number of u types n u is the number of u-type functional POIs in the study area; N represents the total amount of POI data in the study area; LM a is the functional mixing degree of the land use in the station study range. When a = 1, it represents the functional mixing degree of the land use after the update. When a = 0, it represents the functional mixing degree of the land use before the update, and LM is the functional mixing degree update amount.

[0088] The correlation analysis is performed on the site update intensity definition indexes to obtain an analysis result, different analysis groups are generated according to the analysis result, and track transportation site intensity characteristic research elements are obtained according to the analysis groups, wherein the track transportation site intensity characteristic research elements correspond to the site update intensity definition indexes.

[0089] The correlation analysis is performed on the site update intensity definition indexes to obtain an analysis result, different analysis groups are generated according to the analysis result, and track transportation site intensity characteristic research elements are obtained according to the analysis groups, wherein the track transportation site intensity characteristic research elements correspond to the site update intensity definition indexes.

[0090] In the field of statistics, the correlation coefficient refers to a quantity that exists between two variables and has a linear relationship with the quantity and is independent of the structural properties of the two variables. Pearson correlation coefficient (PPMCC) is usually used to evaluate the degree of correlation between variables X and Y, and the value range is between -1 and 1. Therefore, for the same sample, when different values of an index appear, the corresponding correlation coefficient will also change accordingly. According to the general judgment standard, the correlation coefficient between 0.0 and 0.2 is extremely weakly correlated or not correlated, the correlation coefficient between 0.2 and 0.4 is weakly correlated, the correlation coefficient between 0.4 and 0.7 is moderately correlated, and the correlation coefficient between 0.7 and 1.0 is strongly correlated.

[0091] The correlation analysis result of the site update intensity indexes is shown in Table 1.

[0092]

[0093] Table 1

[0094] Q represents the relative update amount of the building, S represents the absolute update amount of the building, V represents the volume rate update amount, R represents the building density update amount, D represents the functional density update amount, and LM represents the functional mixing degree update amount; ** represents strong correlation, and * represents relatively strong correlation.

[0095] Among them, the correlation indexes of Q-S-V three indexes are all greater than 0.7, S represents the absolute update amount of the building in the station area, Q is the relative update amount, and the comprehensive analysis of the two can more comprehensively reflect the volatility of the site update intensity; R-Q-V-D four indexes show the characteristics of strong correlation between each other, and this group of indexes is more directed to the land use related characteristics, and the land use intensity research element is used to comprehensively summarize in the method; the correlation indexes of LM-D-S are all greater than 0.4, and D and LM are directly related to the distribution characteristics of the station area functional industry, so they are summarized as the functional diversity research element.

[0096] The relative building update amount Q, the absolute building update amount S, and the volume rate update amount V have a strong correlation, and the comprehensive evaluation group points to the update volatility of the station site. Among them, since the calculation of the volume rate index is directly related to the building area and the plot area, Q and V have a clear linear positive correlation, so the correlation between S and Q and V is similar. The absolute building update amount represents the total building area of the plot in the update process within the station area, and its value reflects the update activity level of the overall station area. At the same time, the relative building update amount and the volume rate update amount objectively reflect the comparison results before and after the update of the station area, so the comprehensive analysis of the Q-S-V index group can obtain the differentiated characteristics of the update volatility dimension of the rail transit station site.

[0097] According to the correlation coefficient, the building density update amount R, the relative building update amount Q, the volume rate update amount V, and the functional density update amount D can form a new analysis group. As described above, Q and V show a clear positive correlation, but comprehensive analysis with other data can obtain different characteristics at different levels. The building density update amount R has a similar correlation function relationship with Q and S, and the correlation coefficients are 0.69 and 0.82, respectively. The correlation coefficient between the functional density update amount D and Q is 0.82, which also proves that building update will drive the update of functional industry. Q, V, and R can directly reflect the land use in the station area, so the comprehensive analysis of the R-Q-V-D index group points to the differentiated characteristics of the land use intensity dimension in the update process.

[0098] Among the three indexes of functional mix degree update amount LM, functional density update amount D, and absolute building update amount S, D and S have a strong positive correlation, so the correlation between LM and D and S is similar, and the correlation coefficients are-0.491 and-0.482, respectively. The correlation is moderate, and it can also be seen from the following figure that LM has a negative correlation with the other two indexes, and the linear relationship is not very obvious. Since the functional industry aggregation effect is very obvious in the update process of the area around the rail transit station, with the increase of the S value, the functional industry density of functions such as business / offices that adapt to high-value land increases, and some scattered functions such as community services are integrated and replaced, resulting in a decrease in functional mix degree. Therefore, the group formed by LM, D, and S is used to comprehensively reflect the differentiated characteristics of the functional diversity dimension of the station site.

[0099] Receiving sample sites, taking the station update intensity defining indexes corresponding to different rail transit station intensity characteristic research elements as input variables, and performing cluster analysis to obtain a definition result.

[0100] In another aspect, as Figure 7 shown, the embodiment of the present application discloses a multi-parameter-based collaborative rail transit station area space update intensity defining system, which comprises:

[0101] Range defining module: configured to receive an initial sample area, and to define a range of the initial sample area to obtain a land block within a station area, wherein the initial sample area is divided by a partial range of a rail transit station periphery;

[0102] Land block dividing module: configured to divide the land block within the station area to obtain land blocks of different update types, and to calculate a station update intensity definition index by using the land blocks of different update types;

[0103] Correlation analysis module: configured to perform correlation analysis on the station update intensity definition index to obtain an analysis result, to generate different analysis groups according to the analysis result, and to obtain a rail transit station intensity characteristic research element according to the analysis groups, wherein the rail transit station intensity characteristic research element corresponds to the station update intensity definition index;

[0104] Definition analysis module: configured to receive a sample station, to take the station update intensity definition index corresponding to different rail transit station intensity characteristic research elements as an input variable, and to perform cluster analysis to obtain a definition result.

[0105] Embodiment 1: Taking 12 stations of a first phase project of a subway x line in a city as an example, including a station 1, a station 2, a station 3, a station 4, a station 5, a station 6, a station 7, a station 8, a station 9, a station 10, a station 11, and a station 12, the involved stations include types comprehensively, including residential type, commercial type, historical block type, and scenic area type from the functional perspective, including old city type, city center type, and suburb type from the urban location perspective, including general type, transfer type, and transportation hub type, and the types are divided according to the update intensity.

[0106] (1) Determine the station area research range

[0107] Taking each entrance of the stations along the subway x line in the city as a starting point and the superposition of the 10-minute walkable range as the research range. According to the present road network and the entrances of the rail transit stations, the road network dataset is established by using Arcgis. The walking speed of a person is usually 80-100 m / min. The walkable range of a person within ten minutes is calculated at 80 m / min (see the attached Figure 8 ).

[0108] (2) Station area information statistics and calculation

[0109] The land use type distribution maps of the sample stations along the subway x line in the city in 2005 and 2020 are obtained by using high-resolution remote sensing images. The processed images are inserted into the ArcGIS software as a base map. The boundary lines of different land block update types around the sample stations of the subway x line in the city are plotted by comparison.

[0110] After obtaining the network open source POI data information, it needs to be preprocessed, involving data cleaning and reclassification. Data cleaning mainly includes deleting the same name, the same coordinate repeated data points and other operations in the original data; data reclassification will reclassify the original OSM map POI data, such as deleting or merging the data of place name address information, road auxiliary facilities and other data not needed temporarily, finally obtaining the POI data classification required for analysis, which are office, catering, hotel, shopping, government, transportation, education and culture, finance, sports and leisure and residence. ArcGIS counts the number of POIs in the station area, which is the data basis for calculating relevant indicators.

[0111] (3) Station evaluation index statistics

[0112] After calculating the 6 indicators of 12 sample stations according to the formula of each evaluation index by using SPSS, the statistics are sorted out.

[0113]

[0114] Q represents the relative update amount of buildings, S represents the absolute update amount of buildings, V represents the volume rate update amount, R represents the building density update amount, D represents the functional density update amount, and LM represents the functional mixing degree update amount.

[0115] (4) Index correlation analysis

[0116] This paper uses the correlation analysis in SPSS, adopts Pearson correlation coefficient test, and inputs 7 indicators as analysis variables to obtain the results.

[0117]

[0118] Q represents the relative update amount of buildings, S represents the absolute update amount of buildings, V represents the volume rate update amount, R represents the building density update amount, D represents the functional density update amount, and LM represents the functional mixing degree update amount.

[0119] (5) Evaluation index correlation result derivation research elements

[0120] The correlation analysis results show that there are different correlations and strengths between the indicators, therefore, each evaluation indicator forms different analysis groups according to the correlation analysis results, and points to the differentiated track transit station strength characteristic research elements. Among them, the correlation index of Q-S-V three indicators is greater than 0.7, S represents the absolute amount of building renewal in the station area, Q is the relative amount of renewal, and the comprehensive analysis of the two can more comprehensively reflect the volatility of station renewal strength; R-Q-V-D four indicators show the characteristics of strong correlation with each other, this group of indicators is more directed to the land use related characteristics, this paper uses the land use intensity research elements to summarize; The correlation index of LM-D-S is greater than 0.4, and D is directly related to the functional distribution characteristics of the station area, so it is summarized as the functional diversity research element (see the following table) Figure 2 ).

[0121] (6) Station clustering under different renewal intensity elements

[0122] The categories of track transit stations divided from different perspectives have different station area renewal intensities. In order to explore the intensity differentiation characteristics of different research element dimensions, this paper conducts clustering analysis based on the index data of 12 sample stations of a certain city subway x line. Due to the large difference in index values, standardization needs to be performed first, and then the standardized results of the evaluation indicators related to different research elements are used as input variables, and clustering analysis is performed in SPSS.

[0123]

[0124] Q represents the relative amount of building renewal, S represents the absolute amount of building renewal, V represents the volume rate renewal amount, R represents the building density renewal amount, D represents the functional density renewal amount, and LM represents the functional mix renewal amount.

[0125] 1) Renewal volatility intensity

[0126] The renewal volatility of track transit stations is mainly used to analyze the overall renewal intensity differentiation characteristics between different types of stations at the macro level, including three evaluation indicators of building relative renewal amount Q, building absolute renewal amount S, and volume rate renewal amount V.

[0127]

[0128] 2) Land use intensity

[0129] The land use intensity research element mainly focuses on the differentiation characteristics of land use renewal intensity between plots in the track transit station area. The standardized results of the sample station related indicators building density renewal amount R, building relative renewal amount Q, volume rate renewal amount V, and functional density renewal amount D are used as variable inputs for clustering analysis in SPSS, and the results are shown in the following chart.

[0130]

[0131] 3) Functional diversity intensity

[0132] Functional diversity research elements are used to analyze the functional mixing degree of the surrounding area of the rail transit station and the differentiation characteristics of the updating intensity of the aggregation degree, and the standardized results of the sample station related indexes functional mixing degree updating amount LM, functional density updating amount D and building absolute updating amount S are taken as variables for cluster analysis, and the results are shown in the following chart.

[0133]

[0134]

[0135] Based on the same inventive concept, the application further provides a computer device, which comprises one or more processors and a memory for storing one or more computer programs; the program comprises program instructions, and the processor is configured to execute the program instructions stored in the memory. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions, and is specifically used to load and execute one or more instructions in the computer storage medium to realize the above-mentioned method.

[0136] It should be further noted that based on the same inventive concept, the present application further provides a computer storage medium, which stores a computer program, and the computer program is run by a processor to execute the above method. The storage medium can adopt any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device or apparatus, or any combination thereof. More specific examples (non-exhaustive list) of the computer readable storage medium include: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus.

[0137] In the description of the present application, the description of the terms "one embodiment", "an example", "a specific example" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0138] The basic principles, main features and advantages of the present disclosure are shown and described above. It should be understood by those skilled in the art that the present disclosure is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present disclosure. Without departing from the spirit and scope of the present disclosure, various changes and improvements can be made to the present disclosure, and these changes and improvements all fall within the scope of the claimed present disclosure.

Claims

1. A method for defining the intensity of space updates for a coordinated rail transit station area based on multiple parameters, characterized in that, The method comprises the following steps: Receiving an initial sample area, and performing range definition on the initial sample area to obtain a station area block, wherein the initial sample area is divided by a partial range around a rail transit station; Dividing the station area block to obtain blocks of different update types, and calculating a station update intensity definition index by using the blocks of different update types; Performing correlation analysis on the station update intensity definition index to obtain an analysis result, and generating different analysis groups according to the analysis result, and obtaining a rail transit station intensity characteristic research element according to the analysis groups, wherein the rail transit station intensity characteristic research element corresponds to the station update intensity definition index; Receiving a sample station, taking the station update intensity definition index corresponding to different rail transit station intensity characteristic research elements as an input variable, and performing cluster analysis to obtain a definition result.

2. The multi-parameter based coordinated rail station area space update intensity definition method according to claim 1, wherein, The station area block is divided into a reduced update block, an un-updated block, a stock update block and an incremental update block.

3. The multi-parameter based coordinated rail station area space update intensity definition method according to claim 2, characterized in that, The reduced update block refers to a block that originally accommodates building functions and undertakes urban functions and is currently in a state of demolition and construction, or is updated to a public space such as green space or square; the un-updated block refers to a block whose buildings and land use remain unchanged, and only the appearance of part of the buildings, the space quality and the urban environment are improved; The stock update block refers to a block where buildings are replaced due to functional needs or urban space planning adjustments, resulting in an increase, decrease or maintenance of the overall development amount; the incremental update block refers to a block that was initially planned for development or was not planned for development, and has developed buildings after a few years.

4. The multi-parameter based coordinated rail station area space update intensity definition method of claim 1, wherein, The station update intensity definition index includes relative building update amount Q, absolute building update amount S, plot ratio update amount V, building density update amount R, functional density update amount D and functional mix degree update amount LM.

5. The multi-parameter based coordinated rail station area space update intensity definition method according to claim 4, wherein, The calculation formula of the relative building update amount Q is as follows: Q = A1 - A0 In the formula, A1 is the total building area after update, A0 is the total building area before update, and Q is the relative building update amount; The calculation formula of the absolute building update amount S is as follows: S = |Qi| ∑S = ∑|Qi| In the formula, Qi is the relative building update amount of different update block types, i = 1, 2, 3, 4, 1, 2, 3, 4 respectively represent reduced update block, un-updated block, stock update block and incremental update block, and S is the absolute building update amount; The calculation formula of the plot ratio update amount V is as follows: In the formula, Q is the relative building update amount, SM is the total land area, and V is the plot ratio update amount.

6. The multi-parameter based coordinated rail station area space update intensity definition method of claim 4, wherein, The calculation formula of the building density update amount R is as follows: In the formula, B1 is the total building site area after update, B0 is the total building site area before update, SM is the total land area, and R is the building density update amount; The calculation formula of the functional density update amount D is as follows: In the formula, P1 is the number of POIs in the station area range after update, P0 is the number of POIs in the station area range before update, SM is the total land area, and D is the functional density update amount; The calculation formula of the functional mix degree update amount LM is as follows: LM = LM1 - LM0 In the formula, F u k represents the total number of u types n u The number of u type functional POIs in the study area; N represents the total amount of POI data in the study area; LM a The land use function mixing degree in the station area research range, when a = 1, it represents the updated land use function mixing degree, when a = 0, it represents the land use function mixing degree before updating, and LM function mixing degree update amount.

7. The method for defining the spatial update intensity of a coordinated rail transit station domain based on multiple parameters according to claim 1 is characterized in that: The process of performing correlation analysis on the site update intensity definition indexes adopts correlation analysis in SPSS, adopts Pearson correlation coefficient test, inputs the 6 site update intensity definition indexes as analysis variables, and obtains the correlation strength between different site update intensity definition indexes through correlation analysis, and obtains an analysis result.

8. The multi-parameter based coordinated rail station domain space update intensity definition method of claim 1, wherein, The rail transit site intensity characteristic research elements include development volatility, land use intensity, and functional diversity.

9. A multi-parameter based coordinated rail transit station area space update intensity definition system, characterized in that, The method comprises the following steps: a range defining module, configured to receive an initial sample area, perform range defining on the initial sample area, and obtain a land block in a station area, wherein the initial sample area is divided by a partial range around a rail transit site; a land block dividing module, configured to divide the land block in the station area, obtain land blocks of different update types, and calculate site update intensity definition indexes by using the land blocks of different update types; a correlation analysis module, configured to perform correlation analysis on the site update intensity definition indexes, obtain an analysis result, generate different analysis groups according to the analysis result, and obtain rail transit site intensity characteristic research elements according to the analysis groups, wherein the rail transit site intensity characteristic research elements correspond to the site update intensity definition indexes; a definition analysis module, configured to receive a sample site, take site update intensity definition indexes corresponding to different rail transit site intensity characteristic research elements as input variables according to the sample site, and perform cluster analysis to obtain a definition result.

10. An apparatus, comprising: The method comprises the following steps: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the multi-parameter-based collaborative rail transit station area spatial update intensity definition method according to any one of claims 1-8.

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