CN111339492A - Regional city system evolution and space action quantification method and system - Google Patents

Regional city system evolution and space action quantification method and system Download PDF

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CN111339492A
CN111339492A CN202010131998.4A CN202010131998A CN111339492A CN 111339492 A CN111339492 A CN 111339492A CN 202010131998 A CN202010131998 A CN 202010131998A CN 111339492 A CN111339492 A CN 111339492A
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崔耀平
刘玄
周生辉
李东阳
邓晴心
邓晓晴
徐佳宁
石欣瑜
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Abstract

The invention relates to a method for quantifying system evolution and space action of a regional city, which comprises the following steps: step one, collecting relevant data of a city to be detected; step two, constructing a regional city system space-time evolution (CS); step three, expressing a model of the urban system (cs); step four, constructing a multivariable-space distance network (ND-M); constructing and expressing urban system components; and step six, determining the spatial correlation effect of the urban system. The invention innovatively integrates systematic and spatial thinking modes under a method system of urban system space-time evolution aiming at the problems of regional city development state, urban element evolution and growth, inter-city interaction mode and the like, and quantitatively expresses the existing connection mode and connection characteristics in the development process among regional cities by establishing a mathematical model.

Description

Regional city system evolution and space action quantification method and system
Technical Field
The invention belongs to the technical field of urban planning, and particularly relates to a method and a system for quantifying system evolution and space action of a regional city.
Background
The basic idea of the system theory is to consider the object of study and processing as a whole system. The systematic theory is to study the structure, characteristics, behaviors, dynamics, principles, laws and relations between systems and to mathematically summarize the relations. The main task of the system theory is to take the system as an object and study the interrelationship of the whole system and the elements forming the whole system from the whole.
The system evolution refers to the process of evolution and development of the system under the interaction of each component element. The system evolution has both the characteristics of orderliness and orderless, and the orderliness and the orderless are mutually and alternately transformed. The system has directivity in the development trend in the ordered state and irreversible process. The development and evolution of the system are restricted by the leading elements, so the order of the evolution of the leading elements determines the trend of the system evolution to a certain extent.
Spatial interaction refers to the characteristic that certain elements have potential interdependence between observed data within the same region. The local similarity and openness of geographic spaces enable a certain correlation characteristic to exist between geographic elements, the strength of the characteristic is directly related to the distance of spatial positions, and generally, the interaction effect is larger when the spatial positions are closer, and the interaction effect is smaller when the spatial positions are farther.
At present, the urban scale expansion in China mainly adopts the expanding incremental development, which can cause the problems of contradiction between population and resource environment, tension of construction land, aggravation of social differentiation and the like. Therefore, urbanization development should not be expanded blindly, but should be specifically analyzed for actual development trends, which leads to incremental, inventory and decrement planning. The incremental planning is mainly planning based on space expansion with respect to a newly added construction site. The incremental planning is mainly characterized in that positive prediction and expandable development arrangement are carried out on cities in a rapid development stage. The stock planning is planning for promoting the function optimization and adjustment of the built-up area by means of city updating and the like. The method is an effective response to the change of city growth factors, and the stock planning is a reflection and improvement on the increment planning essentially. The decrement planning means that a part of construction land is removed to restore ecology or a part of land is reduced to increase the area of another part of land. The method is an important planning selection for coping with local economic decline and population scale reduction, and is a plan for realizing regional resource integration and resource intensive utilization.
Disclosure of Invention
The invention provides a method and a system for quantifying system evolution and space action of a regional city, aiming at solving the problem of unbalanced urbanization development in the prior art.
The invention relates to a method for quantifying system evolution and space action of a regional city, which comprises the following steps:
step one, collecting relevant data of a city to be detected;
step two, constructing a regional city system space-time evolution (CS);
step three, expressing a model of the urban system (cs);
step four, constructing a multivariable-space distance network (ND-M);
constructing and expressing urban system components;
and step six, determining the spatial correlation effect of the urban system.
Further, in the step one, the related data includes corresponding city development data of all cities in the area within a specified time, and is classified into the following three types: urban economic data (E), urban population data (P) and urban land space data (L).
Further, in the second step, the first step,
Figure BDA0002396027000000021
in the formula, the CS is an evolution matrix of a regional city space-time system.
Further, in the third step, the first step,
Figure BDA0002396027000000022
in the formula, csitRepresenting any one of the urban systems, X, within the areajRepresenting an element, or so-called component, lambda, contained in the urban systemiAnd selecting representative economy (E), population (P) and city space (L) for the component indexes as weight coefficients.
Further, in the fourth step,
Figure BDA0002396027000000023
where the multivariate-spatial distance network (ND-M) may contain any distance, z represents a set of distance types that need to be measured, which may be euclidean, mahalanobis, transit, or temporal; theta12Representation cs1And cs2The distance of (c).
Further, in step five, the urban system component evolution set expresses:
Figure BDA0002396027000000024
in the formula, cs _ x represents the collective expression of system components of the urban system i on a time sequence t, and x is a general form of specific components, wherein the general form comprises an urban economic development scale e, an urban population scale p and an urban built-up area space scale l;
further, in step five, the scale growth of the system components is expressed:
Figure BDA0002396027000000031
in the formulaCs _ rx represents the acceleration of the urban system component i, Ei,t、Pi,t、Li,tShowing the scale growth state of e, p and l of the city i at the time t;
constructing a city evaluation index (US) based on city system components:
Figure BDA0002396027000000032
equation (6) can be abbreviated as follows:
US＝W*cs_rx (7)
wherein W represents a weight matrix of the corresponding system component size increase, and the weight matrix is composed of a set of weight coefficients α on the diagonalnAnd (4) forming.
Further, in step five, the relative development index S between regional cities:
expanding the city scale structure evaluation index (US-PLE) based on spatial interaction, and calculating the development index S of a certain city relative to other cities in the region:
Figure BDA0002396027000000033
in the formula: US*For studying normalized values of urban Scale Structure indices of cities, USi *Is the normalized value of the city scale structure index of the i city, ND-Mij *The normalized weighted distance between the city i and the city j is obtained;
if S > is approximately equal to 0, the scale development rate of the city in the area is greater than that of the surrounding cities, the economy of the area is increased at a high speed, the city has strong expansibility, the urbanization process is in a rapid promotion stage and has greater development potential, and an incremental planning scheme is adopted; if S is approximately equal to 0, the scale development rate of the city in the area is smaller than that of the surrounding cities, the economy of the area continuously increases, the adjustment of the internal structure of the city is intensified, but the expansion trend is obviously limited, and the city enters a new stage of development and transformation and should adopt an inventory planning scheme; if S < ≈ 0, the economic growth of the city in the area is slow, the population scale is reduced, the urban land utilization efficiency is low, and the development trend of the town needs to be changed through decrement planning.
Further, in the sixth step,
Figure BDA0002396027000000034
in the formula, when Δ csit.Δcsjt<Time 0 UCIij,t<0 shows that the space interaction states of the two cities in the t time are growth and inhibition type, delta csit.Δcsjt>Time 0 UCIij,t>0 indicates that the states of the two cities in the time t are mutually promoted; simultaneously introducing an exponential form of a spatial distance network in UCIij,tThe reliability and accuracy of the spatial effect in the forward interval of the values increase at the same distance and decay, in UCIij,tThe reliability and the accuracy of the spatial effect on the negative interval of the numerical value are enhanced by increasing the same distance;
Δcsit＝Δpit.Δeit(10)
in the formula, when Δ p>0、Δe>At 0,. DELTA.csit>0; when Δ p>0、Δe<0 or Δ p<0、Δe>At 0,. DELTA.csit<0; since urban systems are in the decay phase when population and economic development are in the decrement phase, it is specified in particular when Δ p<0、Δe<At 0,. DELTA.csit<0；
Re-use UCIij,tThe method is incorporated into a spatial network to obtain a spatial matrix form:
Figure BDA0002396027000000041
in the formula, UCItThe matrix is a time evolution form of the spatial correlation effect of the urban system, and changes along with the change of time.
The invention also relates to a system for quantifying the evolution and space action of the regional city system, which comprises a data acquisition device, an evaluation database and an analysis platform, wherein the collected data are transmitted to the evaluation database for data storage, and finally, a quantitative result of the evolution and space action of the regional city system is obtained.
The invention relates to a method for urban system space-time evolution, which integrates systematic and spatial analysis visual angles into problems of regional urban development, urban scale expansion and the like under the method framework of urban system space-time evolution, quantitatively expresses the contact modes and contact characteristics existing in the development process among regional cities, provides specific planning types for urban scale expansion by means of relative development indexes, and guides the modes which the urban planning should adopt by using a more practical theory.
According to the method, a systematic and spatial thinking mode is innovatively integrated under a method system of city system space-time evolution aiming at the problems of regional city development state, city element evolution and growth, city mutual influence mode and the like, and a contact mode and contact characteristics existing in the development process of regional cities are quantitatively expressed by establishing a mathematical model, so that the stage influence characteristics of regional center cities on the development of other cities can be reflected; meanwhile, theoretical basis and specific planning type guidance are provided for city scale expansion and planning response by means of the city scale evaluation index and the relative development index. The method is a novel, simple and feasible technical method which can be directly used for urban planning research.
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FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a diagram illustrating urban spatial correlation effect in Zhejiang province according to an embodiment of the present invention;
FIG. 3 is a diagram of city system status, city scale evaluation index and city relative development index in Zhejiang province.
Detailed Description
The invention relates to a quantitative method for regional city system evolution and space action, which takes a city body as a system whole and is simultaneously integrated into a regional space view, and measures the development state of a city system, the development evolution of city system components and the spatial correlation effect of the city system at the level of the generalization and openness of a geographic space. The method comprises the steps of firstly, comprehensively representing the current development state of the urban system by virtue of quantifiable elements in the urban system. And calculating the evolution state of the city elements according to the component development trend of the city system, wherein the evolution state comprises the time gradient characteristics of the elements, and constructing a city scale evaluation index on the basis to further refine the state characteristics of city development and growth. Meanwhile, a spatial interaction principle is introduced, a multivariate spatial distance network is constructed to quantitatively express the spatial correlation effect in the urban system evolution process, and the multivariate spatial distance network comprises three types, namely a mutual promotion type, a growth inhibition type and a steady-state independence type. The method is characterized in that under the framework of the urban system space-time evolution, the method is composed of three parts, namely urban system state measurement, urban system component evolution and urban system space association effect, the three parts are mutually influenced and restricted, and an organic whole-regional urban system evolution is jointly constructed, as shown in figure 1. The method specifically comprises the following steps:
step one, collecting relevant data of a city to be detected: the collected data comprises corresponding city development data of all cities in the region within a specified time, and the specific data is divided into the following three types: urban economic data (E), urban population data (P), urban land space data (L), and linear distances and traffic distances between urban residences.
Step two, constructing a regional city system space-time evolution (CS);
Figure BDA0002396027000000051
step three, expressing a model of the urban system (cs), and specifically comprising the following calculation method:
Figure BDA0002396027000000052
in the formula, CS is a space-time evolution matrix of a regional city system; cs isitRepresents the state of i city system in the area at time t, XijRepresenting a matrix of elements (also called components) included in the urban system, λiAre weight coefficients.
(1) Selection of urban system component indexes
And measuring the development state of the urban system, namely observing the comprehensive development state of the urban system at the moment t. Whereas the state characteristics of urban systems are the result of a set of systematic components acting together. In order to facilitate realization and keep rationality, three representative urban system components are selected: the city economy (E), the city population (P), and the city space (L) include a plurality of indices, and as shown in table 1, the following method is implemented by using the index data.
TABLE 1 index system for urban system status (cs) measurements
Figure BDA0002396027000000061
Since the index has dimension, it needs to be normalized.
Figure BDA0002396027000000062
In the formula, Xij *Representing normalized urban system component index, XijThe j component, X, representing the i cityjmaxRepresenting the maximum value in the j-type component.
(2) Weighting of urban system components
The weight of the city system variable is obtained by adopting an entropy value weighting objective weighting method. The method comprises the following processing steps: (2-1) constructing a normalized matrix Q of system components:
Figure BDA0002396027000000063
wherein Q isijThe index X representing the normalized urban system componentij *And forming a normalization matrix.
(2-2) calculating an entropy value H:
Figure BDA0002396027000000064
wherein HjExpressing the total contribution of all the components to the urban system, and K expresses the influence range of the system components on the whole systemAnd when K is 1/ln (n), then HjStrictly distributed between 0 and 1.
(2-3) calculating a differentiation coefficient D:
Dj＝1-Hj(2-4)
wherein D isjRepresenting the degree of consistency of the contribution of the urban system components to the system.
(2-4) calculating a weight coefficient λ:
Figure BDA0002396027000000071
wherein λ isjRepresenting the weight coefficient of the jth component.
(3) Measurement of urban system status
Figure BDA0002396027000000072
Step four, constructing a multivariable-space distance network (ND-M);
(1) general mathematical form of ND-M expansion:
Figure BDA0002396027000000073
where the multivariate-spatial distance network (ND-M) may contain arbitrary distances, and z represents a set of distance types to be measured, which may be Euclidean distances, Mahalanobis distances, transit distances, time distances, etc.; theta12Representation cs1And cs2The distance of (c). (2) And (3) carrying out standardization treatment on ND-M:
since two types of distance data are selected here, the straight-line distance d between the urban premiseslAnd a traffic distance dtAnd thus z is the set of these two distances.
Figure BDA0002396027000000074
ND-Mij *＝δ1dl *+δ2dt *(3-2)
In the formula (d)l *Representing normalized values of the linear distance between two cities, dt *Representing normalized values of the time distance between two cities, thetamaxAnd thetaminRepresenting the maximum and minimum values of the corresponding distance type. Delta1、δ2For weighting, certain values can be assigned according to the specific situation, for example: when the railways and the highways between two places are developed and the traffic is convenient, delta can be increased2The value is to increase the weight of the time distance, conversely if there is poor traffic between the two places, δ should be increased1To increase the weight of the straight-line distance. ND-Mij *Representing the normalized distance between city i and city j.
Step five, construction and expression of urban system components:
the city system cs is composed of a set of quantifiable city information components in the system, and satisfies cs ═ f (e, p, l, …) where e, p, l respectively represent the scale of city economic development, the scale of city population, and the scale of city built-up area space, and the city system also contains other quantifiable information. The component change of the urban system can directly influence the urban system, and the observation and calculation of the component change trend are helpful for grasping the potential development trend of the urban system state, so that the construction of the predictive expression of the system component under the spatial and temporal evolution of the urban system has important significance.
(1) Urban system component evolution set expression:
Figure BDA0002396027000000081
in the formula, cs _ x represents the collective expression of system components of the i city system on a time series t, and x is a generalized form for a specific component. The method comprises the following steps of urban economic development scale e, urban population scale p and urban built-up area space scale l.
(2) Scale-up expression of systemic components:
Figure BDA0002396027000000082
in the formula, cs _ rx represents the acceleration of the city system component i, Ei,t、Pi,t、Li,tShowing the scale growth state of e, p and l of i city at time t. The growing state of the urban system components provides an important reference for element planning of regional urban development, and the spatial growing difference of the urban system components (elements) is a concern for regional development. In order to optimize the urban system as much as possible, the change of system components in space needs to be observed and guided according to the development trend, so that the urban system in the area is well developed.
(3) Regional city scale evaluation index (US):
Figure BDA0002396027000000083
selecting three main indexes of urban economic development scale, urban population scale and urban built-up area space scale to expand the formula (6) as follows:
US＝α1Ei+α2Pi+α3Li(6-1)
wherein US is city scale structure index α1PiFunction value of membership degree of i city relative to population scale index P α2LiA membership function value of i city relative to the city land scale index L α3EiAnd the membership function value of the i city relative to the economic development index E of the city.
(3-1) calculating the urban economic development speed:
because the influence factors of the urban industry are complex, the method uses the least square method to find out a linear equation, calculates the value b, and takes the product of the value b and the acceptance coefficient K influencing the urban economic connection as EiI.e. by
Ei＝bK (6-2)
Figure BDA0002396027000000091
Figure BDA0002396027000000092
emIs the production value of the m-th economic sector or element of one city and the relevant part of another city, EmIs the value of the m economic departments or elements of a city.
(3-2) calculation of population size exponential development speed:
Piexpressed by using Logistic equation:
Figure BDA0002396027000000093
wherein P is the number of regional population, P0The number of population in the population area at the beginning is represented, r represents the maximum relative growth speed of the area which can be pushed by the limiting factor in the area population growth condition, and K represents the highest population number of the area which can be pushed by the limiting factor in the area population growth condition, namely maxP (K).
(3-3) calculating the urban land scale index development speed:
Lirepresented by a city Expansion Speed (ES) formula:
Figure BDA0002396027000000094
wherein: ES is the urban annual average expansion rate, LaTo study the area of the initial urban built-up area, LbIn order to study the area of the built-up area of the city at the end stage, n is the study period and is in units of years.
(3-4) preprocessing the urban scale structure evaluation index data:
similarly, to ensure the reasonableness of the ratio, US and US are usediNormalization was also performed:
Figure BDA0002396027000000095
(3-5) calculating the relative development index S among regional cities:
based on the influence of the spatial interaction on city development, the city scale structure evaluation index (US-PLE) is spatially expanded, and the development index S of a certain city relative to other cities in the area is calculated.
Figure BDA0002396027000000096
Wherein: US*For studying normalized values of urban Scale Structure indices of cities, USi *Is the normalized value of the city scale structure index of the i city, ND-Mij *Is the weight distance of the normalized city i and the normalized city j.
(3-6) judging whether S is positive or negative:
if S > is approximately equal to 0, the scale development rate of the city in the area is greater than that of the surrounding cities, the economy of the area is increased at a high speed, the city has strong expandability, the urbanization process is in a rapid promotion stage and has greater development potential, and an incremental planning scheme is adopted.
If S is approximately equal to 0, the scale development rate of the city in the area is smaller than that of the surrounding cities, the economy of the area continuously increases, the adjustment of the internal structure of the city is intensified, but the expansion trend is obviously limited, and the city enters a new stage of development and transformation and should adopt an inventory planning scheme.
If S < ≈ 0, the economic growth of the city in the area is slow, the population scale is reduced, the urban land utilization efficiency is low, and the development trend of the town needs to be changed through decrement planning.
(3-7) allocation according to the planned area of the government:
the theoretical urban planning area condition should be determined in f), but because most of the current cities in China belong to the middle stage of urbanization, the urbanization level is rapidly improved, the number of the cities is rapidly increased, the urban scale is continuously enlarged, the requirement of expanding the area caused by continuous urbanization of rural population can also appear in a single city, and the urban planning in China should be mainly incremental based on the national conditions.
If S >0, the total Area of the Area is planned to be Area, and the Area rapidly expands to the outside. If S ≈ 0, it appears as an outward creep. If S < <0, the area of the region should remain substantially unchanged.
The area ratio to be expanded or reduced and the specific values of each county and city are:
Figure BDA0002396027000000101
F＝B*Area (6-10)
wherein B is the percentage of the normalized numerical value of the prefecture S/the sum of the normalized numerical values of the prefectures,
Figure BDA0002396027000000104
the normalized S value of the city is i, n is the total number of cities in the Area, F is the Area planned and expanded in the future of a certain city, and Area is the total amount planned and expanded by the government in the Area.
Step six, determining the spatial correlation effect of the urban system
(1) General form of spatial correlation effect calculation:
Figure BDA0002396027000000102
in the formula, when Δ csit.Δcsjt<Time 0 UCIij,t<0 shows that the correlation states of the two cities in the time t are an increase and inhibition type, delta csit.Δcsjt>Time 0 UCIij,t>0 indicates that the states of the two cities in the time t are mutually promoted; simultaneously introducing an exponential form of a spatial distance network (ND-M) in UCIij,tThe reliability and accuracy of the spatial effect in the forward interval of the values increase at the same distance and decay, in UCIij,tThe reliability and accuracy of the spatial effect on the negative interval of the numerical value are enhanced by increasing the same distance.
(1-1)ND-MijThe calculation of (2):
Figure BDA0002396027000000103
(2) urban system delta (Δ cs)it) The calculating method of (2):
Δcsit＝Δpit.Δeit(7-2)
in the formula, when Δ p>0、Δe>At 0,. DELTA.csit>0; when Δ p>0、Δe<0 or Δ p<0、Δe>At 0,. DELTA.csit<0; since urban systems are in the decay phase when population and economic development are in the decrement phase, it is specified in particular when Δ p<0、Δe<At 0,. DELTA.csit<0。
(2-1)ΔpitThe calculation of (2):
selecting the increment (delta p) of the current year's permanent population of the regional cityres) And household population increment (delta p)reg) The standardized treatment is performed to stabilize The population (The population of people) and The household population (The registered population):
Δpit＝res*-reg*(7-3)
Figure BDA0002396027000000111
Figure BDA0002396027000000112
in the formula res*Normalized form, reg, representing the population increment of a standing population*A standardized form representing the population increment of a standing population.
(2-2)ΔeitThe calculation of (2):
selecting the increment (delta e) of GDP of the current year of the regional citygdp) And sum-normalized for it:
Δeit＝gdp*(7-6)
Figure BDA0002396027000000113
in the formula, gdp*A sum normalized form representing the economic increment of a city.
To resumeTo UCIij,tThe method is incorporated into a spatial network to obtain a spatial matrix form:
Figure BDA0002396027000000114
in the formula, UCItThe matrix is a time evolution form of the spatial correlation effect of the urban system, and changes along with the change of time. Where the values on the diagonal are meaningless and thus are represented by 0; UCItThe matrix helps to illustrate the spatially developed connection and influence role between any two cities in the urbanization process.
Examples
In this embodiment, the detection of the spatial correlation effect (UCI) in the city of the region is performed in zhejiang province (2010-2015).
As shown in fig. 2, when UCI >0, it indicates that the development among regional cities is in a mutually promoting stage (the dotted lines with different thickness represent the positive promoting effect, and the thickness represents the strong and weak characteristics of the effect on the space); UCI <0 indicates that regional intercity development is in the growth and inhibition stages (grey line segments express this effect).
During the period from 2010 to 2015, the Wenzhou city is in a descending stage of development, and a significant relative development glide condition appears compared with other cities in the region, so that the Wenzhou city enters a suppression end of a growth and suppression stage; in addition, the thoroughfare, the lishu and the taizhou are in the growing and restraining states. Other cities in the region are in a positive mutual promotion pattern, wherein the Hangzhou, Ningbo and Shaoxing form a UCI strong triangular pattern on the space, namely a strong correlation development situation in the region; meanwhile, Hangzhou city has strong co-directional development driving effect on peripheral cities such as Huzhou, Jiaxing, Shaoxing and Jinhua. FIG. 3 is a diagram of city system status, city scale evaluation index and city relative development index in Zhejiang province. Table 2 shows the city system status measurement results (cs) in 2010-2015 of zhejiang province.
TABLE 2
Figure BDA0002396027000000121
The above-mentioned embodiments are only preferred embodiments of the present invention, and are not intended to limit the embodiments of the present invention, and those skilled in the art can easily make various changes and modifications according to the main concept and spirit of the present invention, so the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. A quantitative method for regional city system evolution and space effect is characterized by comprising the following steps:
step one, collecting relevant data of a city to be detected;
step two, constructing a regional city system space-time evolution (CS);
step three, expressing a model of the urban system (cs);
step four, constructing a multivariable-space distance network (ND-M);
constructing and expressing urban system components;
and step six, determining the spatial correlation effect of the urban system.
2. The method for quantifying regional urban system evolution and spatial impact according to claim 1, wherein in step one, the related data comprises corresponding urban development data of all cities within a region within a specified time, and the data is classified into the following three categories: urban economic data (E), urban population data (P) and urban land space data (L).
3. The method for quantifying regional urban system evolution and spatial effects according to claim 1, wherein in step two,
Figure FDA0002396026990000011
in the formula, the CS is an evolution matrix of a regional city space-time system.
4. Regional urban system evolution and spatial working according to claim 1The quantization method used is characterized in that, in the third step,
Figure FDA0002396026990000012
in the formula, csitRepresenting any one of the urban systems, X, within the areajRepresenting an element, or so-called component, lambda, contained in the urban systemiAnd selecting representative economy (E), population (P) and city space (L) for the component indexes as weight coefficients.
5. The method for quantifying regional urban system evolution and spatial impact according to claim 1, wherein in step four,
Figure FDA0002396026990000013
where the multivariate-spatial distance network (ND-M) may contain any distance, z represents a set of distance types that need to be measured, which may be euclidean, mahalanobis, transit, or temporal; theta12Representation cs1And cs2The distance of (c).
6. The method for quantifying regional urban system evolution and spatial effects according to claim 1, wherein in step five, the urban system component evolution sets express:
Figure FDA0002396026990000021
in the formula, cs _ x represents the collective expression of system components of the urban system i on a time sequence t, and x is a general form of specific components, wherein the specific components comprise an urban economic development scale e, an urban population scale p and an urban built-up area space scale l.
7. The method for quantifying regional urban system evolution and spatial effects according to claim 6, wherein in step five, the scale growth of the system components is expressed as:
Figure FDA0002396026990000022
in the formula, cs _ rx represents the acceleration of the city system component i, Ei,t、Pi,t、Li,tShowing the scale growth state of e, p and l of the city i at the time t;
constructing a city evaluation index (US) based on city system components:
Figure FDA0002396026990000023
the formula (6) can be abbreviated as follows:
US＝W*cs_rx (7)
wherein W represents a weight matrix of the corresponding system component size increase, and the weight matrix is composed of a set of weight coefficients α on the diagonalnAnd (4) forming.
8. The method for quantifying systematic evolution and spatial effects of regional cities as claimed in claim 7, wherein in step five, the relative development index between regional cities is S:
expanding the city scale structure evaluation index (US-PLE) based on spatial interaction, and calculating the development index S of a certain city relative to other cities in the region:
Figure FDA0002396026990000024
in the formula: US*For studying normalized values of urban Scale Structure indices of cities, USi *Is the normalized value of the city scale structure index of the i city, ND-Mij *The normalized weighted distance between the city i and the city j is obtained;
if S > is approximately equal to 0, the scale development rate of the city in the area is greater than that of the surrounding cities, the economy of the area is increased at a high speed, the city has strong expansibility, the urbanization process is in a rapid promotion stage and has greater development potential, and an incremental planning scheme is adopted; if S is approximately equal to 0, the scale development rate of the city in the area is smaller than that of the surrounding cities, the economy of the area continuously increases, the adjustment of the internal structure of the city is intensified, but the expansion trend is obviously limited, and the city enters a new stage of development and transformation and should adopt an inventory planning scheme; if S < ≈ 0, the economic growth of the city in the area is slow, the population scale is reduced, the urban land utilization efficiency is low, and the development trend of the town needs to be changed through decrement planning.
9. The method for quantifying regional urban system evolution and spatial impact according to claim 1, wherein in step six,
Figure FDA0002396026990000031
in the formula, when Δ csit.Δcsjt<Time 0 UCIij,t<0 shows that the space interaction states of the two cities in the t time are growth and inhibition type, delta csit.Δcsjt>Time 0 UCIij,t>0 indicates that the states of the two cities in the time t are mutually promoted; simultaneously introducing an exponential form of a spatial distance network in UCIij,tThe reliability and accuracy of the spatial effect in the forward interval of the values increase at the same distance and decay, in UCIij,tThe reliability and the accuracy of the spatial effect on the negative interval of the numerical value are enhanced by increasing the same distance;
Δcsit＝Δpit.Δeit(10)
in the formula, when Δ p>0、Δe>At 0,. DELTA.csit>0; when Δ p>0、Δe<0 or Δ p<0、Δe>At 0,. DELTA.csit<0; since urban systems are in the decay phase when population and economic development are in the decrement phase, it is specified in particular when Δ p<0、Δe<At 0,. DELTA.csit<0；
Re-use UCIij,tThe method is incorporated into a spatial network to obtain a spatial matrix form:
Figure FDA0002396026990000032
in the formula, UCItThe matrix is a time evolution form of the spatial correlation effect of the urban system, and changes along with the change of time.
10. A quantitative system for regional city system evolution and space action is characterized by comprising a data acquisition device, an evaluation database and an analysis platform, wherein collected data are transmitted to the evaluation database for data storage, and finally, quantitative results of the regional city system evolution and space action are obtained.
CN202010131998.4A 2020-02-29 2020-02-29 Regional city system evolution and space action quantification method and system Pending CN111339492A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112199566A (en) * 2020-09-27 2021-01-08 成都房联云码科技有限公司 City update effect evaluation method and system based on real estate big data
CN113065806A (en) * 2021-04-30 2021-07-02 河南大学 Urbanization element flow distribution method based on neighborhood and grid
CN114091140A (en) * 2021-10-13 2022-02-25 上海大学 Network construction method of urban space density data

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112199566A (en) * 2020-09-27 2021-01-08 成都房联云码科技有限公司 City update effect evaluation method and system based on real estate big data
CN112199566B (en) * 2020-09-27 2021-07-30 成都房联云码科技有限公司 City update effect evaluation method and system based on real estate big data
CN113065806A (en) * 2021-04-30 2021-07-02 河南大学 Urbanization element flow distribution method based on neighborhood and grid
CN113065806B (en) * 2021-04-30 2022-10-28 河南大学 Urbanization element flow distribution method based on neighborhood and grid
CN114091140A (en) * 2021-10-13 2022-02-25 上海大学 Network construction method of urban space density data
CN114091140B (en) * 2021-10-13 2023-09-29 上海大学 Network construction method for urban space density data

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