CN115496301A - Land utilization and traffic collaborative evaluation method oriented to homeland space planning - Google Patents
Land utilization and traffic collaborative evaluation method oriented to homeland space planning Download PDFInfo
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Abstract
The invention provides a land utilization and traffic collaborative evaluation method facing to territorial space planning, which comprises S1 traffic cell division and index acquisition; s2, constructing a development level evaluation model; s3, classifying development level grades based on cluster analysis; s4, constructing a collaborative evaluation model; and S5, making a land utilization and urban traffic index optimization strategy. The method can be directly applied to evaluation and optimization of a territorial space planning scheme, and the matching degree of the land utilization development level of the traffic community and the supply level of the urban traffic facilities is evaluated from the perspective of cooperativity according to the land utilization and urban traffic index data. And calculating ideal values of the city traffic index and the land utilization index of the traffic cell, and determining the improvement amplitude of the index according to the development level grade of the traffic cell.
Description
Technical Field
The invention belongs to the technical field of homeland space planning, and particularly relates to a land utilization and traffic collaborative evaluation method for the homeland space planning.
Background
Overview of land utilization and urban traffic co-development evaluation
The land utilization development strength and types of different regions of a city are directly determined by a planning scheme corresponding to the territory space planning, however, the development level of the traffic infrastructure of the corresponding region may not be matched with the planning scheme, so that the traffic facility waste or the traffic facility shortage is caused, therefore, the land utilization and urban traffic collaborative development evaluation aims to evaluate and guide the compilation of a large-scale territory space planning scheme according to a judicious principle, ensure that the land utilization development strength of the region is matched with the capacity of the traffic facility, provide a scientific and quantitative land utilization and urban traffic evaluation method for planning workers, and improve the territory space planning, particularly the feasibility and the scientificity of a controlled detailed planning and adjusting work.
The land utilization and urban traffic collaborative development evaluation comprises two main contents: the development level evaluation and the synergistic evaluation.
Brief introduction of traditional land utilization and urban traffic development collaborative evaluation method
At present, the theory and practice method for the collaborative development and evaluation of land utilization and urban traffic, which is not systematic at home and abroad, is shown in fig. 1, and the traditional theory for the collaborative analysis and evaluation of land utilization and urban traffic development at home and abroad at present is as follows:
(1) Urban traffic as the main consideration for evaluation
The method directly uses urban traffic factor indexes, such as road density, bus facility coverage and other related indexes, calculates the bearing capacity of the traffic facility, and evaluates the development level of the traffic facility and the influence on urban and regional space development.
(2) Land utilization as a main consideration factor of evaluation
Directly using land utilization factor indexes such as building area, volume rate, population employment and other related indexes, calculating the pressure of land utilization activities on an area, and evaluating the land utilization development level, the land utilization activity intensity level and the influence on the development of the area space.
(3) The urban traffic and land utilization are regarded as the theory of complex system
Based on a complex system theory, multiple factors of traffic and land utilization are considered at the same time, the traffic system and the land utilization system are divided into multiple small modules, an integrated model is established, simulation is carried out to measure and calculate the mutual influence between the traffic and the land utilization, and the development level and the matching degree of the traffic and the land utilization are evaluated.
(4) Independent system theory for urban traffic and land utilization viewed as mutual influence
Meanwhile, various factors of traffic and land utilization are considered, the traffic system and the land utilization system are regarded as mutually independent and mutually influenced systems, the traffic system and the land utilization system are quantified to a certain degree, a common quantitative relation model such as linear regression and the like is used, so that the quantitative interaction relation between the traffic system and the land utilization system is further determined, the possible situation of one party is estimated through the current data of the other party, and the matching degree is further evaluated.
Problems of traditional land utilization and urban traffic development collaborative evaluation method
The existing theoretical method mainly comprises the steps of evaluating the development level of a single factor of land utilization or urban traffic, analyzing the one-way matching property from land utilization to urban traffic or from urban traffic to land utilization, and limiting the development and synergistic evaluation effects. The complex system method capable of analyzing the development level, the matching degree and the interaction relationship of the two is complex in flow, extremely high in data requirement, more in premise hypothesis and not suitable for the work in the field of homeland space planning. The specific problems of the above practical method are as follows:
(1) Only urban traffic or land utilization is taken as a single consideration
The theoretical method basically neglects the action and influence of land utilization or urban traffic, and estimates the feasibility of land utilization development and the approximate strength of land utilization activity in the region only by calculating the traffic bearing capacity and accessibility of different regions, acquiring the convenient degree of traffic service and the like; or the attraction of the area to the construction of the transportation facility and the economy of the planning of the transportation facility are estimated only by calculating the land use development or the activity intensity. The method can only evaluate the development level of land utilization or urban traffic, cannot evaluate the matching degree between the land utilization and the urban traffic, and neglects the restriction of the traffic facilities on the land utilization and the influence of the land utilization on the traffic facilities.
(2) The integrated model based on the complex system theory has poor feasibility and lacks of popularization possibility
The theoretical method has various model frames, complex process and higher requirement on basic data, contains a large number of precondition assumptions and parameters which need to be preset, and is lack of feasibility in the evaluation of land utilization and urban traffic development cooperation. The interactive relationship between land utilization and urban traffic is represented by a complex system, a specific and brief quantitative relation is lacked, and index values of development level and cooperativity are not explicitly represented.
(3) Independent systems have difficulty describing the complex interaction of land use and urban traffic
The method takes the land utilization and the urban traffic as independent individuals, simplifies the mutual relation between the urban traffic and the land utilization to a certain extent, but the quantitative relation representing the mutual relation between the urban traffic and the land utilization is too simple, and the interaction between the highly-complex land utilization and the urban traffic in space and time is difficult to accurately describe.
The above mentioned are all the defects existing in the existing theoretical method, and in addition, the existing method does not have the evaluation area from the development level and the cooperativity, and the optimization direction and strategy making method after evaluation.
In order to solve the problems of the traditional land utilization and urban traffic development collaborative evaluation method, the technical difficulty is as follows:
1) Simultaneously evaluating the development levels of regional land utilization and urban traffic, and expressing the development levels by using specific numerical indexes;
2) Evaluating the cooperativity, namely the matching degree, between the land utilization and the urban traffic, and expressing the cooperativity by using a specific numerical index;
3) The existing theoretical practice method only has an evaluation method and lacks an optimization method, and a regional land utilization and urban traffic optimization improvement strategy needs to be formulated to perfect a planning scheme;
4) Most of the evaluation objects of the existing theoretical practice methods are single areas, different areas are independent from each other, and correlation exists between different evaluation areas, and the correlation needs to be taken into evaluation consideration;
5) Under the evaluation scene of a plurality of areas, the evaluation method for a single area is long in time consumption, and needs to be replaced by the evaluation method which is short in time consumption.
Disclosure of Invention
Aiming at the problems, the invention provides a land utilization and traffic cooperative evaluation method for national space planning, which is based on land utilization indexes and urban traffic indexes of a plurality of traffic cells, is based on a node-site model theory, processes the land utilization and urban traffic indexes at the same time, draws a scatter diagram, reflects the development levels of different traffic cells and reflects the relative sizes of the development levels among different traffic cells. After the development levels of different traffic districts are evaluated, land utilization and urban traffic indexes are processed simultaneously on the basis of a Data Envelope Analysis (DEA) theory, and the effectiveness of the DEA of each traffic district serving as a decision unit is estimated and used as a collaborative evaluation index. Finally, under the condition of complete cooperation, calculating the scale benefit state of the traffic cell and an ideal land utilization or urban traffic index value for determining the improvement direction and amplitude of the planning scheme and providing reference for planning work;
the technical scheme of the invention is as follows:
a land utilization and traffic collaborative evaluation method for homeland space planning comprises the following specific steps:
s1, dividing and acquiring indexes of traffic cells: dividing the research area into traffic districts, and acquiring a land utilization index and an urban traffic index of each traffic district according to the division result;
s2, construction of a development level evaluation model: based on the node-site model, carrying out centralized and standardized treatment on the land utilization index and the urban traffic index to obtain a land utilization index comprehensive value and an urban traffic index comprehensive value; drawing a development level scatter diagram by taking the urban traffic index comprehensive value as a vertical coordinate and taking the land utilization index comprehensive value as a horizontal coordinate;
s3, classification of development level grades based on cluster analysis: performing clustering analysis on the coordinate points on the development level scatter diagram obtained in the step S2, calculating and determining development level dividing lines according to the distribution of each clustering scatter point after obtaining the optimal clustering number, dividing the scatter points into different grades, and completing the development level grade division of the traffic cell;
s4, construction of a synergetic evaluation model: based on a data envelope analysis model, the maximum ratio of the land utilization index to the urban traffic index weighted comprehensive value is a target, the optimal weight combination of the land utilization index and the urban traffic index is solved, the maximum degree of cooperation is further calculated to serve as the cooperative evaluation index of the traffic cell, and the matching degree of the urban traffic facility supply capacity and the land use strength of the traffic cell is determined according to the value of the maximum degree of cooperation;
s5, land utilization and urban traffic index optimization strategy formulation: and further calculating the ideal values of the urban traffic indexes and the land utilization indexes in the scale benefit state and the complete synergy state of the traffic community according to the calculation result of the S4, comparing the ideal values with the urban traffic indexes and the land utilization indexes, determining the indexes of the traffic community which need to be improved in the aspects of urban traffic and land utilization, and simultaneously determining the improvement amplitude according to the development level grade of the community.
Preferably, S1 is specifically:
s11, dividing research areas according to natural barriers or artificial barriers, and combining areas with similar social, economic and population attributes into areasA single traffic cell to obtain a traffic cell set within the research rangeIThe number of traffic cells isN；
S12, according to the divided traffic districts, each traffic district is obtained
To (1)mTraffic index of individual city
And a firstkIndividual land utilization index
The number of the two indexes is respectivelyMAndKthe index vector formed by urban traffic indexes is
The land utilization index constitutes an index vector of
。
Preferably, S2 is specifically:
s21, constructing a development level evaluation model based on the node-site model, and carrying out centralized and standardized treatment on the land utilization indexes and the urban traffic indexes to obtain a land utilization index comprehensive value and an urban traffic index comprehensive value;
index centralization: each index of the urban traffic index and the land use index is centralized based on index factors according to the following formula, wherein
Represents the mean value:
wherein:
and (3) index addition: adding the centralized urban traffic index and the land utilization index according to the following formula to obtain an urban traffic index sum value and a land utilization index sum value:
wherein:
and (3) index comprehensive value calculation: standardizing the obtained urban traffic index sum value and land utilization index sum value based on traffic districts, and setting the vector of the two index sum values as
And
，
the expression variance, the urban traffic index comprehensive value and the land utilization index comprehensive value are obtained by standardized calculation according to the following formula:
wherein:
s22, drawing a development level scatter diagram: will be provided with
And
respectively as the ordinate and the abscissa, and combining to obtain the traffic districtiDevelopment level scatter plot coordinates of
According to the respective traffic celliAnd drawing the development level scatter diagram according to the development level scatter diagram coordinates.
Preferably, S3 is in particular:
s31, clustering analysis: carrying out clustering analysis on scattered points representing traffic cells on a development level scatter diagram based on the scattered point positions by using a K-means clustering algorithm, evaluating a clustering effect by using average contour coefficients of all the scattered points, and selecting an optimal clustering number according to an evaluation result to obtain corresponding grouped strip-shaped point clouds; each cluster contour systemNumber ofsCalculated by the following formula:
wherein:
s32, grouping zonal point clouds obtained according to clustering analysis and based on the number of the zonal pointscDetermining a specific number of development level grade division lines;
s33, determining a development level grade dividing line: is provided withrNumbering the points of the quantile, dividing the lines by the specific number of the development levelcSetting fractional point from small to large on the axis of abscissa
Representing the correspondence of the abscissa
Quantile, setting quantile point from small to large on ordinate axis
Indicating a correspondence of ordinate
Quantile division; are respectively connected with
And
the straight line segment is a development level grade dividing line, the straight line segment is matched with the separation between the cloud bands at different points, and if the straight line segment is not matched with the separation, the straight line segment is matched with the cloud bands at different points
And
adjusting until the anastomosis is achieved;
s34, calculating a development level grade dividing line intercept equation: determined according to the previous step
And
determining an intercept equation of the development level grade division line to express the development level grade division line:
wherein:xandyrespectively representing the abscissa and ordinate positions;
converting the intercept equation into a truncated equation:
s35, completing development level grade division based on a development level grade division line: traffic communityiBy corresponding scatter coordinate position
Determining a traffic cell according toiGrade of development level ofD：
And determining the development levels of all the traffic cells according to the formula and the development level scatter diagram.
Preferably, S4 is specifically:
s41 calculating traffic cell cooperativity
；
Wherein:
s42 based on the data envelope analysis model, to be synergistic
As an objective function, the index weight
And
as decision variables, the following synergy evaluation model was constructed:
wherein:
j-traffic celljThe number of (2);
S43, solving the synergy evaluation model to obtain the maximum synergy and the corresponding optimal weight combination.
Preferably, in S43, after obtaining the maximum traffic cell cooperativity, according to the cooperativity
Numerically determinable traffic celliMatching degree of supply capacity and land use strength of urban traffic facilities: when in use
In time, the land utilization development level of a traffic district needs to be improved; when in use
The supply capacity of the urban traffic facilities of the traffic community is basically matched with the travel demand corresponding to the land use strength; when in use
In time, the associated traffic infrastructure of the traffic cell needs to be added.
Preferably, S5 is specifically:
s51, calculating ideal values of urban traffic indexes and land utilization indexes of the traffic community in a scale benefit state and a complete synergy state:
the above-mentioned synergistic evaluation model is undergone the process of dual transformation, and introducedmSurplus variable corresponding to urban traffic index
Andkland utilization index mappingOf the relaxation variable
Converting inequality constraints into equality constraints; the residual variable and the slack variable respectively represent the urban transportation facilities that need to be reduced and the increased land use intensity required to reach the fully-coordinated state; the dual form of the synergy evaluation model is:
wherein:
as traffic districtsiAndjinter-cell combination coefficient, representing a celliAndjthe correlation of (a) with (b) is,
calculating traffic districts
After centering treatmentmTraffic index of individual city
：
Computing
：
Calculating traffic districtsiScale benefit status value of
：
S52 according to the scale benefit state
Selecting different planning and developing strategies: when the temperature is higher than the set temperature
Time, traffic districtiIn the state of increasing scale benefit when
And is provided with
Is less than
Increasing the construction of urban traffic facilities, and the method is suitable for the urban traffic facilities
Namely, it is
Is less than
In time, the future land use strength is increased; when in use
Time, traffic districtiIn the state of unchanged scale benefit, the method will
、
And with
、
Comparing, and building urban traffic facilities or using land according to the difference
、
Adjusting the direction; when in use
Time, traffic districtiIn a decreasing scale benefit state when
And is
Is greater than
When the investment of urban traffic facilities is reduced, the investment of urban traffic facilities is reduced
Namely, it is
Is greater than
In time, the future land use strength is reduced;
s53, determining an improvement amplitude according to the development level grade of the cell: when the development level grade of the traffic cell is higher, namely the comprehensive development level is at a higher level, the higher level refers to the number of point cloud bands with the development level grade at least more than half, namelyD≥[c/2]The adjustment range of the urban traffic index is kept between 0 and
middle and earthThe adjustment amplitude is kept between 0 and
in the middle of; when the development level grade of the traffic cell is lower, namely the comprehensive development level is at a lower level, the lower level refers to the number of point cloud zones with the development level grade at least less than half, namelyD≤[c/2]The adjustment range of the urban traffic index is kept at
And
meanwhile, the land utilization index adjustment range is kept at
And with
In between.
Compared with the prior art, the technical scheme adopted by the invention has the following beneficial effects:
the land utilization and traffic collaborative evaluation method for the territorial space planning can be directly applied to evaluation and optimization of the territorial space planning scheme, and the land utilization development level of a traffic district and the supply level of urban traffic facilities are evaluated from the aspect of development level according to land utilization and urban traffic index data to reflect the comprehensive development level of the land utilization development level and the urban traffic facility supply level; and evaluating the matching degree of the land use development level of the traffic district and the supply level of the urban traffic facilities from the perspective of cooperativity, and explaining the degree of the supply level of the urban traffic facilities meeting the traffic demands brought by the land use development of the traffic district. In addition, if the current situation cooperativity of the traffic community is low, the method can calculate the land utilization and urban traffic index level of the traffic community in an ideal cooperativity state to be used as a reference for optimizing the cooperativity of the community.
In the aspect of development level evaluation, the comprehensive value of the urban traffic index is taken as a vertical coordinate to reflect the supply capacity of the traffic facilities of the community; and finally, performing cluster analysis on the scattered points to classify development levels of different grades for each cell.
In the aspect of synergy evaluation, the method takes the input-output ratio of the maximized cell as a target, solves the optimal land utilization and urban traffic index weight, determines the synergy of each cell, further calculates the ideal value of each index of the cell under the condition of complete synergy, and provides reference for optimization of a territorial space planning scheme.
Drawings
FIG. 1 is a method for the collaborative evaluation of existing land utilization and urban traffic development.
FIG. 2 is a flow chart of a multi-facility equal time circle calculation method.
Fig. 3 is a city traffic index used.
Fig. 4 is a land use index used.
Fig. 5 is a development level evaluation model flow.
Fig. 6 is a scatter plot representing the development levels of different traffic cells.
Fig. 7 is a process of progression level ranking based on cluster analysis.
Fig. 8 is a basic principle of maximizing cooperativity representing cell cooperativity.
Fig. 9 is an urban traffic and land use index planning adjustment strategy.
Fig. 10 is a scatter plot of the results of the cluster analysis.
FIG. 11 is a scatter plot of the results of the progression-level grading.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The invention relates to a land utilization and traffic cooperative evaluation method for territorial space planning, which is based on traffic districts, land utilization and urban traffic index data, evaluates the development level and the cooperativity between the traffic districts and provides an optimization suggestion for a territorial space planning scheme.
The invention relates to a land utilization and traffic collaborative evaluation method for territorial space planning, which realizes an isochronal structure of a plurality of traffic facilities through a model consisting of five main steps, as shown in figure 2, and specifically comprises the following steps:
1) Traffic cell division and basic data acquisition: dividing the research area into traffic districts, and acquiring land utilization indexes and urban traffic index data of each traffic district according to the division result;
2) Development level evaluation model construction: based on the node-place model theory, the land utilization index and the urban traffic index are subjected to centralization and standardization treatment, and the index comprehensive value of the land utilization index and the urban traffic index is obtained. The urban traffic index comprehensive value is used as a vertical coordinate and reflects the traffic facility supply capacity of the community; and the land utilization index comprehensive value is used as a horizontal coordinate to reflect the land use strength of the cell, and the land use index comprehensive value and the horizontal coordinate are combined to be used as coordinates to draw a development level scatter diagram to reflect the development level of each traffic cell.
3) Ranking of development levels based on cluster analysis: performing clustering analysis on coordinate points on the development level scatter diagram obtained in the step 2 to obtain the optimal clustering number, calculating and determining development level dividing lines according to the distribution of each clustering scatter point, dividing the scatter points into different grades, and completing the development level grade division of the traffic cell;
4) Synergy evaluation model construction: based on a data envelope analysis model, the maximum ratio of land utilization to urban traffic weighted comprehensive values is a target, the optimal weight combination of land utilization and urban traffic indexes is solved, and the maximum degree of cooperation is further calculated to serve as the cooperative evaluation index of the cell;
5) Land utilization and urban traffic index optimization strategy formulation: and 4) further calculating the ideal values of the urban traffic and land utilization indexes in the scale benefit state and the complete synergy state of the cell according to the calculation result of the step 4), comparing the ideal values with the urban traffic indexes and the land utilization indexes, determining the indexes of the cell which need to be improved in the aspects of urban traffic and land utilization, and simultaneously determining the improvement amplitude according to the development level grade of the cell.
The method aims to evaluate the development level and the cooperativity of each traffic cell in a research area and propose a corresponding optimization strategy.
The land utilization and traffic cooperative evaluation method for territorial space planning of the invention is described in detail below.
Traffic cell division and basic data acquisition
Firstly, dividing research areas according to natural barriers such as rivers and mountains or artificial barriers such as roads and railways, merging areas with similar attributes such as society, economy and population into a single cell, and obtaining a traffic cell set in a research rangeIThe number of traffic cells isN。
Obtaining each traffic cell according to the divided traffic cells
To (1) amIndividual city traffic index
And a first step ofkIndividual land utilization index
The number of the two indexes is respectivelyMAndKthe index vector formed by the urban traffic indexes is
The land utilization index is formed into an index vector of
. The urban traffic index and the land use index used are shown in fig. 3 and 4.
The urban traffic indexes are mainly classified into the following three types:
1) Traffic network facilities: road network density; average distance from the entrance and exit of the highway; the space-time distances between the lower part of a bus or a car and an airport, a high-speed rail and a port are reduced; average travel time to other traffic cells.
2) Conventional public transport facilities: the conventional bus net density, the conventional bus stop coverage rate and the conventional bus stop density.
3) Rail transit facilities: track net density, track site coverage rate, track site 800m covered employment post number, track site 800m covered regular population number.
The land utilization indexes are mainly classified into the following three categories:
1) Population employment data: population density; employment post density.
2) Building data: production, life and ecological point of interest density; a volume fraction; the area of the building.
3) Land parcel data: production, living and ecological land area; the proportion of the land area for production, life and ecology; indexes of diversity of shannon in fields of production, life and ecology.
Definition of synergy and development level
Different traffic districts may have the same cooperativity but different development levels, such as a forest farm with sparse population, the travel demand of the standing population is met only by a small number of roads, the higher matching degree is realized, but the development level is extremely low; the urban center with dense population has a large number of roads and public transport facilities to meet the traveling of a large number of people, realizes higher matching degree and has higher development level. Therefore, the indexes of using two dimensions of cooperativity and development level are needed for describing the land utilization and urban traffic of the traffic district, and the indexes are all indispensable.
The cooperativity is defined as the matching degree of the supply capacity and the land use strength of the urban traffic facilities, and the more similar the development levels of the urban traffic facilities and the land use strength in the traffic cells, the higher the cooperativity of the traffic cells.
The development level is defined as the comprehensive strength value of the land use and the supply capacity of the urban traffic facilities, and the higher the land use strength is, the higher the supply capacity of the urban traffic facilities is, and the higher the development level of the traffic district is.
Development level evaluation model structure
The cooperativity can only reflect the matching degree of the urban transportation facility supply capacity and the land use intensity in a certain traffic cell, but the development level of the cell cannot be evaluated. In order to prevent misjudgment of the regional development condition caused by only referring to the cooperative indexes, a development level evaluation model needs to be constructed to judge the development level of the cell.
The node-site model theory considers that a traffic district comprises two dimensions of node value and site value, respectively corresponds to an urban traffic index and a land utilization index, reflects the supply capacity of traffic facilities and the land utilization strength, and can be used as an important reference for evaluating the development level.
A development level evaluation model is constructed based on a node-site model theory, the model can simply process input indexes and present results, the urban traffic indexes and the land utilization indexes are input into the model, comprehensive values of the urban traffic indexes and the land utilization indexes are obtained after processing, the comprehensive values respectively represent the traffic facility supply capacity and the land use strength of the traffic cells, a development level scatter diagram can be obtained according to the comprehensive values, and the development level distribution of different traffic cells in a research range is obtained. The development level evaluation model flowchart is shown in fig. 5, and the specific calculation steps are as follows:
index centralization: each index of the urban traffic index and the land use index is centralized based on index factors according to the following formula, wherein
Represents the mean value:
wherein:
and (3) index addition: adding the centralized urban traffic index and land utilization index according to the following formula to obtain an urban traffic index sum value and a land utilization index sum value:
wherein:
and (3) index comprehensive value calculation: standardizing the obtained urban traffic index sum value and land utilization index sum value based on traffic districts, and setting the vector of the two index sum values as
And
，
the expression variance, the urban traffic index comprehensive value and the land utilization index comprehensive value are subjected to standardized calculation according to the following formula:
wherein:
drawing a development level scatter diagram: will be provided with
And
respectively as the ordinate and the abscissa, and combining to obtain the traffic districtiDevelopment level scatter plot coordinates of
According to the respective traffic celliAnd drawing a development level scatter diagram according to the development level scatter diagram coordinates and performing subsequent analysis.
Development level ranking based on cluster analysis
As shown in fig. 6, in the development level scattergram obtained by the development level evaluation model, the traffic facility supply capacity and the land use intensity are insufficient near the left lower end of the development level scattergram, the development level is low, and the traffic facility supply capacity and the land use intensity are at a high level near the right upper end of the development level scattergram, the development level is high.
Meanwhile, in fig. 6, a large number of traffic cells are located at the upper left end or the lower right end of the development level scatter diagram, the levels of the transportation facility supply capacity and the land use intensity of the traffic cells are in completely opposite states, and it is difficult to preliminarily judge the development level of such traffic cells. In order to solve the problem that the development level is difficult to judge, clustering analysis is used for classifying the traffic cells represented by the point cloud of the development level scatter diagram to obtain banded point clouds, and a grade dividing line is determined according to the banded point cloud distribution in the clustering analysis result and is used for quantifying the development level grades of the traffic cells at different positions of the development level scatter diagram.
A flowchart of the development level ranking based on cluster analysis is shown in fig. 7, and the specific steps are as follows:
clustering analysis: carrying out clustering analysis on scattered points representing traffic cells on a development level scatter diagram based on the scattered point positions by using a K-means clustering algorithm, evaluating a clustering effect by using average contour coefficients of all the scattered points, and selecting an optimal clustering number according to an evaluation result to obtain corresponding grouped strip-shaped point clouds; coefficient of each cluster contoursCalculated by the following formula:
wherein:
grouping zonal point clouds obtained according to clustering analysis based on the number of zonal pointscDetermining a specific number of development level grade division lines;
determining a development level grade dividing line: is provided withrNumbering the points of the quantile, dividing the lines by the specific number of the development levelcSetting fractional point from small to large on the axis of abscissa
Representing correspondence of abscissa
Quantiles, setting quantile points from small to large on the ordinate axis
Representing a correspondence of ordinate
Quantile division; are respectively connected with
And
the straight line segment is a development level grade dividing line, the straight line segment is matched with the separation between the cloud bands at different points, and if the straight line segment is not matched with the separation, the straight line segment is matched with the cloud bands at different points
And
adjusting until the anastomosis is achieved;
calculating a development level grade dividing line intercept equation: determined according to the previous step
And
determining an intercept equation of the development level grade division line to express the development level grade division line:
wherein:xandyrespectively representing the abscissa and ordinate positions;
converting the intercept equation into a truncated equation:
completing development level grade division based on a development level grade division line: traffic districtiBy corresponding scatter coordinate position
Determining a traffic cell according toiGrade of development ofDThe higher the grade, the higher the development level of the traffic cell:
according to the formula and the development level scatter diagram, the development levels of all traffic cells can be determined.
Collaborative evaluation model structure
The development level can only reflect the comprehensive level of urban traffic facility supply capacity and land use strength in a certain traffic cell, namely the development level is high or low, but the matching adaptation degree of the urban traffic facility supply capacity and the land use strength cannot be determined, namely the urban traffic facility supply capacity meets the travel demand generated under the current land use strength in the traffic cell. In order to prevent the traffic cell from only taking the development level evaluation result as a planning work reference, a collaborative evaluation model structure needs to be constructed to judge the cell collaboration.
(1) Synergistic evaluation index definition
Defining traffic cellsiCooperativity of
The ratio of the weighted sum of the land utilization indexes to the weighted sum of the urban traffic indicates that under the current weight combination, the facility supply capacity of each unit can bear the unit quantity of land utilization intensity:
wherein:
the data envelope analysis model considers the traffic cells in the research area as a group of the same type of multi-input and multi-output input and output system, wherein the traffic facility supply capacity is used as input, and the land use intensity is used as output. As shown in fig. 8, under the condition of determining the input and output of the system, each cell has an optimal index weight combination, and the cooperativity is improved as much as possible under the condition that the current urban traffic index and land utilization index are not changed, so that the cellsiCooperativity
Maximization, the maximization
Indicates the celliThe maximum synergistic potential under the condition that the current urban traffic index and the current land utilization index are not changed. If use is maximized
Representative celliThe cooperativity of the two groups can be objectively compared among different cells, and the influence of subjective empowerment is avoided.
(2) Collaborative evaluation model mathematical representation
For solving traffic cellsiMaximum synergy of
In synergy with
As an objective function, the index weight
And
as decision variables, the following nonlinear programming problem form of the collaborative evaluation model was constructed:
wherein:
j-traffic districtsjNumber of (2);
(3) Collaborative evaluation model solving method and evaluation level
Evaluation model for solving cooperativityType, by Charnes-Cooper transformation, intermediate variables
Intermediate variables
Intermediate variables
Converting the nonlinear programming problem form into a linear programming problem form:
solving the linear programming problem using Branch and bound method (Branch and cut) can obtain maximum cooperativity and corresponding optimal weight combination. There are constraints due to the nonlinear programming problem described above
Thus, the cooperativity is strictly less than or equal to 1. In order to estimate the situation of relatively large input and output, namely the situation that the land use intensity is far greater than the supply capacity of the transportation facilities, the concept of super efficiency is introducedj=iIgnoring temporal constraints
I.e. in evaluating traffic districtsiIn the synergy of (2), the traffic districtiAnd shifting out the decision unit set.
After maximum synergy is obtained, according to
Numerical determinable traffic celliMatching degree of supply capacity and land use strength of urban traffic facilities:
when in use
Supply energy of urban traffic facilities in traffic districtsThe force exceeds the travel requirement corresponding to the land use strength, the traffic facilities are wasted, and the land use development level of a traffic district needs to be improved;
when the temperature is higher than the set temperature
The supply capacity of the urban traffic facilities of the traffic community is basically matched with the travel demand corresponding to the land use strength;
when in use
In time, the travel demand corresponding to the land use strength of the traffic community exceeds the supply capacity of urban traffic facilities, and the matched traffic infrastructure of the traffic community needs to be increased.
Land utilization and urban traffic index optimization strategy formulation
Besides the evaluation of the cooperativity of the traffic cells, the ideal cooperative state index value and the scale benefit state value also need to be calculated for judging the difference between the land utilization and the urban traffic current state index value and the ideal index value and increasing the cost performance of land utilization development or traffic facilities.
For solving the indexes, the linear programming problem form of the cooperative evaluation model is subjected to dual transformation and converted into a dual form, and the dual form is introducedmSurplus variable corresponding to urban traffic index
Andkrelaxation variable corresponding to land use index
And converting the inequality constraint into an equality constraint. The residual variable and the slack variable represent, respectively, a reduced urban transportation facility and an increased land use intensity required to reach the ideal cooperative state. The dual form of the synergy evaluation model is:
wherein:
as traffic districtsiAndjinter-cell combining coefficient, representing a celliAndjthe correlation of (a) with (b),
calculating traffic districts
After centering treatmentmIndividual city traffic index
：
Calculating traffic districts
After centering treatmentkIndividual land utilization index
：
Calculating traffic districtsiScale benefit status value of
：
As shown in fig. 9, different scale benefit states correspond to different planning and development strategies:
when the temperature is higher than the set temperature
Time, traffic districtiIn the state of increasing scale benefit when
And is
Is less than
Meanwhile, the construction of urban traffic facilities is increased
Namely, it is
Is less than
In time, the future land use strength is increased;
when in use
Time, traffic districtiIn the state of unchanged scale benefit, the method will
、
And
、
comparing, and building urban traffic facilities or using land according to the difference
、
Adjusting the direction;
when the temperature is higher than the set temperature
Time, traffic districtiIn a decreasing scale benefit state when
And is provided with
Is greater than
When the investment of urban traffic facilities is reduced, the investment of urban traffic facilities is reduced
Namely, it is
Is greater than
In time, the future land use strength is reduced; different development levels correspond to different improvement adjustment amplitudes:
determining the improvement amplitude according to the development level grade of the cell: when the development level grade of the traffic cell is higher, i.e. the comprehensive development level is at a higher level, the higher level refers to the number of point cloud bands with the development level grade at least larger than half, i.e. the number of point cloud bands with the development level grade is larger than halfD≥[c/2]The adjustment range of the urban traffic index is kept between 0 and
in between, the land utilization index adjustment range is kept between 0 and
in the middle of; when the development level of the traffic cell is lower in grade, i.e. the integrated development level is at a lower level, said lower level is the development levelNumber of point clouds with a flat rating at least less than half, i.e.D≤[c/2]The adjustment range of the urban traffic index is kept at
And
meanwhile, the land utilization index adjustment range is kept at
And
in between.
The invention will now be described in further detail with reference to the following examples:
example (b):
considering a city as a research scope, the research scope is divided into 3989 traffic cells. And acquiring urban traffic and land utilization index data of the community by taking the traffic community as a unit, and evaluating the development level and the synergy.
As shown in fig. 6, the evaluation result of the development level indicates that the traffic cell having the integrated value of the urban traffic and land use index greater than 0 has the corresponding development level above the average level, and has the development level below the average level when the integrated value is less than 0. About 30.8% of the traffic cell city traffic and land utilization index comprehensive values are simultaneously greater than 0, the development level of the cells is greater than the average level of Guangzhou, 38.1% of the traffic cells are simultaneously less than 0, the development level is less than the average level of Guangzhou, and the development level of part of the cells is higher but smaller in number.
The development level grading results based on the clustering analysis are shown in fig. 10 and fig. 11, the best grouping result of 6,6 groups of traffic cells using the K-means clustering algorithm presents a banded point cloud form, and the formed development level dividing line is made to fit the separation among different banded point clouds as much as possible by setting adjustment grading points on the horizontal and vertical coordinates. Finally, two grade dividing lines are formed, the development level grade can be divided into 3 types, and the higher the grade is, the higher the development level of the traffic cell is. High development level cells are concentrated in urban central areas, medium development level cells are concentrated in urban suburban areas, and low development level cells are concentrated in urban suburban areas.
Drawing a synergy evaluation result graph, wherein the synergy level is close to 1.0, namely the traffic districts with the traffic facility supply capacity matched with the travel demand under the current land use intensity are mainly concentrated in suburban areas; the cooperation level of a traffic district in a central area of a city is generally more than 1.0, the land use intensity is high, and the supply capacity of traffic facilities is insufficient; the cooperation level of the traffic cells in the urban suburban area is generally less than 1.0, the land use intensity is low, and the supply capacity of traffic facilities is wasted.
And (3) drawing a scale benefit state and index optimization strategy diagram, wherein regions with unchanged or decreased scale states are mainly concentrated in urban centers and suburban regions, the land utilization development level of the regions is basically higher and is close to the upper limit of the bearing capacity of land and traffic facilities, and the continuous development lacks economic feasibility. The volume fraction distribution of the traffic cells in the ideal coordination state has a similar form with the current situation, and the volume fraction is continuously reduced from the urban center to the suburban area. The volume rate recommended lifting value obtained by the collaborative evaluation model is solved, areas needing to lift the volume rate are mainly concentrated in suburban and suburban areas, the land use strength of the areas needs to be improved, and the volume rate of most areas in the center of a city is not recommended to be lifted.
Compared with the prior art, the technical scheme adopted by the invention has the following beneficial effects:
the land utilization and traffic collaborative evaluation method oriented to the territorial space planning can be directly applied to evaluation and optimization of the territorial space planning scheme, the development level and the cooperativity of a traffic cell are evaluated according to land utilization and urban traffic index data, and optimized data are provided to provide optimized suggestion values for improving the cooperativity.
The method comprises the steps of firstly evaluating the land utilization development level of the traffic districts and the supply level of the urban traffic facilities from the aspect of development level, obtaining specific numerical values reflecting the comprehensive development levels of the land utilization development level and the urban traffic facilities, and then quantitatively classifying the development levels of the traffic districts through cluster analysis to obtain the quantitative levels of the traffic districts.
Meanwhile, the matching degree of the land utilization development level of the traffic community and the supply level of the urban traffic facilities is evaluated from the perspective of cooperativity, so that the degree that the supply level of the urban traffic facilities meets the traffic demand brought by the land utilization development of the traffic community is shown. In addition, if the current cooperativity of the traffic cells is too low or too high, the method can calculate the land utilization and urban traffic index level of the traffic cells in an ideal cooperativity state to be used as a reference for optimizing the cooperativity of the cells.
It will be apparent to those skilled in the art that various changes and modifications can be made in the embodiments of the invention without departing from the inventive concept of the present application, and these embodiments are intended to be covered by the claims of the present application.
Claims (7)
1. A land utilization and traffic collaborative evaluation method oriented to homeland space planning is characterized by comprising the following specific steps:
s1, dividing and acquiring indexes of traffic districts: dividing the research area into traffic districts, and acquiring a land utilization index and an urban traffic index of each traffic district according to the division result;
s2, construction of a development level evaluation model: based on the node-site model, carrying out centralized and standardized treatment on the land utilization index and the urban traffic index to obtain a land utilization index comprehensive value and an urban traffic index comprehensive value; drawing a development level scatter diagram by taking the urban traffic index comprehensive value as a vertical coordinate and taking the land utilization index comprehensive value as a horizontal coordinate;
s3, classifying the development level grades based on cluster analysis: performing clustering analysis on the coordinate points on the development level scatter diagram obtained in the step S2, calculating and determining development level dividing lines according to the distribution of each clustering scatter point after obtaining the optimal clustering number, dividing the scatter points into different grades, and completing the development level grade division of the traffic cell;
s4, construction of a synergetic evaluation model: based on a data envelope analysis model, the maximum ratio of the land utilization index to the urban traffic index weighted comprehensive value is a target, the optimal weight combination of the land utilization index and the urban traffic index is solved, the maximum degree of cooperation is further calculated to serve as the cooperative evaluation index of the traffic community, and the matching degree of the urban traffic facility supply capacity and the land use strength of the traffic community is determined according to the value;
s5, land utilization and urban traffic index optimization strategy formulation: and further calculating the ideal values of the urban traffic indexes and the land utilization indexes in the scale benefit state and the complete synergy state of the traffic community according to the calculation result of the S4, comparing the ideal values with the urban traffic indexes and the land utilization indexes, determining the indexes of the traffic community which need to be improved in the aspects of urban traffic and land utilization, and simultaneously determining the improvement amplitude according to the development level grade of the community.
2. The land utilization and traffic collaborative evaluation method oriented to homeland space planning according to claim 1, wherein S1 specifically is:
s11, dividing research areas according to natural barriers or artificial barriers, combining the areas with similar social, economic and population attributes into a single traffic cell to obtain a traffic cell set in a research rangeIThe number of traffic districts isN；
S12, obtaining each traffic district according to the divided traffic districts
To (1) amIndividual city traffic index
And a first step ofkIndividual land utilization index
The number of the two indexes is respectivelyMAndKthe index vector formed by urban traffic indexes is
Land use indexThe index vector is
。
3. The land utilization and traffic collaborative evaluation method oriented to homeland space planning according to claim 2, wherein S2 specifically comprises:
s21, constructing a development level evaluation model based on the node-site model, and performing centralization and standardization processing on the land utilization indexes and the urban traffic indexes to obtain a comprehensive value of the land utilization indexes and a comprehensive value of the urban traffic indexes;
index centralization: each index of the urban traffic index and the land use index is centralized based on index factors according to the following formula, wherein
Represents the mean value:
wherein:
and (3) index addition: adding the centralized urban traffic index and the land utilization index according to the following formula to obtain an urban traffic index sum value and a land utilization index sum value:
wherein:
and (3) index comprehensive value calculation: standardizing the obtained urban traffic index sum value and land utilization index sum value based on traffic districts, and setting the vector of the two index sum values as
And
，
the expression variance, the urban traffic index comprehensive value and the land utilization index comprehensive value are subjected to standardized calculation according to the following formula:
wherein:
s22, drawing a development level scatter diagram: will be provided with
And
respectively as the ordinate and the abscissa, and combining to obtain the traffic districtiDevelopment level scatter plot coordinates of
According to the respective traffic celliAnd drawing the development level scatter diagram according to the development level scatter diagram coordinates.
4. The land utilization and traffic collaborative evaluation method oriented to homeland space planning according to claim 3, wherein S3 specifically is:
s31, clustering analysis: using a K-means clustering algorithm to perform clustering analysis on scattered points representing traffic cells on a development level scatter diagram based on scattered point positions, evaluating a clustering effect by using average contour coefficients of all the scattered points, and selecting an optimal clustering number according to an evaluation result to obtain corresponding grouped strip-shaped point clouds; coefficient of each cluster profilesCalculated by the following formula:
wherein:
s32, grouping zonal point clouds obtained according to clustering analysis and based on the number of point cloud zonescDetermining a specific number of development level grade division lines;
s33, determining a development level grade dividing line: is provided withrNumbering the points of the quantile, dividing the lines by the specific number of the development levelcSetting fractional point from small to large on the axis of abscissa
Representing the correspondence of the abscissa
Quantiles, setting quantile points from small to large on the ordinate axis
Indicating a correspondence of ordinate
Quantile division; are respectively connected with
And
the straight line segment is the development level grade dividing lineThe separation between the cloud bands at different points is matched, if not, the pair
And
adjusting until the anastomosis is achieved;
s34, calculating a development level grade dividing line intercept equation: determined according to the previous step
And
determining an intercept equation of the development level grade division line to express the development level grade division line:
wherein:xandyrespectively representing the abscissa and ordinate positions;
converting the intercept equation into a truncated equation:
s35, completing development level grade division based on a development level grade division line: traffic communityiBy corresponding scatter coordinate position
Determining a traffic cell according toiGrade of development level ofD：
And determining the development levels of all the traffic cells according to the formula and the development level scatter diagram.
5. The land utilization and traffic collaborative evaluation method oriented to homeland space planning according to claim 4, wherein S4 specifically is:
s41 calculating traffic cell cooperativity
；
Wherein:
s42, based on the data envelope analysis model, to be synergistic
As an objective function, the index weight
And
as decision variables, the following synergy evaluation model was constructed:
wherein:
j-traffic celljNumber of (2);
S43, solving the synergy evaluation model to obtain the maximum synergy and the corresponding optimal weight combination.
6. The land utilization and traffic cooperative evaluation method oriented to homeland space planning as claimed in claim 5, wherein in S43, after maximum traffic cell cooperativity is obtained, according to the cooperativity
Numerical determinable traffic celliMatching degree of supply capacity and land use strength of urban traffic facilities: when in use
In time, the land utilization development level of a traffic district needs to be improved; when the temperature is higher than the set temperature
The supply capacity of the urban traffic facilities of the traffic community is basically matched with the travel demand corresponding to the land use strength; when in use
In time, the supporting traffic infrastructure of the traffic district needs to be added。
7. The land utilization and traffic collaborative evaluation method oriented to homeland space planning according to claim 6, wherein S5 specifically comprises:
s51, calculating ideal values of urban traffic indexes and land utilization indexes of the traffic district in a scale benefit state and a complete synergy state:
the above synergy evaluation model is subjected to dual transformation and introducedmSurplus variable corresponding to urban traffic index
Andkrelaxation variable corresponding to land use index
Converting inequality constraints into equality constraints; the residual variable and the slack variable respectively represent the urban transportation facilities that need to be reduced and the land use intensity that needs to be increased to reach the complete synergy state; the dual form of the synergy evaluation model is:
wherein:
as traffic districtsiAndjinter-cell combination coefficient, representing a celliAndjthe correlation of (a) with (b),
calculating traffic districts
After centering treatmentmIndividual city traffic index
：
Calculating traffic districts
After centering treatmentkIndividual land utilization index
：
Calculating traffic districtsiScale benefit status value of
：
S52 according to the scale benefit state
Selecting different planning and developing strategies: when the temperature is higher than the set temperature
Time, traffic districtiIn the state of increasing scale benefit when
And is provided with
Is less than
Increasing the construction of urban traffic facilities, and the method is suitable for the urban traffic facilities
Namely that
Is less than
In time, the future land use strength is increased; when in use
Time, traffic districtiIn the state of unchanged scale benefit, will
、
And
、
comparing, and building urban traffic facilities or using land according to the difference
、
Adjusting the direction; when in use
Time, traffic districtiIn a decreasing scale benefit state when
And is
Is greater than
Meanwhile, the investment of urban traffic facilities is reduced, and the urban traffic facilities are used as
Namely that
Is greater than
In time, the future land use strength is reduced;
s53, determining an improvement amplitude according to the development level grade of the cell: when the development level grade of the traffic cell is higher, i.e. the comprehensive development level is at a higher level, the higher level refers to the number of point cloud bands with the development level grade at least larger than half, i.e. the number of point cloud bands with the development level grade is larger than halfD≥[c/2]The adjustment range of the urban traffic index is kept between 0 and
meanwhile, the land utilization index adjustment range is kept between 0 and
in the middle of; when the development level grade of the traffic cell is lower, i.e. the comprehensive development level is at a lower level, the lower level refers to the number of point cloud zones with a development level grade at least less than half, i.e. the number of point cloud zonesD≤[c/2]The adjustment range of the urban traffic index is kept at
And
meanwhile, the land utilization index adjustment range is kept at
And
in between.
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