CN106920391B - A kind of access difference analysis method of public transport based on spatial error model - Google Patents
A kind of access difference analysis method of public transport based on spatial error model Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
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Abstract
The access difference analysis method of the infrastructure public transport that the present invention relates to a kind of based on ANOVA, the location information of bus station and infrastructure is got first with Baidu map API, then it gets and takes transit time of the public transport from bus station to infrastructure and current distance, then the transportation accessibility of each administrative division in the transportation accessibility and city of each bus station is calculated, after analyzing and eliminating spatial auto-correlation, utilize variance analysis, finally obtain the otherness of each administrative division transportation accessibility in city, it can analyze to obtain infrastructure Equity evaluation on distribution in city from otherness result.The present invention evaluates the distribution equity of infrastructure in city, can plan urban infrastructure and provide decision support.
Description
Technical field
The invention belongs to space statistical analysis field, in particular to a kind of public transport based on spatial error model is sensible
Sex differernce analysis method.
Background technique
Public transport is main trip mode in social life, by these public transport such as public transport, subway, light rail,
The destination of passenger can be reached.The convenience of one place to another place is defined as the sensible degree of traffic, analyzes one
The sensible degree of the traffic in city is the minimum unit that block is regarded as to city, and the friendship in entire city is analyzed in more macroscopical level
Logical pattern, can provide decision support for city basis public transportation construction.The sensible degree of traffic is by accessibility
(Accessibility) it develops, Hansen defines the concept of accessibility at first, and accessibility is the chance of interaction
Potentiality.In space, accessibility is used to reflect that general traveler to be reached using given traffic system from departure place and lives
The convenience degree in dynamic place is the key factor of traffic system, land use and traveler interaction.And object is obtained in space
There are universal correlations, carry out necessary spatial autocorrelation analysis, can obtain more accurate result.It is ground to accessibility
Study carefully in application, Pooler has investigated the relationship of growth of employment and accessibility with regression analysis, uses employment factor as reachable
The main affecting factors for spending research, study 60, U.S. Metropolitan Area.Ozbay proposes a new accessibility function
Model, research is employment accessibility, and by the field of traffic of this model use to New York and New Jersey Metropolitan Area.In GIS
After achieving some achievements, the correlation theory methods in utilization GIS are more studied, O-Kelly and Horner utilize reachable
Topology degree obtains the research in terms of statistical data has carried out the rate of population increase to U.S.'s population in the region of county.In addition also some scholars will
Accessibility is combined with space-time, is preferably described accessibility in city and is obtained space-time characteristic.Mavoa et al. proposes that two kinds of public transport can
Up to the research method of degree, and the Zelanian city Auckland is applied to, finally proposes and obtained about public transportation vehicle frequency
It is recommended that.Cheng et al. analyzes Shenzhen and sees a doctor sensible degree, it is assumed that primary, second level, three-level are main places of seeing a doctor to obtain, and root
According to the space accessibility in each area of transit time and Spatial Difference.
When calculating the transportation accessibility of a point, following formula is used:
Wherein, AiIndicate that the transportation accessibility of a point, i, j respectively indicate two o'clock different in space, n, N representation space
The quantity at midpoint, SijIndicate the impedance factor of the calculating sensible degree of traffic, usually time or distance.
When calculating the transportation accessibility in a region, following formula is used:
Wherein, E indicates that the transportation accessibility in a region, i indicate any point in this region, n, N representation space
The quantity at midpoint, AiIndicate the transportation accessibility of a point.
Variance analysis (ANOVA) is a kind of testing of statistical hypothesis of special shape, is widely used in the analysis of experimental data
In.Testing of statistical hypothesis is a kind of method [5] that decision is carried out according to data.Variance analysis is for examining two groups or more
Experimental data group data mean value between significant difference, set a null hypothesis first, be expressed as all experimental group in experiment
Significant difference is not present between data mean value.Test result (being calculated by null hypothesis) if not just merely because fortune,
Statistically it is known as significant.Then it is calculated by a series of statistics, the result of statistically significant is (as the P-value of possibility
Less than critical " saliency value ") it can then overthrow null hypothesis.Variance analysis the result is that being indicated with variance table, error is by variance
It indicates, the error in group is the variance expression of each data and the mean value organized where him, and the error between group is that total error subtracts
The interior error of group is gone to obtain, and overall error is equal to population variance, df is freedom degree, for calculating average variance, is finally indicated by F value
Variance analysis as a result, being still typically all with the value of p-value to indicate significant result, when the value of p-value is greater than 0.05
When, then it represents that significant difference is not present, if less than 0.05, then it represents that there are significant difference, specific calculate is as follows:
Wherein
XiIt is the data in data set,It is the mean value of all data,It is each group of mean value, N is the number of group
Amount, n is total data bulk.
Spatial autocorrelation analysis is calculated using spatial error model (spatialerrormodel), space error mould
Type most starts to be proposed in " Spatial Econometrics:Methods and Models " by Anselin, according to geography
First theorem, adjacent things is similar, and separate things is different.Spatial error model is returned from normal linear, i.e. Y=α X
+ ε then needs on the basis of primal variable when two variables returned for normal linear all consider spatial auto-correlation
Subtracting part common to adjacent space around could return using normal linear, that is, need to subtract ρ WY, wherein ρ be space from
Related coefficient, W are Spatial Adjacency matrixes.So it is as follows to obtain spatial error model:
Y- ρ WY=α X- α ρ WX+ ε
Arranging deformation has:
Y=α X+ (I- ρ W)-1ε
Because spatial error model is not linear model, common least square method cannot be used to carry out parameter and estimated
It calculates, needs to carry out parameter estimation using maximum likelihood method.Variable is substituted into estimation in model and obtains the spatial autocorrelation of the variable
Coefficient, then eliminating spatial autocorrelation influences, and guarantees the independence of variable, just can be carried out variance analysis.
For common variance analysis method, experimental data necessity meets the vacation substantially of independence, normality, equal variance
If must satisfy independence, normality, equal variance for analyzing the data of otherness.It is poor to carry out to the data in space
Specific analysis, needs to meet such basic assumption, and the most basic feature of spatial data be exactly with spatial auto-correlation, it is empty
Between autocorrelation be existing complementary relationship between spatial data, so independence is unsatisfactory for, so common variance
Analysis can not carry out difference analysis, the variance analysis based on spatial error model developed on this basis to spatial data
Can effectively analysis space data otherness.
It is dispersed with many infrastructure in city and analyzes the passage convenience degree of urban infrastructure such as hospital, school
It can reflect out distribution situation of the infrastructure in city.It, can be with using the variance analysis method based on spatial error model
The transportation accessibility of different regions infrastructure in city is analyzed, if the traffic of the infrastructure between different regions is sensible
Sex differernce is significant, illustrates that the infrastructure distribution in city is unfair, and if the traffic of the infrastructure between different regions is logical
It is not significant up to sex differernce, illustrate that the infrastructure distribution in city is fair.The distribution equity of infrastructure in city is commented
Valence can plan urban infrastructure and provide decision support.
Summary of the invention
Whether problem to be solved by this invention is to provide in a kind of city infrastructure distribution in each administrative division public
Flat analysis method.
The present invention provide in a kind of city in each administrative division infrastructure distribution whether Gong Ping analysis method, including
Following steps:
Step 1: the API provided from Baidu map gets city upblic traffic station data and infrastructure position data, benefit
Distance of each bus station to infrastructure, time are got with the API that Baidu map provides.It is sensible to calculate public transport
Property, it specifically includes:
Step 1.1: bus station position data and infrastructure position all in city are got using Baidu map API
Set data.
Step 1.2: taking public transport from every using the acquisition of position data obtained in Baidu map API and step 1.1
Transit time and same row distance of one bus station to any infrastructure.
Step 1.3: utilizing transit time and same row distance obtained in the transportation accessibility calculation formula and step 1.2 of point
Calculate the transportation accessibility of each bus station in city.
Step 1.4: the transportation accessibility of point obtained in the transportation accessibility calculation formula and step 1.3 using face calculates
The transportation accessibility of each zoning in city out.
Step 2: using the variance analysis based on spatial error model by the traffic of each region being calculated in step 1
Access, test of normality, spatial autocorrelation analysis, elimination spatial autocorrelation including data influence, and specifically include:
Step 2.1: test of normality, the method used are carried out to the transportation accessibility data being calculated in step 1.4
It is Shapiro-Wilk test of normality, if carrying out step 2.2 by test of normality, otherwise utilizes Boxcox normal state
Property transformation non-normality data are converted into normality.
Step 2.2: doing spatial auto-correlation analysis using data of the spatial error model to step 2.1, analysis obtains sky
Between auto-correlation coefficient, then eliminate the access data of public transport spatial autocorrelation influence.
Step 2.3: the data for carrying out step 2.2 being done into variance analysis, obtain difference analysis result
Step 3: the result analyzed in step 2 being discussed, the infrastructure distribution in entire city is finally obtained
Equity Assessment.
It, can be from passage according to the access difference analysis method of urban infrastructure public transport provided by the present invention
Whether the distribution of infrastructure is reasonable in time and current two factor analysis cities of distance, and this distribution is commented based on fairness
What valence came out.And on the basis of using spatial autocorrelation analysis, more convictive difference can be obtained using variance analysis
Property result.
Detailed description of the invention
Fig. 1 is the flow chart of data acquisition of the embodiment of the present invention.
Fig. 2 is the process of the access difference analysis method of public transport of the embodiment of the present invention based on spatial error model
Figure.
Specific implementation method
For the ease of the understanding and the implementation present invention of those of ordinary skill in the art, with reference to the accompanying drawings and embodiments to this
Invention is described in further detail, it should be understood that and implementation example described herein is merely to illustrate and explain the present invention, and
It is not used in the restriction present invention.
The invention solves key problem be: analysis city in a certain infrastructure in each administrative division whether
Distribution is fair.
Referring to Fig.1, a kind of access difference analysis side of infrastructure public transport based on ANOVA provided by the invention
Method, comprising the following steps:
Step 1: the API provided from Baidu map gets city upblic traffic station data and infrastructure position data, benefit
Distance of each bus station to infrastructure, time are got with the API that Baidu map provides.It is sensible to calculate public transport
Property；
Step 1.1: bus station position data and infrastructure position all in city are got using Baidu map API
Set data；
When it is implemented, developer's site for service developer.baidu.com/ of Baidu map API can be referred to
Map, the bus station position data and infrastructure position data obtained in city are needed using in Baidu map API
JavaScriptAPI is write as html web page and with " bus station " for keyword search, is obtained by the local search API of offer
The title of all bus stations, affiliated administrative division, latitude and longitude coordinates in city.Then with the entitled key of infrastructure
Word scans for, and such as " Grade A hospital ", " primary school ", " middle school " etc. obtains the title of corresponding infrastructure, affiliated administrative area
It draws, latitude and longitude coordinates.The present invention carries out transportation accessibility difference analysis to the Grade A hospital of this selection Wuhan City.Wuhan City is
Provincial capital, Hubei Province is the key city of Central Region, is the whole nation important industrial base, science and education base and comprehensive traffic pivot
Knob, Wuhan City have 13 administrative divisions under its command, are Jiangan District, the Jianghan District 8XXkou District, Hanyang District, Wuchang District, Hongshan District, blueness respectively
Mountain area, Dongxihu District, Caidian District, Jiangxia District, Huangpo District, Xinzhou District, Hannan District.Select urban center of Wuhan City as real here
Test region, i.e. Jiangan District, the Jianghan District 8XXkou District, Hanyang District, Wuchang District, Hongshan District, this 7 administrative divisions of Qingshan District.Finally obtain
Get urban center of Wuhan City totally 1416 bus stations, 29 Grade A hospital position datas.
Step 1.2: taking public transport from every using the acquisition of position data obtained in Baidu map API and step 1.1
Transit time and same row distance of one bus station to any infrastructure；
When it is implemented, developer's site for service developer.baidu.com/ of Baidu map API can be referred to
Map, public transport is taken in acquisition to be made from each bus station to the transit time of any infrastructure and with row distance needs
It can choose different public transport in planning path with the DirectionAPI in Baidu map API in Web service API
Transfer strategy, including few transfer, few walking, not by the subway, the time is short, this preferential five kinds of strategies of subway.Pass through
DirectionAPI, each available bus station pass through the passage to take public transport to each infrastructure
Time and current distance, public transport referred to here includes special bus, subway, light rail etc..
Step 1.3: utilizing transit time and same row distance obtained in the transportation accessibility calculation formula and step 1.2 of point
Calculate the transportation accessibility of each bus station in city；
When it is implemented, it is public that the transit time got in step 1.2 and current distance are substituted into transportation accessibility respectively
Formula obtains the time-based transportation accessibility of each bus station and the transportation accessibility based on distance.
Step 1.4: the transportation accessibility of point obtained in the transportation accessibility calculation formula and step 1.3 using face calculates
The transportation accessibility of each zoning in city out；
When it is implemented, statistics falls in the bus station in each administrative division, it is all in this zoning with falling in
Bus station transportation accessibility calculate this zoning transportation accessibility, it is hereby achieved that zoning all in city
Time-based transportation accessibility and transportation accessibility based on distance.
Step 2: using the variance analysis based on spatial error model by the traffic of each region being calculated in step 1
It is access, the operation such as test of normality, spatial autocorrelation analysis, elimination spatial autocorrelation influence including data.
Step 2.1: test of normality, the method used are carried out to the transportation accessibility data being calculated in step 1.4
It is Shapiro-Wilk test of normality, if carrying out step 2.2 by test of normality, otherwise utilizes Boxcox normal state
Property transformation non-normality data are converted into normality.
When it is implemented, the data obtained in step 1 are carried out test of normality, the method for use is Shapiro-Wilk
Test of normality, Shapiro-Wilk test of normality are a kind of algorithm based on correlation, calculating formula are as follows:
Wherein, xiIt is variable to be measured,It is the mean value of variable to be measured, aiIt is constant to be estimated, W is detection statistic.Detection system
It measures bigger expression variable and more meets normal distribution, mainly still judged in conjunction with the value of P-value, be typically chosen 0.05
Confidence level, that is, indicate when P-value be more than or equal to 0.05 when, indicate variable be normality distribution, when P-value is less than
When 0.05, indicate that variable is not normality distribution.If variable is normality distribution, step 3.2 is carried out, is otherwise needed pair
Variable carries out normality transformation.The transformation of Boxcox normality is that a kind of pair of non-normality data progress power operation is converted to normality
The method of data, equally using the result of Shapiro-Wilk test of normality as judgment basis, calculating is selected in -2 to 2 ranges
Select the power operation parameter for meeting normality transformation.In instances, urban center of Wuhan City is based on the time and based on the public of distance
Traffic medical treatment is access to be not satisfied normality distribution, and finally respectively data are done with the power operation of -0.9 He -1.7, data are turned
It is changed to normality distributed data.
Step 2.2: doing spatial auto-correlation analysis using data of the spatial error model to step 2.1, analysis obtains sky
Between auto-correlation coefficient, then eliminate the access data of public transport spatial autocorrelation influence.
When it is implemented, doing spatial auto-correlation analysis, Yao Liyong spatial error model meter to result is obtained in step 2.1
Spatial autocorrelation coefficient is calculated, first has to establish Spatial Adjacency matrix using the syntople of each zoning in city in space, it is former
Reason is: assuming that there is N block region in space, then having the matrix of such a N*N to indicate the syntople between N block region, such as
I-th piece of region of fruit is adjacent with jth block region, then position is (i, j) in matrix and position be the value of (j, i) is all 1, and otherwise value is
0, while defining the number in matrix on diagonal line is all 0.Because spatial error model is a regression model, if to calculate certain
The spatial autocorrelation coefficient of one unitary variant, need to substitute into Spatial Adjacency matrix as parameter by the data of transportation accessibility with
Itself is returned, and then using the coefficient in maximum likelihood method estimation regression model, just there is space auto-correlation coefficient among these.Meter
After calculation obtains spatial autocorrelation coefficient, need to eliminate spatial autocorrelation influence, specific formula for calculation are as follows:
Y '=Y* (I- ρ WY)
Wherein, I is the unit matrix that 1 is all on diagonal line.
In instances, data are analyzed using spatial error model, is obtained based on the public transport away from discrete time
The spatial autocorrelation coefficient of sensible degree is 0.9812,0.9512, and spatial auto-correlation is especially strong, eliminates spatial auto-correlation ability
The independence for guaranteeing data, difference analysis could be carried out using variance analysis by meeting independence.
Step 2.3: the data for carrying out step 2.2 being done into variance analysis, obtain difference analysis result
When it is implemented, variance analysis is carried out to the data that obtain in step 2.2, it is obtaining the result is that variance analysis calculates
Obtain F value.Then P-value of the F value in entire data distribution is calculated, difference analysis result is analyzed by P-value.
Step 3: the result analyzed in step 2 being discussed, the infrastructure distribution in entire city is finally obtained
Equity Assessment.
When it is implemented, discussing to P-value obtained in step 2.3, commented in 0.05 confidence level
Valence, if P-value is more than or equal to 0.05, then it represents that difference is not significant, which is distributed justice in city；If P-
Value is less than 0.05, then it represents that significant difference, the infrastructure are distributed unfairness in city.But for a city,
Justice spatially is mainly embodied in apart from upper, and while being mainly resident trip on the time considers, so being based on the time
The sensible degree of traffic embody resident trip to the fairness of infrastructure, and the transportation accessibility based on distance embodies basis
The fairness that facility is distributed in city.In instances, urban center of Wuhan City is seen a doctor access based on the public transport of distance
Significant difference has been shown as, has illustrated that inequitable feature is distributed in Wuhan City in Grade A hospital, and it is time-based public
Traffic see a doctor it is access is presented without significant difference, illustrate resident when trip is to Grade A hospital, because of the vehicles
It influences, unfairness spatially is compensated for, and is eventually exhibited as justice.
It should be understood that the part that this specification does not elaborate belongs to the prior art.
It should be understood that the above-mentioned description for preferred embodiment is more detailed, can not therefore be considered to this
The limitation of invention patent protection range, those skilled in the art under the inspiration of the present invention, are not departing from power of the present invention
Benefit requires to make replacement or deformation under protected ambit, fall within the scope of protection of the present invention, this hair
It is bright range is claimed to be determined by the appended claims.
Claims (1)
1. a kind of access difference analysis method of public transport based on spatial error model, it is characterised in that including following step
It is rapid:
Step 1: the API provided from Baidu map gets city upblic traffic station data and infrastructure position data, utilizes hundred
The API that degree map provides gets distance of each bus station to infrastructure, time；It is access to calculate public transport,
It specifically includes:
Step 1.1: bus station position data and infrastructure positional number all in city are got using Baidu map API
According to；
Step 1.2: using position data obtained in Baidu map API and step 1.1 acquisition take public transport from each
Transit time and current distance of the bus station to any infrastructure；
Step 1.3: transit time obtained in the transportation accessibility calculation formula and step 1.2 using point and current distance calculate
Out in city each bus station transportation accessibility；
Step 1.4: the transportation accessibility calculating of point obtained in the transportation accessibility calculation formula and step 1.3 using face is gone out of the city
The transportation accessibility of each zoning in city；
Step 2: using the variance analysis based on spatial error model that the traffic of each region being calculated in step 1 is sensible
Property, test of normality, spatial autocorrelation analysis including data eliminate spatial autocorrelation and influence, specifically include:
Step 2.1: test of normality being carried out to the transportation accessibility data being calculated in step 1.4, the method used is
Otherwise Shapiro-Wilk test of normality utilizes Boxcox normality if carrying out step 2.2 by test of normality
Non-normality data are converted to normality by transformation；
Step 2.2: doing spatial auto-correlation analysis using data of the spatial error model to step 2.1, analysis obtains space certainly
Related coefficient, the spatial autocorrelation for then eliminating the access data of public transport influence；
Step 2.3: the data for carrying out step 2.2 being done into variance analysis, obtain difference analysis result；
Step 3: the result analyzed in step 2 being discussed, the infrastructure distribution for finally obtaining entire city is fair
Property evaluation.
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