CN113327012A - Urban public transport index calculation method based on RGB color space and Monte Carlo method - Google Patents

Urban public transport index calculation method based on RGB color space and Monte Carlo method Download PDF

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CN113327012A
CN113327012A CN202110468086.0A CN202110468086A CN113327012A CN 113327012 A CN113327012 A CN 113327012A CN 202110468086 A CN202110468086 A CN 202110468086A CN 113327012 A CN113327012 A CN 113327012A
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张聪伟
杨敏
刘冬梅
李大韦
程龙
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Abstract

The invention discloses a city bus index calculation method based on an RGB color space and Monte Carlo method, which specifically comprises the following steps: acquiring a general land utilization planning map of an urban area to be researched and land area data of a research area; acquiring position information of public transport stations in a designated research area of a city; digitizing an overall layout intoRGBA matrix; matching the geographical position information of the land use general planning map with the obtained position information of the regional public transport station under the same coordinate system; determining blank and non-urban land areas of an overall planning mapRGBVector quantity; calculating the total area of the land of the area to be researched and the total bus coverage area based on a Monte Carlo method; and calculating the bus coverage rate and the bus stop density. The method provided by the invention has great significance for calculating the improved urban public transport related indexes and establishing an urban public transport evaluation index system of a scientific system so as to measure the urban public transport development.

Description

Urban public transport index calculation method based on RGB color space and Monte Carlo method
Technical Field
The invention relates to a city public transport index calculation method based on an RGB color space and a Monte Carlo method, and belongs to the field of city public transport planning and evaluation.
Background
With the traffic entering the new development stage, the traffic has increasingly obvious tendency of intensive and green development, and the environmental protection concepts such as carbon neutralization are raised to the national compendium level, which means that the urban development of China will further strengthen the attention on the environmental protection problem in the future. The public transportation development is promoted by taking the traffic as one of important sources of carbon emission, so that the urban traffic jam problem can be relieved, the traveling efficiency of residents can be improved, a large amount of automobile tail gas discharged by using private cars for traveling can be greatly reduced, and the method is a traveling mode according with the sustainable development strategy of China. Therefore, the related indexes of urban public transport become important factors for measuring the development of cities and regions.
In the related indexes of public transportation, the bus coverage rate and the bus stop density are two important measurement indexes. In the urban road traffic planning and designing standard, the bus coverage rate is also called the bus stop service area rate and is the percentage of the bus stop service area to the total urban land area; the bus stop density is the percentage of the number of bus stops to the total urban land area. No matter it is bus stop service area or city land used total area all is irregular figure, and it is very complicated that the tradition uses the integral principle to calculate, calculates through the GIS system and needs to gather a large amount of geographic information, and the result is comparatively crude.
The total urban land area of a city or region includes areas that do not require public transportation services, such as the alpine regions of northern mountainous terrain cities and the interior water systems of southern multi-water cities. The public transport indexes aim at reflecting the service condition of public transport to people, so the region is reasonably excluded in actual calculation, but obviously, the calculation process is more complicated, and therefore, it is necessary to provide a method for calculating the relevant indexes of the urban public transport, which can refine the area of the region and simplify the calculation complexity.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the urban public transport index calculation method based on the RGB color space and the Monte Carlo method is provided, the area of an area is finely researched based on the RGB color space, the calculation complexity of the area of an irregular area is reduced based on the Monte Carlo method, and then the urban public transport coverage and the bus stop density index are calculated.
The invention adopts the following technical scheme for solving the technical problems:
the urban public transport index calculation method based on the RGB color space and Monte Carlo method comprises the following steps:
step 1, obtaining a total plan of an urban area to be researched, wherein the total plan of the area to be researched comprises a land utilization total plan map of the area to be researched and a land area of the area to be researched;
step 2, acquiring the position information and the number of public transportation stations in the to-be-researched area of the city, and expressing the position information of the public transportation stations by using the longitude and latitude of a WGS84 international universal geographic coordinate system;
step 3, dividing the total land utilization planning map into m multiplied by n pixel points, recording RGB vectors of the pixel points, and obtaining a two-dimensional map matrix
Figure BDA0003044114780000021
Step 4, determining a new coordinate system according to the total land utilization planning map, and converting the position information of the public transportation station into the coordinates of the position information map of the public transportation station according to the new coordinate system;
step 5, determining RGB vectors of blank areas and non-urban land areas of the land utilization overall planning map, and using a two-dimensional list
Figure BDA0003044114780000022
Recording;
step 6, calculating the total area of land to be researched and the total bus coverage area based on a Monte Carlo method;
and 7, calculating the bus coverage rate according to the total bus coverage area and the total land area, and calculating the bus stop density according to the number of the bus stops and the total land area.
As a preferred embodiment of the present invention, the two-dimensional matrix of the graph in step 3
Figure BDA0003044114780000023
The method specifically comprises the following steps:
Figure BDA0003044114780000024
wherein, the element aijThe RGB vector representing the pixel points in the ith row and the jth column is a three-dimensional vector (R, G, B), i is 1, …, m, j is 1, …, n, m, n respectively represent the row number and column number of the two-dimensional matrix.
As a preferred embodiment of the present invention, the specific process of step 4 is as follows:
4.1, selecting a landmark place in the total land use planning map as a coordinate origin, wherein the WGS84 coordinate of the landmark place is (i)0,j0) The land uses the north direction of the general planning map as the positive direction of the coordinate to establish a new coordinate system;
4.2, selecting two public transportation stations on the total land utilization planning map, and calculating a first conversion factor alpha according to the position information of the two public transportation stations and the linear distance of the two public transportation stations on the total land utilization planning map;
4.3, calculating a second conversion factor beta according to the linear distance of the two public transport stations on the total land utilization planning map selected in the step 4.2 and the number of pixel points between the two public transport stations;
4.4, according to the first conversion factor alpha and the second conversion factor beta, the position information of the public transport station is converted
Figure BDA0003044114780000031
Converting into coordinates of public transport station position information graph
Figure BDA0003044114780000032
As a preferred embodiment of the present invention, the calculation formula of the first conversion factor α is:
the first conversion factor alpha is equal to the straight-line distance of the two public transportation stations on the land use overall planning map divided by the actual distance of the two public transportation stations and multiplied by the denominator of a scale.
As a preferred embodiment of the present invention, the calculation formula of the second conversion factor β is:
the second conversion factor beta is equal to the number of pixel points between the two public transport stations divided by the linear distance of the two public transport stations on the land utilization overall planning graph.
As a preferable aspect of the present invention, the coordinates of the public transportation station position information map
Figure BDA0003044114780000033
The method specifically comprises the following steps:
Figure BDA0003044114780000034
as a preferred embodiment of the present invention, the two-dimensional list of step 5
Figure BDA0003044114780000035
The method specifically comprises the following steps:
Figure BDA0003044114780000036
wherein k is 1, …, t, t is the number of RGB of non-urban land area and blank area on the land utilization overall plan, bkIs an RGB vector, is a three-dimensional vector (R + - ε, G + - ε, B + - ε), and ε is the color space error.
As a preferred embodiment of the present invention, the specific process of step 6 is as follows:
6.1 initializing effective study region points M all0 and the number of effective bus coverage points Mbus＝0；
6.2, determining iteration times N, wherein the value of N is 100 multiplied by m multiplied by N, and m and N respectively represent the row number and the column number of the two-dimensional matrix of the graph;
6.3, determining a color space error epsilon, wherein the epsilon takes a value of 5;
6.4, randomly determining the position coordinates (x, y) at each iteration, wherein x is equal to 0, m]，y∈[0,n]Record axy，axyAn RGB vector representing the position coordinates (x, y);
6.5, if
Figure BDA0003044114780000041
Then Mall＝Mall+1；
6.6, if
Figure BDA0003044114780000042
And is
Figure BDA0003044114780000043
Then Mbus＝Mbus+1，
Figure BDA0003044114780000044
Representing the coordinates of the position information graph of the public transport station, and K representing the converted service radius;
6.7 obtaining the total area of the land to be researched after the iteration is ended
Figure BDA0003044114780000045
Total bus coverage area
Figure BDA0003044114780000046
ATrueRepresenting the area of land in the area to be studied.
In a preferred embodiment of the present invention, the converted service radius K ═ K0×α×β，K0Representing public transportThe station service radius, α is a first conversion factor and β is a second conversion factor.
As a preferable scheme of the invention, the bus coverage rate in the step 7 is equal to the total bus coverage area divided by the total land area, and the bus stop density is equal to the number of the bus stops divided by the total land area.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
1. according to the method, the RGB color space in the urban land overall planning is utilized to carry out a refined research area, the precision is high, the tiny non-research area in the city can be screened out, and the accuracy of the result is improved.
2. The method converts the problem of solving irregular areas into the problem of probability based on the Monte Carlo method, converts the traditional complex integral calculation into the problem of simple random counting, reduces the requirement on the computing power of a computer, and saves a large amount of computing resources.
3. The urban public transport index calculation method can serve urban public transport planning and evaluation well, is easy to understand and operate, and can provide effective reference for establishing an urban evaluation system.
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FIG. 1 is a general flow chart of the urban public transportation index calculation method based on the RGB color space and Monte Carlo method of the present invention.
FIG. 2 is a flow chart of calculating the total area of study area and total bus coverage area using the Monte Carlo method in the present invention.
Fig. 3 is a general plan of land utilization in the city of suzhou city.
Fig. 4 is a matching graph of the overall planning diagram and the position of the bus station.
FIG. 5 is a map of non-urban land area.
Fig. 6 is a map of urban land area.
Fig. 7 is a global RGB color space.
FIG. 8 is a non-urban land area color space.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1, the present invention is a general flow chart of a city bus index calculation method based on RGB color space and monte carlo method. The following will explain the specific steps of the present invention in detail by taking the city of Suzhou city as an example.
(A) Acquiring a city designated research area overall plan, wherein the data to be prepared comprise a city designated research area land utilization overall plan map and research area land area data ATrue；
Downloading a Suzhou city facies city district land utilization overall planning high-precision graph (shown in figure 3) and a Suzhou city facies district land utilization overall planning text which are officially and actively disclosed for the whole society on a Suzhou city natural resource and planning office facies city branch office official network (http:// zrzy. jiangsu. gov. cn /), and obtaining official land area data A of a research areaTrue＝673.311(km2)。
(B) Obtaining position information of all public transport stations in Suzhou city phase city area
Figure BDA0003044114780000051
The public transportation station position information can be obtained by web crawler or by contacting with a public transportation service provider, and the position information is expressed by using the longitude and latitude of a WGS84 international universal geographic coordinate system, as shown in Table 1, wherein the quantity N isbus＝1507；
TABLE 1
Figure BDA0003044114780000052
Figure BDA0003044114780000061
(C) Dividing the total planning map into m × n 4010 × 7821 pixel pointsThe higher the image resolution is, the more accurate the final calculation result is, and the RGB vectors of all the pixel points are recorded to obtain a two-dimensional matrix of the image
Figure BDA0003044114780000062
As follows:
Figure BDA0003044114780000063
wherein the element aijThe RGB vector representing the pixel points in the ith row and the jth column is a three-dimensional vector (R, G, B), where a11、a1n、am1、amnThe four vertex angle vectors are (R, G, B) ═ 255, because the edges of the graph are white;
(D) matching the geographical position information of the land use general planning map with the obtained regional public transport station position information under the same coordinate system, wherein the specific method comprises the following steps:
(D1) the landmark places such as governments in research areas and the like can be taken as the coordinate origin of the overall planning map, and the due north direction is taken as the positive direction, so that the matching is carried out. In the city of government (i)0,j0) Locating with the origin (120.642391, 31.369189) and the public transportation station (120.644928, 31.373369) of the city of the same city as the destination, thereby matching the general planning map of the land utilization of the city of Suzhou city with the position information of the regional public transportation station, including the relative direction and the relative geographic position;
(D2) matching the straight-line distance between two points of the overall planning map under a unified geographic coordinate system according to the scale information (1: 50000) on the Suzhou city facies urban land utilization overall planning map, taking the facies urban government and the facies city tax administration bus station as an example, obtaining a conversion factor alpha for converting the actual distance into the length on the overall planning map, and calculating as follows:
Figure BDA0003044114780000071
(D3) calculating the conversion factor beta of the number of pixel points between the length of the overall plan diagram of the two points of the phase city government and the phase city tax bureau bus station and the number of the pixel points between the two points, and calculating the conversion factor beta as follows:
Figure BDA0003044114780000072
(D4) converted public transport station position information graph coordinates
Figure BDA0003044114780000073
As shown in table 2 and fig. 4.
TABLE 2
Figure BDA0003044114780000074
(E) Determining RGB vectors for the white space and non-urban land areas of the overall layout and using a two-dimensional list
Figure BDA0003044114780000075
It is noted that in the present embodiment, the RGB vector of the blank region is (255 ), the non-urban land region is only the water region, and the RGB vector is (117,225,254), so that
Figure BDA0003044114780000076
As follows;
Figure BDA0003044114780000077
wherein t 2 is the RGB number of non-urban land area and blank area on Suzhou city facies urban area land utilization overall planning diagram, bkIs a corresponding RGB vector, is a three-dimensional vector (R + -epsilon, G + -epsilon, B + -epsilon), wherein epsilon is a color space error; fig. 5 and 6 are non-urban land and urban land area diagrams, respectively. Fig. 7 and 8 are a global RGB color space and a non-urban land area color space, respectively.
(F) As shown in FIG. 2, the total area A of the study area was calculated based on the Monte Carlo methodallBus and bus coverage assemblyArea AbusWhen calculating the urban public transportation coverage rate RbusThen, the service radius K of the public transport station is selected0Is 300 m, and K is equal to K after conversion to the figure0X α × β, the specific method is as follows:
(F1) initializing valid study region points M all0 and the number of effective bus coverage points Mbus＝0；
(F2) Determining the random iteration number N, wherein the value is 100 multiplied by m multiplied by N;
(F3) determining a color space error epsilon, and taking the value of 5;
(F4) randomly determining position coordinates (x, y) in each iteration, wherein x belongs to [0, m ], y belongs to [0, n ], and recording a (x, y);
(F5) if it is
Figure BDA0003044114780000081
Then Mall＝Mall+1；
(F6) If it is
Figure BDA0003044114780000082
And is
Figure BDA0003044114780000083
Then Mbus＝Mbus+1；
(F7) After the iteration is terminated, obtaining the total area of the research region
Figure BDA0003044114780000084
Total bus coverage area
Figure BDA0003044114780000085
(G) Calculating the bus coverage rate RbusAnd bus stop density DbusWherein R isbus＝Abus÷Aall，Dbus＝Nbus÷AallThe results are summarized in Table 3:
TABLE 3
Figure BDA0003044114780000086
According to the design specification of urban road traffic planning, the coverage rate of urban public transport is calculated by taking 500m as the radius, and the result is not less than 90 percent.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.

Claims (10)

1. The urban public transport index calculation method based on the RGB color space and Monte Carlo method is characterized by comprising the following steps of:
step 1, obtaining a total plan of an urban area to be researched, wherein the total plan of the area to be researched comprises a land utilization total plan map of the area to be researched and a land area of the area to be researched;
step 2, acquiring the position information and the number of public transportation stations in the to-be-researched area of the city, and expressing the position information of the public transportation stations by using the longitude and latitude of a WGS84 international universal geographic coordinate system;
step 3, dividing the total land utilization planning map into m multiplied by n pixel points, recording RGB vectors of the pixel points, and obtaining a two-dimensional map matrix
Figure FDA0003044114770000011
Step 4, determining a new coordinate system according to the total land utilization planning map, and converting the position information of the public transportation station into the coordinates of the position information map of the public transportation station according to the new coordinate system;
step 5, determining RGB vectors of blank areas and non-urban land areas of the land utilization overall planning map, and using a two-dimensional list
Figure FDA0003044114770000012
Recording;
step 6, calculating the total area of land to be researched and the total bus coverage area based on a Monte Carlo method;
and 7, calculating the bus coverage rate according to the total bus coverage area and the total land area, and calculating the bus stop density according to the number of the bus stops and the total land area.
2. The method for calculating urban public transportation indexes based on RGB color space and Monte Carlo method according to claim 1, wherein the two-dimensional matrix of the graph in step 3
Figure FDA0003044114770000013
The method specifically comprises the following steps:
Figure FDA0003044114770000014
wherein, the element aijThe RGB vector representing the pixel points in the ith row and the jth column is a three-dimensional vector (R, G, B), i is 1, …, m, j is 1, …, n, m, n respectively represent the row number and column number of the two-dimensional matrix.
3. The urban public transportation index calculation method based on the RGB color space and Monte Carlo method according to claim 1, wherein the specific process of the step 4 is as follows:
4.1, selecting a landmark place in the total land use planning map as a coordinate origin, wherein the WGS84 coordinate of the landmark place is (i)0,j0) The land uses the north direction of the general planning map as the positive direction of the coordinate to establish a new coordinate system;
4.2, selecting two public transportation stations on the total land utilization planning map, and calculating a first conversion factor alpha according to the position information of the two public transportation stations and the linear distance of the two public transportation stations on the total land utilization planning map;
4.3, calculating a second conversion factor beta according to the linear distance of the two public transport stations on the total land utilization planning map selected in the step 4.2 and the number of pixel points between the two public transport stations;
4.4, according to the first conversion factor alpha and the second conversion factor beta, the position information of the public transport station is converted
Figure FDA0003044114770000021
Converting into coordinates of public transport station position information graph
Figure FDA0003044114770000022
4. The urban public transportation index calculation method based on the RGB color space and Monte Carlo method according to claim 3, wherein the calculation formula of the first conversion factor α is as follows:
the first conversion factor alpha is equal to the straight-line distance of the two public transportation stations on the land use overall planning map divided by the actual distance of the two public transportation stations and multiplied by the denominator of a scale.
5. The urban public transportation index calculation method based on the RGB color space and Monte Carlo method according to claim 3, wherein the calculation formula of the second conversion factor β is as follows:
the second conversion factor beta is equal to the number of pixel points between the two public transport stations divided by the linear distance of the two public transport stations on the land utilization overall planning graph.
6. The RGB color space and Monte Carlo method based city bus index calculation method as claimed in claim 3, wherein the public transportation station position information map coordinates
Figure FDA0003044114770000023
The method specifically comprises the following steps:
Figure FDA0003044114770000024
7. the RGB color space and Monte Carlo method based urban public transportation index calculation method as claimed in claim 1, wherein the two-dimensional list in step 5
Figure FDA0003044114770000025
The method specifically comprises the following steps:
Figure FDA0003044114770000026
wherein k is 1, …, t, t is the number of RGB of non-urban land area and blank area on the land utilization overall plan, bkIs an RGB vector, is a three-dimensional vector (R + - ε, G + - ε, B + - ε), and ε is the color space error.
8. The urban public transportation index calculation method based on the RGB color space and Monte Carlo method according to claim 1, wherein the specific process of the step 6 is as follows:
6.1 initializing effective study region points Mall0 and the number of effective bus coverage points Mbus＝0；
6.2, determining iteration times N, wherein the value of N is 100 multiplied by m multiplied by N, and m and N respectively represent the row number and the column number of the two-dimensional matrix of the graph;
6.3, determining a color space error epsilon, wherein the epsilon takes a value of 5;
6.4, randomly determining the position coordinates (x, y) at each iteration, wherein x is equal to 0, m]，y∈[0,n]Record axy，axyAn RGB vector representing the position coordinates (x, y);
6.5, if
Figure FDA0003044114770000031
Then Mall＝Mall+1；
6.6, if
Figure FDA0003044114770000032
And is
Figure FDA0003044114770000033
Then Mbus＝Mbus+1，
Figure FDA0003044114770000034
Representing the coordinates of the position information graph of the public transport station, and K representing the converted service radius;
6.7 obtaining the total area of the land to be researched after the iteration is ended
Figure FDA0003044114770000035
Total bus coverage area
Figure FDA0003044114770000036
ATrueRepresenting the area of land in the area to be studied.
9. The RGB color space and monte carlo method-based urban bus index calculation method according to claim 8, wherein the converted service radius K ═ K0×α×β，K0Representing the service radius of the public transportation station, alpha is a first conversion factor, and beta is a second conversion factor.
10. The method as claimed in claim 1, wherein the bus coverage rate in step 7 is equal to the total bus coverage area divided by the total land area, and the bus stop density is equal to the number of bus stops divided by the total land area.
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