CN112566030B - Mobile phone signaling data-based residence double-period identification method and application - Google Patents

Mobile phone signaling data-based residence double-period identification method and application Download PDF

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CN112566030B
CN112566030B CN202011444072.7A CN202011444072A CN112566030B CN 112566030 B CN112566030 B CN 112566030B CN 202011444072 A CN202011444072 A CN 202011444072A CN 112566030 B CN112566030 B CN 112566030B
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吴晓
何彦
邵云通
张瑞琪
张小国
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Southeast University
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Abstract

The invention discloses a residence double-period identification method based on mobile phone signaling data and application, and belongs to the field of urban residence research. Compared with the prior art, the method for identifying the double time periods of the residential area based on the mobile phone signaling data and the application thereof can accurately identify whether a certain area except the non-construction land is the residential area; in the aspect of spatial processing, a Thiessen polygon formed by a mobile phone base station is used as an identification unit in an area to be identified; in the data acquisition, the user mobile phone signaling data which is spatially associated with the area to be identified is discriminated and screened; in the aspect of time processing, a working day is divided into a day time period and a night time period, and population quantity changes of the area in the two time periods are respectively counted according to mobile phone signaling data of a user. The method can conveniently and accurately identify the residence places of urban population, and provides powerful technical support for effective analysis and utilization of urban space.

Description

Mobile phone signaling data-based residence double-period identification method and application
Technical Field
The invention relates to the field of urban residential area research, in particular to a residential area double-period identification method based on mobile phone signaling data and application.
Background
The residence is a fixed space range formed by continuous residence of residents, and is used as the residence of the place of the living and social center, namely the residence time has permanence and regularity, and the characteristics of few people in the day and more people at night are presented for a long time; the fixed place, which is the most frequently used space by the residents, is also the overlapping area of the multiple outgoing activity spaces. Therefore, with the above definitions in mind, the residence area under investigation in this study is the geographical location of the place of residence, and is taken as the residence of the place of daily life.
Based on the residence defined by the research institute, the identification method of the mobile phone data adopted at present mainly comprises the following steps: taking the complete time period of 23:00 to 5:00 of the next day every day as a time point for identifying a residence, and if at least 3 time points of each working day of a certain mobile phone are in the same base station, preliminarily identifying the coverage of the base station as the residence of the user on the day; if further, at least 6 days out of 10 working days represent the same base station of the residence, the base station can be basically identified as the residence of the user. Therefore, the traditional identification thought mainly depends on the continuity of data of the user at night, namely, whether the user is a living place is judged by accumulating the times of the user appearing in the same base station in one period at night.
At present, the biggest problems of the identification method are as follows: recognizing that the time mainly depends on the base station position movement situation of the user in a single period (night), and possibly misjudging the actual employment place (such as a hospital, a 24-hour convenience store and the like) of the night shift as the residence place of the user; on the basis of the new method developed at this time, a double-period identification method is obviously improved, namely, the large data of the mobile phone user in the daytime and at night are synchronously adopted and analyzed to accurately identify the residence of the mobile phone user, so that obvious omission of the traditional method is avoided.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a residence double-period identification method based on mobile phone signaling data and application thereof.
The purpose of the invention can be realized by the following technical scheme:
a method for identifying two time periods of a residence based on mobile phone signaling data and an application thereof are characterized by comprising the following steps:
acquiring mobile phone signaling data and target base station position data of a target base station in an area;
dividing the time of day into two time periods, dividing the mobile phone signaling data of the target base station into a day group and a night group according to the two time periods, and acquiring a population mobility factor Z according to the day group and the night group;
acquiring a employment population ratio Y according to the base station position data of the target base station and all community data in the area;
and (3) judging according to the sizes of Z and (1-Y) k: if Z < (1-Y) > k is satisfied, the signal coverage area of the target base station is judged as a residential area; wherein k is a correction coefficient.
Further, the obtaining mode of the employment population ratio Y comprises the following steps:
drawing a signal coverage area of the target base station according to a Thiessen polygon method according to the position of the mobile phone signaling data of the target base station at the target base station;
drawing all community coverage areas according to the community positions of the community data in the area, and setting n community coverage areas in the area;
calculating the overlapping area of the signal coverage area of the target base station and all community coverage areas in the area, and sequentially recording as S1,S2,...,Sn；
According to community data in the region, acquiring employment population proportions of communities with all overlapped areas and recording the employment population proportions as Y in sequence1,Y2,...,Yn；
The employment population ratio Y is obtained,
Figure BDA0002823642500000031
further, the method for obtaining the population mobility factor Z comprises the following steps:
dividing the mobile phone signaling data of the target base station into a day group and a night group according to time, wherein the time period of the day group is from 5 am to 11 pm, and the time period of the night group is from 11 pm to 5 pm; the adoption of the double-period identification method can avoid misjudgment of actual employment places (such as hospitals, 24-hour convenience stores and the like) containing night shifts in the target base station as the residence places of the users.
Statistical whiteThe number of people in the signal coverage area which does not leave the target base station in the day group is N1The number of people entering the signal coverage area of the target base station is N2The number of people leaving the signal coverage area of the target base station N3；
Counting the number N of people in the signal coverage area which does not leave the target base station in the night group1'The number of people entering the signal coverage area of the target base station is N2'The number of people leaving the signal coverage area of the target base station N3'；
A population mobility factor Z is obtained and used,
Figure BDA0002823642500000032
and N is1'+N2'-N3'≠0。
K is a correction factor for reducing N during the daytime1The influence of (2) is that the number N is not counted after a part of people go out and return for a short time in the daytime1(ii) a On the other hand, consider the current handset user coverage rate (<100%), the proportion of non-employment population by cell phone data statistics is significantly less than the actual non-employment population of the city.
Further, acquiring the land property of the target base station, wherein the land property of the target base station is E-type or G-type land, and directly judging that the target base station is not a residential area; the land for E type is a non-construction land, the land for G type is a green land, and the land for E type or G type is less in population, and when the judgment is made, the base station whose home location is the land for E type or G type can be directly judged as not being a residential area.
Further, before calculating the employment population proportion of the communities to which all the overlapping areas belong, screening retired population data of all the communities.
Furthermore, data of the mobile phone signaling data of the target base station with the legal working day date is screened out, and the activities of people in the legal working day are irregular, so that the acquisition of the population mobility factor Z is influenced.
Further, the mobile phone signaling data comprises the time when the mobile phone user enters the base station and the time when the mobile phone user leaves the base station; according to the mobile phone user of the target base stationEntering the target base station and the time when the mobile phone user leaves the target base station, and comparing N in the daytime group1、N1、N1And N in the night group1'、N2'、N3'And (6) carrying out statistics.
Judging the initial position and the end position of the mobile phone user according to the time when the mobile phone user of the target base station enters the target base station and the time when the mobile phone user leaves the target base station;
the determination is made according to the following:
in the first case: the starting position is in the target base station, the end position is in the target base station, and the base station is not in the middle, so that the starting position is defined as the person who never leaves in the A time period, and the number of the people is counted as N1(ii) a People who have not left during period B, count N1'；
In the second case: the starting position is at the target base station, the middle leaving base station is less than or equal to 2 hours, the end position is at the base station, which is to record the residents who return to the original base station after going out to buy vegetables, leisure or hospitalizing activities, and the people who return to the original base station after leaving for a short time in the period A, the number N is counted1；
In the third case: the initial position is not in the target base station, the end position is not in the target base station, and statistics is not carried out;
in a fourth case: the starting position is not in the target base station, the end position is in the target base station, the person who enters the target base station in a time period is defined, and N is counted2People entering during another time period count N2'；
In the fifth case: the starting position is in the target base station, the end position is not in the target base station, the person who leaves in a time period is defined, and N is counted3People who have left for another period of time, count N3'。
The invention has the beneficial effects that:
the invention provides a method for identifying whether a certain area is a residential area relatively accurately by adopting mobile phone signaling big data of an operator. Firstly, taking a Thiessen polygon formed by a mobile phone base station as an identification unit, and screening user mobile phone signaling data which are spatially associated with an area to be identified; secondly, dividing the working day into two time periods of daytime and nighttime, and respectively counting the population change of the area in the two time periods; and finally, calculating the change ratio of the population of the area to be identified in the daytime and at night, and judging whether the area is a residential area or not according to the ratio. The method can conveniently and accurately identify the residence places of urban population, and provides powerful technical support for utilization of urban space.
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The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a schematic flow chart of an identification method of the present application;
FIG. 2 is a GIS schematic diagram of the recognition of the residence of the central gate street in the Drum building area of Nanjing;
FIG. 3 is a schematic diagram of a Thiessen polygon generated by a base station in the street of the central gate of the Drum district in Nanjing;
FIG. 4 is a schematic diagram of a process for calculating the employment population proportion of a Thiessen polygonal area to which a base station belongs.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "opening," "upper," "lower," "thickness," "top," "middle," "length," "inner," "peripheral," and the like are used in an orientation or positional relationship merely to facilitate description of the invention and to simplify the description, and are not intended to indicate or imply that the referenced components or elements must be in a particular orientation, constructed and operative in a particular orientation, and are not to be construed as limiting the invention.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Taking the central gate street of the drum building area in Nanjing city as an example, FIG. 2 is a GIS schematic diagram of the method applied to identifying the residence of the central gate street in the drum building area in Nanjing city; the main parts of the flow in fig. 1 include cleaning and statistics of mobile phone signaling data, a thiessen polygon generated by a base station, and area extraction of the thiessen polygon and a community overlapping region, and the judgment is performed according to the flow in fig. 1 according to the following steps:
step 1: generating Thiessen polygons by all mobile phone base stations in a central gate street in Nanjing according to a Thiessen polygon method, wherein each Thiessen polygon represents the signal coverage range of one base station, the Thiessen polygons generated by the mobile phone base stations in the central gate street relate to 4 peripheral streets in total, and then correspondingly generating the Thiessen polygons as shown in an attached figure 3;
step 2: the method comprises the following steps of obtaining population change values of all base stations of mobile phone signaling data in 2015 of Nanjing city in two periods of time:
step 2.1: sequencing the time of the mobile phone signaling data, and dividing the mobile phone signaling data into two sections from 5 am to 11 pm (time period A), and from 11 pm to 5 am (time period B);
step 2.2: extracting data of a mobile phone base station of a central gate street, and counting the number N of people who do not leave the Thiessen polygonal area in the base station in the time period A1The number of people entering the Thiessen polygonal area N2The number of people leaving the Thiessen polygonal area N3(ii) a Counting the number N of people leaving the Thiessen polygonal area in the base station in the time period B1'The number of people entering the Thiessen polygonal area N2'The number of people leaving the Thiessen polygonal area N3'；
And 3, step 3: counting the employment population proportion of the Thiessen polygonal area to which the base station belongs;
step 3.1: acquiring employment population proportions (excluding retired persons) of central gate streets and peripheral streets in Nanjing city, counting employment proportions of the streets, and performing spatial association between the employment proportions and street boundaries in a geographic information system; y is1,Y2,…,Yn
Step 3.2: establishing spatial association between community data and all base stations by using a geographic information system, acquiring an overlapping area of a Thiessen polygon area and a community area to which a single base station belongs, counting the overlapping number of the Thiessen polygon and the community, and extracting the area S of each overlapping area1,S2,…,SnThen, the employment population ratio Y of communities to which each overlapping area belongs is counted1,Y2,…,YnAnd as the employment proportion of the overlapping area, as shown in fig. 4, finally calculating the employment population proportion Y of the thiessen polygon to which the base station belongs, the formula is as follows:
Figure BDA0002823642500000081
and 4, step 4: calculating a population movement factor Z, wherein the formula is as follows:
Figure BDA0002823642500000082
and N is1'+N2'-N3'≠0；
And 5: the coefficient k is used as a correction coefficient, on the one hand to reduce N in the A period1Because the person is not counted in the period A after a short time of going out and returning1(ii) a On the other hand, consider the current handset user coverage rate (<100%), the proportion of non-employment population by cell phone data statistics is significantly less than the actual non-employment population of the city.
After comprehensive consideration, k is more than 0.7 and less than 1, the k value is continuously tried and corrected by combining the current land utilization situation of the sample city, and is compared and checked with the actual situation of the sample city, and finally the k value is determined, for example, according to the table 1, whether the land type obtained by theoretical calculation of Nanjing city is consistent with the actual situation or not is determined, so that the k value of Nanjing city is determined to be 0.8.
Table 1 Nanjing k value trial and error table
Figure BDA0002823642500000091
Step 6: according to the obtained parameters, judging the sizes of Z and (1-Y) xk:
satisfying that when Z < (1-Y) > 0.8, the Thisen polygon area to which the base station belongs is a residential area;
when Z ≧ (1-Y) × 0.8 is satisfied, the Thiessen polygon area is excluded from the habitation.
And 7: and traversing all base stations of the street of the central gate, and performing the operation of the steps on the Thiessen polygon to which each base station belongs until all the base stations are judged.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.

Claims (5)

1. A method for identifying two time periods of a residence based on mobile phone signaling data is characterized by comprising the following steps:
acquiring mobile phone signaling data and target base station position data of a target base station in an area;
dividing the time of day into two time periods, dividing the mobile phone signaling data of the target base station into a day group and a night group according to the two time periods, and acquiring a population mobility factor Z according to the day group and the night group;
acquiring a employment population ratio Y according to the base station position data of the target base station and all community data in the area;
and (3) judging according to the sizes of Z and (1-Y) k: if Z < (1-Y) > k is satisfied, the signal coverage area of the target base station is judged as a residential area; wherein k is a correction coefficient;
the acquisition mode of the employment population ratio Y comprises the following steps:
drawing a signal coverage area of the target base station according to a Thiessen polygon method according to the position of the mobile phone signaling data of the target base station at the target base station;
drawing all community coverage areas according to the community positions of the community data in the area, and setting n community coverage areas in the area;
calculating the overlapping area of the signal coverage area of the target base station and all community coverage areas in the area, and sequentially recording as S1,S2,...,Sn；
According to community data in the region, acquiring employment population proportions of communities with all overlapped areas and recording the employment population proportions as Y in sequence1,Y2,...,Yn；
The employment population ratio Y is obtained,
Figure FDA0003616683880000011
the method for obtaining the population mobility factor Z comprises the following steps:
counting the number N of people in the signal coverage area which does not leave the target base station in the daytime group1The number of people entering the signal coverage area of the target base station is N2The number of people leaving the signal coverage area of the target base station N3；
Counting the number N of people in the signal coverage area which does not leave the target base station in the night group1'The number of people entering the signal coverage area of the target base station is N2'The number of people leaving the signal coverage area of the target base station N3'；
A population mobility factor Z is obtained and,
Figure FDA0003616683880000021
and N is1'+N2'-N3'≠0。
2. The dual-time-zone recognition method of residential areas according to claim 1, wherein the property of the land used by the target base station is obtained, the property of the land used by the target base station is a land used in class E or class G, and it is directly determined that the target base station is not a residential area.
3. The dual-session identification method for residential areas as claimed in claim 1, wherein the percentage of employment population of the communities to which all the overlapping areas belong is filtered out of retirement population data of all the communities before calculation.
4. The method of claim 1, wherein the data of the mobile phone signaling data of the target base station belonging to the legal working day is screened out.
5. The dual-session identification method of a residential area as claimed in claim 1, wherein said cell phone signaling data includes cell phone user entering time and cell phone user leaving time; according to the time when the mobile phone user of the target base station enters the target base station and the time when the mobile phone user leaves the target base station, N in the sky group is compared1、N2、N3And N in the night group1'、N2'、N3'And (6) carrying out statistics.
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