Study of Urban System Spatial Interaction Based on

Research ArticleStudy of Urban System Spatial Interaction Based on MicroblogData A Case of Huaihe River Basin China

Yong Fan 12 Juhui Yao3 Zongyi He 4 Biao He 1 and Minmin Li1

1Research Institute for Smart Cities School of Architecture and Urban Planning Shenzhen University Shenzhen China2College of Geographic Sciences Xinyang Normal University Xinyang China3Navinfo (Xirsquoan) Co Ltd Xirsquoan China4School of Resource and Environmental Sciences Wuhan University Wuhan China

Correspondence should be addressed to Biao He whu_hebiaohotmailcom

Received 6 November 2018 Accepted 17 January 2019 Published 5 February 2019

Guest Editor Alvaro Rubio-Largo

Copyright copy 2019 Yong Fan et al is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

e spatial interaction of urban system has been an hot research issue in the field of urban research In this paper userrsquos microblogspatial information data were used to discern the spatial structure of an urban area Firstly Sina Weibo microblog data for2011ndash2015 were used to establish a thematic database of cities along the Huaihe River Basin China Secondly network con-nectivity inflow and outflow of three indicator systems were analyzed Finally combining this database with socioeconomic dataexperimental verification and comparative analysis were carried out e study found that the urban spatial relation in the HuaiheRiver Basin has the following characteristics the spatial difference of urban size distribution is obvious urban layout presents astratified aggregation phenomenon and the high-grade cities lead the cityrsquos interaction e research shows that this method ofdata mining for urban interaction in the Huaihe River Basin is valid and that this research into urban spatial patterns of riverbasins is applicable to other areas

1 Introduction

In the four decades since Chinarsquos reform the urbanpopulation has increased from 170 million in 1978 to 790million in 2016 and the urbanization rate has increasedfrom 179 to 574 [1] However the level of urbanizationin China is still lower than that of 70ndash80 of developedcountries In the future China will still be in the stage ofrapid urbanization and development e relationshipbetween man and nature has become a hot topic in China atthe same time Urbanization promotes the exchange ofmaterials energy personnel and information among cit-ies this exchange is called urban space interaction [2] Howto effectively model and quantitatively express the spatialinteraction of regional cities is a significant question andthe basis of this research

e regional urban system is a complex network [3 4]e connection between two nodes in this network can berepresented by visible lines such as highways and railways

or by invisible lines such as aviation pathways navigationand the Internet [5] e flow within the system emphasizesthe value of urban nodes in shaping the whole networksystem which provides a theoretical framework and animportant starting point for the study of urban networks [6]Data relate to traffic and information flow can most directlyreflect the degree of urban spatial interaction [7] Earlyresearch on this aspect studied the transmission of mail escope of research on transportation is more comprehensiveincluding the highway railway and aviation networks [8 9]In addition the urban hierarchy can also be exploredthrough the distribution of corporate headquarters [10] andbanks [11] e flow and consumption of network in-formation can reflect the level of urbanization [12] whichcan provide basic data for geographical and sociologicalstudies [13 14]

e age of big data and the rapid development of LBS(location-based service) allow for urban research to beconducted by novel methods [15 16] With the gradual

HindawiScientific ProgrammingVolume 2019 Article ID 2074329 9 pageshttpsdoiorg10115520192074329

penetration of computers into various professions socialmedia data [17ndash19] have attracted the attention of geog-raphers due to its use in research [20] e use of socialmedia was one of the needs of urban communities [21] Asfor the typical spatial-temporal characteristics of socialmedia data many data mining research papers have an-alyzed information such as urban hot events [22]identifying urban Corridors [23] geography of happiness[24] whereabouts of people [25] urban function con-nectivity [26] urban spatial interaction [27] revaluatingurban space [28] and characterizing witness accounts[29] Data mining [30] provides new tools methods andideas for new geographical research improving the effi-ciency accuracy and precision of the analysis [31]

Based on the data of Sina Weibo microblog [32] thispaper established a thematic database of cities along theHuaihe River Basin China e spatial interaction of theregional urban system was analyzed from temporal andspatial characteristics of the data Finally combining thisdatabase with socioeconomic data experimental verificationand comparative analysis were carried out is paperprovides a reference for the exploration of the spatial re-lationship of regional urban systems and the drivingmechanism for spatial structure of urban system

2 Study Area

e Huaihe River Basin is located in the eastern region ofChina between the Yangtze River Basin and the YellowRiver Basin It flows through the four provinces of HenanAnhui Jiangsu and Shandong and covers a total area of27 times105 km2 e Huaihe River Basin has multipletransitional nature and society and connects coastal regionand inland region as well as being the economic in-tegration hub of the Yangtze River and Yellow Rivereconomic belts

e Huaihe River Basin has an enormous population of170 million people accounting for 123 percent of the totalpopulation of China e average population density is 611people per km2 which is 48 times of the average levelacross the country Given that the Huaihe River Basin is anatural geographical unit and does not coincide with theboundaries of the administrative units the study onlyselected the 26 cities whose governmental units are entirelyin the Huaihe River Basin for calculation and analysis(Figure 1)

3 Data Source and Processing

31 Sina Weibo Microblog e data gathered from the SinaWeibo microblog are the information released by microblogusers on the social network Compared with traditionalsocial survey data and economic social statistics the SinaWeibo microblog data have an unparalleled advantage in thefact that it performs well in real-time and is reliable anddiverse Currently information can be gathered from theSina Weibo microblog using web crawlers and the SinaWeibo microblog open platform API is study uses thelatter to obtain the relevant information for this research

32 Preprocessing the Sina Weibo Microblog First thegathered data were cropped to the latitude and longituderange of the survey region Each city administrative unit wasdivided into a 10 km-long grid the coordinates of the gridcenter were obtained and the WGS-84 geographic co-ordinate system was applied Next taking the longitude andlatitude of different cities as parameters user ID informationfrom these cities was obtained through the nearby_timelineinterface (an API interface) e user ID information in-cludes a source (through the authorized APPKey) longitudeand latitude as well as other data Using the user ID in-formation as the parameter the userrsquos historical data throughthe check-in interface (another API interface) were obtainede data returned by calling the API interface were in theJSON format In this study a Python script was written toachieve batch data acquisition e process of data acqui-sition is shown in Figure 2

33 -e Spatial Interaction of the Urban SystemMicroblog check-in data can reflect the spatial interactionof urban system this paper adopts two methods to analyzethese interactions e first is connectivity which is used toanalyze the intensity of communication between regionalcities the second is flow through which the userrsquos tra-jectory and the interactive state among cities can beanalyzed

331 Connectivity ismethod is based on the cityrsquos check-in data from which the network connectivity among citieswas analyzed which is described as follows

(1) Variable Unitization After variable unitization amatching matrix was established regarding the citycheck-in data using the following equation

Vij0 Vij1

111393625j1Vij

(1)

where Vij0 is a microblog user in city i who signedinto city j after unitization Vij1 represents amicroblog user of i city who signed in city j after dataacquisition and 1113936 Vij represents the sum of thecheck-in data of user form city i in city j

(2) Urban External Connection Index e urban ex-ternal connection index represents the differencebetween the total number of check-ins in other citiesand those in city i is is calculated using the fol-lowing equation

Ni0 111394425

j1Vij0minusVii0 (2)

where Ni0 is the external connection index of city iwhich reflects the check-in data (V) of city i in theother 25 cities Vii0 represents the check-in data ofcity i after unitization and Vij0 is the sum of check-in data of microblog users from city i who signed inother cities after unitization

2 Scientific Programming

If Ni0gt 0 users of city i sign into the microblog morewhen not in city i if Ni0lt 0 users registered to city icheck into Sina Weibo locally Ni0 0 means thatusers from city i are equally likely to sign into themicroblog whether they are within city i or awayfrom the city

(3) Urban Network Connectivity First the standardizedcheck-in data of city i in city j and the standardizedcheck-in data of city j in city i are multiplied togetherto obtain the urban network connectivity enthese data are standardized to produce the stan-dardized network connectivity is is summarizedin the following equation

Rij Vij0lowastVji0

Rij0 Rij lowast100

Max Rij( )

(3)

where Rij0 is the standardized network connectivitybetween city i and city j Rij is the network con-nectivity between city i and city j Vij0 is the stan-dardized value of friends of city j residents who livein city i Max(Rij) is the maximum network con-nectivity value and Rij0 reects interconnectednessof each cityrsquos information

(4) Network Connectivity in Each City Mi0 is thestandard network connectivity of city i with itself

Figure 1 Study area

Urban grid division

Sina microblog

Nearby timeline API Check-in APIUser ID

Check-in informationDatabase

Figure 2 e process of sina Weibo microblog data acquisition

Scientic Programming 3

Mi0i is the difference between the standard networkconnectivity of city i and city j and the standardnetwork connectivity of city i itself is is calculatedusing the following equation

Mi0 111394425

j1Rij0minusRii0 (4)

where Mi0 reflects the linkage strength of city iwithin the network system

332 Inflow Rating and Outflow Rating e inflow andoutflow ratings reflect the attractiveness and interaction ofcities respectively e inflow rating is the total number ofother cities signed into the city e greater the inflow thehigher the attractiveness and degree of interaction the cityhas e outflow rating reflects the total number of usersregistered to the city signed into other cities

e greater the outflow rating the greater the output ofthe city which indicates the city has a higher degree ofinteraction with other cities

Formula (5) is used to calculate the inflow rating of city iwhere Vi1 indicates the number of check-ins from usersregistered to city j in city i

Vi1 111394425

j1Vij (5)

Formula (6) is used to calculate the outflow rating of cityi where Vi2 indicates the number of check-ins from usersregistered to city j in city i

Vi2 111394425

j1Vijprime (6)

To further analyze the reasons for flow among cities theratio of inflow to outflow is introduced which can reflect thepopulation flow among cities is is calculated using thefollowing equation

R Vi1

Vi2 (7)

4 Results

41 Connectivity Analysis Based on the calculation of urbanconnectivity the microblog check-in data in the study areacan be calculated From this the urban external connectivityindex and network connectivity are obtained is data aresummarized in Table 1

In Table 1 the Ni0 value of Luohe and Kaifeng is 1 whichshows that there are more check-ins from outside users intoboth Luohe and Kaifeng e Ni0 value of Rizhao is minus060which is the lowest in the Huaihe River Basin is indicatesthat check-in data of Rizhao consist of nearly only local usersIn addition the Mi0 value of Bengbu is minus154359 which is theminimum in the Huaihe River Basin Bengbursquos external re-lations with the basin as a whole are relatively weak e Mi0of Luohe is 29115 which is the largest in the Huaihe River

Basin It shows that Luohe has a strong external relationshipwith the whole basin Luohe is located in the middle of theHenan Province next to the provincial capital Zhengzhoue city has convenient transportation prosperous economywell-developed tourism industry and large population mo-bility these factors allow for more users to travel to otherlocations and increase the Mi0 value of Luohe

By analyzing the relationship between the external andinternal connectivity of a city (Figure 3) the following threeconclusions were reached

(1) e internal urban network connectivity is consis-tent with the urban external connectivity the lowerthe city ranks in terms of internal connectivity thelower the cityrsquos level of external connections with therest of the network Among the 26 cities LuoheKaifeng Huainan and Bozhou comprised the topfour e positive values for these cities indicate thatthe intensity of external connections between thefour cities is greater than that within the cities eremaining 22 cities have negative values which showthat these cities have low external connections andthat communication within these cities is greaterthan that with the external network e networkconnectivity of Fuyang and Bengbu does not cor-respond to the urban city hierarchy which showsthat although the interconnectedness of these 2cities with the other cities in the basin is not hightheir absolute degree of network connectivity isrelatively high is is mainly due to the strongnetwork connectivity in a small area is phe-nomenon is most obvious in Bengbu

Table 1 External connection index and network connectivity

Name Ni0 Mi0Luohe 100 29115Kaifeng 100 20367Huainan 097 15924Bozhou 095 12038Yangzhou 086 minus8464Fuyang 062 minus4769Xinyang 042 minus8331Lianyungang 039 minus7532Jining 032 minus7407Suzhou 023 minus8643Huaiyin minus001 minus9693Zhumadian minus008 minus9796Suqian minus015 minus9690Heze minus016 minus9896Zhoukou minus022 minus9830Bengbu minus025 minus154359Xuchang minus030 minus9677Liuan minus031 minus9811Zaozhuang minus031 minus9863Pingdingshan minus036 minus9727Huaibei minus050 minus9569Shangqiu minus051 minus9760Linyi minus053 minus9788Xuzhou minus053 minus9698Yancheng minus059 minus9080Rizhao minus060 minus9902


(2) Foreign contact intensity is related to a cityrsquos eco-nomic level the standardized network connectivity(Mi0) reects the intensity of a cityrsquos linkage to theentire basin system Mi0 is derived from the dierencebetween the standardized network connectivity valueof city i with the other cities and the value of the city iwithin itself Mi0 reects the strength of the externalconnection of city i Based on the classication ofnatural breakpoints (Jenks classication) the 26 citiesare divided into 5 grades which are shown in Table 2According to the statistical results of the four provincesGDP (Jiangsu Shandong Anhui and Henan) the 26cities are ranked in the order of Jiangsu ShandongHenan and Anhui e ve cities of Luohe KaifengHuainan Bozhou and Fuyang in Henan and Anhuiwere ranked the highest is is because the populationof the two cities generally interacts on a local scale

(3) Signicant dierence in connection intensity be-tween cities the network connectivity of 26 cities wassorted were obtained From the data it was foundthat the strength of the city-to-city relationshipvaries greatly ere are 225 sets of data between 0and 1 occupying 6923 of the total and 62 sets ofdata between 1 and 10 occupying 1908 of the totalMoreover 31 sets of data between 10 and 100accounted for 954 of the data while 16 sets of100ndash1000 accounting for 492

42 Urban Interaction Analysis According to the 26 citiesrsquocheck-in data and the userrsquos mobile track the urban in-teraction of the 26 cities can be analyzed

421 Classication of Inow Ratings e inow rating of thecity reects the total number of microblog entries from othercities signed in the city Taking city i as the research object thecheck-in data of city j in city i are collected and then the totalinow of city i is obtained According to the natural breakpointthe 26 cities are divided into 5 grades as shown in Table 3

From Table 3 we can see that the inow ratings of thecities have the following characteristics

(1) e dierence in inow level is large the largestnumber of check-ins to a city is 96000 while thesmallest city had less than 10000 check-ins

(2) e fourth city rank had the most of cities mostcities had between 10000 and 20000 check-ins

(3) e check-in data are unevenly distributed e dataare mainly distributed in the northeast southeastand east of the basin mainly in the Jiangsu andShandong provinces e amount of data in theAnhui and Henan provinces is relatively small

ndash02

ndash015

ndash01

ndash005

0

005

01

015

02

025

03

Luoh

eKa

ifeng

Hua

inan

Bozh

ouYa

ngzh

ouFu

yang

Xiny

ang

Lian

yung

ang

Jinin

gSu

zhou

Hua

iyin

Zhum

adia

nSu

qian

Hez

eZh

ouko

uBe

ngbu

Xuch

ang

Liua

nZa

ozhu

ang

Ping

ding

shan

Hua

ibei

Shan

gqiu

Liny

iXu

zhou

Yanc

heng

RiZh

aoValu

es o

f Mi0

(lowast10

3 )

City name

Figure 3 Relationship between urban network connectivity and urban hierarchy

Table 2 Classication of foreign contact intensity

Grade City Connectednessvalue

1 Luohe Kaifeng Huainan Bozhou minus4769 to 291452 Fuyang minus7407 to minus4769

3 Jining Lianyungang XinyangYangzhou Suzhou minus9080 to minus7407

4

RiZhao Heze Zaozhuang ZhoukouLiuan Zhumadian Linyi ShangqiuPingdingshan Xuzhou Huaiyin

Suqian Xuchang Huaibei YanchengSuzhou Yangzhou Xinyang

minus15436 to minus9080

5 Bengbu minus15436


422 Classification of Outflow Ratings e outflow ratingreflects the total number of users from a city that signed intoother cities Similarly to the inflow rating the data wereclassified according to the natural breakpoints and theresults shown in Table 4 were obtained

From Table 4 it can be seen that the outflow has thefollowing characteristics

(1) e difference in outflow level varies significantlyacross the basin the largest number of check-insfrom one city is more than 100000 while thesmallest city has less than 10000

(2) e fourth city rank is the largest in terms of outflowmost cities have between 10000 and 30000 check-ins in other cities

(3) e spatial distribution of the outflow data is uneventhe data are mainly distributed in the central andwestern regions of the basin Out of all the provincesthe outflow from the Jiangsu province is the largestShandong province is unevenly distributed andHenan and Anhui provinces have more homoge-neous outflow spatial distributions

423 Ratio of Inflow and Outflow e ratio of inflow andoutflow can directly reflect the flow direction of populationbetween cities and can also help to further analyze thedriving factors of population flow between citiese ratio ofinflow and outflow can reflect the attractiveness of a cityehigher the ratio the greater the attractiveness of the recipientcity or less attractive the city from which the people aremigrating According to natural breakpoint classificationthe 26 cities are divided into 5 grades (Table 5)

From Table 5 the following ratio of inflow and outflowcharacteristics can be determined

(1) e difference between the ratios of inflow andoutflow between cities is large the largest ratio is1244 times more than the smallest

(2) Most of the cities had inflowoutflow ratios below 1and these cities were distributed more evenly isshows that the inflow of most cities is less than that ofthe outflow

(3) e ratio of inflow and outflow in Luohe KaifengandHuainan are relatively large which indicates thatthe inflow and outflow data of these three cities aresignificantly different from those of the other cities inthe river basin

5 Discussion

In this paper we used microblog data to effectively modeland quantitatively express the spatial interaction of regionalcities Microblog data can not only reflect mobile in-formation of usersrsquo tracks but also reflect usersrsquo travel andactivity rules Does socioeconomic status affect usersrsquo traveland activity rules How does it affect In order to answerthese questions this paper analyzes the correlation amongurban microblog registration data urban population andGDP with the statistical data

51 -e Relationship between Urban Interaction and SocialEconomy Take the GDP and the urban population as theabscissa respectively and the total city check-in data as theordinates Figures 4 and 5 are obtained

From Figures 4 and 5 it can be concluded that there isno positive correlation among the total amount of urbancheck-in the economic links in the entity and the totalpopulation To a certain extent this reflects the degree ofurban interaction is a mechanism of the joint action of theeconomic level and population factors of the city e cityrsquoslargest inflow and local check-in data are the side portraitsof the cityrsquos attractiveness index which determines the levelof city interaction Cities with high interactive levels suchas Xuzhou and Yancheng have high inflows and localcheck-in volumes and their GDP is also higher in theprovinces Suqian Suzhou Zhoukou Pingdingshan HezeZhumadian and other cities are based on the local sign ofdata so their inflow is less and the interaction betweencities is not strong From the data of the Statistical Year-book of 2015 it is not difficult to find that the cities withstrong interactive ranks have higher GDP levels erefore

Table 4 Classification of outflow rating

Grade City Outflow rating1 Yangzhou 80001ndash1020872 Xinyang Bozhou Jining Lianyungang 50001ndash800003 Luohe Kaifeng Fuyang Linyi Huaiyin 30001ndash50000

4

Pingdingshan Xuchang ZhoukouZhumadian Shangqiu Heze SuzhouXuzhou Zaozhuang Suqian Huainan

Bengbu Luan Yancheng

10001ndash30000

5 Huaibei Rizhao 10000

Table 5 Ratio of inflow and outflow

Grade City Inflow andoutflow ratio

1 Luohe gt3002 Kaifeng Huainan 51ndash3003 Bozhou Yangzhou 6ndash50

4Xinyang Fuyang Suzhou Jining

Lianyungang Pingdingshan XuchangZhoukou Zhumadian Shangqiu

1ndash5

5Heze Huaibei Bengbu Lursquoan HuaiyinSuqian Xuzhou Zaozhuang Linyi Rizhao

Yanchenglt1

Table 3 Classification of inflow rating

Grade City Inflow rating1 Jining Xuzhou Bengbu Yancheng 60001ndash960002 Shangqiu Huaibei Huaiyin 40001ndash60000

3 Kaifeng Linyi LianyungangYangzhou Liuan 20001ndash40000

4Pingdingshan Xuchang Luohe XinyangZhoukou Fuyang Bozhou HuainanSuzhou Zaozhuang Suqian Rizhao

10001ndash20000

5 Heze Zhumadian 10000


if we want to improve the cityrsquos GDP we must strengthenthe interaction between cities

52 Microblog Data and Traditional Data As a class of bigdata microblog data contain userrsquos location informationwhich is dierent from traditional data such as highway dataand railway data e spatial structure of urban system is thetraditional eld of human geography research With thedevelopment of new urbanization and coordinated devel-opment of urban and rural areas the research of urbansystem structure is developed from the morphological

structure to social structure cultural structure ow struc-ture functional structure and other elds [33] ereforewe need new perspectives and methods to support the studyof the spatial structure of urban system

e key to analyze the characteristics of user movementtrajectories in specic areas is data acquisition Traditionalmethods of group analysis in specic regions have threesteps First dene the group in the region second conducta sample survey of the people in the region by using aquestionnaire third analyze the statistical data Traditionalsampling survey could not get accurate facts to express dataand always consumes large amount of time manpower and

0

50

100

150

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

200

250

300

350

400

City name

Xuzh

ou

Yanc

heng

Yang

zhou

Hez

e

Zaoz

huan

g

Lian

yung

ang

Xiny

ang

Zhum

adia

n

RiZh

ao

Fuya

ng

Liua

n

Luoh

e

Bozh

ouH

uain

an

Beng

bu

Suzh

ou

Kaife

ng

Shan

gqiu

Ping

ding

shan

Suqi

an

Zhou

kou

Xuch

ange

Hua

iyin

Liny

i

Jinin

g

Hua

ibei

Figure 4 Total attendance ordered by GDP

0

50

100

150

200

250

300

350

400

Zhou

kou

Liny

iFu

yang

Xuzh

ouH

eze

Shan

gqiu

Zhum

adia

nXi

nyan

gJin

ing

Yanc

heng

Liua

nSu

zhou

Suqi

anBo

zhou

Hua

iyin

Kaife

ngPi

ngdi

ngsh

anLi

anyu

ngan

gXu

chan

gYa

ngzh

ouZa

ozhu

ang

Beng

buRi

Zhao

Luoh

eH

uain

anH

uaib

ei

City name

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

Figure 5 Total attendance ordered by population


material resources Microblog data are the informationreleased by microblog users in social networks e contentof microblog data has a strong real-time reliability anddiversity which has the advantage that traditional data donot have In the case of scientific research it is more ac-curate and persuasive to further analyze the userrsquos in-formation without revealing the userrsquos personalinformation and privacy Microblog data and traditionaldata have their own advantages If we combine the twofactors to analyze user behavior the result of analysis willbe more reasonable e paper adopts this method whenanalyzing the correlation between microblog data andsocioeconomic statistics

e quality of data directly determines the accuracy ofdata analysis results e data acquired by microblogshould follow certain rules and should show its threecharacteristics of continuity integrity and validityerefore when accessing data we should pay attention tothe time and number of interface calls as well as the in-tegrity and repeatability checking of data e check-ininformation obtained in the study includes check-in citycode provincial code check-in longitude and latitudecoordinates check-in date and check-in time Getmicroblog data and establish a database corresponding tothe data field After entering the warehouse the missingdata and the noise data are removed to ensure the com-pleteness and uniformity of the data

53RiverBasinPerspective StudyofUrbanSpatial InteractionIn recent years reunderstanding of the relationship betweenman and nature has become a hot topic in various fieldsecity is an important habitat of human activities e spatialand temporal structure changes of urban system imply thedynamic interaction between human and nature Studyingthe spatial interaction of regional urban system and re-vealing the driving forces in the process of its change willhelp us to understand the temporal and spatial evolution ofthe urban system scientifically e above research canprovide the basis of space research for the sustainable de-velopment of human society and also provide a technicalroute reference for the spatial layout and optimization of thecities which has a certain theoretical and practicalsignificance

As a complete physical and geographical unit theRiver Basin crosses the administrative boundary and couldreflect the regional human-land relationship more natu-rally and truly e study of spatial interaction betweencities by the river basin excludes the human subjectiveconstraints which more objectively reflect the spatialrelationship characteristics of the regional urban systemerefore the river basin is an ideal area to explore theevolution rules of the relationship between mankind andland e Huaihe River Basin as the transition zone ofChinarsquos urban system has dual transitional nature andsocial elements [34] erefore the research takes theHuaihe River Basin as a case area to study the spatialrelationship of Chinarsquos regional urban system Its per-spective is unique

6 Conclusions

is paper obtains the user microblog information throughthe sina microblog open platform and studies the urbanspatial pattern and urban interaction by means of statisticalanalysis and spatial analysis is paper takes the Huaihebasin as the case area to verify it e main research con-clusion as follows

(1) e data interface provided by microblog platformcan study the urban spatial pattern e user tra-jectory of microblog data can explore the spatialrelationship of regional cities and data acquisitionand data quality evaluation can meet the researchrequirements

(2) Based on microblog data the spatial and temporalcharacteristics of urban system spatial pattern inHuaihe River Basin are analyzed from networkconnectivity and urban interaction e study foundthat the urban spatial relation in the Huaihe RiverBasin has the following characteristics the spatialdifference of urban size distribution is obvious ur-ban layout presents a stratified aggregation phe-nomenon and the high-grade cities lead the cityrsquosinteraction

As for the application of microblog data in urban re-search the current mainly focus on information text socialrelations and other aspects e research is mainly aboutevent detection and hot spot exploration e combinationof big data thinking and data mining technology will havemore research findings in the study of urban problems

Data Availability

e data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Acknowledgments

is work was supported by the Natural Science Foundationof China (Grant no 41701187) and project funded by ChinaPostdoctoral Science Foundation (Grant nos 2018M640813and 2018M633108)

References

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[2] Y Liu L Gong and Q Tong ldquoQuantifying the distance effectin spatial interactionsrdquo Acta Scientiarum Naturalium Uni-versitatis Pekinensis vol 50 no 3 pp 526ndash534 2014

[3] Y Chen ldquoZipfrsquos law hierarchical structure and shuffling-cards model for urban developmentrdquo Discrete Dynamics inNature and Society vol 2012 Article ID 480196 21 pages2012


[4] H Zhang L Zhu and S Xu ldquoModeling the city distributionsystem reliability with bayesian networks to identify influencefactorsrdquo Scientific Programming vol 2016 Article ID7109235 2016

[5] F Zhen B Wang and Y-x Chen ldquoChinarsquos city networkcharacteristics based on social network space an empiricalanalysis of sina microblogrdquo Acta Geographica Sinica vol 67no 8 pp 1031ndash1043 2012

[6] F Giorgio and S Gianluca ldquoHuman-mobility networkscountry income and labor productivityrdquo Network Sciencevol 3 no 3 pp 377ndash407 2015

[7] D Dandan Z Chunshan and Y Changdong ldquoSpatial-temporal characteristics and factors influencing commutingactivities of middle-class residents in Guangzhou city ChinardquoChinese Geographical Science vol 26 no 3 pp 410ndash428 2016

[8] W Wu Y-h Cao S-b Liang and W-d Cao ldquoe acces-sibility pattern of railway passenger transport network inChinardquo Geographical Research vol 28 no 5 pp 1389ndash14002009 in Chinese

[9] J-f Xue ldquoHierarchical structure and distribution pattern ofChinese urban system based on aviation networkrdquo ActaGeographica Sinica vol 27 no 1 pp 23ndash32 2008 in Chinese

[10] Z-f Jin ldquoOn structural properties of transnational urbannetwork based onmultinational enterprises network in Chinaas the case of link with South KoreardquoActa Geographica Sinicavol 29 no 9 pp 1670ndash1682 2010 in Chinese

[11] J Yin F Zhen and C-h Wang ldquoChinarsquos city networkpattern an empirical analysis based on financial enterpriseslayoutrdquo Economic Geography vol 31 no 5 pp 754ndash7592011 in Chinese

[12] Zndashw Sun Jndashl He and F-j Jun ldquoe accessibility and hi-erarchy of network cities in the global Internetrdquo EconomicGeography (Chinese) vol 30 no 9 pp 1449ndash1455 2010

[13] M Stephens and A Poorthuis ldquoFollow thy neighbor con-necting the social and the spatial networks on TwitterrdquoComputers Environment and Urban Systems vol 53 no 3pp 331ndash346 2014

[14] Y Takhteyev A Gruzd and B Wellman ldquoGeography oftwitter networksrdquo Social Networks vol 34 no 1 pp 73ndash812012

[15] Z Liu Y Jia and X Zhu ldquoDeployment strategy for car-sharing depots by clustering urban traffic big data based onaffinity propagationrdquo Scientific Programming vol 2018 Ar-ticle ID 3907513 9 pages 2018

[16] M M Rathore A Ahmad A Paul and S Rho ldquoUrbanplanning and building smart cities based on the Internet ofings using Big Data analyticsrdquo Computer Networksvol 101 pp 63ndash80 2016

[17] D Arribas-Bel K Kourtit P Nijkamp et al ldquoCyber citiessocial media as a tool for understanding citiesrdquo AppliedSpatial Analysis and Policy vol 8 no 3 pp 231ndash247 2015

[18] J Cinnamon and N Schuurman ldquoConfronting the data-divide in a time of spatial turns and volunteered geo-graphic informationrdquo GeoJournal vol 78 no 4 pp 657ndash6742012

[19] A Stefanidis A Crooks and J Radzikowski ldquoHarvestingambient geospatial information from social media feedsrdquoGeoJournal vol 78 no 2 pp 319ndash338 2011

[20] S Elwood ldquoGeographic information science emerging re-search on the societal implications of the geospatial webrdquoProgress in Human Geography vol 34 no 3 pp 349ndash3572009

[21] N Ratnasari E D Candra D H Saputra and A P PerdanaldquoUrban spatial pattern and interaction based on analysis of

nighttime remote sensing data and geo-social media in-formationrdquo IOP Conference Series Earth and EnvironmentalScience vol 47 article 012038 2016

[22] A Schulz E L Mencıa and B Schmidt ldquoA rapid-prototypingframework for extracting small-scale incident-related in-formation in microblogs application of multi-label classifi-cation on tweetsrdquo Information Systems vol 57 pp 88ndash1102015

[23] Z Jiang M Evans D Oliver et al ldquoIdentifying K PrimaryCorridors from urban bicycle GPS trajectories on a roadnetworkrdquo Information Systems vol 57 pp 142ndash159 2016

[24] L Mitchell M R Frank K D Harris P S Dodds andC M Danforth ldquoe geography of happiness connectingtwitter sentiment and expression demographics and objec-tive characteristics of placerdquo PLoS One vol 8 no 5 Article IDe64417 2013

[25] E Steiger R Westerholt B Resch and A Zipf ldquoTwitter as anindicator for whereabouts of people Correlating Twitter withUK census datardquo Computers Environment and Urban Sys-tems vol 54 pp 255ndash265 2015

[26] Y Shen and K Karimi ldquoUrban function connectivitycharacterisation of functional urban streets with social mediacheck-in datardquo Cities vol 55 pp 9ndash21 2016

[27] Z-wei Sui L Wu and Y Liu ldquoStudy on interactive networkamong Chinese cities based on the check-in datasetrdquo Geog-raphy and Geo-Information Science (Chinese) vol 29 no 6pp 1ndash5 2013

[28] G Wessel C Ziemkiewicz and E Sauda ldquoRevaluating urbanspace through tweets an analysis of Twitter-based mobilefood vendors and online communicationrdquo New Media andSociety vol 18 no 8 pp 1636ndash1656 2016

[29] M Truelove M Vasardani and S Winter ldquoTowards credi-bility of micro-blogs characterising witness accountsrdquo Geo-Journal vol 80 no 3 pp 1ndash21 2015

[30] J Capdevila M Arias and A Arratia ldquoGeoSRS a hybridsocial recommender system for geolocated datardquo InformationSystems vol 57 pp 111ndash128 2016

[31] D Kotzias T Lappas and D Gunopulos ldquoHome is whereyour friends are utilizing the social graph to locate twitterusers in a cityrdquo Information Systems vol 57 pp 77ndash87 2016

[32] Chinese Weibo 2018 in Chinese httpsweibocom[33] Z Wang X Ye J Lee X Chang H Liu and Q Li ldquoA spatial

econometric modeling of online social interactions usingmicroblogsrdquo Computers Environment and Urban Systemsvol 70 pp 53ndash58 2018

[34] Y Fan G Yu and Z He ldquoOrigin spatial pattern andevolution of urban system testing a hypothesis of ldquourbantreerdquordquo Habitat International vol 59 pp 60ndash70 2017

Scientific Programming 9

Computer Games Technology

International Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Advances in

FuzzySystems


Volume 2018


ReconfigurableComputing



Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

thinspArtificial Intelligence

Hindawiwwwhindawicom Volumethinsp2018


Civil EngineeringAdvances in


Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications


Hindawi

wwwhindawicom Volume 2018

Advances in

Multimedia


Biomedical Imaging



Engineering Mathematics


RoboticsJournal of



Computational Intelligence and Neuroscience


Mathematical Problems in Engineering

Modelling ampSimulationin EngineeringHindawiwwwhindawicom Volume 2018

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018


Human-ComputerInteraction

Advances in


Scientic Programming

Submit your manuscripts atwwwhindawicom

penetration of computers into various professions socialmedia data [17ndash19] have attracted the attention of geog-raphers due to its use in research [20] e use of socialmedia was one of the needs of urban communities [21] Asfor the typical spatial-temporal characteristics of socialmedia data many data mining research papers have an-alyzed information such as urban hot events [22]identifying urban Corridors [23] geography of happiness[24] whereabouts of people [25] urban function con-nectivity [26] urban spatial interaction [27] revaluatingurban space [28] and characterizing witness accounts[29] Data mining [30] provides new tools methods andideas for new geographical research improving the effi-ciency accuracy and precision of the analysis [31]

Based on the data of Sina Weibo microblog [32] thispaper established a thematic database of cities along theHuaihe River Basin China e spatial interaction of theregional urban system was analyzed from temporal andspatial characteristics of the data Finally combining thisdatabase with socioeconomic data experimental verificationand comparative analysis were carried out is paperprovides a reference for the exploration of the spatial re-lationship of regional urban systems and the drivingmechanism for spatial structure of urban system

2 Study Area

e Huaihe River Basin is located in the eastern region ofChina between the Yangtze River Basin and the YellowRiver Basin It flows through the four provinces of HenanAnhui Jiangsu and Shandong and covers a total area of27 times105 km2 e Huaihe River Basin has multipletransitional nature and society and connects coastal regionand inland region as well as being the economic in-tegration hub of the Yangtze River and Yellow Rivereconomic belts

e Huaihe River Basin has an enormous population of170 million people accounting for 123 percent of the totalpopulation of China e average population density is 611people per km2 which is 48 times of the average levelacross the country Given that the Huaihe River Basin is anatural geographical unit and does not coincide with theboundaries of the administrative units the study onlyselected the 26 cities whose governmental units are entirelyin the Huaihe River Basin for calculation and analysis(Figure 1)

3 Data Source and Processing

31 Sina Weibo Microblog e data gathered from the SinaWeibo microblog are the information released by microblogusers on the social network Compared with traditionalsocial survey data and economic social statistics the SinaWeibo microblog data have an unparalleled advantage in thefact that it performs well in real-time and is reliable anddiverse Currently information can be gathered from theSina Weibo microblog using web crawlers and the SinaWeibo microblog open platform API is study uses thelatter to obtain the relevant information for this research

32 Preprocessing the Sina Weibo Microblog First thegathered data were cropped to the latitude and longituderange of the survey region Each city administrative unit wasdivided into a 10 km-long grid the coordinates of the gridcenter were obtained and the WGS-84 geographic co-ordinate system was applied Next taking the longitude andlatitude of different cities as parameters user ID informationfrom these cities was obtained through the nearby_timelineinterface (an API interface) e user ID information in-cludes a source (through the authorized APPKey) longitudeand latitude as well as other data Using the user ID in-formation as the parameter the userrsquos historical data throughthe check-in interface (another API interface) were obtainede data returned by calling the API interface were in theJSON format In this study a Python script was written toachieve batch data acquisition e process of data acqui-sition is shown in Figure 2

33 -e Spatial Interaction of the Urban SystemMicroblog check-in data can reflect the spatial interactionof urban system this paper adopts two methods to analyzethese interactions e first is connectivity which is used toanalyze the intensity of communication between regionalcities the second is flow through which the userrsquos tra-jectory and the interactive state among cities can beanalyzed

331 Connectivity ismethod is based on the cityrsquos check-in data from which the network connectivity among citieswas analyzed which is described as follows

(1) Variable Unitization After variable unitization amatching matrix was established regarding the citycheck-in data using the following equation

Vij0 Vij1

111393625j1Vij

(1)

where Vij0 is a microblog user in city i who signedinto city j after unitization Vij1 represents amicroblog user of i city who signed in city j after dataacquisition and 1113936 Vij represents the sum of thecheck-in data of user form city i in city j

(2) Urban External Connection Index e urban ex-ternal connection index represents the differencebetween the total number of check-ins in other citiesand those in city i is is calculated using the fol-lowing equation

Ni0 111394425

j1Vij0minusVii0 (2)

where Ni0 is the external connection index of city iwhich reflects the check-in data (V) of city i in theother 25 cities Vii0 represents the check-in data ofcity i after unitization and Vij0 is the sum of check-in data of microblog users from city i who signed inother cities after unitization




Rij Vij0lowastVji0

Rij0 Rij lowast100

Max Rij( )

(3)



Figure 1 Study area

Urban grid division

Sina microblog






Mi0 111394425

j1Rij0minusRii0 (4)





Vi1 111394425

j1Vij (5)


Vi2 111394425

j1Vijprime (6)


R Vi1

Vi2 (7)

4 Results

















ndash02

ndash015

ndash01

ndash005

0

005

01

015

02

025

03

Luoh

eKa

ifeng

Hua

inan

Bozh

ouYa

ngzh

ouFu

yang

Xiny

ang

Lian

yung

ang

Jinin

gSu

zhou

Hua

iyin

Zhum

adia

nSu

qian

Hez

eZh

ouko

uBe

ngbu

Xuch

ang

Liua

nZa

ozhu

ang

Ping

ding

shan

Hua

ibei

Shan

gqiu

Liny

iXu

zhou

Yanc

heng

RiZh

aoValu

es o

f Mi0

(lowast10

3 )

City name






4




5 Bengbu minus15436












5 Discussion






4



10001ndash30000







1ndash5


Yanchenglt1





10001ndash20000







0

50

100

150

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

200

250

300

350

400

City name

Xuzh

ou

Yanc

heng

Yang

zhou

Hez

e

Zaoz

huan

g

Lian

yung

ang

Xiny

ang

Zhum

adia

n

RiZh

ao

Fuya

ng

Liua

n

Luoh

e

Bozh

ouH

uain

an

Beng

bu

Suzh

ou

Kaife

ng

Shan

gqiu

Ping

ding

shan

Suqi

an

Zhou

kou

Xuch

ange

Hua

iyin

Liny

i

Jinin

g

Hua

ibei


0

50

100

150

200

250

300

350

400

Zhou

kou

Liny

iFu

yang

Xuzh

ouH

eze

Shan

gqiu

Zhum

adia

nXi

nyan

gJin

ing

Yanc

heng

Liua

nSu

zhou

Suqi

anBo

zhou

Hua

iyin

Kaife

ngPi

ngdi

ngsh

anLi

anyu

ngan

gXu

chan

gYa

ngzh

ouZa

ozhu

ang

Beng

buRi

Zhao

Luoh

eH

uain

anH

uaib

ei

City name

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )







6 Conclusions





Data Availability




Acknowledgments


References











































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in






Rij Vij0lowastVji0

Rij0 Rij lowast100

Max Rij( )

(3)



Figure 1 Study area

Urban grid division

Sina microblog






Mi0 111394425

j1Rij0minusRii0 (4)





Vi1 111394425

j1Vij (5)


Vi2 111394425

j1Vijprime (6)


R Vi1

Vi2 (7)

4 Results

















ndash02

ndash015

ndash01

ndash005

0

005

01

015

02

025

03

Luoh

eKa

ifeng

Hua

inan

Bozh

ouYa

ngzh

ouFu

yang

Xiny

ang

Lian

yung

ang

Jinin

gSu

zhou

Hua

iyin

Zhum

adia

nSu

qian

Hez

eZh

ouko

uBe

ngbu

Xuch

ang

Liua

nZa

ozhu

ang

Ping

ding

shan

Hua

ibei

Shan

gqiu

Liny

iXu

zhou

Yanc

heng

RiZh

aoValu

es o

f Mi0

(lowast10

3 )

City name






4




5 Bengbu minus15436












5 Discussion






4



10001ndash30000







1ndash5


Yanchenglt1





10001ndash20000







0

50

100

150

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

200

250

300

350

400

City name

Xuzh

ou

Yanc

heng

Yang

zhou

Hez

e

Zaoz

huan

g

Lian

yung

ang

Xiny

ang

Zhum

adia

n

RiZh

ao

Fuya

ng

Liua

n

Luoh

e

Bozh

ouH

uain

an

Beng

bu

Suzh

ou

Kaife

ng

Shan

gqiu

Ping

ding

shan

Suqi

an

Zhou

kou

Xuch

ange

Hua

iyin

Liny

i

Jinin

g

Hua

ibei


0

50

100

150

200

250

300

350

400

Zhou

kou

Liny

iFu

yang

Xuzh

ouH

eze

Shan

gqiu

Zhum

adia

nXi

nyan

gJin

ing

Yanc

heng

Liua

nSu

zhou

Suqi

anBo

zhou

Hua

iyin

Kaife

ngPi

ngdi

ngsh

anLi

anyu

ngan

gXu

chan

gYa

ngzh

ouZa

ozhu

ang

Beng

buRi

Zhao

Luoh

eH

uain

anH

uaib

ei

City name

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )







6 Conclusions





Data Availability




Acknowledgments


References











































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in





Mi0 111394425

j1Rij0minusRii0 (4)





Vi1 111394425

j1Vij (5)


Vi2 111394425

j1Vijprime (6)


R Vi1

Vi2 (7)

4 Results

















ndash02

ndash015

ndash01

ndash005

0

005

01

015

02

025

03

Luoh

eKa

ifeng

Hua

inan

Bozh

ouYa

ngzh

ouFu

yang

Xiny

ang

Lian

yung

ang

Jinin

gSu

zhou

Hua

iyin

Zhum

adia

nSu

qian

Hez

eZh

ouko

uBe

ngbu

Xuch

ang

Liua

nZa

ozhu

ang

Ping

ding

shan

Hua

ibei

Shan

gqiu

Liny

iXu

zhou

Yanc

heng

RiZh

aoValu

es o

f Mi0

(lowast10

3 )

City name






4




5 Bengbu minus15436












5 Discussion






4



10001ndash30000







1ndash5


Yanchenglt1





10001ndash20000







0

50

100

150

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

200

250

300

350

400

City name

Xuzh

ou

Yanc

heng

Yang

zhou

Hez

e

Zaoz

huan

g

Lian

yung

ang

Xiny

ang

Zhum

adia

n

RiZh

ao

Fuya

ng

Liua

n

Luoh

e

Bozh

ouH

uain

an

Beng

bu

Suzh

ou

Kaife

ng

Shan

gqiu

Ping

ding

shan

Suqi

an

Zhou

kou

Xuch

ange

Hua

iyin

Liny

i

Jinin

g

Hua

ibei


0

50

100

150

200

250

300

350

400

Zhou

kou

Liny

iFu

yang

Xuzh

ouH

eze

Shan

gqiu

Zhum

adia

nXi

nyan

gJin

ing

Yanc

heng

Liua

nSu

zhou

Suqi

anBo

zhou

Hua

iyin

Kaife

ngPi

ngdi

ngsh

anLi

anyu

ngan

gXu

chan

gYa

ngzh

ouZa

ozhu

ang

Beng

buRi

Zhao

Luoh

eH

uain

anH

uaib

ei

City name

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )







6 Conclusions





Data Availability




Acknowledgments


References











































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in












ndash02

ndash015

ndash01

ndash005

0

005

01

015

02

025

03

Luoh

eKa

ifeng

Hua

inan

Bozh

ouYa

ngzh

ouFu

yang

Xiny

ang

Lian

yung

ang

Jinin

gSu

zhou

Hua

iyin

Zhum

adia

nSu

qian

Hez

eZh

ouko

uBe

ngbu

Xuch

ang

Liua

nZa

ozhu

ang

Ping

ding

shan

Hua

ibei

Shan

gqiu

Liny

iXu

zhou

Yanc

heng

RiZh

aoValu

es o

f Mi0

(lowast10

3 )

City name






4




5 Bengbu minus15436












5 Discussion






4



10001ndash30000







1ndash5


Yanchenglt1





10001ndash20000







0

50

100

150

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

200

250

300

350

400

City name

Xuzh

ou

Yanc

heng

Yang

zhou

Hez

e

Zaoz

huan

g

Lian

yung

ang

Xiny

ang

Zhum

adia

n

RiZh

ao

Fuya

ng

Liua

n

Luoh

e

Bozh

ouH

uain

an

Beng

bu

Suzh

ou

Kaife

ng

Shan

gqiu

Ping

ding

shan

Suqi

an

Zhou

kou

Xuch

ange

Hua

iyin

Liny

i

Jinin

g

Hua

ibei


0

50

100

150

200

250

300

350

400

Zhou

kou

Liny

iFu

yang

Xuzh

ouH

eze

Shan

gqiu

Zhum

adia

nXi

nyan

gJin

ing

Yanc

heng

Liua

nSu

zhou

Suqi

anBo

zhou

Hua

iyin

Kaife

ngPi

ngdi

ngsh

anLi

anyu

ngan

gXu

chan

gYa

ngzh

ouZa

ozhu

ang

Beng

buRi

Zhao

Luoh

eH

uain

anH

uaib

ei

City name

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )







6 Conclusions





Data Availability




Acknowledgments


References











































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in














5 Discussion






4



10001ndash30000







1ndash5


Yanchenglt1





10001ndash20000







0

50

100

150

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

200

250

300

350

400

City name

Xuzh

ou

Yanc

heng

Yang

zhou

Hez

e

Zaoz

huan

g

Lian

yung

ang

Xiny

ang

Zhum

adia

n

RiZh

ao

Fuya

ng

Liua

n

Luoh

e

Bozh

ouH

uain

an

Beng

bu

Suzh

ou

Kaife

ng

Shan

gqiu

Ping

ding

shan

Suqi

an

Zhou

kou

Xuch

ange

Hua

iyin

Liny

i

Jinin

g

Hua

ibei


0

50

100

150

200

250

300

350

400

Zhou

kou

Liny

iFu

yang

Xuzh

ouH

eze

Shan

gqiu

Zhum

adia

nXi

nyan

gJin

ing

Yanc

heng

Liua

nSu

zhou

Suqi

anBo

zhou

Hua

iyin

Kaife

ngPi

ngdi

ngsh

anLi

anyu

ngan

gXu

chan

gYa

ngzh

ouZa

ozhu

ang

Beng

buRi

Zhao

Luoh

eH

uain

anH

uaib

ei

City name

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )







6 Conclusions





Data Availability




Acknowledgments


References











































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in








0

50

100

150

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )

200

250

300

350

400

City name

Xuzh

ou

Yanc

heng

Yang

zhou

Hez

e

Zaoz

huan

g

Lian

yung

ang

Xiny

ang

Zhum

adia

n

RiZh

ao

Fuya

ng

Liua

n

Luoh

e

Bozh

ouH

uain

an

Beng

bu

Suzh

ou

Kaife

ng

Shan

gqiu

Ping

ding

shan

Suqi

an

Zhou

kou

Xuch

ange

Hua

iyin

Liny

i

Jinin

g

Hua

ibei


0

50

100

150

200

250

300

350

400

Zhou

kou

Liny

iFu

yang

Xuzh

ouH

eze

Shan

gqiu

Zhum

adia

nXi

nyan

gJin

ing

Yanc

heng

Liua

nSu

zhou

Suqi

anBo

zhou

Hua

iyin

Kaife

ngPi

ngdi

ngsh

anLi

anyu

ngan

gXu

chan

gYa

ngzh

ouZa

ozhu

ang

Beng

buRi

Zhao

Luoh

eH

uain

anH

uaib

ei

City name

Num

ber o

f tot

al ci

ty ch

eck-

ins (

lowast10

3 )







6 Conclusions





Data Availability




Acknowledgments


References











































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in








6 Conclusions





Data Availability




Acknowledgments


References











































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in










































Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in









Advances in

FuzzySystems


Volume 2018













Journal of

Journal of



Hindawi


Advances in

Multimedia


Biomedical Imaging





RoboticsJournal of









Volume 2018



Advances in




Documents

Study of Urban System Spatial Interaction Based on