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Evaluating cities' vitality and identifying ghost cities in China with
emerging geographical data
YingLong,AssociateProfessorSchoolofArchitecture,TsinghuaUniversity,China
November14,2016
IncollaborationwithXiaobin Jin,WeiSun,Yuyin Lu,Xuhong Yang
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RapidurbanexpansioninChinaduringlastdecades(around30%residentialdevelopments)
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Search “Ghost Cities/鬼城” at Baidu
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The existing rankings of ghost cities in China
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Housing vacancy rate has been a national secret in each city.
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TheBeijingCityLab(BCL)isaresearchnetwork,dedicatedtostudying,butnotlimitedto, China’scapitalBeijing.TheLabfocusesonemployinginterdisciplinarymethodstoquantifyurbandynamics,generatingnewinsightsforurbanplanningandgovernance,andultimatelyproducingthescienceofcitiesrequiredforsustainableurbandevelopment.Thelab'scurrentmixofplanners,architects,geographers,economists,andpolicyanalystslendsuniqueresearchstrength.
http://www.beijingcitylab.com
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MethodologyIdentifyingghostcitiesthroughthelensofthevitalityofresidentialdevelopments
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• KevinLynchbelievesthattheprimarycriterioninthequalityassessmentofurbanspaceformisthevitality,whichisdefinedasasettlement(thedimensionurbanmorphology)thatsupportsthevitalfunctions(thedimensionurbanfunction)andthebiologicalrequirementsandcapabilitiesofhumanbeings(thedimensionurbansociety),and howtoprotectthecontinuationofthespecies(Lynch,1984).
Three components of urban vitality
Urbanform Urbanfunction Urbanactivity
Urbanvitality
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• Urbanform=Roadjunctiondensity(J)• Urbanfunction=Pointsofinterest(POIs)density(P)• Urbanactivity=LBSdensity(L)• Urbanvitality(V)= ln (J*P*L)
Calculating urban vitality for each place
Roadjunction Pointsofinterest LBS
Urbanvitality
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Ghost cities are always associated with new developments
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No urban fabric/form on urbanized/developed areas
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No urban function on existing urban form
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No urban activities in functioned urban areas
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• G:Thedegreeonacitybeingaghostcity
• Thedegreetowhichacitybelongstoaghostcityisrelatedtovitalityinnewurbanareasandthedifferenceinvitalitybetweenoldandnewurbanareas.Thelargerthedifferenceandthelowerthevitalityinthenewresidentialprojects,themorelikelythecitytobeaghostcity.
Identifying ghost cities via aggregating the vitality of residential projects
G = 1 / (Vnew/Vold * Vnew)
Theaveragevitalityofresidentialdevelopmentsinnewurbanareas(Vnew)andresidentialdevelopmentsinoldurbanareas(Vold)canbecalculatedforeachcitybyoverlayingresidentialtransactionswiththeadministrativeboundariesofcities.
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Data used for this study
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• Thereare653Chinesecitiesin2014.• OnthebasisoftheChineseadministrativesystem,therearemainlyfivelevelsofcitiesclassifiedinthisway,including:• municipalities(MD)directlyledbythenation(with4cities,tier1)
• sub-provincialcities(SPC)(with15cities,tier2)
• otherprovincialcities(OPCC)(with17cities,tier3)
• prefecture-levelcities(PLC)(with250cities,tier4)
• county-levelcities(CLC)(with367cities,tier5)
The Chinese city system
AdministrativeareasofChinesecities
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• Weassumethattheformationofghostcitiesisgenerallyduetothenewlydevelopedareas,thusmakingitnecessarytodefinetherelevantboundaries.
Urban areas in 2000 for differentiating new and old developments
Theurbanareasareinterpretedfromremotesensingimages,andtheoverallaccuracyis94.3%.Thereare9,128patcheswithin33,148km2 intotal,andthemeanpatchsizeis3.6km2.
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Residential projects as the core data for identifying ghost cities
Availableatthegovernmentalwebsite
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• Intotal,thereare535,523residentialprojectswithinatotalareaof7770.2km2from2002-2013• EachprojectisstoredasapointinGIS
Residential projects as the core data for identifying ghost cities
Year CountsumType
AreasuminhaType
Market# Social# Marketinha Socialinha
2002 2,576 2,182 394 4,042.1 3,726.4 315.7
2003 3,194 2,887 307 6,149.2 5,715.5 433.7
2004 10,840 3,965 6,875 13,839.8 11,641.6 2,198.2
2005 7,321 2,933 4,388 10,435.4 8,755.3 1,680.1
2006 7,880 3,897 3,983 10,270.5 9,232.9 1,037.7
2007 48,910 32,924 15,986 65,496.5 54,676.9 10,819.6
2008 43,545 29,682 13,863 60,112.3 48,901.4 11,210.9
2009 73,678 54,849 18,829 85,472.7 71,338.1 14,134.6
2010 87,017 78,234 8,783 127,848.2 109,779.3 18,068.9
2011 86,999 77,888 9,111 133,875.5 108,372.4 25,503.1
2012 72,618 62,861 9,757 116,444.5 87,714.5 28,730.0
2013 90,945 87,141 3,804 143,030.6 136,326.1 6,704.5
Sum 535,523 439,443 96,080 777,017.2 656,180.2 120,837.0
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Road junctions in 2014
8.24millionroadjunctionsforthewholeChina
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Points of interest in 2014
10.6millionPOIsforthewholeChina
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• Wehavegathered1km*1kmLBSdatafromBaidu,oneofthelargestinternetcompaniesinChina,andthedatacoverawholeweekinJulyof2015• Consideringthedatacoverofabout800millionusersinChina,thedatacanwellreflecthumanactivitiesinChina
LBS data in 2015
LBSdensityof asmallareainJiangsuprovince
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Urban form dimension
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Urban function dimension
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Urban activity dimension
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Urban vitality reflecting the previous three components
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We find the average vitality of residential projects in new
urban areas is only 8.8% of that in old urban
areas, denoting the potential existence of ghost cities in newly developed areas in Chinese cities.
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• 1MD=citiesdirectlyledbythenation(with4cities,tier1),2SPC=sub-provincialcities(with15cities,tier2),3OPCC =otherprovincialcities(with17cities,tier3),4PLC=prefecture-levelcities(with250cities,tier4),and5CLC=county-levelcities,and6OthertownsmeansthattheprojectsarebeyondtheadministrativeboundariesofcitiesinChina
The urban vitality and its components by each level of cities
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• TheresultsindicatethatthecitiesinthemiddleregionofChinahavethegreatestvitalityvaluesandthoseinnortheasternChinaandwesternChinaarewithlowervalues.
The average vitality of residential projects (RPs) in new urban areas for all Chinese cities
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Variable Vitality Junctions POIs LBSsURBAN 0.126 0.352 0.307 0.286YEAR 0.008 0.003 0.040 0.015
CENTER -0.025 -0.103 -0.056 -0.089LEVEL -0.132 -0.353 -0.057 -0.336AREA -0.041 -0.051 -0.082 -0.064
AdjustedR2 0.045 0.353 0.123 0.274
The regression model for residential project vitality suggests that residential projects in old urban areas, being close to the city center in an administratively higher tier city, with a smaller development size and more recent development, positively contribute to a higher level of vitality.
Note: All variables are significant at the 0.05 level. All coefficients have been normalized in the linear regression process. When we usethe logarithm value of vitality as the dependent variable, the adjusted R2 and the normalized coefficients do not change much.
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The ghost index (G) for all Chinese cities
Thirty ghost cities are identified accordingto the G indicator evaluation results, andmost of these cities are distributing innorth eastern China, particularly inShandong and Anhui provinces.
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We have also benchmarked our identified ghost cities against existing rankings, the Baidu search engine, and night-time light images.
Although we admit that ghost cities may exist in the particular urbanizing phase in China, and some cities that are ghost cities now may be well developed in future, this study provides a thorough evaluation on the ghost city condition in China.
Our profiling results illustrate a big picture for Chinese past residential developments and then the ghost cities.
This may shed light on policy implications for Chinese urban development.
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• Borrowthetheoryofurbanvitalitytoidentifyandevaluateghostcities• Threecomponents:form,functionandactivity• LBSshouldnotbetheonlydatafortheghostcitystudy
• Evaluateeachcityinabottom-upmannerbyusingubiquitousandincreasinglyavailablebig/opendatafromofficialwebsites,commercialinternetcompaniesandsocialnetworks• Both“ghost”leveland“ghost”sizeinourstudy
• Developtheoreticalmodelstoexplainthecontributingfactorsonvitalityattheresidentialprojectlevel• ProvidingthepossibilityforproposingnecessarypoliciestofightagainstghostcitiesinmodernChina
• TheproposedghostindicatorG considersnotonlythevitalityinnewurbanareas,butalsothegapbetweennewandoldurbanareas• Makingitpossibletoovercomethegapofurbanform,functionandinformationcommunicationtechnology(ICT)penetrationacrossvariouscities
Highlights of this study
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• Theaccesstotherealboundaryofeachresidentialcommunitymayleadtomoreobjectiveevaluationandidentificationresults.• Theinformalresidentialdevelopmentsalsocontributetotheformationofghostcities.Thisshouldbeaddressedinournextstudyaswell.
Potential biases of this study
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References
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Thanks
[email protected]
ThisworkissupportedbygrantsfromtheNationalNaturalScienceFoundationofChina(No.41340016and51408039).TheauthorswouldliketothankMr/MsXuefeng HuangandJinyuan Xie fortheirassistanceon
dataprocessing.OurthanksarealsogiventoMsTraceyTaylorforeditingthelanguageofthispaper.