bcl城市实验室研究成果工作

UnderstandingBeijing’sMovingUrbanFringethroughaSpatialEquilibriumModel1Keywords: ComputableGeneralEquilibrium,SpatialModelling,UrbanFringe,UrbanForm,Policy ThegrowthofthemaincityofBeijingischaracterisedbyapancakelikeexpansion,from100km2in1950to1210km2in2005insuccessivewaves.Theapproachtofutureurbanexpansionwillrequirecarefulconsideration,aseconomic,environmentalandsocialconflictsattheurbanfringehaveintensified.Twosuccessivegreenbeltshavebeendesignatedtocontainexpansionandengendermorecompactgrowth.However,thefirstgreenbelthasnotbeenachievedsuccessfullyandmanyareasdesignatedasthesecondgreenbeltisfacingimplementationchallenges.Thispaperbuildsonexistingresearchintogreenbeltpolicyimplementationandinvestigatestheimpactsofalternativeurbangrowthboundaryproposalsunderasystematicmodellingframework.Itreviewsthetheoreticalinsightsintogrowthattheurbanfringe,andputsforwardamethodologythatlinksdevelopmentattheurbanfringetothefunctioningoftheentiremetropolitanarea.Itoutlinessixalternativedevelopmentscenariosthatencompasstheexistingplanningproposalsfortheurbanfringe:trendgrowth,densification,stringentgreenbelt,loosegreenbelt,skewedandgreenwedge.Weuseaprototypespatialequilibriummodelwhichsimulatestheinteractionsamonghouseholds,businesses,urbanlanduseandtransporttoquantifytheperformanceofthedevelopmentscenariosintermsofproductioncosts,consumerwelfare,wages,floorspacerents,andcommutingtimes.Theanalysessuggestthatthephysicalformsoffringeareadevelopmentdosignificantlyaffecttheeconomicperformanceofthewholemunicipality.Alternativeproposals,includingthosethathaverarelyconsideredinthepast,shouldbeinvestigatedcarefullyinthislight,inconjunctionwithrelatedstudiesonsocialandenvironmentalimpacts.BackgroundandmotivationsoftheUrbanformpoliciescanhaveimportantimpactsonlocalenvironmentalquality,economy,andsocialequity(Echeniqueetal.(2012)).Afringeofacityisatransitionalzonewhereurbanlanduseandrurallandusemixandclash.Typically,thisistheareawherethebulkofnewconstructiontakesplace,anditthereforeplaysacrucialroleinshapingthecity.Therehavebeenmanyattemptstocontrolthedevelopmentoftheurbanfringeforavarietyofpolicyobjectives.Thereisawidevarietyofplanningstrategies.Forexample,intheUKgreenbeltpolicieshaveexistedformorethan60yearstocontroltheribbondevelopmentandsprawlofLondonandmanyothercities(Hall,1973);urbangrowthboundarypolicieshavealongtraditionintheUnitedStates(Staley,1999,Jun,Thishistoricperspectiveof50-60yearsofpastimplementationsisanenormousresourceforplannersinfasturbanising,emergingeconomies.Ithasthepotentialtomakethecomplexplanningtaskssomewhateasierinthefastinggrowingcitiestoday.However,plannersintheemergingeconomiesareoftendiscouragedbythefactthatpoliciesfromthedevelopedcountrycitiessuchasthegreenbeltpolicydonotseemtoleadtothesamehistoricoutcomes(e.g.plannedgreenbeltsdonotseemtowork).Furthermore,evenifthepolicieshaveachievedthesameoutcomestoday(e.g.thegreenbeltpolicyhascontainedurbangrowth),howcouldwebeconfidentthatthesameoutcomeinanentirelydifferenteraandsocio-economiccontextisbeneficialtothecity?1Thisisafirstdraftwithverypreliminarymodelresults.Themodelresultswillbeupdatedinthesubsequentversionofthepaper.1Inthisregard,Beijingisatypicalexampleofcitiesencounteringsuchchallenges.Inthepast60years,withrapideconomicgrowth,theannualpopulationgrowthrateinBeijinghasreached3.8%andoverallpopulationhasreached19.6millionin2011(NationalBureauofStatisticsofChina,(2011)).Thebuilt-upareahasbeenexpandingrapidlyfrom100.2km2in1950to1210.2km2in2005(Aietal.(2008))followingaconcentricpatternofexpansion(Figure1).Figure1.Expansionofbuilt-upareaofBeijing1951-2005(Source:WuAlthoughinBeijingMasterPlan2004-2020itstatesclearlythatBeijingshouldabandonthemono-centricsprawlpatternandmakeatransitionintoapolycentricpattern,thispancakelikeexpansionhasnotshownanysignsofabatingsincethispolicywaslaunched.Inordertotacklethesprawlpattern,twosuccessivegreenbeltpolicieshavebeenputforward(BeijingMunicipalGovernment,(1994),(2003)).TheFirstBeijingGreenbeltpolicywasintroducedin1994.125km2ofgreenareasaroundthefourthring-roadofBeijingweredesignatedastheFirstBeijingGreenbelt.However,theurbanexpansioninthemidtolate1990sspreadacrossthisdesignatedgreenbeltland.Thetotalbuilt-upareawithinthedesignatedFirstGreenbeltincreasedfrom33.3%in1993to49%in2005,withacorrespondingdecreaseinthegreenareafrom66.7%to44.3%(HanandLong(2010)).TheSecondBeijingGreenbeltwasintroducedin2003withadesignationof1556km2ofgreenareasbetweenthefifthandsixthring-roads.However,newconstructionwithinthedesignatedareaappearstocontinue.Thegreenbeltasastandardinstrumentforcontrollingfringegrowthinsomanycitiesinthedevelopedcountries,includingLondon,Paris,Ottawa,Ontario,Seoul,Frankfurt,Viennaandsoon,seemsparticularlydifficulttoachieveinBeijing(Figure2).Figure2.Greenbeltboundaries(drawnbytheItgoeswithoutsayingthatgreenbeltdesignationisnottheonlyplanninginstrumenttocontrolurbangrowth.TheplannersinBeijinghaveexploredawidevarietyofalternativepolices,forexampleWu(2010)hasidentifiedtheTokyoapproach(i.e.densificationofthemaincity)andtheParisapproach(i.e.largeandintensivesuburbannewtowns)asalternativestrategiestothegreenbeltproposal.EvaluateimpactsofurbanformpoliciesonthewholePreferredbymanyphysicalplanners,Beijing’sgreenbeltpolicyisamainstayofgovernmentpolicy.Currentanalysesofthispolicyemphasisethedifficultiesofputtingitintopractice:governmentisfacingchallengeofprovidingdisplacedfarmersadequatesocialwelfare(Fu(2010);Ji(2011));itisbecomingextraordinarilyexpensivetoremovevillagesandcompensatefarmers(Fu(2010));itisextremelyhardtocontrolthelandusewithinthegreenbelt,forexample,therewerecriticismsthatlandwithinthegreenbeltwasactuallyusedforluxuryvillaswhicharedevelopedunderthepretextofgolfcourses(Tan(2008);Du(2011));Thehousingestatestoaccommodatedisplacedfarmersarefarfromadequate(Tan(2008)).However,thesecriticismstendtofocusontheimmediateissuesthatarehamperingtheprogressofthegreenbeltimplementation,andtherearerelativelyfewstudiesthatrelatetheroleofthegreenbeltandtheoverallimpactofurbangrowthinBeijing.Ofcourse,theimpactsofagreenbeltarefeltkeenlybytheresidentsandworkerswithinthearea.Theirhomes,livelihood,andfutureworkprospectswillallchange.Whatislessdiscussedisthefactthattheremaybeevengreaterconsequencesonthegrowth,prosperityandwelfareofthewholemunicipality.Thereareseveralreasonsforexaminingthewiderimpacts.First,greenbeltlimitsthelandsupplyofthemaincity–itactsasanurbangrowthboundaryatatimewhenthecityisfacinghighpressuresofpopulationandbusinessgrowth,andhugedemandforhousing.Secondly,forthosepeoplewholivebeyondthegreenbelt,commutingtimeincreasesiftheystillworkinthecitycentre.Congestionhappensfrequentlyonroadsconnectingthecitycentreandthetownsbeyondthegreenbelt.Additionally,noneoftheexistingcritiquesanalysedeconomicoutputsofagreenbeltinaquantitativeassessment,suchaslandvalue,wageandproductioncostandconsumerutility.Comparisonofwelfareswithandwithoutgreenbeltisdescriptive.Amenityvalueofagreenbeltisinvestigatedinaqualitativeway.TherehasbeennomathematicalrelationestablishedbetweenBeijing’sgreenbeltpolicyandindicesregardingeconomicefficiency.Thereforeitisnecessarytoevaluateexistingpoliciescomprehensivelywithinabroadercontextinaquantitativewayandthismethodologyshouldalsobeappliedtoevaluateotherurbanfringedevelopmentpolicies.ModellingurbanfringedevelopmentUrbanmodelsareoftenusedtopredictpolicyperformancesinurbanplanningindevelopedcountries.Someofthemprovideinsightsintothecomplexinteractionsinthedevelopmentprocessandhelptoevaluatelong-termeffectsofpolicies.Inparticular,therehavebeenmanystudiestomodelthedevelopmentoftheurbanfringe.Someexistingresearchfocusedontheimpactsofgreenbeltonfringelandprices.LeeandLinneman(1998)analysedtheamenityeffectsofgreenbeltovertimeonlandmarketofSeoulandalsoexaminedtheimpactoflandpricesduetolandsupplyrestrictionbyusinganempiricalhedonicmodel.Knaap(1985)measuredtheeffectsofPortlandgreenbeltonlandpricebyintroducingapartialequilibriummodel.Thismodeldescribestheeffectsofagreenbeltonurbanandnonurbanlandvalues,thedemarcationofwherezoningchangesandfutureurbandevelopmentmaytakeplace(Knaap(1985)).Bothmodelsemphasisedamenityvalueofgreenbeltanditsimpactonlandvalue;however,bothstaticmodelsignoredhumanbehaviourrespondingtothefringecontrolpolicy.LeeandFujita(LeeandFujita(1997))examinedtherelationshipsbetweenthetypesofamenitiesgeneratedbyagreenbeltandtheefficientlocationofagreenbeltbyusingHerbert-Stevensmodel(HerbertandStevens(1960)).Bymodellingbehaviourandpurposeofplayers,theauthorcalculatetheoptimalprovisionofagreenbelt,subjecttoutility,landsupplyandpopulationconstraint.Thismono-centricmodelwasapartialequilibriummodelandhadnotshowneconomicinteractionsgeographically.Besidesmono-centricpartialequilibriummodels,researchersdevelopedmulti-centricspatialequilibriummodelstodescribeurbanmovingboundaries,focusingontherelationshipsbetweenurbaneconomy,activitylocationandspatialcosts.Anasdevelopedanashecalledgeneralequilibriummodelin1999(AnasandXu(1999))totestpolicyperformanceonurbanform:willcongestiontollsleadtoadispersedorcentralisedpattern?Thismodelanalysesconsumersandproducers’responsesoflocationchoicetotollsbasedontheprincipleofminimisingcostsandmaximisingutility.Inanequilibriumcondition,wages,pricesofproductsandrentcanbecomputedandcomparedindifferentscenarios.Modelresultsshowthatcentralisingeffectsdominateondispersingeffectsoftolls.Italsoimpliesthatcongestiontollscanshapecompacturbanpatternefficientlyandaffectthewholeurbaneconomicsystem.In2007AnasdevelopedthegeneralequilibriummodelintoRELU-TRANmodeltoexplainthebehaviourofsupply,demandandpriceinacityareawithseveralormanyinteractingmarkets(Anas,Liu(2007)).Basedonthegeneralequilibriummodel,AnasandRheewroteuptwoarticles(AnasandRhee(2006);AnasandRhee(2007))tocompareperformanceofstringenturbanfringegrowthcontrolversuscongestiontolls.Botharticlescastdoubtsonstringentpoliciesofcontrollingurbanfringesprawl.AnasandRhee(2006)juxtaposedcongestiontollsandurbanboundariesastwoalternativepoliciesforeliminatingsprawl.Theygotconclusionthatindispersedcityaboundaryofanystringencyisabsolutelyharmful.AnasandRhee(2007)establishedadual-centricprototypemodelandclaimedthatifthereiscross-commutingbetweencityandsuburb,congestiontollscanshrinkcitysizebyrelocatingeconomicactivitieswhileboundariesofanystringencycanbeinefficient.Asshowninthestory,notonlylandpriceandplayers’behaviour,butalsoactivitieslocationandurbaneconomyinresponsetothefringelandusepoliciescanallbemodelledinaquantitativeway.Modelshaveinvolvedfrompartialequilibriumtogeneralequilibrium,sothatimpactsofapolicyoneveryaspectmentionedabovecouldbetestedInthispaper,wewillusearecursivespatialequilibriummodel(RSEModel)(Jin,Echenique,Hargreaves,(2013))totesttheperformanceofurbanfringelandusepoliciesofBeijing.ThismodelisbeingdevelopedinMartinCentreforArchitecturalandUrbanStudies,UniversityofCambridgeandsharessomesimilarcharacteristicswithAnas’model.Moreover,itfillsthegapofexistingmodels:itcannotonlyexamineimpactsofpoliciesoneconomicindicesinindividualtimeperiod,butalsoexaminedynamicsofpeopleandinvestmentinresponsetoeconomicindices.Datarequiredfromthismodelismoreapproachable,andmostcitiesalreadyhavethem,forexample,censusandinput-outputtable.DetailsofthismodelcouldbefoundinJin,Echenique,Hargreaves(2013).AimsoftheWeproposeinthispaperagenericmodellingmethodologythathelpstheeconomicandphysicalplannerstounderstandandquantifythemaineffectsofurbanfringedevelopmentandcontrolpolicies.Thecomputermodelthatunderliesthismethodologycanincorporatethesocio-economicandinfrastructurecontextofthecitywhencalculatingthemaincostsandbenefitsofthealternativedevelopmentstrategies.Thismeansthatitispossibletoassesstheplanningstrategiesmorepreciselyintermsoftheplannedlocationandintensityofdevelopment–notonlybetweenthemainarchetypalalternatives(suchastheTokyo,ParisandLondonmodels),butalsovariantswithineachmainalternative.Themodellinginthispaperwillbefocusedontheeconomicperformanceoftheplanningstrategies,anditcanbeextendedinfutureworktocoversocialandenvironmentalperformance.Section2proposesaspatialequilibriummodeltotestspatialoptionsforcities,inordertoquantifytheimpactsofpolicyleversonurbanactivities.Section3appliesthemodeltothecaseofBeijingandprovidesquantitativemodellingresults.Thenmodelsimulationresultsarecomparedpair-wiseinsection4.Inthisway,thestrengthsandweaknessesofeachpolicyoptionareoutlinedsothroughquantifiedevidence.Section5presentspreliminaryconclusionsoftheresearch.Inthissection,wewillproposeagenericframeworktopredictandcompareeconomicperformanceoflargescaleurbanlandusedevelopmentinitiatives,includingboththevariantsoftheGreenbeltandalternativestrategies.Wefirstoutlinethemodelstructure,andthenexplainthecomponentsofthemodel.ModelPolicy SpatialEquilibrium Policy •Transport •TransportLanduse Transport

SocialResourcefromlanduseandtransportFigure3.Modelstructure(drawnbytheAssummarisedinfigure3,firstly,scenariosareidentifiedtoexplorethepolicytrendandalternativeurbanforms.Thenthespatialequilibriummodelisappliedtoforecastthelikelylocationalandtravelbehaviourofhouseholdsandfirmsinresponsetotheintroductionofpolicies(Echeniqueetal.(2010)).Finally,modellingoutcomesareassessedthrougheconomicproductivityandhouseholdutility.Thespatialequilibriummodelfocusesonthemacrolevelsimulationandexploresinteractionsbetweenurbanactivities,transportdemand,landsupplyandinfrastructuresupply.Onthedemandside,urbanactivitiesgeneratetransportdemandsothatpeopleandgoodscanmovewithinandbetweendifferentzones,whichalsoaffecturbanactivities.Onthesupplyside,landsupplyincorporateswithtransportandinfrastructuresupply.Thereareinteractionslinkingsupplysideanddemandsideuntilanequilibriumreaches.Traditionally,tripsgeneratedbylandpatternwillbesubstitutedintothetransportmodelwhiletransportmodelwillgenerateupdatedtraveltime,costanddistancewhichwillbefeedbacksforlandusemodel.Inthisway,afeedbackloopisformed.However,thispaperonlyfocusesonexaminingthelandusesideofspatialequilibriumandtransportmodelisusedasanexogenousinput.Tripsgeneratedfromlandusemodelwillnotbeusedasendogenousinputsfortransportmodel.Thedasharrowlinesbetweenthetwomodelsinthepictureaboveshowthisapproach.Asmentionedinsection1.3,theMatlabcodeoftheRSEModel(Jin,Echenique,Hargreaves,(2013))willbeappliedforspatialequilibriumsimulation.Howeverinthispaper,weonlyusethespatialequilibriumpartoftheRSEModel,examiningandcomparingequilibrateresultsfromindividualtimeperiods.TherecursivepartoftheRSEModelwouldbeleftforfuturetest.Therefore,weinvestigatestaticequilibriumindifferenttimehorizons.Modelwillbecalibratedusingbaseyeartdataandparametersmaintainfortheyeart+50inordertofunctionthemodelandpredictoutputsin50years.Noinflationiscountedovertime.SpatialEquilibriumLanduseInordertosimplifythemodelandshowpreliminaryrules,theauthorssetupseveralTherearetwotypesofplayers,namelyproducerandconsumerinthismodel.Thereisnogovernmentanddeveloper,soconsumersdonothavetopaytaxandallrentdividendsissharedequallyamonghouseholds.Theself-sufficientcityconsumeseverythingitproducessoimportsandexportshavenotbeentakenintoconsiderationyet.Thecityisdividedintozonesandlandusemodelrevealsinteractionamongzones.Producerscanchooseanyzonetolocate.Theoutputfunctionofacertainindustrialtyperinazonejis:XrjErjKν

L)

B1)1

r

Y

b

jInthisCESfunction,primaryinputsarecapitalK,labourforceL,industrialfloorspaceBandintermediategoodsY.Eisscaleparameter.Thisfunctionisrenderedconstantreturnsbyν+δ+ω+τ=1.Assumingthecityproducesonlyonekindofconceptualgoodsandservicebyonetypeofindustry,theintermediategoodsarenotcalculatedandthereforeτ=0andr=1.Theinfluenceofcapitaliscurrentlynotcalculatedinourmodelsoν=0.Wedidnotclassifylabourstypesthereforef=1.brepresentsnumberofindustrialbuildingtypes.Consumerscanworkinanyzone,liveinanyzoneandpurchasegoodsinanyzone.Eachconsumerfirstdecideswheretobeemployed.Thenhechooseswheretoresideanddoshoppingamongzones.AssumingthereareQresidentialhousingtypes.Afterhedecidesallthelocation-relatedchoices,hewillchoosehowmanyfloorspacehewouldliketorent,howmanyhourstocontributetoworkandhowmanyretailgoodstobuy.ForaconsumerwholivesinatypeQresidentialbuildinginzonei,worksinzonejandshopsinzonek,theutilityisrepresentedas:

Zf)

q2)2lnLesij

QZisthetotalamountofgoodsandserviceaconsumercanconsume;qisthefloorareaofhisresidentialplaceandLesisthetotalleisuretimeaconsumerhasinayear,where1/(1-η)and1/(1-ξ2)arerespectivelytheelasticityofsubstitutionbetweenanytworetailgoodsandanytwotypesofhousing.μijisanidiosyncraticutilitieswhichrepresentsunobservedfactors.Sincewealreadysetupapreconditionthatthereisonlyonetypeofconceptualgoodsandservice,η=1.α+β+γ=1.Inordertoderivetheprobabilityoflocationalchoice,alogitmodelwillbeadoptedbyspecifyingthedistributionoftheidiosyncraticutilities.AssumingμijisGumbeldistributionwithdispersionparameterλ,theprobabilityPoflocationalchoicecanbederivedthroughadiscretechoicelogitmodel:

(st)exp(Ust(ij)PijThisprobabilityfunctioncanbeappliedwhencalculatingtheprobabilityofconsumer’spreferenceofwheretobuygoodsandalsowheretoliveandwork.Itcanalsocomputelaboursourcedistributionforproducers.Theliving-workingzonepairrevealsthespatialdistributionofacity.Inthispaper,asmentionedinsection2.1,transportmodelisanexternalcomponent.Allthetransportinformationdeducedfromtransportmodelareusedasexogenousinputsforlandusemodel,butoutputsregardingtransportfromlandusemodelwillnotbefeedbacksfortransportmodel,whichmeansthereisnofeedbackloopestablishedbetweenlandusemodelandtransportmodelyet.Exogenoustransportinputsforlandusemodelincludezonetozonetraveltime,distanceandgeneralisedcost.Theseinputsareutilisedwhencalculatingtraveldisutility,deliveredpriceandderivingutilityforconsumersandeconomicmass.Traveldisutility=eta×trips_per_year×(0.01×travel_cost+wage×travel_time/Deliveredprice=2×f_ratio×(0.01×travel_cost+wage×travel_time⁄60)+Whereetaandf_ratioarescalingWeassumethatallconsumersmaximiseutility,allproducersminimisecosts.Themodelistofindanoptimisedconditionthatconsumersandproducerscouldbothmaximisebenefit,subjecttofloorspaceconstraints.Azeroprofitconditionwillbesetforproducersinanopencompetitivemarket.Themarketiszeroexcessdemands,whichmeanszeroexcessdemandinlabourmarketandproductmarket.Theninlabourmarket,totalworkinghoursequalstotalhoursminuscommutingandshoppingtraveltime.Inproductmarket,totalgoodsandserviceequalstotalgoodsandserviceconsumedbyhouseholds.AssessmentofThemodeloutputswillshowtheaverageeconomicproductivityandhouseholdutilityunderdifferentpolicytrendsandtheseeconomicindicescanalsobepresentedinquantitiesinzones,includingtotalproductions,productprice,wages,rents,householdutilityandeconomicmass.Theoverallconsumersurplusinthecityregionasahouseholdwell-beingmeasuremaybedefinedasthechangeinaveragehouseholdutilitydividedbytheaveragemarginalutilityofmoney(Jin,Echenique,Hagreaves,(2013)).CS UA(111(2 WhereUishouseholdutilityandΩishouseholdtime-moneybudgetinbaseyearBandalternativescenariosyearA.CASEInthissection,weapplytheMatlabcodeoftheRSEModelincorporatingequationsabovetotestalternativepoliciesinthefringeareaofBeijing.ModelTherearealreadyestablishedmodelswhichgaveusreferencesforparametervalues.WealsoconductedtestsforsomeparametersbasedonstatisticaldatafromBeijing.Thefollowingtableliststhemodelparametersthathavebeenspecifiedintheequations.Table1.ParametersusedintheLabourcostshareBeijingI-OTable,BusinessfloorspaceBeijingI-OTable,shareforproducersBusinessJin,EcheniqueandvarietyHousingvarietyJin,EcheniqueandResidualtotalfactor1effectsnotconsideredattheHouseholdstageoftheBeijingStatisticYearbook,parameterforgoodsBeijingStatisticYearbook,parameterforHouseholdBeijingStatisticYearbook,parameterforleisuretimeScaleparameterfor1Jin,EcheniqueandlocationalNTotalnumberofMinistryofLabouranddaysperSecurity,HHoursperratiooftraveldisutilityOwncalibrationthatthecostoftheEtaaccordingtoobservedmeantraveldistanceandratioofcostofAnasandRhee,aunitofconceptualandserviceincommutingScenariosA12-zoneprototypemodelisadoptedinordertosimplifypolicytrends.Urbanisedarealocatesinthecentrewitharadiusof15km.Atownshiplocatesinadistanceof30kmfromtheurbancore,beyondfarmland.Villageslocatedispersedlywithinfarmland.Thisprototypemodelisdividedinto6zonesineachside.Zone1isthecentralcitywitharadiusof4km.Zone2istheinnercitywhilezone3istheoutercity.Zone4isestablishedasagreenbeltzonewithdispersedbuilt-upland.Zone5isasatellitetown.Zone6representsanopen-endwiderhinterlandsymbolically.Zone7-12representthesametypessymmetrically.Pinkdotsstandforcentresofzones,wherepopulationconcentrates.Dimensionsinmetreareshowninthepicturebelow.Figure4.prototypemodelzoning(drawnbytheTheprototypemodelcanthenevolveintoamodelrepresentingsituationsofBeijing.WeclassifieddistrictsofBeijinginto6typesofcitycharactersaccordingtotheprototypemodel:theoldcitycentre,innercity,outercity,greenbelt,townshipsandhinterland.Thendataregardinghouseholds,floorspace,traveltimeanddistancecanbeobtainedaccordingtothisclassification.Figure5.ZoneclassificationofWeused2000asbaseyeartocalibratethemodelandthenstaticallyrunthemodelforyear2050.Thereare6possiblepolicyscenariosforyear2050:trendgrowthistocontinuecurrenttrendofexpansion,whichindicatesmassivegrowthintheoutercity,townshipsandhinterland;densificationscenarioistoincreasedensityintheexistingbuilt-upareawithinthegreenbelt;greenbelt1scenarioistoimplementastringentgreenbelt;greenbelt2scenarioistoimplementaloosegreenbelt;“skewed”scenarioisacombinedscenarioinwhichonesideofthecityfollowsacompactpatternandtherestimplementsaloosegreenbelt;thegreenwedgescenariobreaksthecontinuityofgreenbeltintogreenwedgesandallowspopulationconcentratingaroundtransportnodeinthegreenbeltarea.Thetablebelowliststhetotalnumberofhouseholdsandfloorspaceineachscenario.Table2.constraintsinTotalnumberofTotalBaseHJTrendGreenFrom2000to2010thetotalnumberofpopulationincreasedbyabout1.6timesandweassumefrom2010to2050,thepopulationnumberwilldouble.Meanwhile,familysizewillshrinkfrom3.1personsto2personsperhousehold.Thenthetotalnumberofhouseholdin2050willbe4.9timesasmanyasthatin2000.In2000,eachhouseholdprovided1.7workersandthisnumberwilldropto1in2050.Wethencalculatethetotalnumberofjobsandseeanincreaseof2.9timesthroughyear.Thefollowingpictures6-10showthelanduseintensityinzones.Thedarkerthecolouris,themoreintensivethelandisused.Figure6.Baseyear2000zonallanduseInthetrendgrowthscenario,thefloorspaceofcentralcity,innercityandgreenbelt,namelyzone1,2,4,7,8,10,willincreasenaturally,forbothhousingspaceandbusinessfloorspace.Herewedefine50%ofthetotalfloorspaceasnaturegrowth.Meanwhile,thefloorspaceofoutercity,townshipsandhinterland,namelyzone3,5,6,9,11,12,willincreasemorethantheirnaturalgrowthamount,becausetheseareasarecurrentlypopulartonewdevelopmentandthistrendwillcontinue.Figure7.Trendgrowth2050zonallanduseDensificationscenarioistoconfineallnewdevelopmentwithinthegreenbelttocontrolurbansprawl.However,itisnotpossibletocontrolallthedevelopmentsoweallow50%ofthetotalbuilt-upfloorspaceasnaturalgrowthineveryzone.Thenweaddtherestconstrainedgrowthintozone1-3and7-9proportionally.Traveltimewithinandbetweenzone1-3and7-9willthencorrespondinglyincreaseby5to25minutes.Figure8.Densification2050zonallanduseTheGreenbeltscenario1isastringentgreenbeltscenariowhichistoconfinetheexistingboundaryofcitycentreandputnewdevelopmentinthesurroundingareaofasatellitetown.Similarly,wecontrolthedevelopmentinzone1-3,6,7-9,12andonlyallownaturalgrowthinthesezones.Thereiszerogrowthinthegreenbeltzones4an