bcl城市實驗室研究成果工作wp48

楊滔副研究員【摘要】大數(shù)據(jù)時代為研究城市空間形態(tài)與其功能的互動提供了新視角。本文以北京為案【Abstract】Theavailabilityofbigdataprovidesanewangleoninvestigatingwhetherandifso,howfarurbanspatialmorphologyintrinsicallyinteractswithitsfunctions.Thisarticle,usingapilotstudyoftheBeijingcity,firstseekstoexplorespatialconfiguration-thecomplexrelationsamongindividualspaces–ofurbannetworkcollectedfromBaidu,andtheaggregationpatternsofBaidu’sPOI(PointofInterest)regardingfunctionalclassification.Andthen,itfocusestheattentionofconductingastatisticalcorrelationbetweentheconfigurationalpatternsofurbannetworkandtheaggregationpatternsoffunctions.Basedonthesestudies,itarguesthatthedifferentfunctionalpoints,accordingtotheirscales,clientgroups,culturesandmanagementperspectives,adoptandadaptthedifferentlystructuredlayoutsandmeanwhileselectthedifferentlyvaluedlocationsatdifferentradii.Forexample,smallcommercial-orientedfacilitiestendtohighlyaggregateattheplaceswell-structuredatdifferentradii,usuallycalledtheactivecentres;mediumcommercial-orientedfacilitiesaremorelikelydistributedatthewell-structuredsitesonlyatthelargeradius,termedthegenericcentres;andlargecommercial-orientedfacilitieshavehigherpossibilityofbeingsituatedatthespacesthatarenotwell-structuredatanyradii,andsuchspacecanbenamednon-spatialattractors.Inthissense,thedifferentfunctionalaggregationpatternscanbearguedtomoreorlessreflect,andevencorrespondto,thedifferentwaysofstructuringspatiallayoutsatthelevelsofthewholecityanditsparts.《科學(xué)》(Science)198623%的速度增加，普通電IBM報道，20122.5×101890%的數(shù)據(jù)是最近兩年內(nèi)生子交易帳單、通訊、GPSGIS技術(shù)，分析北京興趣點的分布密度，探討北京城市功能的空間分布特征；最后，基于空間句法采用了一系列變量去度量空間構(gòu)成，其中兩個最為重要的是整合度（ChoiceCosness，（Betweenness行度越低，這種現(xiàn)象令人費解[15]。實際上，對于任意由k個節(jié)點構(gòu)成的網(wǎng)絡(luò)，其最短路徑共有k*(k-1)條（圖一；對于每條最短路徑的起始點，它所獲得的深度（Depth）比穿行度（Choice）多1；對于整體網(wǎng)絡(luò)而言，總深度等于每條最短路徑中起始點的深度之和，而總穿行度也等于每個起始點的穿行度之和。因此，網(wǎng)絡(luò)的總深度等于總穿行度與k*(k-1)之和。之為空間構(gòu)成效率（ConfigurationalEfficiency。效率越高的空間，到達其他空間的距離越50多個城市案例的研究中得以證實有效[15]。此外，由于該變量與穿行度高度相關(guān)，也被用于標準紅色表示效率高，而藍色表示效率低（ab。首先，這兩種空間構(gòu)成效率的模式差b位置有一定的契合性。這至少說明了CBD在全城的空間區(qū)位價值較高。POI300米*300米為單元的網(wǎng)格覆蓋在北京城上，計算每個單元在CBD和城市邊緣的密度偏低；行政機構(gòu)和文化設(shè)施則偏向聚集在三環(huán)之內(nèi)，平均密度明CBD及其周邊的密度相對較高，且聚集等級層次較為單一。這也說明，公共服務(wù)設(shè)施中偏0.3以上就表示功能分布模式之間有一定的聯(lián)系，那么（淺灰色標明較高的相關(guān)性；深灰表示中等程度的*****（POI，計算60150公里的數(shù)值，作為局部和全局的首先，規(guī)模大小影響空間區(qū)位的組合。圖七a顯示了各種商業(yè)類型的全局和局部構(gòu)成b進一步展示了中小型商鋪類型的全局和局部構(gòu)成效率。鐘表、首飾、服裝具有較高的全局a所示，郵局、醫(yī)院、公廁、停車、便民服務(wù)、理發(fā)美容都位于ab表達了不同類型的旅游景點。自然風(fēng)d是不同類型的賓館。高檔賓館占據(jù)最后，運作方式影響區(qū)位的空間組合。圖八e圖八f顯示了各類文化設(shè)施。電影院的局部和全局構(gòu)成效率都最高，這與其市場經(jīng)營有g(shù)是各類教育科研機構(gòu)。高校位于全局和局部效率都h顯示了各類高速1.15HilbertM,LópezP.TheWorld’sTechnologicalCapacitytoStore,Communicate,andComputeInformation[J].Science1April2011:Vol.332no.6025pp.60-65.BatsonJ,JouzdaniM.TheDawnofBigData[R].IBM,BattyM.Editorial:Smartcities,bigdata[J].EnvironmentandPlanningB:PlanningandDesign39HillierB.andHansonJ.TheSocialLogicofSpace[M].Cambridge:CambridgeUniversityHillierB.SpaceistheMachine[M].Cambridge:CambridgeUniversitySabidussiG.Thecentralityindexofagraph[J].Psychometrika,1966:31,FreemanL.C.Centralityinsocialnetworks:Conceptualclarification[J].SocialNetworks,1979:1(3),215–HillierB,IidaS.NetworkandPsychologicalEffectsinUrbanMovement[C].In:A.G.CohnandD.M.Mark(Eds.):COSIT2005,LNCS3693,pp.475–490.HillierB,TurnerA,YangT,ParkH-T.Metricandtopo-geometricpropertiesofurbanstreetnetworks:someconvergencies,divergenciesandnewresults[J].TheJournalofSpaceSyntax,2010,V(1)2,258-279.HillierB,PennA,HansonJ,GrajewskiT,XuJ.NaturalMovement:or.ConfigurationandAttractioninUrbanPedestrianMovement[J].EnvironmentPlanningB,1993,20(1)29-66.HillierB.SpatialSustainabilityinCities:OrganicPatternsandSustainableForms[C].In:Koch,D.andMarcus,L.andSteen,J.,(eds.)Proceedingsofthe7thInternationalSpaceSyntaxSymposium.k01.1-20.RoyalInstituteofTechnology(KTH):Stockholm,Sweden,2009.YangT,HillierB.Thefuzzyboundary:thespatialdefinitionofurbanareas[C].In:theProceedingsof6thInternationalSpaceSyntaxSymposium,2007,091-16.HillierB,YangT,TurnerA.AdvancingDepthMaptoadvanceourunderstandingofcities:comparingstreetsandcities,andstreetstocities[C].In:Green,MandReyes,JandCastro,A,(eds.)EighthInternationalSpaceSyntaxSymposium.PontificaUniversidadCatolica:Santiago,Chile.2012.號,HilbertM,LópezP.TheWorld’sTechnologicalCapacitytoStore,Communicate,andComputeInformation[J].Science1April2011:Vol.332no.6025pp.60-65.BatsonJ,JouzdaniM.TheDawnofBigData[R].IBM,BattyM.Editorial:Smartcities,bigdata[J].EnvironmentandPlanningB:PlanningandDesign39HillierB.andHansonJ.TheSocialLogicofSpace[M].Cambridge:CambridgeUniversityHillierB.SpaceistheMachine[M].Cambridge:CambridgeUniversitySabidussiG.Thecentralityindexofagraph[J].Psychometrika,1966:31,FreemanL.C.Centralityinsocialnetworks:Conceptualclarification[J].SocialNetworks,1979:1(3),215–HillierB,IidaS.NetworkandPsychologicalEffectsinUrbanMovement[C].In:A.G.CohnandD.M.Mark(Eds.):COSIT2005,LNCS3693,pp.475–490.HillierB,TurnerA,YangT,ParkH-T.Metricandtopo-geometricpropertiesofurbanstreetnetworks:someconvergencies,divergenciesandnewresults[J].TheJournalofSpaceSyntax,2010,V(1)2,258-279.HillierB,PennA,HansonJ,GrajewskiT,XuJ.NaturalMovement:or.ConfigurationandAttractioninUrbanPedestrianMovement[J].EnvironmentPlanningB,1993,20(1)29-66.HillierB.SpatialSustainabilityinCities:OrganicPatternsandSustainableForms[