基于地理信息系统的元胞自动机对城市土地开发与土地利用变化的模拟 英文翻译与译文 国土资源管理专业

基于地理信息系统的元胞自动机对城市土地开发与土地利用变化的模拟一、引言土地利用变化可以被视为是将某种土地的利用的方式转变为另一种利用方式，例如将农业用地转化为住宅用地；也可以被视为一块暂时，没有被开发的用地开始被开发。然而，土地并不会自己变化发展，所以土地利用变化的决策依赖于土地开发者的选择。除了社会经济和政治因素之外，相邻的土地使用模式也将影响土地开发者的决策行为。近年来，由于计算机科学的快速发展，基于GIS数据的元胞自动机开始广泛的应用于对城市土地利用变化的过程的模拟。本文以决策行为者之间的关系及土地利用变化为基础，通过收集土地利用的GIS数据、土地价格、人口、城市规划等信息，将他们转化成50乘50平方米的网格，然后再利用元胞自动机的NETLogo功能模拟台南市的土地利用变化。实证研究领域是在台湾的台南市第五时期重组的领域。其研究期间为1989年到2016年，土地利用变化模型的估计期限是1989年到2006年，预测期间为2007年到2016年。本文的结构如下所述：下一章描述了本项研究所使用的方法，第三章是对变量和数据处理的描述，第四章是对土地开发概率逻辑模型的预测，第五章是对土地利用变化的模拟，最后第六章是本文的结论。二、方法A.研究领域。此研究领域坐落于台湾的台南市第五时期重组的领域，面积约631.49公顷。该地区原本是钓鱼场，1979年，台南市政府对该地区的城市土地利用计划进行了审查，并计划将该地区作为重组区域进行开发。B.土地利用开发估算模型的概率。本文假设土地利用变化是否取决于土地开发者的决策。土地开发者对土地发展的决策行为取决于土地开发的概率。本文将土地开发可能的模型视为逻辑回归的概率模型。当概率值超过土地开发的阈值时，开发商将会选择开发土地。反之则选择不开发土地。C.土地利用转换的规则。利用CA进行模拟时，土地利用转换规则主要取决于土地开发的可能性和相邻土地的状况。当这种可能性比较大时，土地将会被开发。同时，当土里利用强度邻近的网格高于中心网格时，该中心网格将会有一个更高发展的可能性。规则如下：1.如果土地利用中心的网格是空置的，发展住宅用途的可能性就会比发展成其他类型土地的可能性要大，如果邻近住宅的网格数使用大于3个，那么处于中心网格的土地使用将会由空置变为住宅用地。2.如果土地利用中心的网格是空置的，开发商业用地的可能性大于其他类型的土地，如果邻近烛照用途的网格数大于5个，那么中心网格的土地将会由空置变为商业用地。3.如果位于中心网格的土地用途是住宅区，发展商业用途的概率大于住宅用途的概率，同时邻近住宅用地的网格数大于5个，那么中心网格的土地将会由住宅用地变为商业用地。4.如果位于中心网格的土地用途是商业区，发展住宅用途的概率大于商业用途的概率，同时邻近住宅用地的网格数不少于4个，那么中心网格的土地将会由商业用地变为住宅用地。SimulationofUrbanLandDevelopmentandLandUseChangeEmployingGISwithCellularAutomataI.INTRODUCTIONLand-usechangecanberegardedaschangingacertaintypeoflanduseintotheuseofothertypes,suchasfromagriculturallandusetoresidentialuse;alsobeseenasapieceoflandfrom"undevelopedstate"intoa"developmentstate."However,thelanditselfdoesnotself-developed,sotheactualland-usedecision-makingbehaviordependsonthechoicesoflanddevelopers.Inadditiontothesocio-economicandpolicyfactors,theadjacentlandusepatternswillaffectthelanddeveloper'sdecision-makingbehavior.Inrecentyears,duetotherapiddevelopmentofcomputerscienceandcomplexity,itiswidespreadtouseCellularAutomata(CA)withGISdatatosimulatetheprocessofurbanlandusechange.Thisstudy,basedontherelationshipbetweenactor’sdecision-makingbehaviorandland-usechanges,collectsGISdataoflanduses,landprice,population,urbanplanningandsoforth,transformstheminto50by50meterssquaregrid,andthenusingNetLogowithCellularAutomata(CA)functiontosimulatetheland-usechangeinTainancity.TheempiricalstudyareaisthereconsolidatedareaofthefifthperiodinTainancity,Taiwan.Thestudyperiodis1989-2016yearswhichtheperiodofestimatingtheland-usechangingmodelis1989-2006andtheforecastingperiodis2007-2016.Theorganizationofthepaperisasfollows:thenextsectiondescribesthemethodsadoptedinthisstudy;section3describesthevariablesanddataprocessing;section4estimatestheLogisticmodeloflanddevelopmentprobability;section5simulatesland-usechange;andfinally,section6providestheconclusion.II.METHODSA.StudyAreaTheempiricalstudyarea,covered631.49Hectares,locatesinthereconsolidatedareaofthefifthperiodinTainancity,Taiwan.Thisareawasoriginallyfishingfarms.In1979,TainanCityGovernmentreviewedthearea’surbanplanningandplannedthisareaasareconsolidatedareatodevelop.B.TheEstimatingModelofLand-useDevelopmentProbablityThisarticleassumeswhetherland-usechangesdependonthechoiceoflanddevelopers.Landdevelopersforlanddevelopmentdecision-makingbehaviordependontheprobabilityoflanddevelopment.ThisstudysetlanddevelopmentprobabilitymodelbyLogisticRegressionModel.Whentheprobabilityvalueexceedsathresholdoflanddevelopment,landdeveloperswillchoosetodeveloptheland.Onthecontrary,choosenottodevelop.C.LandUseConversionRulesIntheCAsimulation,Land-useconversionrulesmainlydependonthelanddevelopmentprobabilityandneighborhoodconditions.Whentheprobabilityoflanddevelopmentisgreaterthanthethresholdvalue,thelandwillbedeveloped.Besides,whenthelanduseintensityofneighboringgridsishigherthanthecentergrids’,thecentergridwillhaveahigherdevelopmentprobability.Therulesareasfollows:1.Ifthelanduseinthecentergridisvacant,theprobabilityofdevelopingresidentialuseisthegreatestthanotherstypeuses,andthegridnumbersofneighboringresidentialusearegreaterthan3,thenthelanduseinthecentergridwillbechangedfromvacantintoresidentialuse.2.Ifthelanduseinthecentergridisvacant,theprobabilityofdevelopingcommercialuseisthegreatestthanotherstypeuses,andthegridnumbersofneighboringresidentialusearegreaterthan5,thenthelanduseinthecentergridwillbechangedfromvacantintocommercialuse.3.Ifthelanduseinthecentergridisresidential,theprobabilityofdevelopingcommercialuseisgreaterthanresidentialuse,andthegridnumbersofneighboringresidentialusearegreaterthan5,thenthelanduseinthecentergridwillbechangedfromresidentialintocommercialuse.4.Ifthelanduseinthecentergridiscommercial,theprobabilityofdevelopingresidentialuseisgreaterthancommercialuse,andthegridnumbersofneighboringresidentialusearelessthan4,thenthelanduseinthecentergridwillbechangedfromcommercialuseintoresidualuse.III.VARIABLESANDDATAPROCESSINGA.Variables1.Landusepatterns:Dividinginto10kindsoflanduse,includingvacantuse,residentialuse,commercialuse,officialland,schoolsites,park,roads,gasstationsandparkinglot,sewagefarmandsubstation,conservedland.2.Othervariablesaffectingland-usechange:landprice,landpricegrowthrates,thenumberoflandownership,population:Unitgridaveragepopulation,thenumberofpublicfacilities,distancetothenearestroads,floorarearatio.B.DataProcessingInthisstudy,thegridsizescaleis50by50meterssquare.GISdatabaseconversedintoNetLogosoftwareshownasFig1.Thegridsnumberofland-usepatternin1989&2006showninTableI.IV.ESTIMATINGTHEMODELOFLANDDEVELOPMENTPROBABILITYTheestimatingresultsoflanddevelopmentprobabilityshowninTableII.V.LAND-USECHANGESIMULATIONANALYSISFollowingwewillconfirmtheaccuracyofsimulationresults,andthensimulatelandusechanges.Thesimulationincludes:(a)landusechangesin1989-2006;(b)landusechangesin2007-2016;(c)effectsofpolicychangesinurbanplanning.A.modelvalidationThecorrectrateofpredictingdevelopmentis99.06%.Theaccuracyrateofforecastingland-useis78.61%.Theaccuracyrateofforecastingthetotalnumberofdevelopmentis99.38%.B.Simulationofland-usechangein1989-2006ThegridnumbersofthelandusechangeeachyearshowasfollowedFig.2.Predictionofland-usechangein2007-2016Thepredictionofland-usechangein2007-2016showasFig.3D.PolicySimulationAnalysis1.floorarearatioadjustment2.PopulationdensityadjustmentTheresultsshowninFig.5.VI.CONCLUSIONSThepurposeofland-usechangesimulationistostudytheimpactsofpolicychange.Iftherelationsbetweenlandusechangeandpolicychangecouldberealized,itwillbeausefultoolforlawmaking,andfurtheravoidingcontinuousdamageofenvironment.Thisstudyfindingshowsthatitisusefultocontrolthepopulationdensityandlanduseintensitywhenmakingurbanplanplanning.Therefore,theresultsandprocessesofLUCCsimulationcanbeemployedasassessmentsbeforelandconstructionplanninganddevelopment;italsoprovideslanduseplannersusefulreferences.TheresultsofCAsimulationshowedthattheresidentialuseandcommercialuseoftheland-usepatternsgraduallyincreasedoverthepast13yearsinthisresearcharea,andthere’llbenovacantlandafter2002.Furthermore,thegridnumbersforresidentialusewereaboutfourtimesofgridnumbersforcommercialuse.Thetypeoflanduseismainlyresidentialuse.Thedecision-makersshouldbecarefulconsiderationforguidingthecitytowardstheclosedevelopmentorexpansionofdevelopment.Inthispaper,wehavethepolicyimplicationbyadjustingthefloorarearatioandpopulationdensity.Theresultsshowedthatincreasingfloorarearatiowillincreaselanduseintensity,accommodatemoreurbandevelopmentactivitiesandbusinessbehavior.Besides,thehigherpopulationdensitymaystimulatecommercialactivities.Sotheland-usepatternswillbechangedintohigher-intensitycommercialuse.Theresultsshowedthatdifferentpolicywilldifferentlyaffectthedevelopmentofland-usepatterns,sothegovernmentshouldreconsiderwhat’shisgoalofregionaldevelopment.REFERENCES[1]A.Ligtenberg,A.K.BregtandR.V.Lammeren,”Multi-Actor-BasedLandUseModeling:SpatialPlanningUsingAgents,”LandscapeandUrbanPlanning,vol.56,2001,pp.21-33.[2]F.Wu,“AnEmpiricalModelofIntra-metropolitanLandUseChangeinaChineseCity,”EnvironmentandPlanningB:PlanningandDesign,vol.125,1998,pp.245-263.[3]M.Batty,X.YichunandS.Zhanli,”Mod