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地理学报  2015 

基于乡镇尺度的中国25省区人口分布特征及影响因素

DOI: 10.11821/dlxb201508004, PP. 1229-1242

Keywords: 人口分布,乡镇尺度,格局特征,影响因素,中国

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Abstract:

人口空间分布具有典型的尺度特征,精细尺度的人口分布是当前人口地理学研究的热点和难点。乡镇(街道)是中国人口普查数据公开发布的最小行政单元,乡镇级人口密度计算及其分布特征研究能够更客观、精细地刻画中国人口分布的空间格局和态势,为促进中国人口的合理优化布局提供科学依据和决策支持。本文收集处理了2000年中国25个省(直辖市、自治区)的乡镇(街道)级行政边界数据,基于第五次人口普查乡镇(街道)人口统计数据,计算了乡镇级平均人口密度。采用Lorenz曲线、空间分析及样带分析的方法,分析了研究区乡镇(街道)人口分布的疏密结构、空间集聚性、纬向和经向规律。利用相关分析和逐步回归分析,分省探究了地形起伏度、水网密度、路网密度及社会经济发展水平(利用夜间灯光指数表征)等4个因素对于乡镇级人口分布的影响。研究表明①乡镇级平均人口密度能够有效区分出县域内部的人口密度高低差异,整体不均衡性高于基于县级平均人口密度的研究结果;②乡镇(街道)人口分布总体规律是西北稀疏东南密集,同时,东南密中有疏,西北疏中有密;③乡镇(街道)人口分布的经纬向规律变异较大,既受中国三级阶梯地貌大势的影响,也受局部微地形及区域中心城市的影响,并和海岸线、交通枢纽及大江大河的分布具有一定的空间耦合性。④乡镇级平均人口密度与地形起伏度、水网密度、路网密度及夜间灯光指数等显著相关,省级平均相关系数分别为-0.56、0.28、0.61、0.69。⑤在乡镇尺度上,地形条件及区域发展水平对辽、吉、京、津、沪、冀、豫、陕、晋、鲁、皖、苏、湘、鄂、赣、浙、闽、粤、琼等省份的人口分布具有较强的决定作用。⑥对于藏、青、蒙、滇、黔等5省或自治区,需要引入更多的自然环境及社会因素来解释其人口分布的特殊规律。本研究扩充了中国人口地理学的研究尺度和维度,并引入了新的定量分析和空间分析方法,所构建的覆盖中国25省(直辖市、自治区)的乡镇(街道)级人口分布科学数据集丰富了中国人口地理学的2000年本底数据资源。

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[12]  LiuJiyuan,YueTianxiang,WangYing'an,etal.DigitalsimulationofpopulationdensityinChina.ActaGeographicaSinica,2003,58(1):17-24.原文[刘纪远,岳天祥,王英安,等.中国人口密度数字模拟.地理学报,2003,58(1):17-24.]运用基于格点生成法的人口密度空间分布模拟模型,通过运行净第一性生产力空间分布、数字高程、城市规模及其空间分布和交通基础设施空间分布等数据集,模拟了中国人口密度的空间分布规律。模拟结果表明,人口密度的最高值集中在北京、上海和郑州之间的三角区(BSZ)及珠江三角洲地区;同时,这个BSZ峰值三角区有发展为以上海-南京-杭州大都市密集区、武汉市、西安市、北京-天津-唐山大都市密集区和沈阳-大连大都市密集区为顶点的五角形峰值区的趋势,珠江三角洲峰值区也正在向外围地区扩展。DOI:10.3321/j.issn:0375-5444.2003.01.003原文
[13]  TianYongzhong,ChenShupeng,YueTianxiang,etal.SimulationofChinesepopulationdensitybasedonlanduse.ActaGeographicSinica,2004,59(2):283-292.Landusedataintegrateslotsofinformationoffactorsaffectingpopulationdistribution.Itisthenatureofland,thehouseholdresponsibilitysystem,thehouseholdregistrationsystem,andtheproductionmodeofagricultureinChinathatestablishaclosespatialrelationbetweenlanduseandpopulationdistribution.Accordingtotheideaofmodelingseparatelybytownandcountry,byecologicalzonesalongwiththepopulationofcountiesasrestrictiveconditions,webuildthefollowingmodelbasedonlandusetosimulatethepopulationdensityin1kmsquaregrid-cellsofChina:POP■=P■×V■■V■+P■×V■■V■.Linearweightedmodelisusedtocalculateruralpopulationindices.ItfirstlypicksouttheindicatorsforthemodelwhicharecorrelatedpositivelyandremarkablywiththepopDOI:10.1007/BF02873097原文[田永中,陈述彭,岳天祥,等.基于土地利用的中国人口密度模拟.地理学报,2004,59(2):283-292.]土地利用数据综合了影响人口分布的众多因素的信息.根据分县控制、分城乡、分区建模的思路,建立基于土地利用的中国1km栅格人口模型.对农村人口采用线性加权模型进行模拟,根据全国12个农业生态区内人口与各类农业用地之间的相关关系选取指标,采用逐步回归计算各指标的回归系数,并结合土地的生产力及其与人口的相关性,确定各指标的加权系数.对城市人口,建立基于城镇规模的人口距离衰减加幂指数模型.结果分析表明,"胡焕庸"线以东人口占全国的94.58%,人口密度是该线以西的21倍;东部人口集中于黄淮海地区、四川盆地、长江中下游、东北平原及沿海地区,东南沿海又表现为"点轴"分布的特点.验证表明,模拟结果具有较高的精度.DOI:10.3321/j.issn:0375-5444.2004.02.015原文
[14]  ZhuoLi,ChenJing,ShiPeijun,etal.ModelingpopulationdensityofChinain1998basedonDMSP/OLSnighttimelightimage.ActaGeographicaSinica,2005,60(2):266-276.Spatialdistributionofpopulationdensityiscrucialforanalyzingtherelationshipamongeconomicgrowth,environmentprotectionandresourceutilization.Inthisstudy,populationdensityofChinain1998at1-kmresolutiongridswassimulatedbyintegratingDMSP/OLSnon-radiancecalibratednighttimelightimage,SPOT/VEGETATION10-daymaximumNDVIdata,populationcensusdataandvectordataofcountyboundary.Notonlythepopulationdensityinlightpatchesbutalsothatoutofthemwasestimatedinfourtypesofareas.Foreacharea,inlightpatches,themodelforpopulationdensityestimationwasdevelopedbasedonthesignificantcorrelationbetweenlightintensityan原文[卓莉,陈晋,史培军,等.基于夜间灯光数据的中国人口密度模拟.地理学报,2005,60(2):266-276.]原文
[15]  LvAnming,LiChengming,LinZongjian,etal.Populationgrowthrateanditsspatialassociationbyprovinceinchina.ActaGeographicaSinica,2002,57(2):143-150.原文[吕安民,李成名,林宗坚,等.中国省级人口增长率及其空间关联分析.地理学报,2002,57(2):143-150.]http://www.geog.com.cn/CN/Y2002/V57/I2/143
[16]  MaYan,LiuShuang.EmpiricalresearchontimeandspacediffusionprocessofprovincialdemographictransitioninChina.PopulationJournal,2011,185:16-23.Usingthedataofdemographictransitiononprovinciallevelfrom1949to2008,wetrytodrawapictureoftimeandspacediffusionprocessofprovincialdemographictransitioninChinabyclusteranalysis.Thenwefindtheclusteranalysisoftimeseriesdataindicatesthefertilitytransition,mortalitytransitionandthetransitionofnaturalincreasearenotatthesamepace,andtheyhavedifferenttransitionmodes.Besides,theclusteranalysisoftimepointdatademonstratesprovincialdemographictransitiondiffusesinspaceandhastimelag,andthepaceofprovincialdemographictransitionconvergesmoreandmorequickly.Meanwhile,wetesttheconsistencyofprovincialdemographictransitionandprovincialeconomicdevelopment,andwefindthatboththeconsistencyandnon-consistencyexistinthedifferentprovinces,andtheeconomicdevelopmentisn'tthedeterminedfactorofprovincialdemographictransition.知网[马妍,刘爽.中国省级人口转变的时空演变过程:基于聚类分析的实证研究.人口学刊,2011,185:16-23.]
[17]  ZhangZhibin,PanJing,DaFuwen.PopulationspatialstructureevolutionpatternandregulationpathwayinLanzhoucity.GeographicalResearch,2012,31(11):2055-2068.[张志斌,潘晶,达福文.兰州城市人口空间结构演变格局及调控路径.地理研究,2012,31(11):2055-2068.]以街道和乡镇层面的人口统计数据为基础,综合应用ArcGIS和GS+Version7等软件对兰州市人口空间演变进行定量分析。结果表明:自1982年至2009年,兰州市人口呈逐年“向心聚集”态势,但不同阶段、不同街区人口空间增长存在显著差异;街道和乡镇人口密度差距逐年增大,高密度街区个数增多、范围扩大;距离人口高密度中心越远,人口密度的正相关性逐渐削弱,负相关性则逐渐增强,空间自相关范围不断增大;人口空间分布整体呈“东密西疏”格局,并呈现“双中心”空间结构。人口的极不均衡分布,带来了环境污染、交通拥挤、住宅紧张、就业困难等一系列问题。通过构建多中心城市结构、调整产业空间布局、平衡配置基础设施和引导人口有序流动等方面进行综合调控,不断优化人口空间分布,保障城市的可持续发展。DOI:10.11821/yj2012110013原文
[18]  LiangHaoguang,LiuYansui.Studyonspatio-temporalchangeandsimulationofpopulationinBeijingbasedoncensusdata,ActaGeographicaSinica,2014,69(10):1487-1495.Thisstudymainlyaimstoexplorethespatio-temporalpatternsandtosimulatethefuturescenarioofpopulationchangeinBeijingbasedonthefifthandsixthcensusdataattownshiplevel.Themaincontentsandresultsweresummedupasfollows:(1)TheresidentpopulationofBeijingincreasedwithanaverageannualrateof3.5%between2000and2010,andthepopulationincreasedby0.6millioneveryyear.Beijingwasoneofthemegacitieswhichwereclassifiedintothefirstrangefortheirgreatamountofincreasedpopulation.(2)Therewasanobviouscirclestructureinspace.Thepopulationofinnercitywasalmoststagnant;ithadarapidgrowthinthesuburbs,andahighrateintheoutercity.However,ithadanincreaseonlyinthecountyseatandthekeytownsintheecologicalconservationregionofBeijing.(3)IntermsoftheCA/MASscenariosimulationanalysis,inthespontaneouslayoutscenario,employmentopportunitieswillbefurtheragglomeratedtotheinnercity,whilepopulationissuburbanizedconstantly.Thiswillincreasethecity'scommuterstressandaggravatetheconditionofcitytrafficblock.Whenadjustingtheparametersofemploymentandthusstrengtheningtheguidepolicyofurbanpopulationlivinginworkingfunction,theproblemofimbalancebetweenindustrialspaceandresidentialspaceintheurbaninternalspacescalecanbesolved.Atthesametime,theformationofclusterofsmalltownscanbepromotedandurbancommuterpressurecanbereduced.Thencomesthecity'sradiationanddiffusioneffect.Theauthorssuggestthat,inordertooptimizethespatialdistributionofpopulationinBeijing,moreeffortsshouldbemadetocoordinatetherelationshipbetweenemploymentandresidents.Animportantwayistoaccelerateregionalcoordinateddevelopment,andtoplanmulti-centersdevelopmentasgroups.原文[梁昊光,刘彦随.北京市人口时空变化与情景预测研究.地理学报,2014,69(10):1487-1495.]原文
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[20]  BoyleP.Populationgeography:Doesgeographymatterinfertilityresearch?ProgressinHumanGeography,2003,27(5):615-626.FocusesontheroleplayedbypopulationgeographyinfertilityresearchinGreatBritainandtheUnitedStates.Historicalpatternsofpopulationchangepresentedbygeographers;Persuasiveargumentagainstthedominantroleofsocialclassandoccupationinexplainingfertilitychange;Geographicalperspectivesofunderstandingfertilityandfamilydecision-making.DOI:10.1191/0309132503ph452prCrossref
[21]  CookeTJ.Genderrolebeliefsandfamilymigration.Population,SpaceandPlace,2008,14(3):163-175.onlin
[22]  KanK.Residentialmobilityandsocialcapital.JournalofUrbanEconomics,2007,61(3):436-457.Springer
[23]  FengZhiming,LiPeng.Reviewofpopulationgeographyinthepastcentury.ProgressinGeography,2011,30(2):131-140.Populationgeographyisastudyofthewaysinwhichspatialvariationsinthedistribution,composition,migrationandgrowthofpopulationarerelatedtothenatureofplaces.Longbeforethelastcentury,therewasnodisciplinecalledpopulationgeography.However,theearlysubstantialrelevantinvestigationsofpopulationgeographywereembodiedinthetraditionalgeography.Inthefirsthalfofthe20thcentury,yetresearchesofpopulationgeographystilldidnotbecomeindependentfromhumangeography.ThephilosophyofanthropogeographyofFriedrichRatzelwasinheritedduringthesameperiod.AftertheSecondWorldWar,thestudiesofpopulationgeographyprogressivelydeveloptowardasubfieldwithingeography.Itwasnotuntilthe1950swasthescienceofpopulationgeographygraduallyestablished.Sincethen,thepopulationgeographyasabranchsubjecthasgainedapersistentandfastdevelopment.Bulksofpopulationmattersareinvolvedinthescopeofpopulationgeographyinthestartofnewmillennium.Aboveall,someworldwideconcernedandongoingissuessuchasfertilityandageing,mobilityandmigration,andpopulationandvulnerabilityhaveturnedintohotthemeslately.Inthenearfuture,populationanddifference,vulnerability,andspatialanalysiswillstillbekeyinterestsofpopulationgeographers.Tocopewiththenewchallenges,thegeographicscaleandgeographicdimensionsofpopulationproblemsshouldbeemphasized,andthemethodologiesofspatializationofstatisticalpopulationshouldbeintensifiedsimultaneously.原文[封志明,李鹏.20世纪人口地理学研究进展.地理科学进展,2011,30(2):131-140.]20世纪之前的人口地理学只是从属于传统地理学的人口地理研究。进入20世纪,人口地理研究尚未从人文地理学中独立出来,内容上延续了拉采尔的人类地理学思想;二战以后,人口地理研究逐步向人口地理学纵深发展,50年代人口地理学逐步成形。20世纪后半叶,人口地理学得到了持续快速发展:出生率与老龄化、迁移与流动、人口与脆弱性等世界性人口问题成为热点研究主题。未来人口地理学家仍将关注人口差异、脆弱性及空间分析,加强人口统计数据空间化方法研究,从不同地理尺度与地理维度应对人口地理学的新挑战。DOI:10.11820/dlkxjz.2011.02.001原文
[24]  BalkDL,DeichmannU,YetmanG,etal.Determiningglobalpopulationdistribution:Methods,applicationsanddata.AdvancesinParasitology,2006,62:119-156.Evaluatingthetotalnumbersofpeopleatriskfrominfectiousdiseaseintheworldrequiresnotjusttabularpopulationdata,butdatathatarespatiallyexplicitandglobalinextentatamoderateresolution.Thisreviewdescribesthebasicmethodsforconstructingestimatesofglobalpopulationdistributionwithattentiontorecentadvancesinimprovingbothspatialandtemporalresolution.Toevaluatetheoptimalresolutionforthestudyofdisease,thenativeresolutionofthedatainputsaswellasthatoftheresultingoutputsarediscussed.AssumptionsusedDOI:10.1016/S0065-308X(05)62004-0PMID:3154651ElsevierNCBIPubmedCentral
[25]  DobsonJE,BrightEA,ColemanPR,etal.LandScan:Aglobalpopulationdatabaseforestimatingpopulationsatrisk.PhotogrammetricEngineeringandRemoteSensing,2000,66(7):849-857.PDF
[26]  http://na.unep.net/siouxfalls/datasets/datalist.php.
[27]  http://www.worldpop.org.uk/.
[28]  BriggsDJ,GulliverJ,FechtD,etal.Dasymetricmodellingofsmall-areapopulationdistributionusinglandcoverandlightemissionsdata.RemoteSensingofEnvironment,2007,108(4):451-466.Despitetheimprovementsmadeincensusproceduresoverrecentdecades,theavailabilityofdetailedpopulationdataislimited.Formanyapplications,includingenvironmentalandhealthanalyses,methodsarethereforeneededtomodelpopulationdistributionatthesmall-arealevel.WiththedevelopmentofGISandremotesensingtechniques,theabilitytodevelopsuchmodelshasgreatlyimproved.ThispaperdescribesaGIS-basedapproachusingremotelysensedlandcoverandnighttimelightemissionsdatatomodelpopulationdistributionatthelandparcellevelacrosstheEuropeanUnion.LightemissiondatafromtheDMSPsatelliteswerefirstresampledandmodelledusingkrigingandinversedistanceweightingmethodstoprovidea200-mresolutionlightemissionsmap.ThiswasthenmatchedtoCORINElandcoverclassesacrosstheEU.Regressionmethodswereusedtoderivemodelsofrelationshipsbetweencensuspopulationcounts(atNUTS5level)andlandcoverareaandlightemissions.ModelsweredevelopedatbothnationalandEUscale,usingarangeofdifferentmodellingstrategies.Modelperformance,asindicatedbytheregressionstatistics,wasseentobegood,withtypicallyintheorderof0.8–0.9andSEEca.4000people.Insoutherncountries,especially,incorporationoflightemissionsdatawasfoundtoimprovemodelDOI:10.1016/j.rse.2006.11.020ElsevierPDF
[29]  LiaoYilan,WangJingfeng,MengBin,etal.IntegrationofGPandGAformappingpopulationdistribution.InternationalJournalofGeographicalInformationScience,2010,24(1):47-67.Mappingpopulationdistributionisanimportantfieldofgeographicalandrelatedresearchbecauseofthefrequentneedtocombinespatialdatarepresentingsocio-demographicinformationacrossvariousincompatiblespatialunits.However,theresearchmaybecomeverycomplexanddifficultwhenapopulationinmultipleplacesisestimatedbyvariousfactors.Previouseffortsinthefieldhavecontributedtotheselectionofappropriateindependentvariablesandthecreationofdifferentpopulationmodels.However,thelevelofaccuracyobtainablewiththesestudiesislimitedbythespatialheterogeneityofpopulationdistributionwithintheindividualcensusdistricts,particularlyinlargeruralareas.Ahigh-accuracymodellingmethodforpopulationestimationbasedonintegrationofGeneticProgramming(GP)andGeneticAlgorithms(GA)withGeographicInformationSystems(GIS)ispresentedinthispaper.GISwasappliedtoidentifyandquantifyasetofnaturalandsocioeconomicfactorswhichcontributedtopopulationdistribution,andthenGPandGAwereusedtobuildandoptimisethepopulationmodeltoautomaticallytransformcensuspopulationdatatoregulargrids.Thestudyindicatedthattheproposedmethodperformedmuchbetterthanthestepwiseregressionanalysisandadaptedgravitymodelmethodsinestimatingthepopulationofbothurbanandruralareas.Moreimportantly,thisproposedmethodcouldprovideasingle,unifiedapproachtomappingpopulationdistributioninvariousareasbecausetheparadigmsofthesealgorithmsaregeneral.DOI:10.1080/13658810802186874CrossrefPDF
[30]  LiuXiaohang,KyriakidisPC,GoodchildMF.Populationdensityestimationusingregressionandarea-to-pointresidualkriging.InternationalJournalofGeographicalInformationScience,2008,22(4):431-447.dl.ac
[31]  RaoDM,ChernyakhovskyA,RaoV.Modelingandanalysisofglobalepidemiologyofavianinfluenza.EnvironmentalModelling&Software,2009,24(1):124-134.TheWorldHealthOrganizationhasactivatedaglobalpreparednessplantoimproveresponsetoavianinfluenzaoutbreaks,controloutbreaks,andavoidanH5N1pandemic.Theeffectivenessoftheplanwillgreatlybenefitfromidentificationofepicentersandtemporalanalysisofoutbreaks.Accordingly,wehavedevelopedasimulation-basedmethodologytoanalyzethespreadofH5N1usingstochastic...DOI:10.1016/j.envsoft.2008.06.011ElsevierACM
[32]  McGranahanG,BalkD,AndersonB.Therisingtide:Assessingtherisksofclimatechangeandhumansettlementsinlowelevationcoastalzones.EnvironmentandUrbanization,2007,19(1):17-37.DOI:10.1177/0956247807076960OxfordUnivPressPDF
[33]  YeJing,YangXiaohuan,JiangDong.Thegridscaleeffectanalysisontownleveledpopulationstatisticaldataspatialization.JournalofGeo-informationScience,2010,12(1):40-47.Thegirdscaleeffectisoneofthebasicissuesonpopulationdataspatialization.Forthedemandofallkindsofspatialpopulationdatainthefieldsofresourcesandenvironmentandglobalchangemodels,alotofresearcheshavebeendonebasedonremotesensingandGIStechnologybothathomeandabroad.Butthemodelsusedaremostlyonglobal(suchasGPW,1995,5km),national(suchasnationalpopulationdatabase,2000,1km)orprovincialscale,andtheirresolutionrangesfrom1kmtoseveralkilometers.Inrecentyears,therearestudiesonlocaldistributionofpopulationbyusingofhigh-resolutionimages.Foralltheresearches,boththemethodofdatasourceselectionaccordingtospecificapplicationandtheanalysisonproductionsuitabilityaredeficient.So,manyuncertaintiesexitinpopulationdataapplication,especiallyincountylevelandsecondaryortertiaryrivers.Tosolvetheproblemsmentionedabove,inthisarticlewemainlyproposethemethodofscaleeffectanalysisonpopulationdataspatialization.TakingYiwuCity,ZhejiangProvinceasthestudyarea,usingCBERSandIRS-P5imagesweextractlanduseinformationandbuildaspatializationmodeltothestatisticalpopulationdataofruraltowns,thengetasetofpopulationdatagirdrangingfrom20mto1km.Moreover,bycomparingpopulationdatabygridandstatisticalpopulationdatainruraltowns,thegridscaleeffectanalysisismade;bycomparingpopulationdatabygridandstatisticalpopulationdatainvillages,theremotesensingdatasourcescaleeffectanalysisismade.Theresultofscaleeffectanalysisshows:byusingCBERSasdatasource,thesuitablegridscaleofproductionis200manditsprecisionis76%;byusingP5asadatasource,thesuitablegridscaleofproductionis100manditsprecisionis84%.Themethodofscaleeffectanalysisinspatialdistributionofstatisticalpopulationisarguedinthispaperanditcanprovidebasictechnicalsolutionsandexamplestooptimumscaleselectionintheprocessofhumanisticfactors(suchaspopulation)spatialization.DOI:10.1017/S0004972710001772原文[叶靖,杨小唤,江东.乡镇级人口统计数据空间化的格网尺度效应分析:以义乌市为例.地球信息科学学报,2010,12(1):40-47.]原文
[34]  AzarD,EngstromR,GraesserJ,etal.Generationoffine-scalepopulationlayersusingmulti-resolutionsatelliteimageryandgeospatialdata.RemoteSensingofEnvironment,2013,130:219-232.AgriddedpopulationdatasetwasproducedforPakistanbydevelopinganalgorithmthatdistributedpopulationeitheronthebasisofper-pixelbuilt-upareafractionortheper-pixelvalueofaweightedpopulationlikelihoodlayer.Per-pixelbuilt-upareafractionwascalculatedusingaclassificationandregressiontrees(CART)methodologyintegratinghigh-andmedium-resolutionsatelliteimagery.Thelikelihoodlayerwasproducedbyweightingdifferentgeospatiallayersaccordingtotheireffectonthelikelihoodofpopulationbeingfoundintheparticularpixel.Thegeospatiallayersintegratedintothelikelihoodlayerwere:1)proximitytoremotelysensedbuilt-uppixels,2)densityofsettlementpointsinafixedkernel,3)slope,4)elevation,and5)heterogeneityoflandcovertypesfoundwithinasearchradius.ThemethodforweightingtheselayersvariedaccordingtosettlementpatternsfoundintheprovincesofPakistan.Differencesinzonalpopulationestimatesgeneratedfromthe100-metergriddedpopulationlayerresultingfromthisstudy,,andCIESIN'sGriddedPopulationoftheWorldandGlobalRuralUrbanMappingProject(GPWandGRUMP)areexamined.Populationestimatesforsmallareasproducedusingthispaper'smethodwerefoundtodifferfromcensuscountstoalesserdegreethanthoseproducedusingLandScan,GPW,orGRUMP.TherootDOI:10.1016/j.rse.2012.11.022Elsevier
[35]  MayorSJ,SchaeferJA.Themanyfacesofpopulationdensity.Oecologia,2005,145(2):275-280.PMID:16001227NCBI
[36]  ZhouZixiang,LiJing,RenZhiyuan.ThereliefdegreeoflandsurfaceandpopulationdistributioninGuanzhong-TianshuiEconomicRegionusingGIS.ScientiaGeographicaSinica,2012,32(8):951-957.Withthedegenerationofenvironmentandaccelerationofurbanization,humanenvironmenthasattractedgreatattentionworldwide.Asoneofthekeyfactors,thereliefdegreeoflandsurfaceisanimportantindicatorfornaturalevaluation,anditalsohashighaccuracyandpracticalapplicationinsmallscaleresidentialenvironmentalevaluation.Basedonlatticedigitalelevationmodelofscale1鈭250000inGuangzhong-Tianshuieconomicregion,usingthewindowanalysisandspatialanalysismodelofARCGISsoftware,thisarticleextractsthereliefdegreeoflandsurfaceandpopulationdistributioninGuanzhong-Tianshuieconomicregion.Fromthecharacteristicsofproportion,spatialdistributionandheight,italsosystematicallyanalyzesthedisciplineofthereliefdegreeoflandsurfaceanditsrelationshipwiththedistributionofpopulationinGuanzhong-Tianshuieconomicregion.Thestudyhasshownthat:1)ThereliefdegreeoflandsurfaceinGuanzhong-Tianshuieconomicregionisdominatedbymiddleandlowvalue,anditstopographicareaislessthan2.4occupying96.66%ofthetotalarea,andtheaverageproportionoccupying32.4%ofthewholearea.Thehigheristhereliefdegreeoflandsurface,theloweristheproportionofplains,andviceversa;2)ThereliefdegreeoflandsurfaceinGuanzhong-Tianshuieconomicregionpresentssuchspatialpatternsthatthesouthandnortharehigherandthemiddleislower,andthereisthemaximumvalueinTaibaiCountryinBaojiCityandtheminimumvalueinGuanzhongplains.Thevariationisnotapparentonthelongitude,andthedegreeoflatitudeincreasesafterthefirstdropnomatterfromSouthtoNorthorfromNorthtoSouth;3)Asthealtitudeincreased,thedegreepresentsarisingtrendbuthasnotmuchchange;4)Thereliefdegreeoflandsurfacehasastrongimpactontheregionaldistribution,nearly90%residentsinGuanzhong-Tianshuieconomicregionlivedintheareawherelessthan1.5degree,thecurvedfittingofpopulationdensityandtopographicisveryhigh;5)Therelationalareaoftopographicandpopulationdistributionhavesignificantdifference,thetopographichasobviousrelationwithpopulationdistribution,buttherelationshipofthetopographicissmallerinfourcountriesinShangluoandTianshuicities.Tosumup,thereliefdegreeoflandsurfacecanbetterreflectthetopographicfeatureandrevealitsregularitiesofspaceinGuanzhong-Tianshuieconomicregion.Empiricalresearchshowsthat,asoneofthekeyfactors,thereliefdegreeoflandsurfaceisanimportantindicatorfornaturalevaluation;italsohashighaccuracyandpracticalapplicationinsmallscaleresidentialenvironmentalevaluation.Insummary,theRDLSmodelestablishedinthispapercannotonlyreflectthenaturalenvironmentsuitabilityforhumansettlementsinGuanzhong-Tianshuieconomicregion,butalsocanillustratethespatialdistributionrulesofitverywell.原文[周自翔,李晶,任志远.基于GIS的关中—天水经济区地形起伏度与人口分布研究.地理科学,2012,32(8):951-957.]原文
[37]  GB/T919-2002.CodeforHighwayClassification.StateStandardofthePeople'sRepublicofChina,2002.[GB/T919-2002.公路等级代码..中华人民共和国国家标准,2002.]
[38]  LorenzMO.Methodofmeasuringtheconcentrationofwealth.PublicationsoftheAmericanStatisticalAssociation,1905,70(9):209-219.ResearchGate
[39]  HanJiafu,LiHongsheng,ZhangZhong.ClassificationmethodofpopulationdensitymapbasedonLorenzcurve.JournalofGeo-informationScience,2009,11(6):833-838.Differentfromtraditionalresearcheswhichfocusonstatisticsaccuracyandrepresentationeffectsofchoroplethmap,anewautomaticmethodofdeterminingclassintervalsinrepresentingknowledgeofpopulationdistributionisproposedinthispaper.BasedonpopulationdistributionLorenzcurve,themethodcandeterminethenumberofclassesbyrequirementofknowledgetransferaswellasdeterminetheclassintervalviatheDouglas-Peuckersimplificationmethod.Experimentsofthemethoddemonstratethepotentialofrepresentingpopulationdistributionpatternsandtheimprovementofmapinformationtransfer.Duringsimplification,thetwoclassintervalmapshowstheapproximateoutlineof"Huline".Thepopulationdistributionpatternsandknowledgeofparticularcasesareeasilyunderstoodfrommapsofthreeormoreclassintervals.DOI:10.1016/S1874-8651(10)60080-4原文[韩嘉福,李洪省,张忠.基于Lorenz曲线的人口密度地图分级方法.地球信息科学学报,2009,11(6):833-838.]与传统上地图分级的研究重点关注分级统计精度和图面效果不同,本文提出了一种用于表达和传输人口密度空间分布知识的自动化地图分级方法。该方法基于人口密度分布Lorenz曲线,根据知识传递的需要确定制图分级数,通过Lorenz曲线化简的方法确定分级间隔,以更好地表达人口空间分布的规律性知识,增强地图信息的传输效果。试验表明,分为两级时该方法能够自动地得出"胡焕庸线"的基本轮廓,分为多级时能够很好地体现人口空间分布的基本规律和特例知识。DOI:10.3969/j.issn.1560-8999.2009.06.021原文
[40]  DongChun,LiuJiping,ZhaoRong,etal.Adiscussiononcorrelationofgeographicalparameterwithspatialpopulationdistribution.RemoteSensingInformation,2002(4):61-64.[董春,刘纪平,赵荣,等.地理因子与空间人口分布的相关性研究.遥感信息,2002(4):61-64.]通过建立包括居民地、公路、铁路、水系、高程带、坡度带、坡向带、土地覆盖等要素内容的地理因子库,以及包括国民经济和社会发展主要指标的经济因子库,提取在一定区域内与人口分布密切相关的因子组成,并以其归一化相关系数作为定量分析的权重系数。本文提出的是实现人口在空间单元内遵循人口分布规律的空间化分布的一种尝试。DOI:10.3969/j.issn.1000-3177.2002.04.014万方
[41]  LiuXinhua,YangQinke,TangGuo'an.ExtractionandapplicationofreliefofChinabasedonDEMandGISmethod.BulletinofSoilandWaterConservation,2001,21(1):57-62.BasedonmicroscaleDEMdatum,optimumsizeofanalysiswindowsofrelief,whichis5km脳5km,isdefinedbymeansofwindowsanalysisandsamplestatisticalmethod.ReliefinsoilerosionofChinahasbeenextractedusingARC/INFOsoftwareandmappedusingArcview.ApplicabilityofreliefwasanalyzedandinitiallyapplicationofrelieffactorinassessmentofChinesepotentialsoilandwaterlossisstudied.CrossRef[刘新华,杨勤科,汤国安.中国地形起伏度的提取及在水土流失定量评价中的应用.水土保持通报,2001,21(1):57-62.]基于全国1:100万的栅格数字高程模型(DEM)数据,在ARC/INFO的GRID模块支持下,利用窗口分析方法,经过采样统计,确定中国水土流失地形起伏度的最佳分析窗口大小为5km×5km;基于5km×5km的分析窗口,提取了中国水土流失地形起伏度,完成了中国水土流失地形起伏度制图;最后对中国水土流失地形起伏度进行了适用性分析,并将其初步应用于中国潜在水土流失评价DOI:10.3969/j.issn.1000-288X.2001.01.015CrossRef
[42]  ElvidgeCD,BaughKE,KihnEA,etal.Relationbetweensatelliteobservedvisiblenearinfraredemissions,population,economicactivityandelectricpowerconsumption.InternationalJournalofRemoteSensing,1997,18(6):1373-1379.Tand
[43]  WangHerao,ZhengXinqi,YuanTao.OverviewofresearchesbasedonDMSP/OLSnighttimelightdata.ProgressinGeography,2012,31(1):11-19.Thestablelighttimedata,theradiance-calibratednighttimelightintensitydataandthenonradiance-calibratednighttimelightintensitydataarethethreemajorproductsthathaveemergedinthefieldoftheDMSP/OLSnighttimelightdata.Ithasseveraladvantages,namely,easyacquisitionofdata,detectionoflow-intensitylights,unaffectedbyshadows,convenientprovisionofconditionsforurbanizationstrengthanditsspatial-temporaldifferenceanalysis,andsoon.Atpresent,therearemanyresearchresultsonDMSP/OLSdata,whichmainlyfocusoncitydevelopment,humanactivityandeffect,eco-environmentimpact,buttherearefewstudiesonsystematicresults.ThispaperanalyzedtheexistingresearchesonDMSP/OLSdata,summarizedanddrewsomeconclusionsbasedontheexistingresearchresults,thetechnicalmethodsandtheadvantagesanddisadvantagesofthemethods,aswellasexploredtheapplicationprospectofDMSP/OLSnighttimelightaverageintensitydata.Itpredictedthefutureresearchtrendsofthedata:(1)anin-depthstudyonprocessingmethodsofthedata;(2)furtherexpansionofdataapplication;(3)theintegratedstudyonDMSP/OLSdataandotherdatamodelsneedtobedeepened;(4)combinetheexistingresearchresults,makefurtherresearchonmechanismissuesofgeographyphenomenon.原文[王鹤饶,郑新奇,袁涛.DMSP/OLS数据应用研究综述.地理科学进展,2012,31(1):11-19.]DMSP/OLS夜间灯光数据主要包括稳定灯光数据、辐射标定夜间灯光强度数据、非辐射标定夜间灯光强度数据3种产品。该数据产品具有获取容易、能够探测低强度灯光、不受光线阴影影响、方便为城市化强度及其时空分异分析提供条件等优点。目前,关于DMSP/OLS数据的研究成果已有很多,主要集中于城市发展研究、人类活动及效应研究、生态环境影响研究等方面,但对成果的系统归纳总结性研究却几乎没有。基于此,本文分析比较了现有DMSP/OLS数据研究实例,针对已有成果研究目的、技术方法以及方法优缺点等进行归纳总结,探索DMSP/OLS夜间灯光平均强度数据的应用前景。最后,总结了该数据的未来研究趋势:①对数据本身处理方法深入研究;②数据应用领域应进一步扩展;③DMSP/OLS数据与其他数据模型的集成研究应进一步深化;④将现有研究成果结合,进一步研究地理现象机制问题。DOI:10.11820/dlkxjz.2012.01.002原文
[44]  ZhuZhuo.PopulationGeography.Beijing:ChinaRenminUniversityPress,1991.[祝卓.人口地理学.北京:中国人民大学出版社,1991.]

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