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GEOGRAPHICAL RESEARCH >

2015 , Vol. 34 >Issue 9: 1733 - 1743

DOI: https://doi.org/10.11821/dlyj201509011

Orginal Article

Research of citizenship pressure based on the spatial pattern of population

  • YAN Dongsheng , 1, 2, 3 ,
  • CHEN Wen 1, 2 ,
  • LI Pingxing 1, 2
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  • 1. Nanjing Institute of Geography and Limnology, CAS, Nanjing 210008, China
  • 2.Key Laboratory of Watershed Geographic Sciences, CAS, Nanjing 210008, China
  • 3. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2015-03-27

  Request revised date: 2015-06-04

  Online published: 2015-09-15

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《地理研究》编辑部
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Abstract

Since the reform and opening up, the large-scale migration in China has caused dramatic changes in population distribution, which has become a hot research field of human geography. Drawing upon official census data in 2010, this paper investigates the spatial distribution of registered population (huji renkou), resident population (changzhu renkou) and the relationship between them with the help of exploratory spatial data analysis (ESDA). The results indicate that: (1) The overall distribution of both the resident and registered population is consistent with the Demarcation Line from Heihe of Heilongjiang Province in the northeast to Tengchong of Yunnan Province in the southwest, namely the "Hu Huanyong Line", reflecting a strong spatial agglomeration in the east coastal regions. (2) Registered and resident population are mainly concentrated around the traffic lines and economic belts. Furthermore, the distribution of resident population is based on a stronger oriented economy. (3) By incorporating the method of ESDA, we also reveal the distinct patterns of migration on the whole: migration patterns demonstrate an obvious tendency from the central to the eastern regions of China. (4) The population migration also leads to an obvious difference between hot spot regions of registered and resident population. Although the range of hotspots are different between registered and permanent population, both of them are clustered in the Pan Pearl River Delta and the core areas of the Yangtze River Delta. In addition, the authors apply the ratio of registered and resident population and per capita GDP to identify the four different categories, and then analyze per capita GDP, the ratio of registered and resident population, citizenization pressure and interrelation among them, which may provide references for urbanization research.

Key words： resident population; registered population; spatial distribution; citizenization

Cite this article

YAN Dongsheng , CHEN Wen , LI Pingxing . Research of citizenship pressure based on the spatial pattern of population[J]. GEOGRAPHICAL RESEARCH, 2015 , 34(9) : 1733 -1743 . DOI: 10.11821/dlyj201509011

1 引言

中国人口总量大,区域自然禀赋和社会经济差异较为明显,人口分布也较为复杂[1]。特别是改革开放以来的体制改革深化、沿海工业化和城镇化率先推进,从农村向城市、从落后地区向发达地区的人口转移成为众所瞩目的人口流动现象[2],1982年流动人口占全国总人口比重仅为0.65%,到2010年已超过17%。流动人口的大量出现在促进经济发展的同时也对流入地城市的管理形成空前的考验[3]。2011年,中国的城镇化率首次超过50%,2014年初出台的《国家新型城镇化规划（2014-2020）》将进一步加快城镇化进程。随着新型城镇化战略及户籍制度改革的实施,人口流动和分布格局可能再次出现调整,一些城市人口较快增长,管理压力明显增大;另一些城市人口有可能呈负增长,甚至出现空城和产业衰退[4]。在此背景下,人口分布研究对协调区域人口、经济、资源环境发展,推进新型工业化、新型城镇化和农业现代化互动具有重要意义[5]。
人口分布是指一定时间内人口在地理空间中的分布、集散及组合情况[6],广义概念是人口发展过程中的空间表现形式,狭义概念是人口数量在空间上的分布[4]。人口分布研究以胡焕庸线的提出最为著名。近年来,中国学者从不同层面研究了中国的人口分布规律：国家层面上,人口分布依然呈现“东密西疏”的格局[7,8],中部地区人口大量迁出[9],东南沿海及东北和西北部分省份成为中国人口潜力最大的地区[5],也是未来城镇化吸收人口较大的区域;区域层面上,城市不均衡发展带来了人口大规模、规律性迁移[4,10],人口由外围向核心城市聚集趋势明显,其引力范围也由少数核心城市主导向多中心集聚与核心城市腹地扩散并存的阶段转变[11];在城市层面上,部分发达城市郊区化趋势明显,人口分布的多核心结构日渐成熟[12,13]。
人口研究的关键在于对人口数据的把握。受户籍制度影响,中国的人口涉及较多概念包括户籍人口、常住人口、外来人口、流动人口等。在推进新型城镇化背景下,户籍人口与常住人口分布及其对比研究有助于把握流动人口的分布特征,也同样有助于辨析不同城市市民化压力差异。城市的财政及规划管理主要依据户籍人口进行[14];作为城市经济和社会物质实体的主要载体,常住人口是城市基础设施等的实际使用者。人口大规模迁移导致区域户籍人口和常住人口规模存在较大差异,给城市规划管理带来困难,而基于户籍制度的人口差异化待遇不利于城镇化质量的提升[14]。但已有研究更多地针对户籍人口[13]、常住人口[15,16]、外来人口[17,18]及流动人口[3,19]等进行单一研究,将户籍人口、常住人口联系在一起并进行对比研究相对少见。常住人口与户籍人口结合的研究不仅反映不同城市的人口集聚与扩散能力及状况,还可以在一定程度上测度不同城市“市民化”压力差异,具有一定的实践价值。
提升城镇化质量,需要适时推进外来人口的市民化进程。《国家新型城镇化规划（2014-2020年）》要求政府承担外来人口市民化的任务。由于户籍制度的差异,多数外来人口的市民化需求并没有得到满足和保障。因此,市民化压力更多地体现在如何为外来人口提供与本地市民趋同的公共服务上,而哪些人应该市民化及其数量如何就成为影响市民化压力的重要内容。考虑到中国人口统计口径的差异,相对常住人口而言,流动人口的流动性更大,因此基于常住人口的市民化推进不仅考虑到部分常住流动人口,还可以避免因人口流动性过大而带来的公共资源配置的浪费。因此,以地级市为基本研究单元,采用常住人口与户籍人口的比值来测度不同地区市民化压力,便于识别中国人口流动的影响因素。通过分析户籍人口与常住人口分布特征及其关联性,研究中国的人口空间分布特征,同时反映人口迁移趋势;针对常住人口/户籍人口比值的分析,把握人口流入地与流出地的分布状况,显示不同地区“市民化”压力差异。

2 数据来源与研究方法

2.1 数据来源

为准确把握人口总量分布、集聚特征及人口迁移趋势,以地级市为基本研究单元,参考相关研究区域划分[7],以27个省（自治区）的下一级行政区和4个直辖市为基本研究单元 (基本单元主要为地级市,但包括4个直辖市及部分县,如海南省的部分行政单元为县。)。其中,港澳台及金门县等由于特殊的行政区划、人口普查数据缺失等因素不在研究范围之内。运用探索性空间数据分析（ESDA）方法,分析户籍人口、常住人口分布的基本特征及其关联性。研究户籍人口、常住人口比值的分布特征来测度不同地区市民化压力,具有较强的典型性。
人口数据来源于2010年第六次人口普查数据,人口为市域人口总量,分为常住人口和户籍人口;GDP数据来自于《中国城市统计年鉴2011》,部分数据来自于2010年各市的国民经济和社会发展统计公报。其中,人均GDP为GDP总量与常住人口的比值。

2.2 研究方法

人口在一定的地域环境下并不是随机分布的,而是呈现出一定的空间分布形态[6]。人口的空间集聚特点可以较为直观地表征人口集中分布的整体规律;而针对户籍人口与常住人口空间集聚区域差异的对比,可以在宏观上把握中国人口的流动大趋势。此外,针对常住人口、户籍人口比值集散的分析,可以清晰地了解中国人口净流入、净流出空间集聚特征,还有助于识别不同地区间市民化压力差异。
ESDA分析技术是用来揭示空间异质形式与空间作用机制的技术方法[7],包括全局自相关和局部自相关。全局性指标用于检验区域的空间模式,局部性指标反映一个区域单元上某种属性值临近区域单元上同一属性值的相关程度[13]。全局性指标反映了中国人口分布的整体集散规律、局部性指标可以了解人口总量（比值）较大、较小区域的分布状况,进而为把握人口流动规律、了解市民化压力差异提供依据。
2.2.1 全局Moran's I 全局Moran's I是测度总体空间自相关水平的度量指标,反映人口空间集聚格局的整体特征,其计算公式如下[7]：
I = n S 0 × z ' Wz z ' z （1）
式中：z为n个单元的人口标准化后所得到的的列向量;W为行标准化后的空间权重矩阵（其行和为1）,此时, S 0 = ∑ i = 1 n ∑ j = 1 n w i , j * = n 。如果系数I大于期望值E(I)=-1/(n-1),则意味着人口总量高（低）的与其他总量高（低）的集聚在一起;反之,则意味着人口总量高（低）的与其他总量低（高）的集聚在一起。系数I为显著时,则表示在总体上全国人口分布存在空间集聚效应。
2.2.2 局部Getis-Ord Gi* 全局Moran's I并未对空间自相关的区域结构进行评价,无法反映区域内部空间集聚的特征[7]。为了反映某区域周围相似属性值的空间聚集程度,需要研究区域的局部空间自相关[13]。利用ArcGIS 9.3软件中的热点分析工具,对数据集中的每一个研究单元的相关要素计算Getis-Ord G i * ,得到对应的z得分,获得高值或低值要素在空间上发生聚类的位置。局部的Getis-Ord G i * 的计算公式如下：
G i * = ∑ i = 1 n w i , j x j - X ̅ ∑ j = 1 n w i , j S × n ∑ j = 1 n w i , j 2 - ∑ j = 1 n w i , j 2 n - 1 （2）
式中：xj是地区j的人口总数;wi,j是地区i和j之间的空间权重;n为研究单元总数; X ̅ 和 S 的计算公式分别如下：
X ̅ = ∑ j = 1 n x j n （3）
S = ∑ j = 1 n x j 2 n - ( X ̅ ) 2 （4）
计算过程中,数据集中的每个要素返回的 G i * 值即为z得分。其原理为：某一个高值要素要成为具有显著统计学意义的热点,那么该要素在具有高值的基础上,必须被其他同样具有高值的要素所包围;冷点原理同理。对于显著性的正的z得分,z得分越高,热点的聚类就越紧密;对于显著性的负的z得分,z得分越低,冷点的聚类就越紧密。

3 人口空间分布格局

3.1 人口分布的概况分析

根据2010年第六次人口普查分析,中国的户籍人口、常住人口仍呈现东多西少的格局,人口分布的胡焕庸线依然存在。常住人口超千万的研究单元更多集中在东部沿海地区,人口有向东部沿海发达地区集聚的趋势（图1、图2）。
Fig. 1 The spatial distribution of resident population

图1 户籍人口分布状况

Fig. 2 The spatial distribution of registered population

图2 常住人口分布状况

户籍人口与常住人口均集中在胡焕庸线以东（图1、图2）,沿交通线、经济带集聚,东部沿海经济带、京广线、哈大线、成昆线、厦蓉高速、四川盆地及长江流域是人口集聚区;但与户籍人口较为明显的连片分布格局不同,常住人口的连片格局较弱,人口向中部省会都市圈、东部沿海城市群及部分发达地区集聚的趋势较为明显,经济指向性较强。在胡焕庸线以西,各研究单元人口总量偏小,人口总量相对较大的研究单元多集中在胡焕庸线附近;此外,青藏高原是人口低值集聚区;塔里木盆地和蒙古高原人口总量也相对较大。西部地区人口分布与区域地形起伏度相关性较大[16],而中东部地区人口分布的经济指向性较为明显。
对人口分布的对比研究可以判断出人口迁移的趋势。胡焕庸线以西人口迁移规律相对简单：除锡林郭勒盟常住人口较户籍人口增长明显外,其他地区的户籍人口与常住人口总量比较类似,人口净流入（出）并不明显;胡焕庸线以东人口迁移、集聚趋势显著,向东部沿海、中部少数地区集聚;最为明显的是珠三角 (珠三角包括广州、深圳、佛山、东莞、中山、珠海、惠州、江门、肇庆共9个城市)核心地区常住人口相比于户籍人口增长较为明显,而晋冀鲁皖豫、四川盆地等欠发达地区的常住人口较户籍人口有明显减少、常住人口的连片区域变小。哈尔滨市在吸引外来人口上较为突出,成为东北地区唯一常住人口超千万的城市。人口向经济较为发达的省会城市、东部沿海地区集聚的格局较为明显。

3.2 人口空间集聚规律定量测度

针对中国人口分布的总体格局,分别采用全局空间自相关的Moran's I指数和局部空间自相关的Getis-Ord G i * 测度其空间集聚状况。
3.2.1 全局空间自相关分析 户籍人口的全局Moran's I指数为0.213,z得分为16.881;常住人口的全局Moran's I指数为为0.181,z得分为14.253。二者均在0.001显著性水平上存在空间聚集性,且户籍人口的空间集聚性较为显著,呼应了图1和图2中户籍人口和常住人口的分布格局：户籍人口高低值特别是高值研究单元连片分布特征比常住人口更明显。
3.2.2 局部空间自相关分析 采用Getis-Ord G i * 指数测度出户籍人口和常住人口分布的冷热点区域（图3、图4）。户籍人口的热点和次热点比常住人口的分布区域更广;冷点和次冷点、热点和次热点明显的分布在胡焕庸线东西两侧,且次热点和次冷点主要围绕热点和冷点分布,连片趋势明显。
Fig. 3 The hot spots distribution of resident population

图3 户籍人口冷热点分布

Fig. 4 The hot spots distribution of registered population

图4 常住人口冷热点分布

户籍人口的热点和次热点研究单元数量分别为81和36,常住人口的仅为69和21;说明常住人口向少部分研究单元集聚。户籍人口的热点和次热点区域集中在京津冀、鲁皖豫及苏北地区和四川盆地,呈“哑铃状”连片分布;流动人口分布的空间集聚[14,20]带来常住人口的热点区域集中在珠三角地区、四川盆地核心区、京津唐—山东半岛—长三角城市群等经济发达地区。二者对比发现,热点和次热点减少的区域也是中国人口净流出较大的地区,集中在中国经济较为落后且户籍人口总量大的区域,其连片分布一方面显示中国经济落后地区“集中连片”的状况;另一方面也显示了常住人口分布较强的经济指向性。
二者的冷点和次冷点区域集中在西部的林芝地区、昌都地区、迪庆藏族自治州、巴彦淖尔市、乌海市、塔城地区、阿勒泰地区及北部湾的湛江市、北海市、防城港市等,多为发展较为落后的、边远地区,人口规模总量小,对外吸引力不足。海南省各研究单元市域面积较小,导致人口总量较少而成为冷点区域。

4 常住人口与户籍人口的相对关系及其分布格局

4.1 常住人口、户籍人口比值分布格局

中国常住人口、户籍人口比值分布具有集聚与分散并存的格局。与图1、图2中高值分布格局不同,图5中常住人口、户籍人口比值较高的区域除集中在东部沿海发达地区和中部若干分散研究单元外,在胡焕庸线以西也有连片区域分布。作为中国发展的前沿地带,东部地区依靠良好的区位及优惠政策率先发展,成为中国流动人口的重要集中地,比值较高;西部大开发战略的实施带来大量外来人口,加之户籍人口较少导致西部研究单元的比值较高;中部地区户籍人口较多且增长较快,加之经济较为落后导致人口外流造成常住人口、户籍人口比值普遍较低,呈低值连片分布状况。
Fig. 5 The ratio distribution of resident and registered population

图5 常住人口与户籍人口比值分布图

常住人口、户籍人口比值超过150%的研究单元共10个,其中有9个分布在东部沿海地区,最高的东莞市为443.33%。造成这些地区比值较高的原因存在一定的差异：北上广深作为全国或区域重要的政治、经济、文化中心,以独有的优势、发达的经济、完善的基础设施等具有极大的吸引力;珠三角的4个城市及苏州市是中国较早实行改革开放和接受三来一补的地区,对寻求就业的流动人口有着极大的吸引力;作为沿海宜居的改革开放城市厦门市,依其良好的环境、发达的经济吸引大量外来人口进入;随着西部大开发及东部产业转移[21],乌鲁木齐市作为西部中心城市之一,对周边地区的人口具有较强的吸引力是重要原因。
比值低于80%的研究单元共有13个,东中西部分别有1个、5个和7个,最低的广安市比值为68.68%。西部贵州、四川及内蒙古的研究单元,就业岗位少,人口主要向东部沿海地区特别是泛珠三角区域迁移[9];而中部安徽、河南、湖北等地区,伴随着农业机械化水平的提高,农村出现大量的富余劳动力向东部沿海发达地区及部分西部地区转移;茂名市作为粤西地区较为贫困的城市,区域内经济发展差距明显,其人口较多流向珠三角核心区;人口大量的外移导致这些研究单元的比值较低。

4.2 常住人口/户籍人口比值空间集聚规律的分析

针对中国人口分布总体格局的状况,分别采用全局空间自相关的Moran's I指数和局部空间自相关的Getis-Ord G i * 测度中国人口分布空间集聚状况的差异。
4.2.1 全局空间自相关分析 常住人口、户籍人口比值的全局Moran's I指数为0.179,z得分为15.533,在0.001显著性水平上存在显著的空间聚集性。与常住人口或户籍人口总量分布相比,其空间集聚性最小。这主要由于常住人口、户籍人口比值较高、较低的地区呈分散分布的格局,连续性较弱。
4.2.2 局部空间自相关分析 使用Getis-Ord G i * 指数测度比值分布的冷热点区域,结果如图6。由于研究单元的常住人口、户籍人口比值以处于中间状态居多,导致绝大部分区域并未形成热点或冷点区域。热点及次热点分布在东部地区,冷点及次冷点集中在中部地区。
Fig. 6 The hot spots distribution of the ratio of registered and resident population

图6 常住人口与户籍人口比值的冷热点分布

针对比值分布的冷热点分析,热点研究单元共有21个,分布在珠三角及厦漳泉经济圈;次热点研究单元有8个,集中在长三角及海峡西岸;而京津冀都市圈未形成热点或次热点区域。在泛珠三角 (泛珠三角包括福建、广东、广西、贵州、海南、湖南、江西、四川、云南、香港和澳门。)、长三角一体化过程中伴随着产业的大量集聚[10],导致流动人口大多数流向泛珠三角及长三角核心区[2]。京津冀地区随着经济体制改革的深化,重工业开始衰落,对外来人口吸引力变弱[7],核心城市的带动作用较弱且区域内发展差距较大,外围城市对人口吸引力有限而未能形成热点、次热点区域。
与热点区域不同,冷点区域呈集中连片分布,冷点区域的研究单元共有12个,分布在豫南、皖北及四川盆地等地区;次冷点区域共有47个,集中在冷点区域的周边地区;二者形成集中连片格局。这些区域多是中国经济较为落后、户籍人口总量较大的区域。冷点区域、次冷点区域的集中连片性,说明中国人口外流以及经济相对落后的区域具有较强的连片分布特征。

5 基于比值差异及影响因素的 研究单元类型划分

影响人口空间分布的因素众多[7],不同地区间具有一定的差异性。经济因素是影响人口分布的重要因素（分类的四象限图表明,人均GDP与比值呈现一定的正相关）;前文中关于人口分布及迁移的研究也表明,中国的人口流动具有较强的经济指向性。因此,基于常住人口、户籍人口比值、人均GDP的差异,将研究单元分为以下四类（图7）。
Fig. 7 The four categories based on the ratio of registered and resident population and per capita GDP

图7 基于常住人口与户籍人口比值及人均GDP的研究单元类型划分图

（1）高—高型：人口净流入区域,人均GDP高于平均值,占研究单元总数的24.8%。多以城市群形式集聚在较为发达的东部沿海地区、西部祁连山及蒙古高原等地形起伏较小[16]的宜居地区、中部省会城市及部分较为发达的地区。依靠优越区位、发达的经济成为全国、区域的人口引力中心,成为人口流入区;但不同研究单元之间的“市民化”压力存在较大差异：① 北上广深等较为发达的地区,作为区域政治、经济中心,集中了较多的优势资源[3];随着第二、第三产业,特别是就业吸纳能力最高的第三产业加速发展,提供多样化的就业岗位,对流动人口的吸引力较大,吸引了大量的外来人口[4,22]。中部省会城市依靠较多的就业机会、相对的高工资及低成本的居住空间[18],吸引较多的省内跨市流动人口[23],对省外人口的吸引力有限。在新型城镇化过程中,这些地区是全国、区域经济发展的动力,也是优势资源集中地,外来人口落户期望高;但制度是影响外来人口居住身份的重要因素[24],较为严格的户籍制度导致常住人口、户籍人口的比值较大,市民化压力较大。② 以东莞、佛山为代表的东部沿海地区依靠良好的区位、低廉的成本等率先接受海外产业转移[10],聚集了大量从事加工、制造的企业,提供大量的就业机会[14],吸纳了较多的外来劳动力[4],外来人口多于甚至数倍于户籍人口;以阿拉善盟、克拉玛依市为代表的西部地区,随着西部大开发政策的推进,经济增长加快、对劳动力需求增大,成为新的人口吸引中心[9],常住人口、户籍人口比值较大,但小于东部沿海地区。这些研究单元外来人口年轻化趋势明显,工作往往随产业转型和转移迁移,流动性较强;尽管户籍制度相对宽松,但外来人口落户的欲望并不强烈,市民化压力较小。但随着新型城镇化的推进,针对外来人口公共服务供给的增加,政府的财政支出压力逐渐增大。
（2）高—低型：人均GDP高于平均值、人口净流出区域,占研究单元总数的11.4%。围绕“高—高型”研究单元分布,主要位于京津冀、山东半岛、长三角、海峡西岸等城市群的外围地区、中部部分靠近省会的相对发达地区;这些地区在接受经济较为发达的核心区经济辐射下,经济相对发达;但同时也受到核心区人口较强吸引力的作用,处于核心区人口集聚“阴影区”下,人口向更为发达的核心区集聚[6,9],市民化压力较小;较为典型的如江苏省内的苏南与苏中城市之间的关系：苏中城市在接受苏南产业转移的同时部分人口也向苏南集聚,导致苏中城市人均GDP相对较高,但人口依然向外流出[4]。
（3）低—高型：人口净流入区域（比值以100%~110%居多）,人均GDP低于平均值,占研究单元总数的11.2%。主要集中在经济较为落后的西部、东北等边缘、交界地区,多为少数民族集聚区;区域文化的差异[2]、较低的交通可达性、出行的高成本等均限制了人口向外流动[4,22,24]。由于西部大开发,中部地区部分劳动力向西部地区流动[21],西部地区成为新的人口吸引中心[9],导致部分研究单元常住人口、户籍人口的比值超过100%;东北部分研究单元,良好的工业基础及东北老工业基地振兴的机遇为其吸引外来人口奠定了基础。但流动人口的就业指向强,流动性也较大,落户意愿较低,市民化压力较小;随着国家要求当地政府为外来人口提供公共服务,这些研究单元由于经济欠发达、市民化压力将趋于增大。
（4）低—低型：人口净流出区域,人均GDP低于平均值,占研究单元总数的52.6%。这些研究单元呈现出明显的集聚分布格局,主要集中在中部地区、东北地区;经济欠发达、人口外流的连片集聚格局显示了中国区域发展格局中欠发达地区集中连片的状况。这些研究单元经济发展水平较低,缺乏充足的就业岗位,对流动人口的吸引力较小[2]。在沿海发达地区强大经济吸引及西部大开发的双面夹击下,区域内缺乏大量突出的吸引中心[21],成为中国主要的人口迁出地带,新型城镇化过程中市民化压力较小。但研究单元内部存在较大区别,以重庆市为例,核心市辖区为人口净流入区域,市民化压力较大;而周边人口净流出的市辖县反而面临人口流失的压力。

6 结论

人口分布研究对中国的经济社会发展具有重要的现实意义,对新型城镇化建设过程中人口市民化及相关政策的制定也具有重要的参考价值。基于2010年第六次人口普查数据,研究中国常住人口、户籍人口的空间分布规律,同时基于常住人口、户籍人口比值及人均GDP进行了研究单元分类研究。主要结论如下。
（1）户籍人口、常住人口分布均呈现“东多西少”的格局,沿交通线、经济带集聚趋势明显。胡焕庸线以西常住人口、户籍人口分布差异较小;胡焕庸线以东差异显著,与户籍人口集中连片趋势不同,常住人口的连片格局较弱。ESDA分析一方面显示了人口空间集聚性,同时也表征了人口分布与流动特征。整体上,西部地区人口分布与地形相关,而中东部地区人口分布的经济指向性较强。
（2）中国的人口迁移具有较强的经济指向性,从中西部地区向东部地区迁移是其主要方向,人口迁移呈“大规模迁移、小范围集中”的整体格局;随着西部大开发及东部地区产业向西部的转移,部分流动人口开始向西部地区迁移。但整体上中国人口分布的不合理性依然存在,针对不同地区的发展状况、人力需求及市民化承载力,引导人口合理分布、优化人力资源空间配置是未来人口布局研究的重要内容。
（3）与总量分布不同,比值分布呈现东西较高而中部塌陷的状况,这与中国人口从中西部向东部迁移的大格局有关,也表明了中国中部地区是主要的人口外流区;而西部地区在西部大开发政策下对外来人口有一定吸引力。比值的冷热点分布与人口总量的冷热点分布差异明显,显示了人口外流区域集中连片格局及人口集聚的区域差异。
（4）研究单元分类研究发现,各类型研究单元在三大区域均有分布。经济因素及政策机遇带来的人口定向流动是地区间比值差异的主要因素;但作为一种探索性指标,常住人口、户籍人口比值并不能完全表征市民化压力的差异,外来人口的特征、研究单元的区域地位、国家政策及户籍制度等都是重要因素。因此,寻求户籍人口与常住人口失衡关键因素,区别化、针对性推进市民化进程是新型城镇化建设中的重要议题。
本文在前人研究基础上有所创新,也存在一些的不足：人口分布、结构及其影响因素是一个动态的、变化的过程,仅基于2010年第六次人口普查数据无法准确反映人口分布及其结构的变化特征;尽管全国范围的宏观研究有助于把握人口分布整体状况,但在一定程度上忽视了研究单元间及其内部的差异;而针对研究单元分类也存在一定的主观性;这些方面在后续研究中均需要不断完善,为识别不同尺度的人口特征,引导人口合理分布提供参考。
致谢：感谢中国科学院南京地理与湖泊研究所的孙伟副研究员、高金龙博士、陈欢硕士,以及中山大学地理科学与规划学院的李骞硕士在数据处理及文章修改等方面提供的无私帮助。

The authors have declared that no competing interests exist.

References

Publishing order | Descend order by publishing year | Descend order by cited within
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[Meng Xiangjing.An reasonable evaluation of Chinese population distribution. Population Research, 2008, 32(3): 40-47.]

[6]
苏飞, 张平宇. 辽中南城市群人口分布的时空演变特征. 地理科学进展, 2010, 29(1): 96-102.采用人口分布的结构指数和空间自相关分析方法,并结合GIS技术对20世纪90年代以来辽中南城市群人口分布的时空演变特征进行分析.研究结果表明:① 2007年,辽中南城市群的人口分布具有各地市人口总量差异较大、人口密度呈西高东低态势、市县人口密度差异显著、人口沿交通轴线集中分布、人口分布的局 部空间集聚现象十分显著等现状特征;②20世纪90年代以来,城市群的人几分布变化具有各地市人口增幅差异明显、人口分布具有不断集中趋势、人口重心逐渐 由东北向西南方向移动,人口分布趋同趋势不断增强等演变特征.研究结果表明空间自相关的统计分析方法能够更好地揭示出人口的分布特征、人口集聚及其变化的 热点,对于人口的合理布局方案等政府决策具有重要的参考价值.

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[Su Fei, Zhang Pingyu.Spatio-temporal dynamics of population distribution in the middle and southern Liaoning urban agglomeration. Progress in Geography, 2010, 29(1): 96-102.]The study of regional population evolution is helpful to reveal the rule of population distribution and is important for reasonably making population development policy,and for the promotion of regional sustainable development. By using population structure indexes,spatial auto-correlation analysis and GIS technology,the spatio-temporal dynamics of population distribution in the middle and southern Liaoning urban agglomeration have been analyzed since the 1990s. The results show that:(1) the population quantity of different cities in the middle and southern Liaoning urban agglomeration is quite different,with the density being higher in the west,and the distribution concentrated along traffic axes,and the population distribution of different cities presents distinct positive correlation in 2007. (2) Since the 1990s,there are many differences among the population amplitudes in different cities. The population distribution is of con-centration pattern,and the population centralization is enhanced. From 1993 to 2007,the center of gravity moves from northeast to southwest. This paper shows that statistic analysis of spatial au-to-correlation should be a good method to explore the hotspots and inner mechanism of distribution,centralization and change of population.

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[7]
陈刚强, 李郇, 许学强. 中国城市人口的空间集聚特征与规律分析. 地理学报, 2008, 63(10): 1045-1054.城市集聚增长日益显著以及城市 间连接性的增强等是20世纪90年代以来中国城市发展的显著特征。通过运用GIS环境下的Moran's I等技术方法,探讨了1990-2005年中国城市人口的空间集聚特征及其演变规律,结果表明:尽管总体上城市人口的正空间集聚性不强,但局部空间集聚特 征明显,存在较强的规律性,主要表现为"T"字型和沿主要铁路交通线的发展态势,而其演变过程体现了中国城市体系空间结构正处在不断优化之中;三大地带城 市人口空间集聚的特征反差明显,东部城市区域基本表现为一体化发展趋势,而中西部城市区域则趋向于极化发展或表现出较差的整体协调能力;进一步来看,城市 人口空间集聚的不平衡性,不仅体现于区域之间也体现于区域内部的城市之间,且其作用范围进一步扩大,集聚区位有所变化。总体来看,这一典型转型时期里,中 国城市人口的空间集聚特征及其演变,体现出了市场力量、经济发展状况、基础设施建设及国家空间开发政策等的积极作用。

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[Chen Gangqiang, Li Xun, Xu Xueqiang.Spatial agglomeration and evolution of urban population in China. Acta Geographica Sinica, 2008, 63(10): 1045-1054.]The increasing urban agglomerative growth and urban interactions has been a conspicuous feature of urban development in China since the 1990s.This paper makes an analysis on the spatial agglomeration and evolution of urban population in China, 1990-2005.The spatial data in this study are the cities and towns population of 451 cities in 1990, 662 cities in 2000 and 634 cities in 2005.Moran's I, one of Exploratory Spatial Data Analysis (ESDA) techniques, is the main method, and Moran's I statistics are obtained with the usual 5% significance level in this paper.In order to investigate the rationality of the empirical results, the transition probability matrices are applied to test its robustness, then the results are visualized by ArcGIS 9.0 soft in the research.The main conclusions are as follows:(1) The findings for the global spatial agglomeration of urban population are the existence of positive effect.Though the positive effect of the global spatial agglomeration is not strong, it is more or less increased from 1990 to 2005.On the other hand, the law of the local spatial agglomeration is obvious with a spatial agglomeration of a "T-shaped" pattern or along the main railroad lines, indicating that evolution of spatial structure of urban system has been optimized since 1990.(2) The diversity between HH spatial agglomeration of urban population in the East Zone and the LL ones in the Middle and West zones shows significant imbalance, while its changes show the imbalance had an extended trend during the 1990s and was mitigated in a way after 2000.At the same time, the effect and the changes of spatial agglomeration also suggest that the urban regions in the East Zone represent an integrative development while the ones in the Middle and West zones tend to the polarized development or less harmonious ability as a whole.(3) Furthermore, both different urban regions and the intra-urban regions have distinct state and changes of spatial agglomeration, which manifests that the spatial disparity is reflected not only between regions but also between intra-urban regions.The empirical results also show that the influencing scope of spatial agglomeration has expanded and the state and location of urban agglomeration has changed.(4) To a certain extent, the feature and its change of spatial agglomeration of urban population accord with the functions of market forces, economic development, construction of transport infrastructure, China's spatial development policies and so on.

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[8]
于文丽, 蒲英霞, 陈刚, 等. 基于空间自相关的中国省际人口迁移模式与机制分析. 地理与地理信息科学, 2012, 28(2): 44-49.人口迁移具有空间指向性,表现为迁入地和迁出地在地域上呈现一定的空间集聚特征.然而,大部分针对我国人口迁移进行分析和建模的研究忽视了这一空间指向性及其影响.该文利用全国第五次人口普查省际人口迁移数据和相关资料,以空间自相关分析为基础,对1995-2000年我国省际人口迁移的空间模式与动力机制进行了初步分析.首先,运用全局空间自相关统计量(Moran's I)对人口迁移流中的空间自相关程度进行了测度,发现研究期间我国省际人口迁移的空间指向性明显:从一个区域出发(或抵达一个区域)的人口迁移流均受到周边地区人口迁移的影响.为了进一步研究这种空间指向性对人口迁移规模的影响,分别采用重力模型(仅用距离变量捕捉人口迁移过程中的距离衰减效应)和空间 OD模型(采用因变量空间滞后的不同形式对迁移流的空间指向性加以考虑)研究中国省际人口迁移的动力机制,对比两种模型的估计结果发现:1)空间OD模型在参数估计和模型拟合等方面均优于传统的重力模型；在选取相同解释变量的情况下,空间OD模型的残差平方和仅为传统重力模型的47％,模型拟合指标AIC 值也大大缩小.2)在对中国人口迁移动力机制的定量分析中,如果不考虑人口迁移流之间的空间自相关(空间指向性)现象,会导致对社会、经济等变量作用和距离衰减效应的过高估计.

[Yu Wenli, Pu Yingxia, Chen Gang, et al.Spatial analysis of the patterns and mechanism of inter-provincial migration flows in China. Geography and Geo-Information Science. 2012, 28(2): 44-49.]Migration flows exhibit some spatial patterns in the origin and destination places.By employing inter-provincial migration data from 2000 National Census and some social and economic data in Chinese Statistical Yearbook,the authors attempt to explore the spatial patterns of inter-provincial migration flows between 1995 and 2000 and explain the mechanisms behind the observed patterns.Firstly,global spatial autocorrelation statistics of Moran′s I is used to investigate the spatial autocorrelation in the origin and destination places.The spatial autocorrelation analysis of outmigration flow from some specified province is conducted and iterated one by one at the provincial level.Except the central provinces of Sichuan,Chongqing,Hubei,Shaanxi,Henan and Xinjiang Uygur Autonomous Region,all other provinces have positive estimated Moran′s I values.Similarly,the estimated Moran′s I values of immigration flows to all provinces are positive,which means that distance does have decay effects in the process of population migration.Then,the traditional Gravity and Spatial OD models are constructed to characterize the spatial spillover effects among migration flows and a comparison is made between the traditional Gravity and Spatial OD models.The empirical results indicate that:1) The distance decay effect in Gravity model is statistically significant at the significance level of 1%;population,FDI and education level in the destination places have expected positive sign in the estimated model and are statistically significant at the significance level of 1%;population,landuse,sex rate in the origin places do have expected positive sign and are statistically significant at the same significance level.2) Based on the spatial analysis of outmigration and immigration flows,the Spatial OD model of lagged dependent variables is constructed to fit the spatial interaction among migration flows.In comparison with the traditional Gravity model,the goodness-of-fit of the Spatial OD model is much better,which has smaller AIC value.At the same time,the estimated parameters of origin and destination places are also smaller than those of traditional Gravity model,which indicates that the influences of origin and destination places may be exaggerated in the traditional analysis.In this paper,while the spatial dependence of migration flow is modeled by spatial lagged dependent variable,further research is needed to investigate the specification of spatial lagged independent and spatial autoregressive error models.

[9]
刘盛和, 胡章, 邓羽. 基于区域差异类型的流动人口快速监测方法. 地理研究, 2011, 30(4): 676-686.改革开放以来，我国流动人口增长迅猛，但目前我国还缺乏对流动人口进行快速动态监测的有效方 法与方案，特别是未能考虑我国流动人口的区域差异性，这已成为各级政府在进行科学决策和及时行动时的主要制约因素之一。本文尝试提出一种基于区域差异的我 国流动人口快速监测方法，旨在应用流动人口区域差异的知识来改正流动人口监测样点网络布局方案和监测指标体系，突出监测重点，节约监测成本，提高监测绩 效。该方法依次由划分流动人口区域类型、制定监测样点网络布局方案、设计监测指标体系、估算流动人口规模与特征、数据校核及区域类型调整等五个步骤所组 成。

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[Liu Shenghe, Hu Zhang, Deng Yu.A rapid monitoring method on floating population in China based on its regional differentiation types. Geographical Research, 2011, 30(4): 676-686.]Since the start of opening and reform up in 1978,China's floating population has been increasing dramatically and has had strong influences on its urbanization and regional development.However,China is lack of an effective rapid monitoring method on its rapid increasing floating population,in particular the regional differentiation of floating population has never been considered by the current monitoring methods,which has in fact become major constrains to scientific decision-making and just-in-time action of governments at all levels.By applying the scientific research and knowledge to the regional differentiation types of floating population in China to improve its monitoring methods,this paper proposes a new rapid monitoring method on floating population based on its spatial differentiation and regional types.This method consists of 5 steps or components as follows:(1) to identify regional differentiation types of floating population,(2) to design an effective spatial network of monitoring sample regions,(3) to construct various monitoring indictors for different regional types according to their specific characteristics of floating population,(4) to estimate the total number and characteristics of floating population in the whole country or a certain region,and(5) to check up with new census data and to readjust the identification of regional differentiation types.Because this method can distinguish the active regions from the inactive regions of floating population,it can identify hot spots,reduce the number of monitoring region samples and thus enhance the efficiency.

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[10]
游珍, 王露, 封志明, 等. 珠三角地区人口分布时空格局及其变化特征. 热带地理, 2013, 33(2): 156-163.

[You Zhen, Wang Lu, Feng Zhiming, et al.Spatio-temporal pattern and variation characteristics of population distribution at county level in the Pearl River Delta. Tropical Geography, 2013, 33(2): 156-163.] The Pearl River Delta (PRD) is one of the regions with fastest economic development in China. The process of population concentration and decentralization in this region has been being focused by researchers. In this study, based on the population census data in the PRD from 1982 to 2010, we analyzed the growth and reduction of population, the concentration level of population and stability of population so as to investigate the change of spatial pattern of the population' concentration and decentralization. The results showed that: (1) The growth rate of population from 1982 to 2010 in the PRD was 215.61%, which far exceeded the growth rate averaged over the whole country; (2) The population increased more significantly in the middle and east parts of PRD; (3) The population agglomerating level in the PRD was greater than that in the whole country. The city of Shenzhen, Guangzhou and Dongguan had become the cluster centers in PRD; (4) More and more floating population moved into PRD, especially in the middle and east parts, from 1982 to 2010. The increasing population and agglomerating level of population in the study region were mainly due to this influx. However, the rate of the influx in PRD slowed down in the past decade.

[11]
孙铁山, 李国平, 卢明华. 京津冀都市圈人口集聚与扩散及其影响因素: 基于区域密度函数的实证研究. 地理学报, 2009, 64(8): 956-966.

[Sun Tieshan, Li Guoping, Lu Minghua.Concentration and decentralization of population in the Beijing-Tianjin-Hebei metropolitan region and its determinants: A regional density function approach. Acta Geographica Sinica, 2009, 64(8): 956-966.]The distribution of population is of great importance to regional economic studies, which helps reveal the characteristics and the development trends of regional spatial structure. This paper applied the regional density function approach to study the concentration and the decentralization of population in the Beijing-Tianjin-Hebei Metropolitan Region, one of the largest extended metropolitan regions in North China. Besides, the polycentric regional density function is used to analyze the population growth patterns of the study region. Compared with the classic monocentric density function, the polycentric density function is more appropriate for modeling the modern metropolitan regions, like the Beijing-Tianjin-Hebei region, which usually presents a polycentric pattern. The estimation of the polycentric density function shows the concentration of population into the core urban centers during the 1980s, the coexistence of the concentration of population into multi-urban centers and the decentralization of population from the core urban centers during the 1990s. At the same time, it is shown that three different growth patterns for the urban centers have formed at different levels, namely, the dispersion pattern through decentralization, the dispersion pattern through growth and the concentration pattern. Finally, a dynamic varying parameter model is proposed to identify the determinants of the spatial dynamics of the population distribution and growth, which indicates that the concentration and the decentralization of population within urban centers are influenced by the size, the economic structure and the transportation facilities of urban centers and their changes.

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[12]
秦贤宏, 魏也华, 陈雯, 等. 南京都市区人口空间扩张与多中心化. 地理研究, 2013, 32(4): 711-719.20世纪90年代以来,中国进 入了前所未有的快速城市化阶段,大城市人口增长和空间演变剧烈,值得进行深入研究。以南京市为研究对象,先采用地理图形分析方法对都市区人口空间扩张过程 进行了分析,后又采用数学模型方法对都市区人口分布多中心化趋势进行了系统研究。结果显示:在总人口持续快速增长的背景下,南京都市区人口高密度空间已延 伸到近郊区,且远郊区中的区县政府驻地和一些优先开发区域的人口密度也已很高;城市人口空间分布已出现多中心化趋势,除了老城区北部的山西路已发育成除市 中心新街口之外的人口次中心以外,郊区人口集聚最强的热点——河西新城区的万达广场也有望发育成另一个人口次中心。

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[Qin Xianhong, Wei Yehua, Chen Wen, et al.Population expansion and polycentric development of Nanjing city in a period of hyper-growth. Geographical Research, 2013, 32(4): 711-719.]

[13]
李志刚, 吴缚龙, 肖扬. 基于全国第六次人口普查数据的广州新移民居住分异研究. 地理研究, 2014, 33(11): 2056-2068.

[Li Zhigang, Wu Fulong, XiaoYang. Residential segregation of new migrants in Guangzhou, China: A study of the 6th census. Geographical Research, 2014, 33(11): 2056-2068.]

[14]
姚华松, 许学强, 薛德升. 广州流动人口空间分布变化特征及原因分析. 经济地理, 2010, 30(1): 40-46. 流动人口的大量出现是当代中国城市化和现代化进程中的重要事件，对于中国流动人口的研究引起了学界的高度关注。以中国特大城市——广州为例，首先系统分析了广州流动人口近30年空间分布变化规律，发现流动人口总体分布具有近郊区指向、文化程度较高者多集聚于发展新区、产业转型与转移对流动人口职业分布有重要影响、以户籍地为基础的集聚区经济形态已经出现。此外，全球化背景下广州出现了跨国移民聚居区的基本雏形。其次，对其原因进行归纳，包括城市发展格局的演变及产业地域转移、户籍和劳动力二元市场等制度因素及人力和社会资本的拥有状况。

[Yao Huasong, Xu Xueqiang, Xue Desheng.On spatial distribution and evolutive laws of floating population in Guangzhou. Economic Geography, 2010, 30(1): 40-46.]Floating population plays a vital part in China' current urbanization and modernization.Studies on floating population have been a hot point for scholars from every discipline.This paper,taking Guangzhou as an example,first,analyzed the characteristics of spatial distribution of floating population in Guangzhou during 1978-2007,found that general spatial distribution of floating population was suburb-orientated,population with higher educational level tended to choose new developmental area as their destination,occupation structure was strongly influenced by industrial transition and regional shifting.What is more,Guangzhou witnessed enclave economy by native places of floating population and foreign enclaves under globalization.Then,three evolutive laws of spatial distribution of floating population were come up with,which included urban development pattern and industrial spatial transferring,registered permanent system and dual labor market system,human and social capital of floating population themselves.

[15]
段学军, 田方. 基于人居环境适宜性的市域人口增长调控分区研究: 以南京市为例. 地理科学, 2010, 30(1): 45-52.

[Duan Xuejun, Tian Fang.Regionalization of urban population growth control based on suitability level for human settlements: A case study of Nanjing city. Scientia Geographica Sinica, 2010, 30(1): 45-52.]

[16]
封志明, 唐焰, 杨艳昭, 等. 中国地形起伏度及其与人口分布的相关性. 地理学报, 2007, 62(10): 1073-1082.基于人居环境自然评价的需要, 运用GIS技术,采用窗口分析等方法,提取了基于栅格尺度(10km×10km)的中国地形起伏度,并从比例结构、空间分布和高度特征3个方面系统分析了 中国地形起伏度的分布规律及其与人口分布的相关性。研究表明:中国的地形起伏度以低值为主,63%的区域低于1(相对高差≤500m);空间分布呈现西高 东低、南高北低的格局;随着经度和纬度增高,地形起伏度呈逐渐下降趋势,28oN、35oN、42oN纬线和85oE、102oE、115oE经线上的地 形起伏度符合中国三大阶梯的地貌特征;随着海拔高度增加,地形起伏度呈现逐渐升高趋势。实证分析表明:中国的地形起伏度与人口密度有较好的对数拟合关系, 拟合度高达0.91;全国85%以上的人口居住在地形起伏度小于1的地区,在地形起伏度大于3的地区居住的人口总数只占全国0.57%。中国地形起伏度与 人口

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[Feng Zhiming, Tang Yan, Yang Yanzhao, et al.The relief degree of land surface in China and its correlation with population distribution. Acta Geographica Sinica, 2007, 62(10): 1073-1082.]The relief degree of land surface (RDLS) is an important factor in describing the landform macroscopically. Under the new proposed concept, based on the macro-scale digital elevation model data, by using ARC/INFO software, the RDLS of 10km×10km grid size is extracted and mapped in China. Then this paper systemically depicts the distribution rules of RDLS in China and its correlation with population distribution by analysing the ratio structure, spatial distribution and latitudinal characteristics of the RDLS. The distribution rule is elaborately expatiated in three separate ways: the ratio structure, the accumulative frequency, and the change along with the longitude and latitude, which clearly reflects the regional topographic framework of China. The result shows that the majority of the RDLS is low in China, for more than 63% of the area in China with the RDLS lower than 1 (relative altitude ≤ 500 m). As for the spatial distribution, in general, the RDLS of the west is higher than that of the east and so is the south than the north. Specifically, the Hengduan Mountains and the Tianshan Mountains regions have the highest RDLS, while the Northeast China Plain, the North China Plain and the Tarim Basin have the lowest ones. The RDLS of 28oN, 35ooN and 42oN as well as of 85oE, 102oE and 115oE accords well with the three topographic steps in China. The RDLS of China decreases with the increase of longitude and the change clearly illustrates the landforms characteristics that most of the mountains are located in the west and most plains in the east of China. The RDLS of China decreases with the increase of latitude as well and the trend shows that there are more mountains and hills in South China and more plains and plateaus in North China. In the vertical direction, the ratio of high RDLS increases with the increase of altitude. Finally, this paper analyses the correlation between the RDLS and population distribution in China and the result shows that the RDLS is an important factor affecting the distribution of population and most people in China live in low RDLS areas. To be more specifically, where the RDLS is zero, the population amounts for 0.83% of the total; where the RDLS is less than 1 (relative altitude ≤ 500 m), the population reaches 20.83%; where the RDLS is less than 2, the population amounts for 97.58% of the total; and where the RDLS is bigger than 3, the population only amounts for 0.57%. That is to say, more than 85% of the population in China lives in areas where the RDLS is less than 1 and less than 1% of the population lives in areas where the RDLS is bigger than 3. The correlations between the RDLS and population distribution of eight regions in China are different. The correlation is obvious in north-east, north, central and south China, while it is nearly nonexistent in Inner Mongolia and the Qinghai-Tibet region.

[17]
刘祥, 王茂军, 蔡嘉斌, 等. 2000-2010年北京都市区外来人口的空间结构研究. 城市规划, 2013, 20(10): 86-95.

[Liu Xiang, Wang Maojun, Cai Jiabin, et al.An analysis on the spatial structure of non-native permanent population of Beijing metropolitan area in 2000-2010. Urban Panning, 2013, 20(10): 86-95.]

[18]
袁媛, 许学强, 薛德升. 广州市1990-2000年外来人口空间分布、演变和影响因素. 经济地理, 2007, 27(2): 250-255.

[Yuan Yuan, Xu Xueqiang, Xue Desheng.Spatial distribution, evolution and driving force of non-registered population of Guangzhou metropolitan area in 1990-2000. Economic Geography, 2007, 27(2): 250-255.]The paper studied the spatial distribution, spatial evolution and driving force of Non-registered population in Guangzhou metropolitan area from 1990 to 2000, based on the data of fourth and fifth census. Firstly, the author analyzed the spatial transformation of Non-registered population in three circles of the metropolitan area. The absolute differentiation of spatial distribution among ten districts and two counties decreased, while the relative differentiation increased.The amount of Non-registered population increased in three circles, and they concentrated from the first and second circles to the third circles. Secondly, five different spatial areas were found and defined based on the the change of the location quotient of Non-registered population on the level of sub-districts and towns in the past ten years.Thirdly, on one hand, the paper found that there exited more evident correlation between economic factors and concentrated rations of Non-registered population in 2000 than that in 1990. The influential factors were industries, employment and investment of counties and districts. On the other hand, there exited coupling between the location quotient of Non-registered population and the spatial distribution of urban village, which was the main kind of low-rent apartment for Non-registered population in Pearl River Belt. Behind the economic and social factors, the most powerful driving force was the institutional factors. The Non-registered population have to concentrate in urban villages because they work in the lowest level of labour force markt with low-income and there are lack of housing provision and other social benefits. In a short, the mechanism of spatial character of Non-registered population were caused by the the institutional inherit of planned economy and the new changes of transitional era.

[19]
刘盛和, 邓羽, 胡章. 中国流动人口地域类型的划分方法及空间分布特征. 地理学报, 2010, 65(10): 1187-1197.随着中国流动人口规模快速增长和影响日趋深远,各级政府在制订经济社会发展战略、区域与城市规划等各类重大决策时,亟需准确地认识和把握中国流动人口的空间分布特征及不同地域类型。本文在综合比较现有流动人口地域类型划分方法优缺点的基础上,提出了综合考虑净迁移率和总迁移率的复合型指标及其修正方法,并根据中国第五次人口普查分区县的流动人口数据,运用以上多种划分方法实证研制出中国流动人口地域类型的多种划分方案,并进行了比较分析。结果表明：①综合考虑净迁移率和总迁移率的复合指标法,可以同时测度区域流动人口的方向性与活跃度,兼具以上两种单一性指标法的特色和优势,特别是能清晰地分辨出区域流入人口与流出人口的规模均比较大的平衡型活跃区这种独特类型,具有显著的优势。②进一步考虑份额指标的修正型复合指标法,能有效地消除因区域人口总量过小或过大而导致流动人口活跃度被高估或低估的偏差,划分结果更加符合实际。③中国流动人口地域类型的空间分布格局与其自然环境、人口密度及经济社会发展水平的区域差异关系密切。中国各类流动人口活跃区主要分布在位处第三阶梯和大于800 mm等降雨线的东部季风区,其人口密度及经济社会发展水平相对较高。

[Liu Shenghe, Deng Yu, Hu Zhang.Research on classification methods and spatial patterns of the regional types of China's floating population. Acta Geographica Sinica, 2010, 65(10): 1187-1197.] With the rapid increase of the number and influence of floating population in China,it is urgent to understand the regional types of China's floating population and their spatial characteristics.After reviewing the current methods for identifying regional types of floating population,this paper puts forward a new composite-index method and its further modification method consisting of two indexes simultaneously: the net migration rate and gross migration rate.Further,those methods are empirically tested by using China's 2000 Census data at county level.The results show:(1) The composite-indexes method is much better than the traditional single-index method because it can measure the migration direction and scale of floating simultaneously and in particular it can identify the unique regional types of floating population with large-scale immigration and emigration.(2) The modified composite-indexes method,by using the share of a region's certain type of floating population to the total in China as weight,can effectively correct the over-or under-estimated error due to the rather large or small total population of a region.(3) The spatial patterns of different regional types of China's floating population are closely related to regional differentiation of their natural environment,population density and socio-economic development level.The three active regional types of floating population are mainly located in the eastern China with lower elevation,more than 800 mm precipitation,rather than in the region with higher population density and economic development level.

[20]
张苏北, 朱宇, 晋秀龙, 等. 安徽省内人口迁移的空间特征及其影响因素. 经济地理, 2013, 33(5): 24-30.引入迁移选择指数概念,利用安徽省人口、社会和经济发展数据,计算了2007-2010年安徽省各地级市的人口综合迁入指数、人口综合迁出指数、人口净迁 移指数和各地级市间的人口迁移选择指数,并建立了关于人口净迁移指数的多元线性回归模型；着重从迁出地、迁入地和迁移流的视角,揭示了安徽省省内人口迁移 的空间规律及其影响因子.研究表明:“环省会迁出圈”、“皖南迁出区”是主要的迁出地；“省会迁入区”、“马芜铜迁入区”和“两淮迁入区”是主要的迁入 地.省会合肥和“马芜铜”沿江城市带是人口迁移强度最大的区域:在空间上,它们呈现出“点—轴”形态；省会合肥的辐射范围覆盖全省,而“马芜铜”沿江城市 带是安徽南部地区最主要的人口迁入地；各主要迁入地之间的人口对流较弱.劳动力在三次产业间的分布、城镇从业人员比重,以及城市公园数量是安徽省省内人口 迁移的重要“推—拉”因子.

[Zhang Subei, Zhu Yu, Jin Xiulong, et al.The spatial patterns of intra-provincial migration and their determinants in Anhui province. Economic Geography, 2013, 33(5): 24-30.]Introducing the concept of migration preference index and using population and socioeconomic statistics,this paper first calculates the comprehensive in-migration indexes,the comprehensive out-migration indexes,the net migration indexes,and the migration preference indexes for all prefecture-level municipalities of Anhui Province in the period of 2007 to 2010,and then conducts a multiple linear regression to model the net migration indexes,to reveal the spatial patterns and their determinants of intra-provincial migration in Anhui Province,from the perspectives of source and destination areas and migration flows.The results show that"the out-migration ring area surrounding the capital"and "the Southern Anhui out-migration region"are the main source areas,and that"the capital city in-migration region","the Maanshan-Wuhu-Tongling in-migration region",and"the Huainan-Huaibei in-migration region"are the main destination areas.The capital city Hefei and"the Maanshan-Wuhu-Tongling city strip"along the Yangtze River are the areas with the highest migration intensity.Their spatial configuration is in the form of"point-axis",with capital city Hefei serving as a main destination area for migrants from the whole province,and"the Maanshan-Wuhu-Tongling city strip"along the Yangtze River as a main destination area for migrants from the southern part of the province.The migration intensities between the main destination areas are relatively weak.The results of the regression analysis suggest that the distribution of the labor force among the first,secondary and tertiary sectors,the proportion of the labor force in employment in urban areas,and the number of urban parks,are the main determinants of intra-provincial migration within Anhui Province.

[21]
田明. 中国东部地区流动人口城市间横向迁移规律. 地理研究, 2013, 32(8): 1486-1496. 基于中国东部地区6个城市流动人口问卷调查,并在对已有人口迁移规律研究进行梳理的基础上,通过比较流动人口每一次迁移前一城市和后一城市的差异以及整个迁移过程中迁移速度、迁移距离、迁移城市规模、城市经济发展水平、区域路径等方面的变化趋势,分析流动人口进入城市后在城市间横向迁移的规律和特点.研究发现:东部地区流动人口城市间横向迁移不仅速度快,城市平均居留时间短,而且在多次迁移过程中迁移流向、迁移的空间轨迹方面呈现出更为复杂的特点:随着迁移次数的增加,迁移距离增加,遵循由近及远的同时回流现象明显；随着迁移次数的增加,由收入较高城市流向收入较低城市的比例以及流向中等城市的比例显著提高,不存在由大到小的递补特征；在相邻城市或相同经济区范围内多次往返迁移现象明显.

[Tian Ming.The migration patterns of floating population across cities in eastern China. Geographical Research, 2013, 32(8): 1486-1496.]Based on a survey in six cities of eastern China and theory of migration,this article compares current situation with the patterns of Chinese migration in the past decades,and explores certain important characteristics and law of the migration process of floating population,such as migration frequency,distance,urban scale,urban development level and spatial path between origin and destination cities in each migration and in an entire migration process.Results show that floating population in eastern China migrates frequently across cities,and stays for a short period averagely after leaving their rural homes.Its movement patterns are complex in terms of migration direction and spatial trajectory,which indicates more floating population moved transprovincially to a longer distance with more times of migration,and as the same time more floating population returns to cities in hometown provinces.More and more migrants tend to move to middle-sized and low-income cities along with movements,though flows to big-sized cities,and high-income cities are still the mainstream.These findings show that floating population becomes more rational in choosing their destination cities.Cities in home provinces,and other cities in current host provinces become the transit places to destination cities,and floating population is inclined to move back and forward between several cities in a certain economic region.

[22]
王珏, 陈雯, 袁丰. 基于社会网络分析的长三角地区人口迁移及演化. 地理研究, 2014, 33(2): 385-400.在当今全球化与地方化、区域化的背景下,物质和能量在各节点间的高速流动促进了城市网络的形成并成为一种新的区域组织模式和空间结构,尤其是对区域一体化高度发达的区域产生了深刻影响。以长江三角洲地区为例,从人口迁移的网络空间入手,从网络密度、中心势等角度对1982-2010年长三角地区人口网络的演变进行研究。结果表明:整体上人口迁移网络日趋成熟,但空间分布不均衡;人口迁移主要流向上海、杭州、南京、宁波和苏锡常等核心城市,同时这些城市的人口外迁现象逐渐显现;以无锡、苏州、杭州之间人口迁移联系为主体的省际间人口流动行为增多,空间上具有等级扩散的特征;不同空间尺度的网络结构相互嵌套,在地方尺度下形成了江苏以邻域渗透为主和浙江的等级辐合两种网络结构。最后从就业机会、收入水平、产业结构、迁移成本等方面分析了人口迁移网络的演化历经均质离散—单核心集聚—多核心等级网络—链式空间网络四个阶段的成因。

DOI

[Wang Jue, Chen Wen, Yuan Feng.Human mobility and evolution based on social network: An empirical analysis of Yangtze River Delta. Geographical Research, 2014, 33(2): 385-400.]

[23]
马忠东, 王建平. 区域竞争下流动人口的规模及分布. 人口研究, 2010, 34(3): 3-16. 本文重新定义了流动人口概念,并分析了流动人口的实际规模及分布。广义流动人口包括离开户口 所在地（乡、镇、街道）＂半年以上＂的长期流入者和＂半年以下＂经济型短期流入者。基于2005年全国1%人口抽样调查的现有人口数据,我们发现经济型短 期流入规模达1676.5万,占重要流入省市总人口比重的2%以上。2005年,全国流动人口总数在1.5亿左右,其中跨省流动人口大约6844万。省际 流动的流入地及流出地都比较集中：近3/4来自中南及西南9个欠发达省份,3/4流向经济发达区域广东（34.2%）,长三角（28.5%）和环渤海地区 （13%）。对珠、长三角的选择由距离决定：邻近省选择高度集中,等距或长距时则分散到两个区域。以上分布显示沿海发达地区对中西部人口的强烈吸引力,也 反映出区域发展多极化后发达区域间劳动力需求竞争加剧。

[Ma Zhongdong, Wang Jianping.Regional competition and the distribution of floating population in China. Population Research, 2010, 34(3): 3-16.]Based on the 1% Population Survey of China in 2005,we examine the size and distribution of floating population in the context of regional competition.We found that the size of short-term labor migrants is not negligible,amounted to nearly 17 million,which accounted for 2% to 3% of the total population in the coastal regions.Totally 150 million migrants left their place of registration,mainly inter-provincial in the coastal regions and largely intra-provincial in the interior.Among seventy million interprovincial ones,three-fourth were originated from nine sending provinces in the interior and about three-fourth headed to Guangdong(34.2%),Yangzi-River-Delta Region(28.5%)and the Regions surrounding the Bohai Bay(13%).The destination choice between Guangdong and YRD region is mainly affected by distances to the two regions,being highly concentrated for a neighboring province but spread for distant ones.The above results reflect a strong magnet force of the growth poles on people in the interior as well as increasing regional competition for labor,which helps to explain the labor shortage in despite of massive labor migrations.

[24]
王国霞, 秦志琴, 程丽琳. 20世纪末中国迁移人口空间分布格局: 基于城市的视角. 地理科学, 2012, 32(3): 273-281.

[Wang Guoxia, Qin Zhiqin, Cheng Lilin.Spatial distribution of population migration in China in the 1990s. Scientia Geographica Sinica, 2012, 32(3): 273-281.]China is being at the stage of rapid urbanization. Based on the fifth census data, this paper analyzes the migration structure of China in different administrative and scale cities in the 1990s. The result shows that it is the prefecture cities that plays important role in the Chinese population migration in the 1990s, in which the big cities, especially the mega-cities, take a more significant position. It is also found that there are differ-ences in the migration scale between county-level cities. The average migration scale of county-level city in East China is more than in West and Middle China. For the prefecture and above level cities is more important in the process of China’s urbanization at present and in the future, this article further examines the patial distri-bution pattern of inner-provincial and inter-provincial migration. It is showed that there are three ladder-like levels for prefecture cities in the spatial distribution pattern of inter-provincial migration: the first level in-cludes the Zhujiang River Delta agglomeration, Changjiang River Delta city group, west bank cities, Bei-jing-Tianjin-Henan city agglomeration, the core cities of Liaodong Peninsula and a few of provincial capitals in middle-west area. The second level includes most of provincial capitals in middle-west area: Shandong Pen-insula urban agglomeration and other eastern cities which are close to Beijing-Tianjin-Henan area, Changjiang River and Zhujiang River. The third level includes other provincial cities of middle west area and other cities which are far away from the core cities of three metropolises in the eastern area. Besides, the circle structure is obvious in the southeast coastal area, while the peak structure is more evident in the mid-west area. With re-gard to the spatial distribution pattern of inner-provincial migration, it shows that there are great similarities among prefecture-level in population spatial distribution pattern. The first gathering cities are each provincial capital cities. The ESDA technology is used to study the spatial distribution features of migration in cities in China. The result shows strong concentration for spatial distribution. The Zhujiang River Delta agglomeration, Changjiang River Delta city group are the main gather cities in both of inner and inter provincial migration. Furthermore, the migration gathering city range in Zhujiang River Delta area is larger than the Changjiang Riv-er Delta. On the contrary, the cities with small migration scales are located in agricultural provinces such as An-hui, Henan, and Sichuan, etc.

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