地理学报 ›› 2015, Vol. 70 ›› Issue (8): 1229-1242.doi: 10.11821/dlxb201508004

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基于乡镇尺度的中国25省区人口分布特征及影响因素

柏中强1,2(), 王卷乐1,3(), 杨雅萍1,3, 孙九林1,3   

  1. 1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
    2. 中国科学院大学,北京 100049
    3. 江苏省地理信息资源开发与利用协同创新中心,南京 210023
  • 收稿日期:2014-08-17 修回日期:2015-05-04 出版日期:2015-08-20 发布日期:2015-09-25
  • 作者简介:

    作者简介:柏中强, 博士, 主要从事区域人口格网化时空模拟。E-mail: baizq@lreis.ac.cn

  • 基金资助:
    国家科技基础性工作专项重点项目(2011FY110400, 2013FY114600);中国科学院信息化专项项目(XXH12504-1-01)

Characterizing spatial patterns of population distribution at township level across the 25 provinces in China

Zhongqiang BAI1,2(), Juanle WANG1,3(), Yaping YANG1,3, Jiulin SUN1,3   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
    3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
  • Received:2014-08-17 Revised:2015-05-04 Online:2015-08-20 Published:2015-09-25
  • Supported by:
    Science & Technology Basic Research Program of China, No.2011FY110400, No.2013FY114600;Specific Information Infrastructure Program of the Chinese Academy of Sciences, No.XXH12504-1-01

摘要:

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。

关键词: 人口分布, 乡镇尺度, 格局特征, 影响因素, 中国

Abstract:

Spatial pattern of population distribution has a typical character of scale dependency. Fine-scale estimation of the population distribution has been a huge challenge in the field of population geography. In China, township is the finest administrative unit in official population census data. Thus, population density data at township level can be used to describe and characterize the population spatial pattern and changes elaborately, and support optimized layout plan of Chinese population, and government policy decision making. Township boundaries across 25 provinces in China had been collected in this study. The 5th national population census data was spatially joined to the boundary layer for population density calculation. Methods of Lorenz curve, geo-spatial analysis, and latitude/longitude transect had been applied to reveal the agglomeration degree, spatial patterns of population distribution with latitude and longitude. Based on the correlation and stepwise regression analysis, four variables, including relief degree of land surface (RDLS), water system density (WSD), road system density (RSD) and nighttime light index (NTL), were introduced to check the variety of population distribution in each province. The results showed that: (1) the variety of population distribution can be distinguished clearly by the mean population density on township scale than that of county level. (2) The overall population distribution can be characterized as dense in the southeast and sparse in the northwest, while lower population density occurs in some part of southeastern China, and vice versa. (3) The population density at township level along six designed longitude and latitude transects varies greatly. The possible impact factors include the three-level landscape features, local topography, regional economy, and the proximity to coastline, transportation hub, and hydrological systems. The correlation coefficient at provincial level, between the RDLS, WSD, RSD, NTL, and the population density has been identified as 0.56, 0.28, 0.61, and 0.69, respectively. At township level, topography and economy exert more impacts on population distribution in Liaoning, Jilin, Beijing, Tianjin, Shanghai, Hebei, Henan, Shaanxi, Shanxi, Shandong, Anhui, Jiangsu, Hunan, Hubei, Jiangxi, Zhejiang, Fujian, Guangdong, and Hainan. In addition to the four factors mentioned above, it is necessary to introduce more natural or social factors to explore the population distribution pattern in Tibet, Qinghai, Inner Mongolia, Yunnan, and Guizhou. This study expanded the research scale and dimension of the research in population geography research in China. The resulted population density dataset in 2000 is expected to enrich the baseline data resources for population geography development in China and the world.

Key words: population distribution, township scale, pattern, influencing factor, China