湖北农业科学 ›› 2022, Vol. 61 ›› Issue (16): 193-198.doi: 10.14088/j.cnki.issn0439-8114.2022.16.037

• 信息工程 • 上一篇    下一篇

基于大数据融合的少数民族山区人口空间化研究——以彭水苗族土家族自治县为例

焦欢1, 肖禾1, 李辉2, 高丽3   

  1. 1.重庆市地理信息和遥感应用中心,重庆 401147;
    2.重庆财经学院,重庆 401320;
    3.重庆工程职业技术学院,重庆 402260
  • 收稿日期:2021-10-28 出版日期:2022-08-25 发布日期:2022-09-14
  • 通讯作者: 肖 禾(1985-),男,重庆人,正高级工程师,博士,主要研究方向为生态修复与可持续发展研究。
  • 作者简介:焦 欢(1991-),男,重庆长寿人,工程师,硕士,主要研究方向为遥感、地理信息和自然资源调查监测,(电话)15023306456(电子信箱)70069026@qq.com。
  • 基金资助:
    国家自然科学基金资助项目(42001269); 重庆市教委科学技术研究项目(KJQN202002101)

Research on population spatialization in ethnic minority mountainous areas based on big data fusion:Taking Pengshui Miao and Tujia Autonomous County as an example

JIAO Huan1, XIAO He1, LI Hui2, GAO Li3   

  1. 1. Chongqing Geographic Information and Remote Sensing Application Center, Chongqing 401147, China;
    2. Chongqing Finance and Economics College, Chongqing 401320, China;
    3. Chongqing Vocational Institute of Engineering, Chongqing 402260, China
  • Received:2021-10-28 Online:2022-08-25 Published:2022-09-14

摘要: 针对人口统计数据无法精细直观反映人口真实的空间分布状况的问题,以彭水县2018年人口数据为基础,运用GIS空间分析方法,分析了研究区各乡镇平均人口密度与海拨高度、土地利用、主要道路和河流水系等因素的相关关系,并在乡镇尺度上对其以30 m×30 m评价栅格单元空间化的结果进行精度验证。结果表明,研究区人口分布不均匀,人口高值区主要集中在县城;农村居民点沿主要公路和河流水系居住,且随着海拨的升高人口分布密度越小;从土地利用类型对人口分布的影响来看,耕地和建设用地和人口分布的相关性最大,对2018年彭水县人口数据的空间化,空间误差模型的回归拟合效果优于空间滞后模型;人口数据空间化结果精度比较高,在空间上能精细展现2018年彭水县的人口分布状况,通过大数据融合方法模拟的少数民族山区县域人口密度图与实际的人口分布基本相吻合。

关键词: 空间化, 人口, GIS, 山区, 少数民族

Abstract: In view of the problem that the demographic data can not accurately and intuitively reflect the real spatial distribution of population, based on the population statistics data of Pengshui County in 2018, GIS spatial analysis methods were used to analyze the correlation to the average population density with sea level, land use, main roads and river water system of each township in the study area. At the township scale, the accuracy of the grid element spatial evaluation results of 30 m×30 m was verified. The results showed that the population distribution in the study area was uneven, and the high value areas were mainly concentrated in the county; the rural settlements lived along the main roads and river systems, and the population distribution density was smaller with the increase of the sea level; from the perspective of the impact of land use types on the population distribution, the correlation of cultivated land and construction land with population distribution was the largest, and for the spatial population data of Pengshui County in 2018, the spatial error model had better regression fitting effect than the spatial lag model; the spatial results of population data had higher precision, which could accurately show the population distribution of Pengshui County in 2018. The population density map simulated by big data fusion method was basically consistent with the actual population distribution.

Key words: spatiality, population, GIS, mountain area, minority nationality

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