地理科学进展 ›› 2017, Vol. 36 ›› Issue (7): 832-842.

• 研究论文 • 上一篇    下一篇

东北地区城市宜居性评价及影响因素分析——基于2007-2014年面板数据的实证研究

贾占华(), 谷国锋*()   

  1. 东北师范大学地理科学学院,长春 130024
  • 出版日期:2017-07-31 发布日期:2017-07-31
  • 通讯作者: 谷国锋 E-mail:jiazh42@126.com;gugf@nenu.edu.cn
  • 作者简介:

    作者简介:贾占华(1994-),女,山西应县人,博士研究生,研究方向为区域经济增长与可持续发展,E-mail: jiazh42@126.com

    *指年末固定电话、移动电话使用户数和互联网宽带接入户数之和与当年人口之比。

  • 基金资助:
    国家社会科学基金项目(16BJL032)

Urban livability and influencing factors in Northeast China: An empirical study based on panel data, 2007-2014

Zhanhua JIA(), Guofeng GU*()   

  1. School of Geography Science,Northeast Normal University, Changchun 130024, China
  • Online:2017-07-31 Published:2017-07-31
  • Contact: Guofeng GU E-mail:jiazh42@126.com;gugf@nenu.edu.cn
  • Supported by:
    National Social Science Foundation of China, No.16BJL032

摘要:

新型城镇化背景下,城市宜居性成为当前学术界研究的热点之一。本文基于资源、环境、经济、社会、生活、安全6个方面构建了宜居城市评价指标体系,运用熵值法、ArcGIS空间分析法和面板数据模型分析法,对2007-2014年东北地区37个城市的宜居性及影响因素进行探究。结果表明:①城市宜居水平整体偏低,提高速度较慢,但城市间的差异在缩小。②城市宜居水平在空间上形成以沈阳、大连为核心的“双核”分布模式,以及以长春、哈尔滨和大庆为核心“扇叶”分布格局。③各城市间宜居水平存在较弱的空间相关性,但这种相关性逐年增强。④各单项指标的地域分异与综合水平的地域分异存在差异,不同城市在不同指标下有其优势与不足。⑤在研究社会经济的影响时,通过建立面板数据模型,发现居民储蓄存款余额、市政设施建设投资、人均住宅房地产开发投资、社区服务设施、人口密度与城市宜居性呈正相关,而SO2排放量则呈负相关。

关键词: 宜居性, 时空特征, 影响因素, 面板数据模型, 东北地区

Abstract:

Under the background of new urbanization, urban livability has become a focus of academic research. This study established an evaluation index of urban livability from six aspects, including resources, environment, economy, society, living condition, and safety. Based on entropy analysis method and ArcGIS spatial analysis method, this study explored the spatial-temporal characteristics of livability levels of 37 cities in Northeast China from 2007 to 2014. The results show that: (1) In 2007-2014, overall urban livability level was relatively low and the speed of improvement was relatively small, but the differences between cities were narrowing. (2) The spatial pattern of urban livability presents a "dual core" distribution with two high value centers at Shenyang and Dalian, as well as a "fan blade" shaped distribution centered around Changchun, Harbin, and Daqing. (3) There was a weak spatial correlation in the livability of cities, but the correlation is increasing year by year. (4) There were differences in the overall urban livability and the individual index values. Cities have different advantages and disadvantages in different indicators. (5) When discussing the impact of socioeconomic factors on urban livability, this study established a panel data model and found that the balance of household savings, investment of urban facilities, real estate development, community-level service facilities, and population density have positive effect on livability, while the impact of SO2 emissions was negative.

Key words: livability, spatial-temporal characteristics, influencing factors, panel data model, Northeast China