PROGRESS IN GEOGRAPHY ›› 2017, Vol. 36 ›› Issue (7): 832-842.

• Orginal Article • Previous Articles     Next Articles

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;
  • Supported by:
    National Social Science Foundation of China, No.16BJL032


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