Study on the distribution pattern and influencing factors of shrinking cities in Northeast China based on the random forest model

Guanghua Yan, Xi Chen, Yun Zhang
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Abstract

Based on the population change data of 2005-2009, 2010-2014, 2015-2019 and 2005-2019, the shrinking cities in Northeast China are determined to analyze their spatial distribution pattern. And the influencing factors and effects of Shrinking Cities in Northeast China are explored by using multiple linear regression method and random forest regression method. The results show that: 1) In space, the shrinking cities in Northeast China are mainly distributed in the “land edge” areas represented by Changbai Mountain, Sanjiang Plain, Xiaoxing’an Mountain and Daxing’an Mountain. In terms of time, the contraction center shows an obvious trend of moving northward, while the opposite expansion center shows a trend of moving southward, and the Shrinking Cities gather further; 2) in the study of influencing factors, the results of multiple linear regression and random forest regression show that socio-economic factors play a major role in the formation of shrinking cities; 3) the precision of random forest regression is higher than that of multiple linear regression. The results show that per capita GDP has the greatest impact on the contraction intensity, followed by the unemployment rate, science and education expenses and the average wage of on-the-job workers. Among the four influencing factors, only the unemployment rate promotes the contraction, and the other three influencing factors inhibit the formation of shrinking cities to various degrees.
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基于随机森林模型的东北萎缩城市分布格局及影响因素研究
基于2005-2009年、2010-2014年、2015-2019年和2005-2019年的人口变化数据,确定东北萎缩城市的空间分布格局。运用多元线性回归和随机森林回归方法,探讨了东北地区城市收缩的影响因素和效应。结果表明:①空间上,东北萎缩城市主要分布在以长白山、三江平原、小兴安岭和大兴安岭为代表的“陆缘”地区;从时间上看,收缩中心呈明显的北移趋势,相反的扩张中心呈南移趋势,收缩城市进一步集聚;2)在影响因素研究中,多元线性回归和随机森林回归结果表明,社会经济因素在城市萎缩形成中起主要作用;3)随机森林回归的精度高于多元线性回归。结果表明,人均GDP对收缩强度的影响最大,其次是失业率、科教费用和在岗职工平均工资。在四个影响因素中,只有失业率对收缩有促进作用,其他三个影响因素对收缩城市的形成都有不同程度的抑制作用。
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